Risk Of Adverse Drug Events Research Articles

Development and Application of an Attribute-Based Taxonomy on the Benefits of Oral Anticoagulant Switching in Atrial Fibrillation: A Delphi Study.

Patients with atrial fibrillation (AF) often switch between oral anticoagulants (OACs). It can be hard to know why a patient has switched outside of a clinical setting. Medication attribute comparisons can suggest benefits. Consensus on terms and definitions is required for inferring OAC switch benefits. The objectives of the study were to generate consensus on a taxonomy of the potential benefits of OAC switching in patients with AF and apply the taxonomy to real-world data. Nine expert clinicians (seven clinical pharmacists, two cardiologists) with at least 3years of clinical and research experience in AF participated in a Delphi process. The experts rated and commented on a proposed taxonomy on the potential benefits of OAC switching. After each Delphi round, ratings were analyzed with the RAND Corporation/University of California, Los Angeles (RAND/UCLA) appropriateness method. Median ratings, disagreement index, and comments were used to modify the taxonomy. The resulting taxonomy from the Delphi process was applied to a cohort of patients with AF who switched OACs in a population-based administrative health dataset from 1996 to 2019 in British Columbia, Canada. The taxonomy was finalized in two Delphi rounds, reaching consensus on five switch benefit categories: safety, effectiveness, convenience, economic considerations, and drug interactions. Safety benefit (a switch that could lower the risk of adverse drug events) had three subcategories: major bleeding, intracranial hemorrhage (ICH), and gastrointestinal (GI) bleeding. Effectiveness benefit had four subcategories: stroke and systemic embolism (SSE), ischemic stroke, myocardial infarction (MI), and all-cause mortality. Real-world OAC switches revealed that more OAC switches had convenience (72.6%) and drug interaction (63.0%) benefits compared to effectiveness (SSE 22.0%, ischemic stroke 11.1%, MI 3.1%, all-cause mortality 10.1%), safety (major bleeding 24.3%, GI bleeding 10.6%, ICH 48.5%), and economic benefits (12.1%). The Delphi-based taxonomy identified five criteria for the beneficial effects of OAC switching, aiding in characterizing real-world OAC switching.

Cost-utility analysis of pharmacogenomics-guided tacrolimus treatment in Austrian kidney transplant recipients participating in the U-PGx PREPARE study.

Chronic kidney disease (CKD) is a global health issue. Kidney failure patients may undergo a kidney transplantation (KTX) and prescribed an immunosuppressant medication i.e., tacrolimus. Tacrolimus' efficacy and toxicity varies among patients. This study investigates the cost-utility of pharmacogenomics (PGx) guided tacrolimus treatment compared to the conventional approach in Austrian patients undergone KTX, participating in the PREPARE UPGx study. Treatment's effectiveness was determined by mean survival, and utility values were based on a Visual Analog Scale score. Incremental Cost-Effectiveness Ratio was also calculated. PGx-guided treatment arm was found to be cost-effective, resulting in reduced cost (3902 euros less), 6% less hospitalization days and lower risk of adverse drug events compared to the control arm. The PGx-guided arm showed a mean 0.900 QALYs (95% CI: 0.862-0.936) versus 0.851 QALYs (95% CI: 0.814-0.885) in the other arm. In conclusion, PGx-guided tacrolimus treatment represents a cost-saving option in the Austrian healthcare setting.

Prevalence and characteristics of patients prescribed opioids and central nervous system depression agents on discharge to hospice care.

