Abstract
Introduction
Inflammatory bowel disease (IBD) is a chronic inflammatory condition affecting approximately 2.39 million individuals in the USA. IBD is associated with extraintestinal manifestations (EIMs), among which pericarditis is prominent, comprising 70% of cardiac EIMs. The onset of pericarditis in these patients is primarily attributed to IBD medication-related adverse effects and is predominantly documented through case reports. This highlights the need for an epidemiological study in a large, propensity-matched cohort, given the significant morbidity and mortality of pericarditis.
Methods
Using the National Institutes of Health’s (NIH) All of Us Research Program, we conducted a cross-sectional study and propensity-matched 5,178 IBD cases to 15,534 controls (1:3). We compared demographics, clinical characteristics, prevalence of autoimmune diseases, and rates of pericarditis. Logistic regressions assessed the association between IBD and pericarditis, adjusting for confounders (p < 0.15), and a sensitivity analysis confirmed the association (p < 0.001). A Kaplan-Meier analysis compared the incidence of pericarditis in various IBD severity cohorts, including mild (n = 620) and moderate/severe (n = 1,908), stratified by IBD medication exposure.
Results
Pericarditis was significantly more prevalent in IBD cases (1.3% vs. 0.6%; absolute risk difference 0.7%, 95% confidence interval [CI]: 0.37%–1.03%), with significant associations in univariable (odds ratio [OR] 2.2, 95% CI: 1.6–3.0, p < 0.001) and multivariable (OR 1.9, 95% CI: 1.3–2.6, p < 0.001) analyses. IBD preceded pericarditis in 65% of cases. There was no difference in pericarditis-free survival between mild and moderate/severe cohorts (p = 0.90).
Conclusion
This study uniquely provides evidence of a significant association between IBD and pericarditis, establishing pericarditis as a clinically significant EIM in a large, diverse US cohort, independent of disease severity. This highlights the need for heightened screening to enhance pericarditis management and patient outcomes.
Keywords: Pericarditis, Epidemiology, Inflammatory bowel disease, Cardiac involvement, Extraintestinal manifestation
Introduction
Inflammatory bowel disease (IBD) is a chronic inflammatory disorder of the gastrointestinal tract estimated to affect 2.39 million Americans, imposing a substantial burden on public health [1]. Extraintestinal manifestations (EIMs) from IBD are common and can affect up to 47% of IBD patients [2]. Pericarditis is the most common cardiac EIM, accounting for nearly 70% of cardiac EIMs. The onset of pericarditis has often been linked to adverse effects of IBD medications, but the literature is confined to case reports and small reviews [3–5]. The limited research on pericarditis as an EIM may contribute to reduced clinical awareness, heightening the risk of misdiagnosis or delayed recognition of pericarditis in IBD patients. Given the high prevalence of pericarditis and its potential for severe morbidity and mortality, clarifying the connection between IBD and pericarditis is essential for ensuring timely diagnosis, effective management, and improved patient outcomes [6]. This study uses a large, diverse US cohort from the NIH’s All of Us Research Program to investigate the association between IBD and pericarditis and assess its relationship to comorbidities and disease severity.
Methods
We conducted a cross-sectional analysis of participants in the NIH’s All of Us Registered Tier Dataset v7 who were aged 18 years or older at enrollment and had electronic health record (EHR) data spanning 1 year or more. Diagnoses of IBD and pericarditis were identified using Systemized Nomenclature of Medicine – Clinical Terms (SNOMED CT). SNOMED CT, integrated within the Observational Medical Outcomes Partnership (OMOP) Common Data Model used by All of Us, facilitates accurate capture of clinical diagnoses by providing a granular and interoperable vocabulary that harmonizes data from various hospital systems with differing EHR platforms and minimizes misclassification compared to billing-focused ICD codes. The SNOMED codes included in our study are listed in online supplementary Table 1 (for all online suppl. material, see https://doi.org/10.1159/000550425). Diagnoses were based on at least one EHR entry, consistent with standard practices in large-scale epidemiological studies, though confirmatory testing (e.g., echocardiography, ECG, or clinical notes for pericarditis; endoscopy for IBD) was not available due to the de-identified nature of the dataset [7]. We propensity-matched 5,178 IBD cases to 15,534 controls (1:3) by age, sex, race/ethnicity, and EHR duration quintiles. We then compared the prevalence of potential confounders such as obesity, smoking status, and autoimmune/inflammatory disease prevalence. Finally, we compared the prevalence of pericarditis between the groups.
