Association between serum uric acid levels of patients with gout and their complications and examination fees: A cross-sectional analysis

Study on risk factor analysis and model prediction of hyperuricemia in different populations

Objectives

The purpose of the present study was to explore the influencing factors of hyperuricemia (HUA) in different populations in Shandong Province based on clinical biochemical indicators. A prediction model for HUA was constructed to aid in the early prevention and screening of HUA.

Methods

In total, 705 cases were collected from five hospitals, and the risk factors were analyzed by Pearson correlation analysis, binary logistic regression, and receiver operating characteristic (ROC) curve in the gender and age groups. All data were divided into a training set and test set (7:3). The training set included age, gender, total protein (TP), low-density lipoprotein cholesterol (LDL-C), and 15 other indicators. The random forest (RF) and support vector machine (SVM) methods were used to build the HUA model, and model performances were evaluated through 10-fold cross-validation to select the optimal method. Finally, features were extracted, and the ROC curve of the test set was generated.

Results

TP, LDL-C, and glucose (GLU) were risk factors for HUA, and the area under the curve (AUC) value of the SVM validation set was 0.875.

Conclusion

The SVM model based on clinical biochemical indicators has good predictive ability for HUA, thus providing a reference for the diagnosis of HUA and the development of an HUA prediction model.

Association between serum uric acid levels and lung function in the NHANES cohort (2007-2012): A cross-sectional analysis of a diverse American population

BACKGROUND

Hyperuricemia has been linked to various health conditions. However, the relationship between uric acid (UA) levels and lung function remains debated.

METHODS

In a cross-sectional study of 6750 participants aged 20-69 from NHANES, we assessed UA levels and lung function (FVC and FEV1). We conducted regression analyses while adjusting for potential confounders.

RESULTS

After accounting for factors like age, sex, BMI, smoking, and more, we found a negative association between UA FVC and FEV1. Specifically, for every 0.1 mg/dL increase in UA, FEV1 decreased by 15.265 mL, and FVC decreased by 24.46 mL. No association was observed with FEV1/FVC. Subgroup analyses revealed similar negative correlations among various groups, particularly in non-Hispanic Black females under 60.

CONCLUSION

Serum UA levels are inversely associated with FEV1 and FVC in the American population, with a notable impact on non-Hispanic Black females under 60.

Prediction of renal and cardiometabolic outcomes in gout during urate-lowering therapy by sonography

OBJECTIVES

To assess whether the extent of monosodium urate (MSU) crystal deposition estimated by ultrasound could predict renal and cardiometabolic events during urate-lowering therapy (ULT).

METHODS

A prospective study on gout patients from two referral centers initiating ULT who underwent baseline ultrasound and were followed for 1 year. Ultrasound scans assessed six joints for double-contour (DC) signs and tophi. A five-point change (mL/min/1.73 m2 ) in the glomerular filtration rate at month 12 (M12) was considered significant. Outcomes of interest were renal function degraded versus improved and a composite cardiometabolic outcome (new hypertension, diabetes, atherosclerotic disease, and cardiovascular death). Homogeneity analyses and Cox regression models were performed.

RESULTS

One hundred sixty patients were recruited. At baseline, 81.1% of patients (n = 129) showed sonographic tophi with a mean number of 1.4 joints (±1.3) with a DC sign. At M12, 18 patients (11.3%) were lost to follow-up. The serum urate (SU) target (<6.0 mg/dL) was reached in 86 patients (69.9%). Regarding renal function, 15.9% of patients showed improvement, while in 31.0% it degraded. Fourteen new cardiometabolic events occurred in 12 patients. Neither the DC sign nor tophi showed any significant impact on the outcomes of interest. Baseline SU level was higher in those with renal improvement but not with renal decline, while achieving the SU target protected against new cardiometabolic events (HR = 0.2; 95% CI: 0.05-0.81).

CONCLUSIONS

Sonographic MSU crystal burden was unhelpful in predicting renal and cardiometabolic events during the first year of ULT. Reaching the SU target prevented cardiometabolic events, while its benefit in preserving/improving renal function is unclear.