Incidence and predictors of mortality among preterm neonates admitted to the neonatal intensive care unit of Wallaga University Comprehensive Specialized Hospital, Nekemte Town, East Wallaga, Oromia, Ethiopia: a retrospective cohort study

Incidence and predictors of mortality among preterm neonates admitted to the neonatal intensive care unit of Wallaga University Comprehensive Specialized Hospital, Nekemte Town, East Wallaga, Oromia, Ethiopia: a retrospective cohort study | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Incidence and predictors of mortality among preterm neonates admitted to the neonatal intensive care unit of Wallaga University Comprehensive Specialized Hospital, Nekemte Town, East Wallaga, Oromia, Ethiopia: a retrospective cohort study Minase Abera, Fikadu Enkosa, Emiru Merdassa This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6697745/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract BACKGROUND Preterm birth affects 1 in 10 babies globally, with disproportionately high mortality in low-income settings. Sub-Saharan Africa bears a significant burden due to limited healthcare access. Despite the availability of modifiable risk factors and cost-effective interventions, data on incidence of mortality of preterm neonates in the study area is lacking. OBJECTIVE To assess incidence and predictors of mortality among preterm neonates admitted to the neonatal intensive care unit of Wallaga University Comprehensive Specialized Hospital, Nekemte Town, Oromia, Ethiopia, from July 1, 2022, to June 30, 2024. METHODS An institution-based retrospective cohort study was conducted among 264 preterm neonates admitted to the NICU within the study period and study subjects were selected using systematic random sampling technique. Data were collected using a structured checklist, entered via EpiData version 4.6, and subsequently analyzed using STATA version 14.0. Kaplan-Meier and log-rank tests were used to compare survival probability and assess statistically significance difference between groups. The Cox proportional hazards model assumption was checked. A bivariable Cox regression analysis was fitted and those variable with p < 0.2 were included in the multivariable analysis. Finally, statistical significance was declared at a p-value < 0.05. RESULTS Of 259 preterm neonates, 42 died during follow up time, with incidence proportion of 16%. The median survival time was 28 days (IQR: 22–30), with 2,737 neonate-days of follow-up. The overall incidence rate of mortality was 15.3 per 1,000 neonate-days (95% CI: 11.3–20.7). Significant predictors of mortality included were lack of ANC follow-up (AHR: 2.27, 95% CI: 1.13–4.57), antenatal steroid use (AHR: 0.44, 95% CI: 0.21–0.92), home delivery (AHR: 7.74, 95% CI: 1.99–30.03), and presence of hypothermia (AHR: 4.11; 95% CI: 1.55–10.85). CONCLUSION AND RECOMMENDATION: The study identified key clinical and maternal predictors associated with preterm neonatal mortality. Targeted interventions focusing on antenatal care, delivery practices, steroid administration, and thermal regulation are essential. NICU WUCSH Incidence of mortality Predictors of mortality Preterm Figures Figure 1 Figure 2 Figure 3 Figure 4 1. Background Preterm birth, defined as birth before 37 completed weeks of gestation, is a global public health concern. It is categorized into three groups based on gestational age: moderate to late preterm (32–37 weeks), very preterm (28–<32 weeks), and extremely preterm (< 28 weeks). Globally, approximately 1 in 10 newborns is born preterm, with the highest burden in Southern Asia and sub-Saharan Africa, where neonatal survival is significantly lower compared to high-income countries (1). The prevalence of preterm birth varies from 5–18% across 184 countries (2,3), with six nations—India, China, Nigeria, Pakistan, Indonesia, and the United States—accounting for nearly half of the global burden (4). Preterm birth arises from either spontaneous onset of labor or medically indicated delivery due to maternal or fetal complications. Risk factors include infections, inflammation, vascular conditions, uterine overdistension, and obstetric conditions such as pre-eclampsia and intrauterine growth restriction (5,6). Additional maternal and fetal factors—including low maternal body mass index (BMI), parity, employment status, preeclampsia, low birth weight, male sex, and multiple gestations—also contribute (6,7). A meta-analysis of 30 studies in Ethiopia reported a national preterm birth prevalence of 11.4%, with significant associations observed for pregnancy-induced hypertension, HIV infection, premature rupture of membranes (PROM), rural residence, multiple pregnancies, and maternal anemia (8). Preterm neonates face a high risk of both short- and long-term complications. In the immediate neonatal period, respiratory distress syndrome (RDS), necrotizing enterocolitis, and intraventricular hemorrhage are frequent contributors to morbidity and mortality (9,10). Long-term consequences include increased risks for cardiovascular disease, bronchopulmonary dysplasia (BPD), cerebral palsy, and developmental delays. These risks escalate with decreasing gestational age, and the prognosis is particularly poor for neonates born before 24 weeks (9–11). Globally, complications of preterm birth are responsible for nearly 1 million deaths annually, contributing to 18% of all deaths among children under five and up to 35% of neonatal deaths (4). Sub-Saharan Africa and Southern Asia account for 65% of preterm births, with the highest mortality rates observed in low-income settings. In Africa, more than 90% of extremely preterm infants die within the first few days, compared to fewer than 10% in high-income countries, due to limitations in access to quality neonatal care (1,12). In Ethiopia, the incidence proportion of preterm neonatal mortality is estimated at 30%, with an incidence density of 40 per 1,000 person-days. Identified predictors of mortality include birth before 32 weeks, male sex, low Apgar scores, birth asphyxia, low birth weight, RDS, neonatal jaundice and sepsis, antepartum hemorrhage, and the absence of kangaroo mother care (KMC) (13). Despite the availability of effective interventions, including antenatal corticosteroids, kangaroo mother care, neonatal resuscitation, magnesium sulfate, and delayed cord clamping, implementation gaps persist in resource-limited settings (1,14,15). Ethiopia’s National Neonatal and Child Survival Strategy emphasizes these interventions and aims to reduce neonatal mortality through improved health infrastructure and community engagement. However, barriers such as workforce limitations and supply shortages hinder progress, and neonatal mortality remains a pressing issue (13,16). To date, no studies have assessed the incidence and predictors of preterm neonatal mortality in the study area. Generating local data is essential to inform tailored interventions, strengthen neonatal care services, and support national efforts to reduce neonatal mortality. 2. Methods And Materials 1.1. Study Design and Setting An institution-based retrospective cohort study was conducted. It involved review of charts of preterm neonates admitted between 1 July, 2022 and 30 June, 2024 GC. This study was carried out at WUCSH located in Nekemte town, the capital city of East Wallaga, lies 331 kilometers west of Addis Ababa. WUCSH, a teaching and specialized hospital, serves an estimated population of 5 million within its catchment area. The hospital offers NICU services, to both inborn and out born term and preterm neonates. 2.2. Population Source population All preterm neonates admitted to the neonatal intensive care unit of WUCSH. Study population All preterm neonates admitted to the neonatal intensive care unit of WUCSH from July 1, 2022 to June 30, 2024 GC. Study unit Each randomly selected preterm neonate's chart from the HMIS registry book. 2.3. Eligibility Criteria Inclusion criteria Files of all preterm neonates admitted to the NICU from July 1, 2022 to June 30, 2024 GC. Exclusion criteria Files of preterm neonates that was incomplete during the study period. 2.4. Sample Size Determination and Sampling Technique Sample size determination A previously conducted study at public hospitals in southern Ethiopia was used as a reference to calculate the sample size. The sample size is determined using STATA version 14.0 (Cox model) with the assumptions of 95% CI, 5% margin of error, 80% power, a variability (SD) of 0.5, and probability of failure (event) of 0.255. Predictors of preterm neonatal death included were lack of antenatal care, primiparity, pregnancy complications, resuscitation at birth, and absence of Kangaroo mother care (17). Table 1 Sample size determination for incidence and predictors of mortality among preterm neonates admitted to NICU at WUCSH, Nekemte Town, East Wallaga, Oromia, Ethiopia from July 1, 2022 to June 30, 2024 GC. No Associated factors HR Power Total sample (with 15% for incomplete records) References 1 lack of ANC 7.1 80 38 (17) 2 Primiparity 2.3 80 209 (17) 3 Pregnancy complications 3.4 80 97 (17) 4 Resuscitation at birth 2.1 80 264 (17) 5 Absence of KMC 9.3 80 30 (17) Finally, the largest calculated sample size ( 264 ) was selected as the final sample size. Sampling techniques Study subjects were selected using a systematic random sampling (SRS) technique. The sampling interval (K) was determined by dividing the total number of preterm neonates over the study period by the required sample size (K = N/n). The sampling frame consisted of patient records listed in the HMIS registry book, and every 2nd record was selected until the total sample size was reached. The first record was chosen randomly using a lottery method. Only medical records with complete information were included; if a selected chart was missing or incomplete, the next available record in sequence was used. 2.5. Study Variables Dependent variable Incidence of mortality. Independent variables Maternal related predictors Age, parity, obstetrics related factors (pregnancy induced hypertension, GDM), preterm labor, maternal infection (chorioamnionitis), antenatal care, and antenatal steroid use. Neonatal related predictors Gender of the baby, place of delivery, mode of delivery, gestational age, birth weight, APGAR score, resuscitation at birth, and hospital complications. Health facility related predictors Length of hospital stay, oxygen therapy, and antibiotics & other treatments 2.6. Operational Definition Censored Defined when preterm neonates discharge improved, lost to follow up or referred to other institution within the study period (18). Event Referred to the death of preterm neonates during their hospital stay (18). Follow up time The time starting from admission until either an event or censorship occurs, with a maximum follow-up period of 30 days (18). Time scale Days from the admission of a preterm neonate (18). Preterm Neonates born alive before 37 weeks of pregnancy are completed (1). Moderate to late preterm Infants are those born between 32 weeks and 37 weeks of gestation (1). Very preterm Is defined as 28weeks of gestation to fewer than 32 weeks of gestation (1). Extremely preterm Is designated less than 28 weeks of gestational age (1). Respiratory distress Clinically diagnosed in premature infants with rapid, labored breathing, often with grunting, flaring nostrils, and chest wall retractions (19). Hypothermia Defined as skin (axillary) temperature less than 36.5 0 C (19). Apnea Defined as absence of air flow for ≥ 20 seconds or less than that if it is accompanied by bradycardia (heart rate < 100/min) or cyanosis (19). Necrotizing enterocolitis A clinical diagnosis can be established when a neonate presents with symptoms such as abdominal distention, feeding intolerance, vomiting, bloody stools, loose stools, abdominal wall erythema, and vital sign instability (19). Sepsis Clinical diagnosis is based on the presence of symptoms such as temperature instability, respiratory distress, feeding difficulties, lethargy, seizures, and jaundice in neonates with known risk factors, including maternal infection, PROM, or the need for resuscitation at birth. Further divided into Early onset (below 7 days) and Late onset (7–28 days) sepsis (19). First-line antibiotics Refer to the initial antibiotics administered, commonly including ampicillin and gentamicin (19). Second-line antibiotics are those that are either added or changed into if there is no improvement after 48 hours or if the infant’s condition worsens (19). 2.7. Data Collection Tools and Procedures A structured checklist was adapted for the collection of secondary data from medical records. This checklist was developed through a review of relevant literature and a critical evaluation of existing studies, with a focus on socio-demographic characteristics, maternal medical and obstetric history, prenatal factors, and neonatal variables associated with incidence of preterm mortality (8,13,22,25,26–32). Birth weight and gestational age at birth were classified according to WHO standards (1). Data was collected by trained neonatal nurses from September 15 to October 15, 2024 GC. 2.8. Data Processing and Analysis Data entry was conducted using EpiData version 4.6, and the data was then exported to STATA 14.1. statistical software for analysis. Multicollinearity test was done, and no significant correlation was detected among the independent variables. The Incidence proportion and Incidence Density Rate (IDR) was calculated for the entire study period. Subsequently, the number of mortalities within the follow-up period was divided by the total neonate-time at risk during follow-up and reported per 1000-neonate days. The Kaplan-Meier curve was used to estimate median survival time, and log-rank tests was used to compare survival curves. The Cox proportional hazards assumption was also checked using both graphs and Schoenfeld’s residual test, with variables having p-values greater than 0.05 being considered as fulfilling the assumption. The Cox-Snell residuals were also used to assess the overall goodness-of-fit of the Cox proportional hazards model. Bivariable cox regression was first fitted and those independent variables having p-value < 0.2 were included in the multivariable analysis. Finally, statistical significance was declared at a p-value < 0.05. Hazard Ratios (HR) with 95% Confidence Intervals (CI) was used to assess the relationship between factors associated with the occurrence of death. Variables with zero events during the follow-up period (UTI, Intrauterine infection, APH, Hepatitis B infection, and first-line antibiotics) were excluded from Cox regression due to inability to estimate hazard ratios, but were included in descriptive statistics. Maternal age was initially recorded in 15–19, 20–34 & ≥35years age bands, but was re-grouped into < 20 & ≥20years because the ≥ 35 years group had zero deaths. Similarly, Place of ANC Follow up was re-categorized into Health center & Hospital due to zero events occurs in Tertiary Hospitals. 