Clinical evolution of COVID-19 during pregnancy at different altitudes: a population-based study

  1. Juan Alonso Leon-Abarca
  2. Maria Teresa Peña-Gallardo
  3. Jorge Soliz
  4. Roberto Accinelli

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Abstract

Background

The impact of influenza and various types of coronaviruses (SARS-CoV and MERS-CoV) on pregnancy has been reported. However, the current pandemic caused by SARS-CoV-2 continues to reveal important data for understanding its behavior in pregnant women.

Methods

We analyzed the records of 326,586 non-pregnant women of reproductive age and 7,444 pregnant women with no other risk factor who also had a SARS-CoV-2 RT-PCR result to estimate adjusted prevalence (aP) and adjusted prevalence ratios (aPR) of COVID-19 and its requirement of hospitalization, intubation, ICU admission and case-fatality rates. Adjustment was done through Poisson regressions for age and altitude of residence and birth. Generalized binomial models were used to generate probability plots to display how each outcome varied across ages and altitudes.

Results

Pregnancy was independently associated with a 15% higher probability of COVID-19 (aPR: 1.15), a 116% higher probability of its following admission (aPR: 2.169) and a 127% higher probability of ICU admission (aPR: 2.275). Also, pregnancy was associated with 84.2% higher probability of developing pneumonia (aPR: 1.842) and a 163% higher probability of its following admission (aPR: 2.639). There were no significant differences in COVID-19 case-fatality rates between pregnant and non pregnant women (1.178, 95% CI: 0.68-1.67).

Conclusion

Pregnancy was associated with a higher probability of COVID-19, developing of pneumonia, hospitalization, and ICU admission. Our results also suggest that the risk of COVID-19 and its related outcomes, except for intubation, decrease with altitude.

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  1. ScreenIT

    SciScore for 10.1101/2020.09.14.20193177: (What is this?)

    Please note, not all rigor criteria are appropriate for all manuscripts.

    Table 1: Rigor

    Institutional Review Board Statementnot detected.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variableData sources: We analyzed the records of Mexican women of reproductive age (11) (15-49 years) who were under clinical suspicion of COVID-19 because of a history of cough, fever, headache associated with dyspnea, arthralgia, myalgia, sore throat, runny nose, conjunctivitis or chest pain in the past 7 days.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    The STATA 14.0 software was used for data analysis and p values <0.05 were considered statistically significant.
    STATA
    suggested: (Stata, RRID:SCR_012763)

    Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).

    Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:
    Limitations of the study included that the dataset did not record the trimester of pregnancy, therefore we couldn’t determined the clinical reason for admission to regular hospitalization or ICU or whether the patient was admitted preventively and subsequently worsened their respiratory parameters requiring intubation. Because of this, it remains unclear how SARS-CoV-2 infection in the first trimester affects women and fetal stability across the course of pregnancy, despite that SARS-CoV-2 transplacental transmission has been reported previously (47). Also, pregnant women’s physiology varies across gestational age and might interact with the hypobaric hypoxia seen at high altitudes. In order to isolate the effects of pregnancy, we only included women with no other recorded risk factors in the analysis, so the burden of chronic diseases such as hypertension and obesity remains to be scrutinized.

    Results from TrialIdentifier: No clinical trial numbers were referenced.

    Results from Barzooka: We did not find any issues relating to the usage of bar graphs.

    Results from JetFighter: We did not find any issues relating to colormaps.

    Results from rtransparent:
    • Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
    • Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
    • No protocol registration statement was detected.

    About SciScore

    SciScore is an automated tool that is designed to assist expert reviewers by finding and presenting formulaic information scattered throughout a paper in a standard, easy to digest format. SciScore checks for the presence and correctness of RRIDs (research resource identifiers), and for rigor criteria such as sex and investigator blinding. For details on the theoretical underpinning of rigor criteria and the tools shown here, including references cited, please follow this link.

  2. Version published to 10.1101/2020.09.14.20193177v1 on medRxiv