The Effect of Hemoglobin Correction by Blood Transfusion on Pregnancy Outcomes in Minor and Intermedia Thalassemia Patients: A Single-Blind Controlled Randomized Clinical Trial
Bibliographic record
Abstract
To the best of our knowledge, there is no prospective trial study assessing the management of β-thalassemia by blood transfusion in pregnancy. The aim of this study was to investigate the effect of blood transfusion on maternal and neonatal outcomes in pregnant patients with beta thalassemia minor and intermedia. We did this randomized, single –blind, controlled clinical trial on 36 pregnant women with β thalassemia minor and intermedia at two tertiary hospitals of Imam Khomeini and Shafa in Ahvaz, Iran from January 2016 to July 2016. Patients were randomly assigned to receive either packed cell or not (control group) during pregnancy (ratio 1:1). The main outcomes of interest transfusion times, abortion, preterm delivery, type of delivery (cesarean or vaginal), stillbirth, birth weight, low birth weight, very low birth weight, small for gestational age, low Apgar score (≤7) at 1 and 5 minutes, oligohydramnios, fetal anomalies , and NICU admission. The median of blood transfusion in intervention group during pregnancy was two blood units. The cesarean section rate did not significantly differ between the intervention and control groups (72.2% and 44.4%, respectively, P=0.2). Two infants in intervention group experienced with LBW, one with SGA, one with low Apgar score, two with oligohydramnios, and one with NICU admission, while none in control group experienced these complications. The mean birth weight of infants in intervention group was significantly lower than control group (P value 0.002). The comparison between two groups showed that the adverse maternal and neonatal outcomes, especially low birth weight and preterm delivery were higher in intervention group.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".