Application of explainable ensemble artificial intelligence model to categorization of hemodialysis-patient and treatment using nationwide-real-world data in Japan.

BACKGROUND:Although dialysis patients are at a high risk of death, it is difficult for medical practitioners to simultaneously evaluate many inter-related risk factors. In this study, we evaluated the characteristics of hemodialysis patients using machine learning model, and its usefulness for screening hemodialysis patients at a high risk of one-year death using the nation-wide database of the Japanese Society for Dialysis Therapy. MATERIALS AND METHODS:The patients were separated into two datasets (n = 39,930, 39,930, respectively). We categorized hemodialysis patients in Japan into new clusters generated by the K-means clustering method using the development dataset. The association between a cluster and the risk of death was evaluated using multivariate Cox proportional hazards models. Then, we developed an ensemble model composed of the clusters and support vector machine models in the model development phase, and compared the accuracy of the prediction of mortality between the machine learning models in the model validation phase. RESULTS:Average age of the subjects was 65.7±12.2 years; 32.7% had diabetes mellitus. The five clusters clearly distinguished the groups on the basis of their characteristics: Cluster 1, young male, and chronic glomerulonephritis; Cluster 2, female, and chronic glomerulonephritis; Cluster 3, diabetes mellitus; Cluster 4, elderly and nephrosclerosis; Cluster 5, elderly and protein energy wasting. These clusters were associated with the risk of death; Cluster 5 compared with Cluster 1, hazard ratio 8.86 (95% CI 7.68, 10.21). The accuracy of the ensemble model for the prediction of 1-year death was 0.948 and higher than those of logistic regression model (0.938), support vector machine model (0.937), and deep learning model (0.936). CONCLUSIONS:The clusters clearly categorized patient on their characteristics, and reflected their prognosis. Our real-world-data-based machine learning system is applicable to identifying high-risk hemodialysis patients in clinical settings, and has a strong potential to guide treatments and improve their prognosis

Nardilysin promotes hepatocellular carcinoma through activation of signal transducer and activator of transcription 3

Nardilysin (NRDC) is a metalloendopeptidase of the M16 family. We previously showed that NRDC activates inflammatory cytokine signaling, including interleukin-6-signal transducer and activator of transcription 3 (STAT3) signaling. NRDC has been implicated in the promotion of breast, gastric and esophageal cancer, as well as the development of liver fibrosis. In this study, we investigated the role of NRDC in the promotion of hepatocellular carcinoma (HCC), both clinically and experimentally. We found that NRDC expression was upregulated threefold in HCC tissue compared to the adjacent non-tumor liver tissue, which was confirmed by immunohistochemistry and western blotting. We also found that high serum NRDC was associated with large tumor size (>3 cm, P = 0.016) and poor prognosis after hepatectomy (median survival time 32.0 vs 73.9 months, P = 0.003) in patients with hepatitis C (n = 120). Diethylnitrosamine-induced hepatocarcinogenesis was suppressed in heterozygous NRDC-deficient mice compared to their wild-type littermates. Gene silencing of NRDC with miRNA diminished the growth of Huh-7 and Hep3B spheroids in vitro. Notably, phosphorylation of STAT3 was decreased in NRDC-depleted Huh-7 spheroids compared to control spheroids. The effect of a STAT3 inhibitor (S3I-201) on the growth of Huh-7 spheroids was reduced in NRDC-depleted cells relative to controls. Our results show that NRDC is a promising prognostic marker for HCC in patients with hepatitis C, and that NRDC promotes tumor growth through activation of STAT3

