Volume-12, Issue-9, September 2026

Abstract

Rheumatoid arthritis (RA) is a systemic, chronic autoimmune disease defined by progressive synovial inflammation, structural joint damage, and widespread systemic complications. Despite significant advances in targeted synthetic and biological disease-modifying antirheumatic drugs (DMARDs), patients frequently experience acute exacerbations of disease activity known as flares. These periods of intensified pain, joint swelling, morning stiffness, and systemic fatigue significantly impair functional capacity, reduce health-related quality of life, and contribute to long-term radiographic joint damage if left unmanaged. This paper provides an evidence-based clinical analysis of the recognition, pathobiological mechanisms, and structured management of RA flares. It proposes a six-step action plan integrating validated disease activity metrics, biomarker monitoring, patient-reported outcome measures (PROMs), pharmacological escalation protocols, non-pharmacological therapies, and self-management strategies. By standardizing flare recognition and clinical response, healthcare providers can mitigate structural damage, optimize patient autonomy, and improve long-term disease outcomes.

Keywords: Rheumatoid arthritis flare, DAS28, CDAI disease activity, Inflammatory synovitis, Corticosteroid bridging therapy, DMARD optimization, Treat-to-Target (T2T) strategy.

References

1. Alivernini, S., MacDonald, L., Elmesmari, A., Finlay, S., Tolusso, B., Gigante, M. R., et al. (2020). Distinct synovial macrophage subsets drive remission and relapse in rheumatoid arthritis. Nature Medicine, *26*(8), 1295-1306.
2. Aletaha, D., & Smolen, J. S. (2005). The Simplified Disease Activity Index (SDAI) and the Clinical Disease Activity Index (CDAI): A review of their usefulness and validity in clinical practice and research. Rheumatic Disease Clinics of North America, *31*(4), 773-786.
3. Alten, R., Christensen, R., Bingham III, C. O., Almeida, C., Hewlett, S., Kirwan, J., et al. (2011). Measurement of rheumatoid arthritis flares: The OMERACT RA Flare Questionnaire (RA-FQ). Journal of Rheumatology, *38*(8), 1745-1752.
4. Brosseau, L., Yonge, K. A., Robinson, V., Marchand, S., Judd, M., Wells, G. A., et al. (2003). Thermotherapy for treating rheumatoid arthritis. Cochrane Database of Systematic Reviews, (4), CD002826.
5. Bykerk, V. P., Shadick, N., Frits, M. L., Bingham III, C. O., Iannaccone, C. K., Glass, R. J., et al. (2014). Flares in rheumatoid arthritis: Frequency and association with 2-year radiographic progression. Arthritis Care & Research, *66*(1), 38-46.
6. Flurey, C. A., Morris, M., Richards, P., Hughes, R., & Hewlett, S. (2014). It's localized, it's generalized, it's severe: How patients perceive the onset of rheumatoid arthritis flares. Musculoskeletal Care, *12*(4), 227-236.
7. Fraenkel, L., Bathon, J. M., England, B. R., St Clair, E. W., Arayssi, T., Carandang, K., et al. (2021). 2021 American College of Rheumatology Guideline for the Treatment of Rheumatoid Arthritis. Arthritis & Rheumatology, *73*(7), 1108-1123.
8. Garip, Y., Eser, F., Bodur, H., & Yilmaz, O. (2011). Sleep quality in rheumatoid arthritis: Relationship with disease activity, fatigue, depression, and functional status. Rheumatology International, *31*(11), 1453-1456.
9. Gartlehner, G., Patel, S. V., Feltner, C., Weber, R. P., Long, R., Mullican, K., et al. (2021). Defining and measuring flares in rheumatoid arthritis: A systematic review for OMERACT. Annals of the Rheumatic Diseases, *80*(6), 712-721.
10. Haschka, J., Englbrecht, M., Hueber, A. J., Hayer, S., Englert, S., Simon, D., et al. (2016). Relapse rates in patients with rheumatoid arthritis in stable remission tapering or stopping antirheumatic therapy: Interim results of the RETRO study. Annals of the Rheumatic Diseases, *75*(1), 45-51.
11. Matcham, F., Rayner, L., Steer, S., & Hotopf, M. (2016). The association between depression and disease activity in rheumatoid arthritis: A systematic review and meta-analysis. Rheumatology, *55*(12), 2136-2148.
12. McInnes, I. B., & Schett, G. (2011). The pathogenesis of rheumatoid arthritis. New England Journal of Medicine, *365*(23), 2205-2219.
