Determinants of substance use patterns in patients with narcolepsy type 1: A multi-center comparative cross-sectional study
Bibliographic record
Abstract
OBJECTIVES: In this multi-center cross-sectional study, we compared substance use patterns (SUPs) between patients with narcolepsy type 1 (NT1) and controls, and investigated, among patients, factors associated with the consumption of the main psychoactive substances. METHODS: Adult patients with NT1 and controls completed questionnaires about tobacco, alcohol, and cannabis use patterns. Unadjusted bivariable then multivariate analyses (adjusted for sex, age, education, family status, and depression) were performed to compare SUPs between controls and patients, and to explore socio-demographic, psycho-behavioral, and clinical determinants of consumptions. RESULTS: We included 235 patients (63.8 % women, 36.4 ± 14.7 years) and 166 controls (69.9 % women, 40.3 ± 14.4 years). Substances co-consumptions were frequent in both groups. Patients with NT1 were more frequently current smokers (32.3 % vs. 20.1 %, p < 0.01) or e-cigarettes users (12.1 % vs 2.4 %, p < 0.001) than controls, while no difference was observed for cannabis use and alcohol misuse. Only the increased likelihood of vaping remained significant in adjusted analysis. Among NT1 patients, smoking was associated with disrupted nighttime sleep (OR[95%CI] = 2.28[1.02-5.12], p < 0.05) and less obesity (OR = 0.24[0.09-0.59], p < 0.05). Alcohol misuse was associated with sleep paralysis (OR = 2.11[1.13-3.91], p < 0.05) and treatments (modafinil: OR = 2.14[1.15-4.01], p < 0.05; sodium oxybate: OR = 0.41[0.17-0.97], p < 0.05). Tobacco and cannabis consumptions were associated with lower physical activity (OR = 0.46 [0.24-0.87], p < 0.05 and OR = 0.25[0.10-0.66], p < 0.01). Alcohol misuse and cannabis use were associated with rule breaking behaviors (OR = 5.89[1.61-21.60], p < 0.05 and OR = 8.52[1.79-40.48], p = 0.01). CONCLUSION: Patients with NT1 do not seem less vulnerable to psychoactive substance use/misuse. Consumptions patterns are associated with multiple dimensions of the disease including sleep-related symptoms, comorbidities, treatments, and psycho-behavioral factors.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".