Time-dependent uncertainty of critical care transitions in very old patients - lessons for time-limited trials.
Intensive care
Oldest old
Prognosis
Statistical model
Uncertainty
Journal
Journal of critical care
ISSN: 1557-8615
Titre abrégé: J Crit Care
Pays: United States
ID NLM: 8610642
Informations de publication
Date de publication:
10 2022
10 2022
Historique:
received:
11
01
2022
revised:
10
05
2022
accepted:
12
05
2022
pubmed:
1
6
2022
medline:
3
9
2022
entrez:
31
5
2022
Statut:
ppublish
Résumé
Prognostication for patients with critical conditions remains challenging, especially for very old individuals. Time-limited trials (TLT) are used to decrease prognostic uncertainty in the individual patient by monitoring the response to treatment over a pre-determined period of time. However, there are substantial difficulties with determining the length of that period. This study presents a probabilistic method to estimate a suitable duration of a TLT based on temporal profiles of uncertainty about critical care and outcome. The study included very old patients (age ≥ 80 years, n = 1209) from the VIP2 study cohort who were admitted to the ICU for between 2 and 14 days, with respiratory or circulatory support from day 1 and with either no limitations of life-sustaining treatment or a decision to withdraw that treatment, as well as with complete data. Multi-state modelling of critical care trajectories to obtain time-dependent probabilities for transitions between distinct levels of organ support and to outcome states. The extent of uncertainty is quantified by Shannon's entropy of probability distributions at discrete points in time. We detected periods of enhanced prognostic uncertainty of up to 7 days after admission. The duration of these periods depends on patient characteristics at baseline (frailty, severity of critical illness) and the extent of organ support. Time-dependent patterns of uncertainty concerning the response to critical care can inform decisions about the duration of TLTs which may last up to a week in very old patients.
Identifiants
pubmed: 35636347
pii: S0883-9441(22)00096-X
doi: 10.1016/j.jcrc.2022.154067
pii:
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
154067Informations de copyright
Copyright © 2022 Elsevier Inc. All rights reserved.