Residual Fatigue in Unipolar and Bipolar Depression: A Systematic Review
Bibliographic record
Abstract
BACKGROUND: Residual fatigue is a common and debilitating symptom in patients with unipolar and bipolar depression, even after achieving partial or full remission. It significantly impacts patients' quality of life and increases the risk of relapse. This systematic review aims to evaluate the prevalence and effectiveness of therapeutic options for residual fatigue in individuals with unipolar major depressive disorder (MDD) and bipolar disorder (BD). METHODS: A comprehensive search was conducted in the PubMed, SCOPUS, and Web of Science databases up to September 2024. The protocol for this systematic review was registered in PROSPERO. The search strategy included terms related to depression and residual fatigue. Studies were included if they provided data on adult patients diagnosed with MDD or BD, and if they measured the prevalence or treatment of residual fatigue. Risk of bias was assessed using the Cochrane Risk of Bias tool for randomized controlled trials (RCTs) and the Newcastle-Ottawa Scale for non-randomized studies. RESULTS: Twenty studies were included in the review. The vast majority reported on MDD, and single papers investigated BD. Residual fatigue was reported by up to 83% of patients, and moderate to severe residual fatigue affected a smaller percentage. Pharmacological treatments, such as modafinil and to a lesser extent atomoxetine, demonstrated short-term reductions in residual fatigue. CONCLUSION: Residual fatigue remains a significant challenge in the treatment of depression, persisting in a large portion of patients despite remission. Pharmacological interventions like modafinil appear promising, but more research is needed, especially in BD. Standardized assessment tools and longer-term studies are essential to better understand and treat residual fatigue. TRIAL REGISTRATION: PROSPERO identifier: CRD42024543087.
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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 | 0.005 | 0.021 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.007 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".