Skip to main content
PLOS One logoLink to PLOS One
. 2021 Nov 2;16(11):e0259310. doi: 10.1371/journal.pone.0259310

Incidence and predictors of preterm neonatal mortality at Mbarara Regional Referral Hospital in South Western Uganda

Leevan Tibaijuka 1,2,*, Stephen M Bawakanya 1,2, Asiphas Owaraganise 1,3, Lydia Kyasimire 4, Elias Kumbakumba 4, Adeline A Boatin 5, Musa Kayondo 1,2, Joseph Ngonzi 1,2, Stephen B Asiimwe 6, Godfrey R Mugyenyi 1,2
Editor: Sajid Bashir Soofi7
PMCID: PMC8562818  PMID: 34727140

Abstract

Introduction

Preterm neonatal mortality contributes substantially to the high neonatal mortality globally. In Uganda, preterm neonatal mortality accounts for 31% of all neonatal deaths. Previous studies have shown variability in mortality rates by healthcare setting. Also, different predictors influence the risk of neonatal mortality in different populations. Understanding the predictors of preterm neonatal mortality in the low-resource setting where we conducted our study could guide the development of interventions to improve outcomes for preterm neonates. We thus aimed to determine the incidence and predictors of mortality among preterm neonates born at Mbarara Regional Referral Hospital (MRRH) in South Western Uganda.

Methods

We prospectively enrolled 538 live preterm neonates born at MRRH from October 2019 to September 2020. The neonates were followed up until death or 28 days, whichever occurred first. We used Kaplan Meier survival analysis to describe preterm neonatal mortality and Cox proportional hazards regression to assess predictors of preterm neonatal mortality over a maximum of 28 days of follow up.

Results

The cumulative incidence of preterm neonatal mortality was 19.8% (95% C.I: 16.7–23.5) at 28 days from birth. Birth asphyxia (adjusted hazard ratio [aHR], 14.80; 95% CI: 5.21 to 42.02), not receiving kangaroo mother care (aHR, 9.50; 95% CI: 5.37 to 16.78), delayed initiation of breastfeeding (aHR, 9.49; 95% CI: 2.84 to 31.68), late antenatal care (ANC) booking (aHR, 1.81 to 2.52; 95% CI: 1.11 to 7.11) and no ANC attendance (aHR, 3.56; 95% CI: 1.51 to 8.43), vaginal breech delivery (aHR, 3.04; 95% CI: 1.37 to 5.18), very preterm births (aHR, 3.17; 95% CI: 1.24 to 8.13), respiratory distress syndrome (RDS) (aHR, 2.50; 95% CI: 1.11 to 5.64) and hypothermia at the time of admission to the neonatal unit (aHR, 1.98; 95% CI: 1.18 to 3.33) increased the risk of preterm neonatal mortality. Attending more than 4 ANC visits (aHR, 0.35; 95% CI: 0.12 to 0.96) reduced the risk of preterm neonatal mortality.

Conclusions

We observed a high cumulative incidence of mortality among preterm neonates born at a low-resource regional referral hospital in Uganda. The predictors of mortality among preterm neonates were largely modifiable factors occurring in the prenatal, natal and postnatal period (lack of ANC attendance, late ANC booking, vaginal breech delivery, birth asphyxia, respiratory distress syndrome, and hypothermia at the time of admission to the neonatal unit, not receiving kangaroo mother care and delayed initiation of breastfeeding). These findings suggest that investment in and enhancement of ANC attendance, intrapartum care, and the feasible essential newborn care interventions by providing the warm chain through kangaroo mother care, encouraging early initiation of breastfeeding, timely resuscitation for neonates when indicated and therapies reducing the incidence and severity of RDS could improve outcomes among preterm neonates in this setting.

Introduction

Preterm birth refers to a birth occurring at gestational age less than 37 completed weeks [1, 2]. It is an important cause of mortality and morbidity in new-borns [3]. Globally, in 2014 alone, about 15 million live preterm babies were born and the majority (81%) of these occurred in Asia and sub-Saharan Africa [4]. Preterm birth-related complications account for about 35% of all neonatal deaths [4]. In Uganda, the risk of preterm birth is estimated at 10 to 15%, and preterm birth is the leading cause of neonatal deaths, accounting for 28–31% of all neonatal deaths [5, 6].

Owing to the immature and inadequate physiological compensatory responses to the extra-uterine environment, premature babies are at an increased risk of complications such as respiratory distress syndrome, hypothermia, perinatal asphyxia, neonatal sepsis, intraventricular haemorrhage, neonatal jaundice, necrotizing enterocolitis and feeding difficulties [7, 8]. Unsurprisingly, the mortality from preterm births in resource-limited settings like Uganda is high since these complications are difficult to treat [6]. Interventions to prevent the occurrence of preterm birth like antenatal care attendance and administration of medicines that block the labour process are thus needed and studies focussing on this should be encouraged. Where preterm birth has occurred, interventions to prevent the development of complications that often lead to death are also urgently needed. In the long term, survivors of preterm birth are also more likely to experience motor and sensory impairment, delay in cognitive development and behavioural problems than babies born at term [6]. Long term monitoring of preterm babies and studies to guide such efforts are also important.

Deaths in the neonatal period are linked to maternal-fetal conditions and the care given during antepartum, intrapartum, and postpartum periods [9]. Maternal and obstetric factors implicated in preterm neonatal mortality include maternal age, increased body mass index (BMI), diabetes mellitus, preeclampsia/eclampsia, smoking during pregnancy, preterm premature rupture of membranes (PPROM), antepartum haemorrhage (APH) and labour dystocia [1014]. Neonatal factors contributing to mortality include low gestational age, low birth weight, 5-minute Apgar score less than 7 and the need for neonatal intensive care unit (NICU) admission [1016]. Previous studies have shown variability in the mortality rates and outcomes in different health care settings and across countries; low resource settings like Uganda have higher mortality rates [17, 18].

A better understanding of the role of potentially modifiable risk factors like antenatal corticosteroid (ACS) administration, quality antenatal care (ANC), mode of delivery, tocolysis, respiratory support, kangaroo mother care (KMC), and postnatal surfactant may improve preterm neonatal outcomes, especially in low-resource settings [11, 15, 19]. This study aimed to determine the incidence and predictors of preterm neonatal mortality at Mbarara Regional Referral Hospital (MRRH), a low-resource hospital in South Western Uganda.

Methods

Study design and setting

We conducted a prospective cohort study of live preterm neonates born at Mbarara Regional Referral Hospital (MRRH), in South Western Uganda from October 2019 to September 2020. MRRH is a public tertiary hospital with a maternity ward that conducts approximately 10,000 deliveries per year, with a caesarean delivery rate of 40%, maternal mortality ratio of 375 per 100,000 live births [20] and perinatal mortality rate of 33 per 1000 live birth according to 2019 hospital records [21]. According to hospital records, routine antenatal care attendance averages at 1350 women per month. The maternity ward is managed by a team of about 14 obstetricians/gynaecologists, 38 obstetrics/gynaecology residents, intern doctors, and 38 midwives. There are approximately 50 preterm neonates delivered per month and these are usually transferred to the Paediatric neonatal unit within 10 minutes of delivery, except when there is need for resuscitation before transfer in which case a delay of up to 30 minutes may happen.

The Paediatric ward is managed by a team of about 8 paediatricians, 13 paediatric residents, intern doctors and 10 nurses. The Paediatric department admits about 5,000 children every year, approximately 2,000 (40%) of whom are neonates. Of the neonates admitted to the neonatal unit, approximately two-thirds are born at MRRH and a third are either referred in from other health facilities or directly from the surrounding communities. Premature babies make up 45% of all new-born admissions. The current neonatal unit accommodates 40 neonates. There is no separate KMC ward. Clinical care is provided by two paediatricians, a senior resident and an intern doctor alongside the 3 nurses. The neonatal unit has 2 neonatal phototherapy machines which serve 3–4 neonates at a time, and one full time functional radiant warmer. There is a supply of medical oxygen with oxygen cylinders, and 2 backup oxygen concentrators, 3 nasal continuous positive airway pressure (nCPAP) machines. There is an additional warmer in the emergency admission room.

Participant enrolment

All live preterm neonates born at a gestational age from 28 weeks, 0 days (28W0D) to 36 weeks, 6 days (36W0D) at the MRRH maternity ward during the study period were eligible for the study. The gestational age (GA) was estimated using either the first day of the last normal menstrual period (LNMP), known to be a more reliable measure of GA in a low-resource setting [22] or first trimester dating obstetric ultrasound if available. Mothers with neither a known LNMP nor a first trimester ultrasound scan were excluded.

Sample size determination and sampling techniques

According to the 2018 audit report from the Department of Paediatrics at MRRH (unpublished data), a total of 469 preterm neonates were admitted to the neonatal unit from a total of 3,636 new born babies. Seventy-five (75) of the 469 admitted preterm neonates died, yielding a cumulative mortality incidence of 16%. We used these data to estimate our expected total preterm births per month (≈40 neonates). We explored the precision that different sample sizes would yield around an estimated cumulative mortality of ≈17% for the 12 months planned study duration. The simulation result of 460 neonates would yield reasonable precision (about 2% length of the 95% CI) (Table 1). We therefore consecutively enrolled all live preterm neonates born during the study period while aiming to reach a minimum of 460 neonates.

Table 1. Simulated samples sizes around the departmental cumulative neonatal mortality incidence.

N Mortality estimate (95% CI)
460 17% (15.0%-19.0%)
480 17% (15.5%-18.5%)
520 17% (15.7%-18.2%)
540 17% (16.0%-18.0%)

Data collection and follow-up

Mothers to the eligible preterm neonates were counselled before enrollment, after delivery. Those providing written informed consent were subsequently enrolled alongside their neonates. We developed and pretested the questionnaire to ascertain its adequacy to collect the study variables. The interviewer administered the questionnaire to obtain baseline data from mothers and followed this up with a chart review to obtain additional information about the mothers.

The data collected were categorised into: a) maternal characteristics (age, level of education, marital status, occupation, address, referral status (women referred to MRRH from another health center before delivery), and HIV status); b) obstetric characteristics (parity, gestation age at booking ANC visit, number of ANC visits, ACS administration, duration from administration of the first dose of ACS to delivery, mode of delivery, prior preterm birth, prior early neonatal death and obstetric conditions (preterm labour, PPROM, multiple pregnancy, pre-eclampsia/eclampsia, placenta previa or abruption placenta, and chorioamnionitis); and c) neonatal characteristics (neonatal sex, birth weight, gestational age at birth, and Apgar score at 5 minutes).

