Myocardial Performance Index in Neurocardiogenic Syncope Patients
Bibliographic record
Abstract
BACKGROUND: Many syncopes resulting from neural reflexes in various conditions are called neurocardiogenic syncope (NCS). We aimed to investigate the presence of left ventricular (LV) myocardial performance index (MPI) in patients with NCS, which was diagnosed with head-up tilt table test (HUTT), and the accurateness of the test in order to use it as a method in patients with NCS. Assuming the MPI as a potential cause of syncope, we assessed the Tei index with non-invasive tissue Doppler echocardiography method. METHODS: Consecutive outpatients with a history of recurrent unexplained syncope underwent HUTT. Twenty-nine HUTT (+) patients (24 female and five male, mean age: 30 ± 15 years) as the study group and HUTT (-) 23 healthy patients (six female and 17 male, mean age: 34 ± 16 years) as the control group were included into the study. Conventional and tissue Doppler echocardiography was performed to both groups. The MPI was determined by using PW Doppler. Measurements of Doppler time intervals, according to Tei index ((isovolumic contraction time + isovolumic relaxation time)/ejection time) is calculated as (a - b/b), where "a" is the interval between cessation and onset of the mitral inflow, and "b" is the ejection time (ET) at the LV outflow. RESULTS: When comparing the groups in terms of MPI and ET, there was significant difference between groups. Patients with NCS had significantly longer ET and lower MPI value than control group (284 ± 24 ms vs. 260 ± 24 ms, P < 0.001, respectively and 0.44 ± 0.7 vs. 0.52 ± 0.8, P < 0.001, respectively). There was no significant difference in ejection fraction between groups. CONCLUSION: In the present study, LV MPI value decreases in patients with NCS.
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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 | 0.001 | 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".