جستجوی مقالات مرتبط با کلیدواژه "تداخلات دارویی" در نشریات گروه "پزشکی"

The discovery of hidden patterns in pharmaceutical data can contribute to improving the performance of hospital pharmacies. One of the applications of advanced data analysis techniques is the identification of drug interactions.

This study was conducted using data mining techniques with the FP-growth algorithm in the RapidMiner Studio® 10.1 environment to extract association rules and frequent pharmaceutical patterns. Data preprocessing and modeling were performed based on the CRISP-DM model. The type and level of drug interactions were determined based on the algorithm's results and by referencing the database at www.drugs.com.

The results included 17 association rules and 126 prescribing patterns, ranging from single-drug to four-drug combinations. Of the 64 two-drug prescribing patterns, 56 had no interaction, 6 had moderate interactions, 1 had a minor interaction, and 1 had a major interaction. Additionally, of the 19 three-drug patterns, 18 had no interaction, and only 1 had a moderate interaction. No interactions were observed in the four-drug prescribing pattern.

The findings of this study can assist stakeholders in improving the pharmaceutical supply chain, optimizing prescriptions, reducing drug interactions, and lowering costs. The discovered patterns may also be used as part of a clinical decision support system. Although no significant drug interactions were observed in this study, the discovery of even one major interaction highlights its importance and further underscores the practical role of computer applications in medicine.

The use of medicinal plants for prevention, and treatment of diseases has long  received attention. Some medicinal plants are not safe and some of them are poisonous and, if consumed, can cause serious harms to many body organs and systems. Therefore, the aim of the present study is conducting a review on side effects and drug interactions of native medicinal plants in Kerman province. Side effects and the failure of chemical drugs to treat incurable diseases, being less expensive, and also easier access to herbal medicines have increased the use of herbal medicines. There is a misconception among many people that herbs have no therapeutic effect or, side effects. The results of the present study show that arbitrary and excessive usage of herbal medicines has harmful consequences. Furthermore, usage of many medicinal plants is also contraindicated in different conditions. There are also different reports on medicinal plants interactions with a number of chemical drugs. Therefore, it is necessary that medicinal plants be consumed under the supervision of knowledgeable and expert people in order to avoid any possible consequences and harms; in this way, the consumer can benefit the most from the consumption of medicinal plants.

The prescribing pattern of non-steroidal anti-inflammatory drugs (NSAIDs) has scarcely been studied in Iran. This study aims to evaluate the prescribing pattern of NSAIDs in the prescriptions of the patients who referred to Taleghani and Imam Khomeini educational pharmacies from March 21st to September 22nd, 2019 in order to find a way to reduce their irrational and excessive prescription as well as their serious side effects.

In this retrospective, cross-sectional study all the prescriptions containing NSAIDs from March 21st to September 22nd, 2019 in Taleghani and Imam Khomeini educational pharmacies were analyzed using the Tebyan software and the drug interactions were determined using the Lexicomp application and the data was collected.

Among the overall 47652 prescriptions analyzed in both pharmacies, the most and the least prescribed drug in both pharmacies were the 30 mg/mL ketorolac ampoule and the 250 ml mephenamic acid, respectively. The greatest number of major and moderate interactions between drugs in Imam Khomeini pharmacy were both seen in prescriptions containing the 30mg/mL ketorolac ampoule with the percentages of 41.9% and 32.1%, respectively; and in Taleghani pharmacy the greatest number of both interactions were seen in prescriptions containing the 30mg/1mL ketorolac ampoule with the percentages of 75.2% and 76.6%, respectively.

NSAIDs are widely prescribed and a high number of drug interactions are observed in prescriptions containing these drugs. We can conclude from this study that physicians need more attention and education concerning NSAID drug interactions with each other and with other drugs.

Drug interactions are one of the problems caused by the irrational administration of drugs and one of the common causes of morbidity and mortality in patients. Since drug interactions are usually predictable, they are therefore avoidable and manageable. This study aimed to evaluate the frequency of drug interactions and their related factors in hospitalized patients of the intensive care unit in the Hamadan Besat hospital, Iran.

 This cross-sectional study was performed on the clinical records of patients admitted to the intensive care unit (2019-2020) of Besat Hospital in Hamadan, Iran. Data were analyzed to determine the type of drug interactions based on the interactions available on the Up To Date and RxList databases. Other information was obtained from the patientschr('39') clinical records. Completion of information was recorded in the Pre-Design checklist. Finally, the data was analyzed using SPSS software version 22 and appropriate descriptive-analytical methods.

 The mean number of total drug interactions per prescription was 5.94 ± 4.91. Most interactions were type C (63.89%), Moderate (67.66%), Fair (70.96%) and Significant (44.76%).

According to the results, prolonged stay in an intensive care unit, the elderly, and polypharmacy are the main important factors associated with the occurrence of drug-drug interactions. These results indicate the importance of paying more attention to the monitoring and control of prescribed drugs in these patients.

Despite the tendency to use herbs and herbal medicine, less scientific documents have been published on the problems and necessities of using these types of drugs, especially on side effects, plant health and even drug interactions.

In this study, in order to review and critique the scientific documents related to the challenges of production and consumption of medicinal plants, review studies by examining sources by exploring scientific sources from Science Direct, Google Scholar, PubMed, Magiran and SID databases. The original Gigalib Digital Library was used to prepare the original reports. The terms "herbs", "adverse effects", "side effects", "drug-herbal interactions" and "complementary medicine" were used to search between 2000 and 2018. The fundamental questions of the study were whether the medicinal plants and herbal medicines offered have the necessary health and efficiency for public consumption? And will indiscriminate use of chemical drugs increase the effectiveness of drugs or not?

