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院内死亡率预测:南非一家三级重症监护病房的适应性疾病严重程度评分

Prediction of in-hospital mortality: An adaptive severity-of-illness score for a tertiary ICU in South Africa.

作者信息

Pazi S, Sharp G, van der Merwe E

机构信息

Department of Statistics, Nelson Mandela University, Gqeberha, South Africa.

Adult Critical Care Unit, Livingstone Hospital, Gqeberha, South Africa.

出版信息

South Afr J Crit Care. 2022 May 6;38(1). doi: 10.7196/SAJCC.2022.v38i1.532. eCollection 2022.

DOI:10.7196/SAJCC.2022.v38i1.532
PMID:35892117
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9295203/
Abstract

BACKGROUND

A scoring system based on physiological conditions was developed in 1984 to assess the severity of illness. This version, and subsequent versions, were labelled Simplified Acute Physiology Scores (SAPS). Each extension addressed limitations in the earlier version, with the SAPS III model using a data-driven approach. However, the SAPS III model did not include data collected from the African continent, thereby limiting the generalisation of the results.

OBJECTIVES

To propose a scoring system for assessing severity of illness at intensive care unit (ICU) admission and a model for prediction of in-hospital mortality, based on the severity of illness score.

METHODS

This is a prospective cohort study which included patients who were admitted to an ICU in a South African tertiary hospital in 2017. Logistic regression modelling was used to develop the proposed scoring system, and the proposed mortality prediction model.

RESULTS

The study included 829 patients. Less than a quarter of patients (21.35%; n=177) died during the study period. The proposed model exhibited good calibration and excellent discrimination.

CONCLUSION

The proposed scoring system is able to assess severity of illness at ICU admission, while the proposed statistical model may be used in the prediction of in-hospital mortality.

CONTRIBUTIONS OF THE STUDY

This study is the first to develop a model similar to the SAPS III model, based on data collected in South Africa. In addition, this study provides a potential starting point for the development of a model that can be used nationally.

摘要

背景

1984年开发了一种基于生理状况的评分系统来评估疾病的严重程度。这个版本以及后续版本被称为简化急性生理学评分(SAPS)。每个扩展版本都解决了早期版本中的局限性,SAPS III模型采用了数据驱动的方法。然而,SAPS III模型没有纳入从非洲大陆收集的数据,从而限制了结果的推广。

目的

基于疾病严重程度评分,提出一种用于评估重症监护病房(ICU)入院时疾病严重程度的评分系统以及一种院内死亡率预测模型。

方法

这是一项前瞻性队列研究,纳入了2017年入住南非一家三级医院ICU的患者。采用逻辑回归建模来开发所提出的评分系统和死亡率预测模型。

结果

该研究纳入了829名患者。在研究期间,不到四分之一的患者(21.35%;n = 177)死亡。所提出的模型表现出良好的校准和出色的区分度。

结论

所提出的评分系统能够评估ICU入院时的疾病严重程度,而所提出的统计模型可用于预测院内死亡率。

研究贡献

本研究首次基于在南非收集的数据开发了一个类似于SAPS III模型的模型。此外,本研究为开发一个可在全国范围内使用的模型提供了一个潜在的起点。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/660b/9295203/adc9c519108e/SAJCC-38-1-532-fig6.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/660b/9295203/3f36e0222526/SAJCC-38-1-532-fig1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/660b/9295203/d2f45471f961/SAJCC-38-1-532-fig2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/660b/9295203/96bce7efbd07/SAJCC-38-1-532-fig3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/660b/9295203/c7fe60f6d1cb/SAJCC-38-1-532-fig4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/660b/9295203/353459c3e33b/SAJCC-38-1-532-fig5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/660b/9295203/adc9c519108e/SAJCC-38-1-532-fig6.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/660b/9295203/3f36e0222526/SAJCC-38-1-532-fig1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/660b/9295203/d2f45471f961/SAJCC-38-1-532-fig2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/660b/9295203/96bce7efbd07/SAJCC-38-1-532-fig3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/660b/9295203/c7fe60f6d1cb/SAJCC-38-1-532-fig4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/660b/9295203/353459c3e33b/SAJCC-38-1-532-fig5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/660b/9295203/adc9c519108e/SAJCC-38-1-532-fig6.jpg

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