{"title":"为 KDPI 评分测量血清肌酐的最佳时间，以预测死亡供体肾移植手术后的肾功能。","authors":"","doi":"10.1016/j.transproceed.2024.02.022","DOIUrl":null,"url":null,"abstract":"<div><h3>Introduction</h3><p>The widely employed Kidney Donor Profile Index (KDPI) scoring system, designed for assessing deceased donors (DD), plays a pivotal role in predicting graft function post kidney transplantation<span><span> (KT). Given the dynamic nature of renal function, including </span>serum creatinine (sCr), in managing DDs, it remains uncertain optimal timing to use KDPI for assessing postoperative graft function.</span></p></div><div><h3>Methods</h3><p>In this retrospective review, we assessed 246 DDs who were managed within a donor management program from January 2010 to December 2021. We collected sCr values for KDPI scoring at admission, peak, and last measurements before KT. Recipient data included occurrence of slow graft function (SGF), delayed graft function<span> (DGF), and glomerular filtration rate (GFR) at one-year post-transplantation (1 Y). Using Receiver Operating Characteristic (ROC) and Pearson correlation analyses, we explored correlations of KDPI score (admission, peak, last) with graft function (SGF, DGF, GFR 1 Y).</span></p></div><div><h3>Results</h3><p>The average age of DDs and recipients was 49.78 ± 13.37 and 52.54 ± 10.49 years, respectively, with mean KDPI values at admission, peak, and last measurements of 62.36 ± 25.44, 66.94 ± 24.73, and 63.75 ± 25.80. After transplantation, SGF was observed in 81 recipients (32.9%) and DGF in 32 (13.0%). For SGF, the Area Under the Curve (AUC) from ROC analysis were 0.684 (95% CI, 0.615-0.753; <em>P < .</em>001) at admission, 0.691 (0.623-0.759; <em>P < .</em>001) at peak, and 0.697 (0.630-0.765; <em>P < .</em>001) at the last measurement. In predicting DGF, the corresponding AUC values were 0.746 (0.661-0.831; <em>P < .</em>001) at admission, 0.724 (0.637-0.810; <em>P < .</em>001) at peak, and 0.721 (0.643-0.809; <em>P < .</em>001) at the last. Moreover, KDPI scores at all time points—admission, peak, and last—moderately correlated with GFR 1 Y (R = -0.426, -0.423, -0.417).</p></div><div><h3>Conclusion</h3><p>KDPI measurements at all time points, particularly admission, would be more effective in predicting DGF in DDKT.</p></div>","PeriodicalId":23246,"journal":{"name":"Transplantation proceedings","volume":null,"pages":null},"PeriodicalIF":0.8000,"publicationDate":"2024-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Optimal Timing of Serum Creatinine Measurement for KDPI Scoring to Predict Postoperative Renal Function in Deceased Donor Kidney Transplantation\",\"authors\":\"\",\"doi\":\"10.1016/j.transproceed.2024.02.022\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><h3>Introduction</h3><p>The widely employed Kidney Donor Profile Index (KDPI) scoring system, designed for assessing deceased donors (DD), plays a pivotal role in predicting graft function post kidney transplantation<span><span> (KT). Given the dynamic nature of renal function, including </span>serum creatinine (sCr), in managing DDs, it remains uncertain optimal timing to use KDPI for assessing postoperative graft function.</span></p></div><div><h3>Methods</h3><p>In this retrospective review, we assessed 246 DDs who were managed within a donor management program from January 2010 to December 2021. We collected sCr values for KDPI scoring at admission, peak, and last measurements before KT. Recipient data included occurrence of slow graft function (SGF), delayed graft function<span> (DGF), and glomerular filtration rate (GFR) at one-year post-transplantation (1 Y). Using Receiver Operating Characteristic (ROC) and Pearson correlation analyses, we explored correlations of KDPI score (admission, peak, last) with graft function (SGF, DGF, GFR 1 Y).</span></p></div><div><h3>Results</h3><p>The average age of DDs and recipients was 49.78 ± 13.37 and 52.54 ± 10.49 years, respectively, with mean KDPI values at admission, peak, and last measurements of 62.36 ± 25.44, 66.94 ± 24.73, and 63.75 ± 25.80. After transplantation, SGF was observed in 81 recipients (32.9%) and DGF in 32 (13.0%). For SGF, the Area Under the Curve (AUC) from ROC analysis were 0.684 (95% CI, 0.615-0.753; <em>P < .</em>001) at admission, 0.691 (0.623-0.759; <em>P < .</em>001) at peak, and 0.697 (0.630-0.765; <em>P < .