Evaluation of left atrial volume in obesity. How indexation by body surface compares to indexation by height
Bibliographic record
Abstract
Abstract Funding Acknowledgements Type of funding sources: None. Background Left atrial enlargement (LAE) is a risk factor for atrial fibrillation, stroke and heart failure with preserved ejection fraction. Current ASE/EACVI guidelines recommend indexing left atrial volume (LAV) by body surface area (BSA) for LAE grading. However, in overweight patients, this ratio must be interpreted with caution due to a disproportionate increase in BSA. Purpose We have assessed LAE in overweight (OW), obese (OB) and severely obese (SO) patients by indexing LAV by height (Ht) instead of BSA. Methods We retrospectively evaluated LAV in 1246 patients from our echocardiography clinic. We graded LAE by BSA, in patients with a normal body mass index (BMI ≥18.5 and <25 kg/m², n = 422). Afterwards, we established the cut-offs for the LAV/Ht ratio by the receiver operating curve (ROC) method. We reported sensitivity (Se), specificity (Sp), area under ROC curve (AUC) and Youden’s index (Yi). Finally, we applied the LAV/Ht ratio to OW (BMI ≥25 and <30 kg/m², n = 467), OB (BMI ≥30 and <35 kg/m², n = 235) and SO (BMI ≥35 kg/m², n = 122) patients. Results There were no differences in Ht between groups. As expected, the weight (63.2 ± 8.8, 77.4 ± 9.6, 91.7 ± 11.5 and 110.4 ± 17.3 kg) and BSA were significantly different in between groups. The cut-offs for the LAV/Ht ratio were ≥35 ml/m (Se 96.3%, Sp 97.3%, AUC 0.997, Yi 0.94), ≥42 ml/m (Se 100%, Sp 96.7%, AUC 0.996, Yi 0.97) and ≥48 ml/m (Se 94.3%, Sp 97.0%, AUC 0.954, Yi 0.94) for mild, moderate and severe LAE, respectively. The table shows LAV and LAE grading according to BMI group. When applying the LAV/Ht ratio, the LAE grade increased in 29.8% of OW, 48.5% of OB and 66.4% of SO patients. Conclusion(s): LAV is significantly increased in OW, OB, and SO patients. In this population, the LAV/BSA ratio significantly underestimates the degree of LAE. The LAV/Ht ratio allows an accurate categorization of LAV, leading to a significant reclassification of LAE. Normal Weight Overweight Obese Severely Obese LAV (ml) ¶ 58.3 ± 26.4 63.5 ± 24.0 69.3 ± 25.7 76.4 ± 25.1 LAV/BSA (ml/m2) 33.9 ± 14.2 33.8 ± 12.1 34.3 ± 11.9 35.3 ± 10.7 Normal / Mild 64.5 / 15.4% 63.2 / 19.3% 64.3 / 16.2% 54.1 / 23.8% Moderate / Severe 7.6 / 12.6% 6.9 / 10.7% 8.9 / 10.6% 10.7 / 11.5% LAV/Ht (ml/m) 34.7 ± 15.0 37.6 ± 13.6 41.0 ± 14.6 45.9 ± 14.4 Normal / Mild – 50.3 /20.1% 39.1 / 25.1% 21.3 / 23.0% Moderate / Severe – 13.9 / 15.6% 13.2 / 22.6% 18.9 / 36.9% ¶ ANOVA between BMI groups: <0.0001; Comparison between LAE grading by BSA or Ht: OW χ²=22.4, p = 0.0001; OB χ²=30.8, p < 0.0001; SO χ²=36.5, p = 0.0001
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.010 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".