Variables linked to hepatitis B vaccination success in non-dialyzed chronic kidney disease patients: Use of a bayesian model

Using Bayesian network model with MMHC algorithm to detect risk factors for stroke

Stroke is a major chronic non-communicable disease with high incidence, high mortality, and high recurrence. To comprehensively digest its risk factors and take some relevant measures to lower its prevalence is of great significance. This study aimed to employ Bayesian Network (BN) model with Max-Min Hill-Climbing (MMHC) algorithm to explore the risk factors for stroke. From April 2019 to November 2019, Shanxi Provincial People's Hospital conducted opportunistic screening for stroke in ten rural areas in Shanxi Province. First, we employed propensity score matching (PSM) for class balancing for stroke. Afterwards, we used Chi-square testing and Logistic regression model to conduct a preliminary analysis of risk factors for stroke. Statistically significant variables were incorporated into BN model construction. BN structure learning was achieved using MMHC algorithm, and its parameter learning was achieved with Maximum Likelihood Estimation. After PSM, 748 non-stroke cases and 748 stroke cases were included in this study. BN was built with 10 nodes and 12 directed edges. The results suggested that age, fasting plasma glucose, systolic blood pressure, and family history of stroke constitute direct risk factors for stroke, whereas sex, educational levels, high density lipoprotein cholesterol, diastolic blood pressure, and urinary albumin-to-creatinine ratio represent indirect risk factors for stroke. BN model with MMHC algorithm not only allows for a complicated network relationship between risk factors and stroke, but also could achieve stroke risk prediction through Bayesian reasoning, outshining traditional Logistic regression model. This study suggests that BN model boasts great prospects in risk factor detection for stroke.

Immunogenicity and safety of a high-dose and prolonged-schedule hepatitis B vaccine among chronic kidney disease patients: a randomized, parallel-controlled trial

Background: The immunogenicity against hepatitis B vaccine is unsatisfactory in the chronic kidney disease (CKD) patients, and studies evaluating augmented vaccine regimens to enhance immunogenicity have been inconclusive.Objectives: To evaluate the immunogenicity and safety of four-standard-dose and four-triple-dose regimens hepatitis B vaccine among CKD patients in China.Research design and methods: We conducted a multicenter, randomized, parallel-controlled trial including 273 patients with CKD who were randomly allocated to receive 3 or 4 doses of 20 or 60 µg of recombinant hepatitis B vaccine.Main outcome measures: Seroconversion rates, high-level response rates, and geometric mean concentrations (GMCs) of anti-HBs at months 3 and 7.Results: The seroconversion rates and high-level responses in the IM20 × 4 group and the IM60 × 4 group were higher than those in the IM20 × 3 group at months 3 and 7 (P < 0.05). The IM60 × 4 group had better immune responses than the IM20 × 4 group at month 3 (P < 0.05); however, no significant difference was noted at month 7 (P > 0.05).Conclusions: Both the four-standard-dose and four-triple-dose regimens improved immune response compared to the three-standard-dose regimen of hepatitis B vaccination in CKD patients, and the additional effect of higher dose was minimal.Trial registration: The trial is registered at ClinicalTrials.gov (CT.gov identifier: NCT03962881).