Prospective cohort study of elderly patients with coronary artery disease: impact of frailty on quality of life and outcome
Bibliographic record
Abstract
BACKGROUND: Elderly, frail patients are often excluded from clinical trials so there is lack of data regarding optimal management when they present with symptomatic coronary artery disease (CAD). OBJECTIVE: The aim of this observational study was to evaluate an unselected elderly population with CAD for the occurrence of frailty, and its association with quality of life (QoL) and clinical outcomes. METHODS: Consecutive patients aged ≥80 years presenting with CAD were prospectively assessed for frailty (Fried frailty phenotype (FFP), Edmonton frailty scale (EFS)), QoL (Short form survey (SF-12)) and comorbidity (Charlson Comorbidity Index (CCI)). Patients were re-assessed at 4 months to determine any change in frailty and QoL status as well as the clinical outcome. RESULTS: One hundred fifty consecutive patients with symptomatic CAD were recruited in the study. The mean age was 83.7±3.2 years, 99 (66.0%) were men. The clinical presentation was stable angina in 68 (45.3%), the remainder admitted with an acute coronary syndrome including 21 (14.0%) with ST-elevation myocardial infarction. Frailty was present in 28% and 26% by FFP and EFS, respectively, and was associated with a significantly higher CCI (7.5±2.4 in frail, 6.2±2.2 in prefrail, 5.9±1.6 in those without frailty, p=0.005). FFP was significantly related to the physical composite score for QoL, while EFS was significantly related to the mental composite score for QoL (p=0.003). Treatment was determined by the cardiologist: percutaneous coronary intervention in 51 (34%), coronary artery bypass graft surgery in 15 (10%) and medical therapy in 84 (56%). At 4 months, 14 (9.3%) had died. Frail participants had the lowest survival. Cardiovascular symptom status and the mental composite score of QoL significantly improved (52.7±11.5 at baseline vs 55.1±10.6 at follow-up, p=0.04). However, overall frailty status did not significantly change, nor the physical health composite score of QoL (37.2±11.0 at baseline vs 38.5±11.3 at follow-up, p=0.27). CONCLUSIONS: In patients referred to hospital with CAD, frailty is associated with impaired QoL and a high coexistence of comorbidities. Following cardiac treatment, patients had improvement in cardiovascular symptoms and mental component of QoL.
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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 | 0.002 | 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) | 0.001 | 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".