Abstract
Objective:
To estimate the prevalence of post–acute sequelae of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection (PASC) after infection with SARS-CoV-2 during pregnancy and to characterize associated risk factors.
Methods:
In a multicenter cohort study (NIH RECOVER-Pregnancy Cohort), individuals who were pregnant during their first SARS-CoV-2 infection were enrolled across the U.S. from December 2021 through September 2023, either within 30 days of their infection or at differential timepoints thereafter. The primary outcome was PASC, defined as score ≥ 12 based on symptoms and severity as previously published by the NIH RECOVER- Adult Cohort, at the first study visit at least 6 months after the participant’s first SARS-CoV-2 infection. Risk factors for PASC were evaluated including socio-demographic characteristics, clinical characteristics prior to SARS-CoV-2 infection (baseline comorbidities, trimester of infection, vaccination status), and acute infection severity (classified by need for oxygen therapy). Multivariable logistic regression models were fitted to estimate associations between these characteristics and presence of PASC.
Results:
Of the 1,502 participants, 61.1% had their first SARS-CoV-2 infection on or after December 1, 2021 (i.e., during Omicron variant dominance); 51.4% were fully vaccinated prior to infection; 182 (12.1%) were enrolled within 30 days of their acute infection. The prevalence of PASC was 9.3% (95% CI 7.9–10.9%) measured at a median of 10.3 months (IQR 6.1–21.5) after first infection. The most common symptoms among individuals with PASC were post-exertional malaise (77.7%), fatigue (76.3%), and gastrointestinal symptoms (61.2%). In a multivariable model, history of obesity (14.9% vs 7.5%, aOR 1.65, 95% CI 1.12–2.43), depression or anxiety disorder (14.4% vs 6.1%, aOR 2.64, 95% CI 1.79–3.88) prior to first infection, economic hardship (self-reported difficulty covering expenses) (12.5% vs 6.9%, aOR 1.57, 95% CI 1.05–2.34), and treatment with oxygen during acute SARS-CoV-2 infection (18.1% vs 8.7%, aOR 1.86, 95% CI 1.00–3.44), were associated with increased prevalence of PASC.
Conclusions:
The prevalence of PASC at a median time of 10.3 months after SARS-CoV-2 infection during pregnancy was 9.3% in the NIH RECOVER-Pregnancy Cohort. The predominant symptoms were post-exertional malaise, fatigue, and gastrointestinal symptoms. Several socioeconomic and clinical characteristics were associated with PASC after infection during pregnancy.
Precis:
The prevalence of post–acute sequelae of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) after infection during pregnancy was 9.3%, and several socioeconomic and clinical characteristics were associated with post–acute sequelae of SARS-CoV-2 after infection during pregnancy.
Introduction
Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection during pregnancy is known to adversely affect pregnancy by increasing the risk for serious maternal morbidity, stillbirth, preterm birth, and hypertensive disorders of pregnancy.1–5 These risks are particularly profound among pregnant individuals with moderate to severe COVID-19 during pregnancy.2,5 In addition, pregnant people are at higher risk of developing severe COVID-19, including an increased risk of intensive care unit admission, and death, when compared with non-pregnant reproductive-age female populations.6,7 Thus, pregnant individuals are disproportionately affected by COVID-19.
As the pandemic evolved, a new public health crisis emerged as a proportion of patients who were infected with SARS-CoV-2 were found to experience long-term ramifications of infection in the form of post–acute sequelae of SARS-CoV-2 (PASC), also known as long COVID. Data from non-pregnant populations demonstrate that between 10–23% of those infected with SARS-CoV-2 will develop these long-term sequelae which can affect all organ systems.8,9 Pathophysiologic mechanisms for PASC have been proposed including viral reservoirs, immune activation, and potential genetic predisposition. An increased risk is observed with early variants, higher initial disease severity, and with various comorbidities such as obesity, diabetes, and other underlying chronic medical conditions.10-14
The National Institutes of Health (NIH) Researching COVID to Enhance Recovery (RECOVER) program was designed to better understand the incidence, prevalence and pathophysiology of PASC. As part of the NIH RECOVER initiative, individuals who were either currently within the first 30 days of SARS-CoV-2 infection during pregnancy or who had earlier experienced SARS-CoV-2 during pregnancy (RECOVER-Pregnancy Cohort) were enrolled to evaluate the prevalence of and risk factors associated with PASC. We hypothesized that individuals who acquire SARS-CoV-2 in pregnancy may have unique risk factors for PASC. Therefore, our aims were to estimate the prevalence of PASC after infection with SARS-Cov-2 during pregnancy and to characterize associated risk factors in the RECOVER-Pregnancy Cohort.