13. Meeus, M., Vervisch, S., De Clerck, L. S., Moorkens, G., Hans, G., & Nijs, J. (2012). Central sensitization in patients with rheumatoid arthritis: A systematic review. Seminars in Arthritis and Rheumatism, *41*(4), 556-567.
14. Nygaard, G., & Firestein, G. S. (2020). Restoring joint homeostasis in rheumatoid arthritis by targeting fibroblast-like synoviocytes. Nature Reviews Rheumatology, *16*(6), 316-333.
15. Pincus, T., Swearingen, C. J., & Yazici, Y. (2008). RAPID3 (Routine Assessment of Patient Index Data 3), a rheumatoid arthritis index without formal joint counts for routine care: Validity and reliability. Journal of Rheumatology, *35*(11), 2136-2143.
16. Schiff, M. H., Jaffe, J. S., & Freundlich, B. (2014). Head-to-head clinical trial of subcutaneous methotrexate versus oral methotrexate in rheumatoid arthritis. Annals of the Rheumatic Diseases, *73*(6), 1049-1054.
17. Smolen, J. S., Aletaha, D., & McInnes, I. B. (2018). Rheumatoid arthritis. Lancet, *392*(10147), 615-628.
18. Smolen, J. S., Breedveld, F. C., Schiff, M. H., Kalden, J. R., Emery, P., Eberl, G., et al. (2003). A simplified disease activity index for rheumatoid arthritis for use in clinical practice. Rheumatology, *42*(2), 244-257.
19. Smolen, J. S., Landewé, R. B. M., Bijlsma, J. W. J., Burmester, G. R., Dougados, M., Kerschbaumer, A., et al. (2020). EULAR recommendations for the management of rheumatoid arthritis with synthetic and biological disease-modifying antirheumatic drugs: 2019 update. Annals of the Rheumatic Diseases, *79*(6), 685-699.
20. Straub, R. H., & Cutolo, M. (2018). Psychoneuroimmunology–inflammatory mechanisms in rheumatoid arthritis. Nature Reviews Rheumatology, *14*(10), 603-616.
21. Strehl, C., Bijlsma, J. W., de Wit, M., Boers, M., Caeyers, N., Cutolo, M., et al. (2016). Defining conditions where long-term glucocorticoid treatment has an acceptable low-risk profile in rheumatoid arthritis. Annals of the Rheumatic Diseases, *75*(6), 952-957.
22. van der Heijde, D. M., van 't Hof, M. A., van Riel, P. L., Theunisse, L. A., Lubberts, E. W., van Leeuwen, M. A., et al. (1990). Judging disease activity in clinical practice in rheumatoid arthritis: First step in the development of a disease activity score. Annals of the Rheumatic Diseases, *49*(11), 916-920.
23. Vriezekolk, J. E., Geenen, R., Hartkamp, A., Godaert, G. L., van Booma, A., & Bijlsma, J. W. (2012). Psychological variables associated with pain and fatigue in rheumatoid arthritis: A structural equation modeling approach. Journal of Psychosomatic Research, *73*(5), 376-382.

Abstract

Background: Coronary artery variations encompass a heterogeneous group of developmental and morphological phenotypes whose clinical expression may differ according to subtype and patient characteristics. Population-specific data from North Africa remain limited.

Methods: This multicentre retrospective cross-sectional study analysed 200 Libyan adults aged 26–85 years who underwent coronary assessment at three referral centres. Coronary artery variation status and phenotype were abstracted from coronary imaging reports together with demographic, anthropometric, cardiovascular risk, and symptom data. Descriptive statistics, chi-square tests, Monte Carlo procedures for sparse contingency tables, Cramér's V, and one-way analysis of variance were used as appropriate.

Results: Coronary artery variations were identified in 87/200 participants (43.5%). Among variation-positive cases, anomalous origin/ostial variants were most frequent (33/87, 37.9%), followed by other/unspecified patterns (17.2%), branching/length variants (14.9%), ectasia/aneurysm (13.8%), myocardial bridging (10.3%), and interarterial/intramural courses (5.7%). Phenotype distribution differed by sex (Monte Carlo p=0.004), whereas no significant association was observed with age band (Monte Carlo p=0.243). Palpitations occurred more frequently in participants with a coronary variation than in those without one (19.5% vs 8.8%; χ²=4.811, p=0.028; V=0.155), although the effect size was small. Mean body mass index did not differ across variation phenotypes (F(5,81)=0.483, p=0.788).

