Impact of COVID-19 on Group B Streptococcus Colonization Prevalence And Pregnancy Outcomes: A Single-Center Retrospective Study
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
OBJECTIVES: This study aimed to evaluate the impact of COVID-19 on the prevalence of group B Streptococcus (GBS) colonization and to examine whether the pandemic has influenced pregnancy complications among women colonized by GBS. METHODS: A retrospective chart review was conducted on 2,448 pregnant women who received care at the Outaouais Birthing Center between 2016 and 2023. Pre- and post-pandemic onset data were compared for GBS positive and negative women. Primary outcomes included termination due to miscarriage, transfers (pre- and post-32 weeks, perinatal, postnatal and newborn), reasons for transfers and newborns' Apgar scores. The secondary outcomes included gestational age at delivery, delivery type and location, newborn birth weight, vaginal birth after cesarean (VBAC) and feeding type. Demographic data were collected to ensure group comparability. RESULTS: GBS prevalence was similar before (29.43 %) and after (26.59 %) COVID-19 onset (p = 0.06), with a significant spike in 2020 (32.95 %, p = 0.009). An inverse relationship was observed between COVID-19 and newborn transfers in the GBS positive group (p < 0.001). Apgar scores below 7 increased during the pandemic (p = 0.006), and reasons for perinatal transfers differed significantly (p = 0.004). In the GBS negative group, postnatal transfers were negatively correlated with COVID-19 (p < 0.001), and transfer reasons post-32 weeks (p = 0.02), perinatal (p < 0.001), and newborn (p = 0.02) transfers differed significantly. CONCLUSION: COVID-19 did not increase the prevalence of GBS in pregnant women. The rise in postpartum transfers and variations in transfer reasons suggest that the pandemic may have influenced healthcare practices rather than directly increasing GBS-related complications.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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