Frequency and outcomes of painful physical symptoms in a naturalistic population with major depressive disorder: an analysis of pooled observational studies focusing on subjects aged 65 years and over
Bibliographic record
Abstract
AIMS: To estimate the frequency of painful physical symptoms (PPS) in elderly subjects (≥ 65 years) with major depressive disorder (MDD) in real-world clinical conditions and to establish whether PPS are associated with poor depression outcomes, including more severe depression and worse health-related quality of life (HRQoL). METHODS: Observational studies of MDD that included assessment of PPS and elderly subjects were screened. Measures of PPS were based on the Somatic Symptom Inventory (SSI) or Visual Analogue Scale (VAS). Data from a variety of depressive symptom severity and HRQoL scales were used. Analysis cohorts were based on age [aged ≥ 65 years (elderly) or < 65 years (younger)] and/or PPS status (presence or absence); five subsets were used to examine specific outcomes in matched elderly subjects. RESULTS: Data from seven studies (representing 26 countries) were collated. Of the 11,477 subjects, 14% were aged ≥ 65 years and 71% were classified as having PPS (PPS+). PPS were more frequent in elderly subjects (74% vs. 70% of younger subjects) and were positively associated with being female and Hispanic, and negatively associated with being East Asian in the elderly. The presence of PPS was associated with more severe clinical symptomatology and comparatively poorer HRQoL in elderly subjects. CONCLUSIONS: PPS, although frequent in younger MDD patients, were slightly more frequent in elderly MDD patients and associated with comparatively poorer clinical and functional outcomes. As elderly patients report somatic symptoms more readily than emotional symptoms, physicians should consider depression in addition to physical causes when PPS are present.
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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 | 0.010 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.005 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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 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".