Supplementary Material for: Cognitive Impairments in Patients with GHB Use Disorder Predict Relapse in GHB Use
Bibliographic record
Abstract
<b><i>Background:</i></b> The recreational use of gamma hydroxybutyrate (GHB) is associated with frequent overdoses, coma and the risk of developing GHB use disorder (GUD). Several studies suggest negative effects of GHB use or related comas on cognition. Since relapse rates are high in GUD and cognitive impairment has been associated with relapse in other substance use disorders, we aimed to (1) investigate the prevalence of cognitive impairment before and after detoxification, (2) analyse the relationship between GHB use, comas, and cognitive impairment, and (3) explore the association between cognitive impairment and relapse after detoxification in GUD patients. <b><i>Methods:</i></b> In these secondary analyses of a prospective cohort study, a consecutive series of patients with GUD (<i>n</i> = 103) admitted for detoxification were recruited at six addiction care facilities in the Netherlands. The Montreal Cognitive Assessment (MoCA) was used to screen for cognitive impairments before and after detoxification. The follow-up duration for the assessment of relapse in GHB use was 3 months. <b><i>Results:</i></b> A substantial number of patients with GUD screened positive for cognitive impairment before (56.3%) and after (30.6%) detoxification. Impairment on the MoCA memory domain was most frequent (58.8%). Cognitive impairment was not related to the severity of GUD or number of GHB-induced comas. Logistic regression analysis showed that only the memory score independently predicted relapse. <b><i>Discussion:</i></b> Cognitive impairment seems highly prevalent among patients with GUD, possibly related to the risk of relapse. The absence of a relationship between the severity of GUD, level of GHB use, the number of GHB-induced comas, and cognitive impairment suggest that other factors may also contribute to the observed cognitive impairment.
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 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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.448 | 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".