The 5-Year Incidence of Mental Disorders in a Population-Based ICU Survivor Cohort
Bibliographic record
Abstract
OBJECTIVE: To estimate incidence of newly diagnosed mental disorders among ICU patients. DESIGN: Retrospective-matched cohort study using a population-based administrative database. SETTING: Manitoba, Canada. PARTICIPANTS: A total of 49,439 ICU patients admitted between 2000 and 2012 were compared with two control groups (hospitalized: n = 146,968 and general population: n = 141,937), matched on age (± 2 yr), sex, region of residence, and hospitalization year. INTERVENTION: None. MEASUREMENTS AND MAIN RESULTS: Incident mental disorders (mood, anxiety, substance use, personality, posttraumatic stress disorder, schizophrenia, and psychotic disorders) not diagnosed during the 5-year period before the index ICU or hospital admission date (including matched general population group), but diagnosed during the subsequent 5-year period. Multivariable survival models adjusted for sociodemographic variables, Charlson comorbidity index, admission diagnostic category, and number of ICU and non-ICU exposures. ICU cohort had a 14.5% (95% CI, 14.0-15.0) and 42.7% (95% CI, 42.0-43.5) age- and sex-standardized incidence of any diagnosed mental disorder at 1 and 5 years post-ICU exposure, respectively. In multivariable analysis, ICU cohort had increased risk of any diagnosed mental disorder at all time points versus the hospitalized cohort (year 5: adjusted hazard ratio, 2.00; 95% CI, 1.80-2.23) and the general population cohort (year 5: adjusted hazard ratio, 3.52; 95% CI, 3.23-3.83). A newly diagnosed mental disorder was associated with younger age, female sex, more recent admitting years, presence of preexisting comorbidities, and repeat ICU admission. CONCLUSIONS: ICU admission is associated with an increased incidence of mood, anxiety, substance use, and personality disorders over a 5-year period.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.032 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".