Clinical characteristics and management of patients with secondary hyperparathyroidism undergoing hemodialysis: a feasibility analysis of electronic health records using Natural Language Processing

被引:2
作者
Ortiz, Alberto [1 ]
Portoles, Jose [2 ,3 ,4 ]
Pino-Pino, Maria Dolores [5 ]
Barea, Jesus [6 ]
Lopez, Maria [6 ]
de Sequera, Patricia [7 ]
Quiroga, Borja [8 ]
Echarri, Rocio [9 ]
Prieto Velasco, Mario [10 ]
Diaz, Rafael [11 ]
Gomez Marques, Gonzalo [12 ]
Sanchez Perez, Pilar [13 ]
Torregrosa, Vicens [14 ]
Rodriguez, Mariano [2 ,15 ]
机构
[1] IIS Fdn Jimenez Diaz UAM, Dept Nephrol & Hypertens, Madrid, Spain
[2] RETIC REDINREN, Madrid, Spain
[3] Univ Hosp Puerta Hierro, Dept Nephrol & Transplantat, Madrid, Spain
[4] Big Data Working Grp Spanish Soc Nephrol BIGSEN, Madrid, Spain
[5] Spanish Soc Nephrol, Santander, Spain
[6] Savana, Madrid, Spain
[7] Hosp Univ Infanta Leonor, Dept Nephrol, Madrid, Spain
[8] Hosp Princesa, Dept Nephrol, Madrid, Spain
[9] Hosp Infanta Sofia, Dept Nephrol, Madrid, Spain
[10] CAU Leon, Dept Nephrol, Leon, Spain
[11] Hosp Virgen Salud, Dept Nephrol, Toledo, Spain
[12] Hosp Son Espases, Dept Nephrol, Baleares, Spain
[13] Hosp Univ & P La Fe, Dept Nephrol, Valencia, Spain
[14] Clin Hosp, Dept Nephrol, Barcelona, Spain
[15] Univ Hosp Reina Sofia, Dept Nephrol, Cordoba, Spain
关键词
PARATHYROID-HORMONE; DISEASE PROGRESSION; RISK PREDICTION; MORTALITY RISK; CKD-MBD; ASSOCIATION; COMPLETENESS; CINACALCET; OUTCOMES; PRODUCT;
D O I
10.1159/000528784
中图分类号
R5 [内科学]; R69 [泌尿科学(泌尿生殖系疾病)];
学科分类号
1002 ; 100201 ;
摘要
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 guidelines-recommended analytical goals are achieved in a Spanish cohort of SHPT/CKD-HD patients based on RWD. Methods: Unstructured data in the EHRs from 8 hospitals were retrospectively analyzed using the EHRead (R) technology, based on NLP and machine learning. Variables extracted from EHRs included demographics, CKD-related clinical characteristics, comorbidities, and complications, mineral and bone disorder parameters levels and treatments at baseline, 6 months and 12 months 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 first cause of CKD was diabetic nephropathy. Diagnosis of SHPT was associated with an improvement in median values for parathyroid hormone (PTH), calcium and phosphate. However, the percentage of patients with normal PTH ranges remained stable during the study period (52.8% to 60.4%) while the percentage of patients with within-target range serum calcium or phosphate values showed an increasing trend (43.2% to 60% and 38.8% to 50%). At baseline, 74.1% of patients were using SHPT-related medication, including at least one Vitamin D or analogue (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.
引用
收藏
页码:187 / 196
页数:10
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