3. Results Description of study participants A total of 264 preterm neonates were selected for this study. Among the selected neonatal charts, 5 were excluded due to missing key information such as discharge outcome, date of admission, date of discharge, and other essential baseline data. Finally, two hundred fifty-nine (259) neonatal charts were included in the analysis with 98.1% response rate. 3.1. Socio-Demographic Characteristics and Antenatal Care Status of Mothers According to this study, the mothers' ages ranged from 15 to 38 years, with a mean age of 24.4 ± 1.4 years. The most common age group was ≥ 20 years (88.8%). The majority of the mothers had one or two children 210(81.1%) and lived in rural areas 176(67.9%). The majority of mothers had antenatal care (ANC) follow-up, with 192 (74.1%) attending, of whom 120 (62.5%) visited a health center. Additionally, 180 (93.7%) of them had fewer than four ANC visits, which is below the current national guideline recommendation of at least eight visits. During pregnancy, 116 (44.8%) experienced pregnancy-related complications. The most common complications were pregnancy-related hypertension (30.1%), premature rupture of membranes (PROM) (6.6%), and malaria (6.2%), as shown in Table 2 below. Table 2 Socio-demographic characteristics of mothers of preterm neonates admitted to the NICU at WUCSH, Nekemte Town, East Wallaga, Oromia, Ethiopia, from July 1, 2022 to June 30, 2024 GC. Variables Variables Frequency (%) Survival Status Event (%) Censored (%) Age < 20yrs 29(11.2) 3(1.2) 26(10) ≥ 20yrs 230(88.8) 39(15.1) 191(73.7) Residence Urban 83(32.1) 8(3.1) 75(28.9) Rural 176(67.9) 34(13.1) 142(54.8) Parity 1-2birth 210(81.1) 37(14.3) 173(66.8) 3-5birth 40(15.4) 4(1.5) 36(13.9) > 5birth 9(3.5) 1(0.4) 8(3.1) ANC Follow up Yes 192(74.1) 15(5.8) 177(68.3) No 67(25.8) 27(10.4) 40(15.4) Place of ANC Follow up Health Center 120(62.5) 13(6.8) 107(55.7) Hospital 72(37.5) 2(1.1) 70(36.4) Frequency of ANC Follow up < 4 times 180(93.7) 14(7.3) 166(86.4) ≥ 4 times 12(6.3) 1(0.5) 11(5.8) Antenatal Steroid use Yes 132(50.9) 15(5.8) 117(45.1) No 127(49.1) 27(10.5) 100(38.6) Pregnancy related complication Yes 116(44.8) 26(10) 90(34.8) No 143(55.2) 16(6.2) 127(49) Pregnancy induced Hypertension Yes 78(30.1) 16(6.2) 62(23.9) No 181(69.9) 26(10) 155(59.9) PROM Yes 17(6.6) 4(1.5) 13(5.1) No 242(93.4) 38(14.7) 204(78.7) UTI Yes 3(1.2) 0(0) 3(1.2) No 256(98.8) 42(16.2) 214(82.6) Intrauterine infection (Chorioamnionitis) Yes 2(0.8) 0(0) 2(0.8) No 257(99.2) 42(16.2) 215(83) Malaria Yes 16(6.2) 8(3.1) 8(3.1) No 243(93.8) 34(13.1) 209(80.7) APH Yes 2(0.8) 0(0) 2(0.8) No 257(99.2) 42(16.2) 215(83) Hepatitis B virus status Positive 4(1.5) 0(0) 4(1.5) Negative 255(98.5) 42(16.2) 213(82.3) 3.2. Profile of Preterm Neonates According to this study, most of the preterm neonates were between 32 to 37 weeks 222(85.7%), with 5 (1.9%) being extremely preterm, as shown in Fig. 1 below. The male preterm neonates accounts for 183 (70.7%) of the total cases. Majority of preterm neonates had a birth weight ranging from 1500 to 2400 grams, with 181 (69.9%). Additionally, most of the preterm neonates were born in hospital, comprising 229 (88.4%) of the total cases, as shown in Table 3 below. Table 3 Profile of preterm neonates admitted to the NICU at WUCSH, Nekemte Town, East Wallaga, Oromia, Ethiopia, from July 1, 2022 to June 30, 2024 GC. Variables Variables Frequency (%) Survival Status Event (%) Censored (%) Sex of the neonate Male 183(70.7) 29(11.2) 154(59.5) Female 76(29.3) 13(5.0) 63(24.3) Place of birth Home delivery 6(2.3) 3(1.16) 3(1.16) Health Center 24(9.3) 6(2.3) 18(7) Hospital 229(88.4) 33(12.7) 196(75.7) Gestational age ≤ 28weeks 5(1.9) 4(1.5) 1(0.4) 28-32weeks 32(12.4) 2(0.8) 30(11.6) 32-37weeks 222(85.7) 36(13.9) 186(71.8) Birth weight < 1000gm 5(1.9) 4(1.5) 1(0.4) 1000-1499gm 73(28.2) 10(3.9) 63(24.3) 1500-2400gm 181(69.9) 28(10.8) 153(59.1) APGAR score Known 224(86.5) 35(13.5) 189(73) Unknown 35(13.5) 7(2.7) 28(10.8) Fifth minute APGAR score ≥ 7 196(87.5) 20(8.9) 176(78.6) < 7 28(12.5) 15(6.7) 13(5.8) Resuscitation at birth Yes 44(16.9) 21(8.1) 23(8.8) No 215(83.1) 21(8.1) 194(75) 3.3. Hospital Complications of Preterm Neonates The majority of preterm neonates, 254 (98.1%), experienced one or more hospital complications. The most common complications were hypothermia in 179(69.1%) of the cases, followed by RDS in 119 (45.9%), EONS in 105(40.5%), jaundice in 54(20.8%), and Apnea in 23(8.8%), as shown in Table 4 below. Table 4 Hospital complications of preterm neonates admitted to the NICU at WUCSH, Nekemte Town, East Wallaga, Oromia, Ethiopia, from July 1, 2022 to June 30, 2024 GC. Variables Variables Frequency (%) Survival Status Event (%) Censored (%) Neonatal complications Yes 254(98.1) 42(16.2) 212(81.9) No 5(1.9) 0(0) 5(1.9) Hypothermia Yes 179(69.1) 35(13.5) 144(55.6) No 80(30.9) 7(2.7) 73(28.2) RDS Yes 119(45.9) 29(11.2) 90(34.7) No 140(54.1) 13(5.0) 127(49.1) EONS Yes 105(40.5) 21(8.1) 84(32.4) No 154(59.5) 21(8.1) 133(51.4) Jaundice Yes 54(20.8) 18(6.9) 36(13.9) No 205(79.2) 24(9.3) 181(69.9) Apnea Yes 23(8.8) 7(2.7) 16(6.1) No 236(91.1) 35(13.5) 201(77.6) Seizure Yes 16(6.2) 6(2.3) 10(3.9) No 243(93.8) 36(13.9) 207(79.9) NEC Yes 14(5.4) 8(3.1) 6(2.3) No 245(94.6) 34(13.1) 211(81.5) IVH Yes 13(5.1) 2(0.8) 11(4.3) No 246(94.9) 40(15.4) 206(79.5) Anemia Yes 12(4.6) 7(2.7) 5(1.9) No 247(95.4) 35(13.5) 212(81.9) Congenital Malformation Yes 6(2.3) 2(0.8) 4(1.5) No 253(97.7) 40(15.4) 213(82.3) 3.4. Treatment Given to Preterm Neonates In this study, preterm neonates received a range of treatments including oxygen, antibiotics, aminophylline, phototherapy, phenobarbital, and blood transfusions. The three most commonly given treatments were first-line antibiotic therapy 198(76.4%), followed by oxygen therapy 145(55.9%) and second-line antibiotic therapy 83(41.9%), as shown in Table 5 below. Table 5 Treatment given to preterm neonates admitted to the NICU at WUCSH, Nekemte Town, East Wallaga, Oromia, Ethiopia, from July 1, 2022 to June 30, 2024 GC. Variables Variables Frequency (%) Survival Status Event (%) Censored (%) First-line antibiotics Yes 198(76.4) 42(16.2) 156(60.2) No 61(23.6) 0(0) 61(23.6) Oxygen therapy Yes 145(55.9) 40(15.4) 105(40.5) No 114(44.1) 2(0.8) 112(43.3) Second-line antibiotics Yes 83(41.9) 26(13.1) 57(28.8) No 115(58.1) 16(8.1) 99(50) Aminophylline Yes 31(11.9) 15(5.8) 16(6.1) No 228(88.1) 27(10.4) 201(77.7) Phototherapy Yes 29(11.2) 5(1.9) 24(9.3) No 230(88.8) 37(14.3) 193(74.5) Blood transfusion Yes 13(5.1) 6(2.4) 7(2.7) No 246(94.9) 36(13.9) 210(81) Phenobarbital Yes 11(4.2) 6(2.3) 5(1.9) No 248(95.8) 36(13.9) 212(81.9) 3.5. Outcome of Preterm Neonates Figure 2 shows the outcomes of 259 preterm neonates admitted to the NICU at WUCSH between July 1, 2022, and June 30, 2024 GC and included in the study. Of the neonates, 206 (79.5%) were discharged after clinical improvement, 42 (16.2%) died, 4 (1.5%) were referred, and 7 (2.7%) were lost to follow-up. This figure shows valuable insight into the overall prognosis of preterm neonates during the study period. While the majority (over 79.5%) improved with treatment, the incidence proportion of 16.2% highlights the severity of the condition in this vulnerable population. The relatively high mortality underscores the critical need for improved preventing complication, optimized neonatal care, and early identification of risk factors associated with poor outcomes. 3.6. Incidence of Mortality among Preterm Neonates Admitted to NICU Out of 259 preterm neonates included in the study, 42 died during the follow-up period, makes an incidence proportion of 16.2%. The median survival time was 28 days, with an interquartile range (IQR) of 22 to 30 days. During follow-up time, a total of 2737 neonate-day observation were observed with a minimum of 1 day and maximum of 30 days follow-up time. The overall mortality incidence rate was 15.3 per 1,000 preterm neonates-day (CI: 11.3, 20.7). 3.7. Over-all Kaplan- Meier Failure Estimate The overall Kaplan-Meier estimate showed that the probability of survival of preterm neonates was higher on the first day of admission, with increased failure to survive throughout the follow-up period. Notably, sharper drops in survival were observed after around 15 days, as shown in Fig. 3 below. 3.8. Predictors of Mortality Among Preterm Neonates Admitted NICU. The study identified several significant predictors of neonatal mortality among preterm neonates admitted to the NICU. Lack of antenatal care (ANC) follow-up was associated with a more than twofold increased risk of mortality (AHR: 2.27, 95% CI: 1.13–4.57). Neonates born at home were particularly vulnerable, with a markedly elevated mortality risk (AHR: 7.74, 95% CI: 1.99–30.03) compared to those born in hospital. Hypothermia is also strong independent predictors, with adjusted hazard ratios of 4.11 (95% CI: 1.55–10.85). Importantly, antenatal steroid use demonstrated a protective effect, reducing preterm mortality by 55.7% (AHR: 0.44, 95% CI: 0.21–0.92). These findings highlight the critical importance of quality antenatal care, including hospital delivery, proper thermal regulation, and interventions including antenatal steroid use, in improving preterm neonatal survival. Table 6 Results of the bivariate and multivariate Cox regression analysis of predictors of mortality among preterm neonates admitted to the NICU at WUCSH, Nekemte Town, East Wallaga, Oromia, Ethiopia, from July 1, 2022 to June 30, 2024 GC. Variables Category Status CHR (95% CI) AHR (95%CI) Total (%) Event (%) Censored (%) ANC Follow up Yes 192(74.1) 15(5.8) 177(68.3) 1 1 No 67(25.9) 27(10.5) 40(15.4) 3.42(1.80–6.51) 2.27(1.13–4.57) * Antenatal Steroid use Yes 132(50.9) 15(5.8) 117(45.1) 0.31(0.15–0.61) 0.44(0.21–0.92) * No 127(49.1) 27(10.5) 100(38.6) 1 1 Place of birth Home delivery 6(2.3) 3(1.16) 3(1.16) 9.95(2.87–34.3) 7.74(1.99–30.03) ** Health Center 24(9.3) 6(2.3) 18(7) 2.41(1.00-5.83) 1.65(0.61–4.45) Hospital 229(88.4) 33(12.7) 196(75.7) 1 1 Resuscitation at birth Yes 44(16.9) 21(8.1) 23(8.8) 2.21(1.17–4.19) 1.84(0.86–3.89) No 215(83.1) 21(8.1) 194(75) 1 1 Hypothermia Yes 179(69.1) 35(13.5) 144(55.6) 2.96(1.29–6.8) 4.11(1.55–10.85) ** No 80(30.9) 7(2.7) 73(28.2) 1 1 Anemia Yes 13(5.1) 8(3.1) 5(2) 2.32(1.01–5.31) 2.00(0.79–5.05) No 246(94.9) 34(13.1) 212(81.8) 1 1 IVH Yes 13(5.1) 2(0.8) 11(4.3) 0.37(0.08–1.57) 0.67(0.14–2.99) No 246(94.9) 40(15.4) 206(79.5) 1 1 Seizure Yes 16(6.2) 6(2.3) 10(3.9) 1.82(0.75–4.39) 2.20(0.78–6.23) No 243(93.8) 36(13.9) 207(79.9) 1 1 AHR: Adjusted Hazard Ratio; CHR: Crude Hazard Ratio * Statistically significant at p < 0.05; ** statistically significant at p < 0.01. 3.9. Kaplan-Meier Curve for Different Categorical Variable Separate Kaplan-Meier graphs were constructed to compare the survival probability across different covariates. In the Kaplan-Meier survival curves, one curve lying above the other indicates that the group represented by the higher curve has a longer survival time compared to the group with the lower curve. The log-rank test was used to assess the statistical significance of differences in survival probability among the groups at a 5% significance level. 4. Discussion This Study is aimed to assess incidence and predictors of mortality among preterm neonates admitted to the NICU of Wallaga University Comprehensive Specialized Hospital. From a total of 259 preterm neonates admitted to the NICU 42(16.2%) were died with the median time to death of 28 days with IQR of 22 to 30 days. Throughout the follow-up period, the overall incidence of mortality was 15.3 per 1000 preterm neonates (CI: 11.3, 20.7). The incidence proportion of preterm mortality observed in this study is lower than rates reported in other settings. Studies from Tikur Anbessa, Gondar, and Mizan Tepi reported higher proportions ranging from 28.8–35% (18,20,21), while a study in Southern Ethiopia reported 25.5% (17). Outside Ethiopia, mortality rates were 31.6% in Uganda (22), 20.7% in Sierra Leone (23), and 23% in the India-Pakistan PURPOSe cohort (24). These differences may reflect variations in sample size, follow-up duration, and population characteristics. Studies from Ethiopia have reported shorter median survival times and higher incidence rates than this study. Tikur Anbessa Specialized Hospital found a median survival of 21 days with an incidence rate of 39.1 per 1,000 neonate-days (18). Mizan Tepi reported 15 days and 62.15, respectively (21), while a study from Southern Ethiopia showed 18 days with a rate of 47.7 (17). At Jimma University Medical Center, the incidence rate was 28.9 per 1,000 neonate-days (25). These variations may reflect differences in study design, population characteristics, or NICU care quality. Several predictors were significantly associated with increased mortality. Lack of antenatal care (ANC) follow-up more than doubled the risk of death, consistent with reports from Southern Ethiopia, Mizan Tepi, and Uganda (17,21,22). Possible reason could be lack of ANC visits may result insufficient monitoring of the pregnancy, increasing the risk of complications during and after birth, which in turn may contribute to a higher risk of neonatal death. Antenatal steroid use significantly reduced mortality by 55.7%, which align with findings from Jimma and global meta-analyses highlighting the benefits of corticosteroids in improving lung maturity and reducing respiratory complications (25,26). Despite their proven effectiveness, antenatal steroids remain underutilized in low-resource settings due to late presentation and limited supplies. Home delivery was strongly associated with neonatal mortality, likely due to the lack of skilled birth attendants and delayed access to neonatal care, similar to findings from Gondar (20). Additionally, neonatal hypothermia increased mortality risk fourfold, aligning with studies in Bench Sheko and Sierra Leone (23,27). 