Hospice patients with end-stage liver disease (ESLD) have an increased risk of adverse drug events due to physiological changes and changes in pharmacokinetic and pharmacodynamic properties of medications; however, the use of opioid and central nervous system (CNS) depressant prescribing among patients with ESLD is prevalent. This study quantified the frequency and distribution of opioid and concomitant respiratory and CNS depressant prescribing among hospice patients with ESLD compared to other common hospice diagnoses of cancer, chronic obstructive pulmonary disorder (COPD), heart failure, and end-stage renal disease. This was a cross-sectional study of adult (age 18 years or older) decedents of a large hospice chain. Patients included had a primary diagnosis of liver, cancer, cardiovascular, or respiratory disease. Among 119,424 hospice decedents, mean age of 77.9 years (standard deviation =13.5 years), 54.6% were female, and 58.9% were of a non-Hispanic white race. There was a similar frequency of prescribing a "scheduled" and "as needed [pro re nata (PRN)]" opioid or benzodiazepine in patients with ESLD compared to other common hospice diagnoses. In addition, there was a high prevalence of concurrent opioid and benzodiazepine prescriptions among patients with ESLD compared to cardiovascular and respiratory disease at admission (65.4% vs. 63.9% and 64.9%). Opioid requirements, oral morphine equivalent (OME) median [interquartile range (IQR)] at discharge were similar between cancer, liver, and respiratory disease, 120 OME [60-300], 120 OME [50-240], and 120 OME [50-240], respectively. We observed a high frequency of opioid and CNS depressant prescribing in a hospice patient population with ESLD which was similar to other common admitting hospice diagnoses.

A study to Monitor Adverse drug reactions in a patients of Chronic Obstructive pulmonary Disease

Background: Inappropriate drug usage may preclude ideal benefit due to increased medical cost, adverse effects and mortality. Therefore drug utilization studies have become a plausible means in evaluating the healthcare systems. COPD management usually involves more than one drug which may escalate the risk of ADEs (adverse drug events). The present study aimed at assessing the current drug practice and ADEs in COPD management in ICU. Material and Methods: A prospective, single centered, observational and open labeled study was carried out in Department of Pulmonary Medicine and Pharmacology, Tertiary Care Teaching Hospital. The patient population was broadly divided into four categories based on diagnosis ‑ chronic obstructive pulmonary disease, Infections, Asthma and Others. Suspected ADRs were reported, analyzed, and causality assessment was carried out using Naranjo’s algorithm scal0065. Results: In our study, most important causative drug was Budesonide (11.1%). Causality assessment of ADR by Naranjo’s algorithm showed 11.9% probable and 88.1% possible reactions. According to WHO-UMC scale, 85.9% reactions are possible, 11.1% are probable, and 3% are unlikely. Among the 270 ADR reported, the most common ADR was oral thrush which accounted for 11.1% (n = 30) of the reported cases, followed by palpitation 11.1% (n = 30), sore throat 20 (7.4%), dizziness 17 (6.3%) cases, and headache 20 (7.4%) of reported ADR cases. Conclusion: Many research have been conducted separately on various respiratory diseases such as COPD, tuberculosis, asthma, respiratory tract infections (upper/lower), and so on. However, this study included some of the most common diseases in this field, such as COPD, tuberculosis, and respiratory tract infections. A routine patient follow-up is needed for the early detection and prevention of ADRs in order to improve patient adherence to drug therapy and provide improved drug therapy by avoiding associated morbidity and mortality.

The impact of early in-hospital use of PCSK9 inhibitors on cardiovascular outcomes in acute coronary syndrome patients: A systematic review and meta-analysis

ObjectiveTo explore the safety and assess the cardiovascular impact of early in-hospital administration of PCSK9 inhibitors in patients with acute coronary syndrome (ACS). MethodsA systematic search of PubMed, Web of Science, and Embase databases was conducted for studies involving the use of PCSK9 inhibitors in ACS patients from inception to October 2023. Two independent researchers screened the literature, extracted data, and assessed the risk of bias in the included studies. Meta-analysis was performed using STATA 16.0 software. ResultsNine studies, encompassing a total of 2896 ACS patients, were included in the analysis. When compared to statin monotherapy, early administration of PCSK9 inhibitors during hospitalization for ACS proved effective in reducing the incidence of major adverse cardiovascular events (MACEs). This encompassed a decrease in coronary revascularization [Relative Risk (RR) = 0.78, 95% CI (0.62, 0.98), P < 0.05], recurrent ACS [RR = 0.62, 95% CI (0.42, 0.94), P < 0.05], readmissions due to unstable angina [RR = 0.71, 95% CI (0.59, 0.85), P < 0.01], and strokes [RR = 0.31, 95% CI (0.09, 1.04), P = 0.058]. There was no significant difference in the incidence of death between the two groups.The use of PCSK9 inhibitors notably hastened the reduction of LDL-C, TG, and Non HDL-C levels in the short term. Additionally, it increased HDL-C levels and the number of individuals meeting LDL-C compliance criteria. Importantly, the risk of adverse drug events, such as ALT increase >3xULN, allergies, and musculoskeletal pain, did not significantly elevate with PCSK9 inhibitor use. ConclusionThe early administration of PCSK9 inhibitors has been found to safely and effectively lower diverse lipid levels in patients with ACS. This reduction is associated with a noteworthy decrease in MACEs, encompassing revascularization, recurrent ACS, and hospital readmissions.

