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PLOS One logoLink to PLOS One
. 2025 Jun 18;20(6):e0324640. doi: 10.1371/journal.pone.0324640

Diagnoses and critical care outcomes in a rural Tanzanian high dependency unit: A prospective cohort study

Andrew Katende 1,2,, Julie Rossier 3,4,, Chipegwa Mlula 1,2, Christamonica Chitimbwa 1,2, Martin E Mtula 1,2, Elibariki S Mafole 1,2, Lulu Wilson 1,2, Samuel S Mutasingwa 1,2, Evance Mahundi 1,2, Mohamed K Kipalaunga 1,2, Victor Myovela 1,2, Caspar Mbawala 1,2, Fanuel Faustine 1,2, Geofrey Mbunda 1,2, Winfrid Gingo 5, Faraja Kitila 6, Ipyana Mwasongwe 6, Claudia Bucher 4,6,7, Daniel H Paris 4,7, Thomas Zoller 8, James Okuma 4,7, Maja Weisser 1,4,7,9, Martin Rohacek 1,2,4,6,7,*
Editor: Abraham Aregay Desta10
PMCID: PMC12176112  PMID: 40531899

Abstract

Background

Data on rural sub-Saharan African high-dependency units (HDU) are lacking. We describe patient’s characteristics, diagnoses, and outcomes of patients admitted to a Tanzanian HDU, and identified factors associated with in-hospital mortality.

Methods

This prospective single-center cohort study was conducted in the HDU of a Tanzanian rural referral hospital. All patients admitted to the HDU were eligible. Descriptive analyses, and univariate and multivariate modeling to identify predictors of in-hospital mortality were done. Kaplan-Meier survival curves were employed to estimate mortality rates over time. The area under the receiver operating characteristic curve was used to assess the predictive accuracy of early warning scores.

Results

From April 4th 2023 to March 29th 2024, 491 patients were included and followed-up until hospital discharge. Median age was 46 years (IQR 29−65); 259 (53%) were females. Most common diagnoses were sepsis (N = 96, 20%), arterial hypertension (N = 91, 19%), diabetes mellitus (N = 84, 17%), acute kidney injury (N = 66, 13%), decompensated heart failure (N = 64, 13%), aspiration pneumonia (N = 60, 12%), and stroke (N = 59, 12%). Mortality during HDU- and hospital stay was 30%(N = 146) and 37%(N = 182), respectively. 54% of patients with sepsis, 51% with stroke, 65% with aspiration pneumonia and 27% with heart failure died in the HDU. Predictors of in-hospital mortality were age ≥ 45 years versus 18−44 (adjusted Hazard Ratio (aHR) 1.56, 95% CI 1.07–2.28, p = 0.03), blood pressure <90mmHg (aHR 2.33, 95%CI 1.48–3.81, p < 0.001), Glasgow Coma Scale score ≤8 versus 14−15 (aHR 2.13, 95%CI 1.24–3.64, p = 0.02) and oxygen saturation at room air < 90% (aHR 1.62, 95%CI 1.04–2.51, p = 0.03). The area under the curve predicting in-hospital mortality was 0.69 (95%CI 0.65–0.73) for the NEWS- and UVA scores, 0.66 (95%CI 0.62–0.70) for the MEWS-, and 0.65 (95%CI 0.61–0.69) for the qSOFA score.

Conclusion

Sepsis and non-communicable diseases were the most common diagnoses. Scores predicted in-hospital mortality with a moderate accuracy.

Introduction

Critical care medicine is important to manage seriously ill patients suffering from sepsis, pneumonia, and from non-communicable diseases (NCDs) such as heart failure and stroke [1,2]. Globally, NCDs killed at least 43 million people in 2021, and 73% of these deaths occurred in low- and middle income countries [3]. Critical care services in sub-Saharan Africa increased since the COVID-19 pandemic, but remain limited compared to high-income countries [46]. Intensive care units (ICUs) are few [7,8] and are restricted to major urban centers [4]. In remote areas in sub-Saharan Africa, people often present in advanced stages of diseases, and in critical conditions [912]. This is attributable to delayed diagnosis, geographical barriers that affect timely health seeking behaviors, and lack of live-saving therapies [6,13]. Postoperative care remain the leading cause for admissions in many ICUs in low- and middle income countries, followed by traumatic brain injuries and medical conditions [1416]. The outcomes of patients admitted to ICUs varies by region, with mortality rates up to 52% in urban hospitals [1517]. Replicating standard ICUs in urban centers to rural settings might be challenging due to high costs, inadequate human resources, and lack of expertise [18,19]. Critical care units, tailored to existing health systems in rural areas are warranted. Without these units, critically ill patients admitted to hospital in rural areas are likely to receive inadequate care in general wards [20,21]. High-dependency units (HDU) provide a higher level of care than general wards, but do not reach the level of care provided in ICUs. An HDU can be defined as unit that serves for critically ill patients, but does not provide invasive ventilation [22]. Starting with a HDU as a first step to integrate critical care services into existing hospitals is promising [2]. In sub-Saharan Africa, many hospitals have not implemented these units yet. Data about patient outcomes of ICUs from urban centers are limited, and data on HDUs situated in rural sub-Saharan Africa are lacking. The objective of this study was to describe characteristics, diagnoses, and outcomes of critically ill patients admitted to a recently implemented HDU of a referral hospital in rural Tanzania, and to identify predictors of in-hospital mortality. This is the first study on outcomes of patients admitted to a HDU in rural sub-Saharan Africa.

Materials and methods

Study design and setting

This prospective observational single center cohort study including 491 patients was conducted at the HDU of the St. Francis Regional Referral Hospital (SFRRH), Ifakara, Tanzania.

The SFRRH is a 370-bed regional referral hospital for a rural population of about one million people living in the Kilombero, Malinyi and Ulanga districts in rural Tanzania. It has an emergency department (ED) attending about 90,000 patients per year [23]; 10% of these patients arrive in critical conditions [24].

Implementation of the HDU

In 2021, at the peak of the second COVID-19 wave, an oxygen plant was installed at SFRRH allowing continuous delivery of oxygen to the ED, surgical theaters, neonatal wards, and a dedicated ward was established to operate as the HDU. Key elements of the HDU implementation starting in 2022 were provision of continuous training for nurses and medical doctors [25], installation of locally adapted and reliable medical equipment [25,26] implementation of standardized monitoring to ensure improved patient outcomes [7,27], and the establishment of a multidisciplinary team [28].

Training

Daily bedside teaching, seminars, and exchange programs were implemented to strengthen the knowledge in critical medicine of both the hospital staff and HDU team members, utilizing the expertise of both local and visiting specialists.

Two-week training courses in critical care are held every year since 2022, facilitated by experts from the ICU of the University Hospital Basel, Switzerland, and by experts from the ICU of the Jakaya Kikwete Cardiac Institute, Dar es Salaam, and of the Benjamin Mkapa Hospital, Dodoma, United Republic of Tanzania.  Theoretical instruction was combined with practical trainings. Specialist ICU nurses spent one week in the HDU to provide training in critical nursing during everyday practice. To allow staff to have an external experience and knowledge transfer, 4 members of the HDU were sent to the ICU of the Muhimbili National Hospital for a 4-week attachment. Regular Medical Council of Tanganyika (MCT)- accredited courses in point-of-care ultrasound (POCUS) including lung ultrasound, echocardiography, and vascular ultrasound were conducted. All medical doctors were trained in POCUS and focused echocardiography.

Equipment

Medical equipment such as 8 patient monitors, ultrasound- and electrocardiography (ECG) machines, suction devices, and a defibrillator were installed and staff trained in handing before start of the study. The Abbott iSTAT® point-of-care lab system allows rapid electrolyte and blood gas testing, and the stable supply of consumables such as central venous catheters, and chest and pericardial drains was established. A total of 7 ventilators (Dräger Savina 300) used for non-invasive ventilation, and 4 infusion pumps were implemented during the study period.

Service delivery and organization

The organization at the HDU features a two-shift duty roster for 10 nurses and 4 medical doctors (CM, CC, MEM, ESM,) supervised by two experienced physicians (AK, MR). Clinical rounds occur three times daily, involving nurses, doctors, students, and physicians. An internal HDU staff meeting is held once a month to discuss strategies for enhancing performance of the unit. Patient management is closely coordinated with other specialized units such as obstetrics-gynecology, surgery, urology, internal medicine, infectious diseases specialists, physiotherapy, orthopedic and dialysis unit. Standard operating procedures for patient admissions and discharge to and from the HDU have been developed and disseminated. HDU doctors evaluate all patients who have been referred for admission to the HDU from other hospital departments, and collaborative decisions on the management are done together with specialists and the HDU team. Patients in need of an emergency computed-tomography (CT) scan are directly transferred to the nearby located Good Samaritan Cancer Hospital. Stable patients are discharged to the general ward with summary reports and a verbal handover. The HDU stores emergency and frequently used drugs, allowing patients to receive the medication needed without immediate payment, facilitating timely intervention, with the cost of the drugs being reimbursed subsequently.

Participants

All patients admitted to the HDU during the project period were eligible to participate in the study. Exclusion criterion was the refusal to the use of data for research purposes.

Study procedures and data collection

All patients were assessed upon admission to the HDU, at discharge from the HDU, at discharge from the hospital, and at 30 days post-admission to the HDU using systematic data collection forms. Post-hospital discharge follow-ups were conducted through phone calls. Information on deaths during hospital stay was obtained from the attending physician in the ward or patient files. Data on medical history, physical examination, vital signs, test results (abdominal sonography, POCUS, ECGs, echocardiograms, X-rays, CT scans, laboratory findings) and diagnoses were collected in real-time from patient charts and entered into an electronic locally stored and secured database (Epi Datav4.7.0) by members of the study team. Data were collected by clincians working at the HDU, and responded to queries raised by the data manager and the statistician who cleaned the data. Before the start of the study, all members were trained and instructed how to fill data into the standartized electronic data collection tools. Comprehensive echocardiograms were performed by experienced echocardiographers using a Mindray M7 ultrasound machine equipped with a P 2–5 sector probe. POCUS and focused echocardiograms were done using Mindray M7 or an Echonous Kosmos ultrasound device. ECGs were done using a Schiller Cardiovit MS-2015. Blood gas analyses and serum electrolytes were measured by the iStat point-of-care system (Abbott iSTAT®). Examinations were done upon discretion of the attending physicians. Several early warning scores including Universal Vital Assessment (UVA), National Early Warning Score (NEWS), Modified Early Warning Score (MEWS), and Quick Sequential Organ Failure Assessment (qSOFA) score [2932] were used to assess patient’s severity status.

Definitions

Sepsis was defined as a life-threatening condition with organ dysfunction due to dysregulated host response to infection, and managed according to current international guidelines [32,33]. Heart failure was defined as presence of symptomatic heart disease confirmed by comprehensive echocardiography, accompanied by dilated jugular veins, lower limb edema, pulmonary edema, or shock, and was managed according to current guidelines [34,35]. Pulmonary edema was defined as presence of bilateral crackles on lung auscultation and presence of bilateral B lines in lung ultrasound [36]. Stroke was defined as acute onset of neurologic symptoms such as hemiplegia, aphasia, gaze deviation, or decreased level of consciousness, and no other explanation for the condition such as electrolyte disorder. If CT of the head showed hypodense lesions as signs of infarction, the etiology was presumed ischemic, if hyperdense lesions indicating hemorrhage were present, stroke was deemed hemorrhagic. If CT was not available, an etiology was not definable. Hypertension was defined as presence of at least 2 documented measurements of elevated blood pressure of ≥140/90 mmHg, or history of hypertension treatment [37]. Diabetes was defined as random blood glucose of >11 mmol/L, fasting glucose of >7mmol/L, or history of treated diabetes mellitus. Pneumonia was defined as presence of respiratory symptoms and detection of infiltrates, or interstitial changes by ultrasound or chest X-ray [36]. Kidney failure was defined as an estimated glomerular filtration rate (eGFR) of < 60 ml/min.

Statistical analysis

Descriptive statistics were used to summarize baseline characteristics and diagnoses at admission and discharge. Kaplan-Meier survival curves were employed to estimate and visualize mortality rates over time. Censoring patterns were examined, and the assumption of non-informative censoring was verified. To assess homogeneity between survival groups, log-rank tests were conducted. The association between clinical and demographic factors, including age, sex, occupation, admission source, vital signs, comorbidities, presenting symptoms, and early warning scores (UVA, NEWS, MEWS, qSOFA), and in-hospital mortality was assessed using univariable and multivariable Cox proportional hazards regression. This method accounts for differences in follow-up time and provides adjusted hazard ratios (HRs) to quantify the strength of associations. The proportional hazards assumption was tested using Schoenfeld residuals and log-minus-log plots and was not violated. To compare survival distributions across groups, log-rank tests were performed, and non-informative censoring assumptions were verified. Although we included all eligible patients admitted to the HDU during the study period (i.e., a complete cohort), multivariable analyses were conducted to adjust for potential confounders and to identify independent associations between clinical and demographic variables and in-hospital mortality. These adjusted estimates enhance internal validity and may be generalizable to similar resource-limited clinical settings. To evaluate the predictive performance of clinical scores, we conducted area under the receiver operating characteristic curve (AUROC) analysis, which measures the discriminative ability of each score in predicting in-hospital mortality. All statistical analyses were performed using Stata version 16. A p-value of <0.05 was considered statistically significant.

Ethical approval and consent to participate

Ethical approval was sought from the Institutional Review Board of the Ifakara Health Institute (IHI/IRB/12–2023), and the National Institute for Medical Research (NIMR/HQ/R.8a/Vol.IX/4247). Patients and their relatives were informed orally that data about their diagnosis and their outcome were used for research purposes. Written informed consent was waived by both ethics’ committees.

