Pharmacogenetics to prevent hypersensitivity reactions to antiepileptic drugs: is testing performed when indicated?

Extensive scientific evidence consistently demonstrates the clinical validity and utility of HLA-B*15:02 pre-screening in averting severe cutaneous adverse reactions (SCARs), namely Stevens-Johnson syndrome and toxic epidermal necrolysis, associated with carbamazepine or oxcarbazepine usage. Current practice guidelines and drug labeling actively advocate for pharmacogenetic pre-screening before initiating these antiepileptic drugs (AED), with particular emphasis on patients of Asian descent. However, there is a potential need to strengthen compliance with these recommendations. This retrospective study aimed to describe the pharmacogenetic pre-screening, documentation, and SCARs incidence for patients of Asian ancestry initiated on carbamazepine or oxcarbazepine at a large Northeastern USA healthcare system. Between 1 July 2016 and August 1, 2021, 27 patients with documented Asian heritage in the electronic health record (EHR) were included. The overall rate of HLA-B*15:02 pre-screening before carbamazepine or oxcarbazepine initiation was 4%. None who underwent pharmacogenetic pre-screening carried the associated HLA-B risk allele, and no SCARs were reported. Notably, pharmacogenetic results were not discretely entered into the EHR, and the results were only found as attached documents in the miscellaneous section of the EHR. There remains a significant opportunity for improving HLA-B*15:02 pre-screening for patients starting carbamazepine and oxcarbazepine to prevent SCARs in the USA.

Documentation of results and medication prescribing after combinatorial psychiatric pharmacogenetic testing: A case for discrete results.

PURPOSE: Combinatorial pharmacogenetic (PGx) panels intended to aid psychiatric prescribing are available to clinicians. Here, we evaluated the documentation of PGx panel results and subsequent prescribing patterns within a tertiary health care system. METHODS: We performed a query of psychiatry service note text in our electronic health record using 71 predefined PGx terms. Patients who underwent combinatorial PGx testing were identified, and documentation of test results was analyzed. Prescription data following testing were examined for the frequency of prescriptions influenced by genes on the panel along with the medical specialties involved. RESULTS: A total of 341 patients received combinatorial PGx testing, and documentation of results was found to be absent or incomplete for 198 patients (58%). The predominant method of documentation was through portable document formats uploaded to the electronic health record's "Media" section. Among patients with at least 1 year of follow-up, a large majority (194/228, 85%) received orders for medications affected by the tested genes, including 132 of 228 (58%) patients receiving at least 1 non-psychiatric medication influenced by the test results. CONCLUSION: Results from combinatorial PGx testing were poorly documented. Medications affected by these results were often prescribed after testing, highlighting the need for discrete results and clinical decision support.

Use of the Electronic Health Record for Monitoring Adverse Drug Reactions.

PURPOSE OF REVIEW: Adverse drug reactions (ADRs) are a significant cause of morbidity and mortality. The electronic health record (EHR) provides an opportunity to monitor ADRs, mainly through the utilization of drug allergy data and pharmacogenomics. This review article explores the current use of the EHR for ADR monitoring and highlights areas that require improvement. RECENT FINDINGS: Recent research has identified several issues with using EHR for ADR monitoring. These include the lack of standardization between EHR systems, specificity in data entry options, incomplete and inaccurate documentation, and alert fatigue. These issues can limit the effectiveness of ADR monitoring and compromise patient safety. The EHR has great potential for monitoring ADR but needs significant updates to improve patient safety and optimize care. Future research should concentrate on developing standardized documentation and clinical decision support systems within EHRs. Healthcare professionals should also be educated on the significance of accurate and complete ADR monitoring.

Theoretical Study of Decomposition Kinetics and Thermochemistry of Bis(dimethylamino)silane-Formation of Methyleneimine and Silanimine Species.

