Impact of sickle cell anaemia on cardiac chamber size in the paediatric population
Bibliographic record
Abstract
Purpose Sickle cell disease is known to cause various degrees of vasculopathy, including impact on heart function. The aims of this single-centre, retrospective study were to assess cardiac chamber size and function and the relationship with haematological indices such as haemoglobin, aspartate aminotransferase, reticulocytosis and bilirubin, lactate dehydrogenase in sickle cell disease. METHODS: Right ventricle and left ventricle diastolic diameters, left ventricle mass estimate, left ventricle shortening fraction, myocardial performance index, and an index of myocardial relaxation (E/E') were calculated and correlated with haematological parameters. RESULTS: A total of 110 patients (65% haemoglobin SS, 29% haemoglobin SC) were studied at a mean age of 12.14±5.26 years. Right ventricle dilatation and left ventricle dilatation were present in 61.5 and 42.9%, respectively. Left ventricle mass was abnormal in 21.9%; all patients had normal myocardial performance index, 31.4% had abnormal E/E', and left ventricle shortening fraction was low in 38.1%. Cardiac dilatation was best correlated with haemoglobin, aspartate aminotransferase, reticulocytosis and bilirubin. Best subset regression analysis yielded significant additional prediction for right ventricle or left ventricle dilatation with haemoglobin, bilirubin, and lactate dehydrogenase. Abnormal E/E' was solely predictable with haemoglobin level. Hydroxyurea-treated patients had improved diastolic function. CONCLUSION: Right ventricle dilatation was more prevalent than left ventricle dilatation. The long-term consequences of right ventricular dilatation, clinical consequences, and association with pulmonary vasculopathy need to be further determined.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".