Effect of Preoperative Geriatric Evaluation on Outcomes After Elective Surgery: A Population‐Based Study
Why this work is in the frame
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Bibliographic record
Abstract
BACKGROUND/OBJECTIVES: Randomized and nonrandomized single-center studies suggest that preoperative geriatric evaluation improves postoperative outcomes in older adults. The generalizability and population-level effect of preoperative geriatric evaluation has not been determined. Our objective was to measure the adjusted association between preoperative geriatric evaluation and postoperative outcomes. DESIGN: Multilevel multivariable regression model analysis of a population-based historical cohort. SETTING: Publicly funded universal healthcare system in Ontario, Canada. PARTICIPANTS: All adults aged 65 and older having major, elective, noncardiac surgery from 2002 to 2014 (N = 266,499). INTERVENTION: We studied geriatric consultations and comprehensive assessments performed in the 4 months prior to surgery. These were identified using validated methods. MEASUREMENTS: Ninety-day survival (primary outcome), in-hospital complications, length of stay, 30-day readmissions, need for supported discharge, and 90-day costs of care. RESULTS: The 7,352 participants (2.8%) who had a preoperative geriatric evaluation had longer 90-day survival than those who who did not (adjusted hazard ratio = 0.81, 95% confidence interval = 0.68-0.95). Length of stay and complication rates did not differ between groups, but participants evaluated by a geriatrician preoperatively had higher rates of supported discharge, readmission rates, and costs of care. Sensitivity analyses supported the association between preoperative geriatric assessment and 90-day survival. CONCLUSION: In individuals aged 65 and older undergoing major, elective, noncardiac surgery, preoperative geriatric evaluation was associated with longer 90-day survival, but it is used infrequently. Given these results, and those of previous small studies, the influence of a geriatric evaluation on postoperative outcomes should be determined in a multicenter randomized trial.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 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 | 0.000 |
| 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 it