Modified gorlin equation for the diagnosis of mixed aortic valve pathology.
Bibliographic record
Abstract
BACKGROUND AND AIM OF THE STUDY: The accuracy of the Gorlin equation when applied to mixed valve pathology has not been investigated. An in-vitro study was performed to determine how a range of valve regurgitations and stenoses affects the Gorlin aortic valve area. METHODS: Various combinations of stenosis and regurgitation were simulated by placement of constricting orifices and minimal blockage reflux tubes within a 29-mm prosthetic pericardial valve. The orifice areas ranged from 0.7 cm2 to 1.75 cm2, and regurgitant fraction (RF) ranged from 0 to 0.35. Twenty-eight tests were performed at 70 beats/min, cardiac output of 5 l/min and systole 33-36% of the cycle. The mean pressure drops across the valve were adjusted to a value appropriate to blood density. Peripheral resistance was set to give a mean value of 1,537 dyn.s.cm(-5). RESULTS: The Gorlin area varied up to 0.55 cm2 from the geometric orifice area over the range of regurgitant fractions and stenoses. To improve the Gorlin equation, an amended mean volumetric forward flow rate was obtained by multiplying the cardiac output in the equation by the factor (1 - RF)(-1), to reconcile the equation for valvular regurgitation. The area predicted by the modified equation differed by <0.15 cm2 from the non-regurgitant valve geometric orifice area over the range of regurgitation and stenoses simulated. CONCLUSION: The study supports the validity of the Gorlin equation predicting pure aortic valve stenosis (areas <1.3 cm2); however, the equation overestimates the severity of stenoses when regurgitation is present. A modified equation is proposed, which includes regurgitant fraction. The new equation improves the calculation of valve geometric area in the presence of regurgitation and may be useful in cardiac catheterization laboratories where mixed aortic valve pathology is being evaluated.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.006 | 0.024 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.003 |
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".