Multimorbidity in affective disorders: Impact on length of stay
Bibliographic record
Abstract
Background Multimorbidity (MM) refers to the coexistence of two or more chronic diseases in the same individual; it encompasses medical comorbidity (MC) and psychiatric comorbidity (PC). Hypothesis: MM is prevalent amongst in-patients suffering from affective disorders (AD) and also impacted on length of stay. Aims To determine the prevalence of MM and its impact on duration of hospitalization in AD admissions. Method This cross-sectional study was conducted using secondary data taken from discharge records of 1056 adults admitted for AD to a Quebec-based facility, between 2006 and 2014. Distribution of AD cases: 47% depression, 53% bipolar disorders. Results The prevalence rate of MM: 85%. PC was present in 70% of sample whereas MC was present in 62%. The median number of comorbid illnesses was 2.7 for each study subject. The rate of MM was not related to age or gender. Metabolic syndrome (54%), cardiovascular diseases and chronic pain syndrome (17%) were the most prevalent MC in both depressed and bipolar populations. Personality disorder (65%) was highest in the depression population, whereas substance misuse (55%) was the most prevalent PC in the bipolar subjects. A longer length of stay was correlated with MM. However, a logistic regression analysis indicated that duration of hospitalization was only correlated with MC. Conclusions The observation that MM is the norm, even in this relatively young population with AD. The results confirmed that MC prolongs hospital stay. These findings advocate strongly for integrated management of psychiatric and physical health problems in clinical practice. Disclosure of interest The authors have not supplied their declaration of competing interest.
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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 | 0.000 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".