Categorical variables were compared using Pearson’s chi-squared tests (expected values >5) and continuous variables via unpaired t tests, confirming normality and equal variances. We assessed for an association between IBD and pericarditis in univariable and multivariable analysis, controlling for variables if p < 0.15 in the univariable analysis. This threshold was chosen to balance the inclusion of relevant confounders (e.g., variables with p < 0.001) and potentially relevant confounders (e.g., sarcoidosis) while avoiding overfitting, given the relatively low number of pericarditis events. To assess the robustness of the multivariable model, a sensitivity analysis was conducted using a stricter p value threshold (<0.05) for confounder selection and excluding patients with autoimmune/inflammatory comorbidities. Temporality between IBD and pericarditis was evaluated.
To assess the impact of IBD severity on the risk of pericarditis, we constructed two IBD cohorts – moderate/severe (n = 1,908) and mild (n = 620) – for Kaplan-Meier survival analyses with pericarditis as the outcome. Patients in the moderate/severe cohort had records of immunomodulators (e.g., methotrexate) or ≥2 administrations (≥8 weeks apart) of advanced therapies (e.g., adalimumab, infliximab). Patients in the mild cohort used mesalamine, balsalazide, or sulfasalazine without moderate/severe criteria. Patients with mild criteria but ≥2 prednisone uses (>8 weeks apart) were classified as moderate/severe. Patients with a history of advanced therapy who did not meet the requirements for the moderate/severe cohort were excluded from the study. Survival analysis began at the first qualifying medication date, using the earliest date if multiple dates were available; patients with pericarditis before this date were excluded. Kaplan-Meier survival curves were compared between the mild and moderate/severe cohorts using log-rank tests. The analysis employed a 15-year prospective follow-up period to evaluate pericarditis-free survival.
Results
From 266,612 All of Us participants, 5,178 IBD cases and 15,534 matched controls (mean age 56.5 ± 17 years, 62% female) with no significant demographic differences or rates of smoking were identified (shown in Table 1). IBD cases were significantly less likely to have a history of obesity (39% vs. 43%) and significantly more likely to have diagnoses of ankylosing spondylitis (1.9% vs. 0.5%), celiac disease (2.5% vs. 0.9%), type 1 diabetes (4.0% vs. 2.9%), gout (6.5% vs. 4.3%), systemic lupus erythematosus (3.7% vs. 1.4%), psoriasis (8.1% vs. 3.6%), rheumatoid arthritis (8.2% vs. 3.4%), and sarcoidosis (1.0% vs 0.7%). IBD cases were more likely to be diagnosed with pericarditis (1.3% vs. 0.6%; absolute risk difference 0.7%, 95% confidence interval [CI]: 0.37%–1.03%). Temporality was assessed and showed that IBD diagnoses preceded pericarditis diagnoses in 65% of patients (median: −1.2 years, IQR: −10.3 to 1.1 years) (shown in Table 2). Pericarditis was significantly associated with IBD in univariable (odds ratio [OR] 2.2, 95% CI: 1.6–3.0, p < 0.001) and multivariable (OR 1.9, 95% CI: 1.3–2.6, p < 0.001) analyses, adjusting for potential confounders (shown in Table 3). Pericarditis remained associated with IBD in a sensitivity analysis excluding patients with autoimmune/inflammatory comorbidities (p < 0.001).
Table 1.