Results

Patient enrollment and follow-up

From April 4th 2023 to March 29th 2024, 516 admissions of 491 patients were recorded and included in the final analysis. All 491 patients were assessed at admission and were followed up for up to 30 days post-discharge from HDU. Forty-five (9.2%) patients were not reachable after discharge from the hospital and were classified as lost to follow up. The median length of stay in the HDU was 2 days (Interquartile range IQR: 1–3), while the overall median hospital stay was 4 days (IQR: 2–8).

Baseline characteristics on admission and diagnoses at discharge from HDU

Table 1 shows baseline characteristics of all included patients. The median patient age was 46 years (IQR 29–65), 259 (53%) were females, 128 (26%) had a history of hypertension, 85 (17%) had a history of diabetes mellitus, and 35 (7%) were people living with HIV (PLHIV). A total of 280 (57%) patients had been admitted directly from the emergency department, and 120 (24%) were referred after surgery. The main reason for admission to the HDU was respiratory failure in 247 (50%) patients. Other reasons for admission were a trauma in 39 (8%), and postoperative care in 129 (26%) patients. At admission a Glasgow Coma Scale (GCS) score of less than 8 was observed in 111 (23%), a mean arterial pressure (MAP) of less than 65 was measured in 38 (8%), and an oxygen saturation of <90% on room air was measured in 231 (47%) patients.

Table 1. Patients’ characteristics at admission in the high-dependency unit (N = 491).

Socio-demographic parameters N (%)
Age (years), median (IQR) 46 (29-65)
Age categories (years)
 <18 27 (6)
 18–44 213 (43)
 ≥45 251 (51)
 Male 232 (47)
 Female 259 (53)
 Farmer 385 (78)
 Non-farmer 106 (22)
Medical history
Hypertension 128 (26)
Diabetes mellitus 85 (17)
HIV infection 35 (7)
Heart failure 28 (6)
Stroke 24 (5)
Tuberculosis 12 (2)
Cancer 9 (2)
Asthma 7 (1)
Chronic obstructive pulmonary disease 6 (1)
Admission
Emergency department 280 (57)
Theatre 120 (24)
Hospital ward 91 (19)
Reasons for admission
Respiratory failure 247 (50)
Neurologic problem 157 (32)
Postoperative care 129 (26)
Hyperglycemia 43 (9)
Trauma 39 (8)
Hypertensive emergency 33 (7)
Septic shock 13 (3)
Diabetic coma 10 (2)
Surgery (n = 138)
Laparotomy 81 (59)
Urologic intervention 23 (17)
Chest tube 5 (4)
Assessment at admission
Airway problem 44 (9)
Breathing problem 380 (77)
Circulation problem 339 (69)
Disability problem 309 (63)
Exposure problem 182 (37)
BMI (kg/m2), median (IQR) 23 (21 –25 )
 Underweight (BMI < 18.5) 52 (11)
 Normal (BMI 18.5 – < 25) 298 (61)
 Overweight (BMI 25 – < 30) 102 (21)
 Obese (BMI ≥ 30) 39 (8)
GCS score (n = 490)
 ≤ 8 111 (23)
 9-13 120 (24)
 14-15 259 (53)
Systolic BP, mmHg, median (IQR)a 125 (109-144)
Diastolic BP, mmHg, median (IQR)a 77 (66-92)
Hypotensiona 41 (8)
Hypertensiona 191 (39)
MAP (mmHg), median (IQR)a 94 (80-109)
MAP < 65 mmHga 38 (8)
Heart rate, median (IQR) 100 (84-119)
Heart rate >100/min 244 (50)
Respiratory rate, median (IQR) 26 (20 –33 )
Respiratory rate >18/min 409 (83)
Oxygen saturation, median (IQR)
 On room air 92 (80-97)
 On oxygen (n = 234) 94 (91-97)
Oxygen saturation, n (%)
 On room air < 90% 231 (47)
 On oxygen <90% 46 (20)
Temperature (°C), median (IQR)b 36.2 (36.0-36.8)
Temperature > 37.8°Cb 39 (8)
Laboratory parameters
Hemoglobin (g/dl), median (IQR) 10.2 (7.5-12.2)
White blood cells (103/L), median (IQR) 9.7 (6.6-16.1)
Glucose (mmol/L), median (IQR) 7.9 (5.9-12.7)
Sodium (mmol/L), median (IQR) 137 (131-142)
Potassium (mmol/L), median (IQR) 4.2 (3.7-5.0)
Creatinine (mmol/L), median (IQR) 95.2 (65.8-200.9)
mRDT 11 (2)

Data were available from all participants unless marked with a or b.

ablood pressure was available from 487 patients.

bBody temperature was available from 489 patients. Results are frequency and percent (n (%)) of those with non-missing data, if not indicated otherwise.

IQR-Interquartile range, BMI, Body Mass Index; GCS, Glasgow Coma Scale score; BP, blood pressure; MAP, mean arterial pressure; Hypotension, BP systolic <90mmHg; Hypertension, BP systolic ≥140 mmHg or BP diastolic ≥90 mmHg, HIV-Human immunodeficiency virus, mRDT- Malaria rapid diagnostic test.

Table 2 shows diagnoses at admission and at discharge from the HDU, and the number of deaths in the HDU. The most common patient diagnoses at discharge from HDU were sepsis (N = 96, 20%), hypertension (N = 91, 19%), diabetes mellitus (N = 84, 17%) acute kidney injury (N = 66, 13%), decompensated heart failure (N = 64, 13%), aspiration pneumonia (N = 60, 12%), and stroke (n = 59, 12%), 24/59 (41%) being of hemorrhagic origin. Admission diagnoses to the HDU were broadly similar to those at discharge from HDU.

Table 2. Diagnoses at admission, discharge and death among patients in the high- dependency unit.

Diagnosis Admission
Total n = 491
N (%)
Discharge
Total n = 491
N (%)
Death
Total n = 146a
N (%)
Hypertension 89 (18) 91 (19) 27 (30)
Sepsis 81 (17) 96 (20) 52 (54)
Diabetes mellitus 75 (15) 84 (17) 13 (15)
Heart failure, decompensated 72 (15) 64 (13) 17 (27)
Pulmonary edema 65 (13) 40 (8) 15 (38)
Stroke 62 (13) 59 (12) 30 (51)
 Hemorrhage 15 (24) 24 (41) 11 (45)
 Ischemic 7 (11) 10 (17) 2 (20)
 Inconclusive 40 (65) 25 (42) 17 (68)
Pneumonia, aspiration 54 (11) 60 (12) 39 (65)
Pneumonia, CAP 53 (11) 28 (6) 11 (39)
Acute kidney injury 44 (9) 66 (13) 33 (50)
Trauma brain injury 27 (6) 25 (5) 8 (32)
Hypertensive heart disease 22 (4) 31 (6) 10 (32)
Seizures 21 (4) 14 (3) 9 (64)
Skin ulcers 16 (3) 22 (5) 6 (27)
Pulmonary embolism 15 (3) 20 (4) 10 (50)
Diabetic ketoacidosis 15 (3) 14 (3) 5 (36)
Malaria 11 (2) 13 (3) 7 (54)
Peritonitis 11 (2) 6 (1) 5 (83)
Exacerbated COPD 9 (2) 11 (2) 4 (36)
Delirium 8 (2) 10 (2) 2 (20)
Fracture lower limb 7 (1) 7 (1) 4 (57)
Intestinal obstruction 6 (1) 4 (1) 1 (25)
Trauma abdominal bleeding 5 (1) 6 (1) 2 (33)
Intoxication 5 (1) 5 (1) 1 (20)
Acute myocardial infarction 5 (1) 7 (1) 6 (86)
Asthma 4 (1) 4 (1) 1 (25)
Status epilepticus 4 (1) 5 (1) 1 (20)
Cor pulmonale 3 (1) 4 (1) 2 (50)
Ruptured ectopic pregnancy 3 (1) 3 (1)
Fracture upper limb 3 (1) 3 (1) 2 (67)
Endocarditis 2 (0.4) 2 (0.4) 1 (33)
Pneumothorax 2 (0.4) 1 (0.2)
Hematothorax 2 (0.4) 3 (1) 2 (50)
Rheumatic heart disease 2 (0.4) 1 (33)
Urinary Tract infection 1 (0.2) 1 (100)
Surgical site infection 3 (1) 2 (40)

More than one diagnosis possible per patient: at discharge, 52 (11%) had one diagnosis, 91 (19%) 2 diagnoses, 55 (11%) 3 diagnoses, 293 (60%)>=4 diagnoses.

CAP-Community Acquired Pneumonia, COPD-Chronic Obstructive Pulmonary Disease.

aDeath in the HDU; results are number and column percent of discharge diagnosis.

Patient outcomes and predictors of mortality

Among the 491 patients who were admitted to the HDU, 146 (30%) died during their stay, while 36/345 (10%) died after being discharged. The most common deadliest conditions were sepsis, stroke, seizures, or aspiration pneumonia, with mortality rates of 51% to 65%, while mortality of patients with heart failure was 27% (Table 2).

The total number of in-hospital deaths was 182 (37%) and the overall 30-day mortality was 36% (177 deaths). A total of 25 out of 345 patients (7%) discharged from HDU were readmitted. The Kaplan-Meier survival curve in Fig 1 shows the probability of death over time. The median time to death after admission to the HDU was 2 days (IQR 1–5) and the likelihood of in-hospital mortality increased with prolonged hospital stay.

Fig 1. In-hospital mortality rate among patients in the high-dependency unit.

Fig 1

The Kaplan-Meier curve shows the probability of death over time. The probabilities of death at 2, 6 and 8 days from admission were 22% (95% CI 19-26), 35% (95% CI 31-40) and 41% (95% CI 36-47), respectively.

Predictors of in-hospital mortality shown in Table 3 were age ≥ 45 years versus 18–44 years (adjusted Hazard Ratio (aHR) 1.56, 95%CI 1.07–2.28, p = 0.03), hypotension (systolic blood pressure < 90 mmHg), (aHR 2.33, 95%CI 1.48–3.81, p < 0.001), GCS score ≤8 versus 14–15 (aHR 2.13, 95%CI 1.24–3.64, p = 0.02) and oxygen saturation at room air < 90% (aHR 1.62, 95%CI 1.04–2.51, p = 0.03). Patient medical history, reasons for admission, and source of admission were not significant predictors of in-hospital mortality.

Table 3. Predictors of In-hospital mortality among patients in the high-dependency unit.

Characteristics Univariable
HR (95%CI)a
P valuea Multivariable HR (95%CI)a,b P valuea,b
Age categories (years) <0.001 0.03
 <18 1.67 (0.88-3.19) 1.78 (0.81-3.93)
 18–44 Reference Reference
 ≥45 1.88 (1.37-2.58) 1.56 (1.07-2.28)
Sex 0.32 0.81
 Female Reference Reference
 Male 1.16 (0.87-1.55) 1.04 (0.74-1.46)
Occupation 0.48 0.46
 Non-farmer Reference Reference
 Farmer 1.14 (0.79-1.65) 1.19 (0.75-1.90)
Admission from 0.004 0.32
 Emergency Department
1.18 (0.80-1.74) 1.20 (0.78-1.86)
 Theatre 0.62 (0.38-1.01) 0.65 (0.30-1.42)
 Hospital ward Reference Reference
BMI (kg/m2) 0.28 0.09
 Underweight (BMI < 18.5) 0.83 (0.49-1.40) 0.62 (0.33-1.15)
 Normal (BMI 18.5 – < 25) Reference Reference
 Overweight BMI (25 – < 30) 0.82 (0.55-1.21) 0.82 (0.54-1.25)
 Obesity (BMI ≥ 30) 1.41 (0.87-2.29) 1.56 (0.89-2.72)
GCS <0.001 0.02
 ≤8 3.49 (2.45-4.97) 2.13 (1.24-3.64)
 9−13 2.39 (1.65-3.49)
1.83 (1.08-3.08)
 14-15 Reference Reference
Hypotension 2.70 (1.79-4.07) <0.001 2.33 (1.43-3.81) <0.001
Hypertension 1.04 (0.77-1.41) 0.79 1.07 (0.74-1.55) 0.71
Heart rate 0.08 0.63
 ≤100/bpm Reference Reference
 >100/bpm 1.30 (0.97-1.74) 1.09 (0.77-1.53)
Respiratory rate 0.11 0.48
 ≤18/min Reference Reference
 >18/min 1.42 (0.91-2.22) 0.84 (0.51-1.38)
Oxygen saturation on room air <0.001 0.03
 ≥90% Reference
 <90% 2.90 (2.12-3.96) Reference
Temperature (°C) 0.03 1.62 (1.04-2.51) 0.63
 ≤37.8 Reference Reference
 >37.8 1.69 (1.10-2.60) 0.89 (0.54-1.45)
Medical history
 HIV infection 1.21 (0.73-1.99) 0.48 1.44 (0.83-2.49) 0.19
 Hypertension 1.02 (0.73-1.42) 0.92 0.67 (0.43-1.03) 0.07
 Diabetes mellitus 0.70 (0.45-1.07) 0.08 0.89 (0.55-1.43) 0.63
 Heart failure 1.09 (0.60-2.01) 0.78 0.94 (0.48-1.87) 0.87
Reason for admission
 Trauma 1.08 (0.64-1.80) 0.78 0.95 (0.51-1.76) 0.86
 Respiratory failure 2.43 (1.78-3.32) <0.001 1.38 (0.89-2.14) 0.15
 Postoperative care 0.57 (0.39-0.82) <0.001 0.73 (0.33-1.60) 0.43
Symptoms and physical examinations
 Airway problem 2.46 (1.66-3.64) <0.001 1.27 (0.79-2.05) 0.32
 Breathing problem 3.73 (2.20-6.32)
<0.001 1.47 (0.75-2.86) 0.26
 Circulation problem 2.28 (1.56-3.32) <0.001 1.32 (0.83-2.08) 0.24
 Disability problem 3.01 (2.06-4.40) <0.001 1.57 (0.89-2.77) 0.12
 Exposure problem 0.88 (0.65-1.19) 0.40 1.08 (0.74-1.59) 0.68

aHazard Ratio (HR) and 95% Confident Intervals (CI) obtained from Cox regression.

bAdjusted for all variables shown in the table, missing data excluded, N = 487.

