scholarly journals Comparing Potential Drug-Drug Interactions in Veterinary Medications Using Two Electronic Databases

2020 ◽  
Author(s):  
Anusak Kijtawornrat ◽  
Tussapon Boonyarattanasoonthorn ◽  
Phisit Khemawoot
Keyword(s):  
Health Care ◽  
Veterinary Medicine ◽  
Global Health ◽  
Drug Interactions ◽  
Drug Prescription ◽  
Lower Sensitivity ◽  
Potential Drug ◽  
Health Issues ◽  
Potential Ddis ◽  
Veterinary Medicines

Abstract Background: One of the most common global health issues in humans and animals is drug-drug interactions (DDIs). This issue increases the risks of health care in both human and veterinary medicine, as animals live long lives and receive many medicines to treat their illnesses. Currently, many electronic databases are using as a tool for potential DDI prediction, e.g., Micromedex and Drugs.com. The purpose of this study was to compare the ability of Micromedex and Drugs.com to detect potential DDIs in veterinary medicines.Results: There were 140 drugs, mainly used for the treatment of disease in animal hospitals, but the Micromedex and Drugs.com databases unidentified 44 items, therefore only 96 items were used in this study. The analysis detected 1,132 potential DDI pairs from the two databases. Micromedex identified 429 pairs of potential DDIs, while Drugs.com identified 842 pairs of potential DDIs. The same severity of the potential DDIs occurred between the two databases for 139 pairs (12.28%) and a different severity was found for 993 pairs (87.72%).Conclusion: Although Micromedex had a lower sensitivity to find out potential DDIs than Drugs.com, Micromedex provided more informative documentation. Veterinary pharmacists should evaluate potential DDIs from different databases and communicate with both the veterinarian and animal owners to ensure an appropriate drug prescription.

scholarly journals Comparing potential drug-drug interactions in veterinary medications using two electronic databases

2020 ◽  
Author(s):  
Tussapon Boonyarattanasoonthorn ◽  
Phisit Khemawoot ◽  
Anusak Kijtawornrat
Keyword(s):  
Drug Interactions ◽  
Drug Prescription ◽  
Lower Sensitivity ◽  
Health Issues ◽  
Potential Ddis ◽  
Interval Prolongation ◽  
Veterinary Medicines ◽  
Qt Interval Prolongation ◽  
Drug List ◽  
Cytochrome P450 Induction

Abstract Background: One of the most common global health issues in humans and animals is drug-drug interactions (DDIs). This issue increases the risks associated with healthcare in both human and veterinary medicine, as animals live long lives and receive many medicines to treat their illnesses. Currently, many electronic databases are being used as tools for potential DDI prediction, for example, Micromedex and Drugs.com. The purpose of this study was to examine the different abilities for the identification of potential DDIs in veterinary medicines by Micromedex and Drugs.com. Results: A list of 140 drugs, mainly used for the treatment of disease in animal hospitals, was complied, but the Micromedex and Drugs.com databases could recognise only 96 of these drugs. After inputting the recognised drug list into the databases, Micromedex showed 429 pairs of potential DDIs, whilst Drugs.com showed 842 pairs of potential DDIs. The analysis comparing results between the two databases showed 139 pairs (12.28%) with the same severity and 993 pairs (87.72%) with different severities. Major mechanisms of contraindicated and major potential DDIs were cytochrome P450 induction-inhibition and QT interval prolongation.Conclusion: Although Micromedex had a lower sensitivity to identify potential DDIs than Drugs.com, Micromedex provided more informative documentation. Veterinary pharmacists should evaluate potential DDIs from several databases and communicate with both the veterinarian and animal owner to ensure an appropriate drug prescription.

scholarly journals Potential Drug-Drug Interactions in Primary Health Care in Southern Brazil.

2015 ◽  
Vol 44 (suppl_1) ◽  
pp. i109-i109
Author(s):  
E. T. Santa-Helena ◽  
B. F. Fiamoncini ◽  
S. J. Maldonado ◽  
G. A. Siementcoski
Keyword(s):  
Health Care ◽  
Primary Health Care ◽  
Drug Interactions ◽  
Potential Drug ◽  
Southern Brazil ◽  
Primary Health

scholarly journals ASSESSMENT OF POTENTIAL DRUG INTERACTIONS AMONG HOSPITALIZED PATIENTS IN NEUROLOGY DEPARTMENT IN TERTIARY CARE HOSPITALS

2019 ◽  
pp. 173-176
Author(s):  
DIJO DAIS ◽  
RANJEET AVIS CHERUVATHOOR ◽  
KAMESWARAN R ◽  
SHANMUGA SUNDARAM RAJAGOPAL
Keyword(s):  
Risk Factors ◽  
Drug Interactions ◽  
Tertiary Care ◽  
Length Of Hospital Stay ◽  
Daily Basis ◽  
Potential Drug ◽  
Potential Ddis ◽  
Patient History ◽  
Therapeutic Advantage ◽  
Tertiary Care Hospitals

