Predictors of Institutionalisation in Incident Dementia – Results of the German Study on Ageing, Cognition and Dementia in Primary Care Patients (AgeCoDe Study)
Bibliographic record
Abstract
BACKGROUND/AIMS: In the past few decades, a number of studies investigated risk factors of nursing home placement (NHP) in dementia patients. The aim of the study was to investigate risk factors of NHP in incident dementia cases, considering characteristics at the time of the dementia diagnosis. METHODS: 254 incident dementia cases from a German general practice sample aged 75 years and older which were assessed every 1.5 years over 4 waves were included. A Cox proportional hazard regression model was used to determine predictors of NHP. Kaplan-Meier survival curves were used to evaluate the time until NHP. RESULTS: Of the 254 incident dementia cases, 77 (30%) were institutionalised over the study course. The mean time until NHP was 4.1 years. Significant characteristics of NHP at the time of the dementia diagnosis were marital status (being single or widowed), higher severity of cognitive impairment and mobility impairment. CONCLUSION: Marital status seems to play a decisive role in NHP. Early initiation of support of sufferers may ensure remaining in the familiar surroundings as long as possible.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".