Left atrial volume index as a predictor of ventricle repolarization abnormalities in adult dialyzed patients
Bibliographic record
Abstract
This study was performed to investigate the relationship between left atrium (LA) volume index (LAVI) and left ventricle electrical activity presumably repolarization in end-stage renal disease patients. Study group was consisted of 120 dialyzed patients divided into two subgroups: 57 (age 50.7 ± 7.1) were on continuous ambulatory peritoneal dialysis (CAPD) and 73 (age 51.6 ± 7.6) were hemodialyzed (HD). All patients were undergoing three-dimensional vectorcardiographic (VCG) monitoring to assess parameters concerning T vector: QRS-T angle, Tel, and Taz. Standard echocardiography was performed to assess: LAmax, LAshort, LAlong. LAVI was calculated due to formula: LAVI = (π/6X [LAmax × LAshort × LAlong])/m2. LAVI in HD as well as in CAPD patients was significantly higher compared with controls (respectively: 36.29 ± 10.92; 36.41 ± 11.06; 20.64 ± 6.77 mL/m2). The calculated cutoff value of LAVI was 36.32 mL/m2. In HD patients, the strong correlations between LAVI and QRS-T angle and Tel were determined (respectively: r = 0.407, P < 0.001 and r = 0.359, P = 0.006). Similarly in CAPD group were significant associations between LAVI and QRS-T angle and Tel (respectively: r = 0.423, P < 0.001 and r = 0.374, P = 0.004). The QRS-T angle, Tel and Taz are independently and markedly associated with LAVI in both HD and CAPD patients. LAVI and VCG indices are higher in both HD and CAPD patients. Correlation between QRS-T angle and LAVI may reflect unfavorable influence on the electrical activity of the heart in dialyzed patients with left ventricle diastolic dysfunction. LAVI cutoff value is useful biomarker for stratification of ventricle repolarization disturbances in those patients.
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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".