Major depressive disorder severity and the frequency of painful physical symptoms: a pooled analysis of observational studies
Bibliographic record
Abstract
OBJECTIVE: This retrospective post-hoc analysis of observational studies assesses the frequency of painful physical symptoms (PPS) in patients with major depressive disorder (MDD) of varied severity as may be seen in clinical practice. METHODS: Observational studies of MDD that collected a clinician-reported measure of depression severity and included assessment of PPS were screened for this individual patient-level analysis. Six observational studies were included that enrolled outpatients with a diagnosis of MDD (assessed using the 17-item Hamilton depression scale, Hospital Anxiety and Depression Scale-Depression, or Inventory of Depressive Symptomatology). Measures of PPS were based on the original study assessment (modified Somatic Symptom Inventory [SSI] and Visual Analogue Scale [VAS]). Patients were divided into analysis cohorts based on the presence or absence of PPS. To model PPS status, odds ratios were calculated from logistic regression for cross-sectional analysis (main analysis) and generalized linear mixed models for longitudinal models (exploratory longitudinal analysis). RESULTS: For the main analysis, four studies (N = 2943, 71.6% female, mean age 45.3 years) were identified. Of 2901 eligible patients, 61.7% were classified as having painful physical symptoms (PPS+). At study entry, 73.1% (957/1309) of patients in the severe category of depression, 56.8% (537/945) of those with moderate depression, and 45.6% (295/647) of those with mild depression were PPS+. The exploratory longitudinal analysis was performed using a subset (N = 2430) from the studies used in the main analysis plus two others (an additional 7984 patients, 6742 of which were modeled). The likelihood of patients that were PPS- at baseline later developing PPS was 5% to 13% greater for patients with increased depression severity (P < 0.001) and the likelihood of PPS+ patients later not having PPS was 9% to 17% less for patients with increased depression severity (P < 0.0001). CONCLUSIONS: Since this is a retrospective aggregate analysis of several observational studies, and due to missing data, care should be taken in the interpretation of these results. Despite the use of adjustment techniques, selection bias and unmeasured confounding may still be an issue for comparative analysis as not all variables were collected for all studies. For patients treated in typical care settings, PPS were associated with depression severity. However, patients with mild and moderate depression also exhibited PPS. Clinicians should be aware that PPS are present, and may warrant treatment, across depression severities.
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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 | 0.031 | 0.046 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.018 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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 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".