Prevalence and associated factors of impaired renal function and albuminuria among adult patients admitted to a hospital in Northeast Ethiopia

Temesgen Fiseha; Ermiyas Ahmed; Semagn Chalie; Angesom Gebreweld

doi:10.1371/journal.pone.0246509

. 2021 Feb 4;16(2):e0246509. doi: 10.1371/journal.pone.0246509

Prevalence and associated factors of impaired renal function and albuminuria among adult patients admitted to a hospital in Northeast Ethiopia

Temesgen Fiseha ^1,^*, Ermiyas Ahmed ¹, Semagn Chalie ¹, Angesom Gebreweld ²

Editor: Bamidele O Tayo³

PMCID: PMC7861367 PMID: 33539455

Abstract

Background

Chronic kidney disease (CKD) is increasingly common in hospitalized patients and is associated with increased risk for in-hospital morbidity and mortality. However, data regarding the prevalence of CKD in the African hospitalized patient population are limited. We therefore examined the prevalence and associated factors of impaired renal function and albuminuria among adult patients admitted to the internal medicine wards of a hospital in Northeast Ethiopia.

Methods

A cross-sectional study was conducted from January 1 to April 30, 2020 at the inpatient settings of Dessie referral hospital. Data on demographics and medical history were obtained, and serum creatinine and albuminuria were analyzed. Estimated glomerular filtration rate (eGFR) was calculated using the Modification of Diet in Renal Disease (MDRD) equation. CKD was defined as impaired eGFR (<60 ml/min/1.73m²) and/or albuminuria. Univariate and multivariable analysis were conducted to determine factors associated with impaired eGFR and albuminuria.

Results

A total of 369 patients were included in this study. The prevalence of impaired eGFR was 19.0% (95%CI: 15.2%–23.2%) and albuminuria was 30.9% (95%CI: 26.3%–35.7%). Overall, 33.9% (95%CI: 29.2%–38.9%) of the patients had some degree of CKD, but only 21.6% (95%CI: 15.1%–29.4%) were aware of their renal disease. In multivariable analysis, older age, a family history of kidney disease, diabetes, hypertension and HIV were independently associated with both impaired eGFR and albuminuria while male gender was independently associated with only albuminuria.

Conclusions

CKD is common in adult patients admitted to the internal medicine wards, but only few patients are aware of their condition. These findings highlight the need for feasible approaches to timely identify kidney disease and raise awareness on the importance of detection and early intervention in the inpatient settings.

Introduction

Chronic kidney disease (CKD), typically defined by impaired estimated glomerular filtration rate (eGFR) and albuminuria, is a major global public health problem [1]. CKD affects 11 to 13% of the population worldwide and is an independent risk factor for cardiovascular and all-cause mortality [2, 3]. It has been also shown to be a risk factor for cardiovascular disease and is associated with adverse outcomes, including hospitalizations and progression to kidney failure, which have enormous impacts on the quality of life and health care system [4, 5]. Early detection, intervention and management of patients with CKD is therefore crucial to reduce the morbidity and mortality, delay the progression of disease and improve health outcomes.

CKD is increasingly common in hospital inpatient settings, occurring in up to 39% of hospitalized patients [6]. In hospitalized patients, CKD has been found to be associated with an increased risk for length of hospital stay, acute renal failure, in-hospital mortality and health-related expenditure [7–10]. The presence of CKD has been also shown to be a risk factor for adverse outcomes, including drug toxicity, dose adjustment issues, infections and poor functional status [11–14]. Hospitalized patients with CKD also have a substantial burden of comorbidities, including underlying diseases and consequences of CKD such as diabetes, hypertension, anemia, and bone and mineral disease, that contribute to increase the risk for adverse outcomes and makes the management of these patients potentially challenging [15–17]. Early detection is therefore desirable because effective interventions can then be implemented to reduce the risk of in-hospital morbidity and mortality associated with CKD, and improve outcomes.

Although hospitalization represents an opportunity to identify existing CKD and educate patients earlier in the course of their kidney disease, CKD is often unrecognized and most patients with kidney disease are unaware of their condition [18–21]. Furthermore, the attention paid to this condition is poor [18, 22]. However, despite the high prevalence of CKD and its resulting increased in-hospital morbidity and mortality, little is known about the prevalence of CKD in the African hospitalized patients. The few available studies among hospitalized patients in Africa have reported CKD prevalence of 13.5% in Botswana [23], 38.6% in Kenya [6] and 57.3% in Uganda [24]. Understanding the burden and associated risk factors of CKD based on relevant indicators of kidney disease is important for making relevant decisions regarding identification and prevention of the disease in this resource limited region, where access to renal replacement therapy is strictly rationed [25]. We therefore examined the prevalence and awareness of CKD and identified the factors associated with impaired eGFR and albuminuria among adult patients admitted to the internal medicine wards of a hospital in Northeast Ethiopia.

Methods

Study design, setting and population

This cross-sectional study was conducted from January 1 to April 30, 2020 at the inpatient settings of Dessie referral hospital (DRH), Northeast Ethiopia. DRH is a 597 bed medical center, and serves as a tertiary referral hospital for South Wollo and surrounding Zones of Amhara regional state. The hospital provides 350,000 outpatient and 23,780 inpatient services annually. Patients were eligible for the study if they were aged 18 years or older, were admitted to the internal medicine wards for at least 48 hours, and had serum creatinine measurements at admission. Patients admitted to intensive care units, patients with possibility of functional proteinuria and patients who had evidence of factors that can cause acute kidney injury or those on medical diagnosis of renal failure were excluded. A total of 369 patients who fulfilled the above criteria were consecutively included for the final analysis. The sample size was calculated on the basis of the following assumptions: use of the single proportion formula [26] with a 95% confidence level; 5% margin of error; 32.7% prevalence of impaired eGFR [27]; and 10% non-response rate. The study was approved by the Institutional Review Board of College of Medicine and Health Sciences, Wollo University (# 135/13/12). Written informed consent was obtained from each study participants after explaining the purpose and procedures of the study. Clinical information obtained in this study was communicated to attending physicians so that they could be used for clinical care.

Data collection and measurements

Data were collected from patients and their medical records using structured questionnaire which was developed in English with modification from Screening and Early Evaluation of Kidney Disease (SEEK) study [28]. The questionnaire was carefully designed and pre-tested on 5% of study population and, based on the results, revision was made to minimize errors. Patients were interviewed to collect data on socio-demographic characteristics, family history of kidney disease and lifestyle behaviors. Trained and certified personnel abstracted data on comorbidities, including diabetes mellitus, hypertension, cardiovascular disease (coronary artery disease, myocardial infarction, heart failure, peripheral vascular disease, and old stroke), diseases of the respiratory system, HIV/AIDS and all others from admission medical records. All comorbidities were defined as present if documented in the medical records. Blood pressure was measured with a mercury sphygmomanometer after the patients had rested for 5–10 min in the sitting position. Three readings were taken 5 min apart, and the mean of these readings was recorded. A fasting venous blood sample and spot urine specimen were collected from each patient in the morning and then transported to the hospital inpatient laboratory. Serum creatinine was measured using the Jaffe kinetic method with calibration traceable to isotope dilution mass spectrometry (IDMS). Estimated glomerular filtration rate (eGFR) was calculated using the Modification of Diet in Renal Disease (MDRD) equation [29]. Impaired renal function was defined as eGFR <60 ml/min/1.73 m². Albuminuria was determined using rapid test strips (COMBINA 11S, Human) and was defined as a dipstick of ≥1+. All laboratory measurements were done following the standard procedures recommended by the manufacturer. CKD was defined as the presence of impaired eGFR (<60 ml/min/1.73 m²) and/or albuminuria. The CKD stages were classified according to the NKF Kidney Disease Outcomes Quality Initiative (KDOQI) guideline [30]: stage 1, eGFR ≥90 ml/min/1.73 m² with albuminuria; stage 2, eGFR 60–89.9 ml/min/1.73 m² with albuminuria, and stages 3, 4 and 5 as eGFR 30–59.9, 15–29.9 and < 15 ml/min/1.73 m², respectively. Stage 3 was further classified into 3a (45–59.9 ml/min/1.73 m²) and 3b (30–44.9 ml/min/1.73 m²) [31]. CKD awareness among patients with kidney disease was defined as a ‘yes’ response the question “Has a doctor or other health care provider ever told you that you have a failing kidney or kidney disease (excluding kidney stones, bladder infections, or incontinence)?”.