Probable effects of polypharmacy and equivalent doses of psychotropic drugs on prevalence of adverse drug events among psychiatric inpatients in a general hospital in Japan.

In psychiatry, polypharmacy or high psychotropic drug doses increase adverse drug event (ADE) prevalence. However, the full relationship between polypharmacy and ADEs is unclear, and few studies have evaluated dose equivalents for psychotropic drugs for ADEs. Thus, we conducted a retrospective analysis to clarify the effects of polypharmacy and chlorpromazine (CP)-, diazepam (DAP)-, and imipramine- equivalent doses on all ADEs in inpatients. Psychiatric inpatients in a Japanese hospital from April 1, 2016 to March 31, 2018, were enrolled. ADE severity and causality were assessed. Multiple logistic regression analyses were performed to evaluate ADE risk factors. Among 462 patients analyzed, out of 471 patients enrolled, 145 (31.4%) experienced ADEs. The causality assessment determined that "possible" was 96.5%. The most common ADEs were nervous system disorders (35%). Multiple logistic regression analyses indicated an increase in ADE prevalence with the number of drugs used (≥5; p=0.026); CP-equivalent dose (p=0.048); and endocrine, nutritional, and metabolic disorders (p=0.045). DAP-equivalent dose; infectious and parasitic diseases; and injury, poisoning, and consequences of other external causes decreased ADE prevalence (p=0.047, 0.022, and 0.021, respectively). Avoiding polypharmacy in psychiatric inpatients and adjusting drug regimens to safe equivalent doses could reduce ADEs during hospitalization.

Update and Application of a Deep Learning Model for the Prediction of Interactions between Drugs Used by Patients with Multiple Sclerosis.

Patients with multiple sclerosis (MS) often take multiple drugs at the same time to modify the course of disease, alleviate neurological symptoms and manage co-existing conditions. A major consequence for a patient taking different medications is a higher risk of treatment failure and side effects. This is because a drug may alter the pharmacokinetic and/or pharmacodynamic properties of another drug, which is referred to as drug-drug interaction (DDI). We aimed to predict interactions of drugs that are used by patients with MS based on a deep neural network (DNN) using structural information as input. We further aimed to identify potential drug-food interactions (DFIs), which can affect drug efficacy and patient safety as well. We used DeepDDI, a multi-label classification model of specific DDI types, to predict changes in pharmacological effects and/or the risk of adverse drug events when two or more drugs are taken together. The original model with ~34 million trainable parameters was updated using >1 million DDIs recorded in the DrugBank database. Structure data of food components were obtained from the FooDB database. The medication plans of patients with MS (n = 627) were then searched for pairwise interactions between drug and food compounds. The updated DeepDDI model achieved accuracies of 92.2% and 92.1% on the validation and testing sets, respectively. The patients with MS used 312 different small molecule drugs as prescription or over-the-counter medications. In the medication plans, we identified 3748 DDIs in DrugBank and 13,365 DDIs using DeepDDI. At least one DDI was found for most patients (n = 509 or 81.2% based on the DNN model). The predictions revealed that many patients would be at increased risk of bleeding and bradycardic complications due to a potential DDI if they were to start a disease-modifying therapy with cladribine (n = 242 or 38.6%) and fingolimod (n = 279 or 44.5%), respectively. We also obtained numerous potential interactions for Bruton's tyrosine kinase inhibitors that are in clinical development for MS, such as evobrutinib (n = 434 DDIs). Food sources most often related to DFIs were corn (n = 5456 DFIs) and cow's milk (n = 4243 DFIs). We demonstrate that deep learning techniques can exploit chemical structure similarity to accurately predict DDIs and DFIs in patients with MS. Our study specifies drug pairs that potentially interact, suggests mechanisms causing adverse drug effects, informs about whether interacting drugs can be replaced with alternative drugs to avoid critical DDIs and provides dietary recommendations for MS patients who are taking certain drugs.

