Screening Rheumatic Heart Disease in 1530 New Caledonian Adolescents
Bibliographic record
Abstract
BACKGROUND In New Caledonia, a South Pacific archipelago whose inhabitants comprise Melanesians, Europeans/whites, Wallisians, Futunans, Polynesians, and Asians, the prevalence of rheumatic heart disease (RHD) is 0.9% to 1% at ages 9 and 10. It could be higher at the age of 16, but this remains to be verified. METHODS AND RESULTS A total of 1530 Melanesian, Métis, white, Wallisian, Futunan, Polynesian, and Asian adolescents benefited from a transthoracic echocardiogram. Definite or borderline RHD, nonrheumatic valve lesions, congenital heart defects, family and personal history of acute rheumatic fever, and socioeconomic factors were collected. The prevalence of cardiac abnormalities was 8.1%, made up of 4.1% RHD including 2.4% definite and 1.7% borderline RHD, 1.7% nonrheumatic valve lesions, and 2.3% congenital anomalies. In whites and Asians, there were no cases of RHD. RHD was higher in the Wallisian, Futunan, and Polynesian group (7.6%) when compared with Melanesians (5.3%) and Métis (2.9%). The number of nonrheumatic valve lesions was not statistically different in the different ethnicities. The prevalence of RHD was higher in adolescents with a personal history of acute rheumatic fever, in those living in overcrowded conditions, and in those whose parents were unemployed or had low-income occupations, such as the farmers or manual workers. CONCLUSIONS RHD was 4 times higher in adolescents at age 16 than at ages 9 and 10 (4.1% versus 0.9%-1%). No cases of RHD were observed in whites and Asians. The determining factors were history of acute rheumatic fever and socioeconomic factors.
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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 | 0.001 | 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".