Association between walking speed early after admission and all-cause death and/or re-admission in patients with acute decompensated heart failure
Bibliographic record
Abstract
AIMS: Patients with heart failure (HF) frequently experience decreased physical function, including walking speed. Slower walking speed is associated with poorer prognosis. However, most of these reports focused on patients with stable HF, and the relationship between walking speed in acute phase and clinical outcomes is unclear. Therefore, we aimed to investigate the associations between walking speed early after admission and clinical events in patients with acute decompensated HF (ADHF). METHODS AND RESULTS: We reviewed consecutive 1391 patients admitted due to ADHF. We measured walking speed the first time to walk on the ward more than 10 m after admission, and the speed within 4 days after admission was included in this study. The primary outcome was combined events (all-cause death and/or re-admission due to HF). The follow-up period was up to 1 year from the discharge. The study population had a median age of 74 years [interquartile range (IQR): 65-80 years], and 35.9% of patients were females. The median walking speed was 0.70 m/s (IQR: 0.54-0.88 m/s). Combined events occurred in 429 (30.8%) patients. Faster walking speed was independently associated with lower rate of combined events (adjusted hazard ratio per 0.1 m/s increasing: 0.951, 95% confidence interval: 0.912-0.992). CONCLUSION: Faster walking speed within 4 days after admission was associated with favourable clinical outcomes in patients with ADHF. The results suggest that measuring walking speed in acute phase is useful for earlier risk stratification.
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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 | 0.003 |
| 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 | 0.001 |
| 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".