Methods
RECOVER-Pregnancy is a multicenter cohort study. Participants in the RECOVER-Pregnancy Cohort aged 18–45 years who were pregnant at the time of their first SARS-CoV-2 infection (defined as meeting World Health Organization criteria for suspected, probable or confirmed SARS-CoV-2 infection15) were considered for inclusion. The full protocol for the RECOVER-Pregnancy Cohort has been published previously.16, 17 This analysis cohort included individuals who were either currently within 30 days of SARS-CoV-2 infection during pregnancy or who had earlier experienced SARS-CoV-2 during pregnancy (enrolled more than 30 days after first infection). Participants were excluded from analysis if they had no study visit with a PASC symptom survey 6 months or later after index infection. The cohort included individuals enrolled between December 1, 2021 and September 16, 2023 across 46 states and the District of Columbia. At the time of the planned NIH RECOVER data lock on September 16, 2023, the target sample size for infected participants in the RECOVER-Pregnancy Cohort was achieved.
Participants for the RECOVER-Pregnancy cohort were recruited across RECOVER-Adult sites. The majority of participants (98%) were recruited either in person at 12 Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD) Maternal-Fetal Medicine Units (MFMU) Network Centers which include 27 individual hospital sites (encompassing community and academic hospitals), or remotely nationwide by the University of California San Francisco (UCSF). Institutional Review Board (IRB) approval was obtained through reliance on the New York University IRB as the single IRB. All participants provided written informed consent. STROBE guidelines for reporting of observational studies were followed. Participants were recruited via social media platforms with advertisements about the NIH RECOVER study and study eligibility, in person at healthcare encounters, and via messaging through the electronic medical record to individuals with a positive test for SARS-CoV-2 during pregnancy or delivery of an infant during the study time frame.
The primary outcome was presence of PASC at the first available study visit 6 months or more from index infection. At the study visit, participants completed a survey recording current presence of symptoms and selected symptom severity. Survey instruments have previously been published.9 Using a previously-reported symptom-based algorithm, a PASC score (ranging from 0 through 34) was computed, and participants with a score ≥ 12 were considered PASC-positive.9 The remaining participants were considered PASC-indeterminate. Of note, study visits were not included in the analysis if there was a participant-reported reinfection up to 30 days before or 7 days after the visit. For the primary analysis, this outcome definition for PASC was used regardless of ongoing pregnancy status at the study visit during which the symptom survey was collected. As a planned sensitivity analysis, we excluded study visits at which participants were still pregnant or within 12 weeks postpartum, using the earliest subsequent study visit if available; this analysis was performed because some of the symptoms of PASC may overlap with common pregnancy or postpartum symptoms. Descriptive data regarding patient self-reported pregnancy outcomes were also collected by survey.
Pre-specified risk factors for PASC were considered based on input from a multidisciplinary clinical team including maternal-fetal medicine, obstetrics, pediatrics, internal medicine, critical care, and patient and stakeholder representatives involved in the RECOVER Consortium and existing literature.18–23 Sociodemographic risk factors considered for inclusion in modeling were maternal age, insurance status at enrollment, self-reported difficulty covering expenses and paying bills at enrollment, and self-reported experience of discrimination measured by the Everyday Discrimination Scale at enrollment.24 On the Everyday Discrimination Scale, the frequency of experiencing discriminatory events is measured on a rating scale with responses ranging from never to daily. Scores are calculated based on reported frequency for each survey response with higher scores indicating higher self-reported levels of discrimination (scores range from 9–54). Clinical characteristics considered as risk factors included vaccination status at least two weeks before index infection, number of prior pregnancies, tobacco use, and self-reported presence of comorbidities in the year prior to index infection (obesity; depression or anxiety disorder; or any medical diagnosis of asthma, cardiovascular disease including hypertension, diabetes mellitus, or rheumatologic, autoimmune, or connective tissue disease). Index infection characteristics considered were severity (categorized based on self-report of the receipt of oxygen treatment for COVID-19), trimester at the time of infection, and calendar time of index infection which was used as a proxy for SARS-CoV-2 variant.
Cohort characteristics were summarized using counts and relative frequencies for binary and categorical variables, and means with standard deviations (SDs) or medians with interquartile ranges (IQR) for quantitative variables. Among participants meeting PASC criteria, the PASC score distribution was reported, along with counts and relative frequencies of symptoms used in the score definition. If a symptom survey was initiated, questions with missing values were considered as negative responses in the construction of the PASC score.9
Unadjusted odds ratios and 95% confidence intervals (CIs) between each risk factor and PASC status were estimated via unadjusted logistic regression. Adjusted odds ratios and 95% confidence intervals (CIs) including all risk factors were estimated using multivariable logistic regression. For the regression analysis, missing covariate values were addressed using multiple imputation by chained equations with predictive mean matching for all variables. Twenty-five imputed datasets were created and analyzed, and final odds ratio estimates and standard errors were computed using Rubin’s rules to pool the results across imputed replicates.25 A complete case analysis was performed as a sensitivity analysis to assess the handling of missing data. An additional sensitivity analysis was performed in which those with PASC (score ≥ 12) were compared with individuals with a PASC score of zero. Finally, a sensitivity was performed in the subgroup of participants whose eligible PASC-defining study visit occurred no more than 15 months after their first infection.
Statistical analyses were performed using R Software, and the ‘mice’ package was used for multiple imputation. All study data were stored in a Research Electronic Data Capture (REDCap) database housed in a FISMA moderate compliant environment.