Polypharmacy in acute and chronic kidney diseases

The prevalence for chronic kidney disease (CKD) has steadily increased over the past decades. It is agradually progressive disease that is associated with several comorbidities including cardiovascular diseases, hypertension, anemia, disorders of bone and mineral metabolism, electrolyte imbalance and acid-base abnormalities. All these comorbidities require adequate medication. Therefore, patients with CKD have a high risk for polypharmacy, which is defined as five or more medications daily. Polypharmacy causes agreatly increased risk for adverse drug effects and severe drug-drug interactions, which if not closely controlled and the individual doses adapted to the decreased renal function during the progression of the CKD, can result in increased morbidity and mortality. Therefore, several aspects of the medication need to be considered and constantly addressed. This article summarizes the problems arising from inadequate polypharmacy in CKD patients, including undesired adverse drug effects, drug interactions, the complexity of medication plans, treatment burden and nonadherence to the treatment. Furthermore, the most important steps to identify patients with inadequate polypharmacy are discussed, whereby complications can also be avoided and the benefits of the medication can be increased. Finally, the polypharmacy in acute kidney injury is dealt with.

Adverse Drug Events Presented in Health Institutions in Monteria, Colombia, 2018-2021.

To analyze the adverse events reported in the pharmacovigilance of the health service provider institutions of the municipality of Monteria in the period 2018-2021. Descriptive, cross-sectional, retrospective, and quantitative approach study, the information was analyzed by statistical analysis by multiple correspondence using Orange Data Mining software; the analysis consisted of visual programming to perform interactive data exploration, to identify and differentiate associations or oppositions between different categories in space. The most frequently reported adverse events were allergic reactions, with 28.5%. Female sex and adult age are the groups most prone to present these events; antibiotics were the pharmacological group that produced the most adverse events with 18.3%; the main errors that produce these events are related to prescription. Age and sex increase the risk of adverse drug events; most of these events are the product of erroneous prescriptions. The findings presented in this article are useful for pharmacovigilance programs in health institutions.

Prevalence of polypharmacy: a cross-sectional study in Singapore public healthcare institutions

Abstract Introduction: Polypharmacy is associated with increased prevalence of potentially inappropriate medications (PIMs), leading to higher risk of adverse drug events and medication errors. This study was the first multicentre cross-sectional study in Singapore that determined the prevalence of polypharmacy, its associated factors and the common drug classes involved, and evaluated prescribing appropriateness of drugs used by older adults. Methods: The prescriptions on two randomly selected days from five acute care hospitals and primary care polyclinics were retrospectively reviewed. Patients’ demographic characteristics, number of prescription line items and details of prescribed drugs were collected. Prescribing appropriateness was evaluated by identifying PIMs using the Beers Criteria. Logistic regression was used to assess the association of demographic characteristics and type of care setting with polypharmacy and PIM use. Results: Prevalence of polypharmacy was significantly higher in hospitals than in polyclinics (66.6% vs. 35.0%, P &lt; 0.001). On the contrary, prevalence of PIMs in older adults with polypharmacy was significantly higher in polyclinics than in hospitals (34.6% vs. 27.1%, P = 0.010). Patients aged ≥65 years and hospitalised patients had higher odds of having polypharmacy than patients aged 21–64 years and polyclinic patients, respectively. Drugs used for chronic conditions commonly contributed to polypharmacy in both care settings. The top PIMs in hospitals and polyclinics were drugs for functional gastrointestinal disorders and systemic antihistamines, respectively. Conclusion: With the ageing population and growing burden of chronic disease in Singapore, increase in prevalence of polypharmacy is expected. More focus should thus be placed on reducing inappropriate polypharmacy.

