Xinyi Zhou, Juan Yu, Ke Shi, Xiaohong Guan, Tian Zhang, Wenjing Zhao, Hailing Zhang
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The LCGM was conducted using Mplus 8.4, and a multiple linear regression model was employed to examine the ability of PNI trajectory to predict renal allograft function. RESULTS Using LCGM, 2 classes of PNI patterns best fit the sample: the low PNI slow growth group (C1, n=122,47.5%) and the high PNI fast growth group (C2, n=135, 52.5%). The linear regression showed that being a woman and being in the high PNI fast growth group were negative predictors of a high creatinine level (B=-35.946, P<0.001; B=-15.147, P=0.023). CONCLUSIONS There were 2 trajectories of PNI in the sample, with lower creatinine values 1 year after transplantation in the high PNI fast growth class. The initial level and developmental rate of PNI can positively predict renal allograft function. PNI may serve as a prognostic marker for renal allograft function in kidney transplant recipients.</p>","PeriodicalId":7935,"journal":{"name":"Annals of Transplantation","volume":"30 ","pages":"e947388"},"PeriodicalIF":1.4000,"publicationDate":"2025-05-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12103085/pdf/","citationCount":"0","resultStr":"{\"title\":\"Prognostic Nutritional Index Trajectories Predict Kidney Function in Kidney Transplant Recipients: A Latent Class Growth Model Study.\",\"authors\":\"Xinyi Zhou, Juan Yu, Ke Shi, Xiaohong Guan, Tian Zhang, Wenjing Zhao, Hailing Zhang\",\"doi\":\"10.12659/AOT.947388\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>BACKGROUND Nutritional status can be an important, dynamic determinant of clinical outcomes in kidney transplant recipients. This study investigated the trajectory and potential classes of the prognostic nutritional index (PNI) in kidney transplant recipients using a latent class growth model (LCGM), and assessed their predictive role in renal allograft function. MATERIAL AND METHODS This retrospective study included 257 kidney transplant recipients who received treatment in a tertiary hospital in Anhui Province from January 2019 to November 2020. Their data were collected at each 4 timepoints: T0 (pre-surgery, using the results of the recipient's most recent laboratory test prior to transplant), T1, T2, and T3 (1, 6, and 12 months, respectively after transplant surgery). The LCGM was conducted using Mplus 8.4, and a multiple linear regression model was employed to examine the ability of PNI trajectory to predict renal allograft function. RESULTS Using LCGM, 2 classes of PNI patterns best fit the sample: the low PNI slow growth group (C1, n=122,47.5%) and the high PNI fast growth group (C2, n=135, 52.5%). The linear regression showed that being a woman and being in the high PNI fast growth group were negative predictors of a high creatinine level (B=-35.946, P<0.001; B=-15.147, P=0.023). CONCLUSIONS There were 2 trajectories of PNI in the sample, with lower creatinine values 1 year after transplantation in the high PNI fast growth class. The initial level and developmental rate of PNI can positively predict renal allograft function. 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引用次数: 0
摘要
背景:营养状况是肾移植受者临床预后的重要动态决定因素。本研究使用潜在类生长模型(LCGM)研究肾移植受者预后营养指数(PNI)的发展轨迹和潜在类别,并评估其在同种异体肾移植功能中的预测作用。材料与方法本回顾性研究包括2019年1月至2020年11月在安徽省某三级医院接受肾移植治疗的257例肾移植受者。在每个4个时间点收集他们的数据:T0(术前,使用移植前受体最近的实验室检查结果),T1, T2和T3(分别在移植手术后1,6和12个月)。采用Mplus 8.4进行LCGM,并采用多元线性回归模型检验PNI轨迹预测同种异体肾移植功能的能力。结果采用LCGM,两类PNI模式最适合样本:低PNI慢生长组(C1, n=122,47.5%)和高PNI快生长组(C2, n=135, 52.5%)。线性回归显示,女性和高PNI快速生长组是高肌酐水平的负相关预测因子(B=-35.946, P
Prognostic Nutritional Index Trajectories Predict Kidney Function in Kidney Transplant Recipients: A Latent Class Growth Model Study.
BACKGROUND Nutritional status can be an important, dynamic determinant of clinical outcomes in kidney transplant recipients. This study investigated the trajectory and potential classes of the prognostic nutritional index (PNI) in kidney transplant recipients using a latent class growth model (LCGM), and assessed their predictive role in renal allograft function. MATERIAL AND METHODS This retrospective study included 257 kidney transplant recipients who received treatment in a tertiary hospital in Anhui Province from January 2019 to November 2020. Their data were collected at each 4 timepoints: T0 (pre-surgery, using the results of the recipient's most recent laboratory test prior to transplant), T1, T2, and T3 (1, 6, and 12 months, respectively after transplant surgery). The LCGM was conducted using Mplus 8.4, and a multiple linear regression model was employed to examine the ability of PNI trajectory to predict renal allograft function. RESULTS Using LCGM, 2 classes of PNI patterns best fit the sample: the low PNI slow growth group (C1, n=122,47.5%) and the high PNI fast growth group (C2, n=135, 52.5%). The linear regression showed that being a woman and being in the high PNI fast growth group were negative predictors of a high creatinine level (B=-35.946, P<0.001; B=-15.147, P=0.023). CONCLUSIONS There were 2 trajectories of PNI in the sample, with lower creatinine values 1 year after transplantation in the high PNI fast growth class. The initial level and developmental rate of PNI can positively predict renal allograft function. PNI may serve as a prognostic marker for renal allograft function in kidney transplant recipients.
期刊介绍:
Annals of Transplantation is one of the fast-developing journals open to all scientists and fields of transplant medicine and related research. The journal is published quarterly and provides extensive coverage of the most important advances in transplantation.
Using an electronic on-line submission and peer review tracking system, Annals of Transplantation is committed to rapid review and publication. The average time to first decision is around 3-4 weeks. Time to publication of accepted manuscripts continues to be shortened, with the Editorial team committed to a goal of 3 months from acceptance to publication.
Expert reseachers and clinicians from around the world contribute original Articles, Review Papers, Case Reports and Special Reports in every pertinent specialty, providing a lot of arguments for discussion of exciting developments and controversies in the field.