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

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 [10-14]. 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 [10-16]. 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.

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).

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).

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, 41–47]. 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.

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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

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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.

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Submitted filename: PLOS ONE COMMENTS FOR MANUSCRIPT.docx

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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.

Submitted filename: RESPONSE TO REVIEWERS.docx

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11 Oct 2021

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

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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

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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.

Submitted filename: RESPONSE TO REVIEWERS.docx

Click here for additional data file.

18 Oct 2021

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

PONE-D-21-19132R2

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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:

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