Literature DB >> 26787778

External Validation of the Kidney Failure Risk Equation and Re-Calibration with Addition of Ultrasound Parameters.

Claudia S Lennartz1, John William Pickering2, Sarah Seiler-Mußler1, Lucie Bauer1, Kathrin Untersteller1, Insa E Emrich1, Adam M Zawada1, Jörg Radermacher3, Navdeep Tangri4, Danilo Fliser1, Gunnar H Heine5.   

Abstract

BACKGROUND AND OBJECTIVES: Progression of CKD toward ESRD is heterogeneous. The Kidney Failure Risk Equation (KFRE) was developed to identify CKD patients at high risk of ESRD. We aimed to externally validate KFRE and to test whether the addition of predefined Duplex ultrasound markers - renal resistive index (RRI) or difference of resistive indices in spleen and kidney (DI-RISK) - improved ESRD prediction. DESIGN, SETTING, PARTICIPANTS, & MEASUREMENTS: The prospective Cardiovascular and Renal Outcome in CKD 2-4 Patients-The Fourth Homburg evaluation (CARE FOR HOMe) study recruits CKD stage G2-G4 patients referred to a tertiary referral center for nephrologic care. Four hundred three CARE FOR HOMe participants enrolled between 2008 and 2012 had available RRI measurements at study inclusion; they were subsequently followed for a mean of 4.4±1.6 years. This subcohort was used to validate KFRE and to assess the added value of the ultrasound markers (new models KFRE+RRI and KFRE+DI-RISK). Model performance was assessed by log-likelihood ratio test, c-statistic, integrated discrimination improvement metrics (for study participants without subsequent ESRD [IDI No ESRD] and for patients with ESRD [IDI ESRD]), and calibration plots. If either new model improved on KFRE, we determined to validate it in an independent cohort of 162 CKD patients.
RESULTS: KFRE predicted ESRD in CARE FOR HOMe participants with a c-statistic of 0.91 (95% confidence interval, 0.83 to 0.99). Adding RRI improved the KFRE model (P<0.001), and the KFRE+RRI model was well calibrated; however, the c-statistic (0.91 [0.83-1.00]) was similar, and overall sensitivity (IDI No ESRD=0.05 [0.00-0.10]) or overall specificity (IDI ESRD=0.00 [0.00-0.01]) did not improve. Adding DI-RISK did not improve the KRFE model. In the external validation cohort, we confirmed that the KFRE+RRI model did not outperform KFRE.
CONCLUSIONS: Routine Duplex examinations among CKD patients did not improve risk prediction for progression to ESRD beyond a validated equation.
Copyright © 2016 by the American Society of Nephrology.

Entities:  

Keywords:  Doppler; calibration; chronic kidney failure; humans; prospective studies; renal insufficiency, chronic; survivors; tertiary care centers; ultrasonography

Mesh:

Substances:

Year:  2016        PMID: 26787778      PMCID: PMC4822670          DOI: 10.2215/CJN.08110715

Source DB:  PubMed          Journal:  Clin J Am Soc Nephrol        ISSN: 1555-9041            Impact factor:   8.237


  33 in total

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2.  Integrating the predictiveness of a marker with its performance as a classifier.

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3.  Evaluating the added predictive ability of a new marker: from area under the ROC curve to reclassification and beyond.

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4.  Resistive index predicts renal prognosis in chronic kidney disease.

Authors:  Toshihiro Sugiura; Akira Wada
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5.  Renal resistive index and long-term outcome in chronic nephropathies.

Authors:  Claudia Parolini; Annalisa Noce; Emiliano Staffolani; Gerlando F Giarrizzo; Stefano Costanzi; Giorgio Splendiani
Journal:  Radiology       Date:  2009-06-15       Impact factor: 11.105

6.  A predictive model for progression of chronic kidney disease to kidney failure.

Authors:  Navdeep Tangri; Lesley A Stevens; John Griffith; Hocine Tighiouart; Ognjenka Djurdjev; David Naimark; Adeera Levin; Andrew S Levey
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7.  Color Doppler indices of renal allografts depend on vascular stiffness of the transplant recipients.

Authors:  V Schwenger; T Keller; N Hofmann; O Hoffmann; C Sommerer; A M Nahm; C Morath; M Zeier; B Krumme
Journal:  Am J Transplant       Date:  2006-11       Impact factor: 8.086

8.  Renal resistance index is a marker of future renal dysfunction in patients with essential hypertension.

Authors:  Takafumi Okura; Mie Kurata; Jun Irita; Daijiro Enomoto; Masanori Jotoku; Tomoaki Nagao; Mitsuko Koresawa; Shiho Kojima; Yasuyuki Hamano; Shinichi Mashiba; Ken-Ichi Miyoshi; Jitsuo Higaki
Journal:  J Nephrol       Date:  2010 Mar-Apr       Impact factor: 3.902

9.  The pulsatility index and the resistive index in renal arteries. Associations with long-term progression in chronic renal failure.