Results
Of the 14,636 RECOVER participants enrolled as adults, 1,612 (11.0%) were pregnant at their first infection and 1,502 (93.2%) of these participants completed a symptom survey form at a 6-month study visit or later (Figure 1). The vast majority of infections were reported as confirmed by PCR or antigen test (93.9%). Overall 1,312 (87.4%) of participants had complete data on all risk factors studied. Trimester of pregnancy at infection had the highest rate of missingness (6.3%), largely because these data were not collected for participants with a pregnancy not resulting in live birth, or because participants were still pregnant as of the planned data lock.
Figure 1.
Study population.
In this cohort, 61.1% had an index SARS-CoV-2 infection on or after December 1, 2021 (i.e., during Omicron variant dominance), 48.2% had their index infection during the third trimester of pregnancy, and 51.4% were fully vaccinated (defined as having received the primary COVID-19 vaccination series) at least two weeks before their index SARS-CoV-2 infection (Table 1). Overall, 182 (12.1%) were enrolled within 30 days of their acute infection during pregnancy and the remainder were enrolled at differential timepoints after the acute infection. The timing of PASC-defining study visits from index infection was 6–9 months for 38.8% of PASC positive participants and 51.7% of PASC indeterminate participants; 12–21 months for 35.3% of PASC positive participants and 25.2% of PASC indeterminate participants; 24 months or more for 25.9% of PASC positive participants and 23.1% of PASC indeterminate participants.
Table 1.
Cohort Characteristics
| Characteristic | Overall Study Cohort (N=1,502) |
|---|---|
| Enrollment timing Acute (enrolled within 30 days of infection) Post-Acute (enrolled > 30 days from index infection) |
182/1502 (12.1%) 1320/1502 (87.9%) |
| Time from index infection to study visit 6–9 months 12–21 months 24 or more months |
758/1502 (50.5%) 393/1502 (26.2%) 351/1502 (23.4%) |
| Age at index infection (mean ± SD, years) | 31.6 ± 5.1 |
| Self-reported race and ethnicity Black, Non-Hispanic Hispanic White, Non-Hispanic Additional race or ethnicity, or missing |
238/1502 (15.8%) 253/1502 (16.8%) 908/1502 (60.5%) 103/1502 (6.9%) |
| COVID-19 pandemic wave at index infection First wave (before 6/30/2020) Second wave (7/1/2020–12/31/2020) Third Wave (1/1/2021–6/30/2021) Delta (7/1/2021–11/30/2021) Omicron (12/1/2021 or later) |
173/1502 (11.5%) 199/1502 (13.2%) 67/1502 (4.5%) 145/1502 (9.7%) 918/1502 (61.1%) |
| Insurance status at time of study enrollment Private, Tricare, VA, or multiple insurance carriers Medicare, Medicaid, or self-pay |
1074/1499 (71.6%) 425/1499 (28.4%) |
| Difficulty covering expenses and paying bills in month before enrollment | 630/1499 (42.0%) |
| Discrimination score at enrollment (median, IQR) | 14 (9,18) |
| Fully vaccinated at least two weeks preceding index infection date | 771/1500 (51.4%) |
| Tobacco use in year preceding index infection date Never Has smoked tobacco at some point or prefer not to say |
1314/1491 (88.1%) 177/1491 (11.9%) |
| Obesity in year preceding index date | 349/1471 (23.7%) |
| Depression in year preceding index date | 549/1469 (37.4%) |
| Medical comorbidities in year preceding index date Asthma Cardiovascular disease Diabetes Rheumatologic, autoimmune, or connective tissue disease |
439/1490 (29.5%) 268/1479 (18.1%) 98/1485 (6.6%) 49/1485 (3.3%) 99/1483 (6.7%) |
| Number of prior pregnancies (median, IQR) | 2 (1,3) |
| Oxygen treatment of index acute SARS-CoV-2 infection | 94/1485 (6.3%) |
| Trimester of pregnancy at index infection First trimester Second trimester Third trimester |
244/1407 (17.3%) 485/1407 (34.5%) 678/1407 (48.2%) |
Relative frequency denominators reflect missingness in each binary or categorical variable. Missingness for continuous variables as follows: number of pregnancies (n=25), discrimination score (n=30), number of pregnancies (n=25).
Abbreviations: Standard Deviation (SD), Inter-Quartile Range (IQR).
Descriptive self-reported pregnancy information is reported in the supplemental appendix (Appendix 2, available online at http://links.lww.com/xxx) for 1,489 participants with pregnancy outcome data available, of whom 1,428 (95.9%) had a pregnancy resulting in live birth. Of these participants 56.9% did not report any adverse pregnancy outcomes, while 10.3% reported gestational diabetes, 11.4% preeclampsia, and 9.6% a preterm birth.
Given that the first study visit 6 months or more from index infection was used to assess for presence of PASC, there was differential timing of the assessment of PASC. The most common study visit included in this analysis was a 6-month visit for 543 (36.1%) participants, and over half of the cohort was included using a 6- or 9-month study visit (758; 50.5%). Overall median time from index date to the PASC-defining study visit was 10.3 months (IQR 6.1–21.5).
