Abstract 2301: Frail Elderly Patients at Increased Risk for Mortality and Prolonged Institutional Care After Cardiac Surgery
Bibliographic record
Abstract
Patients referred for cardiac surgery are increasingly older, but chronological age does not always capture biological age. This study assessed frailty, as a functional parameter of biological age, as a predictor of mortality or prolonged institutional care. Functional measures of frailty and clinical preoperative data were collected for all cardiac surgery patients at a single center (2004 –2007). Based on the Katz Index of Activities of Daily Living, frailty was defined as any impairment in feeding, bathing, dressing, transferring, toileting, continence, or ambulation, or dementia. The impact of frailty on in-hospital mortality or institutional discharge (other hospital or nursing facility) was assessed with multivariate logistic regression. The interaction of frailty and age was examined, with non-frail patients age<70 as the referent group. Results: Of 3096 patients, 133 (4.3%) were frail. Frail patients were older, more likely to be female, have COPD, CHF, EF<40%, recent MI, pre-operative renal failure, cerebrovascular disease, greater acuity, and more complex operations (p<0.05). Frail patients experienced higher rates of mortality, sepsis, delirium, post-operative renal failure, and transfusion (p<0.001). A greater proportion of frail patients than non-frail patients (49% vs. 9%) were discharged to a setting other than home. In the risk-adjusted models, frailty was an independent predictor of mortality (OR 1.8, 95% CI 1.0 –3.2) or institutional discharge (OR 6.4, 95% CI 4.1–9.9). Furthermore, frail elderly (age≥70) patients had greater risk of institutional discharge (OR 22.7, CI 12.4 – 41.7) than frail younger patients (OR 6.5, CI 3.4 –12.5) or non-frail elderly patients (OR 3.5, CI 2.6 – 4.6). Similarly, frail elderly patients had greater risk of mortality (OR 4.0, CI 1.9 – 8.1) than frail younger patients (OR 1.9, CI 0.8 – 4.7) or non-frail elderly patients (OR 2.4, CI 1.7–3.5). Frailty was an independent predictor of in-hospital mortality and prolonged institutional care. Frailty combined with older age further discriminated those at highest risk. Special consideration should be given to the management of frail elderly patients who have surgical cardiac 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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".