5. Conclusion In conclusion, while the incidence proportion and incidence rate of preterm neonatal death in this study were lower compared to other studies, several key predictors were identified. This include lack of ANC follow-up, home delivery, and neonatal hypothermia, while the use of antenatal steroids was shown to decrease the risk of death. This study demonstrates that improving antenatal care coverage, encouraging facility-based deliveries, ensuring effective thermal management, and promoting antenatal corticosteroid administration are essential strategies for improving survival among preterm neonates. Abbreviations ANC Antenatal Care AHR Adjusted Hazard Ratio APH Antepartum Hemorrhage BMI Body Mass Index BPD Bronchopulmonary Dysplasia EONS Early Onset Neonatal Sepsis GA Gestational Age GDM Gestational diabetes mellitus HMIS Health Management Information System IQR Interquartile Range IVH Intraventricular Hemorrhage KMC Kangaroo Mother Care NEC Necrotizing Enterocolitis NICU Neonatal Intensive Care Unit PROM Premature Rupture of Membranes RDS Respiratory Distress Syndrome WHO World Health Organization WUCSH Wallaga University Comprehensive Specialized Hospital Declarations Ethics approval and consent to participate: Ethical clearance was obtained from the Wallaga University Institute of Health Science Research Ethics Committee. The study was conducted in accordance with the principles of the Declaration of Helsinki. The need for informed consent was waived by the ethics committee because the data were collected retrospectively from medical records without any direct patient contact. Institute of health science, medical science academic and service directorate wrote an official letter of permission to NICU and Record room head for securing permission. After obtaining permission data gathered from charts. Information obtained from the charts was kept confidentially by not recording neonates and their mother’s name on check lists. Data was kept secured by password which accessed only by researcher and data collectors. Consent for publication: Not applicable. Availability of data and materials: The datasets used during the current study are available from the corresponding author on reasonable request. Competing interests: No competing interests. Funding: No external funding. Authors’ contributions: Minase Abera: Collected and analyzed the data, interpreted the results, and prepared the manuscript. Fikadu Enkosa: Contributed as academic advisor, assisted with data analysis and interpretation, and critically reviewed the manuscript. Emiru Merdassa: Contributed as academic advisor, assisted with data analysis and interpretation, and critically reviewed the manuscript. Acknowledgements: We would like to thank Wallaga University for giving us the opportunity to conduct this study. Clinical trial number: Not applicable. References WHO. Preterm birth [Internet]. 2023 [cited 2024 Jun 30]. Available from: https://www.who.int/news-room/fact-sheets/detail/preterm-birth Khasawneh W, Khriesat W. Assessment and comparison of mortality and short-term outcomes among premature infants before and after 32-week gestation: A cross-sectional analysis. Ann Med Surg [Internet]. 2020 Dec 1 [cited 2024 Sep 7];60:44–9. Available from: https://pubmed.ncbi.nlm.nih.gov/33101673/ Taha Z, Hassan AA, Wikkeling-Scott L, Papandreou D. Factors Associated with Preterm Birth and Low Birth Weight in Abu Dhabi, the United Arab Emirates. Int J Environ Res Public Health [Internet]. 2020 Feb 2 [cited 2024 Sep 7];17(4). 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The causes of preterm neonatal deaths in India and Pakistan (PURPOSe): a prospective cohort study. Lancet Glob Heal [Internet]. 2022 Nov 1 [cited 2024 Jun 30];10(11):e1575–81. Available from: https://pubmed.ncbi.nlm.nih.gov/36240824/ Toma TM, Merga H, Dube L. Incidence and Predictors of Mortality Among Preterm Neonates Admitted to Jimma University Medical Center, Southwest Ethiopia: a Retrospective Follow-Up Study. Int J Public Health [Internet]. 2024 [cited 2025 Apr 19];69. Available from: https://pubmed.ncbi.nlm.nih.gov/39027016/ Mwansa-Kambafwile J, Cousens S, Hansen T, Lawn JE. Antenatal steroids in preterm labour for the prevention of neonatal deaths due to complications of preterm birth. Int J Epidemiol [Internet]. 2010 Apr 1 [cited 2024 Jun 30];39(Suppl 1):i122. Available from: /pmc/articles/PMC2845868/ Mihretu E, Genie YD, Adugnaw E, Shibabaw AT. Survival status and predictors of mortality among preterm neonates admitted in Bench Sheko Zone, Sheka Zone and Keffa Zone Governmental Hospitals, Southwest Ethiopia (2021): prospective follow-up study. BMJ Open [Internet]. 2024 Apr 23 [cited 2025 Apr 12];14(4). Available from: https://pubmed.ncbi.nlm.nih.gov/38658009/ Kamgaing EK, Rogombe SM, Maniaga RK, Mouboungou N, Mikolo AL, Mintsa-Mi-Nkama E, et al. Risk factors for mortality of preterm infants in the neonatal medicine department of the ‘Mère-Enfant’ University Hospital Centre of Libreville. Int J Contemp Pediatr [Internet]. 2023 Jan 24 [cited 2024 Jun 30];10(2):126–33. Available from: https://www.ijpediatrics.com/index.php/ijcp/article/view/5228 Mekasha A, Tazu Z, Muhe L, Abayneh M, Gebreyesus G, Girma A, et al. Factors Associated with the Death of Preterm Babies Admitted toNeonatal Intensive Care Units in Ethiopia: A Prospective, Cross-sectional, andObservational Study. Glob Pediatr Heal [Internet]. 2020 [cited 2024 Jun 30];7. Available from: /pmc/articles/PMC7689001/ Taylor RS, Singh B, Mukerji A, Dorling J, Alvaro R, Lodha A, et al. Intermediate vs. High Oxygen Saturation Targets in Preterm Infants: A National Cohort Study. Neonatology [Internet]. 2025 Feb 7 [cited 2025 Apr 28];122(1):106–13. Available from: https://dx.doi.org/10.1159/000540278 Cantey JB, Pyle AK, Wozniak PS, Hynan LS, Sánchez PJ. Early Antibiotic Exposure and Adverse Outcomes in Preterm, Very Low Birth Weight Infants. J Pediatr [Internet]. 2018 Dec 1 [cited 2025 Apr 28];203:62–7. Available from: https://www.sciencedirect.com/science/article/abs/pii/S0022347618309417 Girma B, Nigussie J. Magnitude of preterm hospital neonatal mortality and associated factors in northern Ethiopia: a cross-sectional study. BMJ Open [Internet]. 2021 Dec 1 [cited 2024 Jun 30];11(12):e051161. Available from: https://bmjopen.bmj.com/content/11/12/e051161 Additional Declarations No competing interests reported. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6697745","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":470870551,"identity":"e9849e2e-5b22-4fbc-846c-61ae21df9bb4","order_by":0,"name":"Minase 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Merdassa","email":"","orcid":"","institution":"Wallaga University","correspondingAuthor":false,"prefix":"","firstName":"Emiru","middleName":"","lastName":"Merdassa","suffix":""}],"badges":[],"createdAt":"2025-05-19 10:08:13","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6697745/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6697745/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":84869451,"identity":"70ce5db6-20b2-4121-8663-18c3c0043dc0","added_by":"auto","created_at":"2025-06-18 08:49:49","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":18734,"visible":true,"origin":"","legend":"\u003cp\u003eFrequency distribution of gestational age categories among preterm neonates admitted to NICU at WUCSH, Nekemte Town, East Wallaga, Oromia, Ethiopia, from July 1, 2022 to June 30, 2024 GC.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-6697745/v1/ee4089a869d0274cb661875c.png"},{"id":84869453,"identity":"96d51adf-dbf4-412b-999b-c58eb7566eed","added_by":"auto","created_at":"2025-06-18 08:49:49","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":21249,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eOutcomes of preterm neonates admitted to NICU at WUCSH, Nekemte Town, East Wallaga, Oromia, Ethiopia, from July 1, 2022 to June 30, 2024 GC.\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-6697745/v1/56239d96c65f4682f67987c1.png"},{"id":84869454,"identity":"35be1b8b-5765-40a6-9bf4-24ca42a958af","added_by":"auto","created_at":"2025-06-18 08:49:49","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":60163,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eOverall Kaplan-Meier Survival probability curve of preterm neonates admitted to NICU at WUCSH, Nekemte Town, East Wallaga, Oromia, Ethiopia, from July 1, 2022 to June 30, 2024 GC.\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-6697745/v1/0163840e6f00a72b16fedd6a.png"},{"id":84870591,"identity":"1943add1-8c41-4d1b-8d68-aa7c35516ba8","added_by":"auto","created_at":"2025-06-18 08:57:49","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":206427,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eKaplan-Meier Curve to compare survival probability by ANC follow-up, Antenatal steroid use, Place of birth, Resuscitation at birth, and Neonatal complication among preterm neonates admitted to the NICU at WUCSH.\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-6697745/v1/8e41118ca6953d3d361c09d3.png"},{"id":101849035,"identity":"9fdf6e82-ad20-487f-a0cd-93c44d43aac2","added_by":"auto","created_at":"2026-02-04 09:43:23","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1997270,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6697745/v1/8207d745-356f-4580-b8cc-4f6326396276.pdf"},{"id":84869459,"identity":"68f4f14d-2426-4edc-9b4f-2544ff7cd814","added_by":"auto","created_at":"2025-06-18 08:49:49","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":72023,"visible":true,"origin":"","legend":"","description":"","filename":"Supplementarymaterial.docx","url":"https://assets-eu.researchsquare.com/files/rs-6697745/v1/6a67116118395a3157750ccc.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Incidence and predictors of mortality among preterm neonates admitted to the neonatal intensive care unit of Wallaga University Comprehensive Specialized Hospital, Nekemte Town, East Wallaga, Oromia, Ethiopia: a retrospective cohort study","fulltext":[{"header":"1. Background","content":"\u003cp\u003ePreterm birth, defined as birth before 37 completed weeks of gestation, is a global public health concern. It is categorized into three groups based on gestational age: moderate to late preterm (32\u0026ndash;37 weeks), very preterm (28\u0026ndash;\u0026lt;32 weeks), and extremely preterm (\u0026lt;\u0026thinsp;28 weeks). Globally, approximately 1 in 10 newborns is born preterm, with the highest burden in Southern Asia and sub-Saharan Africa, where neonatal survival is significantly lower compared to high-income countries (1). The prevalence of preterm birth varies from 5\u0026ndash;18% across 184 countries (2,3), with six nations\u0026mdash;India, China, Nigeria, Pakistan, Indonesia, and the United States\u0026mdash;accounting for nearly half of the global burden (4).\u003c/p\u003e \u003cp\u003ePreterm birth arises from either spontaneous onset of labor or medically indicated delivery due to maternal or fetal complications. Risk factors include infections, inflammation, vascular conditions, uterine overdistension, and obstetric conditions such as pre-eclampsia and intrauterine growth restriction (5,6). Additional maternal and fetal factors\u0026mdash;including low maternal body mass index (BMI), parity, employment status, preeclampsia, low birth weight, male sex, and multiple gestations\u0026mdash;also contribute (6,7). A meta-analysis of 30 studies in Ethiopia reported a national preterm birth prevalence of 11.4%, with significant associations observed for pregnancy-induced hypertension, HIV infection, premature rupture of membranes (PROM), rural residence, multiple pregnancies, and maternal anemia (8).\u003c/p\u003e \u003cp\u003ePreterm neonates face a high risk of both short- and long-term complications. In the immediate neonatal period, respiratory distress syndrome (RDS), necrotizing enterocolitis, and intraventricular hemorrhage are frequent contributors to morbidity and mortality (9,10). Long-term consequences include increased risks for cardiovascular disease, bronchopulmonary dysplasia (BPD), cerebral palsy, and developmental delays. These risks escalate with decreasing gestational age, and the prognosis is particularly poor for neonates born before 24 weeks (9\u0026ndash;11).\u003c/p\u003e \u003cp\u003eGlobally, complications of preterm birth are responsible for nearly 1\u0026nbsp;million deaths annually, contributing to 18% of all deaths among children under five and up to 35% of neonatal deaths (4). Sub-Saharan Africa and Southern Asia account for 65% of preterm births, with the highest mortality rates observed in low-income settings. In Africa, more than 90% of extremely preterm infants die within the first few days, compared to fewer than 10% in high-income countries, due to limitations in access to quality neonatal care (1,12).\u003c/p\u003e \u003cp\u003eIn Ethiopia, the incidence proportion of preterm neonatal mortality is estimated at 30%, with an incidence density of 40 per 1,000 person-days. Identified predictors of mortality include birth before 32 weeks, male sex, low Apgar scores, birth asphyxia, low birth weight, RDS, neonatal jaundice and sepsis, antepartum hemorrhage, and the absence of kangaroo mother care (KMC) (13).\u003c/p\u003e \u003cp\u003eDespite the availability of effective interventions, including antenatal corticosteroids, kangaroo mother care, neonatal resuscitation, magnesium sulfate, and delayed cord clamping, implementation gaps persist in resource-limited settings (1,14,15). Ethiopia\u0026rsquo;s National Neonatal and Child Survival Strategy emphasizes these interventions and aims to reduce neonatal mortality through improved health infrastructure and community engagement. However, barriers such as workforce limitations and supply shortages hinder progress, and neonatal mortality remains a pressing issue (13,16).