The impact of frailty on cardiac surgery outcomes: an international cohort study
Bibliographic record
Abstract
Abstract Background/Introduction Frailty, affecting between 20–46% of people presenting for cardiac surgery, is associated with increased mortality, perioperative complications and poorer post-operative quality of life. Due to a previous lack of standardised definition and tool for assessment a stricter evaluation of the impact of frailty on cardiac surgery is considered a research priority. Recently the Clinical Frailty Scale (CFS) was identified as the first line assessment tool of choice in cardiac surgery pre-assessment (1) Purpose To evaluate the impact of frailty, assessed pre-operatively using CFS, on cardiac surgery outcomes using routinely available data from international centres represented within our international network. Methods Centres for participation were sought through our international network. Appropriate governance approvals were obtained according to local procedures. Routine electronic data for pre-operative details, risk factor profile, operative details and outcome data, matched for definitions (or based on country-norms), were extracted for patients undergoing elective coronary artery bypass graft (CABG) surgery, valve surgery or combination between 8th January 2024 and 7th January 2025. Outcome measures include In-hospital mortality, post-operative complications (new neurological dysfunction, return to theatre, infection), intensive care and hospital length of stay and post-operative supported care. Data will be cleaned and analysed locally, and collated for reporting (adhering to RECORD statement) and comparison. Analysis, conducted in SPSS, will include descriptive statistics and outcomes by age, sex and frailty severity. Results Of 17 international healthcare organisations across eight countries represented within our international network in January 2024, 6 (35.3%) assessed frailty routinely in cardiac surgery patients. Of those, one (Ireland) did not use CFS and a further two centres did not collect data electronically (Canada, Sweden). Final analysis will include three centres (Australia, England and Scotland). Overall, >2000 patients will be included, with discharge cut-off for final patients 1-month post-surgery (6th February 2025), thus analysis is still to be undertaken. All data analysis will be completed for presentation at ACNAP2025. Conclusion(s) This contemporary prospective cross-sectional study highlights the lack of routine frailty assessment prior to cardiac surgery, and documentation in the electronic health record, internationally. Completed analysis exploring the impact of frailty (measured using the recently preferred tool, the CFS) on cardiac surgery outcomes, will provide important and novel evidence in the process of identifying and addressing frailty in patients undergoing cardiac surgery.
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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 | 0.006 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| 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 | 0.000 | 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 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".