Post total splenectomy outcome in thalassemia patients
Bibliographic record
Abstract
Introduction: Splenectomy in thalassemia patient is indicated in the transfusion-dependent patient when hypersplenism increases blood transfusion requirement, prevents adequate control of body iron with chelation therapy and increased risk for infection.Method: This study was retrospective study aims to evaluate the outcome of splenectomy in pediatric thalassemia patients and its related factor. A total 34 thalassemia patient with post total splenectomy patients was included in this study. Result: Mean age was 20.7 ± 6.5 years old with majority mild malnutrition (61.8%) and the majority of spleen size Schaffner 6-7 (73.5%). The duration between thalassemia diagnosis and total splenectomy was 6-7 years. Statistical analysis showed significant decreased of mean blood transfusion volume from 4691.4 cc per year to 3764.2 cc per year (p = 0.048), decreased mean blood transfusion volume from 219.6 cc per Kg Body Weight (BW) per year to 125.5 cc per Kg BW per year (p<0.001) and decreased of blood transfusion frequency from 12-14 times per year to 6-8 times per year (p<0.001). There is only one case subcutaneous emphysema as complication after splenectomy.Conclusion: Overall, this study showed total splenectomy improve the outcome of thalassemia with hypersplenism with low rate of complication.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".