Impact of the clinical frailty scale on mid-term mortality in patients with ST-elevated myocardial infarction
Bibliographic record
Abstract
BACKGROUND: "Frailty" is associated with poor prognosis in ST-elevated myocardial infarction (STEMI). However, there is little data regarding the impact of the Canadian Study of Health and Aging Clinical Frailty Scale (CFS), a simple and semiquantitative tool for assessing frailty, on mid-term mortality in STEMI patients. METHODS: A total of 354 consecutive STEMI patients (mean age 69.8 ± 12.4 years; male 76.6%) who underwent percutaneous intervention between July 2014 and March 2017 were retrospectively reviewed. The study endpoint was mid-term mortality according to the CFS classification. Furthermore, in order to clarify the impact of CFS upon admission on mid-term mortality, the independent predictors of all-cause death were evaluated. RESULTS: Patients were categorized into three groups (CFS 1-3, n = 281; CFS 4-5, n = 62; and CFS 6-7, n = 11). During the study period (median 474 days), all-cause death was observed in 39 patients. After multivariate Cox regression analysis, higher CFS (adjusted hazard ratio [HR] 2.34, 95% confidence interval [CI] 1.43-3.85, p < 0.001), higher Killip score (adjusted HR 2.46, 95%CI 1.30-5.78, p = 0.002), and lower serum albumin level (adjusted HR 4.29, 95%CI 2.16-8.51, p < 0.001) were significantly associated with an increased risk of all-cause death. CONCLUSION: In conclusion, severe frailty was associated with mid-term mortality in STEMI patients who underwent PCI.
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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".