Preterm neonates, subsequently admitted to the neonatal unit, were followed up to ascertain outcomes through observation and chart review from admission time to death or until 28 days. Data abstracted from the neonatal charts included information on neonatal morbidities, interventions and, for those who died, the suspected cause of death. Neonatal morbidities considered were: respiratory distress syndrome (RDS), birth asphyxia, hypothermia, hypoglycaemia, neonatal sepsis, and necrotizing enterocolitis. Neonatal interventions assessed were: kangaroo mother care (KMC), supplemental oxygen therapy, nasal continuous positive airway pressure (nCPAP), prophylactic antibiotics, phototherapy, radiant heat warmed, nasogastric tube (NGT) feeding and breastfeeding initiation within the first hour of life. The clinical causes of neonatal death considered were: RDS, birth asphyxia, hypothermia, hypoglycaemia, neonatal sepsis, necrotizing enterocolitis, and nosocomial pneumonia.

For any neonates discharged alive before 28 days, post-discharge follow-up was done via a phone call on day 3, 7, 14 and 28. A fraction of the neonates discharged from the neonatal unit before 28 days were seen during scheduled post-discharge clinical visits at the neonatal clinic which operates once every week.

Data were collected into a tablet in some cases and a laptop in other cases and managed using a secure online backed up Research Electronic Data Capture (REDCap™) database (version 8.2) hosted at the Department of Obstetrics and Gynaecology at MUST [23].

Study variables

The primary outcome was the time to death of a preterm neonate (in days) obtained via patient chart abstraction or phone call for deaths that occurred at home post-discharge. Primary predictors included maternal characteristics (age, level of education, marital status, occupation, address, referral status, and HIV status); obstetric characteristics (parity, gestation age at booking ANC visit, number of ANC visits, ACS administration, duration from administration of the first dose of ACS to delivery, mode of delivery, prior preterm birth, prior early neonatal death and obstetric conditions (preterm labour, PPROM, multiple pregnancy, pre-eclampsia/eclampsia, placenta previa or abruption placenta, and chorioamnionitis); and neonatal characteristics (neonatal sex, birth weight, gestational age at birth, and Apgar score at 5 minutes).

Variable definitions

A preterm infant was defined as a neonate born at a gestational age from 28 weeks, 0 days (28W0D) to 36 weeks, 6 days (36W6D) and further sub-classified according to gestational age as: very preterm (28weeks, 0days to 31weeks, 6days); moderate preterm (32weeks, 0days to 33weeks, 6days); and late preterm (34weeks, 0days to 36weeks, 6days). Birth weight was categorized into normal birth weight (>2.5 kg), low birth weight (1.5 to 2.5 kg), and very low birth weight (<1.5 kg). Antenatal corticosteroid use was defined as having received any dose of corticosteroids before delivery (within 7 days period of delivery). ANC booking—defined as the first time of ANC attendance, was categorized as: first trimester booking (<13 weeks of gestation), second trimester booking (between 13 to 26 weeks of gestation) and third trimester booking (≥ 27 weeks of gestation). We considered late ANC booking as ≥13 weeks of gestation [24].

Neonatal morbidities were defined as 1) RDS—presence of any of: fast breathing, grunting, subcostal and intercostal recession, cyanosis and reduced air entry in bilateral lung fields starting in the first four hours of life [25]; 2) birth asphyxia—5-minute Apgar score of ≤ 5 [26]; 3) hypothermia—axillary temperature of less than 36.0°C at the time of admission to the neonatal unit; 4) hypoglycaemia—glucose below 40mg/dL (<2.2mmol/l) in a capillary blood sample from a heel prick for blood glucose testing using an electronic glucometer [27]; 5) hyperbilirubinemia—yellowing of eyes and/or body requiring phototherapy or serum bilirubin levels above 15mg/dL as per WHO criteria [27]; 6) sepsis—the presence of clinical symptoms or signs suggestive of sepsis according to the WHO’s Integrated Management of Childhood Illnesses (IMCI) algorithm with a blood culture at any point during the study period [27]; 7) nosocomial pneumonia—diagnosed basing on blood culture and localizing clinical features to the chest including grunting, fast breathing, chest wall in-drawing, oxygen saturation of <90% on room air, with crepitations on auscultation [27]; 8) necrotizing enterocolitis—diagnosed basing on clinical features of abdominal distension and tenderness, intolerance to feeding, bilious vomitus or fluid up the nasogastric tube, bloody stools and abdominal x-ray findings of air bubbles in the intestinal walls [27].

The cause of death was defined as the clinical condition directly and immediately leading to the death of the neonate as documented in the neonate’s medical chart/records. The cause of death for those who died at home was classified as unknown.

Statistical analysis

Data were exported from the REDCap ™ database to Stata (version 15) for cleaning and statistical analysis. Descriptive statistics were obtained for predictor and outcome variables and are presented in tables, charts and graphs. Kaplan Meier (KM) curves were used to estimate survival and describe the pattern of mortality among preterm neonates. Cox proportional hazards regression models were used to describe and assess the predictors of neonatal mortality among the preterm neonates in univariable and multivariable analyses. Preterm neonates that were lost to follow up were censored. However, the total time they contributed to the study was incorporated during analysis of results.

Ethical consideration

Ethical approval was sought and obtained from the MUST Research Ethics Committee (MUREC-19/07-19) and the Uganda National Council for Science and Technology (UNCST-HS469ES). Written informed consent to participate in the study was obtained from the mothers before enrolment. All study methods were performed per the Declaration of Helsinki guidelines and regulations [28].

Results

During the study period from October 2019 to September 2020, a total of 564 live preterm neonates were born at the maternity ward of MRRH. Of these, mothers to 26 neonates declined to consent, and 538 (95.4% response rate) were enrolled. Of the 538 preterm neonates, 106 died, 421 survived and 11 (2.0%) were lost to follow up by 28 days (Fig 1).

Fig 1. Study flow diagram.

Fig 1

Maternal and obstetric characteristics

The mean maternal age was 26.4 (SD±5.9) years. Over half of the mothers (54.8%) lived in Mbarara district. The majority were married (97.0%), unemployed (69.5%), and had attained at least primary education (86.8%) (Table 2). Just under half of the sample were multiparous (49.1%). Of 505 (93.9%) mothers who attended ANC, 343 (63.8%) booked late and 290 (53.9%) attended 3–4 ANC visits. Of the 219 (40.7%) who received antenatal corticosteroids, 111 (50.7%) delivered within less than 24 hours after receiving the first dose. A majority (55.2%) of the neonates were delivered by spontaneous vaginal delivery. The majority of the preterm births followed spontaneous labour (66.5%), but significant proportions also occurred after some complications including PPROM (37.7%), and preeclampsia (11.9%) (Table 2).

Table 2. Baseline socio-demographic and obstetric characteristics of mothers of preterm neonates born at Mbarara Regional Referral Hospital from October 2019 to September 2020 (N = 538).

Characteristics Frequency (n) Percentage (%)
Maternal residence
    Mbarara 295 54.8
    Isingiro 123 22.9
    Others 120 22.3
Maternal age (years)
    <20 68 12.6
    20–34 413 76.8
    >34 57 10.6
Married 522 97.0
Level of education
    Uneducated 71 13.2
    Primary 202 37.6
    Secondary 180 33.5
    Post-secondary 85 15.8
Employed 164 30.5
Mother referred in 255 47.4
HIV serostatus
    HIV positive 86 16.0
    HIV negative 452 84.0
Parity (number of births)
    I 157 29.2
    II-IV 264 49.1
    ≥V 117 21.7
Booking (first) ANC visit
    1st trimester 162 30.1
    2nd trimester 307 57.1
    3rd trimester 36 6.7
ANC attendance
    Did not attend ANC 33 6.1
    1–2 times 110 20.5
    3–4 times 290 53.9
    >4 times 105 19.5
Mode of delivery
    Spontaneous vaginal delivery 297 55.2
    Vaginal breech delivery 39 7.3
    Emergency caesarean section 182 33.8
    Elective caesarean section 20 3.7
Antenatal corticosteroid (ACS) use 219 40.7
Corticosteroid use to delivery interval N = 219
    < 24 hours 111 50.7
    24 to <48 hours 79 36.1
    ≥48 hours 29 13.2
Tocolysis 18 3.6
Previous preterm birth 14 2.6
Previous history of a still births 17 3.2
Previous history of ENND 22 4.1
Obstetric conditions
PPROM 203 37.7
Spontaneous preterm labor 358 66.5
Preeclampsia 64 11.9
APH (placenta previa or abruption) 33 6.1
Mal-presentation 36 6.7
Chorioamnionitis 9 1.7
Other obstetric conditions 15 2.8

ANC—antenatal care, ACS—antenatal corticosteroids, ENND—early neonatal death, PPROM—preterm premature rupture of membranes, APH—antepartum haemorrhage.

Neonatal characteristics of preterm neonates

Among 538 preterm neonates, 283 (52.6%) were males and269 (50%) were born at 34 weeks 0 days to 36 weeks 6 days. Three hundred one (56.0%) had low birth weight (LBW), while107 (19.9%) had very LBW. The majority were admitted to the neonatal unit (74.9%). Two hundred sixteen (37.5%) were diagnosed with respiratory distress syndrome (RDS), 148 (27.5%) with hypothermia at the time of admission, and 29 (7.2%) with birth asphyxia. Two hundred eighty (69.5%) received kangaroo mother care (KMC), 96 (23.8%) received continuous positive airway pressure (CPAP) (Table 3).

Table 3. Characteristics of preterm neonates born at Mbarara Regional Referral Hospital from October 2019 to September 2020 (N = 538).

Characteristics Frequency (n) Percentage (%)
Sex of the neonate
    Male 283 52.6
    Female 255 47.4
Gestational age
    28W0D-31W6D (very preterm) 165 30.7
    32W0D-33W6D (moderate preterm) 104 19.3
    34W0D-36W6D (late preterm) 269 50.0
Birth weight (kg)
    <1.5 (ELBW & VLBW) 107 19.9
    1.5 - <2.5 (LBW) 301 56.0
    ≥2.5 (Normal) 130 24.2
Apgar score at 5 minutes
    < 7 56 10.4
    ≥7 481 89.6
Neonate required admission to neonatal unit 403 74.9
Neonatal morbidities
Birth asphyxia 25 4.6
Respiratory Distress Syndrome (RDS) 223 41.4
Hypothermia at the time of admission 148 27.5
Hypoglycemia at the time of admission 27 5.0
Neonatal sepsis 83 15.4
Neonatal jaundice 135 25.1
Necrotizing enterocolitis (NEC) 7 1.3
Nosocomial pneumonia 9 1.7
Neonatal interventions
Kangaroo mother care (KMC) 280 69.5
Required and received continuous positive airway pressure (CPAP) 96 23.8
Required and received supplemental oxygen therapy 295 73.2
Required and received phototherapy 141 35.7
Warmed with radiant warmer 380 94.3
Nasogastric tube feeding 162 40.3
Breastfeeding initiated within the first hour of life 129 31.9

ELBW—Extreme low birth weight, VLBW—very low birth weight, LBW—Low birth weight.

