Overall mortality in older people receiving physician-led home visits: a multicentre prospective study in Japan
Bibliographic record
Abstract
BACKGROUND: Japan has the most rapidly ageing population in the world. The Japanese government has, therefore, promoted physician-led home health care for frail and disabled people. OBJECTIVES: To describe mortality among older people receiving physician-led health care at home or at a nursing home in Japan and to identify risk factors. METHODS: This was a multicentre prospective cohort study. Participants were aged ≥65 years and had started to receive regular physician-led health care at home or at nursing homes from 13 facilities between 1 February 2013 and 31 January 2016. The observation period ended on 31 January 2017. We used a biopsychosocial approach for exploratory analysis of 13 variables to identify mortality risk factors. RESULTS: The median (25th to 75th percentile) observation time was 417 (121-744) days. Of 825 participants, 380 died. The total cumulative survival for 180, 360, 720 and 1440 days was 73.4% (95% confidence interval: 70.2-76.3), 64.2% (60.8-67.5), 52.6% (48.8-56.3) and 34.6% (23.5-46.0). The Kaplan-Meier cumulative survival curve showed a steep drop during the first 6 months of observation. A multivariate Cox proportional hazard model showed that sex (male), high Charlson Comorbidity Index score, low serum albumin level, low Barthel Index score, receipt of oxygen therapy, high Cornell Scale for Depression in Dementia score and non-receipt of public assistance were associated with mortality. CONCLUSIONS: Overall mortality in physician-led home visits in Japan was described and mortality risk factors identified. Public assistance receipt was associated with lower mortality.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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".