Cardiometabolic and traditional cardiovascular risk factors and their potential impact on macrovascular and microvascular function: Preliminary data
Bibliographic record
Abstract
We studied the relationship between cardiovascular status (CV) and risk factor numbers, macrovascular (flow mediated dilatation: FMD) and microvascular function using near-infrared spectroscopy (NIRS) in adults with different CV status. Seventy adults with different CV status (27 controls, 18 metabolic syndrome (MetS) and 25 coronary heart disease (CHD) patients) underwent a 5-min forearm arterial occlusion in supine position. High-resolution ultrasound examination of the brachial artery was performed during 1 minute at rest and 45 to 120 seconds after cuff release. Oxy, de-oxy and total hemoglobin signals (O2Hb, HHb and tHb) were measured continuously with NIRS on brachio-radialis muscle. FMD was reduced in CHD patients (P<0.05) compared to controls. Max. amplitude of O2Hb and Hmax of tHb were reduced (P<0.05) in MetS patients vs. controls. Post-deflation area under the curve (A.U.C) of O2Hb was lower in CHD (P<0.01) patients vs. controls and MetS patients. Independent predictors of microvascular function (A.U.C of O2Hb) were abdominal obesity and LDL-cholesterol whereas macrovascular function (FMD) was predicted by CV status. Only A.U.C of O2Hb related to CV risk numbers whereas FMD was not. Although macro and microvascular function were impaired in MetS and CHD patients, microvascular function was more strongly related to CV risk factors.
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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) | 0.002 | 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".