The impact of fatigue and energy on work functioning and impairment in patients with major depressive disorder treated with desvenlafaxine
Bibliographic record
Abstract
Fatigue and low energy are cardinal symptoms of major depressive disorder (MDD) that have an impact on work functioning. Antidepressants with noradrenergic activity have been hypothesized to improve symptoms of fatigue and low energy. We examined the impact of these symptoms on work functioning in patients with MDD treated with the serotonin and noradrenaline reuptake inhibitor, desvenlafaxine. A secondary analysis was carried out from a study of employed adult outpatients (n=35) with MDD and subjective cognitive complaints treated with desvenlafaxine 50-100 mg/day for 8 weeks. Multiple regression analyses modeled improvement in work functioning measures (Lam Employment Absence and Productivity Scale, Health and Work Performance Questionnaire, Sheehan Disability Scale) with measures of fatigue (Patient-Reported Outcomes Measurement Information System Fatigue scale and 20-item Hopkins Symptom Check List Energy scale). Patients showed a significant improvement in Montgomery-Åsberg Depression Rating Scale scores as well as in fatigue and work functioning measures following treatment. Fatigue measures were significantly associated with improvement in some (Lam Employment Absence and Productivity Scale, Sheehan Disability Scale), but not all (Health and Work Performance Questionnaire) work functioning measures, independent of improvement in overall depressive symptoms. The limitations of this study include the small sample size and the lack of a placebo or a comparison group. Fatigue and low energy are important symptoms that are associated with occupational impairment in MDD. Treatments that improve these symptoms are likely to improve work functioning.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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) | 0.000 | 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".