Association of Frailty With Readmissions and Outcomes After Impella Mechanical Circulatory Support
Bibliographic record
Abstract
Background: Frailty is associated with a greater risk of readmission after cardiovascular procedures. However, the impact of frailty on readmission rates and outcomes after Impella mechanical circulatory support (MCS) remains unknown. We aimed to explore the impact of frailty on readmission outcomes in patients who received Impella MCS. Methods: Using the National Readmissions Database, patients aged 65 years and older who received Impella MCS between January 2016 and December 2020 were identified. Frailty was determined by the Hospital Frailty Risk Score (HFRS), which stratifies patients into 3 frailty risk categories as low (<5), intermediate (5-15), and high (>15), with intermediate- and high-risk groups defined as frail. The impact of frailty on short-term (within 30 days) and midterm (31-180 days) readmission rates and in-hospital outcomes was assessed. Results: Of the 16,289 patients identified in the 30-day cohort, 8647 (53.1%) were identified as frail (HFRS ≥5) and 2185 (13.4%) had an unplanned readmission at 30 days. After adjusting for age, sex and comorbidities, frailty status (HFRS ≥5) was associated with a greater risk of 30-day readmission (odds ratio [OR] 1.27, 95% confidence interval [CI] 1.17-1.37), death (OR 2.0, 95% CI 1.22-3.30), major adverse events (OR 1.73, 95% CI 1.29-2.33), length of stay >4 days (OR 1.80, 95% CI 1.44-2.26) and greater hospitalization expenditures (OR 1.44, 95% CI 1.17-1.80) during readmission. Of the 6497 patients identified in the 31-180-day cohort, 3521 (54.2%) were considered frail and 1809 (27.8%) experienced unplanned readmissions. An HFRS ≥5 was associated with a greater risk of readmission (OR 2.10, 95% CI 1.88-2.34), in-hospital death (OR 3.02, 95% CI 1.33-6.86), length of stay >4 days (OR 1.66, 95% CI 1.29-2.14), and greater hospital expenditures (OR 1.36, 95% CI 1.05-1.75) during 31-180-day readmission. Conclusions: Frailty is common among patients undergoing Impella MCS and is associated with higher rates of readmission and adverse outcomes during readmission.
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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 | 0.007 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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 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".