A personalized approach to the treatment of chronic tension headache and comorbid mental disorders
Bibliographic record
Abstract
Objective. To compare the effectiveness of a standard and personalized approach to the management of patients with chronic tension headache (CTH) and concomitant mental disorders. Material and methods. The study included 97 CTH patients, randomized into two groups. Patients in Group 1 (main) (n=45) received a personalized approach, including psychiatrist consulting and psychopharmacotherapy, according to their comorbid psychopathological symptoms. The comparison group patients (n=52) received standard care with neurologist consultation and follow-up. The study protocol involved 6 months of therapy and follow-up with efficacy assessment at two points — 3 and 6 months after the start of treatment. The pain severity was assessed using VAS and McGill questionnaire. The severity of subjective pain, the patient’s focus on his disease, and the pain catastrophizing were assessed using the pain catastrophization scale (PCS). Insomnia symptoms were objectively assessed using the insomnia severity index (ISI) questionnaire. The Hamilton scale was used to assess the severity of depression. Results. A personalized approach involving a psychiatrist in the management of patients with CTH and concomitant mental disorders is significantly more effective in the short term and retains certain advantages over the standard of care six months after the start of treatment. Conclusion. The results of the study indicate the need for a wider use of a personalized approach in the clinical practice for CTH patients.
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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 | 0.001 |
| 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) | 0.002 | 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".