Conclusion: Coronary artery variation phenotypes were common in this clinically referred Libyan cohort and showed distinct sex-related patterns and a modest association with palpitations. Phenotype-level anatomical reporting may add clinically useful information beyond recording the presence or absence of a coronary variation.

Keywords: coronary artery variations; coronary anomalies; coronary anatomy; Libya; coronary imaging; myocardial bridging; palpitations.

References

1. Kim, S. Y., Seo, J. B., Do, K. H., Heo, J. N., Lee, J. S., Song, J. W., et al. (2006). Coronary artery anomalies: Classification and ECG-gated multi-detector row CT findings with angiographic correlation. RadioGraphics, 26(2), 317-333. https://doi.org/10.1148/rg.262055068
2. Beecham, R., Prater, S., & Batlle, J. (2026). Coronary artery anomalies. In StatPearls. StatPearls Publishing.
3. Gurvitz, M., Krieger, E. V., Fuller, S., et al. (2026). 2025 ACC/AHA/HRS/ISACHD/SCAI guideline for the management of adults with congenital heart disease: A report of the American College of Cardiology/American Heart Association Joint Committee on Clinical Practice Guidelines. Journal of the American College of Cardiology, 87(7), 822-976. https://doi.org/10.1016/j.jacc.2025.09.006
4. Stout, K. K., Daniels, C. J., Aboulhosn, J. A., et al. (2019). 2018 AHA/ACC guideline for the management of adults with congenital heart disease. Journal of the American College of Cardiology, 73(12), e81-e192. https://doi.org/10.1016/j.jacc.2018.08.1029
5. Yamanaka, O., & Hobbs, R. E. (1990). Coronary artery anomalies in 126,595 patients undergoing coronary arteriography. Catheterization and Cardiovascular Diagnosis, 21(1), 28-40. https://doi.org/10.1002/ccd.1810210110
6. Angelini, P., Velasco, J. A., & Flamm, S. (2002). Coronary anomalies: Incidence, pathophysiology, and clinical relevance. Circulation, 105(20), 2449-2454. https://doi.org/10.1161/01.CIR.0000016175.49835.57
7. Graidis, C., Dimitriadis, D., Karasavvidis, V., Dimitriadis, G., Argyropoulou, E., Economou, F., et al. (2015). Prevalence and characteristics of coronary artery anomalies in an adult population undergoing multidetector-row computed tomography for the evaluation of coronary artery disease. BMC Cardiovascular Disorders, 15, 112. https://doi.org/10.1186/s12872-015-0098-x
8. Ghadri, J. R., Kazakauskaite, E., Braunschweig, S., et al. (2014). Congenital coronary anomalies detected by coronary computed tomography compared to invasive coronary angiography. BMC Cardiovascular Disorders, 14, 81. https://doi.org/10.1186/1471-2261-14-81
9. Ganga, K. P., Goyal, A., Ojha, V., Deepti, S., Sharma, S., & Kumar, S. (2021). Prevalence rates of congenital coronary anomalies and coronary variations in adult Indian population using dual-source computed tomography coronary angiography: Analysis of regional distribution of coronary anomalies and the need for standardized reporting formats. Indian Journal of Radiology and Imaging, 31(1), 138-149. https://doi.org/10.1055/s-0041-1730135
10. Al-Balas, H., Mouhsen, A. M., Ababneh, G. E., Alkhalqi, M. A., Alomari, S. A., Jarrah, H. M., & Alotaibi, A. H. (2026). Prevalence and spectrum of coronary artery anomalies detected on coronary CT angiography. International Journal of Cardiology Cardiovascular Risk and Prevention, 29, 200614. https://doi.org/10.1016/j.ijcrp.2026.200614
11. Taylor, A. J., Cerqueira, M., Hodgson, J. McB., et al. (2010). ACCF/SCCT/ACR/AHA/ASE/ASNC/NASCI/SCAI/SCMR appropriate use criteria for cardiac computed tomography. Journal of the American College of Cardiology, 56(22), 1864-1894. https://doi.org/10.1016/j.jacc.2010.07.005
