Which Hemodynamic Parameter Predicts Nitroglycerin‐Potentiated Head‐Up Tilt Test Response?
Bibliographic record
Abstract
BACKGROUND: The aim of our study was to identify the early hemodynamic predictors of head-up tilt test (HUTT) outcome in healthy patients with recurrent unexplained syncope. METHODS AND RESULTS: The study involved 95 patients (mean age 38 ± 15; 42 male) who were referred for the evaluation of the syncopal episodes from October 2012 to May 2013. According to the nitroglycerin-potentiated diagnostic tilt test response, the study population was divided into two groups: HUTT+ Group (61 patients, mean age 37 ± 10; 27 male) and HUTT- Group (34 patients, mean age 38 ± 11; 15 male) with no tilt-induced syncope. Finger arterial blood pressure (BP) was recorded during tilt testing. Left ventricular stroke volume (SV), cardiac output (CO), and total peripheral resistance (TPR) were computed from the pressure pulsations. After nitroglycerin administration, the HUTT+ Group showed a significant increase in heart rate (92.0 ± 7.3 beats/min vs 68.9 ± 8.7 beats/min, P < 0.0001), with well-maintained systolic BP (111.6 ± 14.1 mm Hg vs 108.8 ± 11.5 mm Hg; P = 0.332) and diastolic BP (66.1 ± 8.5 mm Hg vs 63.1 ± 6.9 mm Hg; P = 0.0913); a significant decrease in SV (53.9 ± 8.0 mL vs 78.6 ± 8.2 mL; P < 0.0001) and CO (4.0 ± 0.5 L/min vs 5.8 ± 1.0 L/min; P < 0.001), and a significant increase in TPR (1.3 ± 0.3 U vs 0.9 ± 0.2 U, P < 0.0011). We tested three hemodynamic parameters (SV, CO, and TPR) as predictors of positive tilt test response with receiver-operating characteristic curve analysis. CONCLUSIONS: Our results show that, 2 minutes after nitroglycerin administration, a statistically significant decrease of SV values (<67 mL) strongly predicts (area under the curve, 0.985; P < 0.0001) the HUTT-positive response in healthy patients with recurrent unexplained syncope.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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) | 0.001 | 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".