Cargando…

Sarcopenia, frailty and cachexia patients detected in a multisystem electronic health record database

BACKGROUND: Sarcopenia, cachexia and frailty have overlapping features and clinical consequences, but often go unrecognized. The objective was to detect patients described by clinicians as having sarcopenia, cachexia or frailty within electronic health records (EHR) and compare clinical variables be...

Descripción completa

Detalles Bibliográficos
Autores principales: Moorthi, Ranjani N., Liu, Ziyue, El-Azab, Sarah A., Lembcke, Lauren R., Miller, Matthew R., Broyles, Andrea A., Imel, Erik A.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7395344/
https://www.ncbi.nlm.nih.gov/pubmed/32736613
http://dx.doi.org/10.1186/s12891-020-03522-9
_version_ 1783565388106170368
author Moorthi, Ranjani N.
Liu, Ziyue
El-Azab, Sarah A.
Lembcke, Lauren R.
Miller, Matthew R.
Broyles, Andrea A.
Imel, Erik A.
author_facet Moorthi, Ranjani N.
Liu, Ziyue
El-Azab, Sarah A.
Lembcke, Lauren R.
Miller, Matthew R.
Broyles, Andrea A.
Imel, Erik A.
author_sort Moorthi, Ranjani N.
collection PubMed
description BACKGROUND: Sarcopenia, cachexia and frailty have overlapping features and clinical consequences, but often go unrecognized. The objective was to detect patients described by clinicians as having sarcopenia, cachexia or frailty within electronic health records (EHR) and compare clinical variables between cases and matched controls. METHODS: We conducted a case-control study using retrospective data from the Indiana Network for Patient Care multi-health system database from 2016 to 2017. The computable phenotype combined ICD codes for sarcopenia, cachexia and frailty, with clinical note text terms for sarcopenia, cachexia and frailty detected using natural language processing. Cases with these codes or text terms were matched to controls without these codes or text terms matched on birth year, sex and race. Two physicians reviewed EHR for all cases and a subset of controls. Comorbidity codes, laboratory values, and other coded clinical variables were compared between groups using Wilcoxon matched-pair sign-rank test for continuous variables and conditional logistic regression for binary variables. RESULTS: Cohorts of 9594 cases and 9594 matched controls were generated. Cases were 59% female, 69% white, and a median (1st, 3rd quartiles) age 74.9 (62.2, 84.8) years. Most cases were detected by text terms without ICD codes n = 8285 (86.4%). All cases detected by ICD codes (total n = 1309) also had supportive text terms. Overall 1496 (15.6%) had concurrent terms or codes for two or more of the three conditions (sarcopenia, cachexia or frailty). Of text term occurrence, 97% were used positively for sarcopenia, 90% for cachexia, and 95% for frailty. The remaining occurrences were negative uses of the terms or applied to someone other than the patient. Cases had lower body mass index, albumin and prealbumin, and significantly higher odds ratios for diabetes, hypertension, cardiovascular and peripheral vascular diseases, chronic kidney disease, liver disease, malignancy, osteoporosis and fractures (all p < 0.05). Cases were more likely to be prescribed appetite stimulants and caloric supplements. CONCLUSIONS: Patients detected with a computable phenotype for sarcopenia, cachexia and frailty differed from controls in several important clinical variables. Potential uses include detection among clinical cohorts for targeting recruitment for research and interventions.
format Online
Article
Text
id pubmed-7395344
institution National Center for Biotechnology Information
language English
publishDate 2020
publisher BioMed Central
record_format MEDLINE/PubMed
