Prediction of non-responsiveness to pre-dialysis care program in patients with chronic kidney disease: a retrospective cohort analysis
Abstract The responsiveness of patients with chronic kidney disease (CKD) to nephrologists’ care is unpredictable. We defined the longitudinal stages (LSs) 1–5 of estimated glomerular filtration rate (eGFR) by group-based trajectory modeling for repeated eGFR measurements of 7135 patients with CKD a...
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2021
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oai:doaj.org-article:2a099885fd6045f195422925c4e662a72021-12-02T18:33:57ZPrediction of non-responsiveness to pre-dialysis care program in patients with chronic kidney disease: a retrospective cohort analysis10.1038/s41598-021-93254-02045-2322https://doaj.org/article/2a099885fd6045f195422925c4e662a72021-07-01T00:00:00Zhttps://doi.org/10.1038/s41598-021-93254-0https://doaj.org/toc/2045-2322Abstract The responsiveness of patients with chronic kidney disease (CKD) to nephrologists’ care is unpredictable. We defined the longitudinal stages (LSs) 1–5 of estimated glomerular filtration rate (eGFR) by group-based trajectory modeling for repeated eGFR measurements of 7135 patients with CKD aged 20–90 years from a 13-year pre-end-stage renal disease (ESRD) care registry. Patients were considered nonresponsive to the pre-dialysis care if they had a more advanced eGFR LS compared with the baseline. Conversely, those with improved or stable eGFR LS were considered responsive. The proportion of patients with CKD stage progression increased with the increase in the baseline CKD stage (stages 1–2: 29.2%; stage 4: 45.8%). The adjusted times to ESRD and all-cause mortality in patients with eGFR LS-5 were 92% (95% confidence interval [CI] 86–96%) and 57% (95% CI 48–65%) shorter, respectively, than in patients with eGFR LS-3A. Among patients with baseline CKD stages 3 and 4, the adjusted times to ESRD and all-cause death in the nonresponsive patients were 39% (95% CI 33–44%) and 20% (95% CI 14–26%) shorter, respectively, than in the responsive patients. Our proposed Renal Care Responsiveness Prediction (RCRP) model performed significantly better than the conventional Kidney Failure Risk Equation in discrimination, calibration, and net benefit according to decision curve analysis. Non-responsiveness to nephrologists’ care is associated with rapid progression to ESRD and all-cause mortality. The RCRP model improves early identification of responsiveness based on variables collected during enrollment in a pre-ESRD program. Urgent attention should be given to characterize the underlying heterogeneous responsiveness to pre-dialysis care.Emily K. KingMing-Han HsiehDavid R. ChangCheng-Ting LuI-Wen TingCharles C. N. WangPei-Shan ChenHung-Chieh YehHsiu-Yin ChiangChin-Chi KuoNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 11, Iss 1, Pp 1-12 (2021) |
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Medicine R Science Q Emily K. King Ming-Han Hsieh David R. Chang Cheng-Ting Lu I-Wen Ting Charles C. N. Wang Pei-Shan Chen Hung-Chieh Yeh Hsiu-Yin Chiang Chin-Chi Kuo Prediction of non-responsiveness to pre-dialysis care program in patients with chronic kidney disease: a retrospective cohort analysis |
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Abstract The responsiveness of patients with chronic kidney disease (CKD) to nephrologists’ care is unpredictable. We defined the longitudinal stages (LSs) 1–5 of estimated glomerular filtration rate (eGFR) by group-based trajectory modeling for repeated eGFR measurements of 7135 patients with CKD aged 20–90 years from a 13-year pre-end-stage renal disease (ESRD) care registry. Patients were considered nonresponsive to the pre-dialysis care if they had a more advanced eGFR LS compared with the baseline. Conversely, those with improved or stable eGFR LS were considered responsive. The proportion of patients with CKD stage progression increased with the increase in the baseline CKD stage (stages 1–2: 29.2%; stage 4: 45.8%). The adjusted times to ESRD and all-cause mortality in patients with eGFR LS-5 were 92% (95% confidence interval [CI] 86–96%) and 57% (95% CI 48–65%) shorter, respectively, than in patients with eGFR LS-3A. Among patients with baseline CKD stages 3 and 4, the adjusted times to ESRD and all-cause death in the nonresponsive patients were 39% (95% CI 33–44%) and 20% (95% CI 14–26%) shorter, respectively, than in the responsive patients. Our proposed Renal Care Responsiveness Prediction (RCRP) model performed significantly better than the conventional Kidney Failure Risk Equation in discrimination, calibration, and net benefit according to decision curve analysis. Non-responsiveness to nephrologists’ care is associated with rapid progression to ESRD and all-cause mortality. The RCRP model improves early identification of responsiveness based on variables collected during enrollment in a pre-ESRD program. Urgent attention should be given to characterize the underlying heterogeneous responsiveness to pre-dialysis care. |
format |
article |
author |
Emily K. King Ming-Han Hsieh David R. Chang Cheng-Ting Lu I-Wen Ting Charles C. N. Wang Pei-Shan Chen Hung-Chieh Yeh Hsiu-Yin Chiang Chin-Chi Kuo |
author_facet |
Emily K. King Ming-Han Hsieh David R. Chang Cheng-Ting Lu I-Wen Ting Charles C. N. Wang Pei-Shan Chen Hung-Chieh Yeh Hsiu-Yin Chiang Chin-Chi Kuo |
author_sort |
Emily K. King |
title |
Prediction of non-responsiveness to pre-dialysis care program in patients with chronic kidney disease: a retrospective cohort analysis |
title_short |
Prediction of non-responsiveness to pre-dialysis care program in patients with chronic kidney disease: a retrospective cohort analysis |
title_full |
Prediction of non-responsiveness to pre-dialysis care program in patients with chronic kidney disease: a retrospective cohort analysis |
title_fullStr |
Prediction of non-responsiveness to pre-dialysis care program in patients with chronic kidney disease: a retrospective cohort analysis |
title_full_unstemmed |
Prediction of non-responsiveness to pre-dialysis care program in patients with chronic kidney disease: a retrospective cohort analysis |
title_sort |
prediction of non-responsiveness to pre-dialysis care program in patients with chronic kidney disease: a retrospective cohort analysis |
publisher |
Nature Portfolio |
publishDate |
2021 |
url |
https://doaj.org/article/2a099885fd6045f195422925c4e662a7 |
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