Impact of Lockdown Measures during COVID-19 Pandemic on Pregnancy and Preterm Birth
Why this work is in the frame
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Bibliographic record
Abstract
OBJECTIVE: The objective of this study is to assess the effect of the lockdown measures during the coronavirus disease 2019 (COVID-19) pandemic on pregnancy outcomes of women who were not affected by severe acute respiratory syndrome coronavirus 2 infection. STUDY DESIGN: We used data from the perinatal health program and neonatal databases to conduct a cohort analysis of pregnancy outcomes during the COVID-19 lockdown in the Calgary region, Canada. Rates of preterm birth were compared between the lockdown period (March 16 to June 15, 2020) and the corresponding pre-COVID period of 2015 to 2019. We also compared maternal and neonatal characteristics of preterm infants admitted to neonatal intensive care units (NICUs) in Calgary between the two periods. FINDINGS: = 0.71). During the lockdown period, the likelihood of multiple births was lower (risk ratio [RR] 0.73, 95% confidence interval [CI]: 0.60-0.88), while gestational hypertension and clinical chorioamnionitis increased (RR 1.24, 95%CI: 1.10-1.40; RR 1.33, 95%CI 1.10-1.61, respectively). CONCLUSION: Observed rates of very preterm and very-low-birth-weight births decreased during the COVID-19 lockdown. Pregnant women who delivered during the lockdown period were diagnosed with gestational hypertension and chorioamnionitis more frequently than mothers in the corresponding pre-COVID period. KEY POINTS: · Lockdown measures to reduce COVID-19 transmission were associated with a lower rate of preterm birth.. · Mental and physical wellbeing of pregnant women were significantly affected by the lockdown measures.. · A comprehensive public health plan to relieve psychosocial stress during pregnancy is required..
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 it