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. 2021 Aug 5;16(8):e0255352. doi: 10.1371/journal.pone.0255352

ELBW and ELGAN outcomes in developing nations–Systematic review and meta-analysis

Viraraghavan Vadakkencherry Ramaswamy 1, Thangaraj Abiramalatha 2, Tapas Bandyopadhyay 3,*, Nasreen Banu Shaik 1, Prathik Bandiya 4, Debasish Nanda 5, Abdul Kareem Pullattayil S 6, Srinivas Murki 7, Charles Christoph Roehr 8,9,10
Editor: Harald Ehrhardt11
PMCID: PMC8342042  PMID: 34352883

Abstract

Context

Morbidity and mortality amongst extremely low birth weight (ELBW) and extremely low gestational age neonates (ELGANs) in developing nations has not been well studied.

Objectives

Evaluate survival until discharge, short- and long-term morbidities of ELBW and ELGANs in LMICs.

Data sources

CENTRAL, EMBASE, MEDLINE and Web of Science.

Study selection

Prospective and retrospective observational studies were included.

Data extraction and synthesis

Four authors extracted data independently. Random-effects meta-analysis of proportions was used to synthesize data, modified QUIPS scale to evaluate quality of studies and GRADE approach to ascertain the certainty of evidence (CoE).

Results

192 studies enrolling 22,278 ELBW and 18,338 ELGANs were included. Survival was 34% (95% CI: 31% - 37%) (CoE–low) for ELBW and 39% (34% - 44%) (CoE—moderate) for ELGANs. For ELBW neonates, the survival for low-income (LI), lower middle-income (LMI) and upper middle income (UMI) countries was 18% (11% - 28%), 28% (21% - 35%) and 39% (36% - 42%), respectively. For ELGANs, it was 13% (8% - 20%) for LI, 28% (21% - 36%) for LMI and 48% (42% - 53%) for UMI countries. There was no difference in survival between two epochs: 2000–2009 and 2010–2020. Except for necrotising enterocolitis [ELBW and ELGANs—8% (7% - 10%)] and periventricular leukomalacia [ELBW—7% (4% - 11%); ELGANs—6% (5%-7%)], rates of all other morbidities were higher compared to developed nations. Rates of neurodevelopmental impairment was 17% (7% - 34%) in ELBW neonates and 29% (23% - 37%) in ELGANs.

Limitations

CoE was very low to low for all secondary outcomes.

Conclusions

Mortality and morbidity amongst ELBW and ELGANs is still a significant burden in LMICs. CoE was very low to low for all the secondary outcomes, emphasizing the need for high quality prospective cohort studies.

Trial registration

PROSPERO (CRD42020222873).

Introduction

Prematurity is one of the leading causes of childhood mortality, rates of which are on the rise across the globe [1–4]. Available data indicate that about 80% of the preterm births happen in the geographical regions of Africa and South Asia [2, 3]. When countries are grouped by their World Bank income categories, it is found that approximately 90% of all preterm births occurs in low‐ and middle‐income countries (LMICs). The average preterm birth rate for LMICs is close to 9–12%, compared to approximately 9% for most of high‐income countries (HICs) [4].

The quantum of impact on decreasing the neonatal mortality rate (NMR) is more pronounced when community based interventions targeting the late preterm and term neonates are implemented successfully across LMICs [1]. It is estimated that about 80% of neonatal deaths can be thwarted in LMICs by achieving a 95% coverage rate of simple neonatal interventions such as neonatal resuscitation, avoiding hypothermia, clean cord practices, kangaroo mother care as well as supporting breast feeding, clubbed with antenatal practices [1]. Henceforth, higher level NICU care targeting extremely low birth weight (ELBW) neonates with a birth weight of less than 1000 grams and extremely low gestational age neonates (ELGANs) born at less than 28 weeks’ gestation might not be a priority as of now in many LMICs.

Every Newborn action plan by WHO envisages reducing national NMR to 12 per 1000 live births by the year 2030 [5]. Historical trends of NMR from developed nations reveal that once a NMR of 15 per 1000 live births is attained, augmenting community based health programmes with facility based neonatal care through establishment of higher level NICUs would facilitate achieving single digit NMR in LMICs [6]. Improved survival rates amongst ELBW and ELGANs in LMICs with such an approach might also be associated with increased rates of typical morbidities of prematurity, including bronchopulmonary dysplasia (BPD), retinopathy of prematurity (ROP) and long term neurodevelopmental impairment (NDI) [7–10]. While previous systematic reviews have tried to quantify the burden of mortality and morbidity in high risk neonates including preterm infants from LMICs, none have been published till date with exclusive focus on the particularly vulnerable group of ELBW neonates and ELGANs [11–13]. Assessing the burden of mortality and morbidity in these infants is vital in developing future newborn targeted health interventions and policies, especially for those LMICs that are transitioning from community based care to a facility based one. Hence, this systematic review and meta-analysis was conducted to study the survival, short- and long-term outcomes of ELGANs and ELBW neonates from LMICs.

Methods

The protocol for the systematic review was registered with PROSPERO (CRD42020222873) [14]. The reporting of the review is in accordance with PRISMA guidelines [15].

Literature search

Electronic databases: MEDLINE, EMBASE, Web of Science and Cochrane CENTRAL were searched from 1st January 2000 till 21st November 2020. There were no language restrictions. Google translate (California, USA) was used for translating non-English literature. Studies published in Urdu and Persian were translated with the help of a translator as there were some limitations in Google translate for these languages. Studies published as abstracts were also eligible for inclusion. Only published data was used in this systematic review. Four authors (TA, NBS and PB, DN) conducted the literature search independently in pairs of two using Rayyan-QCRI software [16]. The search strategy for the different databases is provided in S1 Table in S1 File.

