P758 Should ECHO measurements be indexed to ideal BSA or actual BSA?
Bibliographic record
Abstract
Abstract INTRODUCTION A patient with aortic stenosis with an AVA of 1.22 cm2 who stands 5’ 6" and weighs 145 lb has a BSA of 1.76m2 (AV area index = 0.69 cm2/m2). If the same patient weighs 200 lbs, the BSA increases to 2.09 m2 (AV area index 0.58 cm2/m2). Their calculated AV area index therefore changes from the moderate range to the severe range. PURPOSE To determine from our ECHO database the effect the current obesity epidemic has on all ECHO variables that are indexed to BSA. METHODS Our ECHO database was searched for all patients with the required data variables, gender, age, height (cm)and body weight (kg) were required. Duplicate patients with multiple ECHO studies were removed, only the first ECHO entry being included. Obvious data entry errors were removed (e.g. height 1866 cm, or weight 8.6 kg). Ideal weight was calculated using the Devine formula, ideal weight = Constant + 2.3x[height in inches-60], where constant= 50kg in males and 45.5kg in females. Body surface area in m2 was calculated = [√(height in cm x weight in Kg)/3600]. The paired t-test was used to determine differences between means. A p value of <0.05 was considered significant. RESULTS There were 47,761 ECHO studies entered into the database, of which 46,605 (98%) had all the required fields completed. Once duplicates were removed (-15,903) and erroneous data deleted (-158, 0.33%), 30,536 remained. There were 16,160 females aged 58.7 ± 19.2 years, with a mean height of 161.7 ± 7.2cm and 14,376 males aged 59.8 ± 19.2 years, with a mean height of 176.7 ± 7.6 cm. There were statistically significant differences in both men and women between actual and ideal weight and actual and ideal BSA, see Table 1. CONLUSIONS. For all ECHO measurements where the value is frequently indexed a decision needs to be made to either use the actual BSA or the ideal BSA. It may be more practical to use the ideal BSA which will remain consistent throughout follow up. Using our data any such measurement for females could be multiplied by 1.16 and for males 1.11 (i.e. actual BSA/ideal BSA). It is disappointing to find that, on average, females are 20 kilograms and males 18 kilograms above their ideal weight. Table 1. Weight females (kg) Weight males (kg) BSA females (m2) BSA males (m2) Number. 16,160 14,376 16,160 14,376 Actual. 73.2 ± 18.9 89.1 ± 19.3 1.80 ± 0.24 2.08 ± 0.24 Ideal. 53.4 ± 6.5 71.4 ± 6.9 1.55 ± 0.13 1.87 ± 0.3 P value. <0.0001 <0.0001 <0.0001 <0.0001 BSA = Body surface area.
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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 | 0.002 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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".