Demographic characteristics, autoimmune comorbidities, and pericarditis prevalence in propensity-matched IBD cases (N = 5,178) and controls (N = 15,534)
| Characteristics | Matched controls (N = 15,534) | IBD cases (N = 5,176) | p value |
|---|---|---|---|
| Age, mean (SD), years | 56.5±16.7 | 56.5±16.7 | 0.974 |
| Female sex at birth, n (%) | 9,553 (61.5) | 3,182 (61.5) | 0.896 |
| Race/ethnicity, n (%) | | | 1.000 |
| Asian | 197 (1.3) | 67 (1.3) | |
| Black or African American | 1,883 (12.1) | 626 (12.1) | |
| White | 10,750 (69.2) | 3,585 (69.2) | |
| Hispanic/Latino | 1,701 (11.0) | 567 (11.0) | |
| Other | 1,003 (6.5) | 333 (6.5) | |
| Duration of EHR, median (IQR), years | 13.4 (8.2–21.2) | 13.6 (8.2–21.7) | 0.075 |
| Smoking status, n (%) | | | 0.399 |
| Ever smoker | 6,400 (41.2) | 2,171 (41.9) | |
| Not ever smoker | 8,724 (56.1) | 2,877 (55.6) | |
| Obesity, n (%) | 6,728 (43.3) | 2,000 (38.6) | <0.001 |
| Ankylosing spondylitis, n (%) | 71 (0.5) | 96 (1.9) | <0.001 |
| Celiac disease, n (%) | 138 (0.9) | 131 (2.5) | <0.001 |
| Diabetes type 1, n (%) | 450 (2.9) | 209 (4.0) | <0.001 |
| Gout, n (%) | 673 (4.3) | 335 (6.5) | <0.001 |
| Lupus, n (%) | 215 (1.4) | 193 (3.7) | <0.001 |
| Psoriasis, n (%) | 560 (3.6) | 418 (8.1) | <0.001 |
| Rheumatoid arthritis, n (%) | 529 (3.4) | 424 (8.2) | <0.001 |
| Sarcoidosis, n (%) | 108 (0.7) | 51 (1.0) | 0.048 |
| Pericarditis, n (%) | 90 (0.6) | 65 (1.3) | <0.001 |
Data are presented as n (%) or mean ± SD.
p values were derived from Pearson’s chi-squared tests for categorical variables and unpaired t tests for continuous variables.
IBD, inflammatory bowel disease; SD, standard deviation; IQR, interquartile range.
Table 2.
Years between the first IBD diagnosis and the first pericarditis diagnosis
| Mean | Median | Q1 | Q3 | Min | Max |
|---|---|---|---|---|---|
| 4.12 | 1.21 | −1.06 | 10.27 | −11.22 | 30.09 |
Positive values indicate that the first IBD diagnosis preceded the first pericarditis diagnosis.
Negative values indicate that the first pericarditis diagnosis preceded the first IBD diagnosis.
IBD, Inflammatory bowel disease.
Table 3.
Multivariable, adjusted analysis of pericarditis and IBD
| Variable of interest | Multivariable OR (CI) | p value |
|---|---|---|
| Ankylosing spondylitis | 2.82 (2.03–3.90) | <0.001 |
| Diabetes type 1 | 1.33 (1.12–1.59) | <0.001 |
| Celiac disease | 2.70 (2.11–3.47) | <0.001 |
| Gout | 1.45 (1.25–1.67) | <0.001 |
| Obesity | 0.78 (0.73–0.84) | <0.001 |
| Psoriasis | 2.15 (1.87–2.46) | <0.001 |
| Rheumatoid arthritis | 2.07 (1.80–2.39) | <0.001 |
| Sarcoidosis | 1.11 (0.78–1.58) | 0.545 |
| SLE | 2.12 (1.72–2.61) | <0.001 |
| Pericarditis | 1.85 (1.32–2.59) | <0.001 |
One multivariable model was created to analyze the relationship between pericarditis and IBD, including potential confounders, such as significantly associated autoimmune diseases, with p < 0.15.
IBD, Inflammatory bowel disease; OR, odds ratio; CI, confidence interval; SLE, systemic lupus erythematosus.
Of the 5,178 IBD patients, 620 met the inclusion criteria for the mild disease cohort and 1,908 for the moderate/severe disease cohort. Of the 5,178 IBD patients, 1,190 had no record of IBD medications used for cohort classification, most likely due to incomplete EHR data. The Kaplan-Meier analysis was conducted over a maximum 15-year prospective follow-up period, with censoring for patients lost to follow-up or with incomplete EHR data, resulting in average follow-up times of 8.02 years for the mild cohort (total 4,969.5 person-years) and 8.07 years for the moderate/severe cohort (total 15,395.4 person-years). The mild cohort had 7 pericarditis events, yielding an incidence rate of 1.41 per 1,000 person-years. The moderate/severe cohort experienced 20 pericarditis events, yielding an incidence rate of 1.30 per 1,000 person-years. We found no significant difference in the pericarditis-free survival analyses between the mild and moderate/severe cohorts (p = 0.9) (shown in Fig. 1).
Fig. 1.
