Evidence map›Paper›PMID 34779870›Full record

ArticleEuropean journal of trauma and emergency surgery : official publication of the European Trauma Society2022

Prediction of recovery in trauma patients using Latent Markov models.

Roos Johanna Maria Havermans, Felix Johannes Clouth, Koen Willem Wouter Lansink, Jeroen Kornelis Vermunt, Mariska Adriana Cornelia de Jongh, Leonie de Munter

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Article in European journal of trauma and emergency surgery : official publication of the European Trauma Society, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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0cells of the map it votes in
1citing papers in PubMed
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1 · What the graph read from it

What it found

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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

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3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Characterizing heterogeneity in health-related quality of life trajectories in coronary artery disease: a longitudinal latent Markov analysis.Quality of life research : an international journal of quality of life aspects of treatment, care and rehabilitation · 2026
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4 · The record

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5 · Who and what money

Authors and funding

6 authors.

Roos Johanna Maria HavermansDepartment of Surgery, ETZ Hospital, Tilburg, The Netherlands. r.havermans@etz.nl.ORCID http://orcid.org/0000-0001-7037-4671
Felix Johannes ClouthDepartment of Methodology and Statistics, Tilburg University, Tilburg, The Netherlands.
Koen Willem Wouter LansinkDepartment of Surgery, ETZ Hospital, Tilburg, The Netherlands.
Jeroen Kornelis VermuntDepartment of Methodology and Statistics, Tilburg University, Tilburg, The Netherlands.
Mariska Adriana Cornelia de JonghBrabant Trauma Registry, Network Emergency Care Brabant, Tilburg, The Netherlands.
Leonie de MunterDepartment Trauma TopCare, ETZ Hospital, Tilburg, The Netherlands.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposePatients' expectations during recovery after a trauma can affect the recovery. The aim of the present study was to identify different physical recovery trajectories based on Latent Markov Models (LMMs) and predict these recovery states based on individual patient characteristics.

methodsThe data of a cohort of adult trauma patients until the age of 75 years with a length of hospital stay of 3 days and more were derived from the Brabant Injury Outcome Surveillance (BIOS) study. The EuroQol-5D 3-level version and the Health Utilities Index were used 1 week, and 1, 3, 6, 12, and 24 months after injury. Four prediction models, for mobility, pain, self-care, and daily activity, were developed using LMMs with ordinal latent states and patient characteristics as predictors for the latent states.

resultsIn total, 1107 patients were included. Four models with three ordinal latent states were developed, with different covariates in each model. The prediction of the (ordinal) latent states in the LMMs yielded pseudo-R

conclusionThe use of LMMs to model the development of physical function post-injury is a promising way to obtain a prediction of the physical recovery. The step-by-step prediction fits well with the outpatient follow-up and it can be used to inform the patients more tailor-made to manage the expectations.

Indexed as

Activities of Daily LivingOutcome Assessment, Health CareAdultAgedCohort StudiesHumansLength of StayRecovery of FunctionLatent Markov modelPhysical functionRecoveryTrauma

Identifiers

PMID34779870

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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.