Inclusion criteria

Retrospective as well as prospective observational studies that had reported on outcomes of ELGANs (born at less than 28 weeks’ of gestation) and / or ELBW neonates (birth weight of less than 1000 grams) from a LMIC as per the World Bank country classifications by income levels (2020) were eligible for inclusion [17]. Randomized controlled trials were excluded as certain ELGANs and ELBW neonates who would otherwise have been eligible for inclusion might have been excluded due to a variety of reasons such as stringent inclusion criteria, refusal of consent and presence of co-morbid conditions among others.

Outcomes

The primary outcome of the review was proportion of neonates who had survived until discharge. Secondary outcomes included prevalence of intraventricular hemorrhage (IVH) (> grade II) [18], periventricular leukomalacia (PVL) (any severity), necrotizing enterocolitis (NEC) (stage II or more) [19], PDA requiring surgical or medical treatment, BPD [oxygen requirement at 36 weeks’ postmenstrual age (PMA)], sepsis (early onset and late onset sepsis) diagnosed based on blood culture as well as on other blood markers, ROP (any ROP, ROP stage ≥ 2 as per ICROP classification [20], ROP requiring laser therapy or intravitreal bevacizumab), extrauterine growth retardation (EUGR) (defined as weight less than 10th centile at 36 weeks’ PMA), any NDI (as defined by authors) and cerebral palsy of any severity, both assessed at 18–24 months’ corrected age.

Risk of bias (ROB) assessment

The risk of bias assessment was done using a modified QUIPS scale [21]. Four parameters namely, representativeness of the sample, definition and assessment of the outcomes, evaluation of baseline characteristics of the enrolled subjects known to affect the outcomes and method of data collection were evaluated. Studies that had satisfied all the four criteria were classified as having a low risk of bias. Those fulfilling two or three criteria were adjudged as having an intermediate risk of bias and those satisfying one or none were classified as high risk of bias studies. Two authors (TA, NBS) evaluated the risk of bias independently. Disagreements were resolved by consulting a third author (VVR).

Data collection and synthesis

The data for relevant outcomes were extracted using a pre-specified proforma by two authors independently (PB, DN). Statistical analysis was done using the R-Software. Meta-analysis of proportions was used for synthesis of data. Raw data was used if the proportions were between 0.20 to 0.80. Otherwise, data was logit transformed. Freeman-Tukey Double arcsine transformation of data was preferred over logit transformation when there were many proportions with 0 or 1 values. ‘Metaprop’ package in R-software was used for meta-analysis of proportions. ‘Metaprop’ can analysis meta-analysis of raw data based on proportions as well as convert raw data to logit transformation or Freeman-Tukey Double arcsine transformation and re-transform to proportions by default for meaningful interpretation. A random effects model was chosen as significant heterogeneity was anticipated as reported in prior studies on newborn survival [22]. An inverse variance method was chosen with DerSimonian Liard estimator being used for assessing between study variance [23]. The final estimates were expressed as proportions with 95% confidence interval.

Certainty of evidence (CoE) assessment

CoE was assessed using a modified GRADE approach [24]. Outcomes from prospective studies started as high quality evidence and other type of studies as low. The parameters of risk of bias, inconsistency, imprecision, indirectness and publication bias were evaluated for downgrading the evidence further. I2 value was used to adjudge significant heterogeneity. Imprecision was evaluated based on the point estimate and the 95% confidence interval. If these were to cross a decision threshold to intervene, the CoE was downgraded by one level for imprecision. Though publication bias assessment in meta-analysis of prognosis studies is a contentious topic, we assessed publication bias using funnel plots and Begg’s rank test based on GRADE working group guidelines [24, 25].

Sensitivity analyses

The following sensitivity analyses were performed for the primary outcome

  • Categorizing studies from countries based on three income levels–low income (LI), lower middle-income (LMI) and upper middle-income (UMI).

  • Categorizing studies based on geographical regions where they are situated.

  • Excluding studies with low sample size (less than 50 subjects).

  • Comparison of survival between two time periods—epoch 1: 2000–2009 and epoch 2: 2010–2019.

  • Analyzing studies which had evaluated neonates with varying baseline sickness.

Results

A total of 21,535 studies were identified from the literature search, of which 2157 full texts were assessed for eligibility after removal of duplicates as well as title, abstract screening and 192 studies (ELBW neonates– 22,278; ELGANs– 18,338) were included in the final synthesis (S1 File references 1–192). The PRISMA flow is given in Fig 1. Ninety-two studies with 13,667 ELBW and sixty studies enrolling 8,412 ELGANs had reported on the primary outcome measure of survival until discharge. The included studies were predominantly from middle-income countries. Studies from twenty-four countries situated in six geographical regions namely, Asia, Africa, Europe, Middle East, North America and South America had reported on survival for ELGANs. Similarly, studies from thirty-one countries located in seven different geographical regions (aforementioned regions along with Caribbean) had reported on survival for ELBW neonates. There was a preponderance of studies published from Brazil, China, India, Iran and South Africa. The denominator of the primary outcome measure (live births versus NICU admissions) and level of NICU care were inconsistently reported. Only five studies with 273 ELGANs and ELBW neonates had assessed the long-term neurodevelopmental outcomes at 24 months’ corrected age. The characteristics of included studies is given in Table 1.

Fig 1. PRISMA flow.

Fig 1

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Table 1. Characteristics of included studies.

