Risk Factors for the Occurrence of Asymptomatic Brain Lesions in Patients with β-Thalassemia: a Systematic Review and Meta-Analysis
Bibliographic record
Abstract
BACKGROUND: Several factors, including increased platelet aggregation, decreased platelet survival, decreased antithrombotic factors cause a hypercoagulable state in thalassemia patients. This is the first meta-analysis designed to summarize the association of age, splenectomy, gender, and serum ferritin and hemoglobin levels with the occurrence of asymptomatic brain lesions in thalassemia patients using MRI. METHODS: This systematic review and meta-analysis was conducted according to the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) checklist. We searched four major databases and included eight articles for this review. The quality of the included studies was assessed based on the Newcastle-Ottawa Scale checklist. Meta-analysis was performed using STATA 13. Odds ratio (OR) and standardized mean difference (SMD) were considered as effect sizes for comparing the categorical and continuous variables, respectively. RESULTS: The pooled OR for splenectomy in patients with brain lesions compared to those without lesions was 2.25 (95% CI 1.22 - 4.17, p = 0.01). The pooled analysis for SMD of age between patients with/without brain lesions was statistically significant, 0.4 (95% CI 0.07 - 0.73, p = 0.017). The pooled OR for the occurrence of silent brain lesions was not statistically significant in males compared to females, 1.08 (95% CI 0.62 - 1.87, p = 0.784). The pooled SMD of Hb and serum ferritin in positive brain lesions compared to negatives were 0.01 (95% CI -0.28, 0.35, p = 0.939) and 0.03 (95% CI -0.28, 0.22, p = 0.817), respectively, which were not statistically significant. CONCLUSIONS: Older age and splenectomy are risk factors for developing asymptomatic brain lesions in β-thalassemia patients. Physicians should consider a careful assessment of high-risk patients for starting prophylactic treatment.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.010 | 0.002 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".