Predictors of the Size of Prosthetic Aortic Valve and In-Hospital Mortality in Aortic Valve Replacement
Bibliographic record
Abstract
PURPOSE: We hypothesized that gender, age, aortic root dimension, blood group and Left Ventricular End Diastolic and Systolic Diameters may have a significant correlation with the size of mechanical valve used. METHODS: We included 48 patients retrospectively who had been operated at a single tertiary hospital. All patients with aortic stenosis or regurgitation were included in the study. Patients who had undergone previous cardiac surgery or concomitant surgical procedures, such as coronary artery bypass grafting, were excluded from the study. RESULTS: The median size of the valves used in males (23mm) and females (21mm) were significantly different (P = 0.001). Size of the valve used was significantly associated with Left Ventricular End Systolic Diameter (LVESD) (r = 0.327, P = 0.007) and aortic root dimension (r = 0.526, P < 0.001). Moreover, significantly higher values of LVESD were observed in the expired patients (P = 0.023). CONCLUSION: This study shows that aortic root dimension and gender may be important predictors for the size of the prosthetic aortic valve used in aortic valve replacement. Our study also concludes that LVESD has significant relationship with in-hospital mortality. However, more long term clinical trials should be conducted to confirm these relationships.
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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 | 0.003 |
| 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 | 0.001 |
| 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".