Statistical analysis

Data collected were entered into EpiData version 3.1 software (Epidata Association, Odense, Denmark) and analyzed using SPSS version 20 software (SPSS Inc., Chicago, IL, USA). We derived means for continuous variables and proportions to describe the characteristics of the study patients as well as the prevalence of impaired renal function, albuminuria and CKD. Comparisons of patients according to the presence of impaired renal function or albuminuria were performed using Chi-square (x²) test and t-test, where appropriate. To determine which factors were associated with the presence of impaired renal function or albuminuria, univariate analysis was conducted with age, sex, residence, education, smoking status, family history of kidney disease, presence of diabetes, hypertension, cardiovascular diseases, respiratory diseases and HIV/AIDS, and systolic and diastolic BP as variables. Variables that were found to be significant in univariate analysis (P < 0.25) were included in the multivariable backwards stepwise logistic regression model to identify factors independently associated with impaired renal function or albuminuria. P-value < 0.05 was used to indicate statistical significance.

Results

Demographic and clinical characteristics of the study patients

A total of 369 patients admitted to the internal medicine wards were included in this study. Table 1 shows the demographic and clinical characteristics of the study patients. The mean (± SD) age was 48.8 ± 17.9 years, and 192 (52.0%) were females. Most of the patients were below 60 years of age (65.0%), and 35.0% were ≥ 60 years old. Two hundred and thirty-nine (64.8%) were rural residents and 198 (53.7%) had no formal education. About 8% (7.9%) of patients were current smokers and about 11% (11.1%) were HIV patients. The main clinical diagnosis for admission was diabetes mellitus (25.2%), followed by hypertension (24.9%) and cardiovascular diseases (22.5%). The mean systolic and diastolic blood pressure (BP) of the patients were 126.6 ± 22.7 and 79.1 ± 12.3 mm Hg, respectively. The mean serum creatinine level was 1.22 ± 0.7 mg/dl, and 51 (13.8%) patients had values > 1.5 mg/dl. The mean eGFR was 86.7 ± 39.8 ml/min/ 1.73 m².

Table 1. Demographic and clinical characteristics of the study patients (n = 369).

Characteristics	Category
Age (year), mean ± SD		48.8 ± 17.9
Age group, n (%)	18–39 years	119 (32.2)
	40–59 years	121 (32.8)
	≥ 60 years	129 (35.0)
Sex, n (%)	Male	177 (48.0)
	Female	192 (52.0)
Residence, n (%)	Urban	130 (35.2)
	Rural	239 (64.8)
Education, n (%)	No formal education	198 (53.7)
	Grade 1–8	91 (24.7)
	Grade 9–12	52 (14.1)
	College & above	28 (7.6)
Smoking, n (%)	Yes	29 (7.9)
	No	340 (92.1)
HIV status, n (%)	Yes	42 (11.4)
	No	327 (88.6)
History of DM, n (%)	Yes	93 (25.2)
	No	277 (74.8)
History of HTN, n (%)	Yes	92 (24.9)
	No	278 (75.1)
History of CVD, n (%)	Yes	83 (22.5)
	No	286 (77.5)
Systolic BP (mmHg), mean ± SD		126.6 ± 22.7
Diastolic BP (mmHg), mean ± SD		79.1 ± 12.3
Serum Creatinine (mg/dl), mean ± SD		1.22 ± 0.7
eGFR (ml/min/1.73 m²), mean ± SD		86.7 ± 39.8

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Prevalence of indicators of kidney disease

The prevalence of impaired eGFR (< 60 ml/min/1.73 m²) was 19.0% (95% CI: 15.2%–23.2%) and that of albuminuria was 30.9% (95% CI: 26.3%–35.7%). The prevalence of both impaired eGFR and albuminuria increased with age (P < 0.001; Fig 1), and were significantly higher in the older patients (age ≥60 years; 37.2% and 45.0%) than in the younger adults (9.2% and 23.3%, respectively; both P < 0.001). The prevalence of impaired eGFR was not different between men (18.1%) and women (19.8%; P = 0.675), while that of albuminuria was highest in men than women (37.9% vs. 24.5%; P = 0.005).

Fig 1 — Abbreviations: eGFR, estimated glomerular filtration rate; CKD, chronic kidney disease.

Prevalence and awareness of CKD

Overall, 33.9% (95% CI: 29.2%–38.9%) of the patients had some degree of CKD, i.e. they had either a significantly impaired eGFR (<,60 ml/min/1.73 m²) and/or albuminuria. Classified by disease stage, 11 (3.0%) patients had stage 1, 44 (11.9%) had stage 2, 35 (9.5%) had stage 3a, 15 (4.1%) had stage 3b, 14 (3.8%) had stage 4 and 6 (1.6%) had stage 5 CKD. It was noted that none of the patients at stage 5 CKD received dialysis during their hospitalization. There was a graded trend for increasing CKD prevalence with advancing age (P < 0.001; Fig 1). The prevalence of CKD was highest among older patients (50.4%) compared with younger patients (25.0%, P < 0.001), and it was different in men and women (39.5% vs. 28.6%; P = 0.027).

Awareness of CKD was 21.6% (95% CI: 15.1%–29.4%) among patients found to have any degree of kidney disease (i.e., impaired eGFR and/or albuminuria). Awareness of CKD vary significantly by disease stage, which was 9.1%, 11.4%, 17.1%, 33.3%, 42.9% and 66.7% among patients with stage 1, stage 2, stage 3a, stage 3b, stage 4 and stage 5 CKD, respectively (P = 0.005) (Fig 2). Of 70 patients with impaired eGFR (< 60 ml/min/ 1.73 m²; stages 3–5 of CKD), 30.0% reported having kidney disease. Awareness of kidney disease was 23.7% among all the patients with albuminuria.

Fig 2 — Abbreviations: CKD, chronic kidney disease.

Factors associated with impaired renal function and albuminuria

Univariate and multivariable analysis were conducted to explore the factors associated with impaired renal function and albuminuria. On univariate analysis older age (OR = 5.87; 95% CI: 3.34–10.33), a family history of kidney disease (COR = 2.59; 95% CI: 1.34–4.92), history of diabetes (COR = 2.64; 95% CI: 1.53–4.50), hypertension (COR = 2.09; 95% CI: 1.20–3.64), respiratory disease (COR = 0.37; 95% CI: 0.14–0.95), HIV (COR = 2.75; 95% CI: 1.37–5.50) and systolic blood pressure (COR = 1.02, 95% CI: 1.00–1.04) were associated with impaired eGFR. In the multivariable analysis, older age (AOR = 6.42; 95% CI: 3.36–12.20), a family history of kidney disease (AOR = 3.08; 95% CI: 1.39–6.79), diabetes (AOR = 2.91; 95% CI: 1.41–6.00), hypertension (AOR = 3.83; 95% CI: 1.80–8.18) and HIV (AOR = 2.65; 95% CI: 1.15–6.09) remained independently associated with impaired eGFR (Table 2).

