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Potential Drug-Drug Interactions in a Cardiac Center: Development of Simple Software for Pattern Identification

BACKGROUND: Patients with cardiovascular disorders (CVD) are at higher risk for potential drug-drug interactions (pDDIs) due to complex treatment regimens. This study aimed to evaluate pDDI patterns in physicians' prescriptions in a specialized heart center using simple software. METHODS: This...

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Autores principales: Rangraz Jeddi, Fatemeh, Nabovati, Ehsan, Peykani, Fateme, Anvari, Shima, Bagheri Toolaroud, Parissa
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Tehran University of Medical Sciences 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10154111/
https://www.ncbi.nlm.nih.gov/pubmed/37143746
http://dx.doi.org/10.18502/jthc.v17i4.11610
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author Rangraz Jeddi, Fatemeh
Nabovati, Ehsan
Peykani, Fateme
Anvari, Shima
Bagheri Toolaroud, Parissa
author_facet Rangraz Jeddi, Fatemeh
Nabovati, Ehsan
Peykani, Fateme
Anvari, Shima
Bagheri Toolaroud, Parissa
author_sort Rangraz Jeddi, Fatemeh
collection PubMed
description BACKGROUND: Patients with cardiovascular disorders (CVD) are at higher risk for potential drug-drug interactions (pDDIs) due to complex treatment regimens. This study aimed to evaluate pDDI patterns in physicians' prescriptions in a specialized heart center using simple software. METHODS: This cross-sectional study identified severe and related interactions during a 2-stage survey of experts. The data collected included age, sex, the date of admission and discharge, the length of hospital stay, drug names, inpatient wards, and the final diagnosis. The extracted drug interactions were used as a source of software knowledge. The software was designed using the SQL Server and the C # programming language. RESULTS: Of 24 875 patients included in the study, 14 695 (59.1%) were male. The average age was 62 years. Based on the survey of experts, only 57 pairs of severe pDDIs were identified. The designed software evaluated 185 516 prescriptions. The incidence of pDDIs was 10.5%. The average number of prescriptions per patient was 7.5. The highest frequency of pDDIs was detected in patients with lymphatic system disorders (15.0%). Aspirin with heparin (14.3%) and heparin with clopidogrel (11.7%) were the most common documented pDDIs. CONCLUSION: This study reports the prevalence of pDDIs in a cardiac center. Patients with lymphatic system disorders, male patients, and older patients were at higher risk of pDDIs. This study shows that pDDIs are common among CVD patients and highlights the need to use computer software to screen patients' prescriptions to assist in detection and prevention.
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spelling pubmed-101541112023-05-03 Potential Drug-Drug Interactions in a Cardiac Center: Development of Simple Software for Pattern Identification Rangraz Jeddi, Fatemeh Nabovati, Ehsan Peykani, Fateme Anvari, Shima Bagheri Toolaroud, Parissa J Tehran Heart Cent Original Article BACKGROUND: Patients with cardiovascular disorders (CVD) are at higher risk for potential drug-drug interactions (pDDIs) due to complex treatment regimens. This study aimed to evaluate pDDI patterns in physicians' prescriptions in a specialized heart center using simple software. METHODS: This cross-sectional study identified severe and related interactions during a 2-stage survey of experts. The data collected included age, sex, the date of admission and discharge, the length of hospital stay, drug names, inpatient wards, and the final diagnosis. The extracted drug interactions were used as a source of software knowledge. The software was designed using the SQL Server and the C # programming language. RESULTS: Of 24 875 patients included in the study, 14 695 (59.1%) were male. The average age was 62 years. Based on the survey of experts, only 57 pairs of severe pDDIs were identified. The designed software evaluated 185 516 prescriptions. The incidence of pDDIs was 10.5%. The average number of prescriptions per patient was 7.5. The highest frequency of pDDIs was detected in patients with lymphatic system disorders (15.0%). Aspirin with heparin (14.3%) and heparin with clopidogrel (11.7%) were the most common documented pDDIs. CONCLUSION: This study reports the prevalence of pDDIs in a cardiac center. Patients with lymphatic system disorders, male patients, and older patients were at higher risk of pDDIs. This study shows that pDDIs are common among CVD patients and highlights the need to use computer software to screen patients' prescriptions to assist in detection and prevention. Tehran University of Medical Sciences 2022-10 /pmc/articles/PMC10154111/ /pubmed/37143746 http://dx.doi.org/10.18502/jthc.v17i4.11610 Text en Copyright © 2022 Tehran University of Medical Sciences. Published by Tehran University of Medical Sciences. https://creativecommons.org/licenses/by-nc/4.0/This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International license (https://creativecommons.org/licenses/by-nc/4.0/). Non-commercial uses of the work are permitted, provided the original work is properly cited.
spellingShingle Original Article
Rangraz Jeddi, Fatemeh
Nabovati, Ehsan
Peykani, Fateme
Anvari, Shima
Bagheri Toolaroud, Parissa
Potential Drug-Drug Interactions in a Cardiac Center: Development of Simple Software for Pattern Identification
title Potential Drug-Drug Interactions in a Cardiac Center: Development of Simple Software for Pattern Identification
title_full Potential Drug-Drug Interactions in a Cardiac Center: Development of Simple Software for Pattern Identification
title_fullStr Potential Drug-Drug Interactions in a Cardiac Center: Development of Simple Software for Pattern Identification
title_full_unstemmed Potential Drug-Drug Interactions in a Cardiac Center: Development of Simple Software for Pattern Identification
title_short Potential Drug-Drug Interactions in a Cardiac Center: Development of Simple Software for Pattern Identification
title_sort potential drug-drug interactions in a cardiac center: development of simple software for pattern identification
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10154111/
https://www.ncbi.nlm.nih.gov/pubmed/37143746
http://dx.doi.org/10.18502/jthc.v17i4.11610
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