Mortality incidence of preterm neonates

The cumulative incidence of preterm neonatal mortality was 9.1% at 24 hours, 13.2% at 72 hours, 17.6% at 7 days, 19.3% at 14 days, and 19.8% at 28 days. The cumulative preterm neonatal mortality incidence at 28 days in this study was therefore 19.8% (95% confidence interval: 16.7–23.5) (Fig 2).

Fig 2. Cumulative survival curve of preterm neonates born at MRRH from October, 2019 to September, 2020 (n = 538).

Fig 2

Neonatal morbidities contributing to death of preterm neonates

The morbidities contributing to death of preterm neonates included; respiratory distress syndrome (RDS) (71/106 [67.0%]), birth asphyxia (n = 17 [16.0%], hypothermia (n = 16 [15.1%]), neonatal sepsis (n = 11 [10.4%]), jaundice (n = 7 [6.6%]), necrotizing enterocolitis (NEC) (n = 4 [3.8%]), nosocomial pneumonia (n = 3 [2.8%]), and congenital anomalies (n = 3 [2.8%]). The contributing morbidities were classified as unknown for neonates that died at home after discharge (n = 6 [5.7%])—2 neonates were reported to have had a febrile illness prior to their death, while 4 neonates were reported to have been well but found dead in the bed (Fig 3).

Fig 3. Bar chart showing the clinical causes of death among preterm neonates born at MRRH from October, 2019 to September, 2020 (n = 106).

Fig 3

RDS—respiratory distress syndrome; NEC—necrotizing enterocolitis.

Predictors of mortality among preterm neonates

Birth asphyxia (aHR, 14.80; 95% CI: 5.21–42.02), not receiving KMC (aHR, 9.50; 95% CI: 5.37–16.78), late initiation of breastfeeding (>1 hour after birth) (aHR, 9.49; 95% CI: 2.84–31.68), not attending ANC (aHR, 3.56; 95% CI: 1.51–8.43), late ANC booking (booking in the second trimester (adjusted hazard ratio [aHR], 1.81; 95% CI: 1.03–3.64) and third trimester aHR, 2.52; 95% CI: 1.11–7.11)), vaginal breech delivery (aHR, 3.04; 95% CI: 1.37–5.18), very preterm births (aHR, 3.17; 95% CI: 1.24–8.13), RDS (aHR, 2.50; 95% CI: 1.11–5.64) and hypothermia at admission (aHR, 1.98; 95% CI: 1.18–3.33) increased the risk of preterm neonatal mortality. However, attending more than 4 ANC visits (aHR, 0.35; 95% CI: 0.12–0.96) reduced the risk of mortality (Table 4).

Table 4. Predictors of mortality among preterm neonates born at Mbarara Regional Referral Hospital from October, 2019 to September, 2020.

Predictor variables Categories CHR (95% CI) p-value AHR (95% CI) p-value
Booking ANC visit 1st trimester Ref. Ref.
2nd trimester 2.30 (1.31–4.04) 0.004* 1.81 (1.03–3.64) 0.044*
3rd trimester 5.22 (2.55–10.68) <0.001** 2.52 (1.11–7.11) 0.032*
Number of ANC visits 3–4 visits Ref. Ref.
No ANC attended 2.68 (1.48–4.83) 0.001* 3.56 (1.51–8.43) 0.004*
1–2 visits 1.78 (1.15–2.75) 0.010* 0.76 (0.41–1.42) 0.390
>4 times 0.35 (0.16–0.78) 0.010* 0.35 (0.12–0.96) 0.042*
Mode of delivery Caesarean delivery Ref. Ref.
Spontaneous vertex delivery 0.90 (0.58–1.40) 0.642 1.06 (0.62–1.79) 0.833
Vaginal breech delivery 5.66 (3.40–9.42) <0.001** 3.04 (1.37–5.18) 0.004*
ACS use Yes Ref. Ref.
No 2.87 (1.79–4.59) <0.001* 1.01 (0.56–1.82) 0.966
Gestational Age 34W0D-36W6D Ref. Ref.
32W0D-33W6D 1.43 (0.71–2.88) 0.323 1.38 (0.51–3.74) 0.525
28W0D-31W6D 6.20 (3.84–10.00) < 0.001** 3.17 (1.24–8.13) 0.016*
Birth weight (kg) ≥2.5 Ref. Ref.
1.5-<2.5 2.26 (1.06–4.82) 0.035* 2.30 (0.54–9.79) 0.258
<1.5 10.0 (4.73–21.14) < 0.001** 3.20 (0.66–15.50) 0.148
RDS No Ref. Ref.
Yes 6.59 (4.09–10.63) <0.001** 2.50 (1.11–5.64) 0.027*
Hypothermia at admission No Ref.
Yes 4.38 (2.97–6.46) <0.001** 1.98 (1.18–3.33) 0.010*
Birth asphyxia No Ref. Ref.
Yes 8.03 (4.88–13.22) <0.001** 14.80 (5.21–42.02) < 0.001**
Hypoglycemia No Ref. Ref.
Yes 2.14 (1.12–4.11) 0.022* 1.92 (0.91–4.03) 0.087
NEC No Ref. Ref.
Yes 3.08 (1.13–8.37) 0.027* 0.43 (0.14–1.28) 0.128
KMC Yes Ref. Ref.
No 7.82 (4.95–12.35) <0.001** 9.50(5.37–16.78) <0.001**
Breastfeeding initiation at birth Early (≤ 1 hour) Ref. Ref.
Late (>1 hour) 5.51 (3.28–9.26) <0.001** 9.49(2.84–31.68) <0.001**
nCPAP No Ref. Ref.
Yes 6.22 (4.08–9.49) <0.001** 0.80(0.44–1.45) 0.466
Supplemental oxygen No Ref. Ref.
Yes 2.86 (1.53–5.38) 0.001* 1.22 (0.46–3.25) 0.686
Neonatal Sex Male Ref. Ref.
Female 0.73 (0.50–1.08) 0.112 0.63 (0.39–1.01) 0.053

CHR—crude hazard ratio, AHR—adjusted hazard ratio, *p<0.05, **p <0.001,ANC—antenatal care, ACS—antenatal corticosteroid, RDS—respiratory distress syndrome, NEC—necrotizing enterocolitis, KMC—kangaroo mother care, nCPAP—nasal continuous positive airway pressure.

Discussion

This study aimed to determine the incidence and predictors of preterm neonatal mortality in a tertiary low-resource hospital in South Western Uganda. We observed a high overall incidence of mortality (19.8%). The study highlights the major predictors of preterm neonatal mortality such as birth asphyxia, not receiving kangaroo mother care (KMC), late initiation of breastfeeding, late ANC booking and lack of ANC attendance, vaginal breech delivery, very preterm birth, respiratory distress syndrome and hypothermia at the time of admission to the neonatal unit as increasing the risk of preterm neonatal mortality. Attending more than four ANC visits decreased the risk of preterm neonatal mortality.

The observed incidence of neonatal mortality is comparable to findings from other studies done in similar resource limited settings. For instance, a study done in Mulago National Referral Hospital in Central Uganda reported 22.1% [29], while a multicentre prospective observational study at 5 hospitals in Ethiopia reported 22.7% [30]. Also findings from the University of Nigeria Teaching Hospital in Nigeria showed a mortality incidence of 24.0% [31]. This is likely because of the similar vulnerable study population of preterm neonates, but also the comparable study settings which were referral teaching hospitals. Our result is higher than what was observed at Nairobi hospital in Kenya (11.9%) [32], and Shahid Akbar-Abadi university hospital in Iran (9.1%) [11]. However, our finding is lower than what has been observed at other regional referral hospitals in Uganda: 35.2% in Kiwoko hospital in Central Uganda [33]; and 31.6% in Fort Portal Regional Referral Hospital in Western Uganda [34]. Our result is also lower than what was observed at the NICU in North West Ethiopia (28.8%) [35],and the Fatemieh hospital in Iran (27.4%) [36].

The disparity in mortality is likely due to inequalities in neonatal care for preterm neonates. Settings with specialized and well-equipped neonatal care facilities could provide better care to the preterm neonates compared to the resource limited settings with suboptimal care provided in the inadequately equipped NICUs as noted in sub-Saharan Africa [37]. The differences could also be explained by the source of data. At Nairobi hospital in Kenya and Shahid Akbar-abadi university hospital in Iran (where lower mortality was reported) data was obtained for neonates born at the respective hospitals. At Kiwoko hospital in Uganda, Fort Portal Regional Referral Hospital in Uganda, University of Gondar Comprehensive Specialized Hospital in Ethiopia and Fatemieh hospital in Iran, data were obtained from both delivery and neonatal intensive care units. The studies included neonates referred in from other centres or born from home, and also enrolled extremely preterm neonates (<28 weeks of gestation). Our study prospectively followed up preterm neonates from the delivery room to neonatal unit and / or home, and only enrolled preterm neonates with gestational age at least 28 weeks to <37 weeks born from the maternity unit of Mbarara Regional Referral Hospital, which may explain why our observed mortality was lower than that observed at the other Ugandan hospitals.

The main contributors to neonatal death established in this study were respiratory distress syndrome (RDS), birth asphyxia, hypothermia and neonatal sepsis. This is similar to what is reported in other studies [29, 30, 38]. Respiratory distress syndrome, birth asphyxia and hypothermia are common complications of preterm neonates. Respiratory distress syndrome is associated with surfactant deficiency which is common with decreasing gestational age, mainly in neonates born before 34 weeks of gestation [39]. Hypothermia is mainly due to the large body surface area to weight and the relative lack of subcutaneous fat which makes the preterm neonates prone to heat loss [40]. Notably, neonatal sepsis contributed substantially to mortality, despite preterm neonates, especially those that required admission, receiving prophylactic antibiotics.