BP, blood pressure; Hypotension, systolic BP < 90mmHg; Hypertension, systolic BP ≥ 140 or diastolic BP ≥ 90; BMI, body mass index; GCS, Glasgow Coma Scale score.

Association of clinical scores with in-hospital mortality

Validated clinical scores were used to assess the severity of illness and predict in-hospital mortality. The majority of admitted patients fulfilled the high-risk strata of these scores, underscoring the severity of their clinical conditions: using UVA, a total of 205 (42%), using NEWS, 297 (61%), using MEWS, 313 (65%), and using qSOFA 254 (52%) patients reached high risk scores, respectively (S1 Table). A high-risk NEWS score predicted in-hospital mortality with an odd ratio (OR) of 8.25 (95%CI 4.34–15.67, p < 0.001). Fig 2 shows the AUROC analysis: The Area-Under-The-Curve (AUC) estimation revealed that UVA and NEWS scores had the highest predictive accuracy for in-hospital mortality, both with AUC values of 0.69 (95% CI 0.65–0.73) (Fig 2).

Fig 2. Area under the receiver operating characteristic curves of clinical scores predicting in-hospital mortality of patients.

Fig 2

The area under the receiver operating characteristic curves (AUROC) shows the predictive accuracy of the Universal Vital Assessment (UVA) score, the National Early Warning Score (NEWS), the Modified Early Warning Score (MEWS), and the Quick Sequential Organ Failure Assessment (qSOFA) score for in-hospital mortality. The area under the curve (AUC) values were for UVA: 0.69 (95%CI 0.65–0.73); for NEWS: 0.69 (95%CI 0.65–0.73); for MEWS: 0.66 (95%CI 0.62–0.70); and for qSOFA: 0.65 (95%CI 0.61–0.69).

Diagnostic imaging and treatment done during admission in the HDU

During the stay in the HDU, 460 diagnostic procedures were performed according to clinical indication including POCUS, echocardiography, lung ultrasound and ECG as a bedside investigation. Of these, 330 (72%) procedures were abnormal, as shown in S2 Table. The most common medication administered is shown in S3 Table. Antibiotics were used in 201 (58%), analgesics in 109 (32%), anti-hypertensives in 79 (23%) and heart failure medications in 68 (20%) patients. Vasoactive drugs were administered to 62 (13%) patients. Non-invasive ventilation was done in 25 (5%) patients

Discussion

Key findings

In this cohort study including all patients admitted within one year to a HDU of a regional referral hospital situated in rural Tanzania, most common diagnoses were sepsis, heart failure, and stroke, accompanied by hypertension, diabetes mellitus, acute kidney failure, and aspiration pneumonia. NCDs and their complications were the most relevant causes for HDU admission. Malaria accounted for 3% of diagnoses made upon discharge and was associated with a 54% mortality. Mortality was high with 30% of patients dying during HDU stay. While more than half of the patients with sepsis or stroke died in the HDU, the mortality of patients with decompensated heart failure was lower at 27%. Predictors of in-hospital mortality were age, a GCS score of ≤ 8, a systolic blood pressure of < 90 mmHg and an oxygen saturation of less than 90% at room air at admission. UVA, NEWS, MEWS, and qSOFA scores predicted in-hospital mortality with a moderate diagnostic accuracy.

Comparison with other studies

Comparison of clinical information and outcomes from different critical care units is challenging, as settings and infrastructure are diverse. In our cohort, the median age of 46 years was higher than in another cohort of hospitalizes patients [38]. Since children are usually admitted to the pediatric department, only 6% of the patients admitted to the HDU were younger than 18 years. Sepsis was the most frequent diagnosis (20%), which is similar to studies from urban settings [16,17], but which is different to other studies where about 10% [15,28,39] to 44% [8] of patients had sepsis. The heterogeneity in the proportion of patients diagnosed with sepsis may be explained by different definitions used, and by different study designs such as retrospective study designs [15,28,39,40], or short prospective data collection periods of 2 days [8]. The majority of patients suffering from an NCD is in line with a recent large point prevalence study including patients from 22 African countries, where more than half of critically ill patients were admitted to the hospital because of an NCD [41]. The high number of patients with respiratory failure (N = 247, 50%) is in line with other African studies [12,15,39]. The underlying factors of respiratory failure are diverse and may be attributed to infectious or cardiac causes. Pulmonary edema leading to respiratory failure led to admission to HDU in 13%, which is higher than other studies (3–9%) [8,15,17], possibly due to poor control of underlying cardiopathies.

The high mortality rates in our study are consistent with those described in studies conducted in ICUs in Tanzania, Uganda, Malawi, and Ethiopia with mortality rates ranging between 25.6% and 52% in general [12,1417,28,42] and 42–75% for patients with sepsis [40]. Comparison of outcomes with other studies is challenging due to different study designs [12,15,17,28,42], different periods of data assessment ranging from 6 weeks to 3 months [14,16] and because ICUs were situated in urban centres. The probability of death was highest during the first 5 days following admission which is similar to results reported in other studies [12,16,28]. In high-income countries, ICU-mortality has been reported to be 10.8% in the USA [43], while ICU- and in-hospital mortality was 19.1% and 23.9%, respectively, in an European multicenter cohort study [44].

Studies conducted in ICUs showed that the need for mechanical ventilation, the use of vasopressors or inotropes and an age > 45 years were associated with increased mortality rates [16,17,45]. In our study, hypotension, oxygen saturation < 90% and age > 45 years were strong predictors of in-hospital mortality.

The moderate prediction of mortality by scores is in line with other studies from Africa which included hospitalized patients in general wards [29,38,46]. In studies from high income countries, the NEWS score was the best predictor of in-hospital mortality compared with other scores, with an AUC of 0.87 [30,47]. Since people living with HIV are at greater risk of developing infections and sepsis, the UVA score is worth considering when stratifying mortality risk in Tanzania, where HIV prevalence is 4.7% [48]. All scores can be calculated based on clinical information only and are feasible in settings where laboratory results are not always available.

Implications for practice

A leading cause of HDU admission in our study was stroke. In 65% of patients a CT could not be performed because of financial constraints of patients. Among patients who received a CT, haemorrhagic stroke was diagnosed in 41%. This might be explained due to the high proportion of patients with uncontrolled hypertension. Less than 15% of hypertensive people have controlled blood pressure in sub-Saharan Africa [49], and programes to screen for hypertension and to increase awareness of hypertension in the communities are needed.

Patients presented late in serious conditions. The severity of illness was demonstrated by a high-risk stratum of the scores at admission, which would have qualified patients to admission to an ICU, which is not implemented yet.

Late presentation and high mortality reflect systemic challenges in rural healthcare: The late presentation of patients in already serious conditions is due to lack of awareness of potentially life-threatening infectious – and non-communicable diseases in the communities, limited diagnostic tools to diagnose serious conditions and limited therapeutic options in the periphery, lack of transport, and the fact that a majority of patients do not have a health insurance to cover healthcare costs. This highlights the importance of programmes to increase community awareness of diseases with potentially unfavorable outcomes and to strengthen prevention of NCDs, integrating diagnosis and treatment of NCDs into existing decentralized facilities such as HIV clinics [50], and training of health care personnel in diagnosing infectious diseases and NCDs in the periphery [5153]. The implementation of referral systems and improving transport logistics to specialized centers is needed to maximise benefits from specialized care. While there are 35 ICU beds per 100’000 people in Germany [54], there is less than 1 ICU bed per 100’000 people in Africa [7,55]. One in eight patients in hospitals in Africa are critically ill, and two-thirds of them are cared for in general wards [41]. Therefore, implementation of more HDUs and ICUs is urgently needed in Africa. Training of healthcare personnel is needed to guarantee rapid and appropriate care for patients suffering from severe acute diseases or acute deterioration of pre-existing conditions. Moreover, access to health insurance needs to be ameliorated.

Strengths

To the best of our knowledge, this is the first study reporting characteristics, diagnoses and outcomes of patients managed at a HDU in a hospital from a rural setting in sub-Saharan Africa. Strengths of this study are the prospective study design, the comprehensive data collection, the complete inclusion of all patients admitted to the HDU during one full calendar year, and the availability of the outcome in-hospital mortality for all patients, allowing reliable comparative analyses.

Limitations

Our study has limitations. First, the access to diagnostic tools such as microbiological tests except Xpert MTB/RIF ULTRA®, HIV and malaria rapid tests, and laboratory tests beyond full blood picture, electrolytes, liver and renal function tests was limited. Therefore, diagnoses were mainly based on clinical and ultrasonographic findings, and some diseases could have been missed. However, all doctors working at the HDU were trained in clinical medicine, POCUS, focused echocardiography, and performance of ECG, and were supervised by experienced senior physicians who assessed all patients and reviewed all diagnoses. Second, although some of the treatments were administered before payment, financial constraints limited the use of available diagnostic and therapeutic tools such as CT and hemodialysis. This might have a negative impact on patients outcomes. Third, 9% of patients were lost to follow-up after discharge from the hospital, and patients could not be followed for a longer period to determine their post discharge outcome. However, we could analyse all patients for the endpoint of in-hospital death. Fourth, non-invasive ventilation and the use of vasoactive drugs was implemented during the study period and would have been used more frequently if implemented earlier. Fifth, we could not determine the systemic inflammatory response syndrome (SIRS) score reliably, because white cell count was not available for all patients. Last, this was a single centre study, and generalisability of these findings to populations living in other settings might be limited.

Conclusions

In conclusion, sepsis, heart failure, stroke, hypertension, diabetes mellitus, and renal failure were the most common diagnoses of patients admitted to a HDU of a referral hospital in rural Tanzania. While sepsis and stroke were among the deadliest conditions, patients with heart failure had a better prognosis. Scores such as UVA, MEWS, NEWS and qSOFA predicted in-Hospital mortality with a moderate accuracy. These findings underscore the need for improved critical care in low-resource rural settings. Decentralisation of critical care is needed to serve quickly patients in severe conditions. Future studies should explore interventions to reduce mortality in rural HDUs.

Supporting information

S1 Table. Association of clinical scores with in-hospital mortality among patients in the high-dependency unit.

(DOCX)

pone.0324640.s001.docx (15.9KB, docx)
S2 Table. Diagnostic tests performed on patients in the high-dependency unit.

(DOCX)

pone.0324640.s002.docx (15.1KB, docx)
S3 Table. Treatment and medication among patients in the high-dependency unit.

(DOCX)

pone.0324640.s003.docx (15.9KB, docx)

Acknowledgments

We thank Fabian Fiechter, Sarah Adina Funk, and Albert Urwyler, University Hospital Basel, Switzerland; Wilson Lugano and Victor Zablon Urio, Benjamin Mkapa Hospital, Dodoma; and Vivienne Ayiana Mlawi, Jakaya Kikwete Cardiac Institute, Dar es Salaam, for training of the staff of the high dependency unit in critical care medicine. We thank Valentine Mteki, Ifakara Health Institute, for course organization.

Data Availability

All relevant data are within the paper and its Supporting information. The datasets used and/or analyzed during the current study are available with restricted access from Zenodo at https://zenodo.org/records/15177213.

Funding Statement

Martin Rohacek received a grant from the Else Kröner-Fresenius-Stiftung, Bad Homburg vor der Höhe, Germany, for the implementation of the high dependency unit at the St Francis Regional Referral Hospital, Ifakara. Julie Rossier received financial support from the Freiwillige Akademische Gesellschaft Basel, Basel, Switzerland, to finance her travel- and living expenses during her stay in Ifakara. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

