Neonatal morbidity and mortality remain significant public health concerns worldwide, especially for infants requiring intensive care support. Term neonates are defined as infants born between 37 and 42 we are those born 

between 34 and 36 weeks of gestation. Although near-term infants are closer in gestational age to full-term infants, they have distinct physiological vulnerabilities, including higher risks of respiratory complications, temperature instability, and feeding difficulties, compared to term neonates.  The neonatal period, which encompasses the first 28 days of life, is a critical time when neonates are highly vulnerable to health complications that can lead to mortality if not promptly addressed. According to the World Health Organization (WHO), nearly 2.4 million children died within this period globally in 2020 alone, with a large proportion of these deaths being preventable [1,2]. Advances in neonatal intensive care have significantly improved survival rates among neonates; however, morbidity remains high, especially in resource-limited settings [3]. Morbidity in neonates is often related to a range of conditions, including prematurity, respiratory distress syndrome (RDS), sepsis, and birth asphyxia, which collectively account for the majority of neonatal intensive care unit (NICU) admissions and neonatal deaths [4,5].

          The outcomes of neonatal intensive care are influenced by several factors, such as gestational age, birth weight, maternal health, mode of delivery, and the availability of specialized neonatal care [6,7]. Preterm infants, particularly those born between 34 and 36 weeks of gestation (late preterms), face higher risks of morbidity and mortality compared to their term counterparts due to physiological immaturity [8]. Research indicates that late preterm infants have an increased incidence of respiratory issues, hypoglycemia, and infection, which often necessitates NICU admission [9]. The burden of neonatal morbidity not only affects the immediate health of these infants but can also have long-term developmental implications [10].

         In India, neonatal morbidity and mortality are of significant concern, with preterm birth complications contributing substantially to infant mortality rates [11]. Studies have shown that respiratory distress syndrome (RDS) and neonatal sepsis are among the leading causes of neonatal morbidity in NICUs [12]. Hyderabad, a metropolitan hub with both government and private healthcare facilities, has a high neonatal admission rate, which offers a unique opportunity to examine morbidity and mortality patterns in a teaching hospital setting [13].

           This study aims to analyze the morbidity and mortality profiles of neonates admitted to a NICU in a teaching hospital in Hyderabad. By examining the demographic, maternal, and neonatal characteristics associated with NICU admissions, this study intends to highlight the key risk factors contributing to neonatal morbidity and mortality. Understanding these patterns can aid in designing targeted interventions to improve neonatal outcomes in similar healthcare settings [14,15].

Study design: Prospective Observational study

Place of study: NICU, Princess Esra hospital, Hyderabad, Owaisi Hospital and Research Center, Hyderabad, Telangana.

                 Study sample: All newborns admitted in the NICU of Princess Esra Hospital and Owaisi Hospital and Research Center, Hyderabad during the study period, and whose parents have given informed consent Duration of the study: 18 months (May 2020 to November 2021

       Sample Size: A total of 426 infants were included.

            Inclusion Criteria: All newborns less than 1 month of age admitted in the NICU of Princess Esra Hospital, Hyderabad during the study period, and whose parents give informed consent for participation in the study.

     Exclusion Criteria: Newborns, whose parents do not give consent for participation in the study.

A total of 426 infants were included for the study.  The term infants were 343 and 83 infants were near term infants.

Table 1: Distribution based on Gender and Mode of NICU admission

Among term infants, males constituted 58.30%, while females made up 41.69%, resulting in a male-to-female ratio of 1.39:1. Of these infants, 39.94% were inborn admissions to the NICU, while 60% were outborn admissions.  For near-term infants, males accounted for 68.67% and females for 31.32%, giving a male-to-female ratio of 2.19:1. In this group, 54.21% were inborn admissions to the NICU, while 45.78% were outborn admissions.

Table 2: Distribution based on Gestational age

All term infants (100%) had a gestational age ranging between 37 and 42 weeks, with a mean gestational age of 37.62 ± 0.76 weeks.  All near-term infants (100%) had a gestational age between 36 and 37 weeks, with a mean gestational age of 36.0 ± 0.1 weeks.