The predictors of mortality among preterm neonates born at MRRH were largely modifiable and ranged from prenatal, natal and postnatal predictors (lack of ANC attendance or late ANC booking, vaginal breech delivery, birth asphyxia, respiratory distress syndrome and hypothermia at the time of admission to the neonatal unit, not receiving kangaroo mother care and delayed initiation of breastfeeding). Similar findings have been reported from other studies of various settings [34, 35, 4147]. The predictors found in our study suggest that relatively simple interventions might improve the outcomes of the preterm neonates born at MRRH. Investment in and enhancement of the feasible essential new born (ECN) interventions which include providing the warm chain through kangaroo mother care, encouraging early initiation of breastfeeding and timely resuscitation for neonates when indicated could improve outcomes among preterm neonates [48]. Also strategies to reinforce quality ANC attendance, vigilant intrapartum monitoring and appropriate choice of the delivery mode specifically avoiding vaginal delivery for breech preterm neonates, enhanced care for especially the very preterm neonates at greatest risk for preterm-associated complications and mortality mostly within 7 days of life, and scaling up the implementation of therapies that reduce incidence and severity of respiratory distress syndrome (antenatal corticosteroid administration, use of CPAP and postnatal surfactant) is warranted.

The strength of this study was that it was a prospective study conducted at a single tertiary centre with a large number of preterm neonates staying in the same centre from birth to discharge with a uniform policy on labour room practices, management protocols and discharge criteria. We followed up neonates from the delivery room to the neonatal unit and home until the end of the neonatal period. The discharged preterm neonates were followed up via phone to establish their outcome on days 3, 7, 14 and 28. However, since we only enrolled and followed up neonates born at MRRH, the mortality incidence may not reflect the overall preterm neonatal mortality in the community. Some neonates were lost to follow-up due to persistently off or incorrect telephone contacts provided by study participants. To address this limitation, we had obtained more than one phone contact and we also followed up and tracked some of the lost neonates at the neonatal out-patient clinic that runs every Thursday at the paediatrics ward. This helped to reduce the attrition rates but still, there were a few neonates for whom outcomes could not be established. Since the first trimester obstetric ultrasonography is not routinely accessible to most pregnant women, we used LNMP to determine the gestational age. Also, nosocomial pneumonia was reported separate from neonatal sepsis to highlight the observed contribution of chest infections to the overall neonatal sepsis at our institution. No additional intervention was available for neonates with RDS who failed on CPAP, this could have increased the contribution of RDS to the overall mortality. Confidence intervals for hazard ratios of birth asphyxia and late initiation of breastfeeding were wide, and should therefore be interpreted in context of small numbers of participants with birth asphyxia and those with early initiation of breastfeeding. Finally, although we suggest various clinical causes of death, postmortem examinations were not done. We based on the clinical cause of death as documented by the clinical care team, which can at times be inaccurate.

Conclusions

The preterm neonatal mortality observed in this study was high, especially among the very preterm neonates. The majority of the deaths occurred in the early neonatal period, and the leading clinical causes of death were respiratory distress syndrome, birth asphyxia and hypothermia. The predictors for mortality are largely modifiable including obstetric predictors like lack of ANC attendance, late ANC booking, attending more than 4 ANC visits and vaginal breech delivery, and neonatal predictors like very preterm births, neonatal morbidities suffered including respiratory distress syndrome, hypothermia and birth asphyxia, not receiving KMC and late initiation of breastfeeding.

Our findings highlight the importance of integrated maternal-neonatal care for preterm neonates. Interventions designed around the modifiable predictors such as reinforcing quality ANC attendance, vigilant intrapartum monitoring and appropriate choice of the delivery mode specifically avoiding vaginal delivery for breech preterm neonates could improve outcomes. There is also need for enhanced care for, especially the very preterm neonates at greatest risk for preterm-associated complications and mortality mostly within the early neonatal period. Scaling up the implementation of therapies that reduce incidence and severity of respiratory distress syndrome like antenatal corticosteroid administration, use of CPAP and postnatal surfactant, improving thermal care through kangaroo mother care and encouraging early initiation of breastfeeding could improve outcomes among preterm neonates. We recommend future studies to evaluate the feasibility of implementing these interventions and what their impact would be on preterm neonatal outcomes in this setting.

Supporting information

S1 Fig

(TIF)

S2 Fig

(TIF)

S3 Fig

(TIF)

S4 Fig

(TIF)

S5 Fig

(TIF)

S6 Fig

(TIF)

S7 Fig

(TIF)

S1 Dataset

(DTA)

Acknowledgments

We acknowledge the research assistants Ms. Shanura Masika and Ms. Edivina Ahimbisibwe. We are grateful to the staff at the maternity ward and neonatal unit of Mbarara Regional Referral Hospital, Mbarara University of Science and Technology and the participants for enabling the performance of this study.

Data Availability

All relevant data are within the paper and its Supporting Information files.

Funding Statement

The research reported in this manuscript was supported by The First Mile community Health Program at Mbarara University of Science and Technology. The content is solely the responsibility of the authors. The funders had no role in the study design, data collection, and analysis, decision to publish, or preparation of the manuscript.