\u003c/p\u003e \u003cp\u003eTo date, no studies have assessed the incidence and predictors of preterm neonatal mortality in the study area. Generating local data is essential to inform tailored interventions, strengthen neonatal care services, and support national efforts to reduce neonatal mortality.\u003c/p\u003e"},{"header":"2. Methods And Materials","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e1.1. Study Design and Setting\u003c/h2\u003e \u003cp\u003eAn institution-based retrospective cohort study was conducted. It involved review of charts of preterm neonates admitted between 1 July, 2022 and 30 June, 2024 GC. This study was carried out at WUCSH located in Nekemte town, the capital city of East Wallaga, lies 331 kilometers west of Addis Ababa. WUCSH, a teaching and specialized hospital, serves an estimated population of 5\u0026nbsp;million within its catchment area. The hospital offers NICU services, to both inborn and out born term and preterm neonates.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2. Population\u003c/h2\u003e \u003cp\u003e \u003cb\u003eSource population\u003c/b\u003e \u003c/p\u003e \u003cp\u003eAll preterm neonates admitted to the neonatal intensive care unit of WUCSH.\u003c/p\u003e \u003cp\u003e \u003cb\u003eStudy population\u003c/b\u003e \u003c/p\u003e \u003cp\u003eAll preterm neonates admitted to the neonatal intensive care unit of WUCSH from July 1, 2022 to June 30, 2024 GC.\u003c/p\u003e \u003cp\u003e \u003cb\u003eStudy unit\u003c/b\u003e \u003c/p\u003e \u003cp\u003eEach randomly selected preterm neonate's chart from the HMIS registry book.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e2.3. Eligibility Criteria\u003c/h2\u003e \u003cp\u003e \u003cb\u003eInclusion criteria\u003c/b\u003e \u003c/p\u003e \u003cp\u003eFiles of all preterm neonates admitted to the NICU from July 1, 2022 to June 30, 2024 GC.\u003c/p\u003e \u003cp\u003e \u003cb\u003eExclusion criteria\u003c/b\u003e \u003c/p\u003e \u003cp\u003eFiles of preterm neonates that was incomplete during the study period.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003e2.4. Sample Size Determination and Sampling Technique\u003c/h2\u003e \u003cp\u003e \u003cb\u003eSample size determination\u003c/b\u003e \u003c/p\u003e \u003cp\u003eA previously conducted study at public hospitals in southern Ethiopia was used as a reference to calculate the sample size. The sample size is determined using STATA version 14.0 (Cox model) with the assumptions of 95% CI, 5% margin of error, 80% power, a variability (SD) of 0.5, and probability of failure (event) of 0.255. Predictors of preterm neonatal death included were lack of antenatal care, primiparity, pregnancy complications, resuscitation at birth, and absence of Kangaroo mother care (17).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eSample size determination for incidence and predictors of mortality among preterm neonates admitted to NICU at WUCSH, Nekemte Town, East Wallaga, Oromia, Ethiopia from July 1, 2022 to June 30, 2024 GC.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAssociated factors\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eHR\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003ePower\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eTotal sample (with 15% for incomplete records)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eReferences\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e1\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003elack of ANC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e7.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e(17)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e2\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePrimiparity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e209\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e(17)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e3\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePregnancy complications\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e97\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e(17)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e4\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eResuscitation at birth\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e264\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e(17)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e5\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAbsence of KMC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e9.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e(17)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eFinally, the largest calculated sample size (\u003cb\u003e264\u003c/b\u003e) was selected as the final sample size.\u003c/p\u003e \u003cp\u003e \u003cb\u003eSampling techniques\u003c/b\u003e \u003c/p\u003e \u003cp\u003eStudy subjects were selected using a systematic random sampling (SRS) technique. The sampling interval (K) was determined by dividing the total number of preterm neonates over the study period by the required sample size (K\u0026thinsp;=\u0026thinsp;N/n). The sampling frame consisted of patient records listed in the HMIS registry book, and every 2nd record was selected until the total sample size was reached. The first record was chosen randomly using a lottery method. Only medical records with complete information were included; if a selected chart was missing or incomplete, the next available record in sequence was used.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003e2.5. Study Variables\u003c/h2\u003e \u003cp\u003e \u003cb\u003eDependent variable\u003c/b\u003e \u003c/p\u003e \u003cp\u003eIncidence of mortality.\u003c/p\u003e \u003cp\u003e \u003cb\u003eIndependent variables\u003c/b\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eMaternal related predictors\u003c/strong\u003e \u003cp\u003eAge, parity, obstetrics related factors (pregnancy induced hypertension, GDM), preterm labor, maternal infection (chorioamnionitis), antenatal care, and antenatal steroid use.\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eNeonatal related predictors\u003c/strong\u003e \u003cp\u003eGender of the baby, place of delivery, mode of delivery, gestational age, birth weight, APGAR score, resuscitation at birth, and hospital complications.\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eHealth facility related predictors\u003c/strong\u003e \u003cp\u003eLength of hospital stay, oxygen therapy, and antibiotics \u0026amp; other treatments\u003c/p\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003e2.6. Operational Definition\u003c/h2\u003e \u003cp\u003e \u003cstrong\u003eCensored\u003c/strong\u003e \u003cp\u003eDefined when preterm neonates discharge improved, lost to follow up or referred to other institution within the study period (18).\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eEvent\u003c/strong\u003e \u003cp\u003eReferred to the death of preterm neonates during their hospital stay (18).\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eFollow up time\u003c/strong\u003e \u003cp\u003eThe time starting from admission until either an event or censorship occurs, with a maximum follow-up period of 30 days (18).\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eTime scale\u003c/strong\u003e \u003cp\u003eDays from the admission of a preterm neonate (18).\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003ePreterm\u003c/strong\u003e \u003cp\u003eNeonates born alive before 37 weeks of pregnancy are completed (1).\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eModerate to late preterm\u003c/strong\u003e \u003cp\u003eInfants are those born between 32 weeks and 37 weeks of gestation (1).\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eVery preterm\u003c/strong\u003e \u003cp\u003eIs defined as 28weeks of gestation to fewer than 32 weeks of gestation (1).\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eExtremely preterm\u003c/strong\u003e \u003cp\u003eIs designated less than 28 weeks of gestational age (1).\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eRespiratory distress\u003c/strong\u003e \u003cp\u003eClinically diagnosed in premature infants with rapid, labored breathing, often with grunting, flaring nostrils, and chest wall retractions (19).\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eHypothermia\u003c/strong\u003e \u003cp\u003eDefined as skin (axillary) temperature less than 36.5\u003csup\u003e0\u003c/sup\u003eC (19).\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eApnea\u003c/strong\u003e \u003cp\u003eDefined as absence of air flow for \u0026ge;\u0026thinsp;20 seconds or less than that if it is accompanied by bradycardia (heart rate\u0026thinsp;\u0026lt;\u0026thinsp;100/min) or cyanosis (19).\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eNecrotizing enterocolitis\u003c/strong\u003e \u003cp\u003eA clinical diagnosis can be established when a neonate presents with symptoms such as abdominal distention, feeding intolerance, vomiting, bloody stools, loose stools, abdominal wall erythema, and vital sign instability (19).\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eSepsis\u003c/strong\u003e \u003cp\u003eClinical diagnosis is based on the presence of symptoms such as temperature instability, respiratory distress, feeding difficulties, lethargy, seizures, and jaundice in neonates with known risk factors, including maternal infection, PROM, or the need for resuscitation at birth. Further divided into Early onset (below 7 days) and Late onset (7\u0026ndash;28 days) sepsis (19).\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eFirst-line antibiotics\u003c/strong\u003e \u003cp\u003eRefer to the initial antibiotics administered, commonly including ampicillin and gentamicin (19).\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eSecond-line antibiotics\u003c/strong\u003e \u003cp\u003eare those that are either added or changed into if there is no improvement after 48 hours or if the infant\u0026rsquo;s condition worsens (19).\u003c/p\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003e2.7. Data Collection Tools and Procedures\u003c/h2\u003e \u003cp\u003eA structured checklist was adapted for the collection of secondary data from medical records. This checklist was developed through a review of relevant literature and a critical evaluation of existing studies, with a focus on socio-demographic characteristics, maternal medical and obstetric history, prenatal factors, and neonatal variables associated with incidence of preterm mortality (8,13,22,25,26\u0026ndash;32). Birth weight and gestational age at birth were classified according to WHO standards (1). Data was collected by trained neonatal nurses from September 15 to October 15, 2024 GC.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003e2.8. Data Processing and Analysis\u003c/h2\u003e \u003cp\u003eData entry was conducted using EpiData version 4.6, and the data was then exported to STATA 14.1. statistical software for analysis. Multicollinearity test was done, and no significant correlation was detected among the independent variables.\u003c/p\u003e \u003cp\u003eThe Incidence proportion and Incidence Density Rate (IDR) was calculated for the entire study period. Subsequently, the number of mortalities within the follow-up period was divided by the total neonate-time at risk during follow-up and reported per 1000-neonate days. The Kaplan-Meier curve was used to estimate median survival time, and log-rank tests was used to compare survival curves.\u003c/p\u003e \u003cp\u003eThe Cox proportional hazards assumption was also checked using both graphs and Schoenfeld\u0026rsquo;s residual test, with variables having p-values greater than 0.05 being considered as fulfilling the assumption. The Cox-Snell residuals were also used to assess the overall goodness-of-fit of the Cox proportional hazards model. Bivariable cox regression was first fitted and those independent variables having p-value\u0026thinsp;\u0026lt;\u0026thinsp;0.2 were included in the multivariable analysis. Finally, statistical significance was declared at a p-value\u0026thinsp;\u0026lt;\u0026thinsp;0.05. Hazard Ratios (HR) with 95% Confidence Intervals (CI) was used to assess the relationship between factors associated with the occurrence of death.\u003c/p\u003e \u003cp\u003eVariables with zero events during the follow-up period (UTI, Intrauterine infection, APH, Hepatitis B infection, and first-line antibiotics) were excluded from Cox regression due to inability to estimate hazard ratios, but were included in descriptive statistics.\u003c/p\u003e \u003cp\u003eMaternal age was initially recorded in 15\u0026ndash;19, 20\u0026ndash;34 \u0026amp; \u0026ge;35years age bands, but was re-grouped into \u0026lt;\u0026thinsp;20 \u0026amp; \u0026ge;20years because the \u0026ge;\u0026thinsp;35 years group had zero deaths. Similarly, Place of ANC Follow up was re-categorized into Health center \u0026amp; Hospital due to zero events occurs in Tertiary Hospitals.\u003c/p\u003e \u003c/div\u003e"},{"header":"3. Results","content":"\u003cp\u003e \u003cb\u003eDescription of study participants\u003c/b\u003e \u003c/p\u003e \u003cp\u003eA total of 264 preterm neonates were selected for this study. Among the selected neonatal charts, 5 were excluded due to missing key information such as discharge outcome, date of admission, date of discharge, and other essential baseline data. Finally, two hundred fifty-nine (259) neonatal charts were included in the analysis with 98.1% response rate.\u003c/p\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003e3.1. Socio-Demographic Characteristics and Antenatal Care Status of Mothers\u003c/h2\u003e \u003cp\u003eAccording to this study, the mothers' ages ranged from 15 to 38 years, with a mean age of 24.4\u0026thinsp;\u0026plusmn;\u0026thinsp;1.4 years. The most common age group was \u0026ge;\u0026thinsp;20 years (88.8%). The majority of the mothers had one or two children 210(81.1%) and lived in rural areas 176(67.9%).