References

  • 1.WHO. Integrated emergency, critical and operative care (ECO). [cited 31 Oct 2024]. Available: https://www.who.int/teams/integrated-health-services/clinical-services-and-systems/emergency--critical-and-operative-care [Google Scholar]
  • 2.Ministry of Health, United Republic of Tanzania. National Strategic Plan on Essential Emergency and Critical Care Services (2023-2026). 2022. Dodoma: Ministry of Health; 2022. Available: https://www.moh.go.tz/storage/app/uploads/public/65a/e85/9d2/65ae859d2250d296035040.pdf [Google Scholar]
  • 3.WHO. Non communicable diseases. [cited 27 Mar 2025]. Available: https://www.who.int/news-room/fact-sheets/detail/noncommunicable-diseases [Google Scholar]
  • 4.Atumanya P, Sendagire C, Wabule A, Mukisa J, Ssemogerere L, Kwizera A, et al. Assessment of the current capacity of intensive care units in Uganda; A descriptive study. J Crit Care. 2020;55:95–9. doi: 10.1016/j.jcrc.2019.10.019 [DOI] [PubMed] [Google Scholar]
  • 5.Kodama C, Kuniyoshi G, Abubakar A. Lessons learned during COVID-19: Building critical care/ICU capacity for resource limited countries with complex emergencies in the World Health Organization Eastern Mediterranean Region. J Glob Health. 2021;11:03088. doi: 10.7189/jogh.11.03088 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 6.Baker T. Critical care in low-income countries. Trop Med Int Health. 2009;14(2):143–8. doi: 10.1111/j.1365-3156.2008.02202.x [DOI] [PubMed] [Google Scholar]
  • 7.Kifle F, Boru Y, Tamiru HD, Sultan M, Walelign Y, Demelash A, et al. Intensive care in Sub-Saharan Africa: a national review of the service status in Ethiopia. Anesthesia & Analgesia. 2021;134(5):930–7. doi: 10.1213/ane.0000000000005799 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 8.Dart PJ, Kinnear J, Bould MD, Mwansa SL, Rakhda Z, Snell D. An evaluation of inpatient morbidity and critical care provision in Zambia. Anaesthesia. 2017;72(2):172–80. doi: 10.1111/anae.13709 [DOI] [PubMed] [Google Scholar]
  • 9.Sawe HR, Wallis LA, Weber EJ, Mfinanga JA, Coats TJ, Reynolds TA. The burden of trauma in Tanzania: Analysis of prospective trauma registry data at regional hospitals in Tanzania. Injury. 2020;51(12):2938–45. doi: 10.1016/j.injury.2020.09.032 [DOI] [PubMed] [Google Scholar]
  • 10.Cheng AC, West TE, Limmathurotsakul D, Peacock SJ. Strategies to reduce mortality from bacterial sepsis in adults in developing countries. PLoS Med. 2008;5(8):e175. doi: 10.1371/journal.pmed.0050175 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 11.Stöger L, Katende A, Mapesi H, Kalinjuma AV, van Essen L, Klimkait T, et al. Persistent high burden and mortality associated with advanced HIV disease in rural tanzania despite uptake of World Health Organization “test and treat” guidelines. Open Forum Infect Dis. 2022;9(12):ofac611. doi: 10.1093/ofid/ofac611 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 12.Dünser MW, Towey RM, Amito J, Mer M. Intensive care medicine in rural sub-Saharan Africa. Anaesthesia. 2017;72(2):181–9. doi: 10.1111/anae.13710 [DOI] [PubMed] [Google Scholar]
  • 13.African COVID-19 Critical Care Outcomes Study (ACCCOS) Investigators. Patient care and clinical outcomes for patients with COVID-19 infection admitted to African high-care or intensive care units (ACCCOS): a multicentre, prospective, observational cohort study. Lancet. 2021;397(10288):1885–94. doi: 10.1016/S0140-6736(21)00441-4 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 14.Prin M, Itaye T, Clark S, Fernando RJ, Namboya F, Pollach G, et al. Critical care in a tertiary hospital in Malawi. World J Surg. 2016;40(11):2635–42. doi: 10.1007/s00268-016-3578-y [DOI] [PubMed] [Google Scholar]
  • 15.Bwanali AN, Munthali L, Napolo U, Lubanga AF, Gundo R, Mpinganjira SL. Clinical audit of cases and outcomes of patients admitted to the intensive care unit at Kamuzu Central Hospital, Lilongwe, Malawi. Sci Rep. 2024;14(1):19019. doi: 10.1038/s41598-024-66810-7 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 16.Atumanya P, Agaba PK, Mukisa J, Nakibuuka J, Kwizera A, Sendagire C. Characteristics and outcomes of patients admitted to intensive care units in Uganda: a descriptive nationwide multicentre prospective study. Sci Rep. 2024;14(1):9963. doi: 10.1038/s41598-024-59031-5 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 17.Sultan M, Zewdie A, Priyadarshani D, Hassen E, Tilahun M, Geremew T, et al. Implementing an ICU registry in Ethiopia-Implications for critical care quality improvement. J Crit Care. 2024;81:154525. doi: 10.1016/j.jcrc.2024.154525 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 18.Baker T, Lugazia E, Eriksen J, Mwafongo V, Irestedt L, Konrad D. Emergency and critical care services in Tanzania: a survey of ten hospitals. BMC Health Serv Res. 2013;13:140. doi: 10.1186/1472-6963-13-140 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 19.Kwizera A, Sendagire C, Kamuntu Y, Rutayisire M, Nakibuuka J, Muwanguzi PA, et al. Building critical care capacity in a low-income country. Crit Care Clin. 2022;38(4):747–59. doi: 10.1016/j.ccc.2022.07.003 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 20.Mselle LT. Caring critically ill patients in the general wards in Tanzania: experience of nurses and physicians. Int J Crit Care Emerg Med. [Google Scholar]
  • 21.Acute Care Action Network (ACAN). [cited 31 Oct 2024]. Available: https://www.who.int/groups/acute-care-action-network [Google Scholar]
  • 22.Marshall JC, Bosco L, Adhikari NK, Connolly B, Diaz JV, Dorman T, et al. What is an intensive care unit? A report of the task force of the World Federation of Societies of Intensive and Critical Care Medicine. J Critical Care. 2017;37:270–6. doi: 10.1016/j.jcrc.2016.07.015 [DOI] [PubMed] [Google Scholar]
  • 23.Bauer M, Kitila F, Mwasongwe I, Abdallah IS, Siongo E, Kasunga S, et al. Ultrasonographic findings in patients with abdominal symptoms or trauma presenting to an emergency room in rural Tanzania. PLoS ONE. 2022;17(6):e0269344. doi: 10.1371/journal.pone.0269344 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 24.Mchomvu E, Mbunda G, Simon N, Kitila F, Temba Y, Msumba I, et al. Diagnoses made in an Emergency Department in rural sub-Saharan Africa. Swiss Med Wkly. 2019;149:w20018. doi: 10.4414/smw.2019.20018 [DOI] [PubMed] [Google Scholar]
  • 25.Towey RM, Ojara S. Intensive care in the developing world. Anaesthesia. 2007;62(s1):32–7. doi: 10.1111/j.1365-2044.2007.05295.x [DOI] [PubMed] [Google Scholar]
  • 26.Sonenthal PD, Kasomekera N, Connolly E, Wroe EB, Katete M, Minyaliwa T, et al. Critical Care Units in Malawi: a cross-sectional study. Ann Glob Health. 2023;89(1):51. doi: 10.5334/aogh.4053 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 27.Marotta C, Pisani L, Di Gennaro F, Cavallin F, Bah S, Pisani V, et al. Epidemiology, outcomes, and risk factors for mortality in critically ill women admitted to an obstetric high-dependency unit in Sierra Leone. Am J Trop Med Hyg. 2020;103(5):2142–8. doi: 10.4269/ajtmh.20-0623 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 28.Ttendo SS, Was A, Preston MA, Munyarugero E, Kerry VB, Firth PG. Retrospective descriptive study of an intensive care unit at a Ugandan regional referral hospital. World J Surg. 2016;40(12):2847–56. doi: 10.1007/s00268-016-3644-5 [DOI] [PubMed] [Google Scholar]
  • 29.Moore CC, Hazard R, Saulters KJ, Ainsworth J, Adakun SA, Amir A, et al. Derivation and validation of a universal vital assessment (UVA) score: a tool for predicting mortality in adult hospitalised patients in sub-Saharan Africa. BMJ Glob Health. 2017;2(2):e000344. doi: 10.1136/bmjgh-2017-000344 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 30.Smith GB, Prytherch DR, Meredith P, Schmidt PE, Featherstone PI. The ability of the National Early Warning Score (NEWS) to discriminate patients at risk of early cardiac arrest, unanticipated intensive care unit admission, and death. Resuscitation. 2013;84(4):465–70. doi: 10.1016/j.resuscitation.2012.12.016 [DOI] [PubMed] [Google Scholar]
  • 31.Bulut M, Cebicci H, Sigirli D, Sak A, Durmus O, Top AA, et al. The comparison of modified early warning score with rapid emergency medicine score: a prospective multicentre observational cohort study on medical and surgical patients presenting to emergency department. Emerg Med J. 2014;31(6):476–81. doi: 10.1136/emermed-2013-202444 [DOI] [PubMed] [Google Scholar]
  • 32.Seymour CW, Liu VX, Iwashyna TJ, Brunkhorst FM, Rea TD, Scherag A, et al. Assessment of clinical criteria for sepsis: for the Third International Consensus Definitions for Sepsis and Septic Shock (Sepsis-3). JAMA. 2016;315(8):762–74. doi: 10.1001/jama.2016.0288 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 33.Evans L, Rhodes A, Alhazzani W, Antonelli M, Coopersmith CM, French C, et al. Surviving sepsis campaign: international guidelines for management of sepsis and septic shock 2021. Intensive Care Med. 2021;47(11):1181–247. doi: 10.1007/s00134-021-06506-y [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 34.McDonagh TA, Metra M, Adamo M, Gardner RS, Baumbach A, Böhm M, et al. 2021 ESC Guidelines for the diagnosis and treatment of acute and chronic heart failure. Eur Heart J. 2021;42(36):3599–726. doi: 10.1093/eurheartj/ehab368 [DOI] [PubMed] [Google Scholar]
  • 35.McDonagh TA, Metra M, Adamo M, Gardner RS, Baumbach A, Böhm M, et al. 2023 Focused Update of the 2021 ESC Guidelines for the diagnosis and treatment of acute and chronic heart failure. Eur Heart J. 2023;44(37):3627–39. doi: 10.1093/eurheartj/ehad195 [DOI] [PubMed] [Google Scholar]
  • 36.Katende A, Oehri J, Urio VZ, Mahundi E, Wilson L, Myovela V, et al. Use of a handheld ultrasonographic device to identify heart failure and pulmonary disease in rural Africa. JAMA Netw Open. 2024;7(2):e240577. doi: 10.1001/jamanetworkopen.2024.0577 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 37.Williams B, Mancia G, Spiering W, Agabiti Rosei E, Azizi M, Burnier M, et al. 2018 ESC/ESH Guidelines for the management of arterial hypertension. Eur Heart J. 2018;39(33):3021–104. doi: 10.1093/eurheartj/ehy339 [DOI] [PubMed] [Google Scholar]
  • 38.Bonnewell JP, Rubach MP, Madut DB, Carugati M, Maze MJ, Kilonzo KG, et al. Performance assessment of the universal vital assessment score vs other illness severity scores for predicting risk of in-hospital death among adult febrile inpatients in Northern Tanzania, 2016-2019. JAMA Netw Open. 2021;4(12):e2136398. doi: 10.1001/jamanetworkopen.2021.36398 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 39.Lalani HS, Waweru-Siika W, Mwogi T, Kituyi P, Egger JR, Park LP, et al. Intensive care outcomes and mortality prediction at a national referral hospital in Western Kenya. Ann Am Thorac Soc. 2018;15(11):1336–43. doi: 10.1513/AnnalsATS.201801-051OC [DOI] [PubMed] [Google Scholar]
  • 40.Prin M, Onofrey L, Purcell L, Kadyaudzu C, Charles A. Prevalence, etiology, and outcome of sepsis among critically ill patients in Malawi. Am J Trop Med Hyg. 2020;103(1):472–9. doi: 10.4269/ajtmh.19-0605 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 41.Baker T, Scribante J, Elhadi M, Ademuyiwa A, Osinaike B, Owoo C, et al. The African Critical Illness Outcomes Study (ACIOS): a point prevalence study of critical illness in 22 nations in Africa. The Lancet. 2025;405: 715–24. doi: 10.1016/S0140-6736(24)02846-0 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 42.Sawe HR, Mfinanga JA, Lidenge SJ, Mpondo BCT, Msangi S, Lugazia E, et al. Disease patterns and clinical outcomes of patients admitted in intensive care units of tertiary referral hospitals of Tanzania. BMC Int Health Hum Rights. 2014;14:26. doi: 10.1186/1472-698X-14-26 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 43.Checkley W, Martin GS, Brown SM, Chang SY, Dabbagh O, Fremont RD, et al. Structure, process, and annual ICU mortality across 69 centers: United States critical illness and injury trials group critical illness outcomes study. Crit Care Med. 2014;42(2):344–56. doi: 10.1097/CCM.0b013e3182a275d7 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 44.Capuzzo M, Volta CA, Tassinati T, Moreno RP, Valentin A, Guidet B, et al. Hospital mortality of adults admitted to Intensive Care Units in hospitals with and without Intermediate Care Units: a multicentre European cohort study. Crit Care. 2014;18(5). doi: 10.1186/s13054-014-0551-8 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 45.Venturas JP, Richards GA, Feldman C. Severe community-acquired pneumonia at a tertiary academic hospital in Johannesburg, South Africa. Respiratory Medicine. 2024;234:107823. doi: 10.1016/j.rmed.2024.107823 [DOI] [PubMed] [Google Scholar]
  • 46.Schmedding M, Adegbite BR, Gould S, Beyeme JO, Adegnika AA, Grobusch MP, et al. A prospective comparison of quick sequential organ failure assessment, systemic inflammatory response syndrome criteria, universal vital assessment, and modified early warning score to predict mortality in patients with suspected infection in gabon. The American Journal of Tropical Medicine and Hygiene. 2019;100(1):202–8. doi: 10.4269/ajtmh.18-0577 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 47.Liu VX, Lu Y, Carey KA, Gilbert ER, Afshar M, Akel M, et al. Comparison of early warning scoring systems for hospitalized patients with and without infection at risk for in-hospital mortality and transfer to the intensive care unit. JAMA Netw Open. 2020;3(5):e205191. doi: 10.1001/jamanetworkopen.2020.5191 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 48.HIV/AIDS in Tanzania – NACP-National AIDS Control Programme. [cited 27 Dec 2024]. Available: https://nacp.go.tz/hiv-aids-in-tanzania/ [Google Scholar]
  • 49.May Measurement Month 2018: a pragmatic global screening campaign to raise awareness of blood pressure by the International Society of Hypertension - PubMed. [cited 28 Mar 2025]. Available: https://pubmed.ncbi.nlm.nih.gov/31041440/ [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 50.Kivuyo S, Birungi J, Okebe J, Wang D, Ramaiya K, Ainan S, et al. Integrated management of HIV, diabetes, and hypertension in sub-Saharan Africa (INTE-AFRICA): a pragmatic cluster-randomised, controlled trial. Lancet. 2023;402(10409):1241–50. doi: 10.1016/S0140-6736(23)01573-8 [DOI] [PubMed] [Google Scholar]
  • 51.WHO. HEARTS: Technical package for cardiovascular disease management in primary health care: Tool for the development of a consensus protocol for treatment of hypertension: technical package for cardiovascular disease management in primary health care. [cited 28 Mar 2025]. Available: https://www.who.int/publications/i/item/WHO-NMH-NVI-19- [Google Scholar]
  • 52.Klassen SL, Okello E, Ferrer JME, Alizadeh F, Barango P, Chillo P, et al. Decentralization and integration of advanced cardiac care for the world’s poorest billion through the PEN-plus strategy for severe chronic non-communicable disease. Glob Heart. 2024;19(1):33. doi: 10.5334/gh.1313 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 53.WHO. PEN and integrated outpatient care for severe, chronic NCDS at first referral hospitals in the African region (PEN-PLUS) - Report on regional consultation | WHO | Regional Office for Africa. 27. Mar 2025 [cited 28 Mar 2025]. Available: https://www.afro.who.int/publications/who-pen-and-integrated-outpatient-care-severe-chronic-ncds-first-referral-hospitals [Google Scholar]
  • 54.Bauer J, Brüggmann D, Klingelhöfer D, Maier W, Schwettmann L, Weiss DJ, et al. Access to intensive care in 14 European countries: a spatial analysis of intensive care need and capacity in the light of COVID-19. Intensive Care Med. 2020;46(11):2026–34. doi: 10.1007/s00134-020-06229-6 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 55.Siaw-Frimpong M, Touray S, Sefa N. Capacity of intensive care units in Ghana. J Crit Care. 2021;61:76–81. doi: 10.1016/j.jcrc.2020.10.009 [DOI] [PMC free article] [PubMed] [Google Scholar]

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We look forward to receiving your revised manuscript.