Out of 1502 participants, 139 (9.3%) had PASC based on symptoms at the defining study visit (95% CI 7.9–10.9%). Of the 12 symptoms included in the PASC score definition, the most common among individuals with PASC were post-exertional malaise (77.7%), fatigue (76.3%), and gastrointestinal symptoms (61.2%) (Figure 2). The median PASC score among those with PASC was 15 (IQR 13–18) (Figure 3). Frequency of PASC symptoms and reported symptoms among those classified as PASC indeterminate are reported in Appendix 3, available online at http://links.lww.com/xxx.
Figure 2.
Relative frequencies of post–acute sequelae (PASC) symptoms among participants with PASC. Symptom contribution to the PASC score listed in parentheses after each symptom.
Figure 3.
Distribution of post–acute sequelae (PASC) scores among participants with PASC. Participants met the primary outcome of PASC if they had a PASC score of 12 or greater. The count of the number of participants with various PASC scores are reflected by the vertical blue bars.
In the planned sensitivity analysis, the frequency of PASC was consistent after restricting the cohort to the 1,418 participants who were not pregnant or within 12 weeks postpartum at the time of the PASC-defining study visit; among these participants, 130 (9.2%, 95% CI 7.7–10.8%) had PASC, with similar rates of PASC-defining symptoms (Appendix 4, available online at http://links.lww.com/xxx). In the subgroup of 1,015 participants with PASC-defining study visits no more than 15 months after index infection, 79 (7.8%, 95% CI 6.2–9.6%) had PASC.
In unadjusted analyses, many pre-selected risk factors showed significant associations with PASC (Table 2). Self-reported difficulty paying bills, obesity prior to index infection, depression or anxiety disorder prior to index infection, and treatment with oxygen during the acute index SARS-CoV-2 infection were associated with PASC after adjustment for all other covariates (Table 2).
Table 2.
Analysis of risk factors for post–acute sequelae of SARS-CoV-2 (PASC)
| Proportion PASC Positive | Odds Ratioa | Adjusted ORb | ||
|---|---|---|---|---|
| Characteristic | Characteristic Present | Characteristic Not Present | OR (95% CI) | aOR (95% CI) |
| Age at index infection in years[OR and aOR for a 5-year increase] | - | - | 0.98 (0.82, 1.16) | 1.14 (0.94, 1.39) |
| Index infection pre-Omicron (before 12/1/2021) | 73/584 (12.5%) | 66/918 (7.2%) | 1.84 (1.3, 2.62) | 1.46 (0.88, 2.42) |
| Medicare or Medicaid or no insurance at enrollment | 48/425 (11.3%) | 91/1074 (8.5%) | 1.38 (0.95, 1.99) | 0.99 (0.62, 1.58) |
| Difficulty paying billsc | 79/630 (12.5%) | 60/869 (6.9%) | 1.93 (1.36, 2.75) | 1.57 (1.05, 2.34) |
| Discrimination indexd at enrollment [OR and aOR for a 10-point increase] | - | - | 1.45 (1.17, 1.81) | 1.17 (0.92, 1.49) |
| Not fully vaccinated two weeks prior to index infection | 87/729 (11.9%) | 52/771 (6.7%) | 1.87 (1.31, 2.68) | 1.4 (0.82, 2.41) |
| Any tobacco use (or prefer not to answer) in year prior to index infection | 23/177 (13.0%) | 116/1314 (8.8%) | 1.54 (0.96, 2.49) | 1.01 (0.6, 1.7) |
| Obesity during year prior to index infection | 52/349 (14.9%) | 84/1123 (7.5%) | 2.19 (1.51, 3.16) | 1.65 (1.12, 2.43) |
| Composite of other comorbidities present during year prior to index infection | 56/439 (12.8%) | 82/1051 (7.8%) | 1.73 (1.2, 2.48) | 1.34 (0.92, 1.96) |
| Depression or anxiety disorder during year prior to index infection | 79/549 (14.4%) | 56/920 (6.1%) | 2.61 (1.82, 3.74) | 2.64 (1.79, 3.88) |
| Number of prior pregnancies | - | - | 1.07 (0.98, 1.18) | 0.98 (0.88, 1.1) |
| Oxygen treatment of index acute SARS-CoV-2 infection | 17/94 (18.1%) | 121/1391 (8.7%) | 2.34 (1.34, 4.09) | 1.86 (1.00, 3.44) |
| First trimester of pregnancy at infection | 21/244 (8.6%) | 106/1163 (9.1%) | Reference | Reference |
| Second trimester of pregnancy at infection | 41/485 (8.5%) | 86/922 (9.3%) | 0.99 (0.56, 1.72) | 0.86 (0.48, 1.53) |
| Third trimester of pregnancy at infection | 65/678 (9.6%) | 62/729 (8.5%) | 1.1 (0.65, 1.87) | 0.85 (0.49, 1.49) |
| PASC Status e | Odds Ratio a | Adjusted OR b | ||
| Characteristic | Positive (n=139) | Indeterminate (n=1363) | OR (95% CI) | aOR (95% CI) |
| Age at index infection in years, Mean (SD) [OR and aOR for a 5-year increase] | 31.5 (4.9) | 31.6 (5.1) | 0.98 (0.82, 1.16) | 1.14 (0.94, 1.39) |
| Discrimination indexd at enrollment, Mean (SD) [OR and aOR for a 10-point increase] | 17.1 (7.5) | 15 (6.8) | 1.45 (1.17, 1.81) | 1.17 (0.92, 1.49) |
| Number of prior pregnancies, Mean (SD) | 2.7 (2) | 2.5 (1.8) | 1.07 (0.98, 1.18) | 0.98 (0.88, 1.1) |
Abbreviations: Post-Acute Sequelae of SARS-CoV-2 (PASC); Standard Deviation (SD); Odds Ratio (OR); Adjusted Odds Ratio (aOR); Confidence Interval (CI). Bold face indicates statistically significant result.