Using machine learning or deep learning models in a hospital setting to detect inappropriate prescriptions: a systematic review

ObjectivesThe emergence of artificial intelligence (AI) is catching the interest of hospital pharmacists. A massive collection of health data is now available to train AI models and hold the promise...

Effect of MEF2A and SLC22A3-LPAL2-LPA gene polymorphisms on warfarin sensitivity and responsiveness in Jordanian cardiovascular patients.

This study aims to investigate the influence of MEF2A and SLC22A3-LPAL2-LPA polymorphisms on cardiovascular disease susceptibility and responsiveness to warfarin medication in Jordanian patients, during the initiation and maintenance phases of treatment. Several candidate genes have been reported to be involved in warfarin metabolism and studying such genes may help in finding an accurate way to determine the needed warfarin dose to lower the risk of adverse drug effects, resulting in more safe anticoagulant therapy. The study population included 212 cardiovascular patients and 213 healthy controls. Genotyping of MEF2A and SLC22A3-LPAL2-LPA polymorphisms was conducted to examine their effects on warfarin efficiency and cardiovascular disease susceptibility using PCR-based methods. One SNP (SLC22A3-LPAL2-LPA rs10455872) has been associated with cardiovascular disease in the Jordanian population, whereas the other SNPs in the MEF2A gene and SLC22A3-LPAL2-LPA gene cluster did not have any significant differences between cardiovascular patients and healthy individuals. Moreover, SLC22A3-LPAL2-LPA rs10455872 was correlated with moderate warfarin sensitivity, the other SNPs examined in the current study have not shown any significant associations with warfarin sensitivity and responsiveness. Our data refer to a lack of correlation between the MEF2A polymorphism and the efficacy of warfarin treatment in both phases of treatment, the initiation, and maintenance phases. However, only rs10455872 SNP was associated with sensitivity to warfarin during the initiation phase. Furthermore, rs3125050 has been found to be associated with the international normalized number treatment outcomes in the maintenance phase.

Shaping geriatric practice: evaluating Beers, PRISCUS, and European Union(7) criteria for optimal patient care. A retrospective study

Medications whose risk of adverse drug events exceeds their expected clinical benefit when given to older patients are called potentially inappropriate medications (PIMs). The geriatric population represents about 10% of the world population and 7% of the Indian population and consumes 40% of prescription and 35% of all over-the-counter drugs. That is why it is necessary to evaluate the use of PIMs in the geriatric population. This study aimed to evaluate prescriptions for PIMs by using three pre-validated and internationally used criteria, namely the Beers criteria (2019), the European Union (EU)(7) list (2015), and the PRISCUS list (2010). A retrospective observational study began after obtaining written approval from the institutional review board. Demographic and clinical profiles and patients' complete prescriptions were recorded, and the Beers criteria (2019), the EU(7) (2015) list, and the PRISCUS list (2010) were applied. A p&lt;0.05 was considered statistically significant. A total of 345 patients, with a mean age of 71.48 years, were included in the study. Vitamin D3 (56.81%) was frequently prescribed as medicine. According to the Beers, EU(7), and PRISCUS criteria, PIMs were 311 (11.26%), 272 (9.85%), and 105 (3.80%), respectively. Pantoprazole [20.57% Beers and 23.52% EU(7)] and glimepiride [15.43% Beers and 17.64% EU(7)] were the most inappropriate drugs. According to the PRISCUS list, piroxicam (21.9%) and etoricoxib (19.04%) were the inappropriate drugs. According to the Beers, EU(7), and PRISCUS criteria, total inappropriate prescriptions containing at least one PIM are 183 (52.04%), 174 (50.43%), and 88 (25.5%), respectively. The number of prescriptions with inappropriate medication is highly correlated with the total number of drugs prescribed per prescription (p&lt;0.01) and the total number of fixed-dose combinations (p&lt;0.01). Maximum PIMs were found with the Beers criteria and minimum PIMs with the PRISCUS list. This study shows that the prescription of PIMs ranges from 25.5 to 52.04%. The EU(7) list had the highest sensitivity (63.66%), while the PRISCUS list had the highest specificity (98.48%) to detect PIMs with the Beers criteria taken as a reference.