Table 2. Factors associated with impaired eGFR among patients admitted to internal medicine wards of Dessie referral hospital, Northeast Ethiopia, 2020.

Characteristics	Impaired eGFR		COR (95% CI)	P-value	AOR (95% CI)	P-value
	Yes (n = 70)	No (n = 229)	COR (95% CI)	P-value	AOR (95% CI)	P-value
Age (years)				< 0.001		< 0.001
≥ 60	48 (37.2)	81 (62.8)	5.87 (3.34–10.33)		6.42 (3.36–12.20)
< 60	22 (9.2)	218 (90.8)	1		1
Sex				0.675
Female	38 (19.8)	154 (80.2)	1.12 (0.66–1.86)		NA
Male	32 (18.1)	145 (81.9)	1		NA
Residence				0.854
Rural	46 (19.2)	193 (80.8)	1.05 (0.61–1.82)		NA
Urban	11 (18.5)	106 (81.5)	1		NA
Education				0.178		0.807
< High school	59 (20.4)	230 (79.6)	1.61 (0.80–3.23)		1.11 (0.48–2.58)
≥ High school	115 (13.8)	69 (86.2)	1		1
Family history of kidney disease				0.004		0.005
Yes	17 (34.0)	33 (66.0)	2.59 (1.34–4.92)		3.08 (1.39–6.79)
No	53 (16.6)	266 (83.4)	1		1
Smoking				0.460
Yes	7 (24.1)	22 (75.9)	1.40 (0.57–3.42)		NA
No	63 (18.5)	277 (81.5)	1		NA
Diabetes mellitus				0.001		0.004
Yes	29 (31.2)	64 (68.8)	2.64 (1.53–4.50)		2.91 (1.41–6.00)
No	41 (14.9)	235 (85.1)	1		1
Hypertension				0.009		0.001
Yes	26 (28.3)	66 (71.7)	2.09 (1.20–3.64)		3.83 (1.80–8.18)
No	44 (15.9)	233 (84.1)	1		1
Cardiovascular disease				0.690
Yes	17 (20.5)	66 (79.5)	1.13 (0.62–2.09)		NA
No	53 (18.3)	233 (81.5)	1		NA
Respiratory disease				0.033		0.371
Yes	5 (8.8)	52 (91.2)	0.37 (0.14–0.95)		0.57 (0.19–1.75)
No	65 (20.8)	247 (79.2)	1		1
HIV				0.003		0.022
Yes	15 (35.7)	27 (64.3)	2.75 (1.37–5.50)		2.65 (1.15–6.09)
No	55 (16.8)	272 (83.2)	1		1
Systolic BP (mmHg)	130.5 ± 21.5	125.7 ± 22.9	1.02 (1.00–1.04)	0.040	1.01 (0.99–1.02)	0.325
Diastolic BP (mmHg)	78.9 ± 9.8	79.2 ± 12.8	0.97 (0.95–1.00)	0.089	0.98 (0.96–1.02)	0.330

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Using univariate analysis, we observed that older age (COR = 2.69; 95% CI: 1.70–4.24), male gender (COR = 1.88; 95% CI: 1.20–2.94), residence (COR = 1.62; 95%CI: 1.03–2.55), a family history of kidney disease (COR = 2.58; 95% CI: 1.41–4.74), diabetes (COR = 2.19; 95% CI: 1.35–3.58), hypertension (COR = 2.25; 95% CI: 1.38–3.67), respiratory disease (COR = 0.49; 95% CI: 0.24–0.98), HIV (COR = 2.85; 95% CI: 1.46–5.39) and systolic blood pressure (COR = 1.02, 95% CI: 1.00–1.03) were associated with albuminuria. In multivariable analysis, older age (AOR = 2.57; 95% CI: 1.51–4.40), male gender (AOR = 1.71; 95% CI: 1.02–2.87), family history of kidney disease (AOR = 2.63; 95% CI: 1.35–5.14), diabetes (AOR = 2.97; 95% CI: 1.65–5.35), hypertension (AOR = 3.60; 95% CI: 1.98–6.54) and HIV (AOR = 3.05; 95% CI: 1.42–6.56) were independently associated with the presence of albuminuria (Table 3).

Table 3. Factors associated with albuminuria among patients admitted to internal medicine wards of Dessie referral hospital, Northeast Ethiopia, 2020.

Characteristics	Albuminuria		COR (95% CI)	P-value	AOR (95% CI)	P-value
	Yes (n = 114)	No (n = 229)	COR (95% CI)	P-value	AOR (95% CI)	P-value
Age (years)				< 0.001		0.001
≥ 60	58 (45.0)	71 (55.0)	2.69 (1.70–4.24)		2.57 (1.51–4.40)
< 60	56 (23.3)	184 (76.7)	1		1
Sex				0.005		0.044
Male	67 (37.9)	110 (62.1)	1.88 (1.20–2.94)		1.71 (1.02–2.87)
Female	47 (24.5)	145 (75.5)	1		1
Residence				0.037		0.102
Urban	49 (37.7)	81 (62.3)	1.62 (1.03–2.55)		1.57 (0.92–2.69)
Rural	65 (27.2)	174 (72.8)	1		1
Education				0.725
< High school	88 (30.4)	201 (69.6)	0.91 (0.54–1.55)		NA
≥ High school	26 (32.5)	54 (67.5)	1		NA
Family history of kidney disease				0.002		0.005
Yes	25 (50.0)	25 (50.0)	2.58 (1.41–4.75)		2.63 (1.35–5.14)
No	89 (27.9)	230 (72.1)	1		1
Smoking				0.091		0.064
Yes	13 (44.8)	16 (55.2)	1.92 (0.89–4.74)		2.64 (0.94–7.38)
No	101 (29.7)	239 (70.3)	1		1
Diabetes mellitus				0.001		<0.001
Yes	41 (44.1)	52 (55.9)	2.19 (1.35–3.58)		2.97 (1.65–5.35)
No	73 (26.4)	203 (85.1)	1		1
Hypertension				0.001		0.001
Yes	41 (44.6)	51 (55.4)	2.25 (1.38–3.67)		3.60 (1.98–6.54)
No	73 (26.4)	204 (73.6)	1		1
Cardiovascular disease				0.086		0.138
Yes	32 (38.6)	51 (61.4)	1.56 (0.94–2.60)		2.40 (0.76–7.62)
No	82 (28.7)	204 (71.3)	1		1
Respiratory disease				0.039		0.210
Yes	11 (19.3)	46 (80.7)	0.49 (0.24–0.98)		2.06 (0.67–6.40)
No	103 (33.0)	209 (67.0)	1		1
HIV				0.001		0.022
Yes	22 (54.2)	20 (47.6)	2.81 (1.46–5.39)		3.05 (1.42–6.56)
No	92 (28.1)	235 (71.9)	1		1
Systolic BP (mmHg)	130.7 ± 22.2	124.8 ± 22.7	1.02 (1.00–1.03)	0.030	1.01 (0.99–1.03)	0.175
Diastolic BP (mmHg)	80.1 ± 11.8	78.7 ± 12.5	0.99 (0.97–1.02)	0.451	NA

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Discussion

The present study aimed to determine the prevalence and factors associated with impaired renal function (eGFR) and albuminuria in adult patients admitted to a hospital in Northeast Ethiopia. Findings from this study indicate that 19.0% of the patients had impaired eGFR (< 60 mL/min/1.73 m²). A recent study conducted in adult patients admitted to Jimma University Medical Center in Southwest Ethiopia reported the prevalence of impaired eGFR to be 19.2% by the same definition with MDRD equation [27]. The prevalence of reduced eGFR among patients admitted to a general medical ward in Uganda was found to be 15.3% by using the MDRD equation [24]. In Botswana, the prevalence of CKD stages 3–5 (eGFR _MDRD <60 ml/min/1.73 m²) among patients admitted to the medical wards was estimated at 16.3% [32]. Furthermore, in a retrospective cohort study of acute medical admissions in London, UK, the prevalence of renal impairment of the same degree using the same MDRD equation was found to be 17.7% [33]. The prevalence of albuminuria in this study was 30.9%, which was significantly higher than the prevalences reported from China [34] and Southwest Ethiopia [27], where 8.87% and 12.3% of the patients admitted to the medical wards had albuminuria with dipstick proteinuria of ≥ 1+, respectively. This greater prevalence in our study may reflect the more elderly and complex medical inpatient population.