The gas-phase decomposition kinetics and thermochemistry of bis(dimethylamino)silane (BDMAS), a potential precursor in the chemical vapor deposition of silicon nitride and silicon carbonitride thin films, were systematically studied using ab initio calculations at the CCSD(T)/6-311 + G(2d,p)//B3LYP/6-311 + + G(d,p) level of theory. The reaction routes were mapped out, exploring both the concerted and stepwise reactions in three different zones with the initial cleavage of Si-N, N-Me (Me = CH3), and Si-H, respectively. It was found that the energy needed to break N-Me at 80.6 kcal·mol-1 is lower than the ones for Si-N and Si-H, both at 87.4 kcal·mol-1. When compared with tris(dimethylamino)silane (TrDMAS), it has been shown that the three bonds of N-Me, Si-N, and Si-H in BDMAS can be ruptured more easily, suggesting that BDMAS could be a more efficient precursor gas than TrDMAS. Upon decomposition, BDMAS tends to form methyleneimine and silanimine species, where four methyleneimine species and three silanimine species were produced. From the investigation of the effect of temperature on the kinetic and thermodynamic competition of different decomposition pathways, it has been demonstrated that the concerted formation of N-dimethylaminosilyl methyleneimine (H2C═N-SiH2NMe2) by the elimination of CH4 from BDMAS is the most kinetically and thermodynamically favored pathway in the whole temperature range from 0 K (ΔH0‡ = 62.7 kcal·mol-1 and ΔH0 = 7.7 kcal·mol-1) up to 2673 K. In addition, lower temperatures favor the production of N-methyl methyleneimime (H2C═NMe), whereas high temperatures promote the formation of N-methylsilanimine (H2Si = NMe) and 1-dimethylamino-N-methylsilanimine (Me2NSi = NMe).

How community pharmacists envision using pharmacogenomic data: A qualitative analysis.

BACKGROUND: Nearly 300 medications contain pharmacogenomic information in their labeling approved by the U.S. Food and Drug Administration. As this number continues to grow, community pharmacists will be called on to use available pharmacogenomic data at the point of dispensing. OBJECTIVE: This qualitative study aimed to describe how pharmacists envision the integration of pharmacogenomic data into the current workflows of community pharmacy practice. METHODS: Community pharmacists from a regional supermarket chain pharmacy in the greater Pittsburgh area were interviewed using a semistructured interview guide. Participating pharmacists were presented with 3 clinical scenarios, followed by questions, to gain insight into how they envisioned the integration of pharmacogenomic data into community pharmacy workflow. The interview transcriptions were transcribed and coded. The content was analyzed to deduce the final themes. Supporting quotes were selected to illustrate each theme. RESULTS: Ten community pharmacists from 3 different pharmacy locations participated in the study. A thematic analysis produced 6 themes: (1) integrating pharmacogenomic data into the dispensing software, (2) receiving an alert for pharmacogenomic information within the dispensing software, (3) accessing pharmacogenomic clinical guidelines to guide drug-decision-making, (4) contacting the prescriber by adding a task to the call queue, (5) placing a mandatory counseling alert on medications that were adjusted using pharmacogenomic data, and (6) counseling the patient on the first refill of a medication that was adjusted using pharmacogenomic data. CONCLUSION: This study describes how pharmacists envisioned the integration of pharmacogenomic data into community pharmacy workflow. The participants sought the integration of pharmacogenomic data into existing dispensing software, alerts for actionable prescribing changes using patient-specific pharmacogenomic data when available, and access to clinical decision support. In addition, the participants preferred to engage prescribers and receive alerts to counsel patients at prescription pick-up. These findings are key to integrating pharmacogenomic data into community pharmacy practice.

Evaluating the extent of reusability of CYP2C19 genotype data among patients genotyped for antiplatelet therapy selection.

