Minimizing delays in systemic lupus erythematosus diagnosis: a proposed diagnostic algorithm from symptom onset to rheumatology referral.

Systemic lupus erythematosus (SLE) is a chronic, multisystem autoimmune disease with heterogeneous clinical manifestations that complicate recognition and delay diagnosis, contributing to substantial clinical, emotional, and socioeconomic burden. SLE mainly affects women (female:male ratio ≈ 9:1) during their reproductive years. It should be identified early in primary care to shorten the time to specialist referral. An expert working group was formed to discuss strategies to accelerate SLE recognition and referral in Croatia. It was composed of five rheumatologists/clinical immunologists from tertiary centers with experience in treating SLE patients. They searched Medline/PubMed for articles on diagnostic delay in SLE. During three meetings, local-specific barriers were identified, and a women-specific diagnostic algorithm and educational plan for primary care physicians (PCPs) were developed. Key barriers included limited SLE awareness among PCPs, nonspecific and multiorgan presentations, absence of specific diagnostic tests, reliance on classification criteria, insufficient training and referral protocols, workforce overload, and shortages of rheumatologists/immunologists, leading to multiple unnecessary referrals before specialist assessment. The group developed an expert proposal aimed at reducing diagnostic delays in patients with suspected SLE. Patients should be promptly referred to a rheumatologist/immunologist when ≥1 clinical symptom (arthralgia/myalgia/malar rash/photosensitivity/alopecia/oral ulceration/fatigue/fever) is accompanied by elevated erythrocyte sedimentation rate and ≥1 laboratory abnormality (urinary abnormalities, hypocomplementemia, or cytopenias). The proposed training strategy consists of interactive workshops (≤10 PCPs) using clinical cases, organized through regional primary care managers. A pilot study is planned in which trained PCPs would apply the algorithm to their patients to evaluate its impact on diagnostic delay.