Predicting mortality in patients with diabetes starting dialysis.

<h4>Background</h4>While some prediction models have been developed for diabetic populations, prediction rules for mortality in diabetic dialysis patients are still lacking. Therefore, the objective of this study was to identify predictors for 1-year mortality in diabetic dialysis patien...

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Autores principales:	Merel van Diepen, Marielle A Schroijen, Olaf M Dekkers, Joris I Rotmans, Raymond T Krediet, Elisabeth W Boeschoten, Friedo W Dekker
Formato:	article
Lenguaje:	EN
Publicado:	Public Library of Science (PLoS) 2014
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/090db3bd45aa49f8bdc39b9710380597
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spelling	oai:doaj.org-article:090db3bd45aa49f8bdc39b97103805972021-11-18T08:29:53ZPredicting mortality in patients with diabetes starting dialysis.1932-620310.1371/journal.pone.0089744https://doaj.org/article/090db3bd45aa49f8bdc39b97103805972014-01-01T00:00:00Zhttps://www.ncbi.nlm.nih.gov/pmc/articles/pmid/24594735/?tool=EBIhttps://doaj.org/toc/1932-6203<h4>Background</h4>While some prediction models have been developed for diabetic populations, prediction rules for mortality in diabetic dialysis patients are still lacking. Therefore, the objective of this study was to identify predictors for 1-year mortality in diabetic dialysis patients and use these results to develop a prediction model.<h4>Methods</h4>Data were used from the Netherlands Cooperative Study on the Adequacy of Dialysis (NECOSAD), a multicenter, prospective cohort study in which incident patients with end stage renal disease (ESRD) were monitored until transplantation or death. For the present analysis, patients with DM at baseline were included. A prediction algorithm for 1-year all-cause mortality was developed through multivariate logistic regression. Candidate predictors were selected based on literature and clinical expertise. The final model was constructed through backward selection. The model's predictive performance, measured by calibration and discrimination, was assessed and internally validated through bootstrapping.<h4>Results</h4>A total of 394 patients were available for statistical analysis; 82 (21%) patients died within one year after baseline (3 months after starting dialysis therapy). The final prediction model contained seven predictors; age, smoking, history of macrovascular complications, duration of diabetes mellitus, Karnofsky scale, serum albumin and hemoglobin level. Predictive performance was good, as shown by the c-statistic of 0.810. Internal validation showed a slightly lower, but still adequate performance. Sensitivity analyses showed stability of results.<h4>Conclusions</h4>A prediction model containing seven predictors has been identified in order to predict 1-year mortality for diabetic incident dialysis patients. Predictive performance of the model was good. Before implementing the model in clinical practice, for example for counseling patients regarding their prognosis, external validation is necessary.Merel van DiepenMarielle A SchroijenOlaf M DekkersJoris I RotmansRaymond T KredietElisabeth W BoeschotenFriedo W DekkerPublic Library of Science (PLoS)articleMedicineRScienceQENPLoS ONE, Vol 9, Iss 3, p e89744 (2014)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Merel van Diepen Marielle A Schroijen Olaf M Dekkers Joris I Rotmans Raymond T Krediet Elisabeth W Boeschoten Friedo W Dekker Predicting mortality in patients with diabetes starting dialysis.
description	<h4>Background</h4>While some prediction models have been developed for diabetic populations, prediction rules for mortality in diabetic dialysis patients are still lacking. Therefore, the objective of this study was to identify predictors for 1-year mortality in diabetic dialysis patients and use these results to develop a prediction model.<h4>Methods</h4>Data were used from the Netherlands Cooperative Study on the Adequacy of Dialysis (NECOSAD), a multicenter, prospective cohort study in which incident patients with end stage renal disease (ESRD) were monitored until transplantation or death. For the present analysis, patients with DM at baseline were included. A prediction algorithm for 1-year all-cause mortality was developed through multivariate logistic regression. Candidate predictors were selected based on literature and clinical expertise. The final model was constructed through backward selection. The model's predictive performance, measured by calibration and discrimination, was assessed and internally validated through bootstrapping.<h4>Results</h4>A total of 394 patients were available for statistical analysis; 82 (21%) patients died within one year after baseline (3 months after starting dialysis therapy). The final prediction model contained seven predictors; age, smoking, history of macrovascular complications, duration of diabetes mellitus, Karnofsky scale, serum albumin and hemoglobin level. Predictive performance was good, as shown by the c-statistic of 0.810. Internal validation showed a slightly lower, but still adequate performance. Sensitivity analyses showed stability of results.<h4>Conclusions</h4>A prediction model containing seven predictors has been identified in order to predict 1-year mortality for diabetic incident dialysis patients. Predictive performance of the model was good. Before implementing the model in clinical practice, for example for counseling patients regarding their prognosis, external validation is necessary.
format	article
author	Merel van Diepen Marielle A Schroijen Olaf M Dekkers Joris I Rotmans Raymond T Krediet Elisabeth W Boeschoten Friedo W Dekker
author_facet	Merel van Diepen Marielle A Schroijen Olaf M Dekkers Joris I Rotmans Raymond T Krediet Elisabeth W Boeschoten Friedo W Dekker
author_sort	Merel van Diepen
title	Predicting mortality in patients with diabetes starting dialysis.
title_short	Predicting mortality in patients with diabetes starting dialysis.
title_full	Predicting mortality in patients with diabetes starting dialysis.
title_fullStr	Predicting mortality in patients with diabetes starting dialysis.
title_full_unstemmed	Predicting mortality in patients with diabetes starting dialysis.
title_sort	predicting mortality in patients with diabetes starting dialysis.
publisher	Public Library of Science (PLoS)
publishDate	2014
url	https://doaj.org/article/090db3bd45aa49f8bdc39b9710380597
work_keys_str_mv	AT merelvandiepen predictingmortalityinpatientswithdiabetesstartingdialysis AT marielleaschroijen predictingmortalityinpatientswithdiabetesstartingdialysis AT olafmdekkers predictingmortalityinpatientswithdiabetesstartingdialysis AT jorisirotmans predictingmortalityinpatientswithdiabetesstartingdialysis AT raymondtkrediet predictingmortalityinpatientswithdiabetesstartingdialysis AT elisabethwboeschoten predictingmortalityinpatientswithdiabetesstartingdialysis AT friedowdekker predictingmortalityinpatientswithdiabetesstartingdialysis
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Predicting mortality in patients with diabetes starting dialysis.

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