Bringing heart care home: management of acute cardiovascular pathologies in the Home Hospital
Bibliographic record
Abstract
The Home Hospital (HH) model delivers hospital-level acute care in patients' homes, offering a scalable, patient-centred alternative to traditional brick-and-mortar facilities. By integrating multidisciplinary teams, remote monitoring, and tailored interventions, HH reduces hospital length of stay, enhances patient satisfaction, and lowers healthcare costs. Despite these benefits, universally established diagnosis-specific management guidelines remain limited, leading to variability in care delivery. Current practices rely on clinical experience and governing protocols, but structured HH pathways must be developed based on system-dependent resources and infrastructure. Standardizing care in HH will allow to ensure patient safety, optimize clinical outcomes, and expand access to acute care beyond conventional hospital settings. This article outlines a blueprint for acute cardiac care in HH, focusing on heart failure, atrial arrhythmias, and venous thromboembolism while emphasizing the critical role of patient selection, recruitment strategies, management protocols, and escalation criteria.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".