PURPOSE: Genotype-guided antiplatelet therapy is increasingly being incorporated into clinical care. The purpose of this study is to determine the extent to which patients initially genotyped for CYP2C19 to guide antiplatelet therapy were prescribed additional medications affected by CYP2C19. METHODS: We assembled a cohort of patients from eight sites performingCYP2C19 genotyping to inform antiplatelet therapy. Medication orders were evaluated from time of genotyping through one year. The primary endpoint was the proportion of patients prescribed two or more CYP2C19 substrates. Secondary endpoints were the proportion of patients with a drug-genotype interaction and time to receiving a CYP2C19 substrate. RESULTS: Nine thousand one hundred ninety-one genotyped patients (17% nonwhite) with a mean age of 68 ± 3 years were evaluated; 4701 (51%) of patients received two or more CYP2C19 substrates and 3835 (42%) of patients had a drug-genotype interaction. The average time between genotyping and CYP2C19 substrate other than antiplatelet therapy was 25 ± 10 days. CONCLUSIONS: More than half of patients genotyped in the setting of CYP2C19-guided antiplatelet therapy received another medication impacted by CYP2C19 in the following year. Given that genotype is stable for a patient's lifetime, this finding has implications for cost effectiveness, patient care, and treatment outcomes beyond the indication for which it was originally performed.

Correction: Evaluating the extent of reusability of CYP2C19 genotype data among patients genotyped for antiplatelet therapy selection.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Evaluation of Potential Racial Disparities in CYP2C19-Guided P2Y12 Inhibitor Prescribing After Percutaneous Coronary Intervention.

Black patients suffer worse outcomes after percutaneous coronary intervention (PCI) than White patients. Inequities in antiplatelet prescribing may contribute to this health disparity. We compared P2Y12 inhibitor prescribing by race following CYP2C19 genotyping to guide antiplatelet therapy selection after PCI. Patients from 9 sites that performed clinical CYP2C19 genotyping after PCI were included. Alternative therapy (e.g., prasugrel or ticagrelor) was recommended for CYP2C19 no-function allele carriers, in whom clopidogrel is predicted to be less effective. The primary outcome was choice of P2Y12 inhibitor (clopidogrel vs. alternative therapy) based on genotype. Of 3,342 patients included, 2,448 (73%) were White, and 659 (20%) were Black. More Black than White patients had a no-function allele (34.3% vs. 29.7%, P = 0.024). At hospital discharge following PCI, 44.2% of Black and 44.0% of White no-function allele carriers were prescribed alternative therapy. At the time of the last follow-up within 12 months, numerically fewer Black (51.8%) than White (56.7%) no-function allele carriers were prescribed alternative therapy (P = 0.190). However, the difference was not significant after accounting for other factors associated with P2Y12 inhibitor selection (odds ratio 0.79, 95% confidence interval 0.58-1.08). Alternative therapy use did not differ between Black (14.3%) and White (16.7%) patients without a no-function allele (P = 0.232). Among real-world patients who received CYP2C19 testing after PCI, P2Y12 inhibitor prescribing rates did not differ between Black and White patients. Our data suggest an absence of racial disparity in genotype-guided antiplatelet prescribing among patients receiving CYP2C19 testing.

Clinical Pharmacogenetics Implementation Consortium (CPIC) Guideline for CYP2D6, CYP2C19, CYP2B6, SLC6A4, and HTR2A Genotypes and Serotonin Reuptake Inhibitor Antidepressants.

Serotonin reuptake inhibitor antidepressants, including selective serotonin reuptake inhibitors (SSRIs; i.e., citalopram, escitalopram, fluoxetine, fluvoxamine, paroxetine, and sertraline), serotonin and norepinephrine reuptake inhibitors (i.e., desvenlafaxine, duloxetine, levomilnacipran, milnacipran, and venlafaxine), and serotonin modulators with SSRI-like properties (i.e., vilazodone and vortioxetine) are primary pharmacologic treatments for major depressive and anxiety disorders. Genetic variation in CYP2D6, CYP2C19, and CYP2B6 influences the metabolism of many of these antidepressants, which may potentially affect dosing, efficacy, and tolerability. In addition, the pharmacodynamic genes SLC6A4 (serotonin transporter) and HTR2A (serotonin-2A receptor) have been examined in relation to efficacy and side effect profiles of these drugs. This guideline updates and expands the 2015 Clinical Pharmacogenetics Implementation Consortium (CPIC) guideline for CYP2D6 and CYP2C19 genotypes and SSRI dosing and summarizes the impact of CYP2D6, CYP2C19, CYP2B6, SLC6A4, and HTR2A genotypes on antidepressant dosing, efficacy, and tolerability. We provide recommendations for using CYP2D6, CYP2C19, and CYP2B6 genotype results to help inform prescribing these antidepressants and describe the existing data for SLC6A4 and HTR2A, which do not support their clinical use in antidepressant prescribing.