Kind regards,

Abraham Aregay Desta, MSc, PhD candidate.

Academic Editor

PLOS ONE

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Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. Is the manuscript technically sound, and do the data support the conclusions?

Reviewer #1: Yes

Reviewer #2: Partly

**********

2. Has the statistical analysis been performed appropriately and rigorously? -->?>

Reviewer #1: Yes

Reviewer #2: Yes

**********

3. Have the authors made all data underlying the findings in their manuscript fully available??>

The PLOS Data policy

Reviewer #1: No

Reviewer #2: Yes

**********

4. Is the manuscript presented in an intelligible fashion and written in standard English??>

Reviewer #1: Yes

Reviewer #2: Yes

**********

Reviewer #1: The study addresses an important gap in the literature by providing the first detailed description of diagnoses and outcomes in a rural high dependency unit (HDU) in sub-Saharan Africa.

The methodology is robust, with a prospective cohort design, clear inclusion/exclusion criteria, and comprehensive data collection.

The findings are significant, highlighting high mortality rates and predictors of in-hospital mortality, which have important implications for critical care in low-resource settings.

Areas for Improvement:

Clarity and Structure: Some sections (e.g., Results, Discussion) could be streamlined for better readability.

Contextualization: The paper would benefit from a stronger emphasis on the broader implications of the findings for policy and practice in rural healthcare.

Limitations: While limitations are acknowledged, they could be discussed in more depth, particularly regarding the impact of financial constraints and diagnostic limitations on patient outcomes.

Language: Minor grammatical and stylistic improvements are needed to enhance clarity and flow.

Overall Assessment:

The paper is scientifically sound and makes a valuable contribution to the field. The required revisions are relatively minor and primarily focus on improving clarity, structure, and contextualization.

Reviewer #2: The study addresses an important gap in understanding critically ill patient outcomes in rural HDUs, making it highly relevant for clinicians and policymakers. Here are my recommendations:

1. The introduction focuses heavily on HDU setup rather than framing a clear research gap.

2. The objective should be explicitly stated earlier in the introduction and aligned more clearly with the research question.

3. The methods section needs more focus on patient selection,sample size, data collection, and statistical analysis rather than HDU implementation details.

4. The criteria for selecting variables in multivariable analysis are not clearly stated. Providing justification based on univariate p-values, clinical relevance, or confounding adjustment would improve transparency.

5. There are inconsistencies in reporting p-values and confidence intervals. Using a uniform format (e.g., p = 0.03, 95% CI 1.07–2.28) would enhance readability.

6. Realign all the segments to the objectives rather and HDU implementation.

**********

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Reviewer #1: Yes:  Yamlak Gindola

Reviewer #2: No

**********

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Attachment

Submitted filename: A Review for Manuscript Number PONE.docx

pone.0324640.s004.docx (16.9KB, docx)
PLoS One. 2025 Jun 18;20(6):e0324640. doi: 10.1371/journal.pone.0324640.r003

Author response to Decision Letter 1


10 Apr 2025

To April 10th 2025

Dr Abraham Aregay Desta

Editor

PLOS one

Dear Dr Desta

We thank you and the reviewers very much for the review of our manuscript

PONE-D-25-05201

"Diagnoses and outcomes of critically ill patients admitted to a high dependency unit of a rural referral hospital in Tanzania: A Prospective Cohort Study"

We changed the title to “First Insights into Critical Care Outcomes in a Rural Tanzanian High Dependency Unit: A prospective cohort study” as suggested by a reviewer.

We revised the manuscript according to the valuable comments of the reviewers and responded in a point-by-point reply below.

We uploaded a clean version of the manuscript and a version with track changes.

We uploaded the minimal dataset to https://zenodo.org/records/15177213

We checked all statistical analyses by running them again and corrected 2 numbers in Table 1 and one number in Table 3 which is marked in yellow.

Martin Rohacek received funds from the Else Kröner Fresenius Foundation, Germany, Julie Rossier received funds from the Freiwillige Akademische Gesellschaft Basel, Switzerland. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Thank you very much for evaluating our revised version of the manuscript.

Sincerely yours

PD Dr med Martin Rohacek

Swiss TPH

Kreuzstrasse 2

4123 Allschwil

Switzerland

University of Basel, Switzerland

Ifakara Health Institute, Tanzania

martin.rohacek@swisstph.ch, mrohacek@ihi.or.tz

Point By Point reply to reviewers’ comments which was attached to the e-mail from March 19th and April 1st

A Review for Manuscript Number PONE-D-25-05201

"Diagnoses and outcomes of critically ill patients admitted to a high dependency unit of a rural referral hospital in Tanzania: A prospective cohort study"

Title

Current Title: Diagnoses and outcomes of critically ill patients admitted to a high dependency unit of a rural referral hospital in Tanzania: A prospective cohort study

Comments:

Consider making the title more concise. For example:

"Critical Care Outcomes in a Rural Tanzanian High Dependency Unit: A Prospective Cohort Study"

Alternatively, emphasize the novelty of the study:

"First Insights into Critical Care Outcomes in a Rural Tanzanian High Dependency Unit: A Prospective Cohort Study"

Response:

We thank the reviewer for this comment. We changed the title to "First Insights into Critical Care Outcomes in a Rural Tanzanian High Dependency Unit: A Prospective Cohort Study" as suggested

Abstract

Comments:

Background: Briefly mention the gap in literature (e.g., lack of data on HDUs in rural sub-Saharan Africa).

Response:

We thank the reviewer for this comment. We revised the background of the abstract as follows:

Background: Data on high dependency units (HDU) situated in rural sub-Saharan Africa are lacking. In this study, we describe patient’s characteristics, diagnoses, and outcomes of critically ill patients admitted to a high dependency unit of a referral hospital in rural Tanzania, and factors associated with in-hospital mortality.

Methods:

Comment:

Clarify the sample size earlier (e.g., “491 patients admitted to the HDU”).

Response: We included this information into the first sentence of the methods section on page 3.

Results:

Comment:

Highlight the most striking finding (e.g., “Mortality during HDU stay was 30%, with sepsis and stroke being the deadliest conditions”).

Response:

We thank the reviewer for this comment. We moved the section “Patient outcomes and mortality” up, adapted the numbers of S1-S3 Table and added the sentence “The most common deadliest conditions were sepsis, stroke, seizures, or aspiration pneumonia, with mortality rates of 51 to 65%, while mortality of patients with heart failure was 27% on page 11.

Conclusion:

Comment:

Add a sentence on implications for policy or practice (e.g., “These findings underscore the need for improved critical care resources in rural settings”).

Response:

We thank the reviewer for this suggestion, which we added to the conclusion.

Introduction

Comment:

Contextualize the Problem: Add a sentence on the burden of non-communicable diseases (NCDs) in Tanzania, as they are a major focus of the study.

Response:

We thank the reviewer for this comment.

We added information about NCDs to the first sentence of the introduction on page 3: Critical care medicine is important to manage seriously ill patients suffering from sepsis, pneumonia, and from non-communicable diseases (NCDs) such as heart failure and stroke. Globally, NCDs killed at least 43 million people in 2021, and 73% occurred in low- and middle-income countries.

Comment:

Justify the Study: Emphasize why this study is novel (e.g., “This is the first study to describe outcomes in a rural HDU in sub-Saharan Africa”).

Response:

We added the following sentence at the end of the Introduction: “This is the first study on outcomes of patients admitted to a HDU in rural sub-Saharan Africa”. On page 3

Comment:

Clarify Objectives: Rephrase the objectives to be more specific (e.g., “To describe patient characteristics, diagnoses, and outcomes, and identify predictors of in-hospital mortality”).

Response:

We rephrased the objectives: “The objectives of this study were to describe characteristics, diagnoses, and outcomes of critically ill patients admitted to a recently implemented HDU of a referral hospital in rural Tanzania, and to describe predictors of in-hospital mortality” in the Introduction section on page 3 last 4 lines

Methods

Comment:

Study Design: Clarify the prospective nature of the study earlier in the section.

Response:

We thank the reviewer for this comment.

We included this into the first sentence in the methods section “This prospective observational single center cohort study including 491 patients was conducted at the HDU of the St. Francis Regional Referral Hospital (SFRRH), Ifakara, Tanzania” on page 3

Comment:

Data Collection: Provide more detail on how data quality was ensured (e.g., training of data collectors, use of standardized forms).

Response:

We added the following sentence in the section study procedures and data collection on page 6:

“Data were collected by clinicians working at the HDU, and responded to queries raised by the data manager and the statistician who cleaned the data. Before the start of the study, all members were trained and instructed how to fill data into the standardized electronic data collection tools”

Comment:

Statistical Analysis: Briefly explain why specific statistical methods were chosen (e.g., Cox regression for mortality predictors).

Response:

We thank the reviewer for the suggestion, we have revised the Statistical Analysis section to clarify the rationale for the selected methods. The updated section now explicitly states why each statistical approach was chosen:

• Descriptive statistics were used to summarize baseline characteristics and diagnoses, as they provide a clear and concise overview of patient demographics and clinical profiles.

• Kaplan-Meier survival curves were used to visualize mortality rates over time, which is an effective method for estimating survival probabilities.

• Cox proportional hazards regression was utilized to identify factors associated with in-hospital mortality. This method was chosen because it accounts for varying follow-up times among patients and provides adjusted hazard ratios, which allow for meaningful comparisons of risk factors.

• AUROC analysis was performed to evaluate the predictive accuracy of existing mortality scores, as it is a well-established method for assessing the discriminative ability of clinical prediction models.

These statistical approaches were selected to ensure that our findings are both robust and clinically meaningful. We have incorporated these revisions into the manuscript.

Revised Statistical Analysis Section (for Manuscript)

Statistical Analysis

Descriptive statistics were used to summarize baseline characteristics and diagnoses at admission and discharge. Kaplan-Meier survival curves were employed to estimate and visualize mortality rates over time. The association between clinical factors, risk scores, and mortality was assessed using Cox proportional hazards regression, which accounts for differences in follow-up time and provides adjusted hazard ratios to quantify the strength of associations. To evaluate the predictive performance of early warning scores, we conducted area under the receiver operating characteristic curve (AUROC) analysis, which measures the discriminative ability of each score in predicting in-hospital mortality. All statistical analyses were performed using Stata version 16. A p-value of <0.05 was considered statistically significant.

Revised Methods Section in Abstract (for Manuscript)

Descriptive analyses were performed, followed by univariate and multivariate modeling to identify predictors of in-hospital mortality. The area under the receiver operating characteristic (ROC) curve was used to assess the predictive accuracy of early warning scores.

Comment:

Ethics: Mention how oral consent was documented to address potential concerns about consent validity.

Response:

We thank the reviewer for this comment.

Written informed consent was waived by both ethic committees. If patients were conscious, they were informed that data would be used for research purposes. In case of unconsciousness, relatives were informed. However, it was not specifically documented if the patient or the relative was informed.

Results

Comments:

Clarify Key Findings: Highlight the most important results in the text (e.g., “Sepsis and stroke were associated with the highest mortality rates”).

Response:

Thank you for this comment, the section about outcomes was moved up to page 11, and the sentence “The most common deadliest conditions were sepsis, stroke, seizures, or aspiration pneumonia, with mortality rates of 51 to 65%, while mortality of patients with heart failure was 27%” was added at the beginning of the section.

Comment:

Simplify Tables: Consider merging or simplifying tables to improve readability (e.g., combine Tables 1 and 2).

Response:

We thank the reviewer for this comment. We simplified Table 1 and 2, however, we could not merge Table 1 and 2 together because table 1 shows baseline characteristics and Table 2 shows results

Comment:

Visuals: Ensure figures (e.g., ROC curves) are clearly labeled and interpretable.

Response:

We revised the labels and legends of the figures

Discussion

Comment:

Structure: Use subheadings (e.g., “Key Findings”, “Comparison with Literature”, “Implications for Practice”) to improve flow.

Response: We added subheadings in the discussion section.

Comment:

Contextualize Findings: Discuss how the high mortality rates reflect systemic challenges in rural healthcare.

Response:

Thank you for this comment, we added this on page 16: “Late presentation and high mortality reflect systemic challenges in rural healthcare: The late presentation of patients in already serious conditions is due to lack of awareness of potentially life-threatening infectious – and non-communicable diseases in the communities, limited diagnostic and therapeutical options to diagnose serious conditions in the periphery, lack of transport, and the fact that a majority of patients do not have a health insurance to cover the costs”.

Comment:

Policy Implications: Add a paragraph on how the findings can inform policy (e.g., “These results highlight the need for increased investment in rural critical care infrastructure”).

Response:

Thank you for this comment, we added this on page 16:

This highlights the importance of programmes to increase community awareness of diseases with potentially unfavourable outcomes, training of health care personnel in diagnosing infectious diseases and NCDs, implementation of referral systems, strengthening transport to specialized centers, implementing emergency departments and critical care facilities, and training of healthcare personnel in emergency medicine and critical care. Moreover, access to health insurance needs to be ameliorated, to guarantee rapid and appropriate care for patients suffering from severe acute diseases or acute deterioration of pre-existing conditions.

