Frequency and Clinical Associating Factors of Valvular Heart Disease in Asymptomatic Korean Adults
Bibliographic record
Abstract
Limited information is available on the prevalence and clinical determinants of valvular heart disease (VHD) in apparently healthy people. This study sought to assess the frequency and clinical associating factors of aortic stenosis (AS), aortic regurgitation (AR), mitral stenosis (MS), mitral regurgitation (MR), tricuspid regurgitation (TR) in asymptomatic individuals with health check-up examination. We included 23,254 subjects ≥50 years of age who underwent a health check-up examination with transthoracic echocardiography (TTE) between 2012 and 2016 in a single tertiary-care hospital in Korea. Among a total of 23,254 subjects, 15,358 men (66.0%) and 7,896 women (34.0%) underwent TTE. Newly identified (predominantly mild) VHD was detected in 9.4% of subjects. The most common VHD were TR (4.6%), AR (3.0%) and MR (2.4%). Clinically significant (more than moderate) VHD was identified in 176 subjects (0.8%). Age ≥75 years was associated with all clinically significant VHD, and female gender was associated with AR, MS and TR. Korea has been very active in the health check-up examination including echocardiography. We find that VHD in apparently healthy people is not uncommon than believed; all VHD except MS were more frequent in elderly over 75 years of age in a large population-based study.
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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 | 0.001 | 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 | 0.000 |
| 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".