Outcomes of infectious syphilis in pregnant patients and maternal factors associated with congenital syphilis diagnosis, Alberta, 2017–2020
Bibliographic record
Abstract
Background: Congenital syphilis (CS) is a significant public health challenge, requiring early diagnosis and treatment to improve infant outcomes. The aim of this study is to describe public health outcomes of infectious syphilis cases among pregnant patients and factors associated with a CS diagnosis for their infant. Methods: We conducted a retrospective review of demographic and clinical characteristics of infectious syphilis cases diagnosed during pregnancy and resulting infant outcomes in Alberta from 2017 to 2020 from the provincial communicable disease database. Adequate maternal treatment was defined as receiving at least one dose of Benzathine penicillin G-LA 2.4 million units IM at least 28 days before delivery. Univariate and multivariate analysis was performed to determine factors associated with CS diagnosis using SPSS version 25. Results: A total of 374 cases of infectious syphilis were diagnosed in pregnancy, with two patients being diagnosed twice in a single pregnancy. The majority (79.1%; n=296) of women had a live birth, followed by therapeutic abortion (9.4%; n=35), stillbirth (7.5%; n=28) and spontaneous abortion (4.0%; n=15). Infant records (n=265) were available for review (n=117 CS cases and 148 non-cases). Correlates associated with CS were screening time in third trimester (adjusted odds ratio [AOR] 8.4, 95% confidence interval [CI], 2.9–24.6) and fewer than 28 days before delivery (AOR 8.1, 1.4–47.8 [vs. first and second trimester] and inadequate treatment (AOR 86.1, CI, 15.9–466.5). Among the CS cases, 23.1% (n=27) were stillborn compared with one (0.7%) stillbirth in the non-CS infants (p<0.001). Conclusion: The early identification and treatment of syphilis in pregnancy is crucial to preventing poor infant outcomes.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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 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".