12. Ouali, S., Neffeti, E., Sendid, K., Elghoul, K., Remedi, F., & Boughzela, E. (2009). Congenital anomalous aortic origins of the coronary arteries in adults: A Tunisian coronary arteriography study. Archives of Cardiovascular Diseases, 102(3), 201-208. https://doi.org/10.1016/j.acvd.2009.01.001
13. von Elm, E., Altman, D. G., Egger, M., Pocock, S. J., Gøtzsche, P. C., & Vandenbroucke, J. P. (2007). The Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) statement: Guidelines for reporting observational studies. Lancet, 370(9596), 1453-1457. https://doi.org/10.1016/S0140-6736(07)61602-X
14. Andishmand, A., Montazerghaem, H., Pedarzadeh, A., Varastehravan, H. R., Mohammadi, H., Nafisi Moghadam, R., et al. (2023). Prevalence and characteristics of coronary artery anomalies (CAAs) in 3016 symptomatic adult participants undergoing coronary computed tomography angiography (CCTA): A single-center retrospective study in Iran. Journal of Cardiovascular and Thoracic Research, 15(4), 218-222. https://doi.org/10.34172/jcvtr.2023.32860
15. Alshumrani, G. A. (2024). High prevalence of anatomical variations and anomalies of the coronary arteries detected by CT angiography in symptomatic patients. Congenital Heart Disease, 19(2), 197-206. https://doi.org/10.32604/chd.2024.049401
16. Sidhu, N. S., Wander, G. S., Monga, A., & Kaur, A. (2019). Incidence, characteristics and atherosclerotic involvement of coronary artery anomalies in adult population undergoing catheter coronary angiography. Cardiology Research, 10(6), 358-368. https://doi.org/10.14740/cr941
17. Li, K., Hu, P., Luo, X., et al. (2024). Anomalous origin of the coronary artery: Prevalence and coronary artery disease in adults undergoing coronary tomographic angiography. BMC Cardiovascular Disorders, 24(1), 271. https://doi.org/10.1186/s12872-024-03942-8
18. Basso, C., Maron, B. J., Corrado, D., & Thiene, G. (2000). Clinical profile of congenital coronary artery anomalies with origin from the wrong aortic sinus leading to sudden death in young competitive athletes. Journal of the American College of Cardiology, 35(6), 1493-1501. https://doi.org/10.1016/S0735-1097(00)00566-0
19. Doan, T. T., Wilkes, J. K., Reaves-O'Neal, D. L., et al. (2023). Clinical presentation and medium-term outcomes of children with anomalous aortic origin of the left coronary artery: High-risk features beyond interarterial course. Circulation: Cardiovascular Interventions, 16(5), e012635. https://doi.org/10.1161/CIRCINTERVENTIONS.122.012635
20. Yousif, N., Shahin, M., Lüscher, T. F., & Obeid, S. (2019). Gender differences in types, frequency, clinical manifestations and atherosclerotic burden of coronary artery anomalies. Reviews on Recent Clinical Trials, 14(1), 41-46. https://doi.org/10.2174/1574887113666180820111341
21. Akpinar, I., Sayin, M. R., Karabag, T., Gursoy, Y. C., Kucuk, E., Kiran, S., et al. (2013). Differences in sex, angiographic frequency, and parameters in patients with coronary artery anomalies: Single-center screening of 25,368 patients by coronary angiography. Coronary Artery Disease, 24(4), 266-271. https://doi.org/10.1097/MCA.0b013e32835faf43
22. Möhlenkamp, S., Hort, W., Ge, J., & Erbel, R. (2002). Update on myocardial bridging. Circulation, 106(20), 2616-2622. https://doi.org/10.1161/01.CIR.0000038420.14867.7A
23. Alegria, J. R., Herrmann, J., Holmes, D. R., Jr., Lerman, A., & Rihal, C. S. (2005). Myocardial bridging. European Heart Journal, 26(12), 1159-1168. https://doi.org/10.1093/eurheartj/ehi203
24. Devabhaktuni, S., Mercedes, A., Diep, J., & Ahsan, C. (2016). Coronary artery ectasia—A review of current literature. Current Cardiology Reviews, 12(4), 318-323. https://doi.org/10.2174/1573403X12666160504100159
25. Angelini, P. (2007). Coronary artery anomalies: An entity in search of an identity. Circulation, 115(10), 1296-1305. https://doi.org/10.1161/CIRCULATIONAHA.106.618082