Prognostic Factors for Long-Term Mortality in Critically Ill Patients Treated With Prolonged Mechanical Ventilation: A Systematic Review
Bibliographic record
Abstract
OBJECTIVES: Long-term survival for patients treated with prolonged mechanical ventilation is generally poor; however, patient-level factors associated with long-term mortality are unclear. Our objective was to systematically review the biomedical literature and synthesize data for prognostic factors that predict long-term mortality in prolonged mechanical ventilation patients. DATA SOURCES: We searched PubMed, CINAHL, and Cochrane Library from 1988 to 2015 for studies on prolonged mechanical ventilation utilizing a comprehensive strategy without language restriction. STUDY SELECTION: We included studies of adults 1) receiving mechanical ventilation for more than or equal to 14 days, 2) admitted to a ventilator weaning unit, or 3) received a tracheostomy for acute respiratory failure. We analyzed articles that used a multivariate analysis to identify patient-level factors associated with long-term mortality (≥ 6 mo from when the patient met criteria for receiving prolonged mechanical ventilation). DATA EXTRACTION: We used a standardized data collection tool and assessed study quality with a customized Newcastle-Ottawa Scale. We abstracted the strength of association between each prognostic factor and long-term mortality. Individual prognostic factors were then designated as strong, moderate, weak, or inconclusive based on an a priori previously published schema. DATA SYNTHESIS: A total of 7,411 articles underwent relevance screening; 419 underwent full article review. We identified 14 articles that contained a multivariate analysis. We abstracted 19 patient-level factors that showed association with long-term mortality. Six factors demonstrated strong strength of evidence for association with the primary outcome: age, vasopressor requirement, thrombocytopenia, preexisting kidney disease, failed ventilator liberation, and acute kidney injury ± hemodialysis requirement. All factors, except preexisting kidney disease and failed ventilator liberation, were measured at the time the patients met criteria for prolonged mechanical ventilation. CONCLUSIONS: Despite the magnitude of the public health challenge posed by the prolonged mechanical ventilation population, only 14 articles in the biomedical literature have tested patient-level factors associated with long-term mortality. Further research is needed to inform optimal patient selection for prolonged mechanical ventilation.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.022 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.006 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".