Incidence of neurological and psychiatric comorbidity over time: a population-based cohort study in Ontario, Canada
Bibliographic record
Abstract
INTRODUCTION: Comprehensive, population-based investigations of the extent and temporality of associations between common neurological and psychiatric disorders are scarce. METHODS: This retrospective cohort study used linked health administrative data for Ontarians aged 40-85 years on 1 April 2002, to estimate the adjusted rate of incident dementia, Parkinson's disease (PD), stroke or mood/anxiety disorder (over 14 years) according to the presence and time since diagnosis of a prior disorder. Sex differences in the cumulative incidence of a later disorder were also examined. RESULTS: The cohort included 5,283,546 Ontarians (mean age 56.2 ± 12.1 years, 52% female). The rate of dementia was significantly higher for those with prior PD (adjusted hazard ratio [adjHR] 4.05, 95% confidence interval [CI] 3.99-4.11); stroke (adjHR 2.49, CI 2.47-2.52) and psychiatric disorder (adjHR 1.79, CI 1.78-1.80). The rate of PD was significantly higher for those with prior dementia (adjHR 2.23, CI 2.17-2.30) and psychiatric disorder (adjHR 1.77, CI 1.74-1.81). The rate of stroke was significantly higher among those with prior dementia (adjHR 1.56, CI 1.53-1.58). Prior dementia (adjHR 2.36, CI 2.33-2.39), PD (adjHR 1.80, CI 1.75-1.85) and stroke (adjHR 1.47, CI 1.45-1.49) were associated with a higher rate of an incident psychiatric disorder. Generally, associations were strongest in the 6 months following a prior diagnosis and demonstrated a J-shape relationship over time. Significant sex differences were evident in the absolute risks for several disorders. CONCLUSIONS: The observed nature of bidirectional associations between these neurological and psychiatric disorders indicates opportunities for earlier diagnosis and interventions to improve patient 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) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".