spelling pubmed-73953442020-08-05 Sarcopenia, frailty and cachexia patients detected in a multisystem electronic health record database Moorthi, Ranjani N. Liu, Ziyue El-Azab, Sarah A. Lembcke, Lauren R. Miller, Matthew R. Broyles, Andrea A. Imel, Erik A. BMC Musculoskelet Disord Research Article BACKGROUND: Sarcopenia, cachexia and frailty have overlapping features and clinical consequences, but often go unrecognized. The objective was to detect patients described by clinicians as having sarcopenia, cachexia or frailty within electronic health records (EHR) and compare clinical variables between cases and matched controls. METHODS: We conducted a case-control study using retrospective data from the Indiana Network for Patient Care multi-health system database from 2016 to 2017. The computable phenotype combined ICD codes for sarcopenia, cachexia and frailty, with clinical note text terms for sarcopenia, cachexia and frailty detected using natural language processing. Cases with these codes or text terms were matched to controls without these codes or text terms matched on birth year, sex and race. Two physicians reviewed EHR for all cases and a subset of controls. Comorbidity codes, laboratory values, and other coded clinical variables were compared between groups using Wilcoxon matched-pair sign-rank test for continuous variables and conditional logistic regression for binary variables. RESULTS: Cohorts of 9594 cases and 9594 matched controls were generated. Cases were 59% female, 69% white, and a median (1st, 3rd quartiles) age 74.9 (62.2, 84.8) years. Most cases were detected by text terms without ICD codes n = 8285 (86.4%). All cases detected by ICD codes (total n = 1309) also had supportive text terms. Overall 1496 (15.6%) had concurrent terms or codes for two or more of the three conditions (sarcopenia, cachexia or frailty). Of text term occurrence, 97% were used positively for sarcopenia, 90% for cachexia, and 95% for frailty. The remaining occurrences were negative uses of the terms or applied to someone other than the patient. Cases had lower body mass index, albumin and prealbumin, and significantly higher odds ratios for diabetes, hypertension, cardiovascular and peripheral vascular diseases, chronic kidney disease, liver disease, malignancy, osteoporosis and fractures (all p < 0.05). Cases were more likely to be prescribed appetite stimulants and caloric supplements. CONCLUSIONS: Patients detected with a computable phenotype for sarcopenia, cachexia and frailty differed from controls in several important clinical variables. Potential uses include detection among clinical cohorts for targeting recruitment for research and interventions. BioMed Central 2020-07-31 /pmc/articles/PMC7395344/ /pubmed/32736613 http://dx.doi.org/10.1186/s12891-020-03522-9 Text en © The Author(s) 2020 Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research Article
Moorthi, Ranjani N.
Liu, Ziyue
El-Azab, Sarah A.
Lembcke, Lauren R.
Miller, Matthew R.
Broyles, Andrea A.
Imel, Erik A.
Sarcopenia, frailty and cachexia patients detected in a multisystem electronic health record database
title Sarcopenia, frailty and cachexia patients detected in a multisystem electronic health record database
title_full Sarcopenia, frailty and cachexia patients detected in a multisystem electronic health record database
title_fullStr Sarcopenia, frailty and cachexia patients detected in a multisystem electronic health record database
title_full_unstemmed Sarcopenia, frailty and cachexia patients detected in a multisystem electronic health record database
title_short Sarcopenia, frailty and cachexia patients detected in a multisystem electronic health record database
title_sort sarcopenia, frailty and cachexia patients detected in a multisystem electronic health record database
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7395344/
https://www.ncbi.nlm.nih.gov/pubmed/32736613
http://dx.doi.org/10.1186/s12891-020-03522-9
work_keys_str_mv AT moorthiranjanin sarcopeniafrailtyandcachexiapatientsdetectedinamultisystemelectronichealthrecorddatabase
AT liuziyue sarcopeniafrailtyandcachexiapatientsdetectedinamultisystemelectronichealthrecorddatabase
AT elazabsaraha sarcopeniafrailtyandcachexiapatientsdetectedinamultisystemelectronichealthrecorddatabase
AT lembckelaurenr sarcopeniafrailtyandcachexiapatientsdetectedinamultisystemelectronichealthrecorddatabase
AT millermatthewr sarcopeniafrailtyandcachexiapatientsdetectedinamultisystemelectronichealthrecorddatabase
AT broylesandreaa sarcopeniafrailtyandcachexiapatientsdetectedinamultisystemelectronichealthrecorddatabase
AT imelerika sarcopeniafrailtyandcachexiapatientsdetectedinamultisystemelectronichealthrecorddatabase