Pentagastrin-induced hemoconcentration in healthy volunteers and patients with panic disorder: effect of pretreatment with ethinyl estradiol
Bibliographic record
Abstract
Panic disorder has been associated with both an increased risk of coronary events as well as an increased risk of stroke. Hemoconcentration, with both a decrease in plasma volume and an increase in plasma viscosity, is a possible contributor to the risk of acute ischemic events. Our objectives were to demonstrate the process of hemoconcentration in response to induced panic symptoms and to assess the effect of pretreatment with ethinyl estradiol on panic-induced hemoconcentration. Fifteen male patients with panic disorder and 10 male healthy volunteers were included in a double-blind cross-over placebo-controlled design consisting of two injections of pentagastrin following randomized pretreatment with placebo and ethinyl estradiol. Plasma levels of hematocrit and hemoglobin were assessed at baseline and post-injections, and used to calculate an indirect estimation of the change in plasma volume. Pentagastrin-induced panic symptoms were associated with a mean decrease in plasma volume of 4.8% in the placebo pretreatment condition. Pretreatment with ethinyl estradiol attenuated this effect. The acute hemoconcentration observed in relation to pentagastrin-induced panic symptoms may be relevant to the increased risk of stroke and acute coronary events found in patients with panic disorder.
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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 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".