Association of Frailty and 1-Year Postoperative Mortality Following Major Elective Noncardiac Surgery
Bibliographic record
Abstract
IMPORTANCE: Single-center studies identify frailty as a risk factor for 30-day postoperative mortality. The long-term and population-level effect of frailty on postoperative mortality is, to our knowledge, poorly described, as are the interactions of frailty with important predictors of mortality. OBJECTIVE: To measure the population-level effect of patient frailty on, and its association with, 1-year postoperative mortality. DESIGN, SETTING, AND PARTICIPANTS: Population-based retrospective cohort study in Ontario, Canada, with data collected between April 1, 2002 and March 31, 2012. Analysis was performed from December 2014 to March 2015. All patients were community-dwelling individuals aged 65 years or older on the day of elective, major noncardiac surgery. EXPOSURE: Frailty, as defined by the Johns Hopkins Adjusted Clinical Groups (ACG) frailty-defining diagnoses indicator. The ACG frailty-defining diagnoses indicator is a binary variable that uses 12 clusters of frailty-defining diagnoses. MAIN OUTCOMES AND MEASURES: One-year all-cause postoperative mortality. RESULTS: Of 202 811 patients, 6289 (3.1%) were frail (mean [SD] age, 77 [7] years). Within 1 year, 13.6% (n = 855) of frail and 4.8% (n = 9433) of nonfrail patients died. Adjustment for sociodemographic and surgical confounders resulted in a hazard ratio of 2.23 (95% CI, 2.08-2.40). The interaction between frailty and postoperative time demonstrated an increased relative hazard for death in frail patients (hazard ratio, 35.58; 95% CI, 29.78-40.19) on postoperative day 3. The association between frailty and increased risk of death decreased with patient age (HR, 2.66; 95% CI, 2.28-3.10 at age 65; HR, 1.63; 95% CI, 1.36-1.95 at age 90). Significant variations in the increased risk for death in frail patients existed between different surgery types and was strongest after total joint arthroplasty (HR, 3.79; 95% CI, 3.21-4.47 for hip replacement; HR, 2.68; 95% CI, 2.10-3.42 for knee replacement). CONCLUSIONS AND RELEVANCE: At a population level, preoperative frailty-defining diagnoses were associated with a significantly increased risk of 1-year mortality that was particularly notable in the early postoperative period, in younger patients, and after joint arthroplasty.
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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 | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".