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一项使用改良新生儿疾病评分(MSNS)预测三级护理医院死亡率的研究:一项观察性横断面研究。

A Study of the Prediction of Mortality in a Tertiary Care Hospital Using the Modified Sick Neonatal Score (MSNS): An Observational Cross-Sectional Study.

作者信息

Reddy Prakash, Gowda Beere, R Abhinay

机构信息

Pediatrics, Sri Devaraj Urs Medical College, Kolar, IND.

出版信息

Cureus. 2023 May 3;15(5):e38484. doi: 10.7759/cureus.38484. eCollection 2023 May.

Abstract

PURPOSE

India is a major contributor to neonatal deaths worldwide. There is a paucity of amenities for the management of neonatal health issues in rural areas of our country. Hence, there is a need to invent a reliable scoring system for the analysis of neonatal mortality.

AIM

The aim of the study is to evaluate the Modified Sick Neonatal Score (MSNS) as a predictor of mortality in neonatal care units in resource-limited settings.

MATERIALS AND METHODS

This cross-sectional observational study was performed in the intensive care unit of our hospital. All the data were collected and analyzed using IBM Corp.'s Statistical Package for Social Sciences (SPSS) software.

RESULTS

Overall, 71 participants were considered for the present study. The common clinical diagnoses noticed in our participants were meconium aspiration, malformation, and jaundice. The MSNS score compared between expired and discharged participants is found to be statistically significant with p<0.05.

CONCLUSION

The MSNS scoring system is considered an ideal scoring system for detecting early mortality in neonates.

摘要

目的

印度是全球新生儿死亡的主要贡献国。我国农村地区在新生儿健康问题管理方面的设施匮乏。因此,需要发明一种可靠的评分系统来分析新生儿死亡率。

目的

本研究的目的是评估改良新生儿疾病评分(MSNS)作为资源有限环境下新生儿重症监护病房死亡率预测指标的情况。

材料与方法

本横断面观察性研究在我院重症监护病房进行。所有数据均使用IBM公司的社会科学统计软件包(SPSS)进行收集和分析。

结果

总体而言,本研究纳入了71名参与者。在我们的参与者中观察到的常见临床诊断为胎粪吸入、畸形和黄疸。发现死亡和出院参与者之间的MSNS评分具有统计学意义,p<0.05。

结论

MSNS评分系统被认为是检测新生儿早期死亡率的理想评分系统。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/70f8/10237252/70b2d7b5ce36/cureus-0015-00000038484-i01.jpg

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