Prevalence of Cardiovascular Complications in Individuals with Sickle Cell Anemia and Other Hemoglobinopathies: A Systematic Review
Bibliographic record
Abstract
Abstract Background Sickle cell anemia (SCA) is a hereditary disease whose cardiovascular complications are the main cause of death, the same being observed in other hemoglobinopathies. Early identification of these changes can favorably modify the course of the disease. Objective To compare the prevalence of cardiovascular complications between individuals with SCA and individuals with other hemoglobinopathies. Method Following the recommendations of the PRISMA protocol, a systematic literature review was carried out with searches in PubMed/Medline databases, associated with a manual search. Studies that analyzed the prevalence of cardiovascular alterations in hemoglobinopathies (SCA, sickle cell trait, SC hemoglobinopathy, alpha-thalassemia and beta-thalassemia) were included. The methodological quality of the articles was assessed using the Newcastle-Ottawa scale. Results Four studies were selected for analysis, resulting in a sample size of 582 participants: 289 with SCA, 133 with SC hemoglobinopathy, 40 with beta-thalassemia, 100 healthy individuals and none with alpha-thalassemia or sickle cell trait. Dilatation of the cardiac chambers, left and right ventricular hypertrophy, pulmonary hypertension, diastolic dysfunction, mitral regurgitation and tricuspid regurgitation are more prevalent in SCA than in the other hemoglobinopathies considered. Myocardial iron overload is more frequent in thalassemia major than in sickle cell anemia. Systolic function is similar between different hemoglobinopathies. Conclusion There is greater cardiovascular impairment in individuals with SCA than in those with other hemoglobinopathies, reinforcing the necessity for regular cardiovascular follow-up in sickle cell patients.
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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 | 0.006 | 0.032 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.007 |
| Bibliometrics | 0.011 | 0.011 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".