Multiple Pain Complaints in Patients With Major Depressive Disorder
Why this work is in the frame
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Bibliographic record
Abstract
OBJECTIVE: To characterize the co-existence of multiple pain-related complaints in patients enrolled in a series of pharmaceutical company drug trials for the treatment of Major Depressive Disorder (MDD). METHOD: Pooled 'blinded' data from 2191 patients enrolled in randomized, multicenter, double-blind placebo-controlled studies for the treatment of MDD were analyzed. Painful symptoms were assessed using the seven pain symptoms subset of the Somatic Symptoms Inventory: 'Headache,' 'Pain in lower back,' 'Neck pain,' 'Pain in joints,' 'Soreness in muscles,' 'Pain in heart or chest,' and 'Pain or cramps in abdomen.' The 17-item Hamilton Depression Rating Scale (HAMD) was used to assess severity of depression. RESULTS: Of those meeting the study entry criteria (total HAMD score >or=15), 25% reported no pain complaints and 18% reported 1 pain compliant; the majority (57%) of patients reported the co-existence of multiple pain-related complaints, with 14%, 12%, 11%, 11%, 7%, and 3% of patients reporting 2, 3, 4, 5, 6 and 7 different pain symptoms, respectively. The number of pain-related symptoms experienced was moderately related to severity of depression (r = 0.35), with the most common pain symptom combinations being among headaches, lower back pain, neck pain, pain in joints, and soreness in muscles. CONCLUSIONS: This study supports pain as a component feature of MDD. The number of comorbid pain-related complaints, which generally increased as a function of depressive severity, should be considered in the diagnosis of depression, planning of treatment strategies, and measurement of treatment outcome.
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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 | 0.000 |
| 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 it