</em>001) at the last measurement. In predicting DGF, the corresponding AUC values were 0.746 (0.661-0.831; <em>P < .</em>001) at admission, 0.724 (0.637-0.810; <em>P < .</em>001) at peak, and 0.721 (0.643-0.809; <em>P < .</em>001) at the last. Moreover, KDPI scores at all time points—admission, peak, and last—moderately correlated with GFR 1 Y (R = -0.426, -0.423, -0.417).</p></div><div><h3>Conclusion</h3><p>KDPI measurements at all time points, particularly admission, would be more effective in predicting DGF in DDKT.</p></div>\",\"PeriodicalId\":23246,\"journal\":{\"name\":\"Transplantation proceedings\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.8000,\"publicationDate\":\"2024-07-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Transplantation proceedings\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0041134524003257\",\"RegionNum\":4,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"IMMUNOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Transplantation proceedings","FirstCategoryId":"3","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0041134524003257","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"IMMUNOLOGY","Score":null,"Total":0}
Optimal Timing of Serum Creatinine Measurement for KDPI Scoring to Predict Postoperative Renal Function in Deceased Donor Kidney Transplantation
Introduction
The widely employed Kidney Donor Profile Index (KDPI) scoring system, designed for assessing deceased donors (DD), plays a pivotal role in predicting graft function post kidney transplantation (KT). Given the dynamic nature of renal function, including serum creatinine (sCr), in managing DDs, it remains uncertain optimal timing to use KDPI for assessing postoperative graft function.
Methods
In this retrospective review, we assessed 246 DDs who were managed within a donor management program from January 2010 to December 2021. We collected sCr values for KDPI scoring at admission, peak, and last measurements before KT. Recipient data included occurrence of slow graft function (SGF), delayed graft function (DGF), and glomerular filtration rate (GFR) at one-year post-transplantation (1 Y). Using Receiver Operating Characteristic (ROC) and Pearson correlation analyses, we explored correlations of KDPI score (admission, peak, last) with graft function (SGF, DGF, GFR 1 Y).
Results
The average age of DDs and recipients was 49.78 ± 13.37 and 52.54 ± 10.49 years, respectively, with mean KDPI values at admission, peak, and last measurements of 62.36 ± 25.44, 66.94 ± 24.73, and 63.75 ± 25.80. After transplantation, SGF was observed in 81 recipients (32.9%) and DGF in 32 (13.0%). For SGF, the Area Under the Curve (AUC) from ROC analysis were 0.684 (95% CI, 0.615-0.753; P < .001) at admission, 0.691 (0.623-0.759; P < .001) at peak, and 0.697 (0.630-0.765; P < .001) at the last measurement. In predicting DGF, the corresponding AUC values were 0.746 (0.661-0.831; P < .001) at admission, 0.724 (0.637-0.810; P < .001) at peak, and 0.721 (0.643-0.809; P < .001) at the last. Moreover, KDPI scores at all time points—admission, peak, and last—moderately correlated with GFR 1 Y (R = -0.426, -0.423, -0.417).
Conclusion
KDPI measurements at all time points, particularly admission, would be more effective in predicting DGF in DDKT.
期刊介绍：
Transplantation Proceedings publishes several different categories of manuscripts, all of which undergo extensive peer review by recognized authorities in the field prior to their acceptance for publication.
The first type of manuscripts consists of sets of papers providing an in-depth expression of the current state of the art in various rapidly developing components of world transplantation biology and medicine. These manuscripts emanate from congresses of the affiliated transplantation societies, from Symposia sponsored by the Societies, as well as special Conferences and Workshops covering related topics.
Transplantation Proceedings also publishes several special sections including publication of Clinical Transplantation Proceedings, being rapid original contributions of preclinical and clinical experiences. These manuscripts undergo review by members of the Editorial Board.
Original basic or clinical science articles, clinical trials and case studies can be submitted to the journal?s open access companion title Transplantation Reports.
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