A Narrative Review of the Epidemiology of Congenital Syphilis in the United States From 1980 to 2019
Bibliographic record
Abstract
OBJECTIVES: Congenital syphilis (CS) is the result of antepartum transmission from mother to fetus of the spirochete Treponema pallidum. Although preventable through timely screening and treatment, the incidence of CS in the United States is increasing. This review describes the epidemiological trends in CS in the United States from 1980 to 2019 and characteristics of mothers of infants with CS. METHODS: We performed a narrative review of epidemiological studies of CS following Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines for reporting of observational studies in epidemiology. Quality and bias of included studies were assessed using the Newcastle-Ottawa Scale. Studies that described the demographics and characteristics of pregnant women with syphilis or who delivered an infant with CS in the United States were identified from PubMed and Embase. RESULTS: We identified a total of 2771 studies, of which 309 were selected for further review and 27 were included in the final analysis. Substance use during pregnancy was a risk factor for CS in 16 studies. Maternal cocaine use was described in 11 of the 16 studies, 10 of which were published between the years 1980 and 1999. No prenatal care was a risk factor for CS in 17 studies. Evidence of inadequate syphilis testing (i.e., no maternal screen, first screen after the first trimester, or no repeat screen in third trimester) or treatment (i.e., no treatment, treatment <30 days before delivery, or nonpenicillin treatment) was significantly associated with CS in 13 studies. Finally, higher rates of CS were reported among African American women in 11 studies. CONCLUSIONS: Infection with and antepartum transmission of syphilis disproportionately affect certain subgroups of women. Women who report substance use during pregnancy are more likely to give birth to an infant with CS. No prenatal care and evidence of inadequate syphilis testing and treatment during pregnancy are also significantly associated with giving birth to an infant with CS. Finally, cases of CS disproportionately affect African American women. Addressing the CS epidemic will require identification and targeted allocation of resources to communities at elevated risk for syphilis, removal of barriers to prenatal care, and ensuring timely treatment and adequate partner notification of identified cases.
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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 | 0.004 | 0.023 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.005 |
| Bibliometrics | 0.017 | 0.016 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".