Impact of Fried Frailty Phenotype on Postoperative Outcomes After Durable Contemporary Mechanical Circulatory Support: A Single-Center Experience
Bibliographic record
Abstract
Background: Frailty is prevalent in advanced heart failure patients and may help distinguish patients at risk of worse outcomes. However, the effect of frailty on postoperative clinical outcomes is still understudied. Therefore, we aim to study the relationship between frailty and postoperative clinical outcomes in patients undergoing long-term mechanical circulatory support (MCS). Methods: Forty-six patients undergoing durable MCS (left ventricular assist device and total artificial heart) placement at our medical center were assessed for frailty pre-implant. Frailty was defined as ≥ 3 physical components of the Fried frailty phenotype. Our primary endpoint is 1 year of survival post-implant. Secondary endpoints include 30-day all-cause rehospitalization, pump thrombosis, neurological event (stroke/transient ischemic attack), gastrointestinal bleeding, and driveline infection within 12 months post-MCS support. Results: Of the 46 patients, 32 (69%) met the criteria for frailty according to Fried. The cohort's median age was 67.0 years. The frail group had statistically significant lower left ventricular ejection fraction (LVEF) (11% vs. 20%, P = 0.017) and lower albumin (3.5 vs. 4.0 g/dL, P = 0.021). The frail cohort also had significantly higher rates of comorbid chronic kidney disease (47% vs. 7%, P = 0.016). There were no differences between the frail vs. non-frail group in terms of 30-day readmission rates (40% vs. 39%, P = 0.927) and 1-year post-intervention survival (log-rank, P = 0.165). None of the other secondary endpoints reached statistical significance, although the incidence of gastrointestinal bleed (24% vs. 16%, P = 0.689) and pump thrombosis (8% vs. 0%, P = 0.538) were higher in the frail group. Conclusions: Preoperative Fried frailty was not associated with readmission at 30 days, mortality at 365 days, and other postoperative outcomes in long-term durable MCS patients. Findings may need further validation in larger studies.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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 teacher head, 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".