Kaplan-Meier analysis comparing time to pericarditis diagnosis in IBD severity-stratified cohorts with 15-year follow-up. The “remaining IBD patients” cohort consists of the IBD patients with a diagnosis of pericarditis who did not meet the criteria for either the mild or severe cohort. No significant difference in pericarditis rates was observed over the 15-year follow-up period.
Discussion
This study characterizes a significant association between IBD and pericarditis within a large US-based cohort. Patients with IBD were found to have 2.2-fold increased odds of developing pericarditis and 1.9-fold increased odds when controlling for potential confounders. This association was further supported by a sensitivity analysis excluding autoimmune/inflammatory comorbidities (p < 0.001), suggesting that the link is not solely attributable to overlapping systemic inflammatory conditions. Notably, IBD preceded pericarditis in 65% of cases (median −1.2 years), suggesting IBD more often acts as a trigger for pericarditis, possibly mediated by chronic systemic inflammatory cytokines IL-1β, IL-6, and TNF-α, which are significantly elevated in both IBD flares and pericarditis [8]. IL-1β, a key driver of inflammasome-mediated pericarditis, is targetable with inhibitors like anakinra, which have shown efficacy in recurrent pericarditis. TNF-α promotes systemic inflammation that may trigger pericarditis, but anti-TNF therapies may also rarely contribute to pericarditis, complicating attribution [9]. The mechanisms remain poorly understood, but proposed pathways include drug-induced lupus, allergic reactions, direct cardiac cellular toxicity, and immune activation (both cell mediated and humoral), warranting further investigation [9–11].
The higher prevalence of autoimmune/inflammatory conditions in IBD cases highlights the systemic inflammatory burden in these patients, which may predispose them to EIMs like pericarditis. Interestingly, we found a lower obesity rate in IBD cases (OR 0.78, 95% CI: 0.73%–0.84%, p < 0.001). The lower obesity rate in IBD cases may reflect chronic inflammation-induced cachexia or altered metabolism, potentially modulating EIM risk [12].
Our finding of increased likelihood of pericarditis development in IBD patients across disease severity levels underscores the need for heightened clinical awareness of pericarditis as a rare but significant EIM. We recommend incorporating symptom monitoring for pericarditis (e.g., chest pain, dyspnea) into routine IBD care, with prompt electrocardiogram (ECG) or echocardiogram evaluation for symptomatic patients, like protocols for other EIMs, such as uveitis, which often includes annual ophthalmologic exams [13, 14]. Given the low prevalence of pericarditis (1.3% in IBD cases), routine screening for asymptomatic patients may not be warranted; however, gastroenterologists should collaborate with cardiologists to develop targeted screening protocols for high-risk IBD patients, such as those with other EIMs or uncontrolled disease. Early recognition and treatment of pericarditis could reduce morbidity, such as progression to tamponade. Current guidelines, including the 2024 European Crohn’s and Colitis Organization (ECCO) guidelines for IBD and the 2025 Journal of the American College of Cardiology (JACC) guidelines for pericarditis, do not provide specific recommendations for diagnosis and management of pericarditis as an EIM [13, 14]. Our findings advocate for updating these guidelines to incorporate heightened awareness of pericarditis as an EIM and promote multidisciplinary collaboration between cardiologists and gastroenterologists to optimize patient care.
Kaplan-Meier survival analyses showed no significant difference in pericarditis-free survival between moderate/severe (n = 1,908) and mild (n = 620) IBD severity cohorts (p = 0.90), even after stratification by medication use. This finding challenges the assumption that pericarditis risk escalates with disease severity or treatment intensity, suggesting that pericarditis may manifest relatively consistently across the IBD spectrum (shown in Fig. 1). Another possible explanation for this observation is that medications commonly used in mild cases, such as mesalamine, may contribute to pericarditis risk, potentially masking severity-based differences. Case reports have linked mesalamine and, less commonly, anti-TNF therapies to drug-induced pericarditis, possibly through hypersensitivity or immune-mediated mechanisms [11, 15].
