Frailty scoring in vascular and endovascular surgery: A systematic review
Bibliographic record
Abstract
One in 10 independently living adults aged 65 years old and older is considered frail, and frailty is associated with poor postoperative outcomes. This systematic review aimed to examine the association between frailty assessments and postoperative outcomes in patients with vascular disease. Electronic databases – MEDLINE, Embase, and the Cochrane Library – were searched from inception until January 2022, resulting in 648 articles reviewed for potential inclusion and 16 studies selected. Demographic data, surgery type, frailty measure, and postoperative outcomes predicted by frailty were extracted from the selected studies. The risk of bias was assessed using the Newcastle–Ottawa Scale. The selected studies (mean age: 56.1–76.3 years) had low-to-moderate risk of bias and included 16 vascular (elective and nonelective) surgeries and eight frailty measures. Significant associations ( p < 0.05) were established between mortality (30-day, 90-day, 1-year, 5-year), 30-day morbidity, nonhome discharge, adverse events, failure to rescue, patient requiring care after discharge, and amputation following critical limb ischaemia. The strongest evidence was found between 30-day mortality and frailty. Composite 30-day morbidity and mortality, functional status at discharge, length of stay, spinal cord deficit, and access site complications were found to be nonsignificantly associated with frailty. With frailty being significantly associated with several adverse postoperative outcomes, preoperative frailty assessments can potentially be clinically useful in helping practitioners predict and guide the pre-, peri-, and postoperative management of frail with vascular disease.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.006 | 0.028 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.008 |
| Bibliometrics | 0.009 | 0.007 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".