key: cord-0690404-x3ly6tbd
authors: Reale, Sharon C.; Lumbreras‐Marquez, Mario I.; King, Chih H.; Burns, Stacey L.; Fields, Kara G.; Diouf, Khady; Goldfarb, Ilona T.; Ciaranello, Andrea L.; Robinson, Julian N.; Gregory, Katherine E.; Huybrechts, Krista F.; Bateman, Brian T.
title: Patient characteristics associated with SARS‐CoV‐2 infection in parturients admitted for labour and delivery in Massachusetts during the spring 2020 surge: A prospective cohort study
date: 2021-01-26
journal: Paediatr Perinat Epidemiol
DOI: 10.1111/ppe.12743
sha: a863d7925be74a70b19c7a2676ef4803a73a8ae1
doc_id: 690404
cord_uid: x3ly6tbd

BACKGROUND: While studies from large cities affected by coronavirus disease 2019 (COVID‐19) have reported on the prevalence of SARS‐CoV‐2 in the context of universal testing during admission for delivery, the patient demographic, social and clinical factors associated with SARS‐CoV‐2 infection in pregnant women are not fully understood. OBJECTIVE: To evaluate the epidemiological factors associated with severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2) infection in women admitted for labour and delivery, in the context of universal screening at four Boston‐area hospitals. METHODS: In this prospective cohort study, we reviewed the health records of all women admitted for labour and delivery at four hospitals from the largest health system in Massachusetts between 19 April 2020 and 27 June 2020. We calculated the risk of SARS‐CoV‐2 infection, including asymptomatic infection. We calculated associations between SARS‐CoV‐2 infection and demographic and clinical characteristics. RESULTS: A total of 93 patients (3.2%, 95% confidence interval 2.5, 3.8) tested positive for SARS‐CoV‐2 infection on admission for labour and delivery out of 2945 patients included in the analysis; 80 (86.0%) of the patients who tested positive were asymptomatic at the time of testing. Factors associated with SARS‐CoV‐2 infection included the following: younger age, obesity, African American or Hispanic race/ethnicity, residence in heavily affected communities (as measured in cases reported per capita), presence of a household member with known SARS‐CoV‐2 infection, non‐health care essential worker occupation and MassHealth or Medicaid insurance compared to commercial insurance. 93.8% of patients testing positive for SARS‐CoV‐2 on admission had one or more identifiable factors associated with disease acquisition. CONCLUSIONS: In this large sample of deliveries during the height of the surge in infections during the spring of 2020, SARS‐CoV‐2 infection was largely concentrated in patients with distinct demographic characteristics, those largely from disadvantaged communities. Racial disparities seen in pregnancy persist with respect to SARS‐CoV‐2 infection.

With over 1500 documented severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) cases per 100 000 residents at the end of June 2020, 1 

All women who were admitted for labour and delivery at all Mass General Brigham hospitals between 19 April 2020 and 27 June 2020 and tested for SARS-CoV-2 up to 48 hours before admission or upon admission were included in this study.

All SARS-CoV-2 testing was performed by nasopharyngeal reverse transcription-PCR (RT-PCR) using assays approved via United States Food and Drug Administration Emergency Use Authorisation.

Testing of all women admitted for labour and delivery was routine and universal during this time period. For women undergoing planned induction of labour or caesarean delivery, testing may have been performed prior to admission (though within 48 hours of admission). In these instances, the chart was reviewed for tests performed elsewhere. For women presenting in labour or without prior SARS-CoV-2 testing, the testing was performed in-house with rapid (2-to 8-hour turnaround time) RT-PCR testing. Electronic health records were manually reviewed by four co-authors (SR, MLM, CK, SB) for all patients admitted to labour and delivery during the study period to abstract SARS-CoV-2 test results, demographic data and medical variables that may be associated with SARS-CoV-2 infection. 

What are the factors associated with SARS-CoV-2 infection in women admitted for labour and delivery in Massachusetts during the height of the spring surge in 2020?

Epidemiological factors associated with SARS-CoV-2 infection in pregnant women in the United States are not fully understood and may vary by patient demographics, occupation, comorbidities and socio-economic factors.

In the context of universal testing of patients admitted to labour and delivery in a large health care system in Massachusetts at the height of the initial surge, the risk of SARS-CoV-2 infection was concentrated in younger patients, patients of Hispanic ethnicity and African American race, obese patients, non-health care essential workers, Medicaid beneficiaries, women with household contacts with known infection and those residing in highly affected communities.

Racial disparities seen in adverse pregnancy outcomes extended to SARS-CoV-2 infection during this period and mirror trends seen in the Massachusetts general population.

We calculated the risk (and exact 95% confidence interval) of a positive SARS-CoV-2 test up to 48 hours before or on admission to labour and delivery among our study population over the entire study population and by study week. Patients not tested for SARS-CoV-2 were excluded from these analyses, as were patients who tested positive earlier in pregnancy but negative at the time of admission for labour and delivery, given the focus of the study was on the risk of SARS-CoV-2 infection at the time of delivery. We calculated the proportion of women testing positive for SARS-CoV-2 on admission who were asymptomatic, with symptoms defined as fever, chills, cough, dyspnoea, myalgia, headache, anosmia, ageusia, sore throat, rhinorrhea, nausea or vomiting, abdominal pain, or diarrhoea. Patient symptoms were recorded based on nursing intake questionnaires completed on all patients during the pandemic. Occupation Classification System. 18 Occupations were then classified as essential workers vs nonessential workers, with health care workers being a subset of essential workers. Occupations were determined to be essential based on the emergency order enacted by the governor of Massachusetts on 23 March 2020 19 ; those included as essential were as follows: building and grounds cleaning and maintenance occupations, food preparation and serving related occupations, health care practitioners and technical occupations, health care support occupations, installation, maintenance, and repair occupations, military support occupations, protective service occupations, and transportation and material moving occupations. The medical records of all essential workers were manually searched for documentation of whether the patient was working from home or not working. If patients whose job fell into the essential workers category were specifically noted to be working from home or not working for over 2 weeks prior to delivery, they were not included in the essential worker category.