About 34% (33.9%) of our patients admitted to the internal medicine wards had some degree of CKD (i.e., they had either impaired eGFR and/or albuminuria). This is comparable to the Conakry study, in which 33% of patients admitted to the medical wards had CKD with markers of kidney damage (proteinuria, hematuria, pyuria, renal morphological abnormalities) and impaired eGFR calculated using the MDRD formula [35]. In the Chinese retrospective cross-sectional study, 14.82% of hospitalized adult patients had CKD using the same indicators of renal disease [34]. The Brazilian retrospective study similarly reported a lower prevalence of CKD of 12.7% among adult patients admitted to the internal medicine wards, but the CKD criterion was based on the presence of medical diagnosis in medical records [36]. Other studies conducted in Kenya [6] and Uganda [24] reported a higher prevalence of CKD compared to our study: 38.6% and 57.3%, respectively. The discrepancy could be explained by the differences in CKD definition used as well as methods for assessing albuminuria and eGFR. In the Kenyan study, for example, a diagnosis of CKD was defined as presence of markers of renal damage (including renal imaging, serum phosphate and calcium levels) and eGFR as determined by the Chronic Kidney Disease Epidemiology collaboration equation. The Uganda study, on the other hand, included microalbuminuria from Urine Albumin: Creatinine Ratio formula, renal imaging and eGFR as a definition criterion for CKD. The differences could also be due to variation in the lifestyle and age distribution of the studied patients.

Our study shows a lower awareness of CKD among the patients admitted to the internal medicine wards, only 21.6% of the adults with any degree of kidney disease (impaired eGFR and/or albuminuria) were aware of their condition. Although awareness was higher among patients with advanced disease, even among those with CKD stage 3b, awareness was only 33.3%, less than 50% for stage 4 and 66.7% with stage 5. Similar results have been reported in some of previous studies on hospital inpatients. In a retrospective study of general medicine inpatients from the University of Chicago Hospitalist Project, only 32% of patients with CKD were aware of their CKD. In addition, only 48% of patients with CKD stage 4 and 63% with stage 5 were aware of their disease [21]. In a cross-sectional study of general medicine inpatients at an urban academic medical center, awareness of CKD was at 33% [37]. In the Belgium study, more than a third of the CKD patients were not aware of their condition and only 65% of those with CKD stage 3b or 4 were aware of suffering from renal failure [22]. In the Botswana study, over half (53.5%) of the CKD cases were unaware of their disease [32].

The high prevalence and low awareness of CKD in this study support the evidence that CKD is frequently unrecognized in the inpatient settings, and that awareness is low among both physicians and affected patients [18–20]. In in-hospital patients, CKD is often not recognized until it is advanced and poorly documented in the medical record despite being present [19, 34, 38]. Even in CKD stage 3a or higher, it has been reported that as many as 70% of patients don’t carry a diagnosis in their medical record, suggesting the poor awareness that the inpatient community have in recognizing kidney disease [18, 38]. By identifying and informing patients with CKD, a higher awareness of the disease can be obtained, leading to a significant improvement in outcomes [22]. Thus, inpatient screening for impaired eGFR and albuminuria, and education on the importance of detection and early intervention may help identify kidney disease earlier and raise awareness in this setting.

We found that older age was associated with impaired eGFR and albuminuria, this finding is consistent with prior studies [12, 20, 27, 34, 35]. The increased prevalence of kidney disease in the older patients is probably largely as a result of increasing comorbid renal risk factors such as diabetes and hypertension as well as due to structural and functional changes in the aging kidneys [39, 40]. In the present study, 35% of inpatients were more than 60 years of age, and the prevalence of diabetes and hypertension were 31.8% and 29.5%, and 21.7% and 22.5% in patients aged less than 60 years (data not shown). Our results also showed that male gender was associated with increased risk of having albuminuria. Similar results were reported in the Kenyan and Chinese studies [6, 34]. This is, however inconsistent with the results reported in the Southwest Ethiopian study, where male gender was associated with a higher risk of eGFR impairment, but not albuminuria [27]. Therefore, the role of male gender in predicting kidney disease risk warrants further research. Our study has also shown that a family history of kidney disease was associated with impaired eGFR and albuminuria. Most studies show that patients with a family history of kidney disease have an increased risk of impaired eGFR and albuminuria [41] and assessment of kidney disease in subgroups of people with positive family history has been advocated by recent guidelines. However, there are no data that compare differences with a family history of kidney disease in the hospitalized population.

Our results demonstrate diabetes and hypertension as major risk factors for impaired eGFR and albuminuria. Several studies have shown diabetes and hypertension as independent risk factors for kidney disease, as evidenced by impaired eGFR and/or albuminuria [6, 24, 27, 32, 35]. This may reflect that patients with previously known diabetes and hypertension are likely to have higher rates of complications, including renal involvements during hospitalization [42, 43]. Therefore, inpatient screening of these patients for impaired eGFR and albuminuria can be helpful in the early recognition and treatment of kidney disease [44, 45]. In our study, HIV patients are at greater risk of having impaired eGFR and albuminuria. This was consistent with findings from previous study, which revealed that HIV positivity was independently associated with being diagnosed with kidney disease during hospitalization [32]. In the Zambian study by Banda et al, a higher prevalence of renal impairment was found in hospitalized HIV infected patients compared to uninfected patients with a twofold increased risk of developing kidney disease [46]. HIV infection itself, comorbidities and exposure to potentially nephrotoxic antiretroviral agents may play a role in eGFR impairment and albuminuria in HIV/AIDS patients [47].

However, our study experienced several limitations. Given the cross-sectional design, causal relationships between assessed risk factors and renal disease cannot be drawn. For the same reason the diagnosis of CKD was based on a single measurement of serum creatinine and dipstick albuminuria. Thus, there may be a possibility of overestimating the proportion of patients with CKD. However, the exclusion of intensive care unit admissions, patients with possibility of functional proteinuria and patients who had evidence of factors that can cause acute kidney injury or those on medical diagnosis of renal failure should minimize the risk of misclassification of cases as CKD. The MDRD formula used for the analysis has not been validated for use in Ethiopian patients. Further, because the measurement of serum creatinine was not standardized; this hindered us from using the popular Chronic Kidney Disease Epidemiology Collaboration equation.

Conclusions

In conclusion, CKD is common in adult patients admitted to the internal medicine wards of our hospital in Northeast Ethiopia. About 34% of our patients admitted to the internal medicine wards had CKD according to the diagnosis criterion of impaired eGFR and/or albuminuria, but only 21.6% of affected patients were aware of their condition. These findings highlight the need for feasible approaches to timely identify kidney disease and raise awareness on the importance of early detection and intervention in the inpatient populations. However, the present findings should be confirmed in a larger multicenter study.

