Depression is not the only cause of cognitive impairment in chronic migraine
Bibliographic record
Abstract
Background. Patients with the chronic migraine frequently present with memory and attention complaints. However, the prevalence and phenotype of such impairment in chronic migraine have not been studied.Objective – to evaluate the prevalence of the objective cognitive deficit in patients with chronic migraine and factors underlying its etiology. Materials and methods. We recruited 62 subjects with chronic migraine and 36 genderand age-matched controls with low-frequency episodic migraine (not more, then 4 headache days per month) aged 18–59. All patients filled in the Hospital Anxiety and Depression Scale (HADS) and Sheehan Disability Scale. Cognitive function was assessed with the Montreal Cognitive Assessment (MoCA), Digital Symbol Substitution Test (DSST), Rey Auditory Verbal Learning Test (RAVLT), and the Perceived Deficits Questionnaire (PDQ-20).Results. In this study 58 % of patients with chronic migraine complained of memory loss. Cognitive impairment was also found with PDQ-20. Objectively, we found a significant decrease in 90-second DSST results and RAVLT total recall and learning rate. In 40 % of subjects with chronic migraine scored lower than 26 points on MoCA. Patients with chronic migraine more frequently had lower DSST rates as compared to episodic migraine (odds ratio 5.07 (95 % confidence interval – 1.59–16.17); p = 0.003). Depression and anxiety did not correlate with performance on cognitive tests. Chronic migraine (frequent headache) and longer headache history, but not depression, anxiety or medication overuse were independent predictors of cognitive impairment.Conclusion. Subjective and objective cognitive deficits are prevalent in the chronic migraine population. Most often memory and attention are impaired. Longer headache history and presence of chronic migraine are independent risk factors for cognitive impairment in patients with chronic migraine.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 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) | 0.003 | 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".