Clinical Outcomes of COVID-19 Infection in Pregnant and Nonpregnant Women: Results from The Philippine CORONA Study
Bibliographic record
Abstract
OBJECTIVE: Our study determined the association of pregnancy with various clinical outcomes among women with COVID-19 infection. METHODS: We conducted a retrospective, cohort, subgroup analysis of the Philippine CORONA Study datasets comparing the clinical/neurological manifestations and outcomes of pregnant and nonpregnant women admitted in 37 Philippine hospitals for COVID-19 infection. RESULTS: We included 2448 women in the analyses (322 pregnant and 2.126 nonpregnant). Logistic regression models showed that crude odds ratio (OR) for mortality (OR 0.26 [95% CI 0.11, 0.66]), respiratory failure [OR 0.37 [95% CI 0.17, 0.80]), need for intensive care (OR 0.39 [95% CI 0.19, 0.80]), and prolonged length of hospital stay (OR 1.73 [95% CI 1.36, 2.19]) among pregnant women were significant. After adjusting for age, disease severity, and new-onset neurological symptoms, only the length of hospital stay remained significant (adjusted OR 1.99 [95% CI 1.56,2.54]). Cox regression models revealed that the unadjusted hazard ratio (HR) for mortality (HR 0.22 [95% CI 0.09, 0.55]) among pregnant women was statistically significant; however, after adjustment, the HR for mortality became nonsignificant. CONCLUSION: We did not find a significantly increased risk of mortality, respiratory failure, and need for ICU admission in pregnant women compared with nonpregnant women with COVID-19. However, the likelihood of hospital confinement beyond 14 days was twice more likely among pregnant women than nonpregnant women with COVID-19.
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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 | 0.002 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 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".