Microbiota and arthritis: cause or consequence?

The relationship between intestinal microbiota and arthritis has garnered significant attention, with emerging evidence suggesting a potential association between dysbiosis and various forms of inflammatory arthropathies. While observational studies have provided valuable insights into microbiota alterations in patients with arthritis, establishing causality remains challenging. Observational data, influenced by multiple confounders such as environmental factors, medication effects, and dietary habits, are insufficient to conclusively determine whether microbiota changes are somehow causally linked to arthritis. The heterogeneity of results across independent studies further complicates interpretation. To further support this hypothesis, interventional randomised trials are deemed necessary, yet their implementation in this area presents significant technical limitations. Experimental animal models offer insights into potential pathogenic mechanisms linking dysbiosis to arthritis, including compromised intestinal barrier function, the role of microbiota-derived metabolites and molecular mimicry. However, conflicting findings underscore the complexity of hostmicrobiota interactions and the challenges in establishing causality.Efforts to modulate the microbiota for arthritis treatment or prevention have shown promise, yet efficacy and applicability remains uncertain. Antibacterial drugs, dietary interventions, probiotics, and faecal microbiota transplantation have been explored, but their clinical utility awaits further validation. In conclusion, while the association between intestinal microbiota and arthritis is increasingly recognised, establishing causality remains elusive.

Adding the value of the Charlson Comorbidity Index to the GRACE score for mortality prediction in acute coronary syndromes.

BACKGROUND: Scarce and conflicting data still exist about the role of the Charlson Comorbidity Index (CCI) when added to the traditional Global Registry of Acute Coronary Events (GRACE) risk score for outcome prediction in patients with acute coronary syndrome (ACS). METHODS: All consecutive admissions due to ACS, from 1 January 2018 to 31 December 2020 were retrospectively reviewed from an internal database of a tertiary cardiac center in Salerno (Italy). Logistic and Cox proportional regression analyses were performed in order to assess the contribution of the CCI on 30-day and long-term mortality. The CCI adding value to the GRACE score was analyzed with several measures of improvement in discrimination: increase in the area under the receiver-operating characteristic curve (AUC), the integrated discrimination improvement (IDI), and the categorical and continuous net reclassification improvement (cNRI) more than 0. Robustness of the results was assessed through an internal validation procedure with bootstrapping. RESULTS: One thousand three hundred and ten patients were identified. The median age was 68 (58-78) years. One hundred and twenty (9.2%) and 113 (9.5%) deaths occurred, respectively, during the first 30 days from admission and during long-term follow-up (median follow-up time: 13 months; interquartile range: 9-24). After multivariate regression analysis, the CCI was not associated with short-term mortality, while it was significantly and independently associated with long-term mortality along with the GRACE score (hazard ratio: 1.34, 95% confidence interval: 1.22-1.47; P  < 0.001). An additive effect of CCI with the GRACE risk score was observed in predicting long-term mortality: AUC from 0.768 to 0.819 ( P  = 0.003), category-based NRI: 0.215, cNRI>0: 0.669 ( P  < 0.001), IDI: 0.066 ( P  < 0.001). CONCLUSION: The CCI is a predictor of long-term mortality and improves risk stratification of patients with ACS over the GRACE risk score.