Comment:

Limitations: Expand on the impact of lost-to-follow-up cases and diagnostic limitations.

Response:

Thank you for this comment, we expanded this in the limitation section, page 17

Third, 9% of patients were lost to follow-up after discharge from the hospital, and patients could not be followed for a longer period to determine their post discharge outcome. However, we could analyse all patients for the endpoint of in-hospital death.

Conclusion

Comment:

Call to Action: Add a sentence on next steps (e.g., “Future studies should explore interventions to reduce mortality in rural HDUs”).

Response: Thank you for this comment, We added this sentence at the end.

Comment:

Broader Impact: Mention how the study contributes to global health equity (e.g., “This study provides critical insights into improving healthcare access in low-resource settings”).

Response:

We added “These findings underscore the need for improved critical care in low-resource rural settings

References

Comment:

Ensure all references are formatted consistently according to the journal’s guidelines.

Response:

We checked all references and formatted accordingly

Comment:

Include more references from sub-Saharan Africa to strengthen the regional context.

Response:

We added the following References in the discussion section

Beaney T, Burrell LM, Castillo RR, et al. May Measurement Month 2018: a pragmatic global screening campaign to raise awareness of blood pressure by the International Society of Hypertension. Eur Heart J 2019;40:2006-2017. doi: 10.1093/eurheartj/ehz300

WHO PEN and integrated outpatient care for severe, chronic NCDS at first referral hospitals in the African region (PEN-PLUS). 2019.

https://www.afro.who.int/publications/who-pen-and-integrated-outpatient-care-severe-chronic-ncds-first-referral-hospitals. Last access March 24th 2025

Klassen SL, Okello E, Ferrer JME, et al. Decentralization and Integration of Advanced Cardiac Care for the World's Poorest Billion Through the PEN-Plus Strategy for Severe Chronic Non-Communicable Disease. Glob Heart 2024;19:33. doi: 10.5334/gh.1313

WHO. HEARTS; Technical package for cardiovascular disease management in primary health care: Tool for the development of a consensus protocol for treatment of hypertension: technical package for cardiovascular disease management in primary health care; https://www.who.int/publications/i/item/WHO-NMH-NVI-19-8. Last access March 24th 2025

Kivuyo S, Birungi J, Okebe J, et al. Integrated management of HIV, diabetes, and hypertension in sub-Saharan Africa (INTE-AFRICA): a pragmatic cluster-randomised, controlled trial. Lancet 2023;402:1241-1250. doi: 10.1016/S0140-6736(23)01573-8

Overall Suggestions

Language and Clarity:

Comment:

• Simplify complex sentences for better readability.

• Avoid jargon and define acronyms (e.g., HDU, NEWS, qSOFA) at first use.

Response:

We checked the manuscript and revised appropriately.

Figures and Tables:

Comment:

• Ensure all figures and tables are high-quality and clearly labeled.

• Add a brief narrative summary for each table/figure in the text.

Response:

All Figures were checked and brief narrative summary was added to each table and figure in the text

Data Availability:

Comment:

• Clarify how readers can access the data (e.g., repository name, DOI).

Response:

We stated that “The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request” on page 17.

Strengths and Limitations:

Comment:

• Highlight the study’s strengths (e.g., prospective design, comprehensive data collection) more prominently.

Response:

We added this to the “Strengths Section” on page 16

Comment:

• Discuss limitations in more depth (e.g., impact of financial constraints on patient outcomes).

Response:

We added “ Second, fin

Decision Letter 1

Abraham Desta

  • Please try to indicate the line number and page while you respond for each comment

  • Consider modifying your title as “Diagnoses and Critical Care Outcomes in a Rural Tanzanian High Dependency Unit: A Prospective Cohort Study”. Because, despite the “first insights” draws attention, it can lead a bit vague and may loss academic tone. In addition, this title should directly be coherent with the background, objectives and the results as well, you have showed most common diagnoses.

  • Can you please provide the justification why you conducted multivariable analysis, as you have no sample (you have included all the study participants), or to whom are you going to infer?

  • In the statistical analysis part for the association between clinical factors, risk scores, and mortality was assessed using Cox proportional hazards regression. However, there is no information how you checked the proportional hazard assumption. You will have meaningful comparisons of risk factors if the assumptions are held.

  • Better to replace describe by identify in the “to describe predictors of in-hospital mortality”

  • You have mentioned that Kaplan-Meier survival curves to visualize mortality rate s over time in your feedback however, there is any description about this in your statistical analysis. Additionally, if you used Kaplan-Meier survival curves how do check the effect of the censoring pattern or how do you check the homogeneity of the groups?

  • Overall, you must show the methods clearly, especially your statistical analysis is not clear and try to improve this section.

  • Improve your discussion and compare it with some international findings and show the gaps clearly. Rember that you have mentioned “Critical care services in sub-Saharan Africa increased since the COVID-19 pandemic, but remain limited compared to high-income countries” in the introduction part

plosone@plos.org . When you're ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file.

  • A rebuttal letter that responds to each point raised by the academic editor and reviewer(s). You should upload this letter as a separate file labeled 'Response to Reviewers'.

  • A marked-up copy of your manuscript that highlights changes made to the original version. You should upload this as a separate file labeled 'Revised Manuscript with Track Changes'.

  • An unmarked version of your revised paper without tracked changes. You should upload this as a separate file labeled 'Manuscript'.

If you would like to make changes to your financial disclosure, please include your updated statement in your cover letter. Guidelines for resubmitting your figure files are available below the reviewer comments at the end of this letter.

If applicable, we recommend that you deposit your laboratory protocols in protocols.io to enhance the reproducibility of your results. Protocols.io assigns your protocol its own identifier (DOI) so that it can be cited independently in the future. For instructions see: https://journals.plos.org/plosone/s/submission-guidelines#loc-laboratory-protocols . Additionally, PLOS ONE offers an option for publishing peer-reviewed Lab Protocol articles, which describe protocols hosted on protocols.io. Read more information on sharing protocols at https://plos.org/protocols?utm_medium=editorial-email&utm_source=authorletters&utm_campaign=protocols .

We look forward to receiving your revised manuscript.

Kind regards,

Abraham Aregay Desta 

Academic Editor

PLOS ONE

Additional Editor Comments:

Dear Authors,

Thank you for submitting your revised manuscript entitled “First Insights into Critical Care Outcomes in a Rural Tanzanian High Dependency Unit: A Prospective Cohort Study” (Manuscript ID: PONE-D-25-05201R1) to PLOS ONE.

After careful evaluation of your submission, we appreciate the important contribution your study offers in understanding critical care delivery in a low-resource and rural setting. However, the manuscript still requires major revisions before it can be considered for publication.

Below are the primary concerns and suggestions that must be addressed:

� Please try to indicate the line number and page while you respond for each comment

� Consider modifying your title as “Diagnoses and Critical Care Outcomes in a Rural Tanzanian High Dependency Unit: A Prospective Cohort Study”. Because, despite the “first insights” draws attention, it can lead a bit vague and may loss academic tone. In addition, this title should directly be coherent with the background, objectives and the results as well, you have showed most common diagnoses.

� Can you please provide the justification why you conducted multivariable analysis, as you have no sample (you have included all the study participants), or to whom are you going to infer?

� In the statistical analysis part for the association between clinical factors, risk scores, and mortality was assessed using Cox proportional hazards regression. However, there is no information how you checked the proportional hazard assumption. You will have meaningful comparisons of risk factors if the assumptions are held.

� Better to replace describe by identify in the “to describe predictors of in-hospital mortality”

� You have mentioned that Kaplan-Meier survival curves to visualize mortality rate s over time in your feedback however, there is any description about this in your statistical analysis. Additionally, if you used Kaplan-Meier survival curves how do check the effect of the censoring pattern or how do you check the homogeneity of the groups?

� Overall, you must show the methods clearly, especially your statistical analysis is not clear and try to improve this section.

� Improve your discussion and compare it with some international findings and show the gaps clearly. Rember that you have mentioned “Critical care services in sub-Saharan Africa increased since the COVID-19 pandemic, but remain limited compared to high-income countries” in the introduction part

Please revise the manuscript based on the above feedbacks. We also encourage you to include a point-by-point response addressing each concern raised. Highlight all changes in the revised manuscript for easier evaluation.

Once we receive your revised submission, we will proceed with further editorial review. We appreciate your efforts in advancing research in global health and look forward to receiving your revised manuscript.

Sincerely,

Abraham Desta

Academic Editor

PLOS ONE

[Note: HTML markup is below. Please do not edit.]

[NOTE: If reviewer comments were submitted as an attachment file, they will be attached to this email and accessible via the submission site. Please log into your account, locate the manuscript record, and check for the action link "View Attachments". If this link does not appear, there are no attachment files.]

While revising your submission, please upload your figure files to the Preflight Analysis and Conversion Engine (PACE) digital diagnostic tool, https://pacev2.apexcovantage.com/ . PACE helps ensure that figures meet PLOS requirements. To use PACE, you must first register as a user. Registration is free. Then, login and navigate to the UPLOAD tab, where you will find detailed instructions on how to use the tool. If you encounter any issues or have any questions when using PACE, please email PLOS at figures@plos.org . Please note that Supporting Information files do not need this step.

PLoS One. 2025 Jun 18;20(6):e0324640. doi: 10.1371/journal.pone.0324640.r005

Author response to Decision Letter 2


17 Apr 2025

Point By Point reply to reviewers’ comments which was attached to the e-mail from March 19th and April 1st

A Review for Manuscript Number PONE-D-25-05201

Title

Current Title: "Diagnoses and Critical Care Outcomes in a rural Tanzanian High Dependency Unit: A Prospective Cohort Study"

Comments:

Consider making the title more concise. For example:

"Critical Care Outcomes in a Rural Tanzanian High Dependency Unit: A Prospective Cohort Study"

Alternatively, emphasize the novelty of the study:

"First Insights into Critical Care Outcomes in a Rural Tanzanian High Dependency Unit: A Prospective Cohort Study"

Response:

We thank the reviewer for this comment. We changed the title to "First Insights into Critical Care Outcomes in a Rural Tanzanian High Dependency Unit: A Prospective Cohort Study" as suggested, but changed the title to "Diagnoses and Critical Care Outcomes in a rural Tanzanian High Dependency Unit: A Prospective Cohort Study" later.

Abstract

Comments:

Background: Briefly mention the gap in literature (e.g., lack of data on HDUs in rural sub-Saharan Africa).

Response:

We thank the reviewer for this comment. We revised the background of the abstract as follows:

Background: Data on high dependency units (HDU) situated in rural sub-Saharan Africa are lacking. In this study, we describe patient’s characteristics, diagnoses, and outcomes of critically ill patients admitted to a high dependency unit of a referral hospital in rural Tanzania, and factors associated with in-hospital mortality (page 2, line 43 – 46)

Methods:

Comment:

Clarify the sample size earlier (e.g., “491 patients admitted to the HDU”).

Response: We included this information into the first sentence of the methods section on page 3, line 107.

Results:

Comment:

Highlight the most striking finding (e.g., “Mortality during HDU stay was 30%, with sepsis and stroke being the deadliest conditions”).

Response:

We thank the reviewer for this comment. We moved the section “Patient outcomes and mortality” up to page 11 line 308 ff, adapted the numbers of S1-S3 Table and added the sentence “The most common deadliest conditions were sepsis, stroke, seizures, or aspiration pneumonia, with mortality rates of 51 to 65%, while mortality of patients with heart failure was 27% on page 11 line 310-312.

Conclusion:

Comment:

Add a sentence on implications for policy or practice (e.g., “These findings underscore the need for improved critical care resources in rural settings”).

Response:

We thank the reviewer for this suggestion, which we added to the conclusion on page 18 line 525-526.

Introduction

Comment:

Contextualize the Problem: Add a sentence on the burden of non-communicable diseases (NCDs) in Tanzania, as they are a major focus of the study.

Response:

We thank the reviewer for this comment.

We added information about NCDs to the first sentence of the introduction on page 3 line 78-81: Critical care medicine is important to manage seriously ill patients suffering from sepsis, pneumonia, and from non-communicable diseases (NCDs) such as heart failure and stroke. Globally, NCDs killed at least 43 million people in 2021, and 73% occurred in low- and middle-income countries.

Comment:

Justify the Study: Emphasize why this study is novel (e.g., “This is the first study to describe outcomes in a rural HDU in sub-Saharan Africa”).

Response:

We added the following sentence at the end of the Introduction: “This is the first study on outcomes of patients admitted to a HDU in rural sub-Saharan Africa”. On page 3 line 102-103.

Comment:

Clarify Objectives: Rephrase the objectives to be more specific (e.g., “To describe patient characteristics, diagnoses, and outcomes, and identify predictors of in-hospital mortality”).

Response:

We rephrased the objectives: “The objectives of this study were to describe characteristics, diagnoses, and outcomes of critically ill patients admitted to a recently implemented HDU of a referral hospital in rural Tanzania, and to describe predictors of in-hospital mortality” in the Introduction section on page 3 line 99-102.

Methods

Comment:

Study Design: Clarify the prospective nature of the study earlier in the section.

Response:

We thank the reviewer for this comment.

We included this into the first sentence in the methods section “This prospective observational single center cohort study including 491 patients was conducted at the HDU of the St. Francis Regional Referral Hospital (SFRRH), Ifakara, Tanzania” on page 3 line 107-108.

Comment:

Data Collection: Provide more detail on how data quality was ensured (e.g., training of data collectors, use of standardized forms).

Response:

We added the following sentence in the section study procedures and data collection on page 6 line 189-192:

“Data were collected by clinicians working at the HDU, and responded to queries raised by the data manager and the statistician who cleaned the data. Before the start of the study, all members were trained and instructed how to fill data into the standardized electronic data collection tools”

Comment:

Statistical Analysis: Briefly explain why specific statistical methods were chosen (e.g., Cox regression for mortality predictors).