Supporting information

S1 File

(DOCX)

Click here for additional data file.^{(16.8KB, docx)}

Acknowledgments

Authors would like to acknowledge all those who agreed to participate in this study, mainly respondents and internal medicine staffs.

Abbreviations

AOR: Adjusted odds ratio
BP: Blood pressure
CKD: Chronic kidney disease
CI: Confidence interval
DRH: Dessie Referral hospital
eGFR: Estimated glomerular filtration rate

Data Availability

All relevant data are within the manuscript.

Funding Statement

The authors received no specific funding for this work.

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PLoS One. doi: 10.1371/journal.pone.0246509.r001

Decision Letter 0

Bamidele O Tayo

8 Oct 2020

PONE-D-20-26423

Prevalence and associated factors of impaired renal function and albuminuria among adult patients admitted to a hospital in Northeast Ethiopia

PLOS ONE

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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. Specifically, respond to each of the concerns raised in the accompanying reviewers' comments in addition to the following:

Regarding the eligibility criteria, the text indicated that "Patients were eligible for the study if they were aged 18 years or older, were admitted to the internal medicine wards for at least 48 hours, and had serum creatinine measurements at admission.": (i) were the serum creatinine measurements ordered by the physicians as part of the patients' admission or based on prior investigations and medical records leading to referral? (ii) were the serum creatinine measurements performed by the investigators as part of this study? (iii) When were the blood and urine samples collected for assays from the patients, after 48 hours of being admitted to the internal medicine wards? (iv) The text stated that "A fasting venous blood sample and spot urine specimen were collected from each patient in the morning and then transported to the hospital inpatient laboratory.", explain how patients on hospital admission were made to fast before sample collection, what happened to those that could not fast or where on intravenous fluid or diet? (v) "Blood pressure was measured with a mercury sphygmomanometer after the patients had rested for 5–10 min in the sitting position.", explain whether these measurements were made as part of the admission to the ward or as part of the present study and were they after admission? (vi) Provide description of how patients were screened for "possibility of functional proteinuria and patients who had evidence of factors that can cause acute kidney injury or those on medical diagnosis of renal failure" in this study.

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Reviewer #1: This paper is well written and is relevant. However I have the following comments

Abstract:

Line 38 - 45 (results)

This section can be summarized as follows;

older age (AOR=6.42; 95%CI: 3.36–12.20), a family history of kidney disease (AOR=3.08; 95%CI: 1.39–6.79), diabetes (AOR=2.91; 95%CI: 1.41–6.00), hypertension (AOR=3.83; 95%CI: 1.80–8.18) and HIV (AOR=2.65; 95%CI: 1.15–6.09) were independently associated with both impaired eGFR and albuminuria while male gender (AOR=1.71; 95%CI: 1.02–2.87), was associated with only albuminuria.

Introduction:

Line 75 and 76 (introduction)

This is not entirely true as there is data on CKD among hospitalized patients in Africa. Again, this is not a strong motivation to conduct this research. The author should provide the gap in knowledge clearly, indicate flaws in prior research in Africa and how this current knowledge fills this gap.

Methods:

Line 91 and 92

Were they consecutively recruited and consented?

Please be clear on whether patient provided written informed consent or verbal consent

Line 95

Add the ethical clearance reference number

Line 104 and 105

The mean of the last two readings would have been more accurate as the first reading is often prone to error

Line 110 and 111

Quantification of proteinuria using ACR/UPCR would have been more useful as the dipstick method is prone to problems with dilution and concentration of urine. Further, dipsticks will not detect microalbuminuria. You may add this to your limitations as those with microalbuminuria would have been excluded

Line 112 and 113

Even though, the author excluded patients with suspected AKI based on presence risk factors of AKI or diagnosis of acute renal failure in medical files, this definition is still problematic as there is no baseline creatinine/eGFR. The duration of renal dysfunction or albuminuria; 3 or more or imaging study of shrunken or echogenic kidneys from the clinical files may have strengthened this definition. As it stands some of these patients could have unexplained acute renal failure with no clear risk factors and may have been classified wrongly as CKD in this study.

Line 128

Check this; using a p value of 0.25 as level of significance in the univariate analysis sounds incorrect.

This cannot be right

Results:

Line 140

What cardiovascular diseases were diagnosed? (heart failure, stroke, CAD?)

Discussion:

Line 211 - 213

In this study (Ref 29), did these patients with acute illness have acutely impaired renal function or they were known CKD patients before hospitalization?

If acute, then you cannot compare this with your study cohort as you seem to be studying patients with CKD and not AKI

Line 243

Deleted Disease after CKD

Reviewer #2: Prevalence and associated factors of impaired renal function and albuminuria among adult patients admitted to a hospital in Northeast Ethiopia

REVIEW

Introduction

The authors write on the prevalence of renal impairment, albuminuria and the factors associated with them noting that CKD being increasingly common is often unrecognized in hospitalized patients and that most patients with renal disease in Africa especially, are unaware of their condition. This warranted the study being done to detect this. They noted that the consequences of CKD can be devastating. Therefore, advocating for early detection. The prevalence of renal impairment has been studied in many circumstances and places but has not been studied in their own hospitalized patients and region in east Africa.

The introduction builds a logical case and context for the problem statement which is clear. The research question is implied clearly.

The literature review is up-to-date. The number of references is appropriate and their selection is judicious. The references are mainly primary sources. Ideas are scholarly and acknowledged appropriately and accurately

Comment regarding the novelty and significance of the manuscript.

The research is original, though not novel and addresses important issues which will create avenues for more research on renal diseases and is worth doing. It addresses the need for early evaluation of renal impairment in patients on admission in Africa and it adds to the literature already available on the subject.

Method

The study design is cross sectional and is appropriate for the research question. (prevalence study).

Study population. The setting, locations, and relevant dates, including periods of recruitment, are noted. eligibility criteria, and the sources and methods of selection of participants are noted. The sampling procedures are described as consecutive sampling which is non probabilistic. This study being a local single center, clinic-based study, lacks generalizability which is a limitation of a clinic-based study. Nonetheless, this type of study design is classified as a cross-sectional study.

They did not report numbers of individuals at each stage of study—eg numbers potentially eligible, examined for eligibility, confirmed eligible, included in the study, and analysed. Non-response was not a significant problem in the study.

Threat to internal validity -The manner of selection is non-random, and non-representative which is a source of bias but this is understandable being a small clinic based study. An attempt was made to address potential confounding variables which were excluded in the study.

Instrumentation, Data Collection.

The measurement instruments is appropriate given the study’s major variables; the scoring method is clearly defined for CKD, BP , albuminuria. The terms medical renal failure is rather ambiguous. See footnote below on renal impairment.

They did not specify explicitly which variables were outcome vs exposures. Outcome, exposures, predictors, potential confounders are not clearly stated as such in text but is implied. It is mentioned that observers or raters were trained to take measurements however measures taken to ensure data quality control is not stated.

How the study size was arrived at is appropriate, though formula used to derive it is not referenced.

Data Analysis and Statistics

Statistical tests are simple and appropriate. Data-analysis procedures conform to the research design.

The results are complete, organized and contextualized in a way that is easy to understand. Tables, and figures are used judiciously and agree with the text. Table 1 is presented showing the population characteristics. unadjusted estimates, adjusted estimates and their precision are also presented.

Discussion and Conclusion:

Interpretations of the results are appropriate and alternative interpretations for the findings are considered. Personal perspectives or values related to interpretations are discussed.

guidance for future studies is offered. The study limitations are discussed.

The conclusions key points stand out. My conclusion is consistent with the authors.

Title, authors, and abstract

The title is clear, representative of the content of the study and not misleading. The number of authors is appropriate given the study.