One Size Does Not Fit All: Medication Reconciliation and Review at the Hospital at Home.

Mistakes in the medication process are frequent and a common cause of morbidity and mortality. Medication reconciliation (MRec) and medication review (MRev) are the processes of creating the most accurate medication list and adapting it to optimize the effectiveness of medicines and minimize adverse effects. This is crucial in all stages of medical care, especially at discharge. The present study aims to evaluate and describe the process of MRec and MRev, with a focus on deprescribing, that we conduct at the Hospital at Home. We performed a retrospective cohort study including adult patients admitted at our Hospital at Home from 1 November 2022 to 30 April 2023. MRec and MRev were applied during hospitalization, according to patients' characteristics and clinical evolution, and then communicated to patients upon discharge. Our study involved 125 patients, with an average age of 67.6±18.0 years, and half of them had polypharmacy. We discovered discrepancies in 43.2% of patient's medication and did deprescribing in one-third of them. In the deprescribing group, patients were significantly older (mean age, 76.1 versus66.4 years; p=0.044). It is imperative to create mechanisms to identify patients at a greater risk of adverse drug events and to minimize the burden of care and harms associated with treatments. The Hospital at Home could be an opportunity, although further research is essential.

Impact of deprescribing intervention on potentially inappropriate medications and clinical outcomes among hospitalized older adults in Malaysia: a randomized controlled trial (REVMED RCT) protocol

BackgroundPolypharmacy and the use of potentially inappropriate medications (PIMs) are prevalent among older patients admitted to hospitals, posing a heightened risk of adverse drug events. This trial aims to evaluate the effectiveness of a pharmacist-led deprescribing intervention in reducing medications, PIM and improving clinical outcomes, using the locally developed Malaysian Potentially Inappropriate Prescribing Screening tool in Older Adults (MALPIP).MethodsThis is an 18-month cluster-randomized, open-label, parallel-arm controlled trial conducted at 14 public hospitals in the Perak state of Malaysia. Patients aged 60 and above, who have at least one medication and one comorbidity are eligible. A stratified-cluster randomization design is employed, with 7 hospitals assigned to the control arm and 7 hospitals assigned to the intervention arm. The MALPIP screening tool will be used in the intervention group to review the medications. If PIM is detected, the pharmacists will discuss with doctors and decide whether to stop or reduce the dose. The primary outcomes of this trial are the total number of medications and number of PIM. The secondary outcomes include fall, emergency department visits, readmissions, quality of life and mortality. Outcomes will be measured during enrolment, discharge, 6, 12, and 18 months.DiscussionThis REVMED trial aims to test the hypothesis that a pharmacist-led deprescribing intervention initiated in the hospital will reduce the total number of medications and PIM 18 months after hospital discharge, reducing fall, emergency department visits, readmissions, mortality and lead to improvement in quality of life. Trial findings will quantify the clinical outcomes associated with reducing medications and PIM for hospitalized older adults with polypharmacy.Trial registration number: This trial was prospectively registered at clinicaltrials.gov (NCT05875623) on the 25th of May 2023. NCT05875623 Clinicaltrials.gov URL: NCT05875623 registered on 25th July 2023.

