Early Follow-Up After a Heart Failure Exacerbation
Bibliographic record
Abstract
BACKGROUND: Although early follow-up for heart failure (HF) is recommended, the time window and which physicians should do the follow-up are unclear. We explored whether (1) follow-up within 14 days and (2) physician continuity influence outcomes within 30 days of a HF exacerbation. METHODS AND RESULTS: Retrospective cohort of all adults in Alberta, Canada, with a first discharge from a hospital or an emergency department where HF was the most responsible diagnosis between April 2002 and November 2013, analyzed using Cox proportional hazards models with time-varying covariates. Of 39 249 adults (mean age,76.1 years), 21 848 (55.7%) received follow-up from a familiar physician, 3938 (10.0%) saw an unfamiliar physician, and 13 463 (34.3%) had no outpatient visits in the first 14 days after a hospitalization or emergency department visit for HF. The risk of death or hospitalization within 30 days was lower in patients who saw a familiar physician (16.9%; adjusted hazard ratio [aHR],0.94;95%confidence interval [CI],0.89-0.99) than inthose who sawan unfamiliar physician (20.0%;aHR,1.05;95%CI,0.97-1.15) or those with no outpatient visits (22.0%;aHR,1.00 [referent]). The composite of death or emergency department visit or hospitalization within 30 days was also less common with familiar physician follow-up (25.2%;aHR,0.86;95%CI,0.82-0.89) compared withunfamiliar physicians (26.9%;aHR,0.93;95%CI,0.87-0.996) or those with no outpatient follow-up within 14 days (47.5%;aHR,1.00 [referent]). CONCLUSIONS: Outpatient follow-up within 14 days after HF exacerbation requiring hospitalization or emergency department visit is associated with better outcomes, particularly if the follow-up is with a familiar physician.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".