Clinical epidemiological analysis of cohort studies investigating the pathogenesis of kidney disease

Abstract

In recent years, large cohort studies of patients with chronic kidney disease (CKD) have been established all over the world. These studies have attempted to analyze the pathogenesis of CKD using a large body of published evidence. The design of cohort studies is characterized by the measurement of the exposure prior to the occurrence of the outcome, which has the advantage of clarifying the temporal relationship between predictors and outcomes and estimating the strength of the causal relationship between predictors and multiple outcomes. Recent advances in biostatistical analysis methods, such as propensity scores and risk prediction models, are facilitating causal inference using higher quality evidence with greater precision in observational studies. In this review, we will discuss clinical epidemiological research of kidney disease based on the analysis of observational cohort data sets, with a focus on our previous studies.

Early Detection of Inflammation and Malnutrition and Prediction of Acute Events in Hemodialysis Patients through PINI (Prognostic Inflammatory and Nutritional Index)

“…The malnutrition–inflammation score (MIS) was developed to improve upon the SGA score, incorporating additional elements, such as the body mass index (BMI), serum albumin, and total iron-binding capacity [ 9 , 10 ]. MIA is associated with cardiovascular events, the leading cause of death among hemodialysis patients, independent of comorbidities [ 11 , 12 , 13 ]. Managing the nutritional balance in dialysis patients poses a continuous challenge, given their high risk for cardiovascular diseases (CVD) and infections, compared to the general population.…”