Evidence map›Paper›PMID 32342041›Full record

ArticleAmerican journal of obstetrics & gynecology MFM2020

Forecasting the impact of coronavirus disease during delivery hospitalization: an aid for resource utilization.

Manesha Putra, Malavika Kesavan, Kerri Brackney, David N Hackney, Kimberlyn M Roosa

Abstract read
In one paragraph

Article in American journal of obstetrics & gynecology MFM, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

9 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Covid-19 pandemic and pregnancy.The journal of obstetrics and gynaecology research · 2020
    Article
  8. Review
  9. Informed Consent for Emergency Obstetric Care During COVID-19 Pandemic.Journal of obstetrics and gynaecology of India · 2020
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Manesha PutraDivision of Maternal-Fetal Medicine, Department of Reproductive Biology, MetroHealth Medical Center, Cleveland, OH.
Malavika KesavanDepartment of Reproductive Biology, Case Western Reserve University School of Medicine, Cleveland, OH.
Kerri BrackneyDivision of Maternal-Fetal Medicine, Department of Reproductive Biology, MetroHealth Medical Center, Cleveland, OH.
David N HackneyDivision of Maternal-Fetal Medicine, Department of Obstetrics and Gynecology, University Hospitals Cleveland Medical Center, Cleveland, OH.
Kimberlyn M RoosaDepartment of Population Health Sciences, School of Public Health, Georgia State University, Atlanta, GA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: The ongoing coronavirus disease 2019 pandemic has severely affected the United States. During infectious disease outbreaks, forecasting models are often developed to inform resource utilization. Pregnancy and delivery pose unique challenges, given the altered maternal immune system and the fact that most American women choose to deliver in the hospital setting. Objective: This study aimed to forecast the first pandemic wave of coronavirus disease 2019 in the general population and the incidence of severe, critical, and fatal coronavirus disease 2019 cases during delivery hospitalization in the United States. Study Design: We used a phenomenological model to forecast the incidence of the first wave of coronavirus disease 2019 in the United States. Incidence data from March 1, 2020, to April 14, 2020, were used to calibrate the generalized logistic growth model. Subsequently, Monte Carlo simulation was performed for each week from March 1, 2020, to estimate the incidence of coronavirus disease 2019 for delivery hospitalizations during the first pandemic wave using the available data estimate. Results: From March 1, 2020, our model forecasted a total of 860,475 cases of coronavirus disease 2019 in the general population across the United States for the first pandemic wave. The cumulative incidence of coronavirus disease 2019 during delivery hospitalization is anticipated to be 16,601 (95% confidence interval, 9711-23,491) cases, 3308 (95% confidence interval, 1755-4861) cases of which are expected to be severe, 681 (95% confidence interval, 1324-1038) critical, and 52 (95% confidence interval, 23-81) fatal. Assuming similar baseline maternal mortality rate as the year 2018, we projected an increase in maternal mortality rate in the United States to at least 18.7 (95% confidence interval, 18.0-19.5) deaths per 100,000 live births as a direct result of coronavirus disease 2019. Conclusion: Coronavirus disease 2019 in pregnant women is expected to severely affect obstetrical care. From March 1, 2020, we forecast 3308 severe and 681 critical cases with about 52 coronavirus disease 2019-related maternal mortalities during delivery hospitalization for the first pandemic wave in the United States. These results are significant for informing counseling and resource allocation.

Indexed as

COVID-19Delivery, ObstetricHealth Care RationingHospitalizationObstetricsPregnancy Complications, InfectiousResource AllocationAdultFemaleForecastingHumansIncidenceMaternal MortalityMonte Carlo MethodPatient Acceptance of Health CarePregnancycoronavirusCOVID-19forecastingprediction model

Identifiers

PMID32342041
PMCPMC7182514

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.