AUTHOR/YEAR REGION COUNTRY INCOME CLASSIFICATION ELGAN / ELBW PERIOD OF STUDY SAMPLE SIZE
Abdul-Mumin 2020 Africa Ghana LMI Both 2017 ELGAN-20, ELBW-21
Adegoke 2014 Africa Nigeria LMI Both 2012–2013 ELGAN-15, ELBW-19
Adhikari 2017 Asia Nepal LMI ELBW 2014–2015 38
Adinma 2013 Africa Nigeria LMI ELGAN 2000–2009 2
Afjeh 2013 Middle East Iran UMI Both 2007–2010 ELGAN-196, ELBW-147
Afjeh 2017 Middle East Iran UMI Both 2011–2014 ELGAN-203, ELBW-156
Aggarwal 2002 Asia India LMI ELBW 1999–2000 12
Ahlsen 2015 Africa Malawi LI ELBW 2012 45
Ahmeti 2010 Europe Kosovo UMI ELBW 2002 73
Ali 2019 Asia Pakistan LMI ELBW 2016–2017 200
Ali 2016 Asia Bangladesh LMI ELBW 2013–2014 113
Alizadeh 2015 Middle East Iran UMI Both 2005–2010 ELGAN-32, ELBW-17
Altamemmi 2019 Middle East Iraq UMI ELBW 2003–2008 32
Amadi 2019 Africa Nigeria LMI ELGAN NA 15
Amadi2015 Africa Nigeria LMI ELBW 2011–2014 22
Andegiorgish 2020 Africa Eritrea LI ELBW 2016 22
Araz-Ersan 2013 Middle East Turkey UMI Both 1996–2010 ELGAN-283, ELBW-410
Arnold 2010 Africa South Africa UMI ELBW 1992–1995 18
Atalay 2013 Middle East Turkey UMI ELBW 2010 ELBW-20
Atasay2003 Middle East Turkey UMI Both 1997–2000 ELGAN-37, ELBW-31
Azeredo Cardoso 2013 South America Brazil UMI ELBW 2002–2006 305
Bajaj 2020 Asia India LMI ELBW 2017–2019 97
Ballot 2010 Africa South Africa UMI ELBW 2006–2007 143
Ballot 2012 Africa South Africa UMI ELBW 2006–2007 95
Ballot 2017 Africa South Africa UMI ELBW 2013–2016 546
Ballot 2017a Africa South Africa UMI ELBW 2013 34
Bas 2015 Middle East Turkey UMI Both 2011–2013 ELGAN-3737, ELBW-2694
Bas 2018 Middle East Turkey UMI Both 2016–2017 ELGAN-1539, ELBW-1109
Basiri 2015 Middle East Iran UMI Both 2012 ELGAN-68, ELBW-64
Basu 2008 Asia India LMI Both NA ELGAN-46, ELBW-45
Bhunwal 2018 Asia India LMI Both 2012–2013 ELGAN-16, ELBW-34
Bokade 2018 Asia India LMI ELBW 2016–2017 47
Bolat 2012 Middle East Turkey UMI ELBW 2009–2011 59
Bonotto 2007 South America Brazil UMI ELGAN 1992–1999 12
Boo 2012 Asia Malaysia UMI Both 2007 ELGAN-1246, ELBW-1051
Braimah 2020 Africa Ghana LMI Both 2018–2019 ELGAN-28, ELBW-20
Buenos Aires 2012 South America Argentina UMI Both 2008–2010 ELGAN-426, ELBW-451
Carneiro 2012 South America Brazil UMI ELBW 2007–2010 57
Castro 2007 South America Brazil UMI ELBW 2002–2003 270
Cauicharagon 2017 North America Mexico UMI ELGAN 2005–2014 2
Cenkcelebi 2014 Mideast Turkey UMI ELBW 2010–2013 235
Cetinkaya 2014 Mideast Turkey UMI ELBW 2011–2013 197
Chaudhari 2009 Asia India LMI Both 2000–2006 ELGAN-58, ELBW-58
Chen 2019 Asia China UMI ELBW 2016–2018 284
Chen 2012 Asia China UMI ELGAN 2005–2006 95
Chen 2015 Asia China UMI ELBW 2010–2012 161
Chiabi 2014 Africa Cameroon Both 2003–2011 ELGAN-75, ELBW-74
Chidiebere 2018 Africa Nigeria LMI ELBW 2013–2016 20
Chioukh 2018 Africa Tunisia LMI ELGAN 2012–2013 109
Coyles 2020 Africa South Africa UMI ELBW 2013–2015 104
Dearaujo 2007 South America Brazil UMI Both 1998–2004 ELGAN-30, ELBW-61
Debritoa 2003 South America Brazil UMI Both 1997–2000 ELGAN-70, ELBW-79
Decarvalho 2007 South America Brazil UMI ELGAN 2002–2004 108
Demello 2007 South America Brazil UMI Both 1991–2000 ELGAN-51, ELBW-60
Gebeşçe 2016 Middle East Turkey UMI ELBW 2007–2011 18
Gezmu 2020 Africa Botswana UMI Both 2018–2019 ELGAN-37, ELBW-32
Gharaibeh 2011 Middle East Jordan UMI ELBW 2006–2007 11
Ghaseminejad 2011 Middle East Iran UMI ELBW 2006–2008 7
Golestan 2008 Middle East Iran UMI ELBW 2004 35
Goncalves 2014 South America Brazil UMI ELBW 2009–2011 24
Gooden 2013 Caribbean Jamaica UMI ELBW 2005–2006 46
Gordana 2019 Europe Serbia UMI Both 2006–2011 ELGAN-220, ELBW-157
