The journal of Tehran Heart Center · 2022
Potential Drug-Drug Interactions in a Cardiac Center: Development of Simple Software for Pattern Identification.
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Rangraz Jeddi Fatemeh, Nabovati Ehsan, Peykani Fateme, Anvari Shima, Bagheri Toolaroud Parissa
Аннотация
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.
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.