Left ventricular remodelling in rheumatic heart disease – trends over time and implications for follow-up in childhood
Bibliographic record
Abstract
Abstract Background Rheumatic heart disease (RHD) is the most common form of acquired heart disease worldwide. In RHD, volume loading from mitral regurgitation leads to left ventricular (LV) dilatation, increased wall stress, and ultimately LV dysfunction. Improved understanding of LV dynamics may contribute to refined timing of intervention. We aimed to characterize and compare left ventricular remodelling between rheumatic heart disease (RHD) severity groups by way of serial echocardiographic assessment of volumes and function in children. Methods Children with RHD referred to Perth Children’s Hospital (formally Princess Margaret Hospital) (1987–2020) were reviewed. Patients with longitudinal pre-operative echocardiograms at diagnosis, approximately 12 months and at most recent follow-up, were included and stratified into RHD severity groups. Left ventricular (LV) echocardiographic parameters were assessed. Adjusted linear mixed effect models were used to compare interval changes. Results 146 patients (median age 10 years, IQR 6–14 years) with available longitudinal echocardiograms were analysed. Eighty-five (58.2%) patients had mild, 33 (22.6%) moderate and 28 (19.2%) severe RHD at diagnosis. Mean duration of follow-up was 4.6 years from the initial diagnosis. Severe RHD patients had significantly increased end-systolic volumes (ESV) and end-diastolic volumes (EDV) compared to mild/moderate groups at diagnosis (severe versus mild EDV mean difference 27.05 ml/m 2 , p < 0.001, severe versus moderate EDV mean difference 14.95 ml/m 2 , p = 0.006). Mild and moderate groups experienced no significant progression of changes in volume measures. In severe RHD, LV dilatation worsened over time. All groups had preserved cardiac function. Conclusions In mild and moderate RHD, the lack of progression of valvular regurgitation and ventricular dimensions suggest a stable longer-term course. Significant LV remodelling occurred at baseline in severe RHD with progression of LV dilatation over time. LV function was preserved across all groups. Our findings may guide clinicians in deciding the frequency and timing of follow-up and may be of clinical utility during further reiterations of the Australia and New Zealand RHD Guidelines.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".