High-Dimensional Neural Network Potential for Liquid Electrolyte Simulations.

Liquid electrolytes are one of the most important components of Li-ion batteries, which are a critical technology of the modern world. However, we still lack the computational tools required to accurately calculate key properties of these materials (viscosity and ionic diffusivity) from first principles necessary to support improved designs. In this work, we report a machine learning-based force field for liquid electrolyte simulations, which bridges the gap between the accuracy of range-separated hybrid density functional theory and the efficiency of classical force fields. Predictions of material properties made with this force field are quantitatively accurate compared to experimental data. Our model uses the QRNN deep neural network architecture, which includes both long-range interactions and global charge equilibration. The training data set is composed solely of non-periodic density functional theory (DFT), allowing the practical use of an accurate theory (here, ωB97X-D3BJ/def2-TZVPD), which would be prohibitively expensive for generating large data sets with periodic DFT. In this report, we focus on seven common carbonates and LiPF6, but this methodology has very few assumptions and can be readily applied to any liquid electrolyte system. This provides a promising path forward for large-scale atomistic modeling of many important battery chemistries.

Antiplatelet Therapy and Bleeding Outcomes With CYP2C19 Genotyping.

PURPOSE: The impact of antiplatelet therapy with availability of CYP2C19 genotyping on bleeding in a real-world setting has not been extensively studied. METHODS: Prospective, single-center, cohort study conducted between December 2015 and October 2019 with 1-year follow-up. Patients underwent percutaneous coronary intervention (PCI), CYP2C19 genotyping, and received P2Y12 inhibitor therapy. The primary outcome was time to first bleed of any severity using Bleeding Academic Research Consortium criteria. Secondary outcomes included time to first major bleed and rates of antiplatelet switching. RESULTS: The primary outcome occurred in 697 of 2091 (33%) participants at a median of 15 days. Major bleeding occurred in 176 (8%) of patients. Compared to clopidogrel, treatment with ticagrelor or prasugrel was associated with increased risk of any bleeding (adjusted HR [aHR] 2.04, 95% CI 1.69-2.46). For patients without CYP2C19 no function alleles, treatment with prasugrel or ticagrelor was associated with increased risk of any bleeding (aHR 2.31, 95% CI 1.83-2.90). Similar associations were observed for major bleeding. No difference in ischemic events was observed. Among patients discharged on ticagrelor or prasugrel, 199 (36%) were de-escalated to clopidogrel within 1 year. De-escalation was more likely after a bleed if patients did not have a no function allele (35.9% vs 19.1%; P = .02). CONCLUSION: Bleeding is common in post-PCI patients on antiplatelet therapy. Patients on high potency agents had higher bleeding risk in the population at-large and in non-carriers of CYP2C19 no function alleles. Genotype-guided antiplatelet de-escalation should be further explored in prospective studies.

Pharmacogenetics: A Precision Medicine Approach to Combatting the Opioid Epidemic.

Ineffective pain control is the most commonly cited reason for misuse of prescription opioids and is influenced by genetics. In particular, the gene encoding the CYP2D6 enzyme, which metabolizes some of the most commonly prescribed opioids (e.g., tramadol, hydrocodone) to their more potent forms, is highly polymorphic and can lead to reduced concentrations of the active metabolites and decreased opioid effectiveness. Consideration of the CYP2D6 genotype may allow for predicting opioid response and identifying patients who are likely to respond well to lower potency opioids as well as those who may derive greater pain relief from non-opioid analgesics versus certain opioids. There is emerging evidence that a CYP2D6-guided approach to pain management improves pain control and reduces opioid consumption and thus may be a promising means for combating opioid misuse. Clinical practice guidelines are available for select opioids and other analgesics to support medication and dose selection based on pharmacogenetic data. This article describes the evidence supporting genotype-guided pain management as a means of improving pain control and reducing opioid misuse and clinical recommendations for genotype-guided analgesic prescribing. In addition, a "how to" guide using patient case examples is provided to demystify the process for implementing pharmacogenetics-guided pain management in order to optimize analgesia and minimize adverse effects. Optimizing pain management through genotype-guided approaches may ultimately provide safer and more effective therapy for pain control while decreasing the risk for opioid misuse.