Table 3: Distribution based on Birth weight

The majority of term infants (46.35%) had a birth weight between 2.5 and 2.9 kg, while 21.57% had a birth weight of 2.0 to 2.4 kg. Birth weights of 1.5–1.9 kg were seen in 5.83% of infants, and 7.28% had a birth weight exceeding 3.5 kg. Only 0.87% of infants weighed between 1.0 and 1.4 kg. The mean birth weight for this group was 2.30 ± 0.56 kg.  Among near-term infants, 38.55% had a birth weight between 2.0 and 2.4 kg, with 31.32% weighing between 2.5 and 2.9 kg. Birth weights of 1.5–1.9 kg were observed in 22.89% of infants, while 7.22% had a birth weight between 3.0 and 3.4 kg. The mean birth weight for this group was 1.740 ± 0.37 kg.  The chi-square statistic is 122.3407, with a p-value of <0.00001, indicating statistical significance at p < 0.05.

Table 4: Distribution based on LGA, SGA, AGA

The majority of term infants (86.29%) were appropriate for gestational age (AGA), while 12.24% were small for gestational age (SGA) and 1.45% was large for gestational age (LGA).  Most near-term infants (80.72%) were AGA, with 18% classified as SGA and 1.20% as LGA.

Table 5: Distribution based on maternal comorbidities and risk factors

Maternal comorbidities were present in 1% of cases. Hypothyroidism was noted in 6.70%, gestational diabetes mellitus (GDM) in 3.49%, hypertension in 1.74%, scabies in 0.58%, and both epilepsy and anemia in 0.29% of cases.  Maternal comorbidities were observed in 30.43% of cases, with GDM in 9.63%, pregnancy-induced hypertension (PIH) in 7.22%, hypothyroidism in 2.40%, and epilepsy in 1.20% of cases.  The Fisher’s exact test statistic is 0.7307, showing no statistical significance at p < 0.05.

Table 6: Distribution based on mode of delivery

In the majority of cases, cesarean section (LSCS) was performed in 80.46%, while 19.24% were delivered vaginally. Instrumental vaginal delivery was used in 0.29% of cases.  Among near-term infants, LSCS was conducted in 87.95% of cases, and vaginal delivery in 12.04%.  The Fisher’s exact test statistic is 0.1506, indicating that the result is not significant at p < 0.05.

Table 7: Neonatal Morbidity Risk factors statistical analysis

When comparing neonatal risk factors between term and near-term neonates, factors such as hypothermia, apnoea, cardiovascular complications, congenital malformations, birth asphyxia, polycythaemia, hypocalcemia, seizures, shock, meningitis, anaemia, and feeding difficulties had a p-value > 0.05, indicating statistical insignificance and a negative correlation with neonatal outcomes.  However, risk factors including respiratory distress, sepsis, jaundice, and hypoglycemia showed a p-value < 0.05, demonstrating statistical significance and a positive correlation with neonatal outcomes. The f-ratio value was 0.94324, with a chi-square statistic of 39.635 and a p-value of 0.0005, confirming statistical significance at p < 0.05.

Table 8: Distribution based on Resuscitation and type of resuscitation

Resuscitation was required in 3.49% of cases, with tactile stimulation used in 2.91% and bag-mask ventilation in 0.58%.  Resuscitation was performed in 6.02% of cases, with 4.81% receiving tactile stimulation and 1.20% requiring bag-mask ventilation.

Table 9: Distribution based on Respiratory Distress, type and support

The majority of cases (25.65%) presented with transient tachypnea of the newborn (TTNB), while 10.49% had pneumonia and 2.91% experienced asphyxia. Respiratory support included oxygen therapy in 34.11% of cases, synchronized intermittent mandatory ventilation (SIMV) in 7.28%, bubble continuous positive airway pressure (BCPAP) in 4.95%, and continuous positive airway pressure (CPAP) in 1.45%. Most patients (28%) required respiratory support for 24 to 48 hours.  Among near-term cases, 30.12% had TTNB, 21.68% presented with pneumonia, and 3.61% experienced asphyxia. Respiratory support included oxygen therapy in 49.39% of cases, SIMV in 13.25%, BCPAP in 4.81%, and CPAP in 2.40%. The majority of these patients (32.53%) required respiratory support for 24 hours.

Table 10: Distribution based on neonatal mortality

Neonatal mortality occurred in 0.58% of cases, with causes including shock and cardiovascular issues (CVS), each accounting for 0.29% of cases.  Neonatal mortality was observed in 1.20% of cases, with the cause attributed to neonatal jaundice (NNJ) in 1.20% of cases. The Fisher exact test statistic value is 0.4826. The result is not significant at p<0.05.

