The Role of Ambulatory Heart Failure Clinics to Avoid Heart Failure Admissions
Bibliographic record
Abstract
BACKGROUND: There is a complex relationship between heart failure (HF) clinic services and health outcomes. We hypothesized that ambulatory clinic activity may be associated with both hospital admission and also with avoidance of admission. METHODS: A retrospective comparative cohort study was conducted examining activity in an ambulatory HF Clinic. Consecutive clinic visits in 2013 were recorded (n = 1728) and periods of high-intensity utilization (HIU) were identified (n = 128). A HIU period was defined by ≥2 consecutive clinic visits within 30 days, ending after 30 days passed without an additional clinic visit. For each HIU period identified, patient characteristics (n = 107) and all clinic visits (n = 324) were examined. HIU periods were then classified by association with hospital admission (±30 days). RESULTS: In 2013, 18.8% of all clinic visits occurred during HIU periods, involving 13.7% of the clinic population. Thirty-eight percent of HIU periods were associated with 62 total hospital admissions (±30 days), of which 58% (n = 36) were for a primary diagnosis of HF. In addition,17 HIU periods met criteria for admission avoided, and 7 HIU periods occurring after hospital discharge also met criteria for admission avoided. CONCLUSIONS: We identified periods of intensive ambulatory clinic activity dedicated to patients with high burdens of comorbidities and both HF and non-HF-related admissions. These periods were also associated with episodes of successful decongestion with oral diuretics, resulting in avoidance of admission. Identifying HF patients who can be treated successfully or who are likely to require admission may be helpful for allocating clinic resources.
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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 | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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 | 0.000 | 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".