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Record W3143063178 · doi:10.1080/14767058.2021.1902498

Maternal and perinatal outcomes in pregnant women with confirmed severe and mild COVID-19 at one large maternity hospital in Chile

2021· article· en· W3143063178 on OpenAlexaff
M. Haye, Giorgia Cartes, Jorge Gutiérrez, Paz Ahumada, Bernardo J. Krause, Mario Merialdi, Rogelio González

Bibliographic record

VenueThe Journal of Maternal-Fetal & Neonatal Medicine · 2021
Typearticle
Languageen
FieldMedicine
TopicCOVID-19 Impact on Reproduction
Canadian institutionsCentre for Global Health Research
Fundersnot available
KeywordsMedicinePregnancyObstetricsMaternal deathProspective cohort studyMechanical ventilationPediatricsCoronavirus disease 2019 (COVID-19)Presentation (obstetrics)Observational studyMaternal morbidityDiseaseEmergency medicineInternal medicinePopulationInfectious disease (medical specialty)

Abstract

fetched live from OpenAlex

OBJECTIVE AND METHODS: We conducted a prospective observational cohort study in 458 pregnant and puerperal women, with confirmed COVID-19 at Hospital San Jose, Santiago, Chile, to determine the impact of COVID-19 on pregnancy and confirm safety and feasibility of a management protocol based on clinical presentation of the disease. RESULTS: 25.5% (117/458) of women were severe and 74.4% (341/458) mild presentation. Three percent (9/341) of mild presentations required a subsequent hospitalization. Overall, 26/458 women (5.6%) were admitted to ICU, and 13/458 (2.8%) required mechanical ventilation. One maternal death occurred at 49-days postpartum. Severe presentation, infection above 24 weeks, and comorbidities were associated with an adverse maternal outcome. Of total deliveries, 16.5% (36/217) were <37 weeks. Perinatal mortality was 6/226 (2.7%), mostly due to the fetal component. CONCLUSIONS: A quarter of the women had severe COVID-19 that, combined with occurrence of disease in the second half of pregnancy, resulted in substantial maternal compromise. Perinatal morbidity and mortality in women with severe disease were high and warrant consideration. Outpatient management was safe for mild cases.

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.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.023
Threshold uncertainty score0.860

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.015
GPT teacher head0.287
Teacher spread0.272 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations16
Published2021
Admission routes1
Has abstractyes

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