ArticleCritical care explorations2023
Predictors and Temporal Trends of Withdrawal of Life-Sustaining Therapy After Acute Stroke in the Florida Stroke Registry.
Article in Critical care explorations, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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The trial behind it
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Who cites it
8 citing papers in PubMed, 10 citations in OpenAlex.
- Review
- Detecting Pain Correlates With Recovery in Acute Brain Injury Patients With Disorders of Consciousness.Critical care explorations · 2025Observational
- Association of the ICH Score With Withdrawal of Life-Sustaining Treatment Over a 10-Year Period.Annals of clinical and translational neurology · 2025Article
- Estimating bias from withdrawal of life sustaining treatment in clinical trials.Critical care (London, England) · 2025Review
- Long-Term Outcomes After Severe Acute Brain Injury Requiring Mechanical Ventilation: Recovery Trajectories Among Patients and Mental Health Symptoms of Their Surrogate Decision Makers.Neurocritical care · 2025Observational
- Equity in Clinical Care and Research Involving Persons with Disorders of Consciousness.Neurocritical care · 2024Review
- Time trends in mechanical thrombectomy (2017-2021): do real-world data reflect advances in evidence?Frontiers in neurology · 2024Article
- Factors influencing withdrawal of life-sustaining treatments in patients with severe acquired brain injuries: a scoping review.Frontiers in neurologyReview
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Authors and funding
22 authors at 3 institutions in 1 country.
Funding
Abstract
Temporal trends and factors associated with the withdrawal of life-sustaining therapy (WLST) after acute stroke are not well determined.
designObservational study (2008-2021).
settingFlorida Stroke Registry (152 hospitals). PATIENTS: Acute ischemic stroke (AIS), intracerebral hemorrhage (ICH), and subarachnoid hemorrhage (SAH) patients.
interventionsNone. MEASUREMENTS AND MAIN
resultsImportance plots were performed to generate the most predictive factors of WLST. Area under the curve (AUC) for the receiver operating curve were generated for the performance of logistic regression (LR) and random forest (RF) models. Regression analysis was applied to evaluate temporal trends. Among 309,393 AIS patients, 47,485 ICH patients, and 16,694 SAH patients; 9%, 28%, and 19% subsequently had WLST. Patients who had WLST were older (77 vs 70 yr), more women (57% vs 49%), White (76% vs 67%), with greater stroke severity on the National Institutes of Health Stroke Scale greater than or equal to 5 (29% vs 19%), more likely hospitalized in comprehensive stroke centers (52% vs 44%), had Medicare insurance (53% vs 44%), and more likely to have impaired level of consciousness (38% vs 12%). Most predictors associated with the decision to WLST in AIS were age, stroke severity, region, insurance status, center type, race, and level of consciousness (RF AUC of 0.93 and LR AUC of 0.85). Predictors in ICH included age, impaired level of consciousness, region, race, insurance status, center type, and prestroke ambulation status (RF AUC of 0.76 and LR AUC of 0.71). Factors in SAH included age, impaired level of consciousness, region, insurance status, race, and stroke center type (RF AUC of 0.82 and LR AUC of 0.72). Despite a decrease in the rates of early WLST (< 2 d) and mortality, the overall rates of WLST remained stable.
conclusionsIn acute hospitalized stroke patients in Florida, factors other than brain injury alone contribute to the decision to WLST. Potential predictors not measured in this study include education, culture, faith and beliefs, and patient/family and physician preferences. The overall rates of WLST have not changed in the last 2 decades.
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