Frequencies of pharmacogenomic alleles across biogeographic groups in a large-scale biobank

Pharmacogenomics (PGx) is an integral part of precision medicine and contributes to the maximization of drug efficacy and reduction of adverse drug event risk. Accurate information on PGx allele frequencies improves the implementation of PGx. Nonetheless, curating such information from published allele data is time and resource intensive. The limited number of allelic variants in most studies leads to an underestimation of certain alleles. We applied the Pharmacogenomics Clinical Annotation Tool (PharmCAT) on an integrated 200K UK Biobank genetic dataset (N= 200,044). Based on PharmCAT results, we estimated PGx frequencies (alleles, diplotypes, phenotypes, and activity scores) for 17 pharmacogenes in five biogeographic groups: European, Central/South Asian, East Asian, Afro-Caribbean, and Sub-Saharan African. PGx frequencies were distinct for each biogeographic group. Even biogeographic groups with similar proportions of phenotypes were driven by different sets of dominant PGx alleles. PharmCAT also identified "no-function" alleles that were rare or seldom tested in certain groups by previous studies, e.g., SLCO1B1∗31 in the Afro-Caribbean (3.0%) and Sub-Saharan African (3.9%) groups. Estimated PGx frequencies are disseminated via the PharmGKB (The Pharmacogenomics Knowledgebase: www.pharmgkb.org). We demonstrate that genetic biobanks such as the UK Biobank are a robust resource for estimating PGx frequencies. Improving our understanding of PGx allele and phenotype frequencies provides guidance for future PGx studies and clinical genetic test panel design, and better serves individuals from wider biogeographic backgrounds.

Prolonged use of linezolid in bone and joint infections: a retrospective analysis of adverse effects.

Antibiotic treatment for bone and joint infections generally lasts for 6 weeks or longer. Linezolid may be a good option for treating bone and joint infections, but there is an increased risk of potential serious adverse drug events (ADEs) when used for more than 28 days. The aim of this study was to obtain detailed information on the type and time to occurrence of the patient-reported ADEs, the dynamics of haematopoiesis over time, and the reasons for early discontinuation of linezolid when used for an intended maximum duration of 12 weeks. This single-centre retrospective study was conducted at the Sint Maartenskliniek in The Netherlands. Patients were included if they were planned to use linezolid for more than 28 days. The main reason for discontinuation of linezolid, the ADE according to the Naranjo score, and the time to occurrence of ADEs were analysed. Among 78 patients, drug toxicity led to early discontinuation of linezolid in 11 (14%) patients before and nine (12%) after 28 days of therapy. The median treatment duration was 42 days. Gastrointestinal intolerance (42%) and malaise (32%) were the most common ADEs. In 75% of the cases the ADE occurred within 28 days of therapy. Sixty-seven patients were able to continue linezolid beyond 28 days, 87% of whom completed therapy as scheduled. Severe cytopenia, according to the Common Terminology Criteria for Adverse events (CTCA), was observed in four patients and was reversible after discontinuation of linezolid. One patient suffered optic neuropathy related to linezolid use. Linezolid could be considered an alternative option to the current standard of IV glycopeptides for the treatment of bone and joint infection for up to 12 weeks. If patients pass the first 28 days of therapy, the likelihood of successful completion of therapy is high with a low risk of serious ADEs.

Medication clusters at hospital discharge and risk of adverse drug events at 30 days postdischarge: A population-based cohort study of older adults.

Certain combinations of medications can be harmful and may lead to serious adverse drug events (ADEs). Identifying potentially problematic medication clusters could help guide prescribing and/or deprescribing decisions in hospital. The aim of this study is to characterize medication prescribing patterns at hospital discharge and determine which medication clusters were associated with an increased risk of ADEs in the 30-day posthospital discharge. All residents of the province of Ontario in Canada aged 66 years or older admitted to hospital between March 2016 and February 2017 were included. Identification of medication clusters prescribed at hospital discharge was conducted using latent class analysis. Cluster identification and categorization were based on medications dispensed up to 30-day posthospitalization. Multivariable logistic regression was used to assess the potential association between membership to a particular medication cluster and ADEs postdischarge, while also evaluating other patient characteristics. In total, 188 354 patients were included in the study cohort. Median age (interquartile range) was 77 (71-84) years, and patients had a median (IQR) (interquartile range [IQR]) of 9 (6-13) medications dispensed prior to admission. Within the study population, 6 separate clusters of dispensing patterns were identified: cardiovascular (14%), respiratory (26%), complex care needs (12%), cardiovascular and metabolic (15%), infection (10%), and surgical (24%). Overall, 12680 (7%) patients had an ADE in the 30 days following discharge. After considering other patient characteristics, those belonging to the respiratory cluster had the highest risk of ADEs (adjusted odds ratio: 1.12, 95% confidence interval: 1.08-1.17) compared with all the other clusters, while those in the complex care needs cluster had the lowest risk (adjusted odds ratio: 0.82, 95% confidence interval: 0.77-0.87). This study suggests that ADEs post hospital discharge can be linked with identifiable medication clusters. This information may help clinicians and researchers better understand patient populations that are more or less likely to benefit from peri-hospital discharge interventions aimed at reducing ADEs.

