The predictive value of aGAPSS score combined with clinical factors for thrombosis in systemic lupus erythematosus
In brief
Clinical factors raise lupus thrombosis prediction accuracy beyond aGAPSS alone
In 309 hospitalized patients with systemic lupus, a model combining the antiphospholipid score with age, smoking, disease activity and a lupus anticoagulant measure better distinguished patients with in-hospital thrombosis than the score alone. Its area under the curve was 0.83 versus 0.69, but the retrospective study was internally validated only, so its usefulness for guiding prevention needs testing in other groups.
- Journal
- Frontiers in cellular and infection microbiology (Q1)
- Published
- 18 September 2026
- Study design
- Cohort / observational study
- Evidence level
- Level 3, Low (CEBM 3b)
- Authors
- Juan Shi, Libo Ouyang, Qiong Ma, Peiming Zheng
- PMID
- 42827675
- DOI
- 10.3389/fcimb.2026.1909515
Why clinicians should know about it
- Picked for Rheumatology (paper of the day, 6 October 2026): aGAPSS + clinical factors predict thrombosis in SLE
Abstract
PURPOSE: This study evaluated the predictive value of antiphospholipid antibodies (aPLs) combined with the adjusted global antiphospholipid syndrome score (aGAPSS) for thrombosis in hospitalized systemic lupus erythematosus (SLE) patients. METHODS: A retrospective analysis included 309 SLE patients (65 with in-hospital thrombosis, 244 without). Demographic, clinical, and serological data were collected. Least absolute shrinkage and selection operator (LASSO) regression and multivariate logistic regression identified independent risk factors. A combined predictive model was constructed and internally validated using bootstrap. RESULTS: Patients with thrombosis were older, had higher smoking prevalence, LA ratio, and aGAPSS (all P < 0.05). Disease activity was significantly higher in the thrombosis group, as reflected by a higher mean SLEDAI score (14.29 ± 2.88 vs. 12.45 ± 1.62, P < 0.001). Multivariate analysis identified age (OR = 1.053), smoking (OR = 2.945), SLEDAI (OR = 1.312), LA ratio (OR = 17.432), and aGAPSS (OR = 1.514) as independent predictors. The combined model (aGAPSS + clinical covariates) achieved an area under the curve (AUC) of 0.832, significantly outperforming aGAPSS alone (AUC = 0.693; ΔAUC = 0.139, P < 0.001), with NRI of 0.356 and IDI of 0.142. CONCLUSION: Integrating aGAPSS with clinical factors provides good discriminative ability for in-hospital thrombosis risk stratification in hospitalized SLE patients, offering a practical tool that may inform surveillance intensity and prophylactic consideration.
Abstract as published, via PubMed.
For healthcare professionals. The summary is generated by AI from the published abstract, and the evidence level is assigned automatically from the study design on the Oxford CEBM hierarchy. Neither is medical advice. Read the full paper before changing practice.