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Ling Y, Wang L, Liu X, Wang K, Ma Z, Yu Y, Liu W, Liang W, Qian K, Xu Y, Zuo X, Ge S, Yao Y. Development and validation of prediction model for technique failure in peritoneal dialysis patients: An observational study. Nephrology (Carlton) 2024; 29:383-393. [PMID: 38373789 DOI: 10.1111/nep.14280] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/22/2023] [Revised: 01/23/2024] [Accepted: 02/02/2024] [Indexed: 02/21/2024]
Abstract
AIM This study aimed to establish a prediction model in peritoneal dialysis patients to estimate the risk of technique failure and guide clinical practice. METHODS Clinical and laboratory data of 424 adult peritoneal dialysis patients were retrospectively collected. The risk prediction models were built using univariate Cox regression, best subsets approach and LASSO Cox regression. Final nomogram was constructed based on the best model selected by the area under the curve. RESULTS After comparing three models, the nomogram was built using the LASSO Cox regression model. This model included variables consisting of hypertension and peritonitis, serum creatinine, low-density lipoprotein, fibrinogen and thrombin time, and low red blood cell count, serum albumin, triglyceride and prothrombin activity. The predictive model constructed performed well using receiver operating characteristic curve and area under the curve value, C-index and calibration curve. CONCLUSION This study developed and verified a new prediction instrument for the risk of technique failure among peritoneal dialysis patients.
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Affiliation(s)
- Yue Ling
- Department of Nephrology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Le Wang
- Department of Nephrology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Xiaoqin Liu
- Department of Nephrology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Koushu Wang
- Department of Nephrology, The Third People's Hospital of Chengdu, Chengdu, Sichuan, China
| | - Zufu Ma
- Department of Nephrology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Yang Yu
- Department of Ultrasound, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Wei Liu
- Department of Nephrology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Wangqun Liang
- Department of Nephrology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Kun Qian
- Department of Nephrology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Yulin Xu
- Department of Nephrology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Xuezhi Zuo
- Department of Clinical Nutrition, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Shuwang Ge
- Department of Nephrology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Ying Yao
- Department of Nephrology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
- Department of Clinical Nutrition, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
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Cho Y, Chow KM, Kam-Tao Li P, Runnegar N, Johnson DW. Peritoneal Dialysis-Related Infections. Clin J Am Soc Nephrol 2024; 19:641-649. [PMID: 37574658 PMCID: PMC11108252 DOI: 10.2215/cjn.0000000000000280] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/02/2023] [Accepted: 08/01/2023] [Indexed: 08/15/2023]
Abstract
Peritoneal dialysis (PD) represents an important treatment choice for patients with kidney failure. It allows them to dialyze outside the hospital setting, facilitating enhanced opportunities to participate in life-related activities, flexibility in schedules, time and cost savings from reduced travel to dialysis centers, and improved quality of life. Despite its numerous advantages, PD utilization has been static or diminishing in parts of the world. PD-related infection, such as peritonitis, exit-site infection, or tunnel infection, is a major concern for patients, caregivers, and health professionals-which may result in hesitation to consider this as treatment or to cease therapy when these complications take place. In this review, the definition, epidemiology, risk factors, prevention, and treatment of PD-related infection on the basis of the contemporary evidence will be described.