This study has several limitations that merit consideration. First, reliance on EHR data from the All of Us Research Program introduces potential misclassification bias, as diagnoses of IBD and pericarditis were based on SNOMED codes, which are not always accurate, and on a single EHR visit, which may not fully confirm clinical diagnoses. It also introduces potential selection bias in our survival analysis, as we had to exclude 1,190 IBD patients with incomplete EHR medication data. Although these patients were demographically similar to the included patients, suggesting limited bias, they may represent milder cases of IBD; if so, their exclusion contributed to the low number of pericarditis events in the mild IBD group, thereby decreasing the statistical power of our Kaplan-Meier survival analysis. The absence of data on medication dosage, duration, and adherence also limits our ability to distinguish IBD-driven pericarditis from drug-induced cases, particularly for cases involving mesalamine or TNF inhibitors [11, 15]. Another limitation was that our classification of IBD severity into moderate/severe and mild cohorts assumed guideline-concordant medication use, which may not accurately reflect disease severity or treatment adherence, potentially skewing survival analyses. Furthermore, the US-centric cohort may limit generalizability, as IBD prevalence and related diagnoses of EIMs can differ globally, especially in populations with lower IBD rates, such as the Black, Asian, and Hispanic groups [1]. While international literature suggests a low prevalence of pericarditis across populations, with no significant geographic variation, differences in healthcare access or diagnostic practices may influence detection rates [1, 3]. We acknowledge that our US-centric cohort may not fully reflect global patterns, particularly in regions with lower IBD prevalence (e.g., Asia and Africa), and we call for multicenter international studies to validate our findings.
Conclusion
This study uniquely provides evidence of a significant association between IBD and pericarditis, establishing pericarditis as a clinically significant EIM in a large, diverse US cohort. Our findings support integrating pericarditis screening into clinical practice guidelines for IBD management, including routine symptom assessment and targeted cardiac imaging for high-risk patients, to facilitate early diagnosis and treatment. This is particularly important, as IBD precedes pericarditis in most cases, as we observed. We also suggest that these findings could inform updates to pericarditis management guidelines to recognize pericarditis as an EIM and encourage multidisciplinary care involving cardiologists and gastroenterologists. The lack of association between IBD severity and pericarditis indicates that this EIM might occur at similar rates across all levels of IBD severity, challenging assumptions that associate pericarditis development with more severe disease or treatment side effects. These findings highlight the urgent need for heightened awareness and early recognition of pericarditis as an EIM to mitigate its substantial morbidity and mortality. Future research should elucidate the relative contributions of IBD-related inflammation and IBD therapies to the development of pericarditis. Additionally, the low event rate in our survival analysis underscores the need for larger cohorts or prospective studies to investigate further the impact of IBD severity on the development of various cardiac EIMs. Finally, studies in non-US cohorts, particularly among Black, Asian, and Hispanic populations with lower IBD prevalence, are needed to assess the global burden of pericarditis as an EIM. By fostering improved diagnostic vigilance, this work lays the groundwork for improved outcomes in IBD patients with pericarditis.
Acknowledgments
We gratefully acknowledge All of Us participants for their contributions, without whom this research would not have been possible. We also thank the National Institutes of Health’s All of Us Research Program for making available the participant data examined in this study.
Statement of Ethics
This study utilized the All of Us Research Program’s Registered Tier Dataset v7. The All of Us Research Program is approved by the Institutional Review Board (IRB) of the All of Us Research Program, ensuring compliance with ethical standards for human subjects research. All participants provided written informed consent for the use of their de-identified electronic health record data and other health-related information for research purposes, as part of their enrollment in the All of Us Research Program. Ethical approval and consent were not required as this study was based on publicly available data.
Conflict of Interest Statement
Dr. David Fudman reports receiving consulting and advisory board fees from Pfizer, Janssen, and Fresenius Kabi. The other authors have no conflicts of interest to declare.
Funding Sources
This study was not supported by any sponsor or funder.
Author Contributions
Conceptualization: All authors. Data curation: T.S. and B.W. Formal analysis: D.R., T.S., J.T.S., B.W., and M.S.G. Investigation: D.R. and T.S. Methodology: D.R., D.F., and M.S.G. Project administration: D.R. and M.S.G. Resources: T.S., B.W., and M.S.G. Software: T.S. Supervision: M.S.G. and D.R. Validation: T.S. Visualization: T.S., J.T.S., D.R., H.E., and N.P. Writing – original draft: D.R., T.S., N.P., and H.E. Writing – review and editing: All authors.
Funding Statement
This study was not supported by any sponsor or funder.
Data Availability Statement
The data that support the findings of this study are not publicly available due to privacy and ethical restrictions imposed by the All of Us Research Program. Access to the Registered Tier Dataset v7 is available to authorized users through the Researcher Workbench upon completion of the required registration, training, and approval processes. For more information on accessing the data, visit the All of Us Research Program website at [insert relevant URL, e.g., https://www.researchallofus.org/data-tools/workbench/].
