Bipolar Disorder and Diabetes Mellitus: Epidemiology, Etiology, and Treatment Implications
Bibliographic record
Abstract
INTRODUCTION: Bipolar disorder (BD) is a highly prevalent and disabling condition with significant mortality risk from suicide and other unnatural causes. This ignominious description is alongside recent observations that the majority of excess deaths in BD are secondary to medical comorbidity. The medical burden in BD is associated with a clustering of risk factors (e.g., obesity, smoking, unhealthy dietary habits) and inadequate utilization of preventative and primary healthcare. Diabetes mellitus (DM) is also a prevalent multifactorial disease which imparts substantial illness burden. Preliminary investigations indicate that patients who suffer from BD with comorbid DM have a more severe course and outcome, lower quality of life, higher prevalence of medical comorbidity and higher cost of illness. METHODS: We conducted a MedLine search of all English-language articles 1966-2004 using the key words: bipolar disorder, major depressive disorder, diabetes mellitus, glucose metabolism, mortality, overweight, obesity, body mass index. The search was supplemented with manual review of relevant references. Priority was given to randomized controlled data, when unavailable; studies of sufficient sample size are presented. RESULTS: Subpopulations of BD patients should be considered at high risk for DM. The prevalence of DM in BD may be three times greater than in the general population. CONCLUSIONS: Bipolar disorder populations may be an at-risk group for glucose metabolic abnormalities. Opportunistic screening and vigilance for clinical presentations suggestive of DM is encouraged.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.001 |
| 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 | 0.001 | 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".