Gait Speed Predicts 30-Day Mortality After Transcatheter Aortic Valve Replacement
Bibliographic record
Abstract
BACKGROUND: Surgical risk scores do not include frailty assessments (eg, gait speed), which are of particular importance for patients with severe aortic stenosis considering transcatheter aortic valve replacement. METHODS AND RESULTS: We assessed the association of 5-m gait speed with outcomes in a cohort of 8039 patients who underwent transcatheter aortic valve replacement (November 2011-June 2014) and were included in the Society of Thoracic Surgeons/American College of Cardiology Transcatheter Valve Therapy Registry. We evaluated the association between continuous and categorical gait speed and 30-day all-cause mortality before and after adjustment for Society of Thoracic Surgeons-predicted risk of mortality score and key variables. Secondary outcomes included in-hospital mortality, bleeding, acute kidney injury, and stroke. The overall median gait speed was 0.63 m/s (25th-75th percentile, 0.47-0.79 m/s), with the slowest walkers (<0.5 m/s) constituting 28%, slow walkers (0.5-0.83 m/s) making up 48%, and normal walkers (>0.83 m/s) constituting 24% of the population. Thirty-day all-cause mortality rates were 8.4%, 6.6%, and 5.4% for the slowest, slow, and normal walkers, respectively (P<0.001). Each 0.2-m/s decrease in gait speed corresponded to an 11% increase in 30-day mortality (adjusted odds ratio, 1.11; 95% confidence interval, 1.01-1.22). The slowest walkers had 35% higher 30-day mortality than normal walkers (adjusted odds ratio, 1.35; 95% confidence interval, 1.01-1.80), significantly longer hospital stays, and a lower probability of being discharged to home. CONCLUSIONS: Gait speed is independently associated with 30-day mortality after transcatheter aortic valve replacement. Identification of frail patients with the slowest gait speeds facilitates preprocedural evaluation and anticipation of a higher level of postprocedural care. CLINICAL TRIAL REGISTRATION: URL: http://www.clinicaltrials.gov. Unique identifier: NCT01737528.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 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".