Prophylactic transfusion for pregnant women with sickle cell disease: a systematic review and meta-analysis
Bibliographic record
Abstract
Pregnancy in women with sickle cell disease is associated with adverse maternal and neonatal outcomes. Studies assessing the effects of prophylactic red blood cell transfusions on these outcomes have drawn inconsistent conclusions. The objective of this systematic review was to assess the effect of prophylactic compared with on-demand red blood cell transfusions on maternal and neonatal outcomes in women with sickle cell disease. A systematic search of several medical literature databases was conducted. Twelve studies involving 1291 participants met inclusion criteria. The studies had moderate to high risk of bias. Meta-analysis demonstrated that prophylactic transfusion was associated with a reduction in maternal mortality (7 studies, 955 participants; odds ratio [OR], 0.23; 95% confidence interval [CI], 0.06-0.91), vaso-occlusive pain episodes (11 studies, 1219 participants; OR, 0.26; 95% CI, 0.09-0.76), pulmonary complications (9 studies, 1019 participants; OR, 0.25; 95% CI, 0.09-0.72), pulmonary embolism (3 studies, 237 participants; OR, 0.07; 95% CI, 0.01-0.41), pyelonephritis (6 studies, 455 participants; OR, 0.19; 95% CI, 0.07-0.51), perinatal mortality (8 studies, 1140 participants; OR, 0.43; 95% CI, 0.19-0.99), neonatal death (5 studies, 374 participants; OR, 0.26; 95% CI, 0.07-0.93), and preterm birth (9 studies, 1123 participants; OR, 0.59; 95% CI, 0.37-0.96). Event rates for most of the results were low. Prophylactic transfusions may positively impact several adverse maternal and neonatal outcomes in women with sickle cell disease; however, the evidence stems from a relatively small number of studies with methodologic limitations. A prospective, multicenter, randomized trial is needed to determine whether the potential benefits balance the risks of prophylactic transfusions.
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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 | 0.007 | 0.021 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.015 | 0.030 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| 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".