Objective: This research was instigated to determine and assess the prevalence, severity, type, and the total number of potential drug interactions in the neurology department of two hospitals in India. Methods: The data were collected from the prescriptions and by patient history interview on a daily basis. The drug-drug interactions (DDIs) were identified using Micromedex® database-2.7 and drugs.com. Results: The drug interactions were influenced by a plethora of risk factors: Gender, age, comorbidities, length of hospital stay, and the neurological condition. The study was comprised 320 patients, among 196 patients were identified with potential DDIs (PDDIs), and a total of 450 PDDIs were observed. The prevalence of PDDIs according to the severity was major (42.6%), moderate (45.11%), and minor (12.22%). Conclusion: To lessen PDDIs, the range of medications for the patients must be properly managed, and it is encouraged to remove all medicines without therapeutic advantage, intention, and an indication.

Factors Associated with Potential Drug–Drug Interactions in Patients Attended in Primary Health Care: A Focus on Mental Health

2017 ◽  
Vol 38 (9) ◽  
pp. 769-774 ◽  
Author(s):  
Tatiana Longo Borges ◽  
Kelly Graziani Giacchero Vedana ◽  
Ellen Carolina Dias Castilho ◽  
Adriana Inocenti Miasso
Keyword(s):  
Mental Health ◽  
Health Care ◽  
Primary Health Care ◽  
Drug Interactions ◽  
Potential Drug ◽  
Factors Associated ◽  
Primary Health

scholarly journals Potential drug–drug interactions among prescriptionsfor elderly patients in primary health care

2017 ◽  
Vol 47 ◽  
pp. 47-54 ◽  
Author(s):  
Zafer GÖREN ◽  
Mahluga J. DEMİRKAPU ◽  
Gökçe AKPINAR ACET ◽  
Sanda ÇALI ◽  
Medine GÜLÇEBİ İDRİZ OĞLU
Keyword(s):  
Health Care ◽  
Primary Health Care ◽  
Elderly Patients ◽  
Drug Interactions ◽  
Potential Drug ◽  
Primary Health

scholarly journals Comedications and potential drug-drug interactions with direct-acting antivirals in hepatitis C patients on hemodialysis

2021 ◽  
Vol 27 (1) ◽  
pp. 186-196
Author(s):  
Po-Yao Hsu ◽  
Yu-Ju Wei ◽  
Jia-Jung Lee ◽  
Sheng-Wen Niu ◽  
Jiun-Chi Huang ◽  
...  
Keyword(s):  
Hepatitis C ◽  
Drug Interactions ◽  
Median Number ◽  
Lipid Lowering ◽  
Hcv Rna ◽  
Close Monitoring ◽  
Potential Drug ◽  
Direct Acting Antivirals ◽  
Potential Ddis ◽  
Direct Acting

Background/Aims: Direct‐acting antivirals (DAAs) have been approved for hepatitis C virus (HCV) treatment in patients with end-stage renal disease (ESRD) on hemodialysis. Nevertheless, the complicated comedications and their potential drug-drug interactions (DDIs) with DAAs might limit clinical practice in this special population.Methods: The number, class, and characteristics of comedications and their potential DDIs with five DAA regimens were analyzed among HCV-viremic patients from 23 hemodialysis centers in Taiwan.Results: Of 2,015 hemodialysis patients screened in 2019, 169 patients seropositive for HCV RNA were enrolled (mean age, 65.6 years; median duration of hemodialysis, 5.8 years). All patients received at least one comedication (median number, 6; mean class number, 3.4). The most common comedication classes were ESRD-associated medications (94.1%), cardiovascular drugs (69.8%) and antidiabetic drugs (43.2%). ESRD-associated medications were excluded from DDI analysis. Sofosbuvir/velpatasvir/voxilaprevir had the highest frequency of potential contraindicated DDIs (red, 5.6%), followed by glecaprevir/pibrentasvir (4.0%), sofosbuvir/ledipasvir (1.3%), sofosbuvir/velpatasvir (1.3%), and elbasvir/grazoprevir (0.3%). For potentially significant DDIs (orange, requiring close monitoring or dose adjustments), sofosbuvir/velpatasvir/voxilaprevir had the highest frequency (19.9%), followed by sofosbuvir/ledipasvir (18.2%), glecaprevir/pibrentasvir (12.6%), sofosbuvir/velpatasvir (12.6%), and elbasvir/grazoprevir (7.3%). Overall, lipid-lowering agents were the most common comedication class with red-category DDIs to all DAA regimens (n=62), followed by cardiovascular agents (n=15), and central nervous system agents (n=10).Conclusions: HCV-viremic patients on hemodialysis had a very high prevalence of comedications with a broad spectrum, which had varied DDIs with currently available DAA regimens. Elbasvir/grazoprevir had the fewest potential DDIs, and sofosbuvir/velpatasvir/voxilaprevir had the most potential DDIs.

scholarly journals Potential drug-drug interactions of antiretrovirals and antimicrobials detected by three databases

