Evidence map›Paper›PMID 33728449›Full record

ArticleInternational health2021

A nomogram to predict in-hospital mortality of neonates admitted to the intensive care unit.

Xihua Huang, Zhenyu Liang, Tang Li, Yu Lingna, Wei Zhu, Huiyi Li

Abstract read
In one paragraph

Article in International health, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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1citing papers in PubMed
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1 · What the graph read from it

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3 · Its place in the literature

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1 citing paper in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

6 authors.

Xihua HuangDepartment of Pediatrics, Guangdong Second Provincial General Hospital, No. 466 Middle Xingang Road, Zhuhai District, Guangzhou, Guangdong 510317, P. R. China.
Zhenyu LiangDepartment of Pediatrics, Guangdong Second Provincial General Hospital, No. 466 Middle Xingang Road, Zhuhai District, Guangzhou, Guangdong 510317, P. R. China.
Tang LiDepartment of Pediatrics, Guangdong Second Provincial General Hospital, No. 466 Middle Xingang Road, Zhuhai District, Guangzhou, Guangdong 510317, P. R. China.
Yu LingnaDepartment of Pediatrics, Guangdong Second Provincial General Hospital, No. 466 Middle Xingang Road, Zhuhai District, Guangzhou, Guangdong 510317, P. R. China.
Wei ZhuDepartment of Pediatrics, Guangdong Second Provincial General Hospital, No. 466 Middle Xingang Road, Zhuhai District, Guangzhou, Guangdong 510317, P. R. China.
Huiyi LiDepartment of Pediatrics, Guangdong Second Provincial General Hospital, No. 466 Middle Xingang Road, Zhuhai District, Guangzhou, Guangdong 510317, P. R. China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundTo explore the influencing factors for in-hospital mortality in the neonatal intensive care unit (NICU) and to establish a predictive nomogram.

methodsNeonatal data were extracted from the Medical Information Mart for Intensive Care III (MIMIC-III) database. Both univariate and multivariate logit binomial general linear models were used to analyse the factors influencing neonatal death. The area under the receiver operating characteristics (ROC) curve was used to assess the predictive model, which was visualized by a nomogram.

resultsA total of 1258 neonates from the NICU in the MIMIC-III database were eligible for the study, including 1194 surviving patients and 64 deaths. Multivariate analysis showed that red cell distribution width (RDW) (odds ratio [OR] 0.813, p=0.003) and total bilirubin (TBIL; OR 0.644, p<0.001) had protective effects on neonatal in-hospital death, while lymphocytes (OR 1.205, p=0.025), arterial partial pressure of carbon dioxide (PaCO2; OR 1.294, p=0.016) and sequential organ failure assessment (SOFA) score (OR 1.483, p<0.001) were its independent risk factors. Based on this, the area under the curve of this predictive model was up to 0.865 (95% confidence interval 0.813 to 0.917), which was also confirmed by a nomogram.

conclusionsThe nomogram constructed suggests that RDW, TBIL, lymphocytes, PaCO2 and SOFA score are all significant predictors for in-hospital mortality in the NICU.

Indexed as

Intensive Care UnitsNomogramsHospital MortalityHumansInfant, NewbornPrognosisRetrospective StudiesROC Curvein-hospital mortalityMIMIC databaseneonatesnomogram

Identifiers

PMID33728449
PMCPMC8643428

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