The abstract is complete with essential details presented.

Presentation and Documentation

The text is organized, well written and easy to follow. Reference citations are complete and appropriate.

Scientific Conduct

There are no instances of plagiarism. Ideas and materials of others are correctly attributed.

There is no apparent conflict of interest. There is an explicit statement of approval by an institutional review board (IRB) for the study.

COMMENTS FOR THE AUTHORS

1 Report numbers of individuals at each stage of study—eg numbers potentially eligible, examined for eligibility, confirmed eligible, included in the study, and analysed.

2 Can you clarify what is meant by the term medical renal failure in the patients you excluded. What level of eGFR do you consider renal failure.

3 A statement indicating which of the variables are dependent and independent need to be stated in the analysis plan, say exactly how the prevalence of the condition was derived.

4 The formula used to derive sample size should be referenced.

5 In table 1, Hypertension and diabetes patients do not add up n=370 instead of 369. Reconcile or any explanation? Did you adjust for any other potential confounders in analysis? If yes, make clear which confounders were adjusted for and why they were included.

6 The vocabulary is appropriate, except (in table 1 and any other place with the word illiterate-line 137) use of the term illiterate is inappropriate- change to no formal education.

NOTE: The use of the term renal impairment is ambiguous and generally lacks clarity. The Kidney Disease: Improving Global Outcomes (KDIGO) Consensus Conference held in June 2019, suggested that when referring to ‘decreased or decreasing GFR’, avoid the use of different, poorly defined terms such as ‘impaired kidney function’, ‘renal insufficiency’, ‘renal dysfunction’, ‘renal impairment’, ‘worsening kidney function’ and ‘kidney function decline’. The goal is to facilitate communication within and across disciplines and between practitioners and patients, with the ultimate hope of improving outcomes through consistency and precision. (Refer Andrew S Levey, Kai-Uwe Eckardt, Nijsje M Dorman, Stacy L Christiansen, Michael Cheung, Michel Jadoul, Wolfgang C Winkelmayer, Nomenclature for kidney function and disease: executive summary and glossary from a Kidney Disease: Improving Global Outcomes consensus conference, Nephrology Dialysis Transplantation, Volume 35, Issue 7, July 2020, Pages 1077–1084, https://doi.org/10.1093/ndt/gfaa153

Reviewer #3: This study is pertinent because it highlights an important point that a significant number of patients who are admitted into medical wards but do not have symptoms of kidney disease or require renal replacement therapy may benefit from prevent measures to prevent end-stage kidney disease. Their level of awareness may also be improved when physicians take deliberate steps in this regards.

Anthropometric data are missing and these are important in a study like this in which comprehensive preventive measures are being advocated. Also, could the authors categorize the co-morbidity by age group? In line modern nephrology terminology, 'kidney disease' has generally replaced 'renal disease'.

The last sentence in the discussion (lines 296-298) should be corrected for clarity. Also, the labels on figures 1 and 2 , i.e. 'propertion...' should read 'proportion...'.

**********

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PLoS One. 2021 Feb 4;16(2):e0246509. doi: 10.1371/journal.pone.0246509.r002

Author response to Decision Letter 0

24 Nov 2020

Response to Academic Editor Comments

Comment # 1: Were the serum creatinine measurements ordered by the physicians as part of the patients' admission or based on prior investigations and medical records leading to referral?

Response #1: This were the serum creatinine measurements ordered by the physicians as part of the patients' admission and only adults with serum creatinine results available at admission were included in this study.

Comment # 2: Were the serum creatinine measurements performed by the investigators as part of this study?

Response #2: The first serum creatinine during admission was ordered by the physicians as part of the patients' admission and was abstracted from the admission medical records. The serum creatinine measurements for estimating eGFR of each patient was performed by the investigators as part of this study.

Comment # 3: When were the blood and urine samples collected for assays from the patients, after 48 hours of being admitted to the internal medicine wards?

Response #3: Patients were eligible for the study if they were admitted to the internal medicine wards for at least 48 hours and thus, the blood and urine samples for the study were collected after 48 hours of being admitted to the internal medicine wards.

Comment # 4: The text stated that "A fasting venous blood sample and spot urine specimen were collected from each patient in the morning and then transported to the hospital inpatient laboratory.", explain how patients on hospital admission were made to fast before sample collection, what happened to those that could not fast or where on intravenous fluid or diet?

Response #4: Patients were excluded from the study if they had been hospitalized in critical condition. After discussing with the attending physician, patients meeting the inclusion criteria were asked to fast before sample collection. Those that could not fast or where on acute intervention were excluded.

Comment # 5: "Blood pressure was measured with a mercury sphygmomanometer after the patients had rested for 5–10 min in the sitting position.", explain whether these measurements were made as part of the admission to the ward or as part of the present study and were they after admission?

Response #5: These measurements were made as part of the present study, after 48 hours of being admitted to the internal medicine wards

Comment # 6: Provide description of how patients were screened for "possibility of functional proteinuria and patients who had evidence of factors that can cause acute kidney injury or those on medical diagnosis of renal failure" in this study.

Response #6: Factors associated with false/transient positive dipstick proteinuria were examined and dipstick proteinuria in subjects with fever (>98.6F), haematuria, leukocyturia, nitrites or very alkaline urine (pH >8.0) were not included into the analysis. To reduce the impact of acute renal failure in the study, increase in serum creatinine by ≥ 0.3mg/dl from admission value (i.e., within 48 hours), and critical care admissions (such as acute circulatory or respiratory failure, presence of infection or cirrhosis) were excluded. We also excluded patients with medical record for renal replacement therapy (dialysis) or those with any mention of acute renal failure, renal failure and contrast administration in the medical files.

When submitting your revision, we need you to address these additional requirements.

Comment # 1: Please ensure that your manuscript meets PLOS ONE's style requirements, including those for file naming. The PLOS ONE style templates can be found at

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Response #2: As suggested, our manuscript follows PLOS ONE formatting to meet PLOS ONE's style requirements

Comment # 2: Please include additional information regarding the survey or questionnaire used in the study and ensure that you have provided sufficient details that others could replicate the analyses. For instance, if you developed a questionnaire as part of this study and it is not under a copyright more restrictive than CC-BY, please include a copy, in both the original language and English, as Supporting Information. In addition, please include further details concerning the development and validation of this tool.

Response #2: As suggested, the questionnaire for the study was included as Supporting Information. Data collection tool was developed in English with modification from SEEK study. As suggested, it is stated as “Data were collected from patients and their medical records using structured questionnaire which was developed in English with modification from Screening and Early Evaluation of Kidney Disease (SEEK) study (28). The questionnaire was carefully designed and pre-tested on 5% of study population and, based on the results, revision was made to minimize errors. Patients were interviewed to collect data on socio-demographic…” (Line 103-107)

Comment # 3: Your ethics statement should only appear in the Methods section of your manuscript. If your ethics statement is written in any section besides the Methods, please delete it from any other section.

Response #3: As suggested, it is delete and included in the Methods section of the manuscript, stating “The study was approved by the Institutional Review Board of College of Medicine and Health Sciences, Wollo University. Written informed consent was obtained from each study participants after explaining the purpose and procedures of the study. Clinical information obtained in this study was communicated to attending physicians so that they could be used for clinical care.” (Line 97-101)

Response to Reviewer Comments

Reviewer #1

This paper is well written and is relevant. However, I have the following comments

Comment # 1: Abstract: Line 38 - 45 (results). This section can be summarized as follows; older age (AOR=6.42; 95%CI: 3.36–12.20), a family history of kidney disease (AOR=3.08; 95%CI: 1.39–6.79), diabetes (AOR=2.91; 95%CI: 1.41–6.00), hypertension (AOR=3.83; 95%CI: 1.80–8.18) and HIV (AOR=2.65; 95%CI: 1.15–6.09) were independently associated with both impaired eGFR and albuminuria while male gender (AOR=1.71; 95%CI: 1.02–2.87) was associated with only albuminuria.

