LEFT VENTRICULAR GLOBAL LONGITUDINAL STRAIN IDENTIFIES EARLY IMPAIRMENT IN MYOCARDIAL BLOOD FLOW IN ARTERIAL HYPERTENSION
Bibliographic record
Abstract
Objective: Arterial hypertension causes cardiac functional and structural alterations. In hypertensive patients without flow-limiting epicardial coronary artery disease, we investigated the possible relationship between positron emission tomography myocardial blood flow (MBF) and echocardiographic parameters of left ventricular (LV) performance, including global longitudinal strain (GLS). Design and method: Fifteen hypertensive patients (mean age 65 + 9 years, 9 F) without flow-limiting epicardial coronary artery disease underwent echocardiography and cardiac 13NH3 positron emission tomography (13NH3 PET) with assessment of myocardial coronary flow reserve (CFR). A positive 13NH3 PET was defined as a ratio of resting myocardial blood flow (MBF/mass) and stress MBF/mass lower than 2. Results: No significant differences of demographic and structural echocardiographic parameters were observed between patients with positive (n=6) vs negative (n=9) 13NH3 PET. In all patients CFR was significantly related to GLS (-0,67, p=0.02), at univariate analysis, and remained statistically significant after adjustment for age and sex (-0,54, p=0.05). Conclusions: In hypertensive patients without flow-limiting epicardial coronary artery disease, GLS may indicate the presence of early LV dysfunction and impairment of CFR.
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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".