Transferable Neural Network Potential Energy Surfaces for Closed-Shell Organic Molecules: Extension to Ions.

Transferable high dimensional neural network potentials (HDNNPs) have shown great promise as an avenue to increase the accuracy and domain of applicability of existing atomistic force fields for organic systems relevant to life science. We have previously reported such a potential (Schrödinger-ANI) that has broad coverage of druglike molecules. We extend that work here to cover ionic and zwitterionic druglike molecules expected to be relevant to drug discovery research activities. We report a novel HDNNP architecture, which we call QRNN, that predicts atomic charges and uses these charges as descriptors in an energy model that delivers conformational energies within chemical accuracy when measured against the reference theory it is trained to. Further, we find that delta learning based on a semiempirical level of theory approximately halves the errors. We test the models on torsion energy profiles, relative conformational energies, geometric parameters, and relative tautomer errors.

CYP2C19 Genotype-Guided Antiplatelet Therapy After Percutaneous Coronary Intervention in Diverse Clinical Settings.

Background Studies have demonstrated increased risk of major atherothrombotic events in CYP2C19 loss-of-function (LOF) variant carriers versus non-carriers treated with clopidogrel after percutaneous coronary intervention (PCI). We sought to evaluate real-world outcomes with the clinical implementation of CYP2C19-guided antiplatelet therapy after PCI. Methods and Results Data from 9 medical centers where genotyping was performed in the setting of PCI were included. Alternative therapy with prasugrel or ticagrelor was recommended for patients with a CYP2C19 LOF variant. The primary outcome was the composite of major atherothrombotic events (all-cause death, myocardial infarction, ischemic stroke, stent thrombosis, or hospitalization for unstable angina) within 12 months following PCI. Moderate or severe/life-threatening bleeding within 12 months was a secondary outcome. Among 3342 patients, 1032 (31%) were LOF carriers, of whom 571/1032 (55%) were treated with alternative therapy. In LOF carriers, the rate of major atherothrombotic events was lower in patients treated with alternative therapy versus clopidogrel (adjusted HR, 0.56; 95% CI 0.39-0.82). In those without a LOF allele, no difference was observed (adjusted HR, 1.07; 95% CI 0.71-1.60). There was no difference in bleeding with alternative therapy versus clopidogrel in either LOF carriers or those without a LOF allele. Conclusions Real-world data demonstrate lower atherothrombotic risk in CYP2C19 LOF carriers treated with alternative therapy versus clopidogrel and similar risk in those without a LOF allele treated with clopidogrel or alternative therapy. These data suggest that PCI patients treated with clopidogrel should undergo genotyping so that CYP2C19 LOF carriers can be identified and treated with alternative therapy.

Projected Utility of Pharmacogenomic Testing Among Individuals Hospitalized With COVID-19: A Retrospective Multicenter Study in the United States.