Supplementary Material.
References
- 1. Lewis JD, Parlett LE, Jonsson Funk ML, Brensinger C, Pate V, Wu Q, et al. Incidence, prevalence, and racial and ethnic distribution of inflammatory bowel disease in the United States. Gastroenterology. 2023;165(5):1197–205.e2. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 2. Rogler G, Singh A, Kavanaugh A, Rubin DT. Extraintestinal manifestations of inflammatory bowel disease: current concepts, treatment, and implications for disease management. Gastroenterology. 2021;161(4):1118–32. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 3. Bhardwaj A, Singh A, Midha V, Sood A, Wander GS, Mohan B, et al. Cardiovascular implications of inflammatory bowel disease: an updated review. World J Cardiol. 2023;15(11):553–70. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 4. Cappell MS, Turkieh A. Chronic pericarditis and pericardial tamponade associated with ulcerative colitis. Dig Dis Sci. 2008;53(1):149–54. [DOI] [PubMed] [Google Scholar]
- 5. Patel RS, Rohit Reddy S, Llukmani A, Hashim A, Haddad DR, Patel DS, et al. Cardiovascular manifestations in inflammatory bowel disease: a systematic review of the pathogenesis and management of pericarditis. Cureus. 2021;13(3):e14010. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 6. Vecchié A, Chiabrando JG, Dell MS, Bonaventura A, Mauro AG, Wohlford G, et al. Clinical presentation and outcomes of acute pericarditis in a large urban Hospital in the United States of America. Chest. 2020;158(6):2556–67. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 7. Chang E, Mostafa J. The use of SNOMED CT, 2013-2020: a literature review. J Am Med Inform Assoc. 2021;28(9):2017–26. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 8. Xiao Y, Powell DW, Liu X, Li Q. Cardiovascular manifestations of inflammatory bowel diseases and the underlying pathogenic mechanisms. Am J Physiol Regul Integr Comp Physiol. 2023;325(2):R193–211. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 9. Klein AL, Imazio M, Cremer P, Brucato A, Abbate A, Fang F, et al. Phase 3 trial of Interleukin-1 trap rilonacept in recurrent pericarditis. N Engl J Med. 2021;384(1):31–41. [DOI] [PubMed] [Google Scholar]
- 10. Thiriveedi M, Steuber TD, Hasan M, Baggett A. Infliximab-Induced lupus causing pericarditis: a case report and review of the literature. J Gen Intern Med. 2021;36(7):2134–8. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 11. Dipasquale V, Gramaglia SMC, Catena MA, Romano C. Pericarditis during infliximab therapy in paediatric ulcerative colitis. J Clin Pharm Ther. 2018;43(1):107–9. [DOI] [PubMed] [Google Scholar]
- 12. Kaazan P, Seow W, Yong S, Heilbronn LK, Segal JP. The impact of obesity on inflammatory bowel disease. Biomedicines. 2023;11(12):3256. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 13. Gordon H, Burisch J, Ellul P, Karmiris K, Katsanos K, Allocca M, et al. ECCO Guidelines on extraintestinal manifestations in inflammatory bowel disease. J Crohns Colitis. 2024;18(1):1–37. [DOI] [PubMed] [Google Scholar]
- 14. Wang TKM, Klein AL, Cremer PC, Imazio M, Kohnstamm S, Luis SA, et al. Concise clinical guidance: an ACC expert consensus statement on the diagnosis and management of pericarditis: a report of the American college of Cardiology Solution Set Oversight Committee. J Am Coll Cardiol. 2025;86(25):2691–719. [DOI] [PubMed] [Google Scholar]
- 15. Karki P, Kunwar A, Sharma N, Dogra M. Recurrent pericarditis: a rare adverse effect of mesalamine. Cureus. 2023;15(1):e33661. [DOI] [PMC free article] [PubMed] [Google Scholar]
Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Supplementary Materials
Data Availability Statement
The data that support the findings of this study are not publicly available due to privacy and ethical restrictions imposed by the All of Us Research Program. Access to the Registered Tier Dataset v7 is available to authorized users through the Researcher Workbench upon completion of the required registration, training, and approval processes. For more information on accessing the data, visit the All of Us Research Program website at [insert relevant URL, e.g., https://www.researchallofus.org/data-tools/workbench/].
