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To capture lapses in management, active surveillance of pediatric intensive care unit (PICU) admissions should consider as an essential tool to bring a better outcome with available resources, while there is a scarcity of data from comparatively newly set up peripheral PICU in developing countries. An observational record-based cross-sectional study was conducted in a peripheral medical college PICU over one year to evaluate morbidity pattern, outcome, and predictors of mortality. Binomial logistic regression (SPSS version-25) was used for analysis. The confidence interval (CI) of Odd's ratio was used to report the strength of association between dependent and independent variables. Pneumonia was the major cause of admission (27%), followed by septicemia (25.5%), congenital heart diseases (12.2%), bronchiolitis (6.6%), seizure disorders (8.6%), encephalitis (5%), and meningitis (4%). 51.7% were discharged, 14.6 %were referred, 3.2% were left against medical advice, and 30.4% were expired. Pneumonia (46.44%) was the most common cause of death, followed by sepsis (42.07%), congenital heart disease (15.3%), and bronchiolitis (6.01%). The mean duration of stay in PICU was five days (range 1-31 days). Patients who required ventilation (40%) or Inotropes (55.6%) had increased risk of mortality by 14 and 8 times, respectively. Age below one year, presence of bronchiolitis, pneumonia, ARDS, encephalitis, anemia, sepsis, dyselectrolytemia, and requirement of inotropes or ventilation were statistically significant risk factors for mortality (P<0.05). These predictors of morality will help to identify severe cases, prioritize resources and focus on the preventable methods in the public such as a vaccine, creating awareness about diseases, and proper referral. [ABSTRACT FROM AUTHOR]

Introduction: Small-for-gestational-age (SGA) is one of the important factors for neonatal mortality. Early identification and necessary intervention of these newborns is crucial to increase their chances of survival and reduce long-term disabilities. However, in low- and middle-income countries a large portion of pregnant women are unaware of their accurate gestational age (GA) due to the limited availability of ultrasonography. The purpose of our study was to build an alternative tool to identify SGA., Methods: A institutional-based, prospective observational study was conducted from August-2018 to February-2020, with 1451 live singleton-newborns of 30-40 weeks of gestation. Ultrasonography was used to evaluate accurate GA in early pregnancy and a reference chart for the Asian population, constructed by the National Institute of Child Health and Human Development (NICHD) Fetal Growth Studies was used to classify newborns as SGA. Neonatal anthropometry was measured within 48 hours of birth. Receiver operating characteristic curves were developed to identify the best cut-off point for each anthropometric parameter and the area under the curve (AUC) was estimated to assess the overall precision., Results: Prevalence of SGA was 34.3%. The AUC was 0.888 for head circumference (HC), 0.890 for chest circumference (CC), and 0.865 for mid-upper arm circumference (MUAC). The optimal cut-offs to classify SGA were ≤32.45 cm for HC, ≤29.75 cm for CC and ≤8.55 cm for MUAC with sensitivities of 85.9%, 86.9% and 85.4%, specificities of 75.5%, 85.1% and 72.1%, positive predictive values of 0.64, 0.75 and 0.61 and negative predictive values of 0.91, 0.93 and 0.90 respectively., Conclusion: All three anthropometric measurements could be used to identify SGA but, overall CC is the best., Competing Interests: There are no conflicts of interest., (Copyright: © 2022 Journal of Family Medicine and Primary Care.)