Dataset Information

Prediction of the Mortality Risk in Peritoneal Dialysis Patients using Machine Learning Models: A Nation-wide Prospective Cohort in Korea.

ABSTRACT: Herein, we aim to assess mortality risk prediction in peritoneal dialysis patients using machine-learning algorithms for proper prognosis prediction. A total of 1,730 peritoneal dialysis patients in the CRC for ESRD prospective cohort from 2008 to 2014 were enrolled in this study. Classification algorithms were used for prediction of N-year mortality including neural network. The survival hazard ratio was presented by machine-learning algorithms using survival statistics and was compared to conventional algorithms. A survival-tree algorithm presented the most accurate prediction model and outperformed a conventional method such as Cox regression (concordance index 0.769 vs 0.745). Among various survival decision-tree models, the modified Charlson Comorbidity index (mCCI) was selected as the best predictor of mortality. If peritoneal dialysis patients with high mCCI (>4) were aged ?70.5 years old, the survival hazard ratio was predicted as 4.61 compared to the overall study population. Among the various algorithm using longitudinal data, the AUC value of logistic regression was augmented at 0.804. In addition, the deep neural network significantly improved performance to 0.841. We propose machine learning-based final model, mCCI and age were interrelated as notable risk factors for mortality in Korean peritoneal dialysis patients.

SUBMITTER: Noh J

PROVIDER: S-EPMC7198502 | biostudies-literature | 2020 May

REPOSITORIES: biostudies-literature

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Prediction of the Mortality Risk in Peritoneal Dialysis Patients using Machine Learning Models: A Nation-wide Prospective Cohort in Korea.

Noh Junhyug J Yoo Kyung Don KD Bae Wonho W Lee Jong Soo JS Kim Kangil K Cho Jang-Hee JH Lee Hajeong H Kim Dong Ki DK Lim Chun Soo CS Kang Shin-Wook SW Kim Yong-Lim YL Kim Yon Su YS Kim Gunhee G Lee Jung Pyo JP

Scientific reports 20200504 1

Herein, we aim to assess mortality risk prediction in peritoneal dialysis patients using machine-learning algorithms for proper prognosis prediction. A total of 1,730 peritoneal dialysis patients in the CRC for ESRD prospective cohort from 2008 to 2014 were enrolled in this study. Classification algorithms were used for prediction of N-year mortality including neural network. The survival hazard ratio was presented by machine-learning algorithms using survival statistics and was compared to conv ...[more]

PMID: 32366838

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Project description:Although numerous studies have tried to elucidate the best dialysis modality in end-stage renal disease patients with diabetes, results were inconsistent and varied with the baseline characteristics of patients. Furthermore, none of the previous studies on diabetic dialysis patients accounted for the impact of glycemic control. We explored whether glycemic control had modifying effect on mortality between hemodialysis (HD) and peritoneal dialysis (PD) in incident dialysis patients with diabetes. A total of 902 diabetic patients who started dialysis between August 2008 and December 2013 were included from a nationwide prospective cohort in Korea. Based on the interaction analysis between hemoglobin A1c (HbA1c) and dialysis modalities for patient survival (P for interaction = 0.004), subjects were stratified into good and poor glycemic control groups (HbA1c< or ≥8.0%). Differences in survival rates according to dialysis modalities were ascertained in each glycemic control group after propensity score matching. During a median follow-up duration of 28 months, the relative risk of death was significantly lower in PD compared with HD in the whole cohort and unmatched patients (whole cohort, hazard ratio [HR] = 0.65, 95% confidence interval [CI] = 0.47-0.90, P = 0.01; patients with available HbA1c [n = 773], HR = 0.64, 95% CI = 0.46-0.91, P = 0.01). In the good glycemic control group, there was a significant survival advantage of PD (HbA1c <8.0%, HR = 0.59, 95% CI = 0.37-0.94, P = 0.03). However, there was no significant difference in survival rates between PD and HD in the poor glycemic control group (HbA1c ≥8.0%, HR = 1.21, 95% CI = 0.46-2.76, P = 0.80). This study demonstrated that the degree of glycemic control modified the mortality risk between dialysis modalities, suggesting that glycemic control might partly contribute to better survival of PD in incident dialysis patients with diabetes.