Results indicated the multiplicity of scientific reports related to the medicinal and therapeutic effects of medicinal plants. Factors such as advertising, culture and dislike of chemical drugs are involved in the tendency to use them. There were numerous reports of unhealthy production and fraud in medicinal plants and lack of expertise in prescribing and medication of medicinal plants and herbal medicines.

The use of herbal medicines is not without risk. Conscious use of herbs and attention to their possible side effects and drug interactions is recommended. Standardization of medicinal plant production processes is also necessary to ensure part of their efficiency and safety.

Drug interactions are one of the serious subsets of medication errors and occur when the effects or toxicity of one drug are affected by another. This study aimed to investigate drug interactions and the role of pharmacist in reducing drug interactions in Ramsar Imam Sajjad Hospital, Iran.

This cross-sectional study was performed in all prescriptions of medicinal products by specialist physicians in Ramsar Special Clinic from March to May 2019. Drug interactions were determined based on Drug Interaction Facts (2014) and Drugs website (www.drugs.com). A list of drug interactions prescribed by each physician was compiled and discussed in face-to-face visits with physicians. They were then provided with a list of unsafe combinations of medications. Prescriptions of physicians who had previous history of prescriptions with drug interactions were reviewed within two months in January and February 2020.

In first phase, 2864 prescriptions were studied of which 268 (9.3%) were detected with drug interactions. There were 40 (14.9%) cases of major drug interactions and 228 (85%) cases of moderate drug interactions. After providing feedback to physicians about drug interactions, the rate of drug-drug interactions decreased from 9.3% to 6.4%.

Many drug interactions are preventable and communications between physicians and pharmacists can help identifying drug interactions and minimizing their incidence.

The administration of appropriate drugs to patients is one of the most important processes of treatment and requires careful decision-making based-on the current conditions of the patient and its history and symptoms. In many cases, patients may require more than one drug, or in addition to having a previous illness and receiving the drug, they need new drugs for the new illness, which may increase medical errors in the administration of the drug and the adverse drug events(ADE) such as drug interactions for the patient.

In this article, the stages of designing and describing the requirements and the modeling of the ontology-based semantic recommender system of the prescribing physician and the discovery of the ADEs were presented. First, the requirements of the system were extracted and described in detail and then, based on the extracted requirements, the modeling of the system using the Unified Modeling Language of UML2.0 was discussed. Then, according to the extracted requirements for the discovery of ADEs, a proper ontology was designed for the system and implemented by Protégé software. In order to evaluate the functions of recommendation and discovering ADEs (interactions), a prototype was developed using Java language, and a collection of rules for reasoning and discovering interactions and ADEs were gathered.

The results of the system performance evaluation for the functions of detecting ADEs and medication recommendation suggests improvement of the proposed approach to 9.25% and 11.3% in the precision criterion, 29% and 60.6% in the recall, and 26% (respectively, approaches to the detection of ADEs and drug recommendations).

The use of this system as a computerized physician ordering entry can, in addition to helping physicians to prescribe a more accurate prescription, reduce the risks to the health of patients resulting from medical errors in the prescribing phase.

Potential Drug Interaction (PDI) is one of the medicine error which can led to undesirable reactions in patients. PDI occures when effect of toxocity of one medicine is affected by another one. This study aims to examination of of PDI freguency، clinical value ranking and risk factors in ICU ward of Urmia Taleghani hospital، Iran in 2011.

A cross-sectional study was carried out amog 193 inpatient of ICU ward. Data were collected retrospectively. Descriptive-analytical methods was used to analyse data including mean، median، standard deviation and t-test. Data were anlysed by SPSS.

Frequency of PDI was 73. 6% and mean of PDI was 4. 07. The most common PDI was Ranitidin + Midozolam with 26 (4. 1%) of cases. grade of PDI was mild for 46 (7. 9%)، moderate for 192 (33%)، sever for 51 (8. 8%)، contradicted for 150 (25. 8%)، ()، and unknown for 143 (24. 4%). PDI effects manifested immediately for 195 (33. 5%) and with delay for 384 (66. 5%). 49. 95 % of PDIs had significant clinical value and 41. 19 % higly significant clinical value.

Knowledge of drug interaction، replacing of interacting drug with other drugs as much as possible، noticing of highly interacting drugs، deminishing number of prescribed drugs can reduce PDI number and its consequences.

Drug interaction occurs when a drug affects the action of another. In this line, the present study has been conducted to determine the prevalence of potential drug interactions in critical care units.

In the present retrospective study, the first twenty-four hour prescriptions of 371 patients admitted to intensive care unit of Shahid Bahonar hospital of Kerman were investigated in terms of the number and type of drug interaction in addition to other factors such as number of drugs, age, gender, length of ICU stay and number of prescribing doctors. In order to determine the number and type of drug interactions, a reference textbook of "Drug Interaction Facts" was used, and data analysis was performed by SPSS18 statistical software with respect to the study objectives using descriptive statistics, Pierson correlation test, independent t-test, and variance analysis.

In terms of the drugs received, 77 different drugs and, in total, 2091 cases of drug prescription were found with the average of 5.6 (±1.5) for each patient. Overall, 726 cases of drug interactions were observed among critical care unit patients in the first 24 hour of prescription. Delayed, moderate, and possible interactions were accounted for the most interactions found. The results are indicative of a significant correlation between the number of drug interactions and prescribed medications, age, gender, duration of hospitalizations and number of prescribing doctors.

Due to possessing more risk factors of drug interactions, critical care unit patients are at higher risk of developing drug interaction which behooves the medical team to pay more attention to this issue.