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Affiliation(s)
- Yeoungjee Cho
- Australasian Kidney Trials Network, University of Queensland, Brisbane, Australia
- Department of Kidney and Transplant Services, Princess Alexandra Hospital, Brisbane, Australia
| | - Kai-Ming Chow
- Department of Medicine and Therapeutics, Prince of Wales Hospital, The Chinese University of Hong Kong, Hong Kong, China
- Carol and Richard Yu Peritoneal Dialysis Research Centre, Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Hong Kong, China
| | - Philip Kam-Tao Li
- Department of Medicine and Therapeutics, Prince of Wales Hospital, The Chinese University of Hong Kong, Hong Kong, China
- Carol and Richard Yu Peritoneal Dialysis Research Centre, Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Hong Kong, China
| | - Naomi Runnegar
- Infectious Management Services, Princess Alexandra Hospital, University of Queensland, Brisbane, Australia
| | - David W. Johnson
- Australasian Kidney Trials Network, University of Queensland, Brisbane, Australia
- Department of Kidney and Transplant Services, Princess Alexandra Hospital, Brisbane, Australia
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Ma L, Zhang C, Gao J, Jiao X, Yu Z, Zhu Y, Wang T, Ma X, Wang Y, Tang W, Zhao X, Ruan W, Wang T. Mortality prediction with adaptive feature importance recalibration for peritoneal dialysis patients. PATTERNS (NEW YORK, N.Y.) 2023; 4:100892. [PMID: 38106617 PMCID: PMC10724364 DOI: 10.1016/j.patter.2023.100892] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 04/25/2023] [Revised: 08/18/2023] [Accepted: 11/10/2023] [Indexed: 12/19/2023]
Abstract
The study aims to develop AICare, an interpretable mortality prediction model, using electronic medical records (EMR) from follow-up visits for end-stage renal disease (ESRD) patients. AICare includes a multichannel feature extraction module and an adaptive feature importance recalibration module. It integrates dynamic records and static features to perform personalized health context representation learning. The dataset encompasses 13,091 visits and demographic data of 656 peritoneal dialysis (PD) patients spanning 12 years. An additional public dataset of 4,789 visits from 1,363 hemodialysis (HD) patients is also considered. AICare outperforms traditional deep learning models in mortality prediction while retaining interpretability. It uncovers mortality-feature relationships and variations in feature importance and provides reference values. An AI-doctor interaction system is developed for visualizing patients' health trajectories and risk indicators.
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Affiliation(s)
| | | | - Junyi Gao
- Centre for Medical Informatics, University of Edinburgh, Edinburgh, UK
- Health Data Research UK, London, UK
| | | | | | | | | | - Xinyu Ma
- Peking University, Beijing, China
| | | | - Wen Tang
- Department of Nephrology, Peking University Third Hospital, Beijing, China
| | - Xinju Zhao
- Department of Nephrology, Peking University People’s Hospital, Beijing, China
| | - Wenjie Ruan
- Department of Computer Science, University of Exeter, Exeter, UK
| | - Tao Wang
- Department of Nephrology, Peking University Third Hospital, Beijing, China
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Song X, Zha Y, Liu J, He P, He L. Associations between liver function parameters and poor clinical outcomes in peritoneal dialysis patients. Ther Apher Dial 2023; 27:12-18. [PMID: 36114736 PMCID: PMC10087744 DOI: 10.1111/1744-9987.13926] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/08/2022] [Revised: 07/25/2022] [Accepted: 09/06/2022] [Indexed: 01/05/2023]
Abstract
Patients with end-stage renal disease (ESRD) have significantly lower survival rates compared with the general population of the same age. Peritoneal dialysis (PD) is an effective treatment for patients with ESRD, but the clinical outcome of PD patients is still not promising. The survival of PD patients is associated with various clinical factors, and exploring some valid risk predictors may be beneficial for this population. In this review, by integrating the latest research, we summarized the association of some common and novel liver function parameters (ALT, AST, ALP, GGT, serum bilirubin, pre-albumin, albumin, albumin-globulin ratio [AGR], serum ferritin, and hyaluronic acid) with clinical outcomes in PD patients. It may contribute to a better understanding of potential risk factors and help to develop strategies to prevent the disease progression.
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Affiliation(s)
- Xiyu Song
- School of Basic Medicine, Air Force Medical University, Xi'an, Shaanxi, People's Republic of China
| | - Yang Zha
- Department of Nephrology, Xijing Hospital, Air Force Medical University, Xi'an, Shaanxi, People's Republic of China
| | - Jing Liu
- Department of Nephrology, Xijing Hospital, Air Force Medical University, Xi'an, Shaanxi, People's Republic of China
| | - Peng He
- Department of Nephrology, Xijing Hospital, Air Force Medical University, Xi'an, Shaanxi, People's Republic of China
| | - Lijie He
- Department of Nephrology, Xijing Hospital, Air Force Medical University, Xi'an, Shaanxi, People's Republic of China
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