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Pornpun Vivithanaporn ◽  
Teetat Kongratanapasert ◽  
Bovornpat Suriyapakorn ◽  
Pichayut Songkunlertchai ◽  
Patpicha Mongkonariyawong ◽  
...  
Keyword(s):  
Hiv Infection ◽  
Drug Interactions ◽  
Standard Treatment ◽  
Opportunistic Infections ◽  
Essential Medicines ◽  
Potential Drug ◽  
Potential Ddis

AbstractStandard treatment for HIV infection involves a combination of antiretrovirals. Additionally, opportunistic infections in HIV infected patients require further antimicrobial medications that might cause drug-drug interactions (DDIs). The objective of this study was to to compare the recognition of DDIs between antiretrovirals and antimicrobials by three proprietary databases and evaluate their concordance. 114 items of antiretrovirals and antimicrobials from the National List of Essential Medicines of Thailand 2018 were used in the study. However, 21 items were not recognised by Micromedex, Drugs.com, and Liverpool HIV interactions. Only 93 items were available for the detection of potential DDIs by the three databases. Potential DDIs detected from the three databases included 292 pairs. Liverpool showed the highest number of DDIs with 285 pairs compared with 259 pairs by drugs.com and 133 pairs by Micromedex. Regarding the severity classifications, Liverpool reported 10% Contraindicated; Micromedex reported 14% contraindicated and 59% major; Drugs.com reported 21% major. The Fleiss’ kappa agreements were fair to poor among the three databases, higher agreement was observed for DDIs classified as severe. This study highlights the need to harmonize the evaluation and interpretation of DDI risk in order to produce standardized information to support prescribers.

scholarly journals The effect of different intensivist staffing patterns on the rate of potential drug–drug interactions in adult trauma intensive care units

2020 ◽  
Vol 11 ◽  
pp. 204209862098064
Author(s):  
Mansoor Masjedi ◽  
Mahtabalsadat Mirjalili ◽  
Ehsan Mirzaei ◽  
Hadis Mirzaee ◽  
Afsaneh Vazin
Keyword(s):  
Intensive Care ◽  
Drug Interactions ◽  
Intensive Care Units ◽  
Trauma Center ◽  
Type A ◽  
P Value ◽  
Potential Drug ◽  
Potential Ddis ◽  
Once Daily ◽  
Staffing Patterns

Background: Drug–drug interactions (DDIs) have created alarming challenges for public health, especially in those admitted to intensive care units (ICUs). Many studies have shown that involvement of intensivists in the ICUs improves the outcome and decreases the treatment costs. The effect of academic versus non-academic (therapeutic) intensivist as well as hours of coverage and attendance of intensivist on potential DDIs (pDDIs) was evaluated in six adult trauma ICUs of a level one trauma center. Methods: In this 6-month cross-sectional study, 200 patients were included. The DDIs were classified into five groups, including type A, B, C, D, and X. pDDIs were defined as interactions belonged to C, D and X categories. Patients in six adult ICUs with three different patterns of intensivist staffing models including type A (once-daily therapeutic intensivist visit followed by 24 h on-call), B (twice-daily academic intensivist visit, 8 h of attendance in ICU and 16 h on-call) and C (all criteria just like ICU type B, except for the presence of therapeutic instead of academic intensivist) were screened for pDDIs. Results: In total, 3735 drug orders and 3869 drugs (193 different types) were screened and 1826 pDDIs were identified. Type C, D and X interactions accounted for 60.6%, 35.5%, and 3.9% of all pDDIs, respectively. The mean of pDDI per patient was significantly higher ( p-value < 0.001) in the ICU type A than ICU types C and B. The frequency of pDDIs was the highest in the type A ICUs. A statistically significant relationship was observed between the number of prescribed drugs and ICU length of stay ( p-value < 0.001 and p = 0.009, respectively). Conclusion: Different patterns of intensivist staffing affect pDDIs to varying degrees. In the studied ICUs academic versus therapeutic intensivist, twice versus once-daily visit, and 8 h attendance with16 h on-call versus 24 h on-call were associated with more reductions in pDDIs. Plain language summary The impact of different intensivist staffing patterns in ICUs on the rate of potential drug-drug interactions Drug-drug interactions (DDIs) have created alarming challenges for public health, especially in patients admitted to intensive care units (ICUs). Many studies have shown that involvement of intensivists in the ICUs improves the outcome and limits the costs. Considering the high incidence of potential DDIs (pDDIs) occurring for critically ill patients and the importance of ADRs caused by pDDIs in ICUs, the effect of the presence of an academic versus therapeutic intensivist, as well as the hour of coverage of intensivist on prevalence of pDDIs was evaluated in six adult trauma ICUs of a level one trauma center in Shiraz, Iran. We also determined the prevalence of pDDIs and their associated risk factors. To the best of our knowledge, this is the first study that has assessed the effect of various ICU physician staffing models on the incidence and pattern of pDDIs.

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