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Clinical Characteristics and Management of Patients with Secondary Hyperparathyroidism Undergoing Hemodialysis: A Feasibility Analysis of Electronic Health Records Using Natural Language Processing

INTRODUCTION: This study aimed to assess the feasibility of applying natural language processing (NLP) to analyze real-world data (RWD) and resolve clinical problems in patients with secondary hyperparathyroidism and chronic kidney disease undergoing hemodialysis (SHPT/CKD-HD). The primary objective...

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Autores principales: Ortiz, Alberto, Portoles, Jose, Pino-Pino, Maria Dolores, Barea, Jesús, López, María, de Sequera, Patricia, Quiroga, Borja, Echarri, Rocio, Prieto Velasco, Mario, Díaz, Rafael, Gómez Marqués, Gonzalo, Sanchez Perez, Pilar, Torregrosa, Vicens, Rodriguez, Mariano
Formato: Online Artículo Texto
Lenguaje:English
Publicado: S. Karger AG 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10368074/
https://www.ncbi.nlm.nih.gov/pubmed/37497203
http://dx.doi.org/10.1159/000528784
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author Ortiz, Alberto
Portoles, Jose
Pino-Pino, Maria Dolores
Barea, Jesús
López, María
de Sequera, Patricia
Quiroga, Borja
Echarri, Rocio
Prieto Velasco, Mario
Díaz, Rafael
Gómez Marqués, Gonzalo
Sanchez Perez, Pilar
Torregrosa, Vicens
Rodriguez, Mariano
author_facet Ortiz, Alberto
Portoles, Jose
Pino-Pino, Maria Dolores
Barea, Jesús
López, María
de Sequera, Patricia
Quiroga, Borja
Echarri, Rocio
Prieto Velasco, Mario
Díaz, Rafael
Gómez Marqués, Gonzalo
Sanchez Perez, Pilar
Torregrosa, Vicens
Rodriguez, Mariano
author_sort Ortiz, Alberto
collection PubMed
description INTRODUCTION: This study aimed to assess the feasibility of applying natural language processing (NLP) to analyze real-world data (RWD) and resolve clinical problems in patients with secondary hyperparathyroidism and chronic kidney disease undergoing hemodialysis (SHPT/CKD-HD). The primary objective was to evaluate how well the guideline-recommended analytical goals are achieved in a Spanish cohort of SHPT/CKD-HD patients based on RWD. METHODS: Unstructured data in the electronic health records (EHRs) from 8 hospitals were retrospectively analyzed using the EHRead(®) technology, based on NLP and machine learning. Variables extracted from EHRs included demographics, CKD-related clinical characteristics, comorbidities and complications, mineral and bone disorder parameter levels, and treatments at baseline, 6-month, and 12-month follow-up. RESULTS: A total of 623 prevalent SHPT/CKD-HD patients were identified; of those, 282 fulfilled the inclusion criteria. They were predominantly elderly males with cardiovascular comorbidities, and the first cause of CKD was diabetic nephropathy. Diagnosis of SHPT was associated with an improvement in median values for PTH, calcium, and phosphate. However, the percentage of patients with normal PTH ranges remained stable during the study period (52.8–60.4%), while the percentage of patients with within-target range serum calcium or phosphate values showed an increasing trend (43.2–60% and 38.8–50%). At baseline, 74.1% of patients were using SHPT-related medication, including at least one vitamin D or analog (63.1%), phosphate binders (46.8%), and/or calcimimetics (9.6%). CONCLUSIONS: This study represents the first attempt to use clinical NLP to analyze SHPT/CKD-HD patients based on unstructured clinical data. This methodology is useful to address clinical problems based on RWD and identified a high rate of out-of-range mineral-bone analytical values in patients with HPT/CKD-HD and an increasing trend of out-of-range values for serum calcium and phosphate.