Response:

We thank the reviewer for the suggestion, we have revised the Statistical Analysis section to clarify the rationale for the selected methods. The updated section now explicitly states why each statistical approach was chosen:

• Descriptive statistics were used to summarize baseline characteristics and diagnoses, as they provide a clear and concise overview of patient demographics and clinical profiles.

• Kaplan-Meier survival curves were used to visualize mortality rates over time, which is an effective method for estimating survival probabilities.

• Cox proportional hazards regression was utilized to identify factors associated with in-hospital mortality. This method was chosen because it accounts for varying follow-up times among patients and provides adjusted hazard ratios, which allow for meaningful comparisons of risk factors.

• AUROC analysis was performed to evaluate the predictive accuracy of existing mortality scores, as it is a well-established method for assessing the discriminative ability of clinical prediction models.

These statistical approaches were selected to ensure that our findings are both robust and clinically meaningful. We have incorporated these revisions into the manuscript.

We revised the statistical analysis section accordingly on page 7 line 225 to 245.

Comment:

Ethics: Mention how oral consent was documented to address potential concerns about consent validity.

Response:

We thank the reviewer for this comment.

Written informed consent was waived by both ethic committees. If patients were conscious, they were informed that data would be used for research purposes. In case of unconsciousness, relatives were informed. However, it was not specifically documented if the patient or the relative was informed (page 7 line 248-252).

Results

Comments:

Clarify Key Findings: Highlight the most important results in the text (e.g., “Sepsis and stroke were associated with the highest mortality rates”).

Response:

Thank you for this comment, the section about outcomes was moved up to page 11 line 308ff, and the sentence “The most common deadliest conditions were sepsis, stroke, seizures, or aspiration pneumonia, with mortality rates of 51 to 65%, while mortality of patients with heart failure was 27%” was added at the beginning of the section page 11 line 310-312.

Comment:

Simplify Tables: Consider merging or simplifying tables to improve readability (e.g., combine Tables 1 and 2).

Response:

We thank the reviewer for this comment. We simplified Table 1 and 2, however, we could not merge Table 1 and 2 together because table 1 shows baseline characteristics and Table 2 shows results

Comment:

Visuals: Ensure figures (e.g., ROC curves) are clearly labeled and interpretable.

Response:

We revised the labels and legends of the figures.

Discussion

Comment:

Structure: Use subheadings (e.g., “Key Findings”, “Comparison with Literature”, “Implications for Practice”) to improve flow.

Response: We added subheadings in the discussion section.

Comment:

Contextualize Findings: Discuss how the high mortality rates reflect systemic challenges in rural healthcare.

Response:

Thank you for this comment, we added this on page 16 line 465-477: “Late presentation and high mortality reflect systemic challenges in rural healthcare: The late presentation of patients in already serious conditions is due to lack of awareness of potentially life-threatening infectious – and non-communicable diseases in the communities, limited diagnostic and therapeutical options to diagnose serious conditions in the periphery, lack of transport, and the fact that a majority of patients do not have a health insurance to cover the costs”.

Comment:

Policy Implications: Add a paragraph on how the findings can inform policy (e.g., “These results highlight the need for increased investment in rural critical care infrastructure”).

Response:

Thank you for this comment, we added more information on page 16 line 477-488.

Comment:

Limitations: Expand on the impact of lost-to-follow-up cases and diagnostic limitations.

Response:

Thank you for this comment, we expanded this in the limitation section, page 17 line 507-509:

“Third, 9% of patients were lost to follow-up after discharge from the hospital, and patients could not be followed for a longer period to determine their post discharge outcome. However, we could analyse all patients for the endpoint of in-hospital death”.

Conclusion

Comment:

Call to Action: Add a sentence on next steps (e.g., “Future studies should explore interventions to reduce mortality in rural HDUs”).

Response: Thank you for this comment, We added this sentence on page 18 line 527.

Comment:

Broader Impact: Mention how the study contributes to global health equity (e.g., “This study provides critical insights into improving healthcare access in low-resource settings”).

Response:

We added “These findings underscore the need for improved critical care in low-resource rural settings on page 18 line 525-526.

References

Comment:

Ensure all references are formatted consistently according to the journal’s guidelines.

Response:

We checked all references and formatted accordingly

Comment:

Include more references from sub-Saharan Africa to strengthen the regional context.

Response:

We added the following References in the discussion section

Beaney T, Burrell LM, Castillo RR, et al. May Measurement Month 2018: a pragmatic global screening campaign to raise awareness of blood pressure by the International Society of Hypertension. Eur Heart J 2019;40:2006-2017. doi: 10.1093/eurheartj/ehz300

WHO PEN and integrated outpatient care for severe, chronic NCDS at first referral hospitals in the African region (PEN-PLUS). 2019.

https://www.afro.who.int/publications/who-pen-and-integrated-outpatient-care-severe-chronic-ncds-first-referral-hospitals. Last access March 24th 2025

Klassen SL, Okello E, Ferrer JME, et al. Decentralization and Integration of Advanced Cardiac Care for the World's Poorest Billion Through the PEN-Plus Strategy for Severe Chronic Non-Communicable Disease. Glob Heart 2024;19:33. doi: 10.5334/gh.1313

WHO. HEARTS; Technical package for cardiovascular disease management in primary health care: Tool for the development of a consensus protocol for treatment of hypertension: technical package for cardiovascular disease management in primary health care; https://www.who.int/publications/i/item/WHO-NMH-NVI-19-8. Last access March 24th 2025

Kivuyo S, Birungi J, Okebe J, et al. Integrated management of HIV, diabetes, and hypertension in sub-Saharan Africa (INTE-AFRICA): a pragmatic cluster-randomised, controlled trial. Lancet 2023;402:1241-1250. doi: 10.1016/S0140-6736(23)01573-8

Baker T, Scribante J, Elhadi M, Ademuyiwa A, Osinaike B, Owoo C, et al. The African Critical Illness Outcomes Study (ACIOS): a point prevalence study of critical illness in 22 nations in Africa. The Lancet. 2025;405: 715–724. doi:10.1016/S0140-6736(24)02846-0

Overall Suggestions

Language and Clarity:

Comment:

• Simplify complex sentences for better readability.

• Avoid jargon and define acronyms (e.g., HDU, NEWS, qSOFA) at first use.

Response:

We checked the manuscript and revised appropriately.

Figures and Tables:

Comment:

• Ensure all figures and tables are high-quality and clearly labeled.

• Add a brief narrative summary for each table/figure in the text.

Response:

All Figures were checked and brief narrative summary was added to each table and figure in the text

Data Availability:

Comment:

• Clarify how readers can access the data (e.g., repository name, DOI).

Response:

We added “The datasets used and/or analysed during the current study are available under https://zenodo.org/records/15177213 with restricted access” on page 18 line 533-53

Strengths and Limitations:

Comment:

• Highlight the study’s strengths (e.g., prospective design, comprehensive data collection) more prominently.

Response:

We added this to the “Strengths Section” on page 17 line 491-496

Comment:

• Discuss limitations in more depth (e.g., impact of financial constraints on patient outcomes).

Response:

We added “ Second, financial constraints limited the use of available diagnostic and therapeutic tools such as CT and hemodialysis. This might have a negative impact on patients outcomes.” To the limitation section” on page 17 line 504-507.

Point by Point reply to additional points raised in the e-mail from April 1st 2025

5. Review Comments to the Author

Reviewer #1:

Comments:

The study addresses an important gap in the literature by providing the first detailed description of diagnoses and outcomes in a rural high dependency unit (HDU) in sub-Saharan Africa.

The methodology is robust, with a prospective cohort design, clear inclusion/exclusion criteria, and comprehensive data collection.

The findings are significant, highlighting high mortality rates and predictors of in-hospital mortality, which have important implications for critical care in low-resource settings.

Response:

We thank the reviewer very much for this positive comments

Areas for Improvement:

Comments:

Clarity and Structure: Some sections (e.g., Results, Discussion) could be streamlined for better readability.

Contextualization: The paper would benefit from a stronger emphasis on the broader implications of the findings for policy and practice in rural healthcare.

Limitations: While limitations are acknowledged, they could be discussed in more depth, particularly regarding the impact of financial constraints and diagnostic limitations on patient outcomes.

Language: Minor grammatical and stylistic improvements are needed to enhance clarity and flow.

Response:

We thank the reviewer for this comments. We restructured the result and discussion sections and revised the manuscript accordingly as outlined above. We checked and corrected the language in the manuscript.

Overall Assessment:

Comment:

The paper is scientifically sound and makes a valuable contribution to the field. The required revisions are relatively minor and primarily focus on improving clarity, structure, and contextualization.

Response: We thank the reviewer for reviewing this manuscript

Reviewer #2: The study addresses an important gap in understanding critically ill patient outcomes in rural HDUs, making it highly relevant for clinicians and policymakers. Here are my recommendations:

Comment:

1. The introduction focuses heavily on HDU setup rather than framing a clear research gap.

Response:

We thank the reviewer for this comment: We clarified research gab and objectives in the introduction section (page 3 line 98-102.

Comment:

2. The objective should be explicitly stated earlier in the introduction and aligned more clearly with the research question.

Response:

We stated the objectives at the end of the introduction section more clearly on page 3 line 99-102.

Comment:

3. The methods section needs more focus on patient

Decision Letter 2

Abraham Desta

Dear Dr. Rohacek,

Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process.

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We look forward to receiving your revised manuscript.

Kind regards,

Abraham Aregay Desta, MSc.

Academic Editor

PLOS ONE

Journal Requirements:

Please review your reference list to ensure that it is complete and correct. If you have cited papers that have been retracted, please include the rationale for doing so in the manuscript text, or remove these references and replace them with relevant current references. Any changes to the reference list should be mentioned in the rebuttal letter that accompanies your revised manuscript. If you need to cite a retracted article, indicate the article’s retracted status in the References list and also include a citation and full reference for the retraction notice.

Additional Editor Comments:

PONE-D-25-05201R2

Diagnoses and Critical Care Outcomes in a Rural Tanzanian High Dependency Unit: A Prospective Cohort Study

PLOS ONE

Dear Authors,

Thank you for submitting the 2nd round of the revised version of your manuscript entitled "Diagnoses and Critical Care Outcomes in a Rural Tanzanian High Dependency Unit: A Prospective Cohort Study" to PLOS One. We appreciate the time and effort you have invested in addressing the comments provided by the reviewers’ and editor during the previous rounds.

after carefully reviewing your updated manuscript and your detailed comments, your work is almost ready for publication. However, we kindly ask that you to address a few items before we move forward with acceptance. These are mostly clarifications or editorial adjustments that should be straightforward to address.

We kindly ask that you:

• Be transparent the scope of the generalizability as far as you included all the subjects in the sampling

• Make uniform editing throughout the manuscript such as line spacing and others

• Abstract should be a maximum of 300 words

• Revise the manuscript according to the PLOS One guideline

• Ensure to provide adequate response to all feedback given by the reviewers and editor

• Revise your manuscript considering the comments

• Provide a brief point-by-point response to each comment

• Highlight all changes made in the manuscript

Please submit your revised manuscript within 2 weeks. However, if you need additional time, do not hesitate to contact us.

We look forward to receiving your revised submission and moving forward with publication.

Regards,

Abraham Aregay Desta, MSc, PhD candidate.

PLOS ONE Editor

[Note: HTML markup is below. Please do not edit.]

[NOTE: If reviewer comments were submitted as an attachment file, they will be attached to this email and accessible via the submission site. Please log into your account, locate the manuscript record, and check for the action link "View Attachments". If this link does not appear, there are no attachment files.]

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PLoS One. 2025 Jun 18;20(6):e0324640. doi: 10.1371/journal.pone.0324640.r007

Author response to Decision Letter 3


25 Apr 2025

To April 25th 2025

Dr Abraham Aregay Desta

Editor

PLOS one

Dear Dr Desta

We thank you and the reviewers very much for the review of our manuscript

PONE-D-25-05201

"Diagnoses and Critical Care Outcomes in a rural Tanzanian High Dependency Unit: A Prospective Cohort Study"

We revised the manuscript according to the valuable comments of the reviewers and responded in a point-by-point reply below.

We uploaded a clean version of the manuscript and a version with track changes.

We uploaded the minimal dataset to https://zenodo.org/records/15177213

Martin Rohacek received funds from the Else Kröner Fresenius Foundation, Germany, Julie Rossier received funds from the Freiwillige Akademische Gesellschaft Basel, Switzerland. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Thank you very much for evaluating our revised version of the manuscript.

Sincerely yours

PD Dr med Martin Rohacek

Swiss TPH

Kreuzstrasse 2

4123 Allschwil

Switzerland

University of Basel, Switzerland

Ifakara Health Institute, Tanzania

martin.rohacek@swisstph.ch, mrohacek@ihi.or.tz

Point by Point reply to editor’s comments in the e-mail from April 24th

Thank you for submitting the 2nd round of the revised version of your manuscript entitled "Diagnoses and Critical Care Outcomes in a Rural Tanzanian High Dependency Unit: A Prospective Cohort Study" to PLOS One. We appreciate the time and effort you have invested in addressing the comments provided by the reviewers’ and editor during the previous rounds.

after carefully reviewing your updated manuscript and your detailed comments, your work is almost ready for publication. However, we kindly ask that you to address a few items before we move forward with acceptance. These are mostly clarifications or editorial adjustments that should be straightforward to address.

We kindly ask that you:

Comment: Be transparent the scope of the generalizability as far as you included all the subjects in the sampling

Response: We thank the editor for this comment. While inclusion of all subjects eliminates sampling error, it does not guarantee generalizability to other populations. We revised line 431-432 on page 24 as follows: Last, this was a single centre study, and generalisability of these findings to populations living in other settings might be limited.