References

  • 1.Dbstet A. WHO: recommended definitions, terminology and format for statistical tables related to the perinatal period and use of a new certificate for cause of perinatal deaths. Modifications recommended by FIGO as amended October 14, 1976. Acta Obstet Gynecol Scand. 1977;56(3):247–53. [PubMed] [Google Scholar]
  • 2.Howson CP, Kinney MV, McDougall L, Lawn JE. Born Too Soon: Preterm birth matters. Reproductive Health. 2013;10(1):S1. doi: 10.1186/1742-4755-10-S1-S1 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 3.Platt MJ. Outcomes in preterm infants. Public Health. 2014;128(5):399–403. doi: 10.1016/j.puhe.2014.03.010 [DOI] [PubMed] [Google Scholar]
  • 4.Chawanpaiboon S, Vogel JP, Moller A-B, Lumbiganon P, Petzold M, Hogan D, et al. Global, regional, and national estimates of levels of preterm birth in 2014: a systematic review and modelling analysis. The Lancet Global Health. 2019;7(1):e37—e46. doi: 10.1016/S2214-109X(18)30451-0 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 5.MCEE W. MCEE-WHO methods and data sources for child causes of death 2000–2015. World Health Organization. 2016. [Google Scholar]
  • 6.Blencowe H, Cousens S, Oestergaard MZ, Chou D, Moller AB, Narwal R, et al. National, regional, and worldwide estimates of preterm birth rates in the year 2010 with time trends since 1990 for selected countries: a systematic analysis and implications. Lancet. 2012;379(9832):2162–72. doi: 10.1016/S0140-6736(12)60820-4 [DOI] [PubMed] [Google Scholar]
  • 7.Behrman RE. Preterm Birth: Causes, Consequences, and Prevention. In: Behrman RE, Butler AS, editors. The National Academies Collection: Reports funded by National Institutes of Health. Washington (DC)2007.
  • 8.Henderson J, Carson C, Redshaw M. Impact of preterm birth on maternal well-being and women’s perceptions of their baby: a population-based survey. BMJ Open. 2016;6(10):e012676. doi: 10.1136/bmjopen-2016-012676 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 9.WHO. Newborns: reducing mortality. World Health Organization: WHO. 2019. [Google Scholar]
  • 10.Gargari SS, Kashanian M, Zendedel H, Nayeri F, Shariat M, Haghollahi F. Survival and Risk Factors of Extremely Preterm Babies (< 28 weeks) in the Three Iranian Hospitals. Acta Medica Iranica. 2018;56(3):181–8. [Google Scholar]
  • 11.Haghighi L, Nojomi M, Mohabbatian B, Najmi Z. Survival predictors of preterm neonates: Hospital based study in Iran (2010–2011). Iran J Reprod Med. 2013;11(12):957. [PMC free article] [PubMed] [Google Scholar]
  • 12.Ravelli ACJ, Schaaf JM, Mol BWJ, Tamminga P, Abu-Hanna A. Antenatal prediction of neonatal mortality in very premature infants. European Journal of Obstetrics & Gynecology and Reproductive Biology. 2014;176(1). doi: 10.1016/j.ejogrb.2014.02.030 [DOI] [PubMed] [Google Scholar]
  • 13.Almeida MFBd, Guinsburg R, Martinez FE, Procianoy RS, Leone CR, Marba STM, et al. Perinatal factors associated with early deaths of preterm infants born in Brazilian Network on Neonatal Research centers. J Pediatr (Rio J). 2008;84(4):300–7. doi: 10.2223/JPED.1787 [DOI] [PubMed] [Google Scholar]
  • 14.Yego F, D’Este C, Byles J, Nyongesa P, Williams JS. A case-control study of risk factors for fetal and early neonatal deaths in a tertiary hospital in Kenya. BMC Pregnancy Childbirth. 2014;14:389. doi: 10.1186/s12884-014-0389-8 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 15.Cupen K, Barran A, Singh V, Dialsingh I. Risk Factors Associated with Preterm Neonatal Mortality: A Case Study Using Data from Mt. Hope Women’s Hospital in Trinidad and Tobago. Children (Basel). 2017;4(12):108. doi: 10.3390/children4120108 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 16.Basu S, Rathore P, Bhatia BD. Predictors of mortality in very low birth weight neonates in India. Singapore Med J. 2008;49(7):556–60. [PubMed] [Google Scholar]
  • 17.Helenius K, Sjörs G, Shah PS, Modi N, Reichman B, Morisaki N, et al. Survival in Very Preterm Infants: An International Comparison of 10 National Neonatal Networks. Pediatrics. 2017;140(6):e20171264. doi: 10.1542/peds.2017-1264 [DOI] [PubMed] [Google Scholar]
  • 18.Lawn JE, Kerber K, Enweronu-Laryea C, Massee Bateman O. Newborn survival in low resource settings—are we delivering? BJOG. 2009;116(Suppl):1. [DOI] [PubMed] [Google Scholar]
  • 19.Obstetricians ACo, Gynecologists. Antenatal corticosteroid therapy for fetal maturation. ACOG committee opinion number 713. 2017.
  • 20.Lugobe HM, Boatin AA, Asiimwe F, Karungi C, Kayondo M, Mukiza C, et al. 490 Maternal mortality at a referral hospital in south western uganda: a 5 year descriptive analysis %J Am. J. Obstet. Gynecol. 2021;224(2):S311–S2. [Google Scholar]
  • 21.Lugobe HM, Muhindo R, Kayondo M, Wilkinson I, Agaba DC, McEniery C, et al. Risks of adverse perinatal and maternal outcomes among women with hypertensive disorders of pregnancy in southwestern Uganda. PLoS One. 2020;15(10):e0241207. doi: 10.1371/journal.pone.0241207 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 22.Rosenberg RE, Ahmed ASMNU, Ahmed S, Saha SK, Chowdhury MAKA, Black RE, et al. Determining Gestational Age in a Low-resource Setting: Validity of Last Menstrual Period. J Health Popul Nutr. 2009;27(3):332. doi: 10.3329/jhpn.v27i3.3375 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 23.Harris PA, Taylor R, Thielke R, Payne J, Gonzalez N, Conde JG. Research electronic data capture (REDCap)—a metadata-driven methodology and workflow process for providing translational research informatics support. Journal of biomedical informatics. 2009;42(2):377–81. doi: 10.1016/j.jbi.2008.08.010 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 24.WHO. WHO recommendations on antenatal care for a positive pregnancy experience. 2017:1–196. [PubMed] [Google Scholar]
  • 25.Tochie JN, Choukem S-P, Langmia RN, Barla E, Koki-Ndombo P. Neonatal respiratory distress in a reference neonatal unit in Cameroon: an analysis of prevalence, predictors, etiologies and outcomes. Pan African Medical Journal. 2016;24(1). [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 26.Endrich O, Rimle C, Zwahlen M, Triep K, Raio L, Nelle M. Asphyxia in the newborn: evaluating the accuracy of ICD coding, clinical diagnosis and reimbursement: observational study at a Swiss tertiary care center on routinely collected health data from 2012–2015. PLoS One. 2017;12(1):e0170691. doi: 10.1371/journal.pone.0170691 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 27.Organization WH. Pocket book of hospital care for children: guidelines for the management of common childhood illnesses: World Health Organization; 2013. [PubMed] [Google Scholar]
  • 28.Jama WMAJ. World Medical Association Declaration of Helsinki: ethical principles for medical research involving human subjects. 2013;310(20):2191–4. doi: 10.1001/jama.2013.281053 [DOI] [PubMed] [Google Scholar]
  • 29.Abdallah Y, Namiiro F, Mugalu J, Nankunda J, Vaucher Y, McMillan D. Is facility based neonatal care in low resource setting keeping pace? A glance at Uganda’s National Referral Hospital. African Health Sciences. 2016;16(2):347–55. doi: 10.4314/ahs.v16i2.2 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 30.Muhe LM, McClure EM, Nigussie AK, Mekasha A, Worku B, Worku A, et al. Major causes of death in preterm infants in selected hospitals in Ethiopia (SIP): a prospective, cross-sectional, observational study. Lancet Global Health. 2019;7(8):e1130. doi: 10.1016/S2214-109X(19)30220-7 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 31.Iyoke CA, Lawani OL, Ezugwu EC, Ilechukwu G, Nkwo PO, Mba SG, et al. Prevalence and perinatal mortality associated with preterm births in a tertiary medical center in South East Nigeria. IJWH. 2014;6:881–8. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 32.Patel A, Kandasamy Y. Outcome of premature neonates born in a tertiary neonatal intensive care unit in Nairobi, Kenya. Journal of Pediatric and Neonatal Individualized Medicine (JPNIM). 2017;6(1):e060113–e. [Google Scholar]
  • 33.Hedstrom A, Ryman T, Otai C, Nyonyintono J, McAdams RM, Lester D, et al. Demographics, clinical characteristics and neonatal outcomes in a rural Ugandan NICU. BMC Pregnancy Childbirth. 2014;14:327. doi: 10.1186/1471-2393-14-327 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 34.Egesa WI, Odong RJ, Kalubi P, Yamile EAO, Atwine D, Turyasiima M, et al. Preterm Neonatal Mortality and Its Determinants at a Tertiary Hospital in Western Uganda: A Prospective Cohort Study. Pediatric Health, Medicine and Therapeutics. 2020;11:409. doi: 10.2147/PHMT.S266675 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 35.Yismaw AE, Gelagay AA, Sisay MM. Survival and predictors among preterm neonates admitted at University of Gondar comprehensive specialized hospital neonatal intensive care unit, Northwest Ethiopia. Italian Journal of Pediatrics. 2019;45(1):4. doi: 10.1186/s13052-018-0597-3 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 36.Basiri B, Ashari FE, Shokouhi M, Sabzehei MK. Neonatal Mortality and its Main Determinants in Premature Infants Hospitalized in Neonatal Intensive Care Unit in Fatemieh Hospital, Hamadan, Iran. Journal of Comprehensive Pediatrics. 2015;6(3). [Google Scholar]
  • 37.Moxon SG, Lawn JE, Dickson KE, Simen-Kapeu A, Gupta G, Deorari A, et al. Inpatient care of small and sick newborns: a multi-country analysis of health system bottlenecks and potential solutions. 2015;15(2):1–19. doi: 10.1186/1471-2393-15-S2-S7 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 38.Bulut C, Gürsoy T, Ovalı F. Short-Term Outcomes and Mortality of Late Preterm Infants. Balkan Medical Journal. 2016;33(2):198. doi: 10.5152/balkanmedj.2016.16721 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 39.Behrman RE, Butler AS. Mortality and acute complications in preterm infants. Preterm Birth: Causes, consequences, and prevention: National Academies Press (US); 2007. [PubMed] [Google Scholar]
  • 40.Mank A, van Zanten HA, Meyer MP, Pauws S, Lopriore E, Te Pas AB. Hypothermia in Preterm Infants in the First Hours after Birth: Occurrence, Course and Risk Factors. PLoS One. 2016;11(11). doi: 10.1371/journal.pone.0164817 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 41.Arunda M, Emmelin A, Asamoah BO. Effectiveness of antenatal care services in reducing neonatal mortality in Kenya: analysis of national survey data. Global Health Action. 2017;10(1). doi: 10.1080/16549716.2017.1328796 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 42.Gupta R, Talukdar BJJNB. Frequency and timing of antenatal care visits and its impact on neonatal mortality in EAG states of India. 2017;6(03):2167–0897.1000257. [Google Scholar]
  • 43.Bergenhenegouwen L, Meertens L, Schaaf J, Nijhuis J, Mol B, Kok M, et al. Vaginal delivery versus caesarean section in preterm breech delivery: a systematic review. European Journal of Obstetrics & Gynecology and Reproductive Biology. 2014;172:1–6. doi: 10.1016/j.ejogrb.2013.10.017 [DOI] [PubMed] [Google Scholar]
  • 44.Ghorbani F, Heidarzadeh M, Dastgiri S, Ghazi M, Rahkar Farshi MJIJoNI. Survival of premature and low birth weight infants: a multicenter, prospective, cohort study in Iran. 2017;8(1):16–22. [Google Scholar]
  • 45.Ashish K.C. W, Johan Nelin, Viktoria Ewald, Uwe Clark, Robert Målqvist, Mats. Level of mortality risk for babies born preterm or with a small weight for gestation in a tertiary hospital of Nepal. BMC Public Health. 2015;15. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 46.Xu F, Kong X, Duan S, Lv H, Ju R, Li Z, et al. Care Practices, Morbidity and Mortality of Preterm Neonates in China, 2013–2014: a Retrospective study. Sci Rep. 2019;9(19863):1–7. doi: 10.1038/s41598-019-56101-x [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 47.Phoya F, Langton J, Dube Q, Iroh Tam P-Y. Association of Neonatal Hypothermia with Morbidity and Mortality in a Tertiary Hospital in Malawi. Journal of Tropical Pediatrics. 2020;66(5):470–8. doi: 10.1093/tropej/fmz086 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 48.Mullany LC. Neonatal hypothermia in low-resource settings. Semin Perinatol. 2010;34(6):426–33. doi: 10.1053/j.semperi.2010.09.007 [DOI] [PMC free article] [PubMed] [Google Scholar]

Decision Letter 0

Lloyd J Tooke

3 Aug 2021

PONE-D-21-19132

Incidence and predictors of preterm neonatal mortality at Mbarara Regional Referral Hospital in South Western Uganda

PLOS ONE

Dear Dr. Tibaijuka

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.

Thank you for your interesting article. Please could you address the concerns from the 2 reviewers and re-submit.

Please submit your revised manuscript by 30 September. If you will need more time than this to complete your revisions, please reply to this message or contact the journal office at 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.

Please include the following items when submitting your revised manuscript:

  • 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: http://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,

Lloyd J. Tooke, MBChB, MMed(Paeds)

Academic Editor

PLOS ONE

Journal Requirements:

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

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 

https://journals.plos.org/plosone/s/file?id=wjVg/PLOSOne_formatting_sample_main_body.pdf and 

https://journals.plos.org/plosone/s/file?id=ba62/PLOSOne_formatting_sample_title_authors_affiliations.pdf

2. We note that you have referenced (ie. Bewick et al. [5]) which has currently not yet been accepted for publication. Please remove this from your References and amend this to state in the body of your manuscript: (ie “Bewick et al. [Unpublished]”) as detailed online in our guide for authors

http://journals.plos.org/plosone/s/submission-guidelines#loc-reference-style

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.

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

Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

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

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #1: Yes

Reviewer #2: Yes

**********

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

Reviewer #1: Yes

Reviewer #2: I Don't Know

**********

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

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #1: Yes

Reviewer #2: Yes

**********

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

PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.

Reviewer #1: Yes

Reviewer #2: Yes

**********

5. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #1: PLOS One – Comments to the Author

1. This is an important study on incidence of preterm neonatal mortality and predictors of mortality in a tertiary hospital in South Western Uganda. It highlighted the major predictors such as low antenatal attendance, Hypothermia and RDS and lack of Kangaroo mother care. The predicators identified could help to design appropriate interventions to reduce the preterm related Mortality in the Tertiary Insusitution.

2. The Abstract is well summarised , I would suggest improve the language in paragraph 1

3. The statistics is Rigorous and appropriate for the Study design

4. METHODS SECTION

5. Did we exclude the extreme low birth weight , were all the babies at 28 weeks one kilo and above , is that true, what of the babies born to PET mothers , Did we exclude the extreme low birth weight, if so why, this may affect the mortality rates.

