Primary headache types in adult epilepsy patients
Bibliographic record
Abstract
Abstract Background Headache is among the most common comorbidities in epilepsy. This study examined the distribution of different primary headache disorders in a large cohort of patients with diagnosed epilepsy. Headache types were analysed with regard to gender, type of epilepsy and antiepileptic drugs (AEDs). Methods In this prospective single-centre study, 500 patients with epilepsy (250 female, mean age: 45.52 ± 17.26 years) were evaluated with regards to primary headache types using a validated German headache questionnaire categorizing for migraine (MIG), tension-type headache (TTH) or trigeminal autonomic cephalalgias (TAC), their combinations and unclassifiable headache. Data regarding type of epilepsy, seizure-associated headache, AED treatment and seizure freedom were collected. Results Of 500 patients with epilepsy, 163 (32.6%) patients (108 female and 55 male) reported suffering from headaches at least 1 day per month. MIG (without aura, with aura) and TTH were the most frequent headache type (MIG 33.1%, TTH 33.1%). Female epilepsy patients reported headaches significantly more often than male patients ( x 2 = 8.20, p = 0.0042). In contrast, the type of epilepsy did not significantly affect headache distribution. Of 163 patients with headache, 66 (40.5%) patients reported seizure-associated headache and AEDs were used by 157 patients. Of importance, patients with AED monotherapy suffered from MIG less often when compared to patients on polytherapy ( x 2 = 4.79, p = 0.028). Conclusion MIG and TTH are the most common headache types in epilepsy patients and headache is more frequent among female epilepsy patients. Monotherapy in AEDs might have a beneficial effect on the frequency of headache compared to polytherapy.
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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 | 0.012 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 0.001 |
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".