\u003c/p\u003e \u003cp\u003eThe majority of mothers had antenatal care (ANC) follow-up, with 192 (74.1%) attending, of whom 120 (62.5%) visited a health center. Additionally, 180 (93.7%) of them had fewer than four ANC visits, which is below the current national guideline recommendation of at least eight visits. During pregnancy, 116 (44.8%) experienced pregnancy-related complications. The most common complications were pregnancy-related hypertension (30.1%), premature rupture of membranes (PROM) (6.6%), and malaria (6.2%), as shown in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e below.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eSocio-demographic characteristics of mothers of preterm neonates admitted to the NICU at WUCSH, Nekemte Town, East Wallaga, Oromia, Ethiopia, from July 1, 2022 to June 30, 2024 GC.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eVariables\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eVariables\u003c/p\u003e \u003cp\u003eFrequency (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c5\" namest=\"c3\"\u003e \u003cp\u003eSurvival Status\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003eEvent (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eCensored (%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eAge\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;20yrs\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e29(11.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3(1.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e26(10)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026ge;\u0026thinsp;20yrs\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e230(88.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e39(15.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e191(73.7)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eResidence\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eUrban\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e83(32.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8(3.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e75(28.9)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRural\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e176(67.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e34(13.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e142(54.8)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eParity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1-2birth\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e210(81.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e37(14.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e173(66.8)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3-5birth\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e40(15.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4(1.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e36(13.9)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;5birth\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9(3.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1(0.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e8(3.1)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eANC Follow up\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e192(74.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e15(5.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e177(68.3)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e67(25.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e27(10.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e40(15.4)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003ePlace of ANC Follow up\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHealth Center\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e120(62.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e13(6.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e107(55.7)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHospital\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e72(37.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2(1.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e70(36.4)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eFrequency of ANC Follow up\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;4 times\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e180(93.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e14(7.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e166(86.4)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026ge;\u0026thinsp;4 times\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e12(6.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1(0.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e11(5.8)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eAntenatal Steroid use\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e132(50.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e15(5.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e117(45.1)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e127(49.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e27(10.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e100(38.6)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003ePregnancy related complication\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e116(44.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e26(10)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e90(34.8)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e143(55.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e16(6.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e127(49)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003ePregnancy induced Hypertension\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e78(30.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e16(6.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e62(23.9)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e181(69.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e26(10)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e155(59.9)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003ePROM\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e17(6.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4(1.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e13(5.1)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e242(93.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e38(14.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e204(78.7)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eUTI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3(1.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0(0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3(1.2)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e256(98.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e42(16.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e214(82.6)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eIntrauterine infection (Chorioamnionitis)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2(0.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0(0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2(0.8)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e257(99.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e42(16.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e215(83)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eMalaria\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e16(6.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8(3.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e8(3.1)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e243(93.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e34(13.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e209(80.7)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eAPH\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2(0.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0(0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2(0.8)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e257(99.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e42(16.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e215(83)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eHepatitis B virus status\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePositive\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4(1.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0(0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4(1.5)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNegative\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e255(98.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e42(16.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e213(82.3)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003e3.2. Profile of Preterm Neonates\u003c/h2\u003e \u003cp\u003eAccording to this study, most of the preterm neonates were between 32 to 37 weeks 222(85.7%), with 5 (1.9%) being extremely preterm, as shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e below.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThe male preterm neonates accounts for 183 (70.7%) of the total cases. Majority of preterm neonates had a birth weight ranging from 1500 to 2400 grams, with 181 (69.9%). Additionally, most of the preterm neonates were born in hospital, comprising 229 (88.4%) of the total cases, as shown in Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e below.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eProfile of preterm neonates admitted to the NICU at WUCSH, Nekemte Town, East Wallaga, Oromia, Ethiopia, from July 1, 2022 to June 30, 2024 GC.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" morerows=\"1\" nameend=\"c2\" namest=\"c1\" rowspan=\"2\"\u003e \u003cp\u003eVariables\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eVariables\u003c/p\u003e \u003cp\u003eFrequency (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003eSurvival Status\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eEvent (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eCensored (%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eSex of the neonate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e183(70.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e29(11.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e154(59.5)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e76(29.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e13(5.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e63(24.3)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003ePlace of birth\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHome delivery\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6(2.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3(1.16)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3(1.16)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHealth Center\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e24(9.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6(2.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e18(7)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHospital\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e229(88.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e33(12.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e196(75.7)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eGestational age\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026le;\u0026thinsp;28weeks\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5(1.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4(1.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1(0.4)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e28-32weeks\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e32(12.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2(0.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e30(11.6)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e32-37weeks\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e222(85.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e36(13.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e186(71.8)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eBirth weight\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;1000gm\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5(1.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4(1.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1(0.4)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1000-1499gm\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e73(28.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e10(3.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e63(24.3)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1500-2400gm\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e181(69.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e28(10.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e153(59.1)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eAPGAR score\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eKnown\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e224(86.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e35(13.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e189(73)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eUnknown\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e35(13.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7(2.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e28(10.8)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eFifth minute APGAR score\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026ge;\u0026thinsp;7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e196(87.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e20(8.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e176(78.6)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e28(12.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e15(6.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e13(5.8)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eResuscitation at birth\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e44(16.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e21(8.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e23(8.8)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e215(83.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e21(8.