Low Body Mass Index Is Associated with a Positive Response during a Head‐Up Tilt Test
Bibliographic record
Abstract
BACKGROUND: To describe the association between body mass index (BMI) and a positive response during a head-up tilt test (HUT) in patients referred for an investigation of syncope. METHODS: Observational study of patients referred for the diagnostic evaluation of syncope. Patients were divided into four groups according to their BMI: <18.5 kg/m(2), 18.5-24.9 kg/m(2), 25-29.9 kg/m(2), and > 30 kg/m(2). RESULTS: A total of 419 patients were evaluated. The mean age was 43 ± 22 years, and 62% were female. The prevalence of a positive tilt test was different between groups when stratified by BMI (P = 0.01), with a higher proportion of patients with positive tests among those with BMI <18.5 kg/m(2) compared with other groups (P = 0.05). Multivariate analysis also showed that underweight patients had a 3.9 times higher risk for a positive HUT response (P = 0.01); additionally, the use of contraceptive drugs was associated with a protective effect during HUT (odds ratio: 0.35, confidence interval: 0.19-0.45, P = 0.001). CONCLUSION: In our sample, changes in BMI are associated with a positive response for HUT, and oral contraceptives seemed to protect against this response. Further studies are needed with larger numbers of patients to corroborate this finding.
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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 | 0.000 | 0.004 |
| 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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".