It is surprising all the babies were all above one kilo

6. Did we do Bilirubin levels done, or did we try to use a Kramer Chart – Please clearly state the method of measurement of the Bilirubin Levels

7. The babies that had Respiratory distress sydromme, was it all in the first week

8. What was their time frame ( Between first week ) or was this involving those after one week , If after one week how would you differentiate between other diseases like sepsis or apnea of Prematurity from Respiratory Distress syndrome, because RDS seems to account for many Deaths and yet diseases like sepsis , donot account for very few deaths, which is surprising

9. How would you diagnose Nosocomial pneumonia, were blood Cultures done , What do you mean , Could that be late one set sepsis

10. When was the Hypothermia Diagnosed at the Time of admission or during the course of admission

Discussion

11. Introduction could be improved , by highlighting the purpose of the study, instead of reporting all the important significant Results in the First Paragraph

12. The Respiratory Distress sydromme , assessment, we would have used the SAS score , it has been used in Kiwoko Hospital

13. When did the Hypothermia Occur, was it birth or during the admission, because hypothermia on admission to the NICu is associated with mortality. This could be added to the explanation for hypothermia

14. The difference in the mortality could be explained by the Different levels of care in neonatology ( refer to article Survive and thrive, Inpatient care for small and sick newbor barriers By Hannah Blencowe 2015 )

15. The different interventions available in Mbarara , how do they differ with other the hospitals

16. RDS – major cause of mortality , more studies from Mulago could explain that ( Yaser et al 2012)

17. More explanation for Hypothermia, what prevents Hypothermia, do we have a warm chain, what interventions are available for Hypothermia apart from kangaroo mother care

18. Need to explain, why those that needed CPAP, Died , do we have a criteria for those that have failed CPAP, if so what do we do , do we refer , we need to explain in the discussion

Reviewer #2: Introduction:

This section is well written, however to increase clarity, in this sentence “It is stated that Interventions to prevent the occurrence of preterm birth are thus needed and studies focusing on this should be encouraged”, it would be useful to mention a few, since there are some of spontaneous preterm births with no cause which may not be easy to prevent.

Method:

Study site;

The section is well described; my few comments and questions are as follows

Please add information on the ANC attendance pattern in the study site, also availability of KMC ward and size.

Participant enrollment:

•Was the questionnaire used a newly developed by the researchers or an adopted version of questionnaire which is validated?

Data collection and follow up

•What time was the baseline information collected, was it after delivery or after arrival to newborn unit, this did not come out clearly.

•Authors stated that they used the first day of the last normal menstrual period (LNMP), known to be a more reliable measure of GA in a low-resource setting, however this is prone to recall bias especially if the literacy level is low, this has been a recurring problem in our unit as well, thus this can be cited as a limitation to the study. The use of Modified Ballard score could have added value.

•Suspected cause of death was used, why not actual cause of death since only deaths which occurred in hospital were analysed.

•For any neonates discharged alive before 28 days, post-discharge follow-up was done via a phone call at day 3, 7, 14 and 28, What was the reasons for frequent phone calls, is this part of standard of care? If not was this included in the consent form signed by parents/participants; please clarify.

•For those who died after discharge, one would have expected the deaths which occurred at home to have had verbal autopsy done to establish cause of death, this could have been possible since the deaths were confirmed by mobile phone. Was there a reason this was omitted?

Study variables:

•It would be very useful if the author could clearly clarify the followings in the definition of variables.

-Hypothermia: was this at admission or at any point after admission

-Sepsis: was this combining EOS and LOS ie sepsis diagnosis at any point?

-Hypoglycemia: at admission or any time after, also a cut off point of 2.2 was used, which seems too low, is there an explanation? WHO refers to <2.5mmol/L. also note there is a difference between plasma and blood glucose thus it is always useful to state clearly.

-ACS: any dose at any time before delivery?

-How was RDS differentiated from congenital pneumonia? Especially for mothers with risk factors. -There is also typo instead of starting, it is written staring

-What was the cut off for booking for ANC late? 2nd trimester third, please clarify.

Analysis:

•Were the interaction between variables examined in the Cox proportional hazards regression models; some of the factors seems to be correlated and can affect the outcomes. Ie a baby with sepsis may also present with hypothermia, jaundice. Also including both Birth asphyxia and Apgar score in the same model can cancel the effects. I would advice the Authors to check for correlation and interaction in the covariates included in the final models.

Results:

•Arrangement and labeling of tables and figures is a bit confusing. Ie what appears as table 1 in the result section I presume it should be labeled as table 3, please check.

•For all the tables and figures please include a footnote spelling out all the abbreviations used.

•The KM figures are not clear, title shows mortality probabilities, but the Y –axis shows cumulative survival, please check and rectify.

•It seems like very few-used CPAP (Ie 216 were diagnosed with RDS but only 96 received CPAP) was it because of availability? It would be informative for policy if the median survival time was shown among those with RDS who had access to CPAP Vs those who had no access.

• Under neonatal characteristics the proportion of babies with Sepsis is not shown.

•Neonatal morbidities contributing to death of preterm neonates, I am not sure if there is a clear line to differentiate NEC, nosocomial pneumonia and sepsis, it will be informative to the readers if the authors could say how they managed to do so.

•It is also important to specify of sepsis was based on symptoms or cultures, since in the definition of variable it was either or

•Preterm are prone to IVH and anemia, which contributes to increased mortality, were any of these observed in this study?

•Figure 2, I would advise to use only one curve, ie cumulative survival curve.

•Figure 2; the chart area will be seen more clearly if the font size for the texts was reduced.

•As much as results presented graphically are more visual, having a lot of KP curves around predictors is tiring. For preterm it will be more informative if the median survival time by infant demographics eg sex, GA (late, moderate and early preterm) or weight (LBW/SGA vs LBW/AGA)

•Figure 10 Need for ventilatory support with CPAP, it is obvious that those who needed CPAP may have been versus sick and thus have increased mortality. For policy implication it would be more meaningful to show if those who needed and had access vs those who needed but did not have an access

•I suggest table 4 be omitted, since What is presented in table 4 is a duplicate of what is presented in figure 2,

Predictors of mortality among preterm neonates;

•For strong predictors it will be useful to focus more on those with high aHR and significant CI. Eg Birth asphyxia (aHR 11.9), not receiving KMC(aHR 9.14), late initiation of BF (aHR 8.56), based on these results suggests investment in essential newborn care could reduce mortality in these babies

•Some of the confidence intervals are very wide ie birth asphyxia (aHR, 11.90; 95% CI: 4.08-34.70). Can the authors comment on this and the implication it has on their results and recommendations.

Discussion:

•It would have been more informative if the author could discuss in relation to feasible interventions to overcome the problems they identified. Ie based on the strong predictors enhancement of ENC should be more discussed, I guess many investors would give the money to improve this over postnatal surfactant, which has less value if ENC is not adequate.

References: 19, 37,40 and 42 need to be appropriately cited, they should clearly indicate the source; if they are from the internet then URL and date retrieved should be included.

**********

6. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files.

If you choose “no”, your identity will remain anonymous but your review may still be made public.

Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy.

Reviewer #1: No

Reviewer #2: No

[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.

Attachment

Submitted filename: PLOS ONE COMMENTS FOR MANUSCRIPT.docx

PLoS One. 2021 Nov 2;16(11):e0259310. doi: 10.1371/journal.pone.0259310.r002

Author response to Decision Letter 0


23 Aug 2021

RESPONSE TO ACADEMIC EDITOR’S COMMENTS

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

Response: The manuscript has been reformatted to be in accordance with the PLOS ONE style

2. We note that you have referenced (ie. Bewick et al. [5]) which has currently not yet been accepted for publication. Please remove this from your References and amend this to state in the body of your manuscript: (ie “Bewick et al. [Unpublished]”) as detailed online in our guide for authors

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.

Response: The reference list has been reviewed, we have ensured it is complete and correct.

RESPONSE TO REVIEWERS’ COMMENTS

3. This is an important study on incidence of preterm neonatal mortality and predictors of mortality in a tertiary hospital in South Western Uganda. It highlighted the major predictors such as low antenatal attendance, Hypothermia and RDS and lack of Kangaroo mother care. The predicators identified could help to design appropriate interventions to reduce the preterm related Mortality in the Tertiary Institution.

Response: We appreciate the reviewer for the positive comments.

4. The Abstract is well summarised, I would suggest improve the language in paragraph 1

Response: We have revised the language in the first paragraph to improve clarity. It now reads, “Preterm neonatal mortality contributes substantially to the high neonatal mortality globally. In Uganda, preterm neonatal mortality accounts for 31% of all neonatal deaths” (Page/Line: 2/20-21)

5. The statistics is Rigorous and appropriate for the Study design

Response: Thanks for the comment.

METHODS SECTION

6. Did we exclude the extreme low birth weight , were all the babies at 28 weeks one kilo and above , is that true, what of the babies born to PET mothers , Did we exclude the extreme low birth weight, if so why, this may affect the mortality rates.

It is surprising all the babies were all above one kilo

Response: Thank you for raising this concern. We had very few extreme LBW babies (11) and analysed them in the category of VLBW babies (<1.5kg). (Table 3: Page 13)

7. Did we do Bilirubin levels done, or did we try to use a Kramer Chart – Please clearly state the method of measurement of the Bilirubin Levels

Response: We combined both clinical and laboratory techniques to assess serum bilirubin levels including yellow discoloration of eyes, skin and mucous membranes, and serum bilirubin levels above 15mg/dL. (Page/line: 6/183-184)

8. The babies that had Respiratory distress syndrome, was it all in the first week

Response: Yes. Respiratory distress syndrome (RDS) occurred in the first week.

9. What was their time frame ( Between first week ) or was this involving those after one week , If after one week how would you differentiate between other diseases like sepsis or apnea of Prematurity from Respiratory Distress syndrome, because RDS seems to account for many Deaths and yet diseases like sepsis , do not account for very few deaths, which is surprising

Response: Same as in #8 above, the diagnosis of RDS was made within 4 hours of delivery, none was observed after one week.

10. How would you diagnose Nosocomial pneumonia, were blood Cultures done , What do you mean , Could that be late one set sepsis

Response: Nosocomial pneumonia was diagnosed basing on blood culture and localizing clinical features to the chest/ lungs (grunting, fast breathing, chest wall in-drawing, oxygen saturation of <90% on room air, with crepitations on auscultation). This indeed is late onset sepsis. However, we presented nosocomial pneumonia separate from neonatal sepsis and we have included this limitation. (Page/line: 8/186-188, 20/335-337)

11. When was the Hypothermia Diagnosed at the Time of admission or during the course of admission

Response: We considered hypothermia at the time of admission to the neonatal unit. This has been clarified. (Page/line: 8/180-181)

Discussion

12. Introduction could be improved , by highlighting the purpose of the study, instead of reporting all the important significant Results in the First Paragraph

Response: We agree with the reviewer. We have added information on the purpose of the study to the first paragraph of discussion. It now reads, “This study aimed to determine the incidence and predictors of preterm neonatal mortality in a tertiary hospital in South Western Uganda. The study highlights the major predictors such as birth asphyxia, not receiving kangaroo mother care (KMC), late initiation of breastfeeding, late ANC booking and lack of ANC attendance, vaginal breech delivery, very preterm birth, respiratory distress syndrome and hypothermia at the time of admission to the neonatal unit as increasing the risk of preterm neonatal mortality”. (Page/line: 18/267-268)

13. The Respiratory Distress syndrome assessment, we would have used the SAS score , it has been used in Kiwoko Hospital

Response: To diagnose respiratory distress syndrome, we based on WHO criteria. However, the Silverman-Andersen (SAS) score is routinely used at our institution to grade the severity of RDS before initiation of CPAP to infants with RDS.

