ArticleAmerican journal of respiratory and critical care medicine2023
Accounting for Competing Events When Evaluating Long-Term Outcomes in Survivors of Critical Illness.
Article in American journal of respiratory and critical care medicine, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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.
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
8 citing papers in PubMed.
- Effects of long-term, home-based, virtual cycling after COPD exacerbation - results from the randomised controlled COPDtoParis trial.European clinical respiratory journal · 2026Article
- Clinical characteristics and outcomes of critically ill adult patients admitted with traumatic brain injury: a cohort study.Canadian journal of anaesthesia = Journal canadien d'anesthesie · 2025Article
- Bronchodilator Response: Utility and implications in patients undergoing hematopoietic stem cell transplantation.Respiratory medicine · 2025Article
- Article
- Article
- Severity of Inhalation Injury and Risk of Nosocomial Pneumonia: A Retrospective Cohort Study.Chest · 2024Article
- Preexisting Diabetes Mellitus and All-Cause Mortality in Adult Patients With Sepsis: A Population-Based Cohort Study.Critical care explorations · 2024Article
- A Risk Model for 28-Day in-Hospital Mortality in 173 COVID-19 Patients Admission to ICU: A Retrospective Study.Infection and drug resistance · 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
The clinical trajectory of survivors of critical illness after hospital discharge can be complex and highly unpredictable. Assessing long-term outcomes after critical illness can be challenging because of possible competing events, such as all-cause death during follow-up (which precludes the occurrence of an event of particular interest). In this perspective, we explore challenges and methodological implications of competing events during the assessment of long-term outcomes in survivors of critical illness. In the absence of competing events, researchers evaluating long-term outcomes commonly use the Kaplan-Meier method and the Cox proportional hazards model to analyze time-to-event (survival) data. However, traditional analytical and modeling techniques can yield biased estimates in the presence of competing events. We present different estimands of interest and the use of different analytical approaches, including changes to the outcome of interest, Fine and Gray regression models, cause-specific Cox proportional hazards models, and generalized methods (such as inverse probability weighting). Finally, we provide code and a simulated dataset to exemplify the application of the different analytical strategies in addition to overall reporting recommendations.
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Registered trials
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