Anaesthesia and infection control in cesarean section of pregnant women with coronavirus disease 2019 (COVID-19)

  1. LinLi Yue
  2. Lefei Han
  3. Qiannan Li
  4. Min Zhong
  5. Jun Wang
  6. Zhenzhen Wan
  7. Caijuan Chu
  8. Yi Zeng
  9. Min Peng
  10. Lin Yang
  11. Na Li

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Abstract

Background

The coronavirus disease 2019 (COVID-19) first emerged in Wuhan, China, and soon caused an ongoing pandemic globally. In this study we conducted a retrospective study to evaluate the safety and efficacy of combined spinal-epidural anaesthesia (CSEA) and infection control measures on perinatal care quality of 30 pregnant women with confirmed and suspected COVID-19.

Methods

Individual demographic data, clinical outcomes, laboratory investigations of pregnant women and their newborns were collected from electronic medical records of the Maternal and Children Health Hospital of Hubei Province, during January 24 to February 29, 2020. Anaesthesia and surgery results were compared between pregnant women with confirmed and suspected COVID-19 infection.

Results

Using CSEA in cesarean section was effective and safe for pregnant women with confirmed and suspected COVID-19 infection. Administration of dezocine and morphine was effective as postoperative analgesia, and well tolerated in COVID-19 patients. The assessment of surgery outcomes also showed similar results in both confirmed and suspected cases. No respiratory failure nor distress were found in the mothers with confirmed COVID-19 infection and their neonates. None of these patients experienced severe obstetric complications related to anaesthesia and surgeries. No COVID-19 infection was reported in the neonates born to the mothers with confirmed COVID-19 infection and healthcare workers in these operations.

Conclusions

In cesarean section for pregnant women with COVID-19 infection, CSEA was safe and efficient in achieving satisfactory obstetrical anaesthesia and postoperative analgesia. No cross-infection occurred in the HCWs working in these operations.

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  1. ScreenIT

    SciScore for 10.1101/2020.03.23.20040394: (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 variablePatients: Medical records of pregnant women who were admitted into our hospital for scheduled or emergency cesarean section were retrospectively retrieved during the period of January 24 – February 29, 2020.

    Table 2: Resources

    No key resources detected.

    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:
    Our study has a few limitations. First, we have a small sample size of 34 pregnant women, although this is the largest sample for pregnant women with COVID-19 infection to date. Second, all patients were in the third trimester. All of them had relatively mild infection and most did not show any respiratory symptoms on admission. Hence, it is not clear that our findings can also be applied to patients with moderate and severe infection, since they might require endotracheal intubation or other airway management during surgery. Last but not least, this is a one-center retrospective study at the epicenter of COVID outbreaks, so the results might be generalized to other settings.

    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 10.1101/2020.03.23.20040394v1 on medRxiv