14. When did the Hypothermia Occur, was it birth or during the admission, because hypothermia on admission to the NICU is associated with mortality. This could be added to the explanation for hypothermia

Response: Same as # 11 above, we considered hypothermia at the time of admission. We agree with the reviewer that hypothermia at the time of admission is associated with mortality and have the information in the discussion section. (Page/line: 20/310-312)

15. The difference in the mortality could be explained by the Different levels of care in neonatology ( refer to article Survive and thrive, Inpatient care for small and sick newborn barriers By Hannah Blencowe 2015 )

Response: This has been noted and referenced appropriately. (Page/line: 19/285-288)

16. The different interventions available in Mbarara , how do they differ with other the hospitals

Response: Mbarara Regional Referral Hospital is a low resource tertiary hospital serving the South-western Uganda. The different interventions available include phototherapy machines, warmers, oxygen therapy, continuous positive airway pressure (CPAP), Kangaroo mother care. These services are lacking in the peripheral facilities. This is highlighted in the study setting section. (Page/line: 5/105-109)

17. RDS – major cause of mortality , more studies from Mulago could explain that ( Yaser et al 2012)

Response: Thank you, we have included the suggested reference. (Page/Line: 19/300-302)

18. More explanation for Hypothermia, what prevents Hypothermia, do we have a warm chain, what interventions are available for Hypothermia apart from kangaroo mother care

Response: We have discussed the importance of essential new born care interventions including the warm chain and timely resuscitation of neonates when indicated. (Page/ Line: 20/314-317)

19. Need to explain, why those that needed CPAP, Died , do we have a criteria for those that have failed CPAP, if so what do we do , do we refer , we need to explain in the discussion

Response: We have acknowledged this limitation because no additional intervention was available following failed CPAP, this could have increased the contribution of RDS to mortality at our institution. (Page/line: 21/337-338)

Reviewer #2:

Introduction:

20. This section is well written, however to increase clarity, in this sentence “It is stated that Interventions to prevent the occurrence of preterm birth are thus needed and studies focusing on this should be encouraged”, it would be useful to mention a few, since there are some of spontaneous preterm births with no cause which may not be easy to prevent.

Response: We appreciate the reviewer’s comment. We have cited examples of interventions to prevent occurrence of preterm labor. (Page/line: 3/65-66)

Methods:

Study site:

The section is well described; my few comments and questions are as follows

21. Please add information on the ANC attendance pattern in the study site, also availability of KMC ward and size.

Response: The information on ANC attendance and KMC availability has been added. Page/line: 5/93-94 and 5/104

Participant enrollment:

22. Was the questionnaire used a newly developed by the researchers or an adopted version of questionnaire which is validated?

Response: The questionnaire was newly developed by the researchers basing on the research questions. We however pretested it before use for data collection. (Page/line: 6/131-132)

Data collection and follow up

23. What time was the baseline information collected, was it after delivery or after arrival to newborn unit, this did not come out clearly.

Response: We have clarified the point of entry into the study and collection of baseline information as after delivery. (Page/line: 6/132)

24. Authors stated that they used the first day of the last normal menstrual period (LNMP), known to be a more reliable measure of GA in a low-resource setting, however this is prone to recall bias especially if the literacy level is low, this has been a recurring problem in our unit as well, thus this can be cited as a limitation to the study. The use of Modified Ballard score could have added value.

Response: We agree with the reviewer the use of Modified Ballard could have added value. We have cited the limitation arising from using LNMP to establish gestational age. (Page/line: 20/334-335)

25. Suspected cause of death was used, why not actual cause of death since only deaths which occurred in hospital were analyzed.

Response: We used the term “suspected” cause of death because we relied on clinical cause of death since postmortem examinations were not performed for the neonates who died. (Page/line: 21/338-340)

26. For any neonates discharged alive before 28 days, post-discharge follow-up was done via a phone call at day 3, 7, 14 and 28. What was the reasons for frequent phone calls, is this part of standard of care? If not was this included in the consent form signed by parents/participants; please clarify.

Response: The phone calls at day 3, 7, 14 and 28 were not part of standard of care. The calls were aimed at keeping close contact with the study participants and to obtain the required information. This was included in the consent form signed by the parents/participants.

27. For those who died after discharge, one would have expected the deaths which occurred at home to have had verbal autopsy done to establish cause of death, this could have been possible since the deaths were confirmed by mobile phone. Was there a reason this was omitted?

Response: Verbal autopsies were carried out on phone, however, the findings were inconclusive and we categorized the deaths that occurred at home as unknown. Of the 6 neonates who died at home, 2 were reported to have died following a febrile illness, while the other 4 were reported to have been well but found dead in the bed. (Page/line: 15/248-250)

Study variables:

28. It would be very useful if the author could clearly clarify the followings in the definition of variables.

-Hypothermia: was this at admission or at any point after admission

Response: Hypothermia was at the time of admission to the neonatal unit. This has been clarified in the definition of variables. (Page/line: 8/180-181)

-Sepsis: was this combining EOS and LOS i.e. sepsis diagnosis at any point?

Response: Yes. Sepsis accounted for any sepsis diagnosed at any point. This has been clarified in the definition of variables. (Page/line: 8/184-186)

-Hypoglycemia: at admission or any time after, also a cut-off point of 2.2 was used, which seems too low, is there an explanation? WHO refers to <2.5mmol/L. also note there is a difference between plasma and blood glucose thus it is always useful to state clearly.

Response: We used capillary blood from a heel prick for blood glucose testing using an electronic glucometer and classified hypoglycaemia as glucose <2.2mmol/l as is the routine cutoff used at the neonatal unit of Mbarara Regional Referral Hospital. This is clarified. (Page/line: 8/181-183)

-ACS: any dose at any time before delivery?

Response: Antenatal corticosteroid use was defined as having received any dose of corticosteroids at any time within 7 days before delivery. This has been clarified in the definition of variables. (Page/line: 8/173-175)

-How was RDS differentiated from congenital pneumonia? Especially for mothers with risk factors.

Response: Thank you for raising the crucial challenge of potentially mixing up diagnoses for newborns congenital chest infection and RDS. However, when we reviewed babies at a higher risk of congenital pneumonia due to being born to women with chorioamnionitis (n=9), none had RDS.

-There is also typo instead of starting, it is written staring

Response: The typographical error has been edited. (Page/line: 7/179)

-What was the cut off for booking for ANC late? 2nd trimester third, please clarify.

Response: The cut offs for antenatal booking were defined as; first trimester booking (first antenatal visit before 13 weeks of gestation), second trimester booking (between 13 to 26 weeks of gestation) and third trimester booking (≥ 27 weeks of gestation). We considered late ANC booking as ≥13 weeks of gestation. This has been clarified in the manuscript. (Page/line: 7/175-177)

Analysis:

29. Were the interaction between variables examined in the Cox proportional hazards regression models; some of the factors seems to be correlated and can affect the outcomes i.e., a baby with sepsis may also present with hypothermia, jaundice. Also including both Birth asphyxia and Apgar score in the same model can cancel the effects. I would advise the Authors to check for correlation and interaction in the covariates included in the final models.

Response: The interaction and correlation between the variables in the Cox proportional hazards regression models were examined. There was no correlation and interaction between the variables in the multivariable model. Sepsis and jaundice were not correlated. Similarly, there was no correlation and interaction between sepsis and hypothermia at the time of admission. We however, noted correlation between birth asphyxia and Apgar score at 5 minutes, we therefore dropped Apgar score at 5 minutes from the final model. This did not alter the results as shown in table 4. (Page: 16)

Results:

30. Arrangement and labeling of tables and figures is a bit confusing. i.e what appears as table 1 in the result section I presume it should be labeled as table 3, please check.

Response: The tables are labelled as follows; table 1: sample size calculation (this is within the text), table 2: Baseline socio-demographic and obstetric characteristics, table 3: Characteristics of preterm neonates, table 4: Cumulative mortality incidence of preterm neonates, table 5: Predictors of mortality among preterm neonates born at Mbarara Regional Referral Hospital

31. For all the tables and figures please include a footnote spelling out all the abbreviations used.

Response: The footnotes have been included for all tables and figures as advised.

32. The KM figures are not clear, title shows mortality probabilities, but the Y –axis shows cumulative survival, please check and rectify.

Response: The KM curves presented depict the declining survival probabilities which mirrors the increasing mortality probabilities overtime. We thought presenting the decreasing survival on the Y-axis would be easily interpreted by the reader as commonly presented in the publications.

33. It seems like very few-used CPAP (i.e., 216 were diagnosed with RDS but only 96 received CPAP) was it because of availability? It would be informative for policy if the median survival time was shown among those with RDS who had access to CPAP Vs those who had no access.

Response: All neonates with RDS that required CPAP during the study period received it (n=96). Majority of the neonates with RDS only required respiratory support with supplemental oxygen therapy. We acknowledge that the legend of Fig. 10, the Kaplan Meier curve for CPAP “Need for CPAP” may be misleading, it was meant to represent the neonates who required and received CPAP versus those who did not require CPAP. We have corrected the legend for Fig. 10 and presented the KM curves ventilatory support with CPAP across preterm neonates with RDS who required and received CPAP versus those who did not. Fig 10. (Page: 31)

34. Under neonatal characteristics the proportion of babies with Sepsis is not shown.

Response: This proportion is in the row number 5 of the neonatal morbidities in table 3. The portion of neonates with neonatal sepsis was 83/538 (15.4%). (Page: 13)

35. Neonatal morbidities contributing to death of preterm neonates, I am not sure if there is a clear line to differentiate NEC, nosocomial pneumonia and sepsis, it will be informative to the readers if the authors could say how they managed to do so.

Response: Differentiating necrotizing enterocolitis (NEC) and nosocomial pneumonia from sepsis may be challenging. However, basing on the 2013 WHO guidelines for diagnosis of childhood illnesses, NEC was diagnosed basing on clinical features of abdominal distension and tenderness, intolerance to feeding, bilious vomitus or fluid up the nasogastric tube, bloody stools and abdominal x-ray findings of air bubbles in the intestinal walls. This has been highlighted in the definition of variables. (Page/line: 8/189-191)

Same as in #10 above, nosocomial pneumonia was diagnosed basing on blood culture and localizing clinical features to the chest (grunting, fast breathing, chest wall in-drawing, oxygen saturation of <90% on room air, with crepitations on auscultation). This indeed is late onset sepsis. However, we presented nosocomial pneumonia separate from neonatal sepsis and we have included this limitation. (Page/line: 8/186-188, 20/335-337)

36. It is also important to specify if sepsis was based on symptoms or cultures, since in the definition of variable it was either or

Response: Sepsis diagnosis was based on the presence of clinical features suggestive of sepsis according to the WHO’s Integrated Management of Childhood Illnesses (IMCI) algorithm and blood cultures. This has been clarified under variable definition. (Page/line: 8/184-186)

37. Preterm are prone to IVH and anemia, which contributes to increased mortality, were any of these observed in this study?

