Frailty Significantly Associated with a Risk for Mid-term Outcomes in Elderly Chronic Coronary Syndrome Patients: a Prospective Study
Bibliographic record
Abstract
Abstract Introduction: Frailty is a condition of elderly characterized by increased vulnerability to stressful events. Frail patients are more likely to have adverse events. The purposes of this study were to define frailty in patients aged ≥ 70 years with chronic coronary syndrome (CCS) and to evaluate mortality and prognostic significance of frailty in these patients. Methods: We included 99 patients, ≥ 70 years old (mean age 74±5.3 years), with diagnosis of CCS. They were followed-up for up to 12 months. The frailty score was evaluated according to the Canadian Study of Health and Aging (CSHA). All patients were divided as frail or non-frail. The groups were compared for their characteristics and clinical outcomes. Results: Fifty patients were classified as frail, and 49 patients as non-frail. The 12-month Major Adverse Cardiac Events (MACE) rate was 69.4% in frail patients and 20% in non-frail patients. Frailty increases the risk for MACE as much as 3.48 times. Two patients died in the non-frail group and 11 patients died in the frail group. Frailty increases the risk for death as much as 6.05 times. When we compared the aforementioned risk factors by multivariate analysis, higher CSHA frailty score was associated with increased MACE and death (relative risk [RR] = 22.94, 95% confidence interval [CI] 3.33-158.19, P=0.001, for MACE; RR = 7.41, 95% CI 1.44-38.03, P=0.016, for death). Conclusion: Being a frail elderly CCS patient is associated with worse outcomes. Therefore, frailty score should be evaluated for elderly CCS patients as a prognostic marker.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".