The purpose of this study was to assess the association between patient factors (including maternal age category, delivery BMI category, race/ethnicity, gestational diabetes, pre-existing diabetes, asthma, smoking, opioid use disorder, COVID-19 rate percentile among Massachusetts town category, household member with known SARS-CoV-2 infection, number of children at home grouped as none or 1 or more, occupation category and insurance type) and infection. Lasso is a penalised regression method that constrains the sum of the magnitude of regression model coefficients such that covariates that do not improve prediction of the outcome are shrunk to zero, thus creating a more parsimonious model. 24 The degree of penalisation, lambda, was selected as the largest value that maintained tenfold cross-validated prediction error within 1 standard error of the minimum. 23 Predictors entered into the lasso model included all factors assessed for univariate association with SARS-CoV-2 infection.

Missing data on maternal race (0.3%), occupation category (7.4%) and delivery BMI category (0.1%) were addressed using multiple imputation by fully conditional specification, assuming that data were missing at random given observed data. 25 BCa bootstrap CIs were calculated in the presence of multiply imputed data using a modified version of the "Boot MI" approach. 26 First, 3000 bootstrap resamples were drawn from the dataset with missing values.

Second, in each bootstrap resample race and occupation category were imputed by the discriminant function method and delivery BMI category was imputed using logistic regression, producing 20 complete datasets per bootstrap resample. Imputation models included all predictors assessed for univariate association with SARS-CoV-2 infection, as well as delivery hospital and SARS-CoV-2 test result.

Third, prevalence and odds ratio estimates were obtained from each of the 20 complete datasets and combined using Rubin's rules to produce one point estimate per bootstrap sample. 27 Fourth, these 3000 point estimates were used to calculate 95% BCa bootstrap CI for each prevalence and odds ratio estimate. For the lasso logistic regression model, pooled beta coefficients were obtained by averaging across imputations.

Statistical analyses were performed using SAS software version 9.4 (SAS Institute Inc, Cary, NC, USA) and R software version 3.6.1 (R Foundation for Statistical Computing, Vienna, Austria).

Mass General Brigham Institutional Review Board approval was obtained for this study, and the need for informed consent was waived.

There were 2945 deliveries at Mass General Brigham hospitals during the study time period. Five patients who were not tested for SARS-CoV-2 and 18 who tested positive earlier in pregnancy but negative at the time of admission for labour and delivery were excluded from all analyses; 63 patients residing outside Massachusetts were excluded from any analysis assessing COVID-19 rate by zip code (Figure 1 ).

Ninety-three out of 2945 women tested positive for SARS-CoV-2 on admission; the risk of SARS-CoV-2 infection of patients tested in our sample was 3.2% (95% CI 2.5, 3.8). In Figure 2 , new positive tests per capita in our study are compared to age-specific statewide data from the Massachusetts Department of Public Health by study week. Table 1 (Table S1 ). Among women testing positive on admission for labour and delivery, 86.0% were asymptomatic (Table 4 ). 

Strengths of our study include the high rate (>99%) rate of SARS-CoV-2 testing on admission, with a large study population of nearly 3000 patients included in a 10-week time period. Furthermore, manual chart review of all patients allowed for robust examination of detailed demographic and clinical data. 

The Compared to data from our study, the documented rates of new SARS-CoV-2 infection per capita in the state of Massachusetts for the people aged 20-39 were multi-fold lower, 1 likely due to a substantial undercounting of disease burden given widespread asymptomatic disease among routinely tested labour and delivery patients, in contrast to the limited testing available for the general population.

Most SARS-CoV-2 testing is performed due to patient symptoms;

there are few settings where ongoing universal screening of otherwise healthy patients is conducted. Thus, such universal testing can provide valuable insight into the disease dynamics in the community and can be used to monitor the burden of disease. 3-6

In this large cohort of women admitted for labour and delivery in Massachusetts undergoing universal SARS-CoV-2 infection screening, there were multiple identifiable factors associated with infection. Almost all patients who tested positive for infection had one or more identifiable factors associated with disease. SARS-CoV-2 infection most heavily affected pregnant women who were younger, African American or Hispanic, non-health care essential workers, publicly insured or from heavily affected areas, underscoring another source of disparity in obstetrics.

The authors thank Yonatan H. Grad for comments on an earlier version of this manuscript.

The authors report no conflicts of interest. Abbreviations: SARS-CoV-2, Severe acute respiratory syndrome coronavirus 2; SD, Standard deviation.

Massachusetts Department of Public Health. The Commonwealth of Massachusetts

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Patient characteristics associated with SARS-CoV-2 infection in parturients admitted for labour and delivery in Massachusetts during the spring 2020 surge: A prospective cohort study