Goulart 2011 South America Brazil UMI ELBW 1997–2003 36
Gupta 2020 Asia India LMI Both 2017 ELGAN-30, ELBW-49
Hadi 2013 Middle East Egypt LMI ELGAN 2010–2012 15
Haghighi 2013 Middle East Iran UMI ELBW 2010–2011 52
Hakeem 2012 Middle East Egypt LMI ELBW 2009–2010 3
Hendriks 2014 Africa South Africa UMI ELBW 2006–2009 97
Ho 2001 Asia Malaysia UMI Both 1996 ELGAN-168, ELBW-136
Hussain 2012 Middle East Iraq UMI ELGAN 2018–2019 44
Jiang 2020 Asia China UMI ELGAN 2015–2016 320
Jirapaet 2010 Asia Thailand UMI ELBW 1998–2001 5
Jodeiry 2012 Middle East Iran UMI ELGAN NA 51
Kalimba 2013 Africa South Africa UMI ELBW 2006–2010 382
Karabulut 2019 Middle East Turkey UMI ELGAN 2015–2018 87
Kareem 2011 Middle East Iraq UMI ELBW 2003–2009 48
Karkhaneh 2008 Middle East Iran UMI Both 2003–2007 ELGAN-199, ELBW-117
Kidamba 2018 Africa South Africa UMI Both 2013 ELGAN-15, ELBW-15
Kift 2016 Africa South Africa UMI ELGAN 2009–2014 98
Kirsten 2012 Africa South Africa UMI ELGAN 2007–2009 309
Klingenberg 2003 Africa Tanzania LMI ELBW 1999 11
Koksal 2002 Middle East Turkey UMI ELBW NA 12
Kong 2016 Asia China UMI ELGAN 2013–2014 148
Kong 2020 Asia China UMI ELGAN 2013–2014 50
Kulali 2019 Middle East Turkey UMI ELGAN 2011–2015 165
Lara-Molina 2013 North America Mexico UMI ELBW 2008–2010 44
Lermann 2008 South America Brazil UMI Both 2002–2004 ELGAN-7, ELBW-28
Li 2018 Asia China UMI ELGAN 2010–2015 79
Li 2019 Asia China UMI ELGAN 2010–2016 307
Lin 2015 Asia China UMI ELBW 2011 258
Liu 2014 Asia China UMI Both 2009–2012 ELGAN-85, ELBW-24
Liu 2005 Asia China UMI ELBW 1996–2000 37
Lomuto 2008 South America Argentina UMI ELBW 2008 190
Luthuli 2019 Africa South Africa UMI Both 2011–2014 ELGAN-53, ELBW-105
Mabhandi 2019 Africa South Africa UMI ELBW 2015–2017 89
Montano Perez 2019 North America Mexico UMI ELBW 2010–2014 52
Martinez-Cruz 2012 North America Mexico UMI ELBW 2000–2008 139
Martinez 2010 North America Mexico UMI ELBW 2005–2006 152
Mcgready 2018 Asia Thailand UMI ELGAN 1995–2015 132
Medina-Valenton 2016 South America Brazil UMI Both 2012–2014 ELGAN-23, ELBW-25
Mekasha 2020 Africa Ethiopia LI ELBW 2016–2018 164
Miles 2017 Asia Vietnam LMI Both 2011–2012 ELGAN-5, ELBW-63
Moghaddam 2015 Middle East Iran UMI ELBW 2010–2014 108
Muhe 2019 Africa Ethiopia LI Both 2016–2018 ELGAN-104, ELBW-165
Mukhopadhyay 2013 Asia India LMI ELBW 2001–2010 436
Nakubulwa 2020 Africa Uganda LI ELBW 2017–2018 18
Navaei 2010 Middle East Iran UMI Both 2005–2006 ELGAN-122, ELBW-107
NEOCOSUR 2002 South America Multi-Country UMI Both 1997–1998 ELGAN-95, ELBW-126
Nepal 2020 Asia Nepal LMI Both 2019 ELGAN-2, ELBW-3
Nevacinovic 2020 Europe Bosnia UMI ELBW NA 49
NNPD 2004 Asia India LMI ELBW 2000 101
Ntuli 2020 Africa South Africa UMI Both 2015 ELGAN-25, ELBW-50
Ogunlesi 2011 Africa Nigeria LMI ELBW 2008 15
Okello 2019 Africa Uganda LI ELBW 2015–2017 36
Omoigberale 2010 Africa Benin LMI Both 2003–2006 ELGAN-190, ELBW-151
Omer 2014 Africa Sudan LI ELBW 2012–2013 6
Onalo 2015 Africa Nigeria LMI ELBW 2006–2010 42
Onyiriuka 2009 Africa Nigeria LMI ELBW 2000–2003 9
Oomen 2019 Asia India LMI ELBW 2010–2012 30
Osorno-Covarrubiasa 2002 North America Mexico UMI Both 1995–1999 ELGAN-50, ELBW-162
Ozcan 2015 Middle East Turkey UMI ELGAN 2014–2015 18
Pervin 2015 Asia Bangladesh LMI Both 2007–2010 ELGAN-14, ELBW-15
Pinheiro 2010 South America Brazil UMI ELBW 1999–2006 445
Piriyapokin 2020 Asia Thailand UMI ELGAN 2005–2015 67
Poudel 2010 Asia Nepal LMI Both 2005–2008 ELGAN-9, ELBW-23
Pourarian 2016 Middle East Iran UMI ELBW 2014 28
Prabha 2014 Asia India LMI Both 2008–2013 ELGAN-7, ELBW-6
