SynthesisMedical care2019
Measuring and Analyzing Length of Stay in Critical Care Trials.
Synthesis in Medical care, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 41 papers, 1 of them a synthesis that pooled 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.
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.
Who cites it
41 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Heterogeneity in design and analysis of ICU delirium randomized trials: a systematic review.Trials · 2021Pooled it
- Mobile App-Facilitated Collaborative Palliative Care Intervention for Critically Ill Older Adults: A Randomized Clinical Trial.JAMA internal medicine · 2025Trial
- Haloperidol vs. placebo for the treatment of delirium in ICU patients: a pre-planned, secondary Bayesian analysis of the AID-ICU trial.Intensive care medicine · 2023Trial
- Valproic acid as adjuvant treatment for convulsive status epilepticus: a randomised clinical trial.Critical care (London, England) · 2023Trial
- Timely administration of tocilizumab improves outcome of hospitalized COVID-19 patients.PloS one · 2022Trial
- Statistical analysis of a cluster-randomized clinical trial on adult general intensive care units in Brazil: TELE-critical care verSus usual Care On ICU PErformance (TELESCOPE) trial.Revista Brasileira de terapia intensivaTrial
- Evaluation of the clinical impact of different telemedicine practices in intensive care units: A stepped-wedge cluster randomized clinical trial (TELESCOPE 2): Study protocol.Critical care and resuscitation : journal of the Australasian Academy of Critical Care Medicine · 2026Article
- Outcomes After Acute Respiratory Failure in Patients With Interstitial Lung Disease.CHEST pulmonary · 2026Article
- Unraveling the Length of Hospital Stay for Patients with Urinary Tract Infections: Contributing Factors and Microbial Susceptibility.Antibiotics (Basel, Switzerland) · 2025Article
- A cross-sectional study on the relationship between length of stay and patient satisfaction based on the SERVQUAL model.Scientific reports · 2025Article
- The Real-World Effect of Early Screening for Palliative Care Criteria in a Medical Intensive Care Unit: An Instrumental Variable Analysis.Annals of the American Thoracic Society · 2025Article
- Article
- Statistical Power and Performance of Strategies to Analyze Composites of Survival and Duration of Ventilation in Clinical Trials.Critical care explorations · 2024Article
- The times are changing: A primer on novel clinical trial designs and endpoints in critical care research.American journal of health-system pharmacy : AJHP : official journal of the American Society of Health-System Pharmacists · 2024Article
- Early clinical outcomes of two regimens of prophylactic antibiotics in cardiac surgical patients with delayed sternal closure.World journal of critical care medicine · 2024Article
- Article
- Measuring Quality-weighted Hospital-Free Days in Acute Respiratory Failure: A Modified Delphi Study.Annals of the American Thoracic Society · 2024Article
- Review
- Article
- A BAYESIAN MACHINE LEARNING APPROACH FOR ESTIMATING HETEROGENEOUS SURVIVOR CAUSAL EFFECTS: APPLICATIONS TO A CRITICAL CARE TRIAL.The annals of applied statistics · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
Abstract
backgroundIn randomized clinical trials among critically ill patients, it is uncertain how choices regarding the measurement and analysis of nonmortal outcomes measured in terms of duration, such as intensive care unit (ICU) length of stay (LOS), affect studies' conclusions.
objectivesAssess the definitions and analytic methods used for ICU LOS analyses in published randomized clinical trials. RESEARCH
designThis is a systematic review and statistical simulation study.
resultsAmong the 80 of 150 trials providing sufficient information regarding the chosen definition of ICU LOS, 3 different start times (ICU admission, trial enrollment/randomization, receipt of intervention) and 2 end times (discharge readiness, actual discharge) were used. In roughly three quarters of these studies, ICU LOS was compared using approaches that did not explicitly account for death, either by ignoring it entirely or stratifying the analyses by survival status. The remaining studies used time-to-event (discharge) models censoring at death or applied a fixed LOS value to patients who died. In statistical simulations, we showed that each analytic approach tested a different question regarding ICU LOS, and that approaches that do not explicitly account for death often produce misleading or ambiguous conclusions when treatments produce small effects on mortality, even if those are not detected as significant in the trial.
conclusionsThere is considerable variability in how ICU LOS is measured and analyzed which impairs the ability to compare results across trials and can produce spurious conclusions. Analyses of duration-based outcomes such as LOS should jointly assess the impact of the intervention on mortality to yield correct interpretations.
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What OpenQuestion holds
Registered trials
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.