Panic Disorder and Chronic Caffeine Use: A Case-control Study
Bibliographic record
Abstract
BACKGROUND: Acute administration of caffeine produces panic attacks in most Panic Disorder (PD) patients, but little is known about chronic caffeine use in these patients. OBJECTIVE: To assess caffeine use in patients with PD and to ascertain if caffeine consumption is associated with sociodemographic or clinical features. METHODS: 65 adults with PD and 66 healthy controls were included in the current study. Their caffeine intake within the previous week was quantified with a questionnaire and compared. Harmful caffeine use was defined as consumption above 400 mg/day of caffeine. We tested for correlations between caffeine intake, demographic and clinical features. RESULTS: Patients consumed significantly more caffeine than controls (P < 0.001). 14% (N = 9) of the PD patients made harmful use of caffeine. The use of caffeine-containing medications was observed in 40% (N = 26) of the PD patients and 6% (N = 4) of controls. Consumption of energy drinks was observed in 11% (N = 7) of PD patients and in none of the healthy subjects. Patients reported sleeping significantly less than controls (P < 0.001). In PD patients, caffeine consumption was not correlated with the presence of panic attacks or comorbidity with depression. The use of benzodiazepines or sedative medications was not correlated with caffeine intake. CONCLUSION: High caffeine consumption in PD patients could be explained by the development of tolerance with regular use of this substance. Subtypes of sensitive and non-sensitive PD patients could also explain why some of these patients are able to tolerate high doses of caffeine.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".