Response: It is true IVH and anemia are common occurrences in preterm neonates. These were however not observed in this study.

38. Figure 2, I would advise to use only one curve, i.e. cumulative survival curve.

Response: This is noted. The cumulative mortality curve has been dropped as advised.

39. Figure 2; the chart area will be seen more clearly if the font size for the texts was reduced.

Response: The chart is now clearer after dropping the cumulative mortality curve and formatting the figures. (Page: 14)

40. As much as results presented graphically are more visual, having a lot of KP curves around predictors is tiring. For preterm it will be more informative if the median survival time by infant demographics e.g. sex, GA (late, moderate and early preterm) or weight (LBW/SGA vs LBW/AGA)

Response: We conducted the statistical analyses for the median survival time by the different infant demographics. However the median survival time is not reached for any of the infant demographics above. We have therefore maintained the KM curves.

41. Figure 10 Need for ventilatory support with CPAP, it is obvious that those who needed CPAP may have been versus sick and thus have increased mortality. For policy implication it would be more meaningful to show if those who needed and had access vs those who needed but did not have an access

Response: As in #33 above, all neonates with RDS that required CPAP during the study period received it (n=96). Majority of the neonates with RDS only required respiratory support with supplemental oxygen therapy. We acknowledge the miss representation of the KM curve for CPAP in Fig. 10 as “Need for CPAP”, it was meant to represent the neonates who required and received CPAP versus those who did not require CPAP. We have corrected the legend for Fig. 10 and presented the KM curves for ventilatory support with CPAP across preterm neonates with RDS who received CPAP versus those who did not. (Page: 31)

42. I suggest table 4 be omitted, since What is presented in table 4 is a duplicate of what is presented in figure 2,

Response: Table 4 has been omitted as suggested.

Predictors of mortality among preterm neonates;

43. For strong predictors it will be useful to focus more on those with high aHR and significant CI. Eg Birth asphyxia (aHR 11.9), not receiving KMC (aHR 9.14), late initiation of BF (aHR 8.56), based on these results suggests investment in essential newborn care could reduce mortality in these babies

Response: This has been noted. We have focused more on the strong predictors with high aHR as recommended. Essential newborn care has been emphasized in the discussion as recommended. (Page/line: 15/256-263)

44. Some of the confidence intervals are very wide i.e. birth asphyxia (aHR, 11.90; 95% CI: 4.08-34.70). Can the authors comment on this and the implication it has on their results and recommendations.

Response: Some of the confidence intervals are wide (for example for birth asphyxia and late initiation of breastfeeding) which implied loss of precision due to small numbers of participants with birth asphyxia and those with early initiation of breastfeeding. However we believe that our findings are informative because the lower boundaries of these confidence intervals for each of the point estimates are above two-fold.

Discussion:

45. It would have been more informative if the author could discuss in relation to feasible interventions to overcome the problems they identified i.e. based on the strong predictors enhancement of ENC should be more discussed, I guess many investors would give the money to improve this over postnatal surfactant, which has less value if ENC is not adequate.

Response: We agree with the reviewer and have included this information in the discussion section. (Page/line: 20/314-317)

46. References: 19, 37, 40 and 42 need to be appropriately cited, they should clearly indicate the source; if they are from the internet then URL and date retrieved should be included.

Response: The references 19, 37, 40 and 42 have been appropriately cited and the source has been clearly indicated.

Attachment

Submitted filename: RESPONSE TO REVIEWERS.docx

Decision Letter 1

Sajid Bashir Soofi

11 Oct 2021

PONE-D-21-19132R1Incidence and predictors of preterm neonatal mortality at Mbarara Regional Referral Hospital in South Western UgandaPLOS ONE

Dear Dr. Tibaijuka,

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 MINOR revised version of the manuscript that addresses the points raised during the review process.

==============================

Thank you for submitting revised manuscript. You have addressed most of comments raised by the reviewers. Please could you address the concerns from the reviewer 1 and re-submit.

==============================

Please submit your revised manuscript by October 31, 2021. If you will need more time than this to complete your revisions, please reply to this message or contact the journal office at 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.

Please include the following items when submitting your revised manuscript:

  • 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,

Sajid Bashir Soofi

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 (if provided):

Thank you for submitting your revised manuscript to PLOS ONE. But reviewer has some minor comments, please submit a revised version of the manuscript that addresses the points raised during the review process.

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

Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. If the authors have adequately addressed your comments raised in a previous round of review and you feel that this manuscript is now acceptable for publication, you may indicate that here to bypass the “Comments to the Author” section, enter your conflict of interest statement in the “Confidential to Editor” section, and submit your "Accept" recommendation.

Reviewer #2: (No Response)

Reviewer #3: (No Response)

**********

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

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #2: Yes

Reviewer #3: Yes

**********

3. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #2: Yes

Reviewer #3: Yes

**********

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

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #2: Yes

Reviewer #3: (No Response)

**********

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

PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.

Reviewer #2: Yes

Reviewer #3: Yes

**********

6. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #2: Most of the comments have been sufficiently addressed except the following

1. Labeling of the tables reviewer responded that "The tables are labelled as follows; table 1: sample size calculation (this is within the text), table 2: Baseline socio-demographic and obstetric characteristics, table 3: Characteristics of preterm neonates, table 4: Cumulative mortality incidence of preterm neonates, table 5: Predictors of mortality among preterm neonates born at Mbarara Regional Referral Hospital .

however in the document table section they are labeled as table 2, table 1, table 2 then table 5, please correct.

2. Wide confidence interval as this could results in loss of precision should at least be mentioned to caution the readers.

3. Based on the objective of the study "to determine the incidence and predictors of preterm

neonatal mortality" i am not convinced that KM curves for each risk factor is necessary especially since they are not adjusted. Multvariate cox regression answer the question well. KM curves could be attached as supplementary material if needed.

Reviewer #3: well articulated manuscript on an important public health subject especially in the settings where the study is carried out .

the paper highlights important interventions required to improve preterm outcomes.

recommend it for publication and dissemination

**********

7. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files.

If you choose “no”, your identity will remain anonymous but your review may still be made public.

Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy.

Reviewer #2: No

Reviewer #3: Yes: Shabina Ariff

[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. 2021 Nov 2;16(11):e0259310. doi: 10.1371/journal.pone.0259310.r004

Author response to Decision Letter 1


11 Oct 2021

RESPONSE TO REVIEWERS’ COMMENTS

Reviewer #2: Most of the comments have been sufficiently addressed except the following

1. Labelling of the tables reviewer responded that "The tables are labelled as follows; table 1: sample size calculation (this is within the text), table 2: Baseline socio-demographic and obstetric characteristics, table 3: Characteristics of preterm neonates, table 4: Cumulative mortality incidence of preterm neonates, table 5: Predictors of mortality among preterm neonates born at Mbarara Regional Referral Hospital. However in the document table section they are labelled as table 2, table 1, table 2 then table 5, please correct.

Response: This is noted and has been corrected. The tables are now labelled as follows; table 1: Sample size calculation, table 2: Baseline socio-demographic and obstetric characteristics, table 3: Characteristics of preterm neonates, table 4: Predictors of mortality among preterm neonates born at Mbarara Regional Referral Hospital.

2. Wide confidence interval as this could results in loss of precision should at least be mentioned to caution the readers.

Response: We acknowledge this limitation and have stated it as such. (Page/Line: 21/338-340)

3. Based on the objective of the study "to determine the incidence and predictors of preterm neonatal mortality", I am not convinced that KM curves for each risk factor is necessary especially since they are not adjusted. Multivariate cox regression answer the question well. KM curves could be attached as supplementary material if needed.

Response: We acknowledge that multivariable cox regression models answer the objective of this study and that KM curves are not adjusted. We have therefore attached the KM curves as supplementary material as advised.

Reviewer #3: Well articulated manuscript on an important public health subject especially in the settings where the study is carried out. The paper highlights important interventions required to improve preterm outcomes.

Recommend it for publication and dissemination.

Response: We appreciate the reviewer for the positive comments.

Attachment

Submitted filename: RESPONSE TO REVIEWERS.docx

Decision Letter 2

Sajid Bashir Soofi

18 Oct 2021

Incidence and predictors of preterm neonatal mortality at Mbarara Regional Referral Hospital in South Western Uganda

PONE-D-21-19132R2

Dear Dr. Leevan Tibaijuka

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 for payment will follow shortly after the formal acceptance. To ensure an efficient process, please log into Editorial Manager at http://www.editorialmanager.com/pone/, click the 'Update My Information' link at the top of the page, and double check that your user information is up-to-date. If you have any billing related questions, 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,

Prof Sajid Bashir Soofi

Academic Editor

PLOS ONE

Additional Editor Comments (optional):

Reviewers' comments:

Acceptance letter

Sajid Bashir Soofi

20 Oct 2021

PONE-D-21-19132R2

Incidence and predictors of preterm neonatal mortality at Mbarara Regional Referral Hospital in South Western Uganda

Dear Dr. Tibaijuka:

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

If your institution or institutions have a press office, please let them know about your upcoming paper now to help maximize its impact. If they'll be preparing press materials, please inform our press team within the next 48 hours. 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.

If we can help with anything else, please email us at plosone@plos.org.

Thank you for submitting your work to PLOS ONE and supporting open access.

Kind regards,

PLOS ONE Editorial Office Staff

on behalf of

Professor Sajid Bashir Soofi

Academic Editor

PLOS ONE

Associated Data

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

    Supplementary Materials

    S1 Fig

    (TIF)

    S2 Fig

    (TIF)

    S3 Fig

    (TIF)

    S4 Fig

    (TIF)

    S5 Fig

    (TIF)

    S6 Fig

    (TIF)

    S7 Fig

    (TIF)

    S1 Dataset

    (DTA)

    Attachment

    Submitted filename: PLOS ONE COMMENTS FOR MANUSCRIPT.docx

    Attachment

    Submitted filename: RESPONSE TO REVIEWERS.docx

    Attachment

    Submitted filename: RESPONSE TO REVIEWERS.docx

    Data Availability Statement

    All relevant data are within the paper and its Supporting Information files.


    Articles from PLoS ONE are provided here courtesy of PLOS

    RESOURCES