Response #1: If it has to be summarized as suggested above we need to remove the adjusted odds ratios (AOR), as these are odds ratios of albuminuria. As suggested, it is stated as “In multivariable analysis, older age, a family history of kidney disease, diabetes, hypertension and HIV were independently associated with both impaired eGFR and albuminuria while male gender was independently associated with only albuminuria.” (Line 41-44)

Comment # 2: Introduction: Line 75 and 76 (introduction). This is not entirely true as there is data on CKD among hospitalized patients in Africa. Again, this is not a strong motivation to conduct this research. The author should provide the gap in knowledge clearly, indicate flaws in prior research in Africa and how this current knowledge fills this gap.

Response #2: Only 3 published studies are available on CKD and its risk factors among hospitalized patients in Africa. These few studies do not capture the whole picture around the region and this calls for more information, and research should be encouraged to gauge the prevalence of CKD in African countries and define its risk factors. This cross-sectional study was therefore conducted to contribute in filling this knowledge gap. As suggested, it is stated as” However, despite the high prevalence of CKD and its resulting increased in-hospital morbidity and mortality, little is known about the prevalence of CKD in the African hospitalized patients. The few available studies among hospitalized patients in Africa have reported CKD prevalence of 13.5% in Botswana, 38.6% in Kenya (6) and 57.3% in Uganda (27). Understanding the burden and associated risk factors of CKD based on relevant indicators of kidney disease is important for making relevant decisions regarding identification and prevention of the disease in this resource limited region, where access to renal replacement therapy is strictly rationed (25). We therefore ...” (Line 74-81)

Comment # 3: Methods: Line 91 and 92. Were they consecutively recruited and consented? Please be clear on whether patient provided written informed consent or verbal consent

Response #3: We consecutively included inpatients meeting the inclusion criteria until the required sample size was achieved. Written informed consent was obtained from each study participants after explaining the purpose and procedures of the study. This information was mistakenly written in other section besides the Methods, and it now appear in the method section as stated in response # 3 of academic reviewer comments in the additional requirements section.

Comment # 4: Line 95. Add the ethical clearance reference number

Response #4: As suggested, the ethical clearance reference number was added as "..., Wollo University (# 135/13/12).” (Line 98-99)

Comment # 5: Line 104 and 105. The mean of the last two readings would have been more accurate as the first reading is often prone to error

Response #5: BP measurements taken during the first two days of hospitalization were not used for the statistical analyses. Three sequential readings were taken 5 min apart in the sitting position. The subject is asked to relax for 10–15 min (in order to minimize anxiety, which will increase variability). Caffeine was not allowed for at least 1 h and smoking was not allowed for at least 30 min before the BP measurement. If the difference between readings were within the clinically insignificant 0-5 mm Hg range (no error of clinical relevance), the average of the three readings was recorded; otherwise, one additional reading was taken (for 18 patients). The average of three BP measurements was also taken in related African study (in Botswana).

Comment # 6: Line 110 and 111. Quantification of proteinuria using ACR/UPCR would have been more useful as the dipstick method is prone to problems with dilution and concentration of urine. Further, dipsticks will not detect microalbuminuria. You may add this to your limitations as those with microalbuminuria would have been excluded.

Response #6: Albuminuria was evaluated using a semiquantitative urine dipstick test due to unavailability of quantitative albuminuria test. In an effort to correct for problems arising out of variability in urine concentration while screening for albuminuria by dipsticks, the urine specimen was assessed if the urine’s specific gravity was >1.015. It has been also suggested that dipstick testing for albumin, protein, or their ratios to creatinine in hospitalized patients had good or excellent agreement with quantitative methods (Pugia et al. 2001 Albuminuria and proteinuria in hospitalized patients as measured by quantitative and dipstick methods). The albuminuria diagnosis based on a single urinalysis dipstick measurement could lead to overestimating the prevalence of CKD. As suggested, it is stated as “… the diagnosis of CKD was based on a single measurement of serum creatinine and dipstick albuminuria.” in the limitation section (Line 321-322)

Comment # 7: Line 112 and 113. Even though, the author excluded patients with suspected AKI based on presence risk factors of AKI or diagnosis of acute renal failure in medical files, this definition is still problematic as there is no baseline creatinine/eGFR. The duration of renal dysfunction or albuminuria; 3 or more or imaging study of shrunken or echogenic kidneys from the clinical files may have strengthened this definition. As it stands some of these patients could have unexplained acute renal failure with no clear risk factors and may have been classified wrongly as CKD in this study.

Response #7: As already stated in the method section of the manuscript, only adults with serum creatinine results available at admission were included in this study. To reduce the impact of acute renal failure on the study, increase in serum creatinine by ≥ 0.3mg/dl from admission value (i.e., within 48 hours) were excluded. Regarding the duration of renal impairment or albuminuria; based on a single serum creatinine or dipstick albuminuria measurement could lead to overestimating the prevalence of CKD, and this was already stated as the limitation of the study (Line 321-323). Data on imaging study of shrunken or echogenic kidneys from the clinical files was not available because the majority of patients in this study were not hospitalized for kidney disease. As stated in line 323-326, the exclusion of intensive care unit admissions, patients with possibility of functional proteinuria and patients who had evidence of factors that can cause acute kidney injury or those on medical diagnosis of renal failure should minimize the risk of misclassification of cases as CKD in this study.

Comment # 8: Line 128. Check this; using a p value of 0.25 as level of significance in the univariate analysis sounds incorrect. This cannot be right

Response #8: Variable selection should start with the univariate analysis of each variable and variables that show significance (P<0.25) in the univariate analysis should be included in the multivariate analysis (Hosmer et al, 2013. Applied logistic regression). As such, a univariate analysis was done to sort variables candidate for multivariable analyses having value less than 0.25. Multivariable logistic regression analyses were conducted using backward stepwise selection method to identify factors independently associated with impaired renal function or albuminuria. P-value < 0.05 and 95% confidence interval (CI) and AOR was used in judging the statistical significance of the associations between independent variables and the dependent variable.

Comment # 9: Results: Line 140. What cardiovascular diseases were diagnosed? (heart failure, stroke, CAD?)

Response #9: As stated in the method section (Line 109-110), cardiovascular diseases (coronary artery disease, myocardial infarction, heart failure, peripheral vascular disease, and old stroke) were defined as present if recorded as the main admission diagnoses on medical records.

Comment # 10: Discussion: Line 211 – 213. In this study (Ref 29), did these patients with acute illness have acutely impaired renal function or they were known CKD patients before hospitalization? If acute, then you cannot compare this with your study cohort as you seem to be studying patients with CKD and not AKI

Response #10: The lowest creatinine was obtained for each hospital admission and, for up to 3 months before and after the admission. These patients have CKD Stages 3–5 (eGFR < 60 mL/min/1.73 m2).

Comment # 11: Line 243. Deleted Disease after CKD

Response #11: As suggested, the term “Disease” after CKD was deleted (Line 271)

Reviewer #2

Comment # 1: Report numbers of individuals at each stage of study—eg numbers potentially eligible, examined for eligibility, confirmed eligible, included in the study, and analysed.

Response #1: This was a cross-sectional study with only one stage.

Comment # 2: Can you clarify what is meant by the term medical renal failure in the patients you excluded. What level of eGFR do you consider renal failure.