Pradhan 2019 Asia Bhutan LMI ELGAN 2017 18
Qazi 2011 Asia Pakistan LMI ELGAN 2009 3
Qian 2008 Asia China UMI ELGAN 2004–2005 45
Rezaeizadeh 2018 Middle East Iran UMI Both 2013–2016 ELGAN-85, ELBW-127
Roy 2006 Asia India LMI ELBW 2001–2005 36
Ruiz-Pelaez 2014 South America Colombia UMI Both 2004 ELGAN-81, ELBW-86
Rylance 2013 Africa Malawi LI ELBW 2010 71
Sivanandan 2016 Asia India LMI Both 1999–2014 ELGAN-39, ELBW-125
Sabzehei 2013 Middle East Iran UMI Both 2007–2010 ELGAN-84, ELBW-53
Saucedo 2008 North America Mexico UMI ELBW 2002–2006 727
Sackey 2019 Africa Ghana LMI Both 2011–2015 ELGAN-539, ELBW-560
Sahin 2014 Middle East Turkey UMI ELGAN 2010–2012 109
Sahoo 2020 Asia India LMI Both 2013–2018 ELGAN-95, ELBW-231
Saeidi 2009 Middle East Iran UMI ELBW 2005–2006 52
Saeidi 2017 Middle East Iran UMI ELBW 2013–2015 14
Saini 2016 Asia India LMI Both NA ELGAN-7, ELBW-17
Salahuddin 2018 Asia Pakistan LMI ELGAN 2015–2016 11
Saygili 2016 Middle East Turkey UMI Both 2010–2013 ELGAN-203, ELBW-110
Sehgal 2004 Asia India LMI Both 2000–2001 ELGAN-9, ELBW-52
Seid 2019 Africa Ethiopia LI Both 2014–2017 ELGAN-25, ELBW-29
Serce 2014 Middle East Turkey UMI Both 2010–2011 ELGAN-156, ELBW-179
Shrestha 2010 Asia Nepal LMI ELGAN 2005 12
Singh2020 Asia India LMI ELBW 2016 9
Siswanto 2018 Asia Indonesia UMI Both 2005–2015 ELGAN-185, ELBW-182
Sousa 2017 South America Brazil UMI ELBW 2014–2015 158
Sritipsukho 2017 Asia Thailand UMI ELBW 2003–2006 21
Sun 2013 Asia China UMI Both 2010 ELGAN-32, ELBW-28
Tamene 2020 Africa Ethiopia LI Both 2017–2018 ELGAN-15, ELBW-23
Taqui 2008 Asia Pakistan LMI Both 2003–2006 ELGAN-15, ELBW-14
Thakre 2017 Asia India LMI ELBW 2011–2013 7
Thakur2013 Asia India LMI Both 2010–2012 ELGAN-81, ELBW-283
Tosif 2019 Asia Solomon Island LMI ELBW 2014–2016 45
Tran 2015 Asia Vietnam LMI Both 2010–2011 ELGAN-29, ELBW-26
Trotman 2012 Caribbean Jamaica UMI ELBW 1999–2010 286
Trotman 2006 Caribbean Jamaica UMI Both 1995–2000 ELGAN-4, ELBW-7
Trotman 2007 Caribbean Jamaica UMI ELBW 1987–2001 40
Trotman 2007a Caribbean Jamaica UMI Both 2002–2003 ELGAN-14, ELBW-47
Tshehla 2019 Africa South Africa UMI ELBW 2016–2017 71
Ugwu 2010 Africa Nigeria LMI ELBW 2002–2009 149
Undela 2019 Asia India LMI Both 2017 ELGAN-6, ELBW-10
Velaphi 2005 Africa South Africa UMI ELBW 2000–2002 453
Viau 2015 South America Brazil UMI ELGAN 2006–2007 671
Vilanova 2019 South America Brazil UMI ELBW 2000–2015 1325
Vural 2007 Middle East Turkey UMI ELBW 2003–2005 19
Wang 2012 Asia China UMI ELBW 2009–2010 160
Welbeck 2003 Africa Ghana LMI Both 1995 ELGAN-382, ELBW-128
Winkler 2020 Africa Tanzania LMI ELBW 2014–2018 8
Wu 2018 Asia China UMI ELBW 2012–2015 60
Wu 2019 Asia China UMI Both 2008–2017 ELGAN-2051, ELBW-1303
Xu 2013 Asia China UMI Both 2010–2012 ELGAN-285, ELBW-99
Xu 2019 Asia China UMI ELGAN 2013–2014 148
Yadav 2019 Asia Nepal LMI Both 2019 ELGAN-6, ELBW-5
Yakoob 2014 Asia India LMI ELGAN 1998–2003 38
Yau 2014 Asia China UMI ELBW 2007–2012 131
Zea-Vera 2019 South America Peru UMI ELBW 2012–2014 69
Zepeda Romero 2016 North America Mexico UMI ELGAN 2012–2014 9
Zhang 2011 Asia China UMI Both 1999–2009 ELGAN-29, ELBW-39
Zhang 2016 Asia China UMI Both 2011–2012 ELGAN-13, ELBW-10
Zhang 2019 Asia China UMI Both 2016–2017 ELGAN-89, ELBW-55
Zhang 2020 Asia China UMI Both 2007–2016 ELGAN-32, ELBW-100
Zhou 2014 Asia China UMI ELGAN 2010–2011 72
Zhu 2020 Asia China UMI ELGAN 2010–2019 441
Ziadeh 2000 Middle East Jordan UMI ELBW 1996–1999 12
Ziylan 2006 Middle East Turkey UMI ELBW 1998–2003 114
Zuniga 2013 Africa Burundi LI ELBW 2011 11
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Risk of bias

