Tuberculosis Following In Vitro Fertilization: A Systematic Review of Maternal and Newborn Outcomes
Bibliographic record
Abstract
Tuberculosis (TB) in pregnancies conceived via in vitro fertilization (IVF) presents unique diagnostic and management challenges, especially in TB-endemic regions. This systematic review synthesizes evidence on maternal and neonatal TB outcomes after IVF. We conducted a systematic review of case reports, case series, and cohort studies, following PRISMA 2020 guidelines. Databases searched included PubMed, Scopus, Embase, and Google Scholar. Quality assessment was performed using Murad's framework and the Newcastle-Ottawa Scale. Seventy-three IVF pregnancies complicated by maternal TB were analyzed. Median maternal age was 32 years; 63.0% had no prior TB history. TB was diagnosed during pregnancy (56.2%) or postpartum (38.4%). Miliary TB (38.4%) and genital TB (27.4%) were most common; central nervous system (CNS) TB occurred in 13.7%. Microbiological confirmation was achieved in 38.4%. Anti-TB therapy was administered to 79.5%; 8.2% had drug-resistant TB. Neonatal TB manifestations included congenital TB (39.7%), miliary TB (34.2%), and CNS TB (15.1%). Of 55 live births, 28 infants survived, 12 died neonatally, and outcomes were missing for 15; there were 18 pregnancy losses. Most mothers recovered, some had residual deficits, and three deaths occurred. Seven cohort studies from China reported earlier TB onset in IVF pregnancies (11-19 weeks' gestation), higher incidence of miliary and CNS TB, and poor fetal outcomes, including >80% pregnancy terminations or losses, in comparison with natural conceptions. TB after IVF is often undiagnosed before conception and carries high fetal risks. Routine TB screening before IVF is essential in endemic areas. Early diagnosis and maternal-neonatal management can improve outcomes.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 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) | 0.000 | 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".