Odds ratios reported from unadjusted univariable logistic regression models.
Adjusted odds ratios reported from multivariable logistic regression model with all variables shown included as covariates. Regression models fit after multiple imputation of missing values.
Difficulty paying bills was a response that covering expenses and paying bills was “somewhat difficult” or “very difficult” in month prior to enrollment.
Discrimination index score was calculated using the Everyday Discrimination Index with the frequency of discrimination reported on a Likert scale for various social interactions. Score range is 10–60.
Continuous variables are also shown summarized by PASC status for comparison
The adjusted odds ratio estimates between risk factors and PASC were qualitatively similar in sensitivity analyses when restricting the cohort to those who were not pregnant or within 12 weeks postpartum at the time of the PASC symptom assessment (Appendix 5, available online at http://links.lww.com/xxx). The adjusted odds ratios for self-reported difficulty paying bills and depression or anxiety disorder prior to index infection continued to exclude the null value of 1, while other estimates were slightly attenuated. Adjusted odds ratio point estimates also remained similar when handling missing risk factor variables using a complete case analysis rather than multiple imputation by chained equations, albeit with wider confidence intervals due to the reduction in sample size (Appendix 6, available online at http://links.lww.com/xxx). The adjusted odds ratio 95% CI for depression or anxiety disorder prior to index infection remained statistically significant. Results remained similar when individuals with PASC were compared with those with a PASC score of zero, and when the cohort was restricted to participants with PASC-defining study visits no more than 15 months after index infection (Appendices 7 and 8, available online at http://links.lww.com/xxx). In these sensitivity analyses, the association with infection pre-Omicron became statistically significant (aOR 2.23, 95% CI 1.26–3.94), as did the association with discrimination score (aOR 1.31, 95% CI 1.02–1.70, for every 10 point increase) in the comparison to PASC score of zero. Appendix 9, available online at http://links.lww.com/xxx, summarizes the adjusted odds ratios and 95% CIs across sensitivity analyses.
Discussion
The observed PASC prevalence was 9.3% at a median of 10.3 months after SARS-CoV-2 infection during pregnancy in the RECOVER-Pregnancy cohort. The most common symptoms among those with PASC following SARS-CoV-2 infection during pregnancy included post-exertional malaise, fatigue, gastrointestinal symptoms and dizziness. Several socioeconomic and clinical characteristics were associated with the development of PASC including self-reported obesity, pre-existing depression or anxiety disorder, economic hardship, and treatment with oxygen during the acute SARS-CoV-2 infection indicating higher disease severity. These findings were robust to planned sensitivity analyses.
The RECOVER- Adult Cohort developed and published an algorithm for identifying cases at high likelihood of PASC based on symptoms and associated severity using the same surveys included in this study.9 The NIH RECOVER-Adult cohort estimates of PASC ranged from 10% among those enrolled in the acute infection phase to 23% among all participants9, which is consistent with other published literature.8 The Centers for Disease Control and Prevention (CDC) estimated that 7% of U.S. adults had PASC (any self-reported symptoms lasting 3 months or longer) at some point, with a decline in rates over time.26 Variation in reported prevalence is likely a result of differing definitions of PASC, sampling methodology, and population studied.
In the RECOVER-Adult Cohort publication, which largely includes adults who acquired SARS-CoV-2 outside of pregnancy, the most common PASC-defining symptoms were similar to the findings here and included post-exertional malaise, fatigue, gastrointestinal symptoms and dizziness; brain fog was also common. There are limited data regarding symptom persistence following SARS-CoV-2 during pregnancy. One study estimated that 25% of pregnant individuals with SARS-CoV-2 had persistence of acute infection symptoms 8 weeks from index infection.27 Another study of individuals with SARS-CoV-2 in pregnancy (n=259) found a prevalence of fatigue at 6 months post-virus of 27.8%.28
Risk factors for PASC in this cohort are similar to those identified in other cohorts including obesity, the presence of medical comorbidities, and higher disease severity. Other cohorts have also identified earlier SARS-CoV-2 variants and lack of vaccination as additional risk factors. Both era of infection (pre-Omicron) and lack of vaccination were associated with PASC in unadjusted models in this analysis, but were no longer associated with PASC in adjusted models.
