Association of serum concentrations of remnant cholesterol with incident cardiovascular disease in patients with rheumatoid arthritis: A real-world data from 2001 to 2022.

BACKGROUND: Remnant cholesterol (RC) promotes cardiovascular disease (CVD) in the general population, but its role among rheumatoid arthritis (RA) patients remains unknown. We aimed to investigate circulating RC levels associated with incident CVD among Chinese patients with RA. METHODS: A total of 1018 RA patients free of baseline CVD were included and followed up in a prospective RA CVD cohort from 2001 to 2022. Fasting serum levels of triglycerides, total cholesterol (TC), low-density (LDL-C), and high-density lipoprotein cholesterol (HDL-C) were measured, while RC and Non-HDL-C levels were calculated. The primary exposure was RC levels. A LASSO Cox model was used to select covariates. The Fine-Gray competing risk model was used to estimate hazard ratios (HRs). RESULTS: RA patients had a mean age of 53.9 years, and 802 (78.8%) were females. After a median follow-up of 5.54 years, 131 patients developed CVD with an incidence rate of 21.6 per 1000 person-years. Continuous and quartile-categorized RC levels were associated with incident CVD before and after multivariate adjustment and Bonferroni correction (all P < 0.001). There were no robust associations of other lipids with incident CVD. The fully adjusted HRs for RC were 2.30 (95% CI 1.58-3.35) per 1 mmol/L increase, and 2.40 (1.36-4.25) and 2.81 (1.60-4.94) for patients in the 3rd and 4th versus the 1st quartile, respectively. CONCLUSIONS: Circulating RC levels are positively associated with incident CVD among Chinese RA patients independent of known risk factors, implying its clinically preferable use for improving the stratification of CVD risk in RA patients.

PM2.5 constituents associated with mortality and kidney failure in childhood-onset lupus nephritis: A 19-year cohort study.

BACKGROUND: Childhood-onset lupus nephritis (cLN) is a severe form of systemic lupus erythematosus (SLE) with high morbidity and mortality. The impact of long-term exposure to fine particulate matter (PM2.5) on adverse outcomes in cLN remains unclear. METHODS: We combined a 19-years cLN cohort from seven provinces in China with high-resolution PM2.5 dataset from 2001 to 2020, investigating the association between long-term exposure to PM2.5 and its constituents (sulfate, nitrate, organic matter, black carbon, ammonium) with the risk of death and kidney failure, analyzed with multiple variables Cox models. We also evaluated the association between 3-year average PM2.5 exposure before study entry and baseline SLE disease activity index (SLEDAI) scores using linear regression models. RESULTS: Each 10 µg/m3 increase in annual average PM2.5 exposure was associated with an increased risk of death and kidney failure (HR = 1.58, 95 % CI: 1.24-2.02). Black carbon showed the strongest association (HR = 2.14, 95 % CI: 1.47-3.12). Higher 3-year average exposures to PM2.5 and its constituents were significantly associated with higher baseline SLEDAI scores. CONCLUSIONS: These findings highlight the significant role of environmental pollutants in cLN progression and emphasize the need for strategies to mitigate exposure to harmful PM2.5 constituents, particularly in vulnerable pediatric populations.

Cardiovascular mortality risk in patients with ovarian cancer: a population-based study.

OBJECTIVES: Ovarian cancer (OC) can occur at different ages and is affected by a variety of factors. In order to evaluate the risk of cardiovascular mortality in patients with ovarian cancer, we included influencing factors including age, histological type, surgical method, chemotherapy, whether distant metastasis, race and developed a nomogram to evaluate the ability to predict occurrence. At present, we have not found any correlation studies on cardiovascular death events in patients with ovarian cancer. This study was designed to provide targeted measures for effective prevention of cardiovascular death in patients with ovarian cancer. METHODS: Kaplan-Meier analysis and multivariable Cox proportional model were performed to evaluate the effectiveness of cardiovascular diseases on overall survival (OS) and ovarian cancer-specific survival (OCSS). We compared multiple groups including clinical, demographic, therapeutic characteristics and histological types. Cox risk regression analysis, Kaplan-Meier survival curves, and propensity score matching were employed for analyzing the data. RESULTS: A total of 88,653 ovarian cancer patients were collected, of which 2,282 (2.57%) patients died due to cardiovascular-related diseases. Age, chemotherapy and whether satisfactory cytoreduction surgery is still the most important factors affecting the prognosis of ovarian cancer patients, while different histological types, diagnosis time, and race also have a certain impact on the prognosis. The newly developed nomogram model showed excellent predictive performance, with a C-index of 0.759 (95%CI: 0.757-0.761) for the group. Elderly patients with ovarian cancer are still a high-risk group for cardiovascular death [HR: 21.07 (95%CI: 5.21-85.30), p < 0.001]. The calibration curve showed good agreement from predicted survival probabilities to actual observations. CONCLUSION: This study found that age, histology, surgery, race, chemotherapy, and tumor metastasis are independent prognostic factors for cardiovascular death in patients with ovarian cancer. The nomogram-based model can accurately predict the OS of ovarian cancer patients. It is expected to inform clinical decision-making and help develop targeted treatment strategies for this population.