Predicting Intrauterine Transfusion Interval and Perinatal Outcomes in Alloimmunized Pregnancies: Time-to-Event Survival Analysis
Bibliographic record
Abstract
<b><i>Background:</i></b> The risk factors determining the frequency of intrauterine transfusions (IUTs) for severely affected red blood cell alloimmunized singleton pregnancies are not well known. <b><i>Objective:</i></b> To assess factors associated with IUT frequency and adverse pregnancy outcomes in transfused pregnancies<i>.</i><b><i>Methods:</i></b> Retrospective cohort analysis of 246 consecutive cases between 1991 and 2014. Time-to-event survival analysis for repeated events was used to evaluate risk of subsequent IUT. Multivariable logistic regression assessed odds of a composite adverse pregnancy outcome (intrauterine fetal death, termination of pregnancy, neonatal death, preterm birth &#x3c;34 weeks’ gestation). <b><i>Results:</i></b> Full information was available on<i></i>232 cases (94.3%) and 716 IUTs. Fetal hydrops was associated with increased frequency (hazard ratio [HR] 1.29 [95% CIs 1.15–1.47, <i>p</i> &#x3c; 0.001]) while higher fetal hemoglobin (Hb) pre-IUT (HR) 0.99 (95% CI 0.99–1.00, <i>p</i> = 0.021) and post-IUT (HR 0.99 [95% CI 0.99–1.00] <i>p</i> = 0.042), and higher transfused blood volume (HR 0.98 [95% CI 0.97–0.99] <i>p</i> &#x3c; 0.001) were associated with reduced IUT frequency. Adverse pregnancy outcomes were more likely with lower gestational age (GA) at initial IUT. Antibody type was not associated with IUT frequency or adverse pregnancy outcomes. <b><i>Conclusions:</i></b> Hydrops is associated with increased IUT frequency while lower GA at initial IUT is associated with higher adverse pregnancy outcomes in alloimmunized pregnancies.<i></i>Higher transfused blood volumes, pre- and post-IUT Hb are associated with lower IUT frequency.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.001 | 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".