It is notable that 42% of our cohort of patients who had SARS-CoV-2 during pregnancy reported difficulties covering expenses and paying bills in the month prior to enrollment. Given that most participants enrolled after their acute infection and economic hardship was measured at enrollment, this association may represent difficulty covering expenses prior to index infection, or may be a result of PASC. A study of nearly 7,000 U.S. families reported that persistent symptoms after SARS-CoV-2 infection were associated with economic hardship, irrespective of economic status prior to infection.29 Importantly, individuals who identify as Black or Hispanic were disproportionately affected by SARS-CoV-2 early in the pandemic, and are more likely to experience socioeconomic disadvantage, which may both influence PASC prevalence in these at-risk populations.
Strengths of this study include the multicenter and diverse population that is largely representative of the U.S. population. All participants were asked systematically about PASC symptoms that could stem from dysfunction in all organ systems. Survey questions collected in depth information about symptom severity. Detailed measures of socioeconomic status were collected including information about economic hardship. Sampling was not limited to those who were previously identified as having long COVID or PASC. We focused on people with SARS-CoV-2 in pregnancy, which is an understudied population in PASC research.
Limitations include inability to estimate a true population prevalence of PASC as participants willing to participate in a study of PASC may be different than those who did not enroll; thus, the estimate is subject to selection bias. Different people experience different symptoms and severity of PASC; therefore, the research PASC definition used in the reported analysis should not be used to exclude PASC in clinical settings, as reflected in the labeling of participants as either PASC positive or PASC indeterminate. Similarly, the cohort was evaluated for PASC at a median time of 10 months from infection; some patients may have experienced PASC with resolution by the time of assessment, so the proportion observed with PASC in this cohort represents a time-aggregated view of PASC prevalence using the earliest eligible time point for each participant. We did not examine pharmacologic therapeutics administered at time of acute infection. Some of the symptoms of PASC, such as fatigue, may overlap with symptoms seen in those without PASC during pregnancy or postpartum. However, a sensitivity analysis including only participants who were more than 12 weeks postpartum generated consistent results. In addition, all participants had recent pregnancies, the vast majority had live births (96%), thus were caring for newborns, and only a subset developed symptoms of PASC. Finally, the present analysis does not include directly comparable control groups of non-pregnant reproductive age females. Future research is needed to rigorously assess comparative PASC prevalence, symptoms, and risk factors.
In conclusion, in the RECOVER-Pregnancy Cohort, approximately 1 in 10 had PASC at a time point six months or more (median time of 10.3 months) after infection. It is important for healthcare clinicians who care for pregnant people to be aware of PASC, and to consider referral to clinicians who manage patients with PASC for anyone with new or persistent symptoms following SARS-CoV-2 during pregnancy. Our findings may also help to inform the targeted development of future therapies with a focus on populations that are at increased risk for PASC.
Supplementary Material
Authors’ Data Sharing Statement.
Will individual participant data be available (including data dictionaries)? Yes
What data in particular will be shared? Deidentified participant data, Data dictionary
What other documents will be available? None
When will data be available (start and end dates)? The NIH RECOVER Initiative releases data to the public on a regular basis.
By what access criteria will data be shared (including with whom, for what types of analyses, and by what mechanism)? Authorized researchers can access RECOVER data from BioData Catalyst (BDC, https://biodatacatalyst.nhlbi.nih.gov/) and data specific to publications through request portals listed on the RECOVER webpage (https://recovercovid.org/data). BDC provides instructions for finding and viewing RECOVER data as well as the steps to request authorization to use de-identified individual participant data for scientific analysis within BDC. Researchers may propose to use the data for a specified scientific purpose, and data will be shared after approval of the proposal and with a signed data access agreement.
Acknowledgments
This study is part of the NIH Researching COVID to Enhance Recovery (RECOVER) Initiative, which seeks to understand, treat, and prevent the post–acute sequelae of SARS-CoV-2 infection (PASC). For more information on RECOVER, visit https://recovercovid.org/. We would like to thank the National Community Engagement Group (NCEG), all patient, caregiver and community representatives, and all the participants enrolled in the RECOVER initiative.
This research was funded by the National Institutes of Health (NIH) Agreements OTA OT2HL161847, OT2HL161841 and OT2HL156812 as part of the Researching COVID to Enhance Recovery (RECOVER) Research Initiative. No funding source had any role in the study design; in the collection, analysis, and interpretation of data; in the writing of the report; or in the decision to submit the article for publication. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.
Financial Disclosure:
Torri D. Metz is the site PI for a Pfizer study of Paxlovid in pregnancy, and was the site PI for a Pfizer study of COVID-19 vaccination in pregnancy. She has received UptoDate royalties for two topics on trial of labor after cesarean. Carmen J Beamon disclosed receiving payments from Wellcare of North Carolina. Ann Chang’s institution received payment from New York University for her efforts on this study. Kelly S. Gibson disclosed that her institution received funding from the NICHD, NHLBI, and Materna. Rachel Hess received payment from Astellas Pharmaceuticals. M. Camile Hoffman disclosed her institution received payment for her expert testimony for one medicolegal trial from Wheeler, Trigg, and Associates (a defense attorneys firm). Her institution also received payment for a disease state presentation on postpartum depression and zuranolone from SAGE/Biogen. Brenna L. Hughes disclosed receiving payments from UptoDate and Moderna. Stuart Katz disclosed payments for providing expert testimony for Venable LLP. Jennifer Hadlock has received funding (paid to institution) for retrospective studies of COVID-19 from Pfizer, Novartis, Janssen, and Gilead. Grace A. McComsey served as an advisor for Gilead and ViiVGlaxoSmithKline. Patrick Ramsey disclosed receiving royalties from UptoDate. His institution was paid by the Texas Collaborative for Healthy Mothers and Babies (TCHMB) - Texas PQC for part of his efforts. Daniel W Skupski reports receiving payments from Organon, Inc. and Cooper Surgical. Alan T N Tita disclosed money paid to his institution from Pfizer for his efforts in this study. Andrea Foulkes disclosed receiving past payments from Round Table, Inc.The other authors did not report any potential conflicts of interest.
