Association between pain intensity and cognitive function in primary headache
Bibliographic record
Abstract
Background : Patients suffering from primary headaches such as migraine, tension-type headache, and cluster headache frequently report cognitive problems, particularly with attention and memory. The aim of this study was to see if there was a link between pain intensity and cognitive function in people who had primary headaches. Methods : This cross-sectional study included 69 primary headache patients (37 migraines, 27 tension-type headaches and 5 cluster headaches; age range 18–80 year). Migraine, tension-type headache and cluster headache diagnosis were determined according to the International Classification of Headache Disorders 3 rd edition beta version (ICHD-3 beta) diagnostic criteria. All eligible subjects underwent cognitive function examination using Montreal Cognitive Assessment Indonesian version (MoCA-INA), Trail Making test A (TMT-A), Trail Making test B (TMT-B), Trail Making test C (TMT-C), Forward Digit Span and Backward Digit Span. The intensity of pain was assessed using Numeric Rating Scale (NRS). Results : There were 69 primary headache patients included in this study, 52 (75.4%) patients had abnormal MoCA-INA, 52(75.4%) patients had abnormal Forward Digit Span and 48(69.6%) patients had abnormal Backward Digit Span. There was significant correlation between pain intensity and cognitive function in migraine, TTH and cluster headaches patients. The MoCA-INA, Forward Digit Span and Backward Digit Span had negative correlations with pain intensity, whereas TMT A-time, TMT A-error, TMT B-time and TMT B-error had positive correlation. Conclusion : There were significant associations between pain intensity of and cognitive function in primary headaches with p<0.05. It is suggested that the more severe pain intensity, the more impair of cognitive function.
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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 | 0.001 | 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".