Predicting hospital mortality for intensive care unit patients: Time-series analysis.
Health Informatics J
; 26(2): 1043-1059, 2020 06.
Article
em En
| MEDLINE
| ID: mdl-31347428
ABSTRACT
Current mortality prediction models and scoring systems for intensive care unit patients are generally usable only after at least 24 or 48 h of admission, as some parameters are unclear at admission. However, some of the most relevant measurements are available shortly following admission. It is hypothesized that outcome prediction may be made using information available in the earliest phase of intensive care unit admission. This study aims to investigate how early hospital mortality can be predicted for intensive care unit patients. We conducted a thorough time-series analysis on the performance of different data mining methods during the first 48 h of intensive care unit admission. The results showed that the discrimination power of the machine-learning classification methods after 6 h of admission outperformed the main scoring systems used in intensive care medicine (Acute Physiology and Chronic Health Evaluation, Simplified Acute Physiology Score and Sequential Organ Failure Assessment) after 48 h of admission.
Palavras-chave
Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Assunto principal:
Cuidados Críticos
/
Unidades de Terapia Intensiva
Tipo de estudo:
Observational_studies
/
Prognostic_studies
/
Risk_factors_studies
Limite:
Humans
Idioma:
En
Revista:
Health Informatics J
Ano de publicação:
2020
Tipo de documento:
Article
País de afiliação:
Egito