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e194(75)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003e3.3. Hospital Complications of Preterm Neonates\u003c/h2\u003e \u003cp\u003eThe majority of preterm neonates, 254 (98.1%), experienced one or more hospital complications. The most common complications were hypothermia in 179(69.1%) of the cases, followed by RDS in 119 (45.9%), EONS in 105(40.5%), jaundice in 54(20.8%), and Apnea in 23(8.8%), as shown in Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e below.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eHospital complications of preterm neonates admitted to the NICU at WUCSH, Nekemte Town, East Wallaga, Oromia, Ethiopia, from July 1, 2022 to June 30, 2024 GC.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" morerows=\"1\" nameend=\"c2\" namest=\"c1\" rowspan=\"2\"\u003e \u003cp\u003eVariables\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eVariables\u003c/p\u003e \u003cp\u003eFrequency (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003eSurvival Status\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eEvent (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eCensored (%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eNeonatal complications\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e254(98.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e42(16.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e212(81.9)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5(1.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0(0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e5(1.9)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eHypothermia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e179(69.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e35(13.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e144(55.6)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e80(30.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7(2.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e73(28.2)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eRDS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e119(45.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e29(11.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e90(34.7)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e140(54.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e13(5.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e127(49.1)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eEONS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e105(40.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e21(8.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e84(32.4)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e154(59.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e21(8.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e133(51.4)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eJaundice\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e54(20.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e18(6.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e36(13.9)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e205(79.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e24(9.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e181(69.9)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eApnea\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e23(8.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7(2.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e16(6.1)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e236(91.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e35(13.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e201(77.6)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eSeizure\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e16(6.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6(2.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e10(3.9)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e243(93.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e36(13.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e207(79.9)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eNEC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e14(5.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8(3.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e6(2.3)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e245(94.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e34(13.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e211(81.5)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eIVH\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e13(5.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2(0.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e11(4.3)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e246(94.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e40(15.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e206(79.5)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eAnemia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e12(4.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7(2.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e5(1.9)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e247(95.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e35(13.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e212(81.9)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eCongenital Malformation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6(2.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2(0.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e4(1.5)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e253(97.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e40(15.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e213(82.3)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003e3.4. Treatment Given to Preterm Neonates\u003c/h2\u003e \u003cp\u003eIn this study, preterm neonates received a range of treatments including oxygen, antibiotics, aminophylline, phototherapy, phenobarbital, and blood transfusions. The three most commonly given treatments were first-line antibiotic therapy 198(76.4%), followed by oxygen therapy 145(55.9%) and second-line antibiotic therapy 83(41.9%), as shown in Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e below.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eTreatment given to preterm neonates admitted to the NICU at WUCSH, Nekemte Town, East Wallaga, Oromia, Ethiopia, from July 1, 2022 to June 30, 2024 GC.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" morerows=\"1\" nameend=\"c2\" namest=\"c1\" rowspan=\"2\"\u003e \u003cp\u003eVariables\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eVariables\u003c/p\u003e \u003cp\u003eFrequency (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003eSurvival Status\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eEvent (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eCensored (%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eFirst-line antibiotics\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e198(76.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e42(16.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e156(60.2)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e61(23.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0(0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e61(23.6)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eOxygen therapy\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e145(55.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e40(15.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e105(40.5)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e114(44.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2(0.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e112(43.3)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eSecond-line antibiotics\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e83(41.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e26(13.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e57(28.8)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e115(58.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e16(8.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e99(50)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eAminophylline\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e31(11.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e15(5.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e16(6.1)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e228(88.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e27(10.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e201(77.7)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003ePhototherapy\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e29(11.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5(1.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e24(9.3)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e230(88.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e37(14.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e193(74.5)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eBlood transfusion\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e13(5.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6(2.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e7(2.7)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e246(94.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e36(13.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e210(81)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003ePhenobarbital\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11(4.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6(2.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5(1.9)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e248(95.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e36(13.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e212(81.9)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003e3.5. Outcome of Preterm Neonates\u003c/h2\u003e \u003cp\u003eFigure \u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e shows the outcomes of 259 preterm neonates admitted to the NICU at WUCSH between July 1, 2022, and June 30, 2024 GC and included in the study. Of the neonates, 206 (79.5%) were discharged after clinical improvement, 42 (16.2%) died, 4 (1.5%) were referred, and 7 (2.7%) were lost to follow-up.\u003c/p\u003e \u003cp\u003eThis figure shows valuable insight into the overall prognosis of preterm neonates during the study period. While the majority (over 79.5%) improved with treatment, the incidence proportion of 16.2% highlights the severity of the condition in this vulnerable population. The relatively high mortality underscores the critical need for improved preventing complication, optimized neonatal care, and early identification of risk factors associated with poor outcomes.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003e3.6. Incidence of Mortality among Preterm Neonates Admitted to NICU\u003c/h2\u003e \u003cp\u003eOut of 259 preterm neonates included in the study, 42 died during the follow-up period, makes an incidence proportion of 16.2%. The median survival time was 28 days, with an interquartile range (IQR) of 22 to 30 days. During follow-up time, a total of 2737 neonate-day observation were observed with a minimum of 1 day and maximum of 30 days follow-up time. The overall mortality incidence rate was 15.3 per 1,000 preterm neonates-day (CI: 11.3, 20.7).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec18\" class=\"Section2\"\u003e \u003ch2\u003e3.7. Over-all Kaplan- Meier Failure Estimate\u003c/h2\u003e \u003cp\u003eThe overall Kaplan-Meier estimate showed that the probability of survival of preterm neonates was higher on the first day of admission, with increased failure to survive throughout the follow-up period. Notably, sharper drops in survival were observed after around 15 days, as shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e below.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec19\" class=\"Section2\"\u003e \u003ch2\u003e3.8. Predictors of Mortality Among Preterm Neonates Admitted NICU.\u003c/h2\u003e \u003cp\u003eThe study identified several significant predictors of neonatal mortality among preterm neonates admitted to the NICU. Lack of antenatal care (ANC) follow-up was associated with a more than twofold increased risk of mortality (AHR: 2.27, 95% CI: 1.13\u0026ndash;4.57). Neonates born at home were particularly vulnerable, with a markedly elevated mortality risk (AHR: 7.74, 95% CI: 1.99\u0026ndash;30.03) compared to those born in hospital. Hypothermia is also strong independent predictors, with adjusted hazard ratios of 4.11 (95% CI: 1.55\u0026ndash;10.85). Importantly, antenatal steroid use demonstrated a protective effect, reducing preterm mortality by 55.7% (AHR: 0.44, 95% CI: 0.21\u0026ndash;0.92). These findings highlight the critical importance of quality antenatal care, including hospital delivery, proper thermal regulation, and interventions including antenatal steroid use, in improving preterm neonatal survival.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab6\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 6\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eResults of the bivariate and multivariate Cox regression analysis of predictors of mortality among preterm neonates admitted to the NICU at WUCSH, Nekemte Town, East Wallaga, Oromia, Ethiopia, from July 1, 2022 to June 30, 2024 GC.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eVariables\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eCategory\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c5\" namest=\"c3\"\u003e \u003cp\u003eStatus\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eCHR (95% CI)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eAHR (95%CI)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003eTotal (%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003eEvent (%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003eCensored (%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eANC Follow up\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e192(74.