MultiGML: Multimodal graph machine learning for prediction of adverse drug events

Adverse drug events constitute a major challenge for the success of clinical trials. Several computational strategies have been suggested to estimate the risk of adverse drug events in preclinical drug development. While these approaches have demonstrated high utility in practice, they are at the same time limited to specific information sources. Thus, many current computational approaches neglect a wealth of information which results from the integration of different data sources, such as biological protein function, gene expression, chemical compound structure, cell-based imaging and others. In this work we propose an integrative and explainable multi-modal Graph Machine Learning approach (MultiGML), which fuses knowledge graphs with multiple further data modalities to predict drug related adverse events and general drug target-phenotype associations. MultiGML demonstrates excellent prediction performance compared to alternative algorithms, including various traditional knowledge graph embedding techniques. MultiGML distinguishes itself from alternative techniques by providing in-depth explanations of model predictions, which point towards biological mechanisms associated with predictions of an adverse drug event. Hence, MultiGML could be a versatile tool to support decision making in preclinical drug development.

A real-world pharmacovigilance analysis of FDA adverse event reporting system database for upadacitinib.

Objective: To mine the adverse drug event (ADE) signals of upadacitinib based on the Food and Drug Administration (FDA) Adverse Event Reporting System (FAERS) database to provide a reference for the safe clinical use of the drug. Methods: The ADE data for upadacitinib from Q1 2004 to Q1 2023 in the FAERS database were retrieved, and data mining was performed using the reporting odds ratio and proportional reporting ratio. Results: A total of 21,213 ADE reports for the primary suspect drug upadacitinib were obtained, involving 444 ADEs. Patients aged ≥60years (21.48%) and female (70.11%) patients were at a higher risk of ADEs with upadacitinib. After data cleaning, 182 ADE signals from 19 system organ classes (SOCs) were obtained. Six of these SOCs that occurred more frequently and were not mentioned in the drug labeling information included renal and urinary system (1.09%), reproductive and breast diseases (1.14%), ear and labyrinth disorders (0.57%), psychiatric disease (0.57%), blood and lymphatic system disorders (0.57%), and endocrine disorders (0.57%). The top ten most frequent ADE signals reported for upadacitinib were mainly related to: infections and infestations (7), investigations (2), and skin and subcutaneous tissue disorders (1). The top 10 ADEs in signal intensity ranking were lip neoplasm, ureteral neoplasm, eczema herpeticum, vulvar dysplasia, mediastinum neoplasm, eosinopenia, herpes zoster cutaneous disseminated, eye ulcer, acne cystic, and Moraxella infection. The top 10 high-frequency events leading to serious adverse events were urinary tract infection (2.74%), herpes zoster (1.63%), diverticulitis (1.19%), bronchitis (0.68%), nasopharyngitis (0.68%), localised infection (0.66%), nephrolithiasis (0.66%), pulmonary thrombosis (0.66%), blood cholesterol increased (0.55%), and Pneumocystis jirovecii pneumonia (0.53%). Conclusion: Clinicians should be vigilant to upadacitinib-induced events in systems not covered in the drug labeling information and to new and highly signaled ADEs to ensure the safe and effective use of upadacitinib.