The association of vitamin-D level with catheter-related-thrombosis in hemodialysis patients: A data mining model.

PURPOSE: This study aims to investigate the association of different risk factors including vitamin-D level with catheter-related-thrombosis in hemodialysis patients by applying data mining techniques. METHODS: This study used the retrospectively approach and was done based on the CRISP-DM framework. The data of 1048 hemodialysis patients of Hasheminejad Kidney Center whose first catheterization was between 2014 and 2019 was used for analysis. In this study, patients with a previous history of deep venous thrombosis, thrombophilic condition, and undergone anticoagulant therapy were excluded. The decision tree J48 in WEKA software was used for modeling. The K-fold cross-validation method was also used to evaluate the classification performance. Finally, the model was evaluated by using Confusion Matrix and F-Measure. RESULTS: The approved model was accurate in 70.3% of the predictions, and it demonstrated an association between patients' vitamin-D range and catheter-related-thrombosis. CONCLUSION: The results indicated that in hemodialysis patients without the history of cancer or high blood pressure, vitamin-D had a significant impact on catheter related thrombosis.

Investigation of risk factors for tunneled hemodialysis catheters dysfunction: competing risk analysis of a tertiary center data.

BACKGROUND: Hemodialysis tunneled catheters are prone to failure due to infection or thrombosis. Prediction of catheter dysfunction chance and finding the predisposing risk factors might help clinicians to prolong proper catheter function. The multidimensional mechanism of failures following infection or thrombosis needs a multivariable and comprehensive analytic approach. METHODS: A longitudinal cross-sectional study was implemented on 1048 patients admitted for the first hemodialysis tunneled catheterization attempt between 2013 and 2019 in Shahid Hasheminejdad hospital, Tehran, Iran. Patients' information was extracted from digital and also paper records. Based on their criteria, single and multiple variable analyses were done separately in patients with catheter dysfunction due to thrombosis and infection. T-test and Chi-square test were performed in quantitative and categorical variables, respectively. Competing risk regression was performed under the assumption of proportionality for infection and thrombosis, and the sub-distributional hazard ratios (SHR) were calculated. All statistical inferences were made with a significance level of 0.05. RESULTS: Four hundred sixty-six patients were enrolled in the analysis based on study criteria. Samples' mean (SD) age was 54(15.54), and 322 (69.1%) patients were female. Three hundred sixty-five catheter dysfunction cases were observed due to thrombosis 123(26.4%) and infection 242(52%). The Median (range) time to catheter dysfunction event was 243(36-1131) days. Single variable analysis showed a statistically significant higher proportion of thrombosis in females (OR = 2.66, 95% CI: 1.77-4.00) and younger patients, respectively. Multivariate competing risk regression showed a statistically significant higher risk of thrombosis in females (Sub-distributional hazard (SHR) = 1.81), hypertensive (SHR = 1.82), and more obese patients (BMI SHR = 1.037). A higher risk of infection was calculated in younger (Age SHR = 0.98) and diabetic (SHR = 1.63) patients using the same method. CONCLUSION: Female and hypertensive patients are considerably at higher risk of catheter thrombosis, whereas diabetes is the most critical risk factor for infectious catheter dysfunction. Competing risk regression analysis showed a comprehensive result in the assessment of risk factors of catheter dysfunction.

Predictive Factors of Advanced Colonic Adenomas and Cancer Using Data Mining.

BACKGROUND Colorectal cancer is the third common cancer in Iran. In this study we aimed to identify factors associated with the prevalence of advanced colonic neoplasms among a high-risk population. METHODS Participants were 474 first degree relatives of patients with colon cancer who underwent a screening colonoscopy at Digestive Disease Research Institute, Shariati Hospital affiliated to Tehran University of Medical Sciences. Features examined in this study were age, sex, body mass index, Aspirin use, smoking, and relationship type with patients with cancer in family. Also, patient's age at the time of cancer diagnosis, number and sex of the patients with colon cancer in the family were assessed. Data analysis was performed by data mining methods using K-Medoid clustering and decision tree C4.5. RESULTS Results showed that female sex of the patients with colon cancer and their young age (< 60 years old) at the time of cancer diagnosis were important predictive factors for the prevalence of colorectal advanced neoplasms among their family members. CONCLUSION Data mining methods were found to be applicable in recognizing predictive factors of colorectal advanced neoplasms in each cluster and tree.