52 studies had a high risk of bias, 131 studies had an intermediate risk of bias and only 7 studies had a low risk of bias. Risk of bias was unclear in two studies. Only 31 studies had described the baseline characteristics of the neonates known to affect the survival and other morbidities such as receipt of antenatal corticosteroids, gender, small for gestational age (SGA) Status, Apgar scores and Level of NICU care. 83 studies had a prospective study design. The risk of bias of included studies is given in S2 Table in S1 File.

Primary outcome

1a. Survival until discharge for ELBW neonates

The overall survival was 34% (95% CI: 31% - 37%). There was significant heterogeneity in the survival rates between studies. Sub-group analysis to address the heterogeneity was done by analyzing studies based on the income status, region and country of origin. While there were widely varying survival rates between countries of similar economic status as well as region of origin, it was much lesser when studies were analyzed according to the country of origin.

For ELBW neonates, the survival for LI, LMI and UMI countries was 18% (11% - 28%), 28% (21% - 35%) and 39% (36% - 42%), respectively (S1 and S2 Figs in S1 File). While most of the countries from the African subcontinent had a survival rate of less than 20%, single center studies from Benin, Eritrea, South Africa and Tanzania reported better survival rates of more than 40% for ELBW neonates. While single center studies from China and India had reported survival rates of more than 60%, it was much lesser from the other Asian countries. While the countries from South America had a reported survival of 39% - 48%, the only middle-income country from North America, Mexico had a survival rate of 43% (37% - 49%). Amongst the countries from the Middle East, Turkey had the highest survival rate of 43% (31% - 57%). Country-wise survival outcomes for ELBW neonates is given in Fig 2. Publication bias was detected for this outcome (S3 Fig in S1 File)

Fig 2. Survival until discharge for ELBW neonates based on country of origin.

Fig 2

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1b. Survival until discharge for ELGANs

Survival until discharge was 39% (34% - 44%). It was 13% (8% - 20%) for LI, 28% (21% - 36%) for LMI and 48% (42% - 53%) for UMI countries. Similar to ELBW survival, there was considerable variation between countries of similar economic classification and geographic region (S4-S6 Figs in S1 File) Single-center outlier studies from Benin, China, South Africa, Thailand and Turkey had reported relatively higher survival of more than 60% when compared to other countries (Fig 3). The survival as assessed by synthesizing data from multiple studies was highest in China [61% (53% - 68%)].

Fig 3. Survival until discharge for ELGANs based on country of origin.

Fig 3

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Secondary outcomes

Short-term and long-term neurological outcomes

2a. Severe IVH and PVL. The rate of severe IVH and PVL in ELBW neonates was 14% (9% - 20%) and 7% (4% - 11%), respectively. For ELGANs, while the overall rate of severe IVH was 14% (11% - 19%). it was 6% (5% - 7%) for PVL (S7-S11 Figs in S1 File).

2b. CP and NDI assessed at 24 months’ corrected age. Only one study had reported NDI outcome for ELBW neonates which was 17% (7% - 34%). Meta-analysis of five studies revealed a NDI prevalence of 29% (23% - 37%) for ELGANs. The prevalence of CP in ELGAN population was 3% (1% - 9%) (S12-S14 Figs in S1 File)

Cardio-respiratory outcomes

3a. PDA. There was considerable variation in the reported rates of PDA requiring intervention between countries which was 15% (7% - 30%) for ELBW neonates and 50% (35% - 65%) for ELGANs (S15-S19 Figs in S1 File).

3b. Requirement of invasive mechanical ventilation. Higher rates of requirement of mechanical ventilation was reported from China which was 78% (65% - 92%) for ELBW neonates and 75% (65% - 84%) for ELGANs (S20 and S21 Figs in S1 File)

3c. BPD assessed as oxygen requirement at 36 weeks’ PMA. For ELBW neonates, BPD prevalence was 39% (30% - 48%). One study from South Africa had reported a relatively lower rate of 17% (6% - 33%). The overall prevalence of BPD was 37% (29% - 47%) in ELGANs. Three centers from China, India and Turkey had reported a higher rate of more than 60% (S22-S25 Figs in S1 File).

Sepsis

The rates of any sepsis and culture proven sepsis in ELBW neonates was 37% (28% - 48%) and 28% (21% - 35%), respectively. Rates of any and culture proven sepsis in ELGANs was 40% (25% - 57%) and 21% (12% - 32%), respectively (S26-S31 Figs in S1 File).

NEC stage II or more

The rates of NEC were uniform across countries with its prevalence being 8% (7% - 10%) for ELBW neonates as well as ELGANs. Publication bias was detected for studies reporting on NEC in ELBW neonates (S32-S35 Figs in S1 File).

EUGR

Two studies from the African sub-continent had reported on EUGR rates in ELBW neonates which was 88% (80% - 93%) (S36 Fig in S1 File).

ROP

Amongst ELBW neonates, any stage ROP, severe ROP and ROP requiring intervention rates was 49% (42% - 55%), 24% (19% - 30%) and 18% (12% - 27%), respectively. One study each from India, Iran and Pakistan had reported severe ROP rate of more than 50%. Also, some reports from China, Turkey and Jordan had ROP requiring intervention rates of more than 30%.

In ELGANs, any stage ROP, severe ROP and ROP requiring intervention was reported in 53% (46% - 59%), 22% (16% - 30%) and 20% (13% - 29%) of neonates, respectively. Single center reports from Thailand and Brazil had rates exceeding 40%.

Data related to ROP is given in S37-S48 Figs in S1 File.

Sensitivity analyses

4a. Excluding studies with low sample size. Analysis of survival outcome after excluding studies with low sample size did not result in any significant changes in the effect estimate when compared to the primary analysis for both ELBW neonates and ELGANs (S49 and S50 Figs in S1 File).

4b. Comparison of survival between epoch 1: 2000–2009 and epoch 2: 2010–2019. There was no significant difference in the survival rates between the two epochs for ELBW neonates (Test of moderators p value– 0.83) and ELGANs. (Test of moderators p value– 0.78) (S51 and S52 Figs in S1 File).

