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Multivariable prognostic model for dialysis patients with end stage renal disease: An observational cohort study of Pakistan by external validation

OBJECTIVES: To develop an externally validated multivariable prognostic model for an underprivileged dialysis population. METHODS: This was a multicenter retrospective cohort study of 5 years duration from January 2013 to December 2017. A total of 758 patients (37.5% female; mean±SD age, 44.26±14.77...

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Autores principales: Siddiqa, Maryam, Kimber, Alan Charles, Shabbir, Javid
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Saudi Medical Journal 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9195532/
https://www.ncbi.nlm.nih.gov/pubmed/34187914
http://dx.doi.org/10.15537/smj.2021.42.7.20210082
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author Siddiqa, Maryam
Kimber, Alan Charles
Shabbir, Javid
author_facet Siddiqa, Maryam
Kimber, Alan Charles
Shabbir, Javid
author_sort Siddiqa, Maryam
collection PubMed
description OBJECTIVES: To develop an externally validated multivariable prognostic model for an underprivileged dialysis population. METHODS: This was a multicenter retrospective cohort study of 5 years duration from January 2013 to December 2017. A total of 758 patients (37.5% female; mean±SD age, 44.26±14.77 years) were enrolled for construction of the prognostic model. The data were analyzed using a proportional hazards model to identify predictors of survival. Three risk groups were identified at the 25th and 75th percentiles of the resultant prognostic index. The model was externally validated with another dataset of 622 dialysis patients. RESULTS: The prognostic index included 5 predictor variables: hemoglobin, serum potassium, interdialytic weight gain, serum albumin, and duration of dialysis, which had good predictive performance on the calibration and discrimination aspects of the model (Harrell’s c statistic: 0.748, Gonen and Heller k statistic: 0.647, Somers’ D statistic: 0.496, calibration slope: 1.156). There were significant interaction effects between weight and hemoglobin, weight and albumin, albumin and potassium, and albumin and hemoglobin. CONCLUSIONS: We developed an externally validated model that contained 5 routinely collected prognosticators and confirmed its calibration and discrimination abilities in obtaining reliable prognostic estimates in developing countries. The model will assist clinicians in deciding the prognosis of dialysis patients. The application of this model in different clinical settings of developing countries can indicate interesting findings regarding public health.
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spelling pubmed-91955322022-06-21 Multivariable prognostic model for dialysis patients with end stage renal disease: An observational cohort study of Pakistan by external validation Siddiqa, Maryam Kimber, Alan Charles Shabbir, Javid Saudi Med J Original Article OBJECTIVES: To develop an externally validated multivariable prognostic model for an underprivileged dialysis population. METHODS: This was a multicenter retrospective cohort study of 5 years duration from January 2013 to December 2017. A total of 758 patients (37.5% female; mean±SD age, 44.26±14.77 years) were enrolled for construction of the prognostic model. The data were analyzed using a proportional hazards model to identify predictors of survival. Three risk groups were identified at the 25th and 75th percentiles of the resultant prognostic index. The model was externally validated with another dataset of 622 dialysis patients. RESULTS: The prognostic index included 5 predictor variables: hemoglobin, serum potassium, interdialytic weight gain, serum albumin, and duration of dialysis, which had good predictive performance on the calibration and discrimination aspects of the model (Harrell’s c statistic: 0.748, Gonen and Heller k statistic: 0.647, Somers’ D statistic: 0.496, calibration slope: 1.156). There were significant interaction effects between weight and hemoglobin, weight and albumin, albumin and potassium, and albumin and hemoglobin. CONCLUSIONS: We developed an externally validated model that contained 5 routinely collected prognosticators and confirmed its calibration and discrimination abilities in obtaining reliable prognostic estimates in developing countries. The model will assist clinicians in deciding the prognosis of dialysis patients. The application of this model in different clinical settings of developing countries can indicate interesting findings regarding public health. Saudi Medical Journal 2021-07 /pmc/articles/PMC9195532/ /pubmed/34187914 http://dx.doi.org/10.15537/smj.2021.42.7.20210082 Text en Copyright: © Saudi Medical Journal https://creativecommons.org/licenses/by-nc/4.0/This is an Open Access journal and articles published are distributed under the terms of the Creative Commons Attribution-NonCommercial License (CC BY-NC). Readers may copy, distribute, and display the work for non-commercial purposes with the proper citation of the original work.
spellingShingle Original Article
Siddiqa, Maryam
Kimber, Alan Charles
Shabbir, Javid
Multivariable prognostic model for dialysis patients with end stage renal disease: An observational cohort study of Pakistan by external validation
title Multivariable prognostic model for dialysis patients with end stage renal disease: An observational cohort study of Pakistan by external validation
title_full Multivariable prognostic model for dialysis patients with end stage renal disease: An observational cohort study of Pakistan by external validation
title_fullStr Multivariable prognostic model for dialysis patients with end stage renal disease: An observational cohort study of Pakistan by external validation
title_full_unstemmed Multivariable prognostic model for dialysis patients with end stage renal disease: An observational cohort study of Pakistan by external validation
title_short Multivariable prognostic model for dialysis patients with end stage renal disease: An observational cohort study of Pakistan by external validation
title_sort multivariable prognostic model for dialysis patients with end stage renal disease: an observational cohort study of pakistan by external validation
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9195532/
https://www.ncbi.nlm.nih.gov/pubmed/34187914
http://dx.doi.org/10.15537/smj.2021.42.7.20210082
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