Authors:  L J Petersen; J R Petersen; U Talleruphuus; S D Ladefoged; J Mehlsen; H A Jensen
Journal:  Nephrol Dial Transplant       Date:  1997-07       Impact factor: 5.992

10.  Predicting the risk of dialysis and transplant among patients with CKD: a retrospective cohort study.

Authors:  Eric S Johnson; Micah L Thorp; Robert W Platt; David H Smith
Journal:  Am J Kidney Dis       Date:  2008-06-30       Impact factor: 8.860

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  15 in total

1.  Arteriovenous Fistula Maturation in Prevalent Hemodialysis Patients in the United States: A National Study.

Authors:  Kenneth J Woodside; Sarah Bell; Purna Mukhopadhyay; Kaitlyn J Repeck; Ian T Robinson; Ashley R Eckard; Sudipta Dasmunshi; Brett W Plattner; Jeffrey Pearson; Douglas E Schaubel; Ronald L Pisoni; Rajiv Saran
Journal:  Am J Kidney Dis       Date:  2018-02-09       Impact factor: 8.860

Review 2.  Renal Resistive Index: not only kidney.

Authors:  Pierpaolo Di Nicolò; Antonio Granata
Journal:  Clin Exp Nephrol       Date:  2016-08-16       Impact factor: 2.801

3.  Shared decision-making in advanced kidney disease: a scoping review.

Authors:  Noel Engels; Gretchen N de Graav; Paul van der Nat; Marinus van den Dorpel; Anne M Stiggelbout; Willem Jan Bos
Journal:  BMJ Open       Date:  2022-09-21       Impact factor: 3.006

4.  Performance of the Kidney Failure Risk Equation by Disease Etiology in Advanced CKD.

Authors:  Gregory L Hundemer; Navdeep Tangri; Manish M Sood; Tim Ramsay; Ann Bugeja; Pierre A Brown; Edward G Clark; Mohan Biyani; Christine A White; Ayub Akbari
Journal:  Clin J Am Soc Nephrol       Date:  2020-09-14       Impact factor: 8.237

5.  Lessons learnt when accounting for competing events in the external validation of time-to-event prognostic models.

Authors:  Chava L Ramspek; Lucy Teece; Kym I E Snell; Marie Evans; Richard D Riley; Maarten van Smeden; Nan van Geloven; Merel van Diepen
Journal:  Int J Epidemiol       Date:  2022-05-09       Impact factor: 9.685

6.  Towards the best kidney failure prediction tool: a systematic review and selection aid.

Authors:  Chava L Ramspek; Ype de Jong; Friedo W Dekker; Merel van Diepen
Journal:  Nephrol Dial Transplant       Date:  2020-09-01       Impact factor: 5.992

7.  Validation of the kidney failure risk equation for end-stage kidney disease in Southeast Asia.

Authors:  Yeli Wang; Francis Ngoc Hoang Long Nguyen; John C Allen; Jasmine Quan Lan Lew; Ngiap Chuan Tan; Tazeen H Jafar
Journal:  BMC Nephrol       Date:  2019-12-04       Impact factor: 2.388

Review 8.  Renal resistive index in hypertensive patients.

Authors:  Ioannis Andrikou; Costas Tsioufis; Dimitris Konstantinidis; Alexandros Kasiakogias; Kyriakos Dimitriadis; Ioannis Leontsinis; Eirini Andrikou; Elias Sanidas; Ioannis Kallikazaros; Dimitris Tousoulis
Journal:  J Clin Hypertens (Greenwich)       Date:  2018-10-25       Impact factor: 3.738

Review 9.  Statistical Methods for Cohort Studies of CKD: Prediction Modeling.

Authors:  Jason Roy; Haochang Shou; Dawei Xie; Jesse Y Hsu; Wei Yang; Amanda H Anderson; J Richard Landis; Christopher Jepson; Jiang He; Kathleen D Liu; Chi-Yuan Hsu; Harold I Feldman
Journal:  Clin J Am Soc Nephrol       Date:  2016-09-22       Impact factor: 10.614

10.  Value of adding the renal pathological score to the kidney failure risk equation in advanced diabetic nephropathy.

Authors:  Masayuki Yamanouchi; Junichi Hoshino; Yoshifumi Ubara; Kenmei Takaichi; Keiichi Kinowaki; Takeshi Fujii; Kenichi Ohashi; Koki Mise; Tadashi Toyama; Akinori Hara; Kiyoki Kitagawa; Miho Shimizu; Kengo Furuichi; Takashi Wada
Journal:  PLoS One       Date:  2018-01-16       Impact factor: 3.240

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