Comment: Make uniform editing throughout the manuscript such as line spacing and others

Response: We double spaced the whole manuscript and edited the font size according to PLOS one guidelines

Comment: Abstract should be a maximum of 300 words

Response: We shortened the Abstract to 299 words

Comment: Revise the manuscript according to the PLOS One guideline

Response: We revised the manuscript according to PLOS one guidelines

Comment Ensure to provide adequate response to all feedback given by the reviewers and editor

Response: We responded to all points raised in the point by point reply and revised the manuscript accordingly

Comment Revise your manuscript considering the comments

Response: The manuscript has been revised according to the comments of reviewers and editor

Comment: Provide a brief point-by-point response to each comment

Response: We provided a point by point response to each comment

Comment: Highlight all changes made in the manuscript

Response: We uploaded a tracked changed version

Comment: Please submit your revised manuscript within 2 weeks. However, if you need additional time, do not hesitate to contact us.

We look forward to receiving your revised submission and moving forward with publication.

Response: Thank you for reviewing our manuscript

Point By Point reply to reviewers’ comments which was attached to the e-mail from March 19th and April 1st

A Review for Manuscript Number PONE-D-25-05201

"Diagnoses and outcomes of critically ill patients admitted to a high dependency unit of a rural referral hospital in Tanzania: A prospective cohort study"

Title

Current Title: Diagnoses and outcomes of critically ill patients admitted to a high dependency unit of a rural referral hospital in Tanzania: A prospective cohort study

Comments:

Consider making the title more concise. For example:

"Critical Care Outcomes in a Rural Tanzanian High Dependency Unit: A Prospective Cohort Study"

Alternatively, emphasize the novelty of the study:

"First Insights into Critical Care Outcomes in a Rural Tanzanian High Dependency Unit: A Prospective Cohort Study"

Response:

We thank the reviewer for this comment. We changed the title to "First Insights into Critical Care Outcomes in a Rural Tanzanian High Dependency Unit: A Prospective Cohort Study" as suggested, but changed the title to "Diagnoses and Critical Care Outcomes in a rural Tanzanian High Dependency Unit: A Prospective Cohort Study" later.

Abstract

Comments:

Background: Briefly mention the gap in literature (e.g., lack of data on HDUs in rural sub-Saharan Africa).

Response:

We thank the reviewer for this comment. We revised the background of the abstract as follows:

Background: Data on rural sub-Saharan African high-dependency units (HDU) are lacking. We describe patient’s characteristics, diagnoses, and outcomes of patients admitted to a Tanzanian HDU, and identified factors associated with in-hospital mortality.

(page 2, line 41 – 43)

Methods:

Comment:

Clarify the sample size earlier (e.g., “491 patients admitted to the HDU”).

Response: We included this information into the first sentence of the methods section on page 4, line 95.

Results:

Comment:

Highlight the most striking finding (e.g., “Mortality during HDU stay was 30%, with sepsis and stroke being the deadliest conditions”).

Response:

We thank the reviewer for this comment. We moved the section “Patient outcomes and mortality” up to page 16 line 267 ff, adapted the numbers of S1-S3 Table and added the sentence “The most common deadliest conditions were sepsis, stroke, seizures, or aspiration pneumonia, with mortality rates of 51 to 65%, while mortality of patients with heart failure was 27% on page 16 line 269-271.

Conclusion:

Comment:

Add a sentence on implications for policy or practice (e.g., “These findings underscore the need for improved critical care resources in rural settings”).

Response:

We thank the reviewer for this suggestion, which we added to the conclusion on page 24 line 439-440.

Introduction

Comment:

Contextualize the Problem: Add a sentence on the burden of non-communicable diseases (NCDs) in Tanzania, as they are a major focus of the study.

Response:

We thank the reviewer for this comment.

We added information about NCDs to the first sentence of the introduction on page 3 line 66-69: Critical care medicine is important to manage seriously ill patients suffering from sepsis, pneumonia, and from non-communicable diseases (NCDs) such as heart failure and stroke. Globally, NCDs killed at least 43 million people in 2021, and 73% occurred in low- and middle-income countries.

Comment:

Justify the Study: Emphasize why this study is novel (e.g., “This is the first study to describe outcomes in a rural HDU in sub-Saharan Africa”).

Response:

We added the following sentence at the end of the Introduction: “This is the first study on outcomes of patients admitted to a HDU in rural sub-Saharan Africa”. On page 3 line 102-103.

Comment:

Clarify Objectives: Rephrase the objectives to be more specific (e.g., “To describe patient characteristics, diagnoses, and outcomes, and identify predictors of in-hospital mortality”).

Response:

We rephrased the objectives: “The objectives of this study were to describe characteristics, diagnoses, and outcomes of critically ill patients admitted to a recently implemented HDU of a referral hospital in rural Tanzania, and to describe predictors of in-hospital mortality” in the Introduction section on page 3 line 90-91.

Methods

Comment:

Study Design: Clarify the prospective nature of the study earlier in the section.

Response:

We thank the reviewer for this comment.

We included this into the first sentence in the methods section “This prospective observational single center cohort study including 491 patients was conducted at the HDU of the St. Francis Regional Referral Hospital (SFRRH), Ifakara, Tanzania” on page 4 line 95-96.

Comment:

Data Collection: Provide more detail on how data quality was ensured (e.g., training of data collectors, use of standardized forms).

Response:

We added the following sentence in the section study procedures and data collection on page 7 line 163-166:

“Data were collected by clinicians working at the HDU, and responded to queries raised by the data manager and the statistician who cleaned the data. Before the start of the study, all members were trained and instructed how to fill data into the standardized electronic data collection tools”

Comment:

Statistical Analysis: Briefly explain why specific statistical methods were chosen (e.g., Cox regression for mortality predictors).

Response:

We thank the reviewer for the suggestion, we have revised the Statistical Analysis section to clarify the rationale for the selected methods. The updated section now explicitly states why each statistical approach was chosen:

• Descriptive statistics were used to summarize baseline characteristics and diagnoses, as they provide a clear and concise overview of patient demographics and clinical profiles.

• Kaplan-Meier survival curves were used to visualize mortality rates over time, which is an effective method for estimating survival probabilities.

• Cox proportional hazards regression was utilized to identify factors associated with in-hospital mortality. This method was chosen because it accounts for varying follow-up times among patients and provides adjusted hazard ratios, which allow for meaningful comparisons of risk factors.

• AUROC analysis was performed to evaluate the predictive accuracy of existing mortality scores, as it is a well-established method for assessing the discriminative ability of clinical prediction models.

These statistical approaches were selected to ensure that our findings are both robust and clinically meaningful. We have incorporated these revisions into the manuscript.

We revised the statistical analysis section accordingly on page 8 line 195-215.

Comment:

Ethics: Mention how oral consent was documented to address potential concerns about consent validity.

Response:

We thank the reviewer for this comment.

Written informed consent was waived by both ethic committees. If patients were conscious, they were informed that data would be used for research purposes. In case of unconsciousness, relatives were informed. However, it was not specifically documented if the patient or the relative was informed (page 9 line 218-222).

Results

Comments:

Clarify Key Findings: Highlight the most important results in the text (e.g., “Sepsis and stroke were associated with the highest mortality rates”).

Response:

Thank you for this comment, the section about outcomes was moved up to page 16 line 267ff, and the sentence “The most common deadliest conditions were sepsis, stroke, seizures, or aspiration pneumonia, with mortality rates of 51 to 65%, while mortality of patients with heart failure was 27%” was added at page 16 line 269-271

Comment:

Simplify Tables: Consider merging or simplifying tables to improve readability (e.g., combine Tables 1 and 2).

Response:

We thank the reviewer for this comment. We simplified Table 1 and 2, however, we could not merge Table 1 and 2 together because table 1 shows baseline characteristics and Table 2 shows results

Comment:

Visuals: Ensure figures (e.g., ROC curves) are clearly labelled and interpretable.

Response:

We revised the labels and legends of the figures.

Discussion

Comment:

Structure: Use subheadings (e.g., “Key Findings”, “Comparison with Literature”, “Implications for Practice”) to improve flow.

Response: We added subheadings in the discussion section.

Comment:

Contextualize Findings: Discuss how the high mortality rates reflect systemic challenges in rural healthcare.

Response:

Thank you for this comment, we added this on page 23 line 389-394 “Late presentation and high mortality reflect systemic challenges in rural healthcare: The late presentation of patients in already serious conditions is due to lack of awareness of potentially life-threatening infectious – and non-communicable diseases in the communities, limited diagnostic and therapeutical options to diagnose serious conditions in the periphery, lack of transport, and the fact that a majority of patients do not have a health insurance to cover the costs”.

Comment:

Policy Implications: Add a paragraph on how the findings can inform policy (e.g., “These results highlight the need for increased investment in rural critical care infrastructure”).

Response:

Thank you for this comment, we added more information on page 23 line 394-405.

Comment:

Limitations: Expand on the impact of lost-to-follow-up cases and diagnostic limitations.

Response:

Thank you for this comment, we expanded this in the limitation section, page 24 line 425-427:

“Third, 9% of patients were lost to follow-up after discharge from the hospital, and patients could not be followed for a longer period to determine their post discharge outcome. However, we could analyse all patients for the endpoint of in-hospital death”.

Conclusion

Comment:

Call to Action: Add a sentence on next steps (e.g., “Future studies should explore interventions to reduce mortality in rural HDUs”).

Response: Thank you for this comment, We added this sentence on page 25 line 441.

Comment:

Broader Impact: Mention how the study contributes to global health equity (e.g., “This study provides critical insights into improving healthcare access in low-resource settings”).

Response:

We added “These findings underscore the need for improved critical care in low-resource rural settings on page 18 line 439-440.

References

Comment:

Ensure all references are formatted consistently according to the journal’s guidelines.

Response:

We checked all references and formatted accordingly

Comment:

Include more references from sub-Saharan Africa to strengthen the regional context.

Response:

We added the following References in the discussion section

Beaney T, Burrell LM, Castillo RR, et al. May Measurement Month 2018: a pragmatic global screening campaign to raise awareness of blood pressure by the International Society of Hypertension. Eur Heart J 2019;40:2006-2017. doi: 10.1093/eurheartj/ehz300

WHO PEN and integrated outpatient care for severe, chronic NCDS at first referral hospitals in the African region (PEN-PLUS). 2019.

https://www.afro.who.int/publications/who-pen-and-integrated-outpatient-care-severe-chronic-ncds-first-referral-hospitals. Last access March 24th 2025

Klassen SL, Okello E, Ferrer JME, et al. Decentralization and Integration of Advanced Cardiac Care for the World's Poorest Billion Through the PEN-Plus Strategy for Severe Chronic Non-Communicable Disease. Glob Heart 2024;19:33. doi: 10.5334/gh.1313

WHO. HEARTS; Technical package for cardiovascular disease management in primary health care: Tool for the development of a consensus protocol for treatment of hypertension: technical package for cardiovascular disease management in primary health care; https://www.who.int/publications/i/item/WHO-NMH-NVI-19-8. Last access March 24th 2025

Kivuyo S, Birungi J, Okebe J, et al. Integrated management of HIV, diabetes, and hypertension in sub-Saharan Africa (INTE-AFRICA): a pragmatic cluster-randomised, controlled trial. Lancet 2023;402:1241-1250. doi: 10.1016/S0140-6736(23)01573-8

Baker T, Scribante J, Elhadi M, Ademuyiwa A, Osinaike B, Owoo C, et al. The African Critical Illness Outcomes Study (ACIOS): a point prevalence study of critical illness in 22 nations in Africa. The Lancet. 2025;405: 715–724. doi:10.1016/S0140-6736(24)02846-0

Overall Suggestions

Language and Clarity:

Comment:

• Simplify complex sentences for better readability.

• Avoid jargon and define acronyms (e.g., HDU,

Decision Letter 3

Abraham Desta

Diagnoses and Critical Care Outcomes in a Rural Tanzanian High Dependency Unit: A Prospective Cohort Study

PONE-D-25-05201R3

Dear Authors,

We’re pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it meets all outstanding technical requirements.

Within one week, you’ll receive an e-mail detailing the required amendments. When these have been addressed, you’ll receive a formal acceptance letter and your manuscript will be scheduled for publication.

An invoice will be generated when your article is formally accepted. Please note, if your institution has a publishing partnership with PLOS and your article meets the relevant criteria, all or part of your publication costs will be covered. Please make sure your user information is up-to-date by logging into Editorial Manager at Editorial Manager®  and clicking the ‘Update My Information' link at the top of the page. If you have any questions relating to publication charges, please contact our Author Billing department directly at authorbilling@plos.org.

If your institution or institutions have a press office, please notify them about your upcoming paper to help maximize its impact. If they’ll be preparing press materials, please inform our press team as soon as possible -- no later than 48 hours after receiving the formal acceptance. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information, please contact onepress@plos.org.

Kind regards,

Abraham Aregay Desta

Academic Editor

PLOS ONE

Acceptance letter

Abraham Desta

PONE-D-25-05201R3

PLOS ONE

Dear Dr. Rohacek,

I'm pleased to inform you that your manuscript has been deemed suitable for publication in PLOS ONE. Congratulations! Your manuscript is now being handed over to our production team.

At this stage, our production department will prepare your paper for publication. This includes ensuring the following:

* All references, tables, and figures are properly cited

* All relevant supporting information is included in the manuscript submission,

* There are no issues that prevent the paper from being properly typeset

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Associated Data

    This section collects any data citations, data availability statements, or supplementary materials included in this article.

    Supplementary Materials

    S1 Table. Association of clinical scores with in-hospital mortality among patients in the high-dependency unit.

    (DOCX)

    pone.0324640.s001.docx (15.9KB, docx)
    S2 Table. Diagnostic tests performed on patients in the high-dependency unit.

    (DOCX)

    pone.0324640.s002.docx (15.1KB, docx)
    S3 Table. Treatment and medication among patients in the high-dependency unit.

    (DOCX)

    pone.0324640.s003.docx (15.9KB, docx)
    Attachment

    Submitted filename: A Review for Manuscript Number PONE.docx

    pone.0324640.s004.docx (16.9KB, docx)

    Data Availability Statement

    All relevant data are within the paper and its Supporting information. The datasets used and/or analyzed during the current study are available with restricted access from Zenodo at https://zenodo.org/records/15177213.


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