4c. Analysing studies which had evaluated neonates with varying baseline sickness. While of most of the studies were single centre studies, survival rates were reported by five studies for ELBW neonates and ELGANs with RDS. ELBW survival was 33% (20% - 50%) and ELGANs survival was 37% (28% - 47%) for RDS. While 41% (28% - 56%) of ELBW neonates who underwent invasive ventilation survived, the survival rate was 23% (9% - 48%) for ELGANs.

Certainty of evidence

CoE for the primary outcome measure of survival until discharge for ELGANs was moderate and for ELBW neonates was low. While most of the included studies reporting on the primary outcome measure were prospective in design and started with high CoE, they were downgraded for serious inconsistency by one level. The outcome of survival until discharge for ELBW neonates was further downgraded by one level for publication bias. The CoE for other secondary outcomes were very low to low, with retrospective study design and heterogeneity being reasons for downgrading the CoE. The CoE is given in Table 2.

Table 2. Certainty of evidence for the primary outcome and all secondary outcomes for ELBW neonates and ELGANs.

Outcomes Number of studies Number of neonates evaluated Rate (95% CI) Predominant type of studies Risk of bias Inconsistency Indirectness Imprecision Publication bias CoE
ELGANs
Survival 66 8,412 39% [34%- 44%] Prospective Not serious Serious Not serious Not serious None Moderate
Severe IVH 8 2,001 14% [11%- 19%] Retrospective Serious Not serious Not serious Serious - Very low
PVL 7 1,905 6% [5%-7%] Retrospective Not serious Not serious Not serious Serious - Very low
NDI 4 243 29% [23%-37%] Retrospective Not serious Not serious Not serious Serious - Very low
CP 2 105 3% [1%-9%] Prospective Not serious Not serious Not serious Very serious - Low
PDA requiring intervention 5 511 50% [35%-65%] Prospective Not serious Very serious Not serious Serious - Very low
BPD 7 2,809 37% [29%-47%] Retrospective Not serious Serious Not serious Serious None Very low
Any sepsis 7 855 40% [25%-57%] Retrospective Not serious Serious Not serious Serious - Very low
Culture positive sepsis 7 2,301 21% [12%- 32%] Retrospective Not serious Not serious Not serious Serious - Very low
NEC stage ≥II 14 4,094 8% [7%- 10%] Retrospective Not serious Not serious Not serious Serious - Very low
Severe ROP 14 6,003 22% [16%-30%] Retrospective Not serious Serious Not serious Not serious None Very low
ROP requiring intervention 14 1,796 20% [13%- 29%] Retrospective Not serious Not serious Not serious Not serious None Low
Outcomes Rate (95% CI) Predominat type of studies Risk of bias Inconsistency Indirectness Imprecision Publication bias Overall Certainty of Evidence
ELBW neonates
Survival 92 13,667 34% [31%-37%] Prospective Not serious Serious Not serious Not serious Serious Low
Severe IVH 11 1.098 14% [9%- 20%] Retrospective Not serious Not serious Not serious Not serious None Low
PVL 8 616 7% [4%-11%] Retrospective Not serious Not serious Not serious Serious - Very low
NDI 1 30 17% [6%-35%] Prospective Not serious - Not serious Very serious - Low
PDA requiring intervention 4 486 15% [7%-30%] Retrospective Not serious Serious Not serious Serious - Very low
BPD 10 594 39% [30%-48%] Retrospective Not serious Serious Not serious Serious None Very low
Any sepsis 12 1,284 37% [28%-48%] Prospective Not serious Serious Not serious Serious None Low
Culture positive sepsis 11 1,465 28% [21%-35%] Retrospective Not serious Serious Not serious Serious None Very low
NEC stage ≥II 14 2,914 8% [7%-10%] Retrospective Not serious Not serious Not serious Serious Serious Very low
EUGR 2 107 88% [80%-93%] Retrospective Serious Not serious Not serious Serious - Very low
Severe ROP 17 5,413 24% [19%-30%] Retrospective Not serious Not serious Not serious Not serious None Low
ROP requiring intervention 11 1,293 18% [12%-27%] Retrospective Not serious Not serious Not serious Not serious None Low
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Discussion

This systematic review and meta-analysis included 192 studies (ELBW neonates– 22,278; ELGANs– 18,338) from LMICs situated in different geographical regions across the globe. To the best of our knowledge, this is the only systematic review evaluating survival and morbidities in ELGANs or ELBW neonates from LMICs.

The primary outcome of the review was the proportion of neonates who had survived until discharge. The results of this study indicate that the overall survival until discharge of ELBW neonates was 34% and ELGANs was 39%, with significant heterogeneity between studies based on the income status, region as well as country of origin. These survival rates are much lower than that reported from HICs [22]. Myrhaug et al. in their meta-analysis (2019) had reported a survival rate of 74% at 25 weeks’ and 90% at 27 weeks’ amongst neonates born alive in HICs [22]. Such stark differences in survival between LMICs and HICs can be explained by many reasons. Attitudes towards providing life-saving intervention to these immature infants are quite different between LMICs and HICs. In LMICs, the focus of healthcare programmes to reduce NMR comprise predominantly of cost-effective high impact interventions comprising of early essential newborn care services which are predominantly targeted to address mortality in relatively bigger neonates [6, 26]. Decreasing mortality rates in ELGANs in LMICs through establishment of higher level NICUs might impose further financial burden as well as risk of inequity, diverting resources from the relatively more mature neonates. Further, absence of healthcare insurance schemes in LMICs result in financial constraints for parents who eventually have to bear most of the costs incurred [27]. Finally, ‘denominator bias’ due to lack of surveillance data and consequent inconsistent reporting from LMICs regarding live births versus NICU admissions might also result in significant variability in survival rates in LMICs when compared to HICs [28, 29].