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e15(5.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e177(68.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e67(25.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e27(10.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e40(15.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3.42(1.80\u0026ndash;6.51)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e2.27(1.13\u0026ndash;4.57) *\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eAntenatal Steroid use\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e132(50.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e15(5.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e117(45.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.31(0.15\u0026ndash;0.61)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e0.44(0.21\u0026ndash;0.92) *\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e127(49.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e27(10.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e100(38.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003ePlace of birth\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHome delivery\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6(2.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3(1.16)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3(1.16)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e9.95(2.87\u0026ndash;34.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e7.74(1.99\u0026ndash;30.03) **\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHealth Center\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e24(9.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6(2.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e18(7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.41(1.00-5.83)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.65(0.61\u0026ndash;4.45)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHospital\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e229(88.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e33(12.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e196(75.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eResuscitation at birth\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e44(16.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e21(8.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e23(8.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.21(1.17\u0026ndash;4.19)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.84(0.86\u0026ndash;3.89)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e215(83.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e21(8.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e194(75)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eHypothermia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e179(69.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e35(13.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e144(55.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.96(1.29\u0026ndash;6.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e4.11(1.55\u0026ndash;10.85) **\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e80(30.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7(2.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e73(28.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eAnemia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e13(5.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8(3.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5(2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.32(1.01\u0026ndash;5.31)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2.00(0.79\u0026ndash;5.05)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e246(94.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e34(13.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e212(81.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eIVH\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e13(5.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2(0.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e11(4.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.37(0.08\u0026ndash;1.57)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.67(0.14\u0026ndash;2.99)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e246(94.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e40(15.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e206(79.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eSeizure\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e16(6.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6(2.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e10(3.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.82(0.75\u0026ndash;4.39)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2.20(0.78\u0026ndash;6.23)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e243(93.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e36(13.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e207(79.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"7\"\u003eAHR: Adjusted Hazard Ratio; CHR: Crude Hazard Ratio\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e* Statistically significant at p\u0026thinsp;\u0026lt;\u0026thinsp;0.05; ** statistically significant at p\u0026thinsp;\u0026lt;\u0026thinsp;0.01.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec20\" class=\"Section2\"\u003e \u003ch2\u003e3.9. Kaplan-Meier Curve for Different Categorical Variable\u003c/h2\u003e \u003cp\u003eSeparate Kaplan-Meier graphs were constructed to compare the survival probability across different covariates. In the Kaplan-Meier survival curves, one curve lying above the other indicates that the group represented by the higher curve has a longer survival time compared to the group with the lower curve. The log-rank test was used to assess the statistical significance of differences in survival probability among the groups at a 5% significance level.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"4. Discussion","content":"\u003cp\u003eThis Study is aimed to assess incidence and predictors of mortality among preterm neonates admitted to the NICU of Wallaga University Comprehensive Specialized Hospital. From a total of 259 preterm neonates admitted to the NICU 42(16.2%) were died with the median time to death of 28 days with IQR of 22 to 30 days. Throughout the follow-up period, the overall incidence of mortality was 15.3 per 1000 preterm neonates (CI: 11.3, 20.7).\u003c/p\u003e \u003cp\u003eThe incidence proportion of preterm mortality observed in this study is lower than rates reported in other settings. Studies from Tikur Anbessa, Gondar, and Mizan Tepi reported higher proportions ranging from 28.8\u0026ndash;35% (18,20,21), while a study in Southern Ethiopia reported 25.5% (17). Outside Ethiopia, mortality rates were 31.6% in Uganda (22), 20.7% in Sierra Leone (23), and 23% in the India-Pakistan PURPOSe cohort (24). These differences may reflect variations in sample size, follow-up duration, and population characteristics.\u003c/p\u003e \u003cp\u003eStudies from Ethiopia have reported shorter median survival times and higher incidence rates than this study. Tikur Anbessa Specialized Hospital found a median survival of 21 days with an incidence rate of 39.1 per 1,000 neonate-days (18). Mizan Tepi reported 15 days and 62.15, respectively (21), while a study from Southern Ethiopia showed 18 days with a rate of 47.7 (17). At Jimma University Medical Center, the incidence rate was 28.9 per 1,000 neonate-days (25). These variations may reflect differences in study design, population characteristics, or NICU care quality.\u003c/p\u003e \u003cp\u003eSeveral predictors were significantly associated with increased mortality. Lack of antenatal care (ANC) follow-up more than doubled the risk of death, consistent with reports from Southern Ethiopia, Mizan Tepi, and Uganda (17,21,22). Possible reason could be lack of ANC visits may result insufficient monitoring of the pregnancy, increasing the risk of complications during and after birth, which in turn may contribute to a higher risk of neonatal death.\u003c/p\u003e \u003cp\u003eAntenatal steroid use significantly reduced mortality by 55.7%, which align with findings from Jimma and global meta-analyses highlighting the benefits of corticosteroids in improving lung maturity and reducing respiratory complications (25,26). Despite their proven effectiveness, antenatal steroids remain underutilized in low-resource settings due to late presentation and limited supplies.\u003c/p\u003e \u003cp\u003eHome delivery was strongly associated with neonatal mortality, likely due to the lack of skilled birth attendants and delayed access to neonatal care, similar to findings from Gondar (20). Additionally, neonatal hypothermia increased mortality risk fourfold, aligning with studies in Bench Sheko and Sierra Leone (23,27).\u003c/p\u003e"},{"header":"5. Conclusion","content":"\u003cp\u003eIn conclusion, while the incidence proportion and incidence rate of preterm neonatal death in this study were lower compared to other studies, several key predictors were identified. This include lack of ANC follow-up, home delivery, and neonatal hypothermia, while the use of antenatal steroids was shown to decrease the risk of death. This study demonstrates that improving antenatal care coverage, encouraging facility-based deliveries, ensuring effective thermal management, and promoting antenatal corticosteroid administration are essential strategies for improving survival among preterm neonates.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cdiv class=\"DefinitionList\"\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eANC\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eAntenatal Care\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eAHR\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eAdjusted Hazard Ratio\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eAPH\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eAntepartum Hemorrhage\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eBMI\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eBody Mass Index\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eBPD\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eBronchopulmonary Dysplasia\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eEONS\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eEarly Onset Neonatal Sepsis\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eGA\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eGestational Age\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eGDM\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eGestational diabetes mellitus\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eHMIS\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eHealth Management Information System\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eIQR\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eInterquartile Range\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eIVH\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eIntraventricular Hemorrhage\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eKMC\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eKangaroo Mother Care\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eNEC\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eNecrotizing Enterocolitis\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eNICU\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eNeonatal Intensive Care Unit\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003ePROM\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003ePremature Rupture of Membranes\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eRDS\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eRespiratory Distress Syndrome\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eWHO\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eWorld Health Organization\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eWUCSH\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eWallaga University Comprehensive Specialized Hospital\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"Declarations","content":"\u003ch2\u003eEthics approval and consent to participate:\u0026nbsp;\u003c/h2\u003e\n\u003cp\u003eEthical clearance was obtained from the Wallaga University Institute of Health Science Research Ethics Committee. The study was conducted in accordance with the principles of the Declaration of Helsinki. The need for informed consent was waived by the ethics committee because the data were collected retrospectively from medical records without any direct patient contact. Institute of health science, medical science academic and service directorate wrote an official letter of permission to NICU and Record room head for securing permission. After obtaining permission data gathered from charts. Information obtained from the charts was kept confidentially by not recording neonates and their mother\u0026rsquo;s name on check lists. Data was kept secured by password which accessed only by researcher and data collectors. \u0026nbsp;\u0026nbsp;\u003c/p\u003e\n\u003ch2\u003eConsent for publication:\u0026nbsp;\u003c/h2\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003ch2\u003eAvailability of data and materials:\u003c/h2\u003e\n\u003cp\u003eThe datasets used during the current study are available from the corresponding author on reasonable request.\u003c/p\u003e\n\u003ch2\u003eCompeting interests:\u0026nbsp;\u003c/h2\u003e\n\u003cp\u003eNo competing interests.\u003c/p\u003e\n\u003ch2\u003eFunding:\u0026nbsp;\u003c/h2\u003e\n\u003cp\u003eNo external funding.\u003c/p\u003e\n\u003ch2\u003eAuthors\u0026rsquo; contributions:\u003c/h2\u003e\n\u003cp\u003e\u003cstrong\u003eMinase Abera:\u003c/strong\u003e Collected and analyzed the data, interpreted the results, and prepared the manuscript. \u003cstrong\u003eFikadu Enkosa:\u003c/strong\u003e Contributed as academic advisor, assisted with data analysis and interpretation, and critically reviewed the manuscript. \u003cstrong\u003eEmiru Merdassa:\u003c/strong\u003e Contributed as academic advisor, assisted with data analysis and interpretation, and critically reviewed the manuscript.