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spelling pubmed-103680742023-07-26 Clinical Characteristics and Management of Patients with Secondary Hyperparathyroidism Undergoing Hemodialysis: A Feasibility Analysis of Electronic Health Records Using Natural Language Processing Ortiz, Alberto Portoles, Jose Pino-Pino, Maria Dolores Barea, Jesús López, María de Sequera, Patricia Quiroga, Borja Echarri, Rocio Prieto Velasco, Mario Díaz, Rafael Gómez Marqués, Gonzalo Sanchez Perez, Pilar Torregrosa, Vicens Rodriguez, Mariano Kidney Dis (Basel) Research Article INTRODUCTION: This study aimed to assess the feasibility of applying natural language processing (NLP) to analyze real-world data (RWD) and resolve clinical problems in patients with secondary hyperparathyroidism and chronic kidney disease undergoing hemodialysis (SHPT/CKD-HD). The primary objective was to evaluate how well the guideline-recommended analytical goals are achieved in a Spanish cohort of SHPT/CKD-HD patients based on RWD. METHODS: Unstructured data in the electronic health records (EHRs) from 8 hospitals were retrospectively analyzed using the EHRead(®) technology, based on NLP and machine learning. Variables extracted from EHRs included demographics, CKD-related clinical characteristics, comorbidities and complications, mineral and bone disorder parameter levels, and treatments at baseline, 6-month, and 12-month follow-up. RESULTS: A total of 623 prevalent SHPT/CKD-HD patients were identified; of those, 282 fulfilled the inclusion criteria. They were predominantly elderly males with cardiovascular comorbidities, and the first cause of CKD was diabetic nephropathy. Diagnosis of SHPT was associated with an improvement in median values for PTH, calcium, and phosphate. However, the percentage of patients with normal PTH ranges remained stable during the study period (52.8–60.4%), while the percentage of patients with within-target range serum calcium or phosphate values showed an increasing trend (43.2–60% and 38.8–50%). At baseline, 74.1% of patients were using SHPT-related medication, including at least one vitamin D or analog (63.1%), phosphate binders (46.8%), and/or calcimimetics (9.6%). CONCLUSIONS: This study represents the first attempt to use clinical NLP to analyze SHPT/CKD-HD patients based on unstructured clinical data. This methodology is useful to address clinical problems based on RWD and identified a high rate of out-of-range mineral-bone analytical values in patients with HPT/CKD-HD and an increasing trend of out-of-range values for serum calcium and phosphate. S. Karger AG 2023-01-23 /pmc/articles/PMC10368074/ /pubmed/37497203 http://dx.doi.org/10.1159/000528784 Text en © 2023 The Author(s). Published by S. Karger AG, Basel https://creativecommons.org/licenses/by-nc/4.0/This article is licensed under the Creative Commons Attribution-NonCommercial 4.0 International License (CC BY-NC) (http://www.karger.com/Services/OpenAccessLicense). Usage and distribution for commercial purposes requires written permission.
spellingShingle Research Article
Ortiz, Alberto
Portoles, Jose
Pino-Pino, Maria Dolores
Barea, Jesús
López, María
de Sequera, Patricia
Quiroga, Borja
Echarri, Rocio
Prieto Velasco, Mario
Díaz, Rafael
Gómez Marqués, Gonzalo
Sanchez Perez, Pilar
Torregrosa, Vicens
Rodriguez, Mariano
Clinical Characteristics and Management of Patients with Secondary Hyperparathyroidism Undergoing Hemodialysis: A Feasibility Analysis of Electronic Health Records Using Natural Language Processing
title Clinical Characteristics and Management of Patients with Secondary Hyperparathyroidism Undergoing Hemodialysis: A Feasibility Analysis of Electronic Health Records Using Natural Language Processing
title_full Clinical Characteristics and Management of Patients with Secondary Hyperparathyroidism Undergoing Hemodialysis: A Feasibility Analysis of Electronic Health Records Using Natural Language Processing
title_fullStr Clinical Characteristics and Management of Patients with Secondary Hyperparathyroidism Undergoing Hemodialysis: A Feasibility Analysis of Electronic Health Records Using Natural Language Processing
title_full_unstemmed Clinical Characteristics and Management of Patients with Secondary Hyperparathyroidism Undergoing Hemodialysis: A Feasibility Analysis of Electronic Health Records Using Natural Language Processing
title_short Clinical Characteristics and Management of Patients with Secondary Hyperparathyroidism Undergoing Hemodialysis: A Feasibility Analysis of Electronic Health Records Using Natural Language Processing
title_sort clinical characteristics and management of patients with secondary hyperparathyroidism undergoing hemodialysis: a feasibility analysis of electronic health records using natural language processing
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10368074/
https://www.ncbi.nlm.nih.gov/pubmed/37497203
http://dx.doi.org/10.1159/000528784
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