Response #2: We mean patients with medical diagnosis of renal failure, i.e., renal failure documented in their medical records.

Comment # 3: A statement indicating which of the variables are dependent and independent need to be stated in the analysis plan, say exactly how the prevalence of the condition was derived.

Response #3: As suggested, it is stated as “… 20 software (SPSS Inc., Chicago, IL, USA). We derived means for continuous variables and proportions to describe the characteristics of the study patients as well as the prevalence of impaired renal function, albuminuria and CKD. Comparisons of patients according to the presence of impaired renal function or albuminuria were performed using Chi-square (x2) test and t-test, where appropriate. To determine which factors were associated with the presence of impaired renal function or albuminuria, univariate analysis was conducted with age, sex, residence, education, smoking status, family history of kidney disease, presence of hypertension, diabetes, cardiovascular diseases, respiratory diseases and HIV, and current systolic and diastolic BP as variables. Variables that were found to be significant in univariate analysis (P < 0.25) were included in the multivariable backwards stepwise logistic regression model to identify factors independently associated with impaired renal function or albuminuria. P-value < 0.05 was used to indicate statistical significance.” (Line 133-144)

Comment # 4: The formula used to derive sample size should be referenced.

Response #4: As suggested, it is referenced as “(26)” (Line 96)

Comment # 5: In table 1, Hypertension and diabetes patients do not add up n=370 instead of 369. Reconcile or any explanation? Did you adjust for any other potential confounders in analysis? If yes, make clear which confounders were adjusted for and why they were included.

Response #5: As stated in the method (Line 94-95) and result (Line 145-146) sections of the manuscript, a total of 369 patients who fulfilled the eligibility criteria were consecutively included in this study. Diabetes and non-diabetes/ Hypertension and non-hypertension patients add up n=369 (i.e., we included 369 patients admitted due to a primary diagnosis of diabetes, hypertension, cardiovascular diseases, respiratory diseases, HIV/AIDS and others as recorded on their medical records). To identify factors independently associated with impaired renal function or albuminuria, all variables with univariate P values < 0.25 were included in the multivariable (backward stepwise) logistic regression.

Comment # 6: The vocabulary is appropriate, except (in table 1 and any other place with the word illiterate-line 137) use of the term illiterate is inappropriate- change to no formal education

Response #6: As suggested, the term “illiterate” is changed to “no formal education” (Line 152 and 163 [in table 1])

Reviewer #3

Comment # 1: Anthropometric data are missing and these are important in a study like this in which comprehensive preventive measures are being advocated. Also, could the authors categorize the co-morbidity by age group? In line modern nephrology terminology, 'kidney disease' has generally replaced 'renal disease'.

Response #1: Obtaining anthropometry measurements at admission is challenging, and anthropometric data are frequently documented based on “best-guess” estimates by the clinical care team or parent/relatives, with varying degrees of accuracy. Anthropometric data are not collected during data collection due to fear of procedure associated accidents/discomforts in inpatients, for example patients are expected to stand by themselves, and weight and height are measured in light clothes without footwear. We did not provide data on co-morbidity by age group, but diabetes and hypertension (the two main comorbid renal risk factors) were present in 31.8% and 29.5% of the inpatients aged ≥ 60 years compared to 21.7% and 22.5% of those aged < 60 years. As suggested, it is stated as “In the present study, 35% of inpatients were more than 60 years of age, and the prevalence of diabetes and hypertension were 31.8% and 29.5%, and 21.7% and 22.5% in patients aged less than 60 years (data not shown).” (Line 292-294). As suggested, the term “renal disease” is replaced with “kidney disease” (Line 47, 72, 73, 79, 128, 166, 188, 192, 192, 265, 283, 286, 289, 298, 302, 311, 314, 316 and 334)

Comment # 2: The last sentence in the discussion (lines 296-298) should be corrected for clarity. Also, the labels on figures 1 and 2 , i.e. 'propertion...' should read 'proportion...'.

Response #2: As suggested, it is stated as “HIV infection itself, comorbidities and exposure to potentially nephrotoxic antiretroviral agents may play a role in eGFR impairment and albuminuria in HIV/AIDS patients (46).” (Line 316-318). As suggested, the labels on figures 1 and 2 are corrected and read “proportion (%)”.

Table 2 and 3 were labelled mistakenly as Table 3 and 4. As suggested, the labels are corrected as "Table 2" and "Table 3"

PLoS One. doi: 10.1371/journal.pone.0246509.r003

Decision Letter 1

Bamidele O Tayo

21 Jan 2021

Prevalence and associated factors of impaired renal function and albuminuria among adult patients admitted to a hospital in Northeast Ethiopia

PONE-D-20-26423R1

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Reviewer #1: All comments have been addressed

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Reviewer #3: All comments have been addressed

**********

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

Reviewer #1: Yes

Reviewer #2: Yes

Reviewer #3: Yes

**********

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Reviewer #1: I Don't Know

Reviewer #2: Yes

Reviewer #3: Yes

**********

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Reviewer #1: Yes

Reviewer #2: Yes

Reviewer #3: Yes

**********

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Reviewer #1: Yes

Reviewer #2: Yes

Reviewer #3: Yes

**********

6. Review Comments to the Author

Reviewer #1: All comments addressed. However, for choosing P < 0.25 for the univariate analysis as explained by the author, it will be appreciable if the author can check for co-linearity between the dependent and independent variables.

Reviewer #2: (No Response)

Reviewer #3: The authors have provided adequate answers to questions raised in the first round of review. I have also read their responses to other reviewers' comments. Within the limitations so stated in a cross-sectional section the manuscript has improved. Again, this paper draws attention to the burden of CKD among hospitalised patients in the medical wards, many of whom have never had opportunity of visiting family physicians to screen for CKD. CKD is in the community as well as in the hospital, and patients on our beds should not go undetected.

**********

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Reviewer #1: No

Reviewer #2: No

Reviewer #3: No

PLoS One. doi: 10.1371/journal.pone.0246509.r004

Acceptance letter

Bamidele O Tayo

25 Jan 2021

PONE-D-20-26423R1

Prevalence and associated factors of impaired renal function and albuminuria among adult patients admitted to a hospital in Northeast Ethiopia

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PERMALINK

Prevalence and associated factors of impaired renal function and albuminuria among adult patients admitted to a hospital in Northeast Ethiopia

Temesgen Fiseha

Ermiyas Ahmed

Semagn Chalie

Angesom Gebreweld

Roles

Abstract

Background

Methods

Results

Conclusions

Introduction

Methods

Study design, setting and population

Data collection and measurements

Statistical analysis

Results

Demographic and clinical characteristics of the study patients

Table 1. Demographic and clinical characteristics of the study patients (n = 369).

Prevalence of indicators of kidney disease

Fig 1. Prevalence of impaired eGFR, albuminuria and CKD according to age group of study patients.

Prevalence and awareness of CKD

Fig 2. Awareness of CKD stratified by CKD stages.

Factors associated with impaired renal function and albuminuria

Table 2. Factors associated with impaired eGFR among patients admitted to internal medicine wards of Dessie referral hospital, Northeast Ethiopia, 2020.

Table 3. Factors associated with albuminuria among patients admitted to internal medicine wards of Dessie referral hospital, Northeast Ethiopia, 2020.

Discussion

Conclusions

Supporting information

Acknowledgments

Abbreviations

Data Availability

Funding Statement

References

Decision Letter 0

Bamidele O Tayo

Roles

Author response to Decision Letter 0

Decision Letter 1

Bamidele O Tayo

Roles

Acceptance letter

Bamidele O Tayo

Roles

Associated Data

Supplementary Materials

Data Availability Statement

ACTIONS

PERMALINK

RESOURCES

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