Each author has confirmed compliance with the journal’s requirements for authorship.
Footnotes
Presented at the Society for Maternal-Fetal Medicine’s 2024 Pregnancy Meeting, February 10–14, 2024, National Harbor, Maryland.
Clinical Trial Registration: ClinicalTrials.gov, NCT05172024.
PEER REVIEW HISTORY
Received April 22, 2024. Received in revised form May 14, 2024. Accepted May 23, 2024. Peer reviews and author correspondence are available at http://links.lww.com/xxx.
References
- 1.Chinn J, Sedighim S, Kirby KA, et al. Characteristics and outcomes of women with COVID-19 giving birth in U.S. academic centers during the COVID-19 pandemic. JAMA Netw Open 2021; 4(8):e2120456. DOI: 10.1001/jamanetworkopen.2021.20456 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 2.Metz TD, Clifton RG, Hughes BL, et al. Association of SARS-CoV-2 infection with serious maternal morbidity and mortality from obstetric complications. JAMA 2022; 327(8):748–59. DOI: 10.1001/jama.2022.1190. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 3.Simon E, Gouyon JB, Cottenet J, et al. Impact of SARS-CoV-2 infection on risk of prematurity, birthweight and obstetric complications: A multivariate analysis from a nationwide, population-based retrospective cohort study. BJOG 2022; 129(7):1084–94. DOI: 10.1111/1471-0528.17135 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 4.Desisto CL, Wallace B, Simeone RM, et al. Risk for stillbirth among women with and without COVID-19 at delivery hospitalization – United States, March 2020-September 2021. MMWR Morb Mortal Wkly Rep 2021; 70(47):1640–45. . DOI: 10.15585/mmwr.mm7047e1. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 5.Metz TD, Clifton RG, Hughes BL, et al. Disease severity and perinatal outcomes of pregnant patients with coronavirus disease 2019 (COVID-19). Obstet Gynecol 2021; 137(4):571–80. DOI: 10.1097/AOG.0000000000004339. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 6.Zambrano LD, Ellington S, Strid P, et al. Centers for Disease Control and Prevention. Characteristics of symptomatic women of reproductive age with laboratory-confirmed SARS-CoV-2 infection by pregnancy status- United States, January 22 to October 3, 2020. MMWR Morb Mortal Wkly Rep 2020; 69(44):1641–7. DOI: 10.15585/mmwr.mm6944e3. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 7.Jering KS, Claggett BL, Cunningham JW, et al. Clinical characteristics and outcomes of hospitalized women giving birth with and without COVID-19. JAMA Int Med 2021; 181(5):714–7. DOI: 10.1001/jamainternmed.2020.9241. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 8.Lancet The. Long COVID: 3 Years In. Lancet 2023; 401(10379): 795. DOI: 10.1016/S0140-6736(23)00493–2. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 9.Thaweethai T, Jolley SE, Karlson EW, et al. ; RECOVER Consortium. Development of a Definition of Postacute Sequelae of SARS-CoV-2 Infection. JAMA 2023. Jun 13;329(22):1934–1946. DOI: 10.1001/jama.2023.8823. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 10.Klein J, Wood J, Jaycox JR, et al. Distinguishing features of long COVID identified through immune profiling. Nature 2023; 623(7985):139–48. DOI: 10.1038/s41586-023-06651-y. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 11.Opsteen S, Files JK, Fram T, Erdmann N. The role of immune activation and antigen persistence in acute and long COVID. J Investig Med 2023; 71(5):545–62. DOI: 10.1177/10815589231158041. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 12.Sherif ZA, Gomez CR, Connors TJ, Henrich TJ, Reeves WB; RECOVER Mechanistic Pathway Task Force. Pathogenic mechanisms of post–acute sequelae of SARS-CoV-2 infection (PASC). Elife. 2023. Mar 22;12:e86002. DOI: 10.7554/eLife.86002. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 13.Mohandas S, Jagannathan P, Henrich TJ, et al. ; RECOVER Mechanistic Pathways Task Force. Immune mechanisms underlying COVID-19 pathology and post–acute sequelae of SARS-CoV-2 infection (PASC). Elife. 2023. May 26;12:e86014. DOI: 10.7554/eLife.86014. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 14.Wang C, Ramasamy A, Verduzco-Gutierrez M, Brode WM, Melamed E. Acute and post–acute sequelae of SARS-CoV-2 infection: a review of risk factors and social determinants. Virol J 2023. Jun 16;20(1):124. DOI: 10.1186/s12985-023-02061-8. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 15.World Health Organization. WHO COVID-19: case definitions, updated in public health surveillance for COVID-19, 22 July 2022. https://www.who.int/publications/i/item/WHO-2019-nCoV-Surveillance_Case_Definition-2022.1. Accessed March 9, 2023. [Google Scholar]