There was significant variation in survival between LMICs as well. Similar findings are also seen in the studies published from HICs [30]. While some studies from HICs have pointed out factors such as differing gestational age cut-offs for instituting active care, selective versus comprehensive care and variations in clinical care practices for babies born at less than 25 weeks’ gestation being some of the reasons for varying survival rates between different countries, such comparative studies are lacking for LMICs [31–33]. Differing survival rates between studies from the same LMIC might be explained by the survival gap between rural and urban areas [34]. Whether there are any differences in survival between private versus public sector systems in LMICs still remains a contested topic, it was beyond the scope of our review to look into the same [35]. Differences in health policy, financial resources, access to and use of health services, infrastructure, and economic development might also explain the significant variability in survival between countries of similar economic status [36–38].

Sensitivity analysis indicated that there was no significant differences in the survival rates between the two epochs (epoch 1: 2000–2009 and epoch 2: 2010–2019). Similar findings were noted in the meta-analysis by Myrhaug et al. for HICs [22]. However, some neonatal network studies from other HICs have shown both an improving as well as static trend for survival in the past few decades [39–43]. The rates of some secondary outcomes such as NEC and PVL were comparable with data from HICs [40–42]. This might be due to the fact that many of the HICs provide active care for neonates born from 22 weeks’ gestation who are at the highest risk of major brain injury, whilst most of the ELBW neonates and ELGANs enrolled in studies from LMICs were of higher gestational ages ranging from 25–27 weeks [31, 33, 40, 44]. However, rates of all other morbidities were higher in LMICs when compared to HICs. Information from limited studies in the meta-analysis have shown that the rates of NDI was 17% (7% - 34%) and 29% (23% - 37%) in ELBW neonates and ELGANs, respectively. Milner et al. in their systematic review and meta-analysis of long-term neurodevelopmental outcomes of preterm VLBW neonates in resource limited settings had reported a lower NDI rate of 21.4% (11.6% - 30.8%) [12]. This could be because of the fact that Milner et al.’s study consisted of neonates who were gestationally more mature. Also, many studies from HICs such as Croatia, Korea, Poland and Taiwan were included in their study.

This systematic review had some limitations. There was considerable heterogeneity in the various outcome measures despite performing multiple sensitivity and sub-group analyses to address the same. The analysis might be limited by denominator bias as survival rates could not be assessed based on different denominators such as live births versus NICU admissions, due to inconsistent reporting in studies. Accurate gestational age assessment is still a major issue in LMICs and might have influenced our final estimates. Further, analysis by stratification on the basis of gestational age or birth weight could not be performed for ELGANs and ELBW neonates. Important confounders determining survival such as antenatal corticosteroid use, multiple gestation, SGA status, gender, chorioamnionitis and level of NICU care were not reported by majority of the included studies, thus precluding any sensitivity analysis based on these parameters. The overall CoE was very low to low for all the secondary outcomes. Finally, though the literature search included the standard databases as recommended by the Cochrane group, studies from LMICs might be more likely to be published in alternative databases as well.

Conclusion

Mortality and morbidity of ELBW neonates and ELGANs is still a huge burden in LMICs, with significant differences in their occurrence between countries of similar economic status and geographical region of location. For ELBW neonates, the survival for LI, LMI and UMI countries was 18% (11% - 28%), 28% (21% - 35%) and 39% (36% - 42%), respectively. For ELGANs, it was 13% (8% - 20%) for LI, 28% (21% - 36%) for LMI and 48% (42% - 53%) for UMI countries. These are significantly lower than the survival rates reported from HICs. The CoE for most of the outcomes was very low to low, emphasizing the need for surveillance and high quality prospective cohort studies from LMICs on this sub-group of vulnerable neonates. Such studies should provide data related to still births, live births, delivery room deaths, important baseline characteristics such as antenatal corticosteroid use, multiple gestation status, SGA, gender, chorioamnionitis and level of NICU care, and sub-group data on different gestational ages or birth weights for ELGANs or ELBW neonates. Such data would not only quantify the burden of mortality and morbidity in these preterm infants, but also enable evaluating the post-implementation impact of important public health interventions.

Supporting information

S1 Checklist. PRISMA checklist for reporting of the review.

(DOC)

Click here for additional data file. (63KB, doc)
S1 File. This file with tables and figures showing various outcomes assessed, literature search strategy, risk of bias of included studies and references of included studies.

(PDF)

Click here for additional data file. (2.5MB, pdf)

Abbreviations

BPD

Bronchopulmonary dysplasia

CoE

Certainty of evidence

ELBW

Extremely low birth weight

ELGANs

Extremely low gestational age neonates

EUGR

Extrauterine growth retardation

HICs

High income countries

IVH

Intraventricular hemorrhage

LMICs

Low- and middle-income countries

MA

Meta-analysis

NEC

Necrotising enterocolitis

NDI

Neurodevelopmental impairment

NMR

Neonatal mortality rate

PDA

Patent ductus arteriosus

PMA

Post-menstrual age

PVL

Periventricular leukomalacia

ROB

Risk of bias

ROP

Retinopathy of prematurity

SR

Systematic review

SDG

Sustainable Development Goals

VLBW

Very low birth weight

Data Availability

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

Funding Statement

The author(s) received no specific funding for this work.

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Associated Data

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

Supplementary Materials

S1 Checklist. PRISMA checklist for reporting of the review.

(DOC)

Click here for additional data file. (63KB, doc)
S1 File. This file with tables and figures showing various outcomes assessed, literature search strategy, risk of bias of included studies and references of included studies.

(PDF)

Click here for additional data file. (2.5MB, pdf)

Data Availability Statement

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

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