Identifying opportunities to address the congestive heart failure burden: the Improving Cardiovascular Outcomes in Nova Scotia (ICONS) study.
Bibliographic record
Abstract
BACKGROUND: Medical, social and economic costs of congestive heart failure (CHF) continue to rise. There exists a 'care gap' between what the optimal care populations with CHF should receive and actually do receive. Central to the goal to develop effective strategies against the 'care gap' is accurate measurement of the CHF burden. Administrative data are limited in detail and accuracy and clinical databases suffer from limited size. Improving Cardiovascular Outcomes in Nova Scotia (ICONS) is a province-wide population-based disease management study with access to all patient health data including outcomes. METHODS: Medical records of all patients admitted to any Nova Scotia health care institution with a cardiovascular disorder were prospectively examined by trained abstractors. Patients were followed up and health outcomes measured through assignment of unique identifier numbers and linkage with Vital Statistics Nova Scotia. This report summarizes baseline data for the population admitted to hospital with a diagnosis of CHF between October 15, 1997 and October 14, 1998. RESULTS: There were 2637 unique patients enrolled with 3547 hospitalizations. The median length of stay was eight days, with in-hospital mortality of 18.2%; 10.8% were discharged to long term care. The mortality rate was 38.7% at 12 months and the rehospitalization rate was 39.9%. Average age was 75 +/- 10 years (median 76) and 52% were female. There were 4.5 comorbidities per patient. Left ventricular ejection fraction (LVEF) was measured in fewer than 40%; of these, fewer than 39% had a documented ejection fraction less than 40%. At discharge, 61.3% of survivors were prescribed angiotensin-converting enzyme (ACE) inhibitors, 6.0% angiotensin blockers, 42.1% beta-blockers, 75.6% diuretics, 26.1% calcium channel blockers and 19.3% warfarin. Females were older and had lower rate of LVEF testing and ACE and warfarin usage. CONCLUSION: The burden of disease for CHF in Nova Scotia is large and affects an elderly population with multiple comorbidities. Adverse outcomes such as death, rehospitalization and admission to a chronic care facility are common. Measurement of the 'care gap' requires consideration of these factors and of elderly and female patients regardless of left ventricular function. Successful strategies will likely be multidisciplinary in scope with a focus toward improving access to care.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".