Background Very limited data is available on the epidemiology of systemic Lupus erythematosus (SLE) in the Caribbean. This study was aimed at analysing the demographic data among patients diagnosed with SLE in the South and Central regions of Trinidad.

Materials and method This was a retrospective analysis of patients attending the Rheumatology Clinic at the South-West Regional Health Authority. After written consent was obtained, a data capture sheet (DCS) was completed; collecting information from patients with suspected SLE. Each patient was given a unique identification number. From this DCS, patients with a confirmed diagnosis of SLE (defined by at least 4 criteria of the Systemic Lupus International Collaborating Clinics (SLICC) Classification Criteria for SLE, of which at least 1 clinical and 1 laboratory criteria OR biopsy-proven lupus nephritis with positive ANA or Anti- dsDNA) were identified. The information was entered into a specially designed excel database, which was later transferred into the SPSS version 22 for Windows for analysis. Frequent edit checks were done.

Results Of the 169 patients on the database, to date, 91 were confirmed with SLE. Demographic variables are shown in Table 1. Among the patients with confirmed SLE 50.50% were Indo-Trinidadian, 26.40% were Afro-Trinidadian and 23.10% were of Mixed Ethnicity. Females accounted for 96.70% of the 91 patients. Mean (SD) age was 39.47 (15.22) years, the youngest was 5 years old and the eldest 74 years old. The most common religious affiliation was Hinduism (20.90%), closely followed by Pentecostal/Evangelical/Full Gospel (19.80%) and then Roman Catholic (15.40%).

Conclusion An unexpectedly high percentage of our patients were of East Indian origin. It is not clear whether this is a reflection of the ethnic background of the regional population being evaluated, or if this is a previously unidentified occurrence. Detailed epidemiologic studies would be necessary to address this question. Understanding this disease in our population has implications for resource allocation and access to subspecialty care.

Acknowledgements We would like to thank Mr. Darien Wong for his initial work on the DCS, which was later modified and used for data collection.

We would also like to thank Mr. Jared Ramkissoon for creating the excel database which was used to record all the data prior to its transfer to the SPSS program.

Special thanks to the Doctors of the Rheumatology Unit who aided in the Ethical Approval of our project as well as in the collection of data on the DCS- Dr Sobrina Mohammed, Dr Alicia Ramnath, Dr Malini Basdeo, Dr Amrika Samsundar, as well as the Interns who worked with us over the last five months.

Thanks to Dr. Peter Poon King for assistance with the rheumatology clinics.

Finally, thanks to Ms. Havisha Sankar for assisting with the collection of some of the data; and its inputting into the excel database.