ArticleActa anaesthesiologica Scandinavica2022
Optimizing an existing prediction model for quality of life one-year post-intensive care unit: An exploratory analysis.
Article in Acta anaesthesiologica Scandinavica, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- Determinants of Early Quality-of-Life Improvement After Open Abdominal Wall Eventration Repair: A Large Single-Center Cohort Study Using the EuraHS-QoL Score.Journal of clinical medicine · 2026Article
- Prediction of glycaemic control and quality of life in people with type 2 diabetes using glucose-lowering drugs with machine learning-The Maastricht study.Diabetes, obesity & metabolism · 2025Article
- Article
- Machine learning to predict poor school performance in paediatric survivors of intensive care: a population-based cohort study.Intensive care medicine · 2023Article
- Optimizing an existing prediction model for quality of life one-year post-intensive care unit: An exploratory analysis.Acta anaesthesiologica Scandinavica · 2022Article
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Authors and funding
9 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundThis study aimed to improve the PREPARE model, an existing linear regression prediction model for long-term quality of life (QoL) of intensive care unit (ICU) survivors by incorporating additional ICU data from patients' electronic health record (EHR) and bedside monitors.
methodsThe 1308 adult ICU patients, aged ≥16, admitted between July 2016 and January 2019 were included. Several regression-based machine learning models were fitted on a combination of patient-reported data and expert-selected EHR variables and bedside monitor data to predict change in QoL 1 year after ICU admission. Predictive performance was compared to a five-feature linear regression prediction model using only 24-hour data (R
resultsThe 67.9% of the included ICU survivors was male and the median age was 65.0 [IQR: 57.0-71.0]. Median length of stay (LOS) was 1 day [IQR 1.0-2.0]. The incorporation of the additional data pertaining to the entire ICU stay did not improve the predictive performance of the original linear regression model. The best performing machine learning model used seven features (R
conclusionPre-ICU QoL was by far the most important predictor for change in QoL 1 year after ICU admission. The incorporation of the numerous additional features pertaining to the entire ICU stay did not improve predictive performance although the patients' LOS was relatively short.
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