PS-C30-12: IMPACT OF SARS-COV-2 INFECTION TO RISK AND SEVERITY OF HYPERTENSION IN PREGNANCY AND ITS OUTCOME TO THE NEW BORN
Bibliographic record
Abstract
Objective: To determine relationship of SARS-CoV-2 infection to the risk and severity of preeclampsia, as well as its impact on newborns. Design and method: We performed a systematic search in databases (PubMed, ScienceDirect, ProQuest, and Cochrane Library) for studies examining impact of SARS-CoV-2 infection on pregnancy. Included studies were evaluated for risk of bias based on the Newcastle Ottawa Score. A meta-analysis was conducted using the data extracted from each study. Review Manager (RevMan) 5.4 was utilized to compute the summary of odds ratios (OR), mean differences (MD), and 95% confidence intervals (CI) for the outcomes. Our outcomes of interest are preeclampsia, preeclampsia with severe features, eclampsia, fetal distress and still birth. The other outcomes are preterm birth (< 37 week), instrumental labor, sectio caesaria and birth defect. Results: We identified twenty two observational studies involving 1,025,048 pregnancy patients. Based on the analysis, SARS-CoV-2 infection in pregnancy significantly increased the risk of preeclampsia [OR 2.01(95% CI 1.59–2.53; p < 0.00001; I2 = 82%)], and the severity was based on the high prevalence of preeclampsia with severe features [OR 3.04(95% CI 1.19–7.78; p = 0.02; I2 = 91%)] and eclampsia [OR 17.73(95% CI 13.83–22.72;p < 0.00001; I2 = 0%)]. Poor outcome in newborns in terms of incidence of preterm birth [OR 1.65(95% CI 1.54–1.76; p < 0.00001; I2 = 86%)], fetal distress [OR 19.18(95% CI 17.14–21.45; p < 0.00001; I2 = 99%)] and still birth [OR 2.12(95% CI 1.74–2.59; p < 0.00001; I2 = 0%)], were also significantly associated with SARS-CoV-2 infection. Conclusions: SARS-CoV-2 infection during pregnancy increases the risk and severity of preeclampsia and gives a poor outcome in newborn.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".