Many academic institutions are collecting blood samples from patients seeking treatment for coronavirus disease 2019 (COVID-19) to build research biorepositories. It may be feasible to extract pharmacogenomic (PGx) information from biorepositories for clinical use. We sought to characterize the potential value of multigene PGx testing among individuals hospitalized with COVID-19 in the United States. We performed a cross-sectional analysis of electronic health records from consecutive individuals hospitalized with COVID-19 at a large, urban academic health system. We characterized medication orders, focusing on medications with actionable PGx guidance related to 14 commonly assayed genes (CYP2C19, CYP2C9, CYP2D6, CYP3A5, DPYD, G6PD, HLA-A, HLA-B, IFNL3, NUDT15, SLCO1B1, TPMT, UGT1A1, and VKORC1). A simulation analysis combined medication data with population phenotype frequencies to estimate how many treatment modifications would be enabled if multigene PGx results were available. Sixty-four unique medications with PGx guidance were ordered at least once in the cohort (n = 1,852, mean age 60.1 years). Nearly nine in 10 individuals (89.7%) had at least one order for a medication with PGx guidance and 427 patients (23.1%) had orders for 4 or more actionable medications. Using a simulation, we estimated that 17 treatment modifications per 100 patients would be enabled if PGx results were available. The genes CYP2D6 and CYP2C19 were responsible for the majority of treatment modifications, and the medications most often affected were ondansetron, oxycodone, and clopidogrel. PGx results would be relevant for nearly all individuals hospitalized with COVID-19 and would provide the opportunity to improve clinical care.

Genome-wide association study accounting for anticholinergic burden to examine cognitive dysfunction in psychotic disorders.

Identifying genetic contributors to cognitive impairments in psychosis-spectrum disorders can advance understanding of disease pathophysiology. Although CNS medications are known to affect cognitive performance, they are often not accounted for in genetic association studies. In this study, we performed a genome-wide association study (GWAS) of global cognitive performance, measured as composite z-scores from the Brief Assessment of Cognition in Schizophrenia (BACS), in persons with psychotic disorders and controls (N = 817; 682 cases and 135 controls) from the Bipolar-Schizophrenia Network on Intermediate Phenotypes (B-SNIP) study. Analyses accounting for anticholinergic exposures from both psychiatric and non-psychiatric medications revealed five significantly associated variants located at the chromosome 3p21.1 locus, with the top SNP rs1076425 in the inter-alpha-trypsin inhibitor heavy chain 1 (ITIH1) gene (P = 3.25×E-9). The inclusion of anticholinergic burden improved association models (P < 0.001) and the number of significant SNPs identified. The effect sizes and direction of effect of the top variants remained consistent when investigating findings within individuals receiving specific antipsychotic drugs and after accounting for antipsychotic dose. These associations were replicated in a separate study sample of untreated first-episode psychosis. The chromosome 3p21.1 locus was previously reported to have association with the risk for psychotic disorders and cognitive performance in healthy individuals. Our findings suggest that this region may be a psychosis risk locus that is associated with cognitive mechanisms. Our data highlight the general point that the inclusion of medication exposure information may improve the detection of gene-cognition associations in psychiatric genetic research.

Impact of the CYP2C19*17 Allele on Outcomes in Patients Receiving Genotype-Guided Antiplatelet Therapy After Percutaneous Coronary Intervention.

Genotyping for CYP2C19 no function alleles to guide antiplatelet therapy after percutaneous coronary intervention (PCI) improves clinical outcomes. Although results for the increased function CYP2C19*17 allele are also reported, its clinical relevance in this setting remains unclear. A collaboration across nine sites examined antiplatelet therapy prescribing and clinical outcomes in 3,342 patients after implementation of CYP2C19-guided antiplatelet therapy. Risk of major atherothrombotic and bleeding events over 12 months after PCI were compared across cytochrome P450 2C19 isozyme (CYP2C19) metabolizer phenotype and antiplatelet therapy groups by proportional hazards regression. Clopidogrel was prescribed to a similar proportion of CYP2C19 normal (84.5%), rapid (82.9%), and ultrarapid metabolizers (80.6%) (P = 0.360). Clopidogrel-treated normal metabolizers (20.4 events/100 patient-years; adjusted hazard ratio (HR) 1.00, 95% confidence interval (CI), 0.75-1.33, P = 0.993) and clopidogrel-treated rapid or ultrarapid metabolizers (19.1 events/100 patient-years; adjusted HR 0.95, 95% CI, 0.69-1.30, P = 0.734) exhibited no difference in major atherothrombotic events compared with patients treated with prasugrel or ticagrelor (17.6 events/100 patient-years). In contrast, clopidogrel-treated intermediate and poor metabolizers exhibited