Alertness in patients with treatment-resistant depression: interface between sleep medicine and psychiatry—review article
Bibliographic record
Abstract
Abstract Background Treatment-resistant depression (TRD) is a significant problem in clinical practice and reason for the lack of functional recovery among depressed patients. Sleep disturbances and poor alertness are common residual symptoms. Main body of the abstract Many patients with refractory depression experience residual symptoms, such as insomnia, daytime sleepiness, and poor alertness. This is a literature review and we searched the electronic databases, including PubMed, the Cochrane database, Ovid MEDLINE, PsycINFO, and Google Scholar of all studies published between 2000 and 2020. The literature on the relationship between sleep quality and alertness in a patient with depression is very sparse. One possible reason could be the difficulty in defining alertness as a mental function. Alertness itself has been described as a state of responsivity to both interoceptive and external stimuli. Subjective and objective measures of alertness, daytime somnolence, and quality of sleep are presented. Adjunctive treatment with stimulant medications (methylphenidate, amphetamine, modafinil) to the standard antidepressant medications might be warranted in patients in patients with daytime sleepiness, decreased alertness, fatigue, and poor work performance. Short conclusion Patients with treatment-resistant depression usually suffer from poor quality of sleep and decreased alertness. Stimulant medications may help with alertness, daily functioning, and work performance.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".