Critically Ill Older Adults’ Representation in Intervention Trials: A Systematic Review
Bibliographic record
Abstract
OBJECTIVES: Older adults may be under-represented in critical care research, and results may not apply to this specific population. Our primary objective was to evaluate the prevalence of inclusion of older adults across critical care trials focused on common ICU conditions or interventions. Our secondary objective was to evaluate whether older age was used as a stratification variable for randomization or outcome analysis. DESIGN SETTING AND SUBJECTS: We performed a systematic review of previously published systematic reviews of randomized controlled trials (RCTs) in critical care. We searched PubMed, Ovid, CENTRAL, and Cochrane from 2009 to 2022. Systematic reviews of any interventions across five topics: acute respiratory distress syndrome (ARDS), sepsis/shock, nutrition, sedation, and mobilization were eligible. MAIN RESULTS: We identified 216 systematic reviews and included a total of 253 RCTs and 113,090 patients. We extracted baseline characteristics and the reported proportion of older adults. We assessed whether any upper age limit was an exclusion criterion for trials, whether age was used for stratification during randomization or data analysis, and if age-specific subgroup analysis was present. The most prevalent topic was sepsis (78 trials, 31%), followed by nutrition (62 trials, 25%), ARDS (39 trials, 15%), mobilization (38 trials, 15%), and sedation (36 trials, 14%). Eighteen trials (7%) had exclusion criteria based on older age. Age distribution with information on older adults prevalence was given in six trials (2%). Age was considered in the analysis of ten trials (5%) using analytic methods to evaluate the outcome stratified by age. Conclusions: In this systematic review, the proportion of older critically ill patients is undetermined, and it is unclear how age is or is not an effect modifier or to what extent the results are valid for older adult groups. Reporting age is important to guide clinicians in personalizing care. These results highlight the importance of incorporating older critically ill patients in future trials to ensure the results are generalizable to this growing population.
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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 | 0.002 | 0.111 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.006 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.001 |
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".