Project description:BackgroundResults concerning the association between peritoneal dialysis-related peritonitis and mortality in peritoneal dialysis patients are inconclusive, with one potential reason being that the time-dependent effect of peritonitis has rarely been considered in previous studies. This study aimed to evaluate whether peritonitis has a negative impact on mortality in a large cohort of peritoneal dialysis patients. We also assessed the changing impact of peritonitis on patient mortality with respect to duration of follow-up.MethodsThis retrospective cohort study included incident patients who started peritoneal dialysis from 1 January 2006 to 31 December 2011. Episodes of peritonitis were recorded at the time of onset, and peritonitis was parameterized as a time-dependent variable for analysis. We used the Cox regression model to assess whether peritonitis has a negative impact on mortality.ResultsA total of 1321 patients were included. The mean age was 48.1 ± 15.3 years, 41.3% were female, and 23.5% with diabetes mellitus. The median (interquartile) follow-up time was 34 (21-48) months. After adjusting for confounders, peritonitis was independently associated with 95% increased risk of all-cause mortality (hazard ratio, 1.95; 95% confidence interval: 1.46-2.60), 90% increased risk of cardiovascular mortality (hazard ratio, 1.90; 95% confidence interval: 1.28-2.81) and near 4-fold increased risk of infection-related mortality (hazard ratio, 4.94; 95% confidence interval: 2.47-9.86). Further analyses showed that peritonitis was not significantly associated with mortality within 2 years of peritoneal dialysis initiation, but strongly influenced mortality in patients dialysed longer than 2 years.ConclusionsPeritonitis was independently associated with higher risk of all-cause, cardiovascular and infection-related mortality in peritoneal dialysis patients, and its impact on mortality was more significant in patients with longer peritoneal dialysis duration.

Project description:Background New lipid-lowering therapy at the start of dialysis and measurement of lipid parameters over the follow-up period is not recommended in dialysis patients, which seems unappropriated in clinical practice. We aimed to examine the effect of hyperlipidemia on mortality in patients undergoing continuous ambulatory peritoneal dialysis (CAPD). Methods A retrospective cohort study was performed, including 2939 incident CAPD patients from five dialysis facilities between January 1, 2005, and December 31, 2018. The primary outcome was all-cause mortality. The association between hyperlipidemia at the start of CAPD and all-cause mortality was evaluated using Cox proportional hazards regression. Results Of 2939 with a median age of 50.0 (interquartile range, 39.0–61.0), 1697 (57.7%) were men, 533 (18.1%) had hyperlipidemia, 549 (18.7%) had diabetes mellitus, 1915 (65.2%) had hypertension, and 410 (14.0%) had a history of CVD. During the median follow-up period of 35.1 months, 519 (17.7%) died, including 402 (16.7%, 47.4/1000 patient-years) in the non-hyperlipidemia group and 117 (22.0%, 71.1/1000 patient-years) in the hyperlipidemia group. Over the overall follow-up period, patients with hyperlipidemia had an equally high risk of all-cause mortality throughout follow-up as those without hyperlipidemia ([HR] 1.04, 95% confidence interval [CI] 0.83 to 1.31). However, from the 48-month follow-up onwards, hyperlipidemia was associated with a 2.26 (95% CI 1.49 to 3.43)-time higher risk of all-cause mortality than non-hyperlipidemia. Hypertension modified the association between hyperlipidemia and all-cause mortality (P for interaction < 0.001). A significantly increased risk of all-cause mortality was observed among patients with hypertension (HR 2.27, 95%CI 1.44–3.58). Conclusion Among CAPD patients, hyperlipidemia at the beginning of CAPD was associated with a high risk of long-term mortality. Hypertension may mediate the association. Our findings suggested that long-term lipid-lowering treatment should be used in those patients with hyperlipidemia. Supplementary information The online version contains supplementary material available at 10.1186/s12882-022-02970-w.

Dataset Information

Prediction of the Mortality Risk in Peritoneal Dialysis Patients using Machine Learning Models: A Nation-wide Prospective Cohort in Korea.

Publications

Prediction of the Mortality Risk in Peritoneal Dialysis Patients using Machine Learning Models: A Nation-wide Prospective Cohort in Korea.

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