The impact of socioeconomic factors on the efficiency of voluntary toxoplasmosis screening during pregnancy: a population-based study
Bibliographic record
Abstract
BACKGROUND: Congenital toxoplasmosis is associated with severe complications. German state health insurance covers rubella, but not toxoplasmosis, immunity screening. We analysed the effect of socioeconomic factors on the efficiency of private toxoplasmosis screening during pregnancy. METHODS: Toxoplasmosis and rubella screening data (n = 5402 mothers) were collected within the population-based Survey of Neonates in Pomerania (SNiP). RESULTS: At the first-trimester screening, 34.4 % (88.1 %) of expecting mothers were immune to toxoplasmosis (rubella). Susceptibility for toxoplasmosis (rubella) was observed in 39.6 % (8.9 %) and 25.8 % (2.95 %) were not tested. Data on a 2(nd) screening were available in a subgroup of women with negative immunity showing less than 45 % participation rate. Active toxoplasmosis (no rubella) infection was observed in 0.3 % (n = 17) of pregnant women. A multiple logistic regression model (AIC = 719.67; AUC = 0.725) revealed that the likelihood of participating in a second toxoplasmosis screening increased among women with a good level of education and a steady partnership and decreased with paternal unemployment and the absence of breastfeeding. The highest probability of non-participation in toxoplasmosis screening was found among women with temporal burden and family responsibilities. A cost-benefit analysis showed that covering general screening for toxoplasmosis with health insurance saved costs. CONCLUSION: Toxoplasmosis carried a substantial risk of infection during pregnancy. Although increased socioeconomic status was positively associated with the participation in toxoplasmosis screening, this was not the case when pregnant women had strong temporal burden and family responsibilities. This data supports the need for toxoplasmosis screening among pregnant women as a general healthcare benefit covered by insurance.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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".