\u003c/p\u003e\n\u003ch2\u003eAcknowledgements: \u0026nbsp;\u003c/h2\u003e\n\u003cp\u003eWe would like to thank Wallaga University for giving us the opportunity to conduct this study.\u003c/p\u003e\n\u003ch2\u003eClinical trial number:\u003c/h2\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eWHO. Preterm birth [Internet]. 2023 [cited 2024 Jun 30]. Available from: https://www.who.int/news-room/fact-sheets/detail/preterm-birth\u003c/li\u003e\n\u003cli\u003eKhasawneh W, Khriesat W. Assessment and comparison of mortality and short-term outcomes among premature infants before and after 32-week gestation: A cross-sectional analysis. Ann Med Surg [Internet]. 2020 Dec 1 [cited 2024 Sep 7];60:44\u0026ndash;9. Available from: https://pubmed.ncbi.nlm.nih.gov/33101673/\u003c/li\u003e\n\u003cli\u003eTaha Z, Hassan AA, Wikkeling-Scott L, Papandreou D. Factors Associated with Preterm Birth and Low Birth Weight in Abu Dhabi, the United Arab Emirates. Int J Environ Res Public Health [Internet]. 2020 Feb 2 [cited 2024 Sep 7];17(4). Available from: https://pubmed.ncbi.nlm.nih.gov/32098043/\u003c/li\u003e\n\u003cli\u003eWalani SR. Global burden of preterm birth. Int J Gynaecol Obstet [Internet]. 2020 Jul 1 [cited 2024 Jun 30];150(1):31\u0026ndash;3. Available from: https://pubmed.ncbi.nlm.nih.gov/32524596/\u003c/li\u003e\n\u003cli\u003eAbadiga M, Wakuma B, Oluma A, Fekadu G, Hiko N, Mosisa G. Determinants of preterm birth among women delivered in public hospitals of Western Ethiopia, 2020: Unmatched case-control study. PLoS One [Internet]. 2021 Jan 1 [cited 2025 Apr 28];16(1):e0245825. Available from: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0245825\u003c/li\u003e\n\u003cli\u003eKhandre V, Potdar J, Keerti A. Preterm Birth: An Overview. Cureus [Internet]. 2022 Dec 27 [cited 2025 May 11];14(12):e33006. Available from: https://pmc.ncbi.nlm.nih.gov/articles/PMC9879350/\u003c/li\u003e\n\u003cli\u003eEtil T, Opio B, Odur B, Lwanga C, Atuhaire L. Risk factors associated with preterm birth among mothers delivered at Lira Regional Referral Hospital. BMC Pregnancy Childbirth [Internet]. 2023 Dec 1 [cited 2024 Jun 30];23(1):1\u0026ndash;9. Available from: https://bmcpregnancychildbirth.biomedcentral.com/articles/10.1186/s12884-023-06120-4\u003c/li\u003e\n\u003cli\u003eSendeku FW, Beyene FY, Tesfu AA, Bante SA, Azeze GG. Preterm birth and its associated factors in Ethiopia: a systematic review and meta-analysis. Afr Health Sci [Internet]. 2021 [cited 2024 Jun 30];21(3):1321. Available from: /pmc/articles/PMC8843273/\u003c/li\u003e\n\u003cli\u003eMocking M, Adu-Bonsaffoh K, Osman KA, Tamma E, Ruiz AM, van Asperen R, et al. Causes, survival rates, and short-term outcomes of preterm births in a tertiary hospital in a low resource setting: An observational cohort study. Front Glob Women\u0026rsquo;s Heal [Internet]. 2022 [cited 2024 Jun 30];3. Available from: /pmc/articles/PMC9932588/\u003c/li\u003e\n\u003cli\u003eZivaljevic J, Jovandaric MZ, Babic S, Raus M. Complications of Preterm Birth\u0026mdash;The Importance of Care for the Outcome: A Narrative Review. Medicina (B Aires) [Internet]. 2024 Jun 1 [cited 2025 May 11];60(6):1014. Available from: https://pmc.ncbi.nlm.nih.gov/articles/PMC11205595/\u003c/li\u003e\n\u003cli\u003eSiffel C, Hirst AK, Sarda SP, Kuzniewicz MW, Li DK. The clinical burden of extremely preterm birth in a large medical records database in the United States: Mortality and survival associated with selected complications. Early Hum Dev [Internet]. 2022 Aug 1 [cited 2024 Jun 30];171. Available from: https://pubmed.ncbi.nlm.nih.gov/35785690/\u003c/li\u003e\n\u003cli\u003eOhuma EO, Moller AB, Bradley E, Chakwera S, Hussain-Alkhateeb L, Lewin A, et al. National, regional, and global estimates of preterm birth in 2020, with trends from 2010: a systematic analysis. Lancet (London, England) [Internet]. 2023 Oct 7 [cited 2024 Jun 30];402(10409):1261\u0026ndash;71. Available from: https://pubmed.ncbi.nlm.nih.gov/37805217/\u003c/li\u003e\n\u003cli\u003eSolbana LK, Etana D, Nazi D, Regea F, Berhanu S. Incidence and Predictors of Preterm Mortality in Ethiopia: A Systematic Review and Meta-analysis. https://doi.org/101177/09732179231221883 [Internet]. 2024 Jan 4 [cited 2024 Jun 30];38(1):124\u0026ndash;34. Available from: https://journals.sagepub.com/doi/abs/10.1177/09732179231221883\u003c/li\u003e\n\u003cli\u003eMabrouk A, Abubakar A, Too EK, Chongwo E, Adetifa IM. A Scoping Review of Preterm Births in Sub-Saharan Africa: Burden, Risk Factors and Outcomes. Int J Environ Res Public Health [Internet]. 2022 Sep 1 [cited 2024 Jun 30];19(17):10537. Available from: /pmc/articles/PMC9518061/\u003c/li\u003e\n\u003cli\u003eAndrew Shennan MH. 80% of premature baby deaths happen in poorer countries. Five simple measures that can help save them [Internet]. 2024 [cited 2024 Jun 30]. Available from: https://theconversation.com/80-of-premature-baby-deaths-happen-in-poorer-countries-five-simple-measures-that-can-help-save-them-222302\u003c/li\u003e\n\u003cli\u003eFMOH. National Newborn and Child Survival Strategy Document Brief Summary 2015/16-2019/20. 2015;(June 2015). \u003c/li\u003e\n\u003cli\u003eHuka AE, Oljira L, Weldesenbet AB, Bushra AA, Ahmed IA, Tura AK, et al. Predictors of time to death among preterm neonates admitted to neonatal intensive care units at public hospitals in southern Ethiopia: A cohort study. PLoS One [Internet]. 2023 Oct 1 [cited 2025 Apr 12];18(10). Available from: https://pubmed.ncbi.nlm.nih.gov/37824535/\u003c/li\u003e\n\u003cli\u003eAynalem YA, Mekonen H, Akalu TY, Gebremichael B, Shiferaw WS. Preterm Neonatal Mortality and its predictors in Tikur Anbessa Specialized Hospital, Addis Ababa, Ethiopia: a retrospective cohort study. Ethiop J Health Sci [Internet]. 2021 Jan 1 [cited 2024 Jun 30];31(1):43. Available from: /pmc/articles/PMC8188116/\u003c/li\u003e\n\u003cli\u003eFMOH. Neonatal Intensive Care Unit ( NICU ) Training Participants \u0026rsquo; Manual. Fmoh. 2021;(November):194. \u003c/li\u003e\n\u003cli\u003eYismaw AE, Gelagay AA, Sisay MM. Survival and predictors among preterm neonates admitted at University of Gondar comprehensive specialized hospital neonatal intensive care unit, Northwest Ethiopia. Ital J Pediatr [Internet]. 2019 Jan 7 [cited 2025 Apr 12];45(1):1\u0026ndash;11. Available from: https://link.springer.com/articles/10.1186/s13052-018-0597-3\u003c/li\u003e\n\u003cli\u003eBereka B, Demeke T, Fenta B, Dagnaw Y. Survival Status and Predictors of Mortality Among Preterm Neonates Admitted to Mizan Tepi University Teaching Hospital, South West Ethiopia. Pediatr Heal Med Ther [Internet]. 2021 Sep [cited 2024 Jun 30];Volume 12:439\u0026ndash;49. Available from: https://www.tandfonline.com/action/journalInformation?journalCode=dphm20\u003c/li\u003e\n\u003cli\u003eEgesa WI, Odong RJ, Kalubi P, Ortiz Yamile EA, Atwine D, Turyasiima M, et al. Preterm Neonatal Mortality and Its Determinants at a Tertiary Hospital in Western Uganda: A Prospective Cohort Study. Pediatr Heal Med Ther [Internet]. 2020 Oct [cited 2025 Apr 12];11:409\u0026ndash;20. Available from: https://pubmed.ncbi.nlm.nih.gov/33117056/\u003c/li\u003e\n\u003cli\u003eLuke RDC, Bell NVT, Jonjo DAJ, Akhigbe IE, Bell NVT, Sovula HS, et al. Survival status and predictors of mortality among preterm neonates admitted to a tertiary hospital in Sierra Leone. 2024;89\u0026ndash;96. \u003c/li\u003e\n\u003cli\u003eDhaded SM, Saleem S, Goudar SS, Tikmani SS, Hwang K, Guruprasad G, et al. The causes of preterm neonatal deaths in India and Pakistan (PURPOSe): a prospective cohort study. Lancet Glob Heal [Internet]. 2022 Nov 1 [cited 2024 Jun 30];10(11):e1575\u0026ndash;81. Available from: https://pubmed.ncbi.nlm.nih.gov/36240824/\u003c/li\u003e\n\u003cli\u003eToma TM, Merga H, Dube L. Incidence and Predictors of Mortality Among Preterm Neonates Admitted to Jimma University Medical Center, Southwest Ethiopia: a Retrospective Follow-Up Study. Int J Public Health [Internet]. 2024 [cited 2025 Apr 19];69. Available from: https://pubmed.ncbi.nlm.nih.gov/39027016/\u003c/li\u003e\n\u003cli\u003eMwansa-Kambafwile J, Cousens S, Hansen T, Lawn JE. Antenatal steroids in preterm labour for the prevention of neonatal deaths due to complications of preterm birth. Int J Epidemiol [Internet]. 2010 Apr 1 [cited 2024 Jun 30];39(Suppl 1):i122. Available from: /pmc/articles/PMC2845868/\u003c/li\u003e\n\u003cli\u003eMihretu E, Genie YD, Adugnaw E, Shibabaw AT. Survival status and predictors of mortality among preterm neonates admitted in Bench Sheko Zone, Sheka Zone and Keffa Zone Governmental Hospitals, Southwest Ethiopia (2021): prospective follow-up study. BMJ Open [Internet]. 2024 Apr 23 [cited 2025 Apr 12];14(4). Available from: https://pubmed.ncbi.nlm.nih.gov/38658009/\u003c/li\u003e\n\u003cli\u003eKamgaing EK, Rogombe SM, Maniaga RK, Mouboungou N, Mikolo AL, Mintsa-Mi-Nkama E, et al. Risk factors for mortality of preterm infants in the neonatal medicine department of the \u0026lsquo;M\u0026egrave;re-Enfant\u0026rsquo; University Hospital Centre of Libreville. Int J Contemp Pediatr [Internet]. 2023 Jan 24 [cited 2024 Jun 30];10(2):126\u0026ndash;33. Available from: https://www.ijpediatrics.com/index.php/ijcp/article/view/5228\u003c/li\u003e\n\u003cli\u003eMekasha A, Tazu Z, Muhe L, Abayneh M, Gebreyesus G, Girma A, et al. Factors Associated with the Death of Preterm Babies Admitted toNeonatal Intensive Care Units in Ethiopia: A Prospective, Cross-sectional, andObservational Study. Glob Pediatr Heal [Internet]. 2020 [cited 2024 Jun 30];7. Available from: /pmc/articles/PMC7689001/\u003c/li\u003e\n\u003cli\u003eTaylor RS, Singh B, Mukerji A, Dorling J, Alvaro R, Lodha A, et al. Intermediate vs. High Oxygen Saturation Targets in Preterm Infants: A National Cohort Study. Neonatology [Internet]. 2025 Feb 7 [cited 2025 Apr 28];122(1):106\u0026ndash;13. Available from: https://dx.doi.org/10.1159/000540278\u003c/li\u003e\n\u003cli\u003eCantey JB, Pyle AK, Wozniak PS, Hynan LS, S\u0026aacute;nchez PJ. Early Antibiotic Exposure and Adverse Outcomes in Preterm, Very Low Birth Weight Infants. J Pediatr [Internet]. 2018 Dec 1 [cited 2025 Apr 28];203:62\u0026ndash;7. Available from: https://www.sciencedirect.com/science/article/abs/pii/S0022347618309417\u003c/li\u003e\n\u003cli\u003eGirma B, Nigussie J. Magnitude of preterm hospital neonatal mortality and associated factors in northern Ethiopia: a cross-sectional study. BMJ Open [Internet]. 2021 Dec 1 [cited 2024 Jun 30];11(12):e051161. Available from: https://bmjopen.bmj.com/content/11/12/e051161\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"NICU, WUCSH, Incidence of mortality, Predictors of mortality Preterm","lastPublishedDoi":"10.21203/rs.3.rs-6697745/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6697745/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBACKGROUND\u003c/h2\u003e \u003cp\u003ePreterm birth affects 1 in 10 babies globally, with disproportionately high mortality in low-income settings. Sub-Saharan Africa bears a significant burden due to limited healthcare access. Despite the availability of modifiable risk factors and cost-effective interventions, data on incidence of mortality of preterm neonates in the study area is lacking.\u003c/p\u003e\u003ch2\u003eOBJECTIVE\u003c/h2\u003e \u003cp\u003e To assess incidence and predictors of mortality among preterm neonates admitted to the neonatal intensive care unit of Wallaga University Comprehensive Specialized Hospital, Nekemte Town, Oromia, Ethiopia, from July 1, 2022, to June 30, 2024.\u003c/p\u003e\u003ch2\u003eMETHODS\u003c/h2\u003e \u003cp\u003eAn institution-based retrospective cohort study was conducted among 264 preterm neonates admitted to the NICU within the study period and study subjects were selected using systematic random sampling technique. Data were collected using a structured checklist, entered via EpiData version 4.6, and subsequently analyzed using STATA version 14.0. Kaplan-Meier and log-rank tests were used to compare survival probability and assess statistically significance difference between groups. The Cox proportional hazards model assumption was checked. A bivariable Cox regression analysis was fitted and those variable with p\u0026thinsp;\u0026lt;\u0026thinsp;0.2 were included in the multivariable analysis. Finally, statistical significance was declared at a p-value\u0026thinsp;\u0026lt;\u0026thinsp;0.05.\u003c/p\u003e\u003ch2\u003eRESULTS\u003c/h2\u003e \u003cp\u003eOf 259 preterm neonates, 42 died during follow up time, with incidence proportion of 16%. The median survival time was 28 days (IQR: 22\u0026ndash;30), with 2,737 neonate-days of follow-up. The overall incidence rate of mortality was 15.3 per 1,000 neonate-days (95% CI: 11.3\u0026ndash;20.7). Significant predictors of mortality included were lack of ANC follow-up (AHR: 2.27, 95% CI: 1.13\u0026ndash;4.57), antenatal steroid use (AHR: 0.44, 95% CI: 0.21\u0026ndash;0.92), home delivery (AHR: 7.74, 95% CI: 1.99\u0026ndash;30.03), and presence of hypothermia (AHR: 4.11; 95% CI: 1.55\u0026ndash;10.85).\u003c/p\u003e\u003ch2\u003eCONCLUSION AND RECOMMENDATION:\u003c/h2\u003e \u003cp\u003eThe study identified key clinical and maternal predictors associated with preterm neonatal mortality. Targeted interventions focusing on antenatal care, delivery practices, steroid administration, and thermal regulation are essential.\u003c/p\u003e","manuscriptTitle":"Incidence and predictors of mortality among preterm neonates admitted to the neonatal intensive care unit of Wallaga University Comprehensive Specialized Hospital, Nekemte Town, East Wallaga, Oromia, Ethiopia: a retrospective cohort study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-06-18 08:49:44","doi":"10.21203/rs.3.rs-6697745/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"4ccb9b29-860f-43c8-adec-84ac0c769b55","owner":[],"postedDate":"June 18th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2026-02-04T09:42:25+00:00","versionOfRecord":[],"versionCreatedAt":"2025-06-18 08:49:44","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6697745","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6697745","identity":"rs-6697745","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}