Serum Lipid Concentrations in Patients with Comorbid Generalized Anxiety Disorder and Major Depressive Disorder
Bibliographic record
Abstract
OBJECTIVE: To examine the lipid levels in a sample of patients with comorbid generalized anxiety disorder (GAD) and major depressive disorder (MDD). METHODS: Serum lipid concentrations were examined in 40 patients with both GAD and MDD, in 27 patients with MDD only, in 26 patients with GAD only, and in 24 healthy control subjects. RESULTS: All mean serum cholesterol concentrations are presented in Table 1. The mean serum total cholesterol concentration in patients with both GAD and MDD was significantly higher than in MDD-only patients, GAD-only patients, and control subjects. The triglyceride concentration was also significantly higher in patients with both GAD and MDD than in MDD-only patients, GAD-only patients, and control subjects. Patients with both GAD and MDD had a lower mean high-density lipoprotein cholesterol (HDL-C) concentration than did patients with GAD only and control subjects. The serum concentration of low-density lipoprotein cholesterol (LDL-C) was higher in patients with both GAD and MDD than in patients with MDD only and GAD only and healthy control subjects. CONCLUSIONS: Our findings indicate that the patients with both GAD and MDD have increased serum cholesterol, triglyceride, and LDL-C and reduced HDL-C levels. These patients may have a greater risk of mortality from coronary artery disease (CAD) than do patients with either depression or anxiety disorder.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".