ArticleCritical care medicine2015
Development and Validation of a Mortality Prediction Model for Patients Receiving 14 Days of Mechanical Ventilation.
Article in Critical care medicine, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to 2 registered trials, which are not on this map. Cited by 37 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.
Prediction of Functional Outcomes From Chronic Critical Illness
Prognostic Estimates Among ICU Clinicians Caring for Patients Requiring Prolonged Mechanical Ventilation
Who cites it
37 citing papers in PubMed.
- The Association between Patient Health Status and Surrogate Decision Maker Post-Traumatic Stress Disorder Symptoms in Chronic Critical Illness.Annals of the American Thoracic Society · 2021Trial
- Effects of a Personalized Web-Based Decision Aid for Surrogate Decision Makers of Patients With Prolonged Mechanical Ventilation: A Randomized Clinical Trial.Annals of internal medicine · 2019Trial
- Risk Factors for Post-Traumatic Stress Disorder Symptoms in Surrogate Decision-Makers of Patients with Chronic Critical Illness.Annals of the American Thoracic Society · 2018Trial
- Trial
- Measuring Uncertainty to Inform Time-Limited Trials: Do We Know What We Don't Know?Critical care medicine · 2026Article
- Development and validation of the Tracheostomy‑ProVent score to predict long-term mortality in patients on ventilator care > 21 days: a retrospective cohort study.Respiratory research · 2026Article
- Development of a Prognostic Scoring System for Tracheostomized Patients Requiring Prolonged Ventilator Care: A Ten-Year Experience in a University-Affiliated Tertiary Hospital.Medicina (Kaunas, Lithuania) · 2024Article
- Healthcare Trajectories and Outcomes in the First Year After Tracheostomy Based on Patient Characteristics.Critical care medicine · 2023Article
- Identifying Patterns of Medical Intervention in Acute Respiratory Failure: A Retrospective Observational Study.Critical care explorations · 2023Article
- Surrogates of Patients With Severe Acute Brain Injury Experience Persistent Anxiety and Depression Over the 6 Months After ICU Admission.Journal of pain and symptom management · 2022Review
- Taking a Chance to Recover: Families Look Back on the Decision to Pursue Tracheostomy After Severe Acute Brain Injury.Neurocritical care · 2022Article
- Long-Term Mortality in Critically Ill Tracheostomized Patients Based on Home Mechanical Ventilation at Discharge.Journal of personalized medicine · 2021Article
- Article
- Machine Learning Models to Predict 30-Day Mortality in Mechanically Ventilated Patients.Journal of clinical medicine · 2021Article
- Development of a prognostic scoring system in patients with pneumonia requiring ventilator care for more than 4 days: a single-center observational study.Acute and critical care · 2021Article
- Deep learning to predict long-term mortality in patients requiring 7 days of mechanical ventilation.PloS one · 2021Article
- Functional Status After Pulmonary Rehabilitation as a Predictor of Weaning Success and Survival in Patients Requiring Prolonged Mechanical Ventilation.Frontiers in medicine · 2021Article
- Long-term outcome of prolonged critical illness: A multicentered study in North Brisbane, Australia.PloS one · 2021Article
- Mortality prediction model for the triage of COVID-19, pneumonia, and mechanically ventilated ICU patients: A retrospective study.Annals of medicine and surgery (2012) · 2020Article
- Prognosis for Mechanically Ventilated Patients: A Moving Target.Annals of the American Thoracic Society · 2020Article
Corrections and comments
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Authors and funding
12 authors.
Funding
Abstract
objectivesThe existing risk prediction model for patients requiring prolonged mechanical ventilation is not applicable until after 21 days of mechanical ventilation. We sought to develop and validate a mortality prediction model for patients earlier in the ICU course using data from day 14 of mechanical ventilation.
designMulticenter retrospective cohort study.
settingForty medical centers across the United States. PATIENTS: Adult patients receiving at least 14 days of mechanical ventilation.
interventionsNone. MEASUREMENTS AND MAIN
resultsPredictor variables were measured on day 14 of mechanical ventilation in the development cohort and included in a logistic regression model with 1-year mortality as the outcome. Variables were sequentially eliminated to develop the ProVent 14 model. This model was then generated in the validation cohort. A simplified prognostic scoring rule (ProVent 14 Score) using categorical variables was created in the development cohort and then tested in the validation cohort. Model discrimination was assessed by the area under the receiver operator characteristic curve. Four hundred ninety-one patients and 245 patients were included in the development and validation cohorts, respectively. The most parsimonious model included age, platelet count, requirement for vasopressors, requirement for hemodialysis, and nontrauma admission. The area under the receiver operator characteristic curve for the ProVent 14 model using continuous variables was 0.80 (95% CI, 0.76-0.83) in the development cohort and 0.78 (95% CI, 0.72-0.83) in the validation cohort. The ProVent 14 Score categorized age at 50 and 65 years old and platelet count at 100×10(9)/L and had similar discrimination as the ProVent 14 model in both cohorts.
conclusionUsing clinical variables available on day 14 of mechanical ventilation, the ProVent 14 model can identify patients receiving prolonged mechanical ventilation with a high risk of mortality within 1 year.
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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.