- 16.Metz TD, Clifton RG, Gallagher R, et al. ; RECOVER Initiative. Researching COVID to enhance recovery (RECOVER) pregnancy study: Rationale, objectives and design. PLoS One. 2023. Dec 21;18(12):e0285351. DOI: 10.1371/journal.pone.0285351. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 17.Horwitz LI, Thaweethai T, Brosnahan SB, et al. Researching COVID to Enhance Recovery (RECOVER) adult study protocol: Rationale, objectives, and design. PLoS One. 2023. Jun 23;18(6):e0286297. DOI: 10.1371/journal.pone.0286297. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 18.Hill EL, Mehta HB, Sharma S, Mane K, et al. ; N3C Consortium; and the RECOVER Consortium. Risk factors associated with post–acute sequelae of SARS-CoV-2: an N3C and NIH RECOVER study. BMC Public Health 2023. Oct 25;23(1):2103. DOI: 10.1186/s12889-023-16916-w. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 19.Bai F, Tomasoni D, Falcinella C, et al. Female gender is associated with long COVID syndrome: a prospective cohort study. Clin Microbiol Infect 2022. Apr;28(4):611.e9–611.e16. DOI: 10.1016/j.cmi.2021.11.002. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 20.Yoo SM, Liu TC, Motwani Y, et al. Factors Associated with Post-Acute Sequelae of SARS-CoV-2 (PASC) After Diagnosis of Symptomatic COVID-19 in the Inpatient and Outpatient Setting in a Diverse Cohort. J Gen Intern Med 2022. Jun;37(8):1988–1995. DOI: 10.1007/s11606-022-07523-3. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 21.Jacobs ET, Catalfamo CJ, Colombo PM, et al. Pre-existing conditions associated with post–acute sequelae of COVID-19. J Autoimmun 2023. Feb;135:102991. DOI: 10.1016/j.jaut.2022.102991. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 22.Stephens MD, Gazmararian JA, Khakharia A. Prevalence and risk factors of post–acute sequelae of COVID-19 among United States Veterans. Ann Epidemiol 2024. Jan;89:1–7. DOI: 10.1016/j.annepidem.2023.11.006. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 23.Durstenfeld MS, Peluso MJ, Peyser N, et al. Factors Associated With Long COVID Symptoms in an Online Cohort Study. Open Forum Infect Dis 2023. Feb 1;10(2):ofad047. DOI: 10.1093/ofid/ofad047. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 24.Williams DR, Yan Yu, Jackson JS, Anderson NB. Racial Differences in Physical and Mental Health: Socio-economic Status, Stress and Discrimination. J Health Psychol. 1997. Jul;2(3):335–51. DOI: 10.1177/135910539700200305. [DOI] [PubMed] [Google Scholar]
- 25.Van Buuren S, Groothuis-Oudshoorn K. mice: Multivariate imputation by chained equations in R. Journal of statistical software. 2011. Dec 12;45:1–67. [Google Scholar]
- 26.Adjaye-Gbewonyo D, Vahratian A, Perrine CG, Bertolli J. Long COVID in Adults: United States, 2022. NCHS Data Brief 2023. Sep;(480):1–8. [PubMed] [Google Scholar]
- 27.Afshar Y, Gaw SL, Flaherman VJ, Chambers BD, Krakow D, Berghella V, Shamshirsaz AA, Boatin AA, Aldrovandi G, Greiner A, Riley L, Boscardin WJ, Jamieson DJ, Jacoby VL; Pregnancy CoRonavIrus Outcomes RegIsTrY (PRIORITY) Study. Clinical Presentation of Coronavirus Disease 2019 (COVID-19) in Pregnant and Recently Pregnant People. Obstet Gynecol 2020. Dec;136(6):1117–1125. DOI: 10.1097/AOG.0000000000004178. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 28.Oliveira AMDSS Carvalho MA, Nacul L Cabar FR, Fabri AW Peres SV, Zaccara TA, O’Boyle S, Alexander N, Takiuti NH, Mayaud P, Brizot ML, Francisco RPV. Post-Viral Fatigue Following SARS-CoV-2 Infection during Pregnancy: A Longitudinal Comparative Study. Int J Environ Res Public Health. 2022. Nov 26;19(23):15735. DOI: 10.3390/ijerph192315735. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 29.Hair NL, Urban C. Association of Severe COVID-19 and Persistent COVID-19 Symptoms With Economic Hardship Among US Families. JAMA Netw Open 2023. Dec 1;6(12):e2347318. DOI: 10.1001/jamanetworkopen.2023.47318. [DOI] [PMC free article] [PubMed] [Google Scholar]
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