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Familial Hypercholesterolemia Identification Algorithm in Patients with Acute Cardiovascular Events in A Large Hospital Electronic Database in Bulgaria: A Call for Implementation

BACKGROUND: Familial hypercholesterolemia (FH) is a genetic disorder characterized by a high level of low-density lipoprotein cholesterol (LDL-C) and is an important cause for premature cardiovascular disease. Because of underdiagnoses, an acute event is often the first clinical manifestation of FH....

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Autores principales: Petrov, Ivo, Postadzhiyan, Arman, Vasilev, Dobrin, Kasabov, Ruslan, Tokmakova, Mariya, Nikolov, Fedya, Istatkov, Veselin, Zhao, Boyang, Mutafchiev, Dimiter, Petkova, Reneta
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Healthcare 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8107160/
https://www.ncbi.nlm.nih.gov/pubmed/33754300
http://dx.doi.org/10.1007/s12325-020-01608-3
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author Petrov, Ivo
Postadzhiyan, Arman
Vasilev, Dobrin
Kasabov, Ruslan
Tokmakova, Mariya
Nikolov, Fedya
Istatkov, Veselin
Zhao, Boyang
Mutafchiev, Dimiter
Petkova, Reneta
author_facet Petrov, Ivo
Postadzhiyan, Arman
Vasilev, Dobrin
Kasabov, Ruslan
Tokmakova, Mariya
Nikolov, Fedya
Istatkov, Veselin
Zhao, Boyang
Mutafchiev, Dimiter
Petkova, Reneta
author_sort Petrov, Ivo
collection PubMed
description BACKGROUND: Familial hypercholesterolemia (FH) is a genetic disorder characterized by a high level of low-density lipoprotein cholesterol (LDL-C) and is an important cause for premature cardiovascular disease. Because of underdiagnoses, an acute event is often the first clinical manifestation of FH. There are limited data on the prevalence and treatment of FH among adults admitted for treatment of acute cardiovascular events in Bulgaria. Our objective was to assess the proportion and management of FH patients from those admitted to hospital for treatment of acute symptomatic acute atherosclerotic cardiovascular events (ASCVD), the achievement of LDL-C targets of European Society of Cardiology/European Atherosclerosis Society guidelines and related public healthcare resources. OBJECTIVE: Digitalized healthcare records for patients admitted for treatment of symptomatic ASCVD acute events between August 2018 and August 2019 were used for the analysis. Five cardiology hospitals provided data for hospitalizations, laboratory tests, and ambulatory follow-ups up to February 2020. Patients’ hospital and ambulatory records were linked, and medical histories were extracted via a specifically developed algorithm, and analyzed. Outcomes included the proportion of patients classified as FH as defined by the Dutch Lipid Network Criteria (DLNC), use of lipid-lowering therapy, LDL-C achieved by 1, 3, 6, and 12 months post-index event, and public resources spent on hospital and ambulatory treatment. RESULTS: We reviewed 11,090 hospital records of patients admitted for treatment of acute events in the period August 2018–August 2019 with ICD codes for ASCVD (Supplementary Table S3). FH was identified in 731 (6.6%) patients, with DLNC score ≥ 3, (682 with coronary artery disease, 32 with cerebrovascular disease, and 17 with peripheral artery disease). We did not find the criteria for FH in 5797 patients. The remaining 4562 records were inconclusive due to lack of data in the hospital dossier. Less than half of FH patients (274/731, 37%) were discharged on high-intensity statin therapy prescribed (34/731, 5%) with combination therapy. The vast majority (96.2% with LDL-C ≥ 1.8 mmol/l) had poorly controlled LDL-C during the first year after discharge. Patients with a probable/definite DLNC score ≥ 6 points and those with recurrent events contributed to the higher cost paid both by the healthcare system and the patients themselves. CONCLUSION: These findings reinforce the need for more aggressive lipid-lowering therapy, and underline the efficiency of using an electronic medical records search tool to support physicians in improving early FH diagnosis, aiming to minimize residual and future ASCVD events among FH patients and their family members. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s12325-020-01608-3.
