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ORIGINAL ARTICLE
Year : 2023  |  Volume : 12  |  Issue : 1  |  Page : 1-6

Role of modified sick neonatal score in predicting the neonatal mortality at limited-resource setting of central India


Department of Paediatrics, Government Medical College, Nagpur, Maharashtra, India

Correspondence Address:
Rajkumar Motiram Meshram
Department of Paediatrics, Government Medical College, Nagpur, Maharashtra
India
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Source of Support: None, Conflict of Interest: None


DOI: 10.4103/jcn.jcn_83_22

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Background: The targets of Sustainable Development Goals cannot be achieved without reducing mortality of inborn as well as outborn neonates. Objective: The objective was to predict the mortality of neonates by applying Modified Sick Neonatal Score (MSNS). Material and Methods: Parameters of MSNS scoring system were applied to 450 neonates at the time of admission and followed up prospectively till discharge or death. The score and individual parameters were correlated with outcome. A receiver operating curve was plotted to determine the cutoff value for score to predict the mortality. Results: The common clinical diagnoses were respiratory distress (38%), sepsis (26%), and jaundice (14.44%). Sixty-two percent neonates were born at term and 38% were preterm while 55.56% neonates were low birth weight and 44.4% were weighted more than 2500 gms. Neonates who died were older at the time of admission, and duration of hospital stay was shorter compared to alive neonates (P < 0.001) with a mortality rate of 23.11%. The total MSNS for neonates who died was statistically significantly low, (mean ± standard deviation) 7.93 ± 2.70, compared to alive neonates, 12.02 ± 1.84 (P < 0.0001). With optimum cutoff score of ≤10, the sensitivity was 79.80% and the specificity was 82.37% while the positive predictive value and negative predictive value was 57.64% and 93.14% respectively with the area under curve was 0.89 (odds ratio-18.46, 95% confidence interval 10.3-33.64, P < 0.0001). Conclusion: The MSNS of ≤10 has a better sensitivity and specificity in predicting neonatal mortality and is easy to use with minimal resources to both preterm and term neonates.


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