Premenopausal Singaporean Women Suffering from Major Depressive Disorder Treated with Selective Serotonin Reuptake Inhibitors Had Similar Bone Mineral Density as Compared with Healthy Controls
Bibliographic record
Abstract
The association between selective serotonin reuptake inhibitor (SSRI) treatment and lower bone mineral density (BMD) remains controversial, and further research is required. This study aimed to compare the BMD, levels of bone formation and bone metabolism markers in medicated premenopausal Singaporean women with major depressive disorder (MDD) and matched healthy controls. We examined 45 women with MDD who received SSRI treatment (mean age: 37.64 ± 7) and 45 healthy controls (mean age: 38.1 ± 9.2). BMD at the lumbar spine, total hip and femoral neck were measured using dual-energy X-ray absorptiometry. We also measured bone formation markers, procollagen type 1 N-terminal propeptide (P1NP) and bone metabolism markers, osteoprotegerin (OPG) and receptor activator of nuclear factor-kappa-Β ligand (RANKL). There were no significant differences in the mean BMD in the lumbar spine (healthy controls: 1.04 ± 0.173 vs. MDD patients: 1.024 ± 0.145, p = 0.617, left hip (healthy controls: 0.823 ± 0.117 vs. MDD patients: 0.861 ± 0.146, p = 0.181) and right hip (healthy controls: 0.843 ± 0.117 vs. MDD patients: 0.85 ± 0.135, p = 0.784) between healthy controls and medicated patients with MDD. There were no significant differences in median P1NP (healthy controls: 35.9 vs. MDD patients: 37.3, p = 0.635), OPG (healthy controls: 2.6 vs. MDD patients: 2.7, p = 0.545), RANKL (healthy controls: 23.4 vs. MDD patients: 2178.93, p = 0.279) and RANKL/OPG ratio (healthy controls: 4.1 vs. MDD patients: 741.4, p = 0.279) between healthy controls and medicated patients with MDD. Chronic SSRI treatment might not be associated with low BMD in premenopausal Singaporean women who suffered from MDD. This finding may help female patients with MDD make an informed decision when considering the risks and benefits of SSRI treatment.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".