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spelling pubmed-81071602021-05-24 Familial Hypercholesterolemia Identification Algorithm in Patients with Acute Cardiovascular Events in A Large Hospital Electronic Database in Bulgaria: A Call for Implementation Petrov, Ivo Postadzhiyan, Arman Vasilev, Dobrin Kasabov, Ruslan Tokmakova, Mariya Nikolov, Fedya Istatkov, Veselin Zhao, Boyang Mutafchiev, Dimiter Petkova, Reneta Adv Ther Original Research BACKGROUND: Familial hypercholesterolemia (FH) is a genetic disorder characterized by a high level of low-density lipoprotein cholesterol (LDL-C) and is an important cause for premature cardiovascular disease. Because of underdiagnoses, an acute event is often the first clinical manifestation of FH. There are limited data on the prevalence and treatment of FH among adults admitted for treatment of acute cardiovascular events in Bulgaria. Our objective was to assess the proportion and management of FH patients from those admitted to hospital for treatment of acute symptomatic acute atherosclerotic cardiovascular events (ASCVD), the achievement of LDL-C targets of European Society of Cardiology/European Atherosclerosis Society guidelines and related public healthcare resources. OBJECTIVE: Digitalized healthcare records for patients admitted for treatment of symptomatic ASCVD acute events between August 2018 and August 2019 were used for the analysis. Five cardiology hospitals provided data for hospitalizations, laboratory tests, and ambulatory follow-ups up to February 2020. Patients’ hospital and ambulatory records were linked, and medical histories were extracted via a specifically developed algorithm, and analyzed. Outcomes included the proportion of patients classified as FH as defined by the Dutch Lipid Network Criteria (DLNC), use of lipid-lowering therapy, LDL-C achieved by 1, 3, 6, and 12 months post-index event, and public resources spent on hospital and ambulatory treatment. RESULTS: We reviewed 11,090 hospital records of patients admitted for treatment of acute events in the period August 2018–August 2019 with ICD codes for ASCVD (Supplementary Table S3). FH was identified in 731 (6.6%) patients, with DLNC score ≥ 3, (682 with coronary artery disease, 32 with cerebrovascular disease, and 17 with peripheral artery disease). We did not find the criteria for FH in 5797 patients. The remaining 4562 records were inconclusive due to lack of data in the hospital dossier. Less than half of FH patients (274/731, 37%) were discharged on high-intensity statin therapy prescribed (34/731, 5%) with combination therapy. The vast majority (96.2% with LDL-C ≥ 1.8 mmol/l) had poorly controlled LDL-C during the first year after discharge. Patients with a probable/definite DLNC score ≥ 6 points and those with recurrent events contributed to the higher cost paid both by the healthcare system and the patients themselves. CONCLUSION: These findings reinforce the need for more aggressive lipid-lowering therapy, and underline the efficiency of using an electronic medical records search tool to support physicians in improving early FH diagnosis, aiming to minimize residual and future ASCVD events among FH patients and their family members. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s12325-020-01608-3. Springer Healthcare 2021-03-23 2021 /pmc/articles/PMC8107160/ /pubmed/33754300 http://dx.doi.org/10.1007/s12325-020-01608-3 Text en © The Author(s) 2021 https://creativecommons.org/licenses/by-nc/4.0/Open AccessThis article is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License, which permits any non-commercial 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-nc/4.0/ (https://creativecommons.org/licenses/by-nc/4.0/) .
spellingShingle Original Research
Petrov, Ivo
Postadzhiyan, Arman
Vasilev, Dobrin
Kasabov, Ruslan
Tokmakova, Mariya
Nikolov, Fedya
Istatkov, Veselin
Zhao, Boyang
Mutafchiev, Dimiter
Petkova, Reneta
Familial Hypercholesterolemia Identification Algorithm in Patients with Acute Cardiovascular Events in A Large Hospital Electronic Database in Bulgaria: A Call for Implementation
title Familial Hypercholesterolemia Identification Algorithm in Patients with Acute Cardiovascular Events in A Large Hospital Electronic Database in Bulgaria: A Call for Implementation
title_full Familial Hypercholesterolemia Identification Algorithm in Patients with Acute Cardiovascular Events in A Large Hospital Electronic Database in Bulgaria: A Call for Implementation
title_fullStr Familial Hypercholesterolemia Identification Algorithm in Patients with Acute Cardiovascular Events in A Large Hospital Electronic Database in Bulgaria: A Call for Implementation
title_full_unstemmed Familial Hypercholesterolemia Identification Algorithm in Patients with Acute Cardiovascular Events in A Large Hospital Electronic Database in Bulgaria: A Call for Implementation
title_short Familial Hypercholesterolemia Identification Algorithm in Patients with Acute Cardiovascular Events in A Large Hospital Electronic Database in Bulgaria: A Call for Implementation
title_sort familial hypercholesterolemia identification algorithm in patients with acute cardiovascular events in a large hospital electronic database in bulgaria: a call for implementation
topic Original Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8107160/
https://www.ncbi.nlm.nih.gov/pubmed/33754300
http://dx.doi.org/10.1007/s12325-020-01608-3
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