Impact of Frailty on Mortality and Discharge Outcomes in Critically Ill Patients: A Systematic Review and Meta-analysis
Bibliographic record
Abstract
Abstract Rationale: Critical illness in patients living with frailty has been reported to be associated with poor health outcomes. Understanding its impact on key outcomes such as mortality, and function is crucial for guiding care strategies and informed shared decision-making in this vulnerable population. This systematic review and meta-analysis provides an updated synthesis of evidence evaluating mortality and likelihood of discharge home in frail patients with critical illness. Methods: We registered this review on Prospero (CRD42023473646) and ensured it follows Meta-analysis of Observational Studies in Epidemiology (MOOSE) and PRISMA guidelines. We searched MEDLINE, EMBASE, CINAHL, ClinicalTrials.gov, and the Cochrane Library up to October 23, 2023, and included observational studies and randomized controlled trials reporting outcomes of adult, critically ill, frail populations. We included studies in all types of ICUs that used a validated frailty ascertainment tool. Two reviewers independently conducted study selection and data extraction. Using RevMan, we conducted random-effects meta-analysis to determine the association of frailty with long-term mortality (≥ 3 months), hospital mortality, and discharge home. We report Risk Ratios (RR) and 95% Confidence Intervals (CIs). We conducted subgroup analyses examining various frailty instruments and ICU type [Medical-Surgical ICU (MSICU) or Cardiovascular ICU (CVICU)]. Results: From 4,687 citations, we included 90 studies with 92 reports and 102 analyses. Frail patients had higher hospital mortality RR 2.29 (95% CI 1.95-2.70), long-term mortality RR 2.59 (95% CI 2.26-2.97) (Figure 1) and were less likely to be discharged home RR 0.43 (95% CI 0.39-0.47) compared with non-frail patients. Subgroup analysis revealed frailty was linked to increased long-term mortality in MSICUs RR 1.75 (95% CI 1.60-1.92) and CVICUs RR 1.68 (95% CI 0.79-3.57). The RR for long-term mortality for frailty across instruments was; Clinical Frailty Scale 1.86 (95% CI 1.61-2.09), Edmonton Frail Scale 2.44 (95% CI 1.67-3.57), Frailty Index 1.40 (95% CI 1.23-1.58), Frailty Phenotype 2.56 (95% CI 1.22-5.37), Hospital Frailty Risk Score 1.72 (95% CI 1.53-1.94), Modified Frailty Index-5 0.84 (95% CI 0.55-1.27) and Modified Frailty Index-11 1.70 (95% CI 1.48-1.95). Conclusions: Frailty is associated with adverse outcomes in critically ill patients. The strength of the association varies by type and frailty ascertainment tool. These findings underscore the importance of standardizing frailty assessment and the need to investigate targeted interventions to improve outcomes in frail critically ill patients. Funding: The Canadian Frailty Network
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.020 | 0.054 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.019 | 0.034 |
| Bibliometrics | 0.009 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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 source (direct Gemma or distilled Codex), 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".