Annual dialysis data report 2019, JSDT Renal Data Registry

Abstract Background The Japanese Society for Dialysis Therapy is conducting the survey annually since 1968. The results provide a comprehensive picture of dialysis therapy in Japan. The survey for the year 2019 was performed as of December 2019. Methods Questionnaires were sent to all facilities that provide patients with dialysis therapy in Japan as an Excel file. Data were collected and compiled to form cross-sectional results of dialysis therapy from various aspects. Results At the end of 2019, the annual survey of the Japanese Society for Dialysis Therapy Renal Data Registry (JRDR) was conducted at 4487 dialysis facilities, of which 4411 facilities (98.3%) responded to the facility survey and 4238 facilities (94.5%) responded to the patient survey. The number of chronic dialysis patients in Japan continues to increase every year; it reached 344,640 at the end of 2019, and the prevalence ratio of dialysis patients was 2732 per million population. In the patient survey, the mean age of prevalent dialysis patients was 69.09 years. The most prevalent primary disease among prevalent dialysis patients was diabetic nephropathy (39.1%), followed by chronic glomerulonephritis (25.7%) and nephrosclerosis (11.1%). In 2019, there were 40,885 new patients on dialysis, an increase of 417 over 2018. The average age of incident dialysis patients was 70.42 years, and diabetic nephropathy (41.6%) was the most common cause. The second cause was nephrosclerosis, followed by glomerulonephritis. As 34,642 patients passed away in 2019, the crude mortality rate for the year was 10.1%. Heart failure (22.7%), infectious disease (21.5%), and malignancy (8.7%) were the three leading causes of death. Since 2012, the number of patients treated by hemodiafiltration (HDF) has increased substantially. The figure reached 144,686 by year's end, representing 42.0% of all dialysis patients. In 2019, the number of peritoneal dialysis (PD) patients was 9,920, a small rise from 2017. 19.2% of PD patients also received hemodialysis (HD) or HDF to compensate for the reduction in dialysis dosage or in fluid removal by PD alone (hybrid therapy). At the end of 2019, 760 patients received home HD therapy, an increase of 40 from 2018. In 2019, a detailed survey was conducted on the current status of CKD-MBD treatment, 10 years after the previous survey in 2009. The clinical efficacy of newly released medications during this time period and the impact of the 2012 revisions to the CKD-MBD guidelines require further investigation. These analyses would serve as the foundation for the next revision of the CKD-MBD guidelines and may reveal deeper therapeutic insights regarding CKD-MBD. Conclusions The results obtained by the survey revealed the comprehensive practice patterns of dialysis therapy and served as a basis for future guidelines. Trial registration: JRDR was approved by the ethics committee of JSDT (approval number 1–5) and registered in the "University hospital Medical Information Network (UMIN) Clinical Trials Registry" on 10th September 2019 with a clinical trial ID of UMIN000018641. https://upload.umin.ac.jp/cgi-bin/ctr/ctr_view_reg.cgi?recptno=R000021578 (Accessed 20 November 2020)

Empagliflozin in Patients with Chronic Kidney Disease

Background The effects of empagliflozin in patients with chronic kidney disease who are at risk for disease progression are not well understood. The EMPA-KIDNEY trial was designed to assess the effects of treatment with empagliflozin in a broad range of such patients. Methods We enrolled patients with chronic kidney disease who had an estimated glomerular filtration rate (eGFR) of at least 20 but less than 45 ml per minute per 1.73 m(2) of body-surface area, or who had an eGFR of at least 45 but less than 90 ml per minute per 1.73 m(2) with a urinary albumin-to-creatinine ratio (with albumin measured in milligrams and creatinine measured in grams) of at least 200. Patients were randomly assigned to receive empagliflozin (10 mg once daily) or matching placebo. The primary outcome was a composite of progression of kidney disease (defined as end-stage kidney disease, a sustained decrease in eGFR to < 10 ml per minute per 1.73 m(2), a sustained decrease in eGFR of & GE;40% from baseline, or death from renal causes) or death from cardiovascular causes. Results A total of 6609 patients underwent randomization. During a median of 2.0 years of follow-up, progression of kidney disease or death from cardiovascular causes occurred in 432 of 3304 patients (13.1%) in the empagliflozin group and in 558 of 3305 patients (16.9%) in the placebo group (hazard ratio, 0.72; 95% confidence interval [CI], 0.64 to 0.82; P < 0.001). Results were consistent among patients with or without diabetes and across subgroups defined according to eGFR ranges. The rate of hospitalization from any cause was lower in the empagliflozin group than in the placebo group (hazard ratio, 0.86; 95% CI, 0.78 to 0.95; P=0.003), but there were no significant between-group differences with respect to the composite outcome of hospitalization for heart failure or death from cardiovascular causes (which occurred in 4.0% in the empagliflozin group and 4.6% in the placebo group) or death from any cause (in 4.5% and 5.1%, respectively). The rates of serious adverse events were similar in the two groups. Conclusions Among a wide range of patients with chronic kidney disease who were at risk for disease progression, empagliflozin therapy led to a lower risk of progression of kidney disease or death from cardiovascular causes than placebo