Established risk prediction models for the incidence of a low lean tissue index in patients with peritoneal dialysis
Objective The objective of this study is to investigate the incidence of low lean tissue index (LTI) and the risk factors for low LTI in peritoneal dialysis (PD) patients, including to establish risk prediction models.Methods A total of 104 PD patients were enrolled from October 2019 to 2021. LTI wa...
| Main Authors: | , , , , , , , |
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| Format: | Article |
| Language: | English |
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Taylor & Francis Group
2022-12-01
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| Series: | Renal Failure |
| Subjects: | |
| Online Access: | https://www.tandfonline.com/doi/10.1080/0886022X.2022.2113794 |
| _version_ | 1811183179291164672 |
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| author | Feng Li Lei Wang Yanling Mao Changqing Mao Jie Yu Dan Zhao Yingying Zhang Ying Li |
| author_facet | Feng Li Lei Wang Yanling Mao Changqing Mao Jie Yu Dan Zhao Yingying Zhang Ying Li |
| author_sort | Feng Li |
| collection | DOAJ |
| description | Objective The objective of this study is to investigate the incidence of low lean tissue index (LTI) and the risk factors for low LTI in peritoneal dialysis (PD) patients, including to establish risk prediction models.Methods A total of 104 PD patients were enrolled from October 2019 to 2021. LTI was measured by bioimpedance spectroscopy. Multivariate logistic regression and machine learning were used to analyze the risk factors for low LTI in PD patients. Kaplan–Meier analysis was used to analyze the survival rate of patients with low LTI.Results The interleukin-6 (IL-6) level, red cell distribution width (RDW), overhydration, body mass index (BMI), and the subjective global assessment (SGA) rating significantly differed between the low LTI and normal LTI groups (all p < 0.05). Multivariate logistic regression showed that IL-6 (1.10 [95% CI: 1.02–1.18]), RDW (1.87 [95% CI: 1.18–2.97]), BMI (0.97 [95% CI: 0.68–0.91]), and the SGA rating (6.33 [95% CI: 1.59–25.30]) were independent risk factors for LTI. Cox regression analysis showed that low LTI (HR 3.14, [95% CI: 1.12–8.80]) was the only significant risk factor for all-cause death in peritoneal dialysis patients. The decision process to predict the incidence of low LTI in PD patients was established by machine learning, and the area under the curve of internal validation was 0.6349.Conclusions Low LTI is closely related to mortality in PD patients. Microinflammatory status, high RDW, low BMI and low SGA rating are risk factors for low LTI in PD patients. The developed prediction model may serve as a useful tool for assessing low LTI in PD patients. |
| first_indexed | 2024-04-11T09:43:30Z |
| format | Article |
| id | doaj.art-c3f5a13991f742b1a2a1743b7c301dce |
| institution | Directory Open Access Journal |
| issn | 0886-022X 1525-6049 |
| language | English |
| last_indexed | 2024-04-11T09:43:30Z |
| publishDate | 2022-12-01 |
| publisher | Taylor & Francis Group |
| record_format | Article |
| series | Renal Failure |
| spelling | doaj.art-c3f5a13991f742b1a2a1743b7c301dce2022-12-22T04:31:09ZengTaylor & Francis GroupRenal Failure0886-022X1525-60492022-12-014411417142510.1080/0886022X.2022.2113794Established risk prediction models for the incidence of a low lean tissue index in patients with peritoneal dialysisFeng Li0Lei Wang1Yanling Mao2Changqing Mao3Jie Yu4Dan Zhao5Yingying Zhang6Ying Li7Department of Nephrology, Jiading District Central Hospital Affiliated Shanghai University of Medicine & Health Sciences, Shanghai, ChinaDepartment of Nephrology, Jiading District Central Hospital Affiliated Shanghai University of Medicine & Health Sciences, Shanghai, ChinaDepartment of Nephrology, Jiading District Central Hospital Affiliated Shanghai University of Medicine & Health Sciences, Shanghai, ChinaDepartment of Nephrology, Jiading District Central Hospital Affiliated Shanghai University of Medicine & Health Sciences, Shanghai, ChinaDepartment of Nephrology, Jiading District Central Hospital Affiliated Shanghai University of Medicine & Health Sciences, Shanghai, ChinaDepartment of Nephrology, Tongji Hospital, School of Medicine, Tongji University, Shanghai, ChinaDepartment of Nephrology, Tongji Hospital, School of Medicine, Tongji University, Shanghai, ChinaDepartment of Nephrology, Jiading District Central Hospital Affiliated Shanghai University of Medicine & Health Sciences, Shanghai, ChinaObjective The objective of this study is to investigate the incidence of low lean tissue index (LTI) and the risk factors for low LTI in peritoneal dialysis (PD) patients, including to establish risk prediction models.Methods A total of 104 PD patients were enrolled from October 2019 to 2021. LTI was measured by bioimpedance spectroscopy. Multivariate logistic regression and machine learning were used to analyze the risk factors for low LTI in PD patients. Kaplan–Meier analysis was used to analyze the survival rate of patients with low LTI.Results The interleukin-6 (IL-6) level, red cell distribution width (RDW), overhydration, body mass index (BMI), and the subjective global assessment (SGA) rating significantly differed between the low LTI and normal LTI groups (all p < 0.05). Multivariate logistic regression showed that IL-6 (1.10 [95% CI: 1.02–1.18]), RDW (1.87 [95% CI: 1.18–2.97]), BMI (0.97 [95% CI: 0.68–0.91]), and the SGA rating (6.33 [95% CI: 1.59–25.30]) were independent risk factors for LTI. Cox regression analysis showed that low LTI (HR 3.14, [95% CI: 1.12–8.80]) was the only significant risk factor for all-cause death in peritoneal dialysis patients. The decision process to predict the incidence of low LTI in PD patients was established by machine learning, and the area under the curve of internal validation was 0.6349.Conclusions Low LTI is closely related to mortality in PD patients. Microinflammatory status, high RDW, low BMI and low SGA rating are risk factors for low LTI in PD patients. The developed prediction model may serve as a useful tool for assessing low LTI in PD patients.https://www.tandfonline.com/doi/10.1080/0886022X.2022.2113794Peritoneal dialysislean tissue indexmalnutritionbioimpedance spectroscopysubjective global assessment |
| spellingShingle | Feng Li Lei Wang Yanling Mao Changqing Mao Jie Yu Dan Zhao Yingying Zhang Ying Li Established risk prediction models for the incidence of a low lean tissue index in patients with peritoneal dialysis Renal Failure Peritoneal dialysis lean tissue index malnutrition bioimpedance spectroscopy subjective global assessment |
| title | Established risk prediction models for the incidence of a low lean tissue index in patients with peritoneal dialysis |
| title_full | Established risk prediction models for the incidence of a low lean tissue index in patients with peritoneal dialysis |
| title_fullStr | Established risk prediction models for the incidence of a low lean tissue index in patients with peritoneal dialysis |
| title_full_unstemmed | Established risk prediction models for the incidence of a low lean tissue index in patients with peritoneal dialysis |
| title_short | Established risk prediction models for the incidence of a low lean tissue index in patients with peritoneal dialysis |
| title_sort | established risk prediction models for the incidence of a low lean tissue index in patients with peritoneal dialysis |
| topic | Peritoneal dialysis lean tissue index malnutrition bioimpedance spectroscopy subjective global assessment |
| url | https://www.tandfonline.com/doi/10.1080/0886022X.2022.2113794 |
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