O4–04–06: Hospitalized Alzheimer's disease or dementia in Canada
Bibliographic record
Abstract
This study provides an overall picture of the burden of hospitalized Alzheimer's disease or dementia (AD) in Canada. The diagnosis of AD (ICD-10-CA codes G300–301, G308–301, F010–013, F018–019, and F03) were identified from 2007/08 to 2010/11 acute care hospital separations (Hospital Morbidity Database) in all Canadian jurisdictions. In-hospital case fatality and hospital separation rates were calculated. Further, the most common comorbid (secondary) diagnoses were identified for the hospital separations with AD as the most responsible diagnosis (MRDx). The reverse was also examined. When AD was found as a comorbid (secondary) condition, the frequency of the MRDx was also quantified. Over the last four years, the number of hospitalizations with AD as MRDx increased from 12,484 in 2007/08 to 13,789 in 2010/11, the proportion of all hospitalization for each year remained stable (0.4%). There were more females than males (59% vs. 41%) for all four years. In 2010/11, on average, each AD hospitalization has 7.1 comorbid conditions, such as hypertension, diabetes, atrial fibrillation, hypothyroidism, and ischemic heart disease. Moreover, AD contributed to an additional 68,866 (males: 38.6%; females: 61.4%) hospital separations as a comorbid condition. Primarily, they were pneumonia, heart failure, COPD, and stroke. The average length of stay in hospital for AD was 46 days, compared to 7.1 days for hospitalizations for all causes in Canada. Only 20.2% (males: 19.2%; females: 21.0%) of AD patients were discharged home after their hospitalization. The in-hospital case fatality rate was 9.3% (males: 11.5%; females: 7.8%). Nearly half of AD patients (48.5%; males: 47.0%; females: 49.5%) were transferred to a long-term care facility. One fifth of the patients (18.3%) were transferred to home with support services. Although the proportion of AD hospitalization remained stable, the number of AD hospitalizations has increased over the last four years. AD has a high in-hospital case fatality rate, particularly among males. The long hospital stay, multiple comorbid conditions, and high rate of transfer to a long term care facility for AD indicate that it places a significant burden per case on the health care system in Canada.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.006 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".