OBJECTIVES
To examine whether patients with autoimmune diseases receive differential cardiometabolic and inflammatory laboratory monitoring compared to matched controls in primary care, and to identify predictors of monitoring patterns.
METHODS
We conducted a matched case-control study using electronic health records from the Primary Health Care Corporation (PHCC), Qatar (January 2015 to December 2024). Adults with Hashimoto's thyroiditis, rheumatoid arthritis (RA), or systemic lupus erythematosus (SLE) were matched 1:2 to controls without autoimmune disease on age and sex. Primary outcomes were receipt of cardiometabolic tests (haemoglobin A1c [HbA1c], complete lipid panel) and inflammatory markers (C-reactive protein [CRP], erythrocyte sedimentation rate [ESR]). We used conditional logistic regression adjusting for comorbidities, medications, and healthcare utilisation.
RESULTS
Among 27,911 participants (9,356 cases, 18,555 controls; mean age 46.7 years; 74.4% female) in 9,356 matched sets, we observed divergent monitoring patterns. Compared to controls, patients with RA had significantly lower odds of HbA1c monitoring (OR 0.77, 95% CI 0.69-0.85) and complete lipid panels (OR 0.74, 95% CI 0.67-0.82). Similar patterns were observed for SLE (HbA1c: OR 0.67, 95% CI 0.57-0.80; lipid: OR 0.60, 95% CI 0.51-0.70). Conversely, RA patients had 4.2-fold higher odds of CRP testing and 4.4-fold higher odds of ESR testing; SLE patients showed similar elevations (3.7-fold and 4.2-fold, respectively). Hashimoto's patients showed modestly increased monitoring across all test types (HbA1c: OR 1.45, 95% CI 1.23-1.70).
CONCLUSIONS
Despite elevated cardiovascular risk, patients with systemic autoimmune diseases (RA, SLE) receive less cardiometabolic laboratory monitoring than matched controls while receiving substantially more inflammatory marker testing. This differential monitoring pattern - which we describe as a "monitoring gap paradox" and which persisted across sensitivity analyses - is consistent with care coordination challenges at the primary care-specialty interface. The observational design precludes inferences about the underlying causes, but the findings identify a potential quality improvement opportunity warranting further investigation.
Aisha Al-Khinji, D. Malouche, A. Al-Hor et al.· Journal of Translational Med...· 0 citations
Health status influences COVID-19 vaccine uptake, with vaccinated individuals generally being healthier than unvaccinated ones. This difference may impact vaccine effectiveness estimates. This study investigated the magnitude of this healthy vaccinee effect on effectiveness estimates. Three national, matched, retrospective cohort studies were conducted on Qatar’s population from February 5, 2020-May 14, 2024, to estimate effectiveness of primary-series and booster vaccinations and of natural infection against infection and severe, critical, or fatal COVID-19. The studies explored three matching scenarios by coexisting conditions, reflecting varying levels of health-status imbalance between vaccinated and unvaccinated individuals. Each matched cohort included >810,000 individuals in the primary-series analysis, >330,000 in the booster analysis, and >730,000 in the natural-infection analysis. Effectiveness was derived from adjusted hazard ratios estimated using Cox regression models. Here we show that vaccine effectiveness against infection and severe, critical, or fatal COVID-19 remained consistent across matching strategies, despite differences in non-COVID-19 mortality. For example, primary-series effectiveness against severe COVID-19 was 96.3% (95% CI: 94.5–97.5) when matching by exact coexisting conditions, 94.2% (95% CI: 92.5–95.6) when matching by number of coexisting conditions, and 94.0% (95% CI: 92.3–95.3) with no matching by coexisting conditions. Similar results were observed in subgroup analyses by follow-up duration and among clinically vulnerable individuals. Comparable findings applied to natural infection’s effectiveness against reinfection and severe COVID-19. Health status differences between vaccinated and unvaccinated individuals did not introduce measurable bias in real-world vaccine effectiveness estimates. Findings highlight the importance of using specific outcomes in vaccine effectiveness studies.
H. Chemaitelly, H. Ayoub, Peter V. Coyle et al.· Communications Health· 0 citations