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INTRODUCTION: Inflammation is associated with development of chronic kidney disease (CKD). However, the association of the high-sensitivity C-reactive protein (hs-CRP)/albumin ratio (CAR) on the risk of CKD in the general population is unknown. This study explored the relationship between the CAR and CKD and the ability of this ratio to predict CKD in the general population. METHODS: A total of 47,472 participants in the Kailuan study who met the inclusion criteria in 2010 were selected and grouped using the quartile method. A Cox proportional hazard regression model was used to evaluate the association of the CAR on the risk of CKD. The C-index, net reclassification index (NRI), and overall identification index (IDI) were calculated to evaluate the ability of the CAR to predict CKD. RESULTS: During a follow-up of 378,383 person-years, CKD events occurred in 6,249 study participants (13.16%). The Cox proportional hazard regression model showed that the hazard ratio (95% confidence interval) for CKD events was 1.18 (1.10-1.28) in the Q3 group and 1.42 (1.32-1.53) in the Q4 group when compared with the Q1 group. Compared with the single index, the C-index, NRI, and IDI values were significantly improved when the CAR was added for prediction of risk of CKD. CONCLUSIONS: A higher CAR was an independent risk factor for CKD. The ability of the CAR to predict CKD was better than that of hs-CRP or albumin. The CAR provides an important reference index for predicting the risk of CKD.
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Proteína C-Reactiva , Insuficiencia Renal Crónica , Humanos , Proteína C-Reactiva/metabolismo , Insuficiencia Renal Crónica/epidemiología , Factores de Riesgo , Inflamación , China/epidemiologíaRESUMEN
Objective: The ratio of uric acid to high-density lipoprotein cholesterol (UHR) was related to the risk of chronic kidney disease (CKD), we aimed to investigate the association of cumulative UHR (cumUHR) with incidence and progression of CKD. Methods: Our study included a total of 49,913 participants (mean age 52.57 years, 77% males) from the Kailuan Study conducted between 2006 and 2018. Participants who completed three consecutive physical examinations were included. Cumulative UHR (cumUHR) was computed as the summed average UHR between two consecutive physical examinations, multiplied by the time between the two examinations. Participants were then categorized into four groups based on cumUHR quartiles. Subsequently, participants were further divided into a CKD group and a non-CKD group. The associations between cumUHR and CKD and it's progression were assessed by Cox proportional hazards regression models. The cumulative incidence of endpoint events was compared between the cumUHR groups using the log-rank test. The C-index, net reclassification improvement (NRI) and integrated discrimination improvement (IDI) were calculated to assess the predictive performance of cumUHR. Results: After a mean follow-up of 8.0 ± 1.7 years, there were 4843 cases of new-onset CKD, 2504 of low eGFR, and 2617 of proteinuria in the non-CKD group. Within the CKD group, there were 1952 cases of decline in eGFR category, 1465 of >30% decline in eGFR, and 2100 of increased proteinuria. In the non-CKD group, the adjusted hazard ratios (HRs) and confidence intervals (CIs) in the fourth quartile were 1.484 (1.362-1.617), 1.643 (1.457-1.852), and 1.324 (1.179-1.486) for new-onset CKD, low eGFR, and proteinuria, respectively. In the CKD group, the adjusted HRs in the fourth quartile were 1.337 (1.164-1.534), 1.428 (1.216-1.677), and 1.446 (1.267-1.651) for decline in eGFR category, >30% decline in eGFR, and increase in proteinuria, respectively. In addition, we separately added a single UHR measurement and cumUHR to the CKD base prediction model and the CKD progression base prediction model, and found that the models added cumUHR had the highest predictive value. Conclusion: High cumUHR exposure was an independent risk factor for the incidence and progression of CKD, and it was a better predictor than a single UHR measurement.
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Insuficiencia Renal Crónica , Ácido Úrico , Masculino , Humanos , Persona de Mediana Edad , Femenino , Incidencia , HDL-Colesterol , Progresión de la Enfermedad , Tasa de Filtración Glomerular , Insuficiencia Renal Crónica/epidemiología , Insuficiencia Renal Crónica/complicaciones , Proteinuria/complicacionesRESUMEN
Importance: Although a high body mass index (BMI) has been found to be associated with increased risk of cardiac conduction block (CCB) in older adults, no further studies have investigated the association between obesity and CCB in the general population. Objective: To investigate the association between obesity and CCB, including its subtypes. Design, Setting, and Participants: This cohort study used data from participants in the Kailuan Study in China (2006-2018) who had completed a physical examination in 2006 (baseline) and had not experienced CCB before baseline. Data analysis was conducted from March to September 2023. Exposures: Obesity status was defined by BMI in 3 groups: normal weight (18.5 to <24), overweight (24 to <28), and obesity (≥28). Main Outcome and Measures: The primary outcome was CCB, which was diagnosed from standard 12-lead electrocardiography. The primary end point included high-grade atrioventricular block (HAVB), complete right bundle branch block, complete left bundle branch block, left anterior fascicular block (LAFB), and left posterior fascicular block. First-degree atrioventricular block (FAVB), second-degree type 1 AVB, HAVB, complete and incomplete right and left bundle branch block, LAFB, and left posterior fascicular block were considered separately as secondary end points. Results: Among 86â¯635 participants (mean [SD] age, 50.8 [11.9] years; 68â¯205 males [78.7%]), there were 33â¯259 individuals with normal weight (38.4%), 37â¯069 individuals with overweight (42.8%), and 16â¯307 individuals with obesity (18.8%). The mean (SD) follow-up was 10.6 (3.07) years. In the multivariable Cox proportional hazards regression analysis, obesity was associated with an increased risk of incident CCB (hazard ratio [HR], 1.21; 95% CI, 1.04-1.42) vs normal BMI. In secondary analysis, obesity was associated with an increased risk of FAVB (HR, 1.44; 95% CI, 1.21-1.73), HAVB (HR, 1.99; 95% CI, 1.03-3.82), and LAFB (HR, 1.29; 95% CI, 1.03-1.62) vs normal BMI. There was no association between obesity and other CCB subtypes. Obesity was associated with a greater increase in risk of CCB vs normal BMI in older (aged ≥65 years; HR, 1.44; 95% CI, 1.05-1.96) vs younger (aged <65 years; HR, 1.13; 95% CI, 0.96-1.34) participants (P for interaction < .001) and those with diabetes (HR, 2.16; 95% CI, 1.24-3.76) vs without diabetes (HR, 1.19; 95% CI, 1.02-1.39) (P for interaction = .02). Conclusions and Relevance: This study found that obesity was associated with an increased risk of CCB, with greater increases in risk for FAVB, HAVB, and LAFB. Individuals who were older and those who had diabetes had larger increases in risk.