Evidence map›Paper›PMID 35892117›Full record

ArticleThe Southern African journal of critical care : the official journal of the Critical Care Society2022

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

S Pazi, G Sharp, E van der Merwe

Abstract read
In one paragraph

Article in The Southern African journal of critical care : the official journal of the Critical Care Society, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Article
  2. Mortality risk prediction models: Methods of assessing discrimination and calibration and what they mean.The Southern African journal of critical care : the official journal of the Critical Care Society · 2022
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

S PaziDepartment of Statistics, Nelson Mandela University, Gqeberha, South Africa.
G SharpDepartment of Statistics, Nelson Mandela University, Gqeberha, South Africa.
E van der MerweAdult Critical Care Unit, Livingstone Hospital, Gqeberha, South Africa.ORCID https://orcid.org/0000-0002-4628-8885

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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.

Indexed as

Africacritical carehospital mortalityICU scoring systemintensive careSAPS IIIseverity of illness

Identifiers

PMID35892117
PMCPMC9295203

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.