Table 11: Distribution based on comorbidities at discharge

Comorbidities at discharge were noted in 0.59% of cases.  No comorbidities were observed at discharge.  The Fisher's exact test statistic is 1, indicating that the result is not statistically significant at p < 0.05.

The morbidity and mortality profile of neonates admitted to the NICU highlights the critical health challenges faced by newborns, especially those born prematurely or with low birth weight. Common complications include respiratory distress, infections, and jaundice, often necessitating interventions like ventilation and antibiotics. Prematurity remains a leading cause of neonatal mortality, reflecting the vulnerability of immature organ systems. Enhanced prenatal care and timely, specialized neonatal interventions are essential to reduce these rates. However, the data emphasizes the ongoing need for improving neonatal care strategies to lower the incidence of adverse outcomes in this high-risk group.

              In this study, male neonates were admitted at a higher rate than females, likely due to the inherent vulnerability of the male gender and societal preference for male children. Research indicates that male infants face greater risks of mortality and morbidity during prenatal, infancy, and childhood stages. Compared to females, male newborns are more prone to preterm birth, intrauterine growth restriction, and respiratory complications, partly due to elevated testosterone levels, which suppress immune function. While boys generally have higher neonatal and infant mortality rates in high-income countries, recent studies in South Asia have reported higher rates among females. Studies by Saharia et al., Malik et al., and Kotwal et al. [16, 17, 18] in various regions of India have found similar patterns.

             Near-term newborns often require hospitalization, making up a significant portion of the workload in neonatal units. In a study by Raju TN et al., [19] the NICU admission rates were 51% for near-term and 16% for term infants, comparable to our findings of 55.7% and 18.6%, respectively. Our study also showed inborn admissions at 43.66% and outborn admissions at 56.33%, aligning with studies by Sridhar PV [20], Modi R [21], and Kumar MK [22].

                   In this study, near-term births accounted for 17.78% of all deliveries, a higher incidence than previously reported in Indian studies. For example, studies by Femitha P et al [23], Abu Salah et al [24], and Wagh AS et al [25] reported near-term birth rates of 6.5%, 7.8%, and 8.9%, respectively, while Jaiswal et al [26] noted an 11.24% incidence. Compared to these studies, our near-term rate is notably higher. This figure aligns more closely with data from the United States, where near-term births make up approximately 74% of all births, as reported by Davidoff et al [27]. Additionally, other studies, such as those by Femitha P et al. and Abu Salah et al., found near-term births to represent 55% and 72.7% of their respective study populations.

               In this study, near-term infants had a higher rate of caesarean sections (87.95%) compared to term infants (80.46%), with near-term deliveries showing greater NICU admissions. Similar findings were reported by Pinar B et al [28] where near-term infants delivered by caesarean section had a 7.37 times higher morbidity rate. Other studies also highlight variations: Jaiswal et al [26] reported caesarean rates of 67.8% for near-term and 57.4% for term deliveries, while Femitha et al [23] noted significantly lower rates, with 32.4% of near-term and 7.2% of term infants delivered by LSCS.

               In the present study, near-term infants had a mean birth weight of 1.74 kg compared to 2.30 kg for term infants, aligning with findings by Jaiswal et al. [26] (2.35 kg vs. 3.04 kg) and Pinar B et al. [28] (2.06 kg vs. 3.16 kg). Near-term infants consistently presented higher morbidity, with rates reaching 75.15% in our study, 70.8% in Jaiswal et al., and 85% in Wagh AS et al., significantly exceeding those of term infants. Research by Femitha P et al. and Pinar B et al. similarly demonstrated increased morbidity in near-term infants at 63.2% and 54.5%, respectively, compared to 15.2% and 14% in term infants. Population-based research by Shapiro-Mendoza et al [29] also highlighted this trend, showing a 22% morbidity rate in near-term infants versus 3% in term infants. These findings emphasize the heightened clinical challenges faced by near-term infants compared to term neonates.

              Respiratory distress was more prevalent in near-term infants (69.87%) compared to term infants (47.52%). Supporting this trend, other studies reported similar findings: Pinar B et al. observed respiratory distress in 31.8% of near-term versus 2% of term infants; Kalyoncu et al [30] reported rates of 44.8% in near-term and 6.7% in term infants; and Jaiswal et al. noted it in 10.5% of near-term compared to 1.5% of term infants. These consistent results emphasize the elevated risk of respiratory distress in near-term infants across various research contexts.

          Near-term infants face a notable mortality risk, often from conditions like respiratory distress syndrome (RDS), birth asphyxia, and sepsis, despite having lower overall morbidity and mortality rates than smaller near-term infants. In this study, early neonatal mortality was 1.20% among near-term infants compared to 0.59% in term infants. This is lower than findings by Tomashek et al [31]., who reported a sixfold increase in early neonatal mortality for near-term infants, and also lower than the mortality rates reported by Saharia N et al. (13%) [16] and Malik S et al. (26%) [17]. Similar to studies in South India by Sridhar PV et al [20] and Babu MC et al [32] at JIPMER, which identified systemic infections and birth asphyxia as significant causes of death, this study underscores RDS as the leading cause, reflecting higher near-term admissions and possibly insufficient prenatal care, particularly in rural areas

Understanding the morbidity risk in term and preterm infants not only aids in identifying and treating these at-risk neonates, but also in determining the timing of discharge and follow-up after discharge, as well as directing non-emergencyobstetric intervention considerations. the multiple neonatal morbidities andmortalities were caused by etiological variables. Since the underlying etiological factor is acknowledged as a predictor of newborn outcome, greater effort should be directed into determining the aetiology of near-term births and preventing unnecessary preterm births.

ETHICAL CLEARANCE

Ethical Clearance Certificate was obtained from the Institutional Ethics Committee (IEC) prior to commencement of study

CONFLICT OF INTEREST

 Nil - No conflict of interest

SOURCE OF FUNDING

Self.

1. World Health Organization. Newborn Mortality. 2021. Available from: https://www.who.int
2. United Nations Inter-agency Group for Child Mortality Estimation (UN IGME). Levels and Trends in Child Mortality Report 2021. New York: United Nations Children’s Fund; 2021.
3. Liu L, Oza S, Hogan D, et al. Global, regional, and national causes of child mortality in 2000–13, with projections to inform post-2015 priorities: An updated systematic analysis. The Lancet. 2015;385(9966):430-40. doi:10.1016/S0140-6736(14)61698-6
4. Blencowe H, Cousens S, Oestergaard MZ, et al. National, regional, and worldwide estimates of preterm birth rates in the year 2010 with time trends since 1990 for selected countries: A systematic analysis and implications. The Lancet. 2012;379(9832):2162-72. doi:10.1016/S0140-6736(12)60820-4
5. Lawn JE, Kinney MV, Black RE, et al. Newborn survival: A multi-country analysis of a decade of change. Health Policy Plan. 2012;27(Suppl 3)
6. . doi:10.1093/heapol/czs053
7. Stoll BJ, Hansen NI, Bell EF, et al. Neonatal outcomes of extremely preterm infants from the NICHD Neonatal Research Network. Pediatrics. 2010;126(3):443-56. doi:10.1542/peds.2009-2959
8. Goldenberg RL, Culhane JF, Iams JD, Romero R. Epidemiology and causes of preterm birth. The Lancet. 2008;371(9606):75-84. doi:10.1016/S0140-6736(08)60074-4
9. Engle WA, Tomashek KM, Wallman C. “Late-preterm” infants: A population at risk. Pediatrics. 2007;120(6):1390-401. doi:10.1542/peds.2007-2952
10. Escobar GJ, Clark RH, Greene JD. Short-term outcomes of infants born at 35 and 36 weeks gestation: We need to ask more questions. Semin Perinatol. 2006;30(1):28-33. doi:10.1053/j.semperi.2006.01.006
11. Vohr BR, Tyson JE, Wright LL, et al. Maternal age, multiple birth, and extremely low birth weight infants. J Pediatr. 2009;154(3):498-505. doi:10.1016/j.jpeds.2008.10.012
12. Sankar MJ, Agarwal R, Deorari AK, Paul VK. Sepsis in the newborn. Indian J Pediatr. 2008;75(3):261-6. doi:10.1007/s12098-008-0039-4
13. Bhutta ZA, Das JK, Bahl R, et al. Can available interventions end preventable deaths in mothers, newborn babies, and stillbirths, and at what cost? The Lancet. 2014;384(9940):347-70. doi:10.1016/S0140-6736(14)60792-3
14. Patel RM, Rysavy MA, Bell EF, Tyson JE. Survival of infants born at periviable gestational ages. Clin Perinatol. 2017;44(2):287-303. doi:10.1016/j.clp.2017.01.009
15. Modi N, Clark H, Wolfe I, Costello A, Budge H, et al. A healthy nation: Strengthening child health research in the UK. The Lancet. 2013;381(9860):73-87. doi:10.1016/S0140-6736(12)62024-8
16. Narang A, Kumar P, Kumar R. Cost of neonatal intensive care in a tertiary care center. Indian Pediatr. 2005;42(10):989-97.
17. Saharia N, Deka A, Vivekananda MS. Mortality and morbidity pattern of neonatal ICU of Guwahati Medical College and Hospital. IOSR JDMS. 2016;15:73-5. doi:10.9790/0853-1503087375
18. Malik S, Gohiya P, Khan IA. Morbidity profile and mortality of neonates admitted in Neonatal Intensive Care Unit of a Central India Teaching Institute: A prospective observational study. J Clin Neonatol. 2016;5:168-73. doi:10.4103/2249-4847.184623
19. Kotwal YS, Yatoo GH, Ahmed Jan FA. Morbidity and mortality among neonates admitted to a neonatal intensive care unit of a tertiary care teaching hospital of Jammu and Kashmir (India). Neonat Pediatr Med. 2011;3:136.
20. Raju TN, Higgins RD, Stark AR, Leveno KJ. Optimizing care and outcome for late-preterm (near-term) infants: A summary of the workshop sponsored by the National Institute of Child Health and Human Development. Pediatrics. 2006;118:1207-14. doi:10.1542/peds.2006-0018
21. Sridhar PV, Thammanna PS, Sandeep M. Morbidity pattern and hospital outcome of neonates admitted in a tertiary care Teaching Hospital, Mandya. Int J Sci Stud. 2015;3(6):126-9.
22. Modi R, Modi B, Patel JK, Punitha KM. Study of the morbidity and the mortality pattern in the neonatal intensive care unit at a tertiary care teaching hospital in Gandhinagar District, Gujarat, India. J Res Med Den Sci. 2015;3(3):208-12.
23. Kumar MK, Thakur S, Singh B. Study of the morbidity and the mortality patterns in the neonatal intensive care unit at a tertiary care teaching hospital in Rohtas District, Bihar, India. J Clin Diagn Res. 2012;6(2):282-5.
24. Femitha P, Bhat BV. Early neonatal outcome in late preterms. Indian J Pediatr. 2012;79(8):1019-24. doi:10.1007/s12098-012-0703-7
25. Abu-Salah O. Unfavourable outcomes associated with late preterm birth: Observations from Jordan. J Pak Med Assoc. 2011;61(8):769-72.
26. Wagh AS, Jain N. Comparison of neonatal morbidities of late preterm with term born babies. J Pharm Biomed Sci. 2012;15(9):1-5.
27. Jaiswal A, Murki S, Gaddam P, Reddy A. Early neonatal morbidities in late preterm infants. Indian Pediatr. 2011;48:607-11.
28. Davidoff MJ, Dias T, Damus K. Changes in the gestational age distribution among U.S. singleton births: Impact on rates of late preterm birth, 1992 to 2002. Semin Perinatol. 2006;30:8–15. doi:10.1053/j.semperi.2006.01.009
29. Binarbasi P, Akın Y, Narter F, Telatar B, Polatoglu E, Agzıkuru T. Mortality and morbidity in late-preterm newborns. Turk Arch Pediatr. 2013;48:17-22. doi:10.4274/tpa.1480
30. Shapiro-Mendoza CK, Tomashek KM, Kotelchuck M, Barfield W, Nannini A, Weiss J, et al. Effect of late-preterm birth and maternal medical conditions on newborn morbidity risk. Pediatrics. 2008;121:223-32. doi:10.1542/peds.2006-3629
31. Kalyoncu O, Aygun C, Cetinoglu E, Kucukoduk Ş. Neonatal morbidity and mortality of late-preterm babies. J Matern Fetal Neonatal Med. 2010;23:607-12. doi:10.3109/14767050903258725
32. Tomshek KM, Shapiro-Mendoza CK, Davidoff MJ. Differences in mortality between late preterm and term singleton infants in United States, 1995-2002. J Pediatr. 2007;151:450-6. doi:10.1016/j.jpeds.2007.04.060
33. Babu MC, Prakash PS, Prasanna CL. Neonatal morbidity and mortality patterns of babies admitted in SNCU @ ACSR Government Medical College, Nellore, Andhra Pradesh. J Evol Med Dent Sci. 2018;7(2):203-6.].