The incidence of pulmonary embolism (PE) is high during severe Coronavirus Disease 2019 (COVID-19). We aimed to identify predictive and prognostic factors of PE in non-ICU hospitalized COVID-19 patients. In the retrospective multicenter observational CLOTVID cohort, we enrolled patients with confirmed RT-PCR COVID-19 who were hospitalized in a medicine ward and also underwent a CT pulmonary angiography for a PE suspicion. Baseline data, laboratory biomarkers, treatments, and outcomes were collected. Predictive and prognostics factors of PE were identified by using logistic multivariate and by Cox regression models, respectively. A total of 174 patients were enrolled, among whom 86 (median [IQR] age of 66 years [55–77]) had post-admission PE suspicion, with 30/86 (34.9%) PE being confirmed. PE occurrence was independently associated with the lack of long-term anticoagulation or thromboprophylaxis (OR [95%CI], 72.3 [3.6–4384.8]) D-dimers ≥ 2000 ng/mL (26.3 [4.1–537.8]) and neutrophils ≥ 7.0 G/L (5.8 [1.4–29.5]). The presence of these two biomarkers was associated with a higher risk of PE (p = 0.0002) and death or ICU transfer (HR [95%CI], 12.9 [2.5–67.8], p < 0.01). In hospitalized non-ICU severe COVID-19 patients with clinical PE suspicion, the lack of anticoagulation, D-dimers ≥ 2000 ng/mL, neutrophils ≥ 7.0 G/L, and these two biomarkers combined might be useful predictive markers of PE and prognosis, respectively.

Objective: We aimed to assess the prevalence of clonal haematopoiesis (CH) in patients with giant cell arteritis (GCA) compared with controls and individuals with other autoimmune diseases (AIDs) and to identify high-risk clinical/genetic profiles that could influence disease outcomes. Methods: In a prospective observational study at three hospitals, we included 49 patients diagnosed with GCA, 48 patients with other AIDs and 27 control participants. We used next-generation sequencing to detect clonal haematopoiesis (CH) among them. Results: CH was detected in 55.1% of patients with GCA, 59.3% of controls and 18.8% of patients with other AIDs. The most commonly mutated genes in GCA and control groups were DNMT3A and TET2. No significant differences in CH prevalence were found between patients with GCA and controls or other AID when adjusted for age and sex. Cluster analysis revealed two distinct groups within the patients with GCA, one of which displayed a higher prevalence of TET2 and JAK2 variants, and was associated with worse prognosis. Conclusions: CH is prevalent among patients with GCA but does not differ significantly from controls or other autoimmune conditions. However, specific genetic profiles, particularly mutations in TET2 and JAK2, are associated with a higher risk cluster within the GCA cohort. This observation highlights the interest of detecting CH in patients with GCA in both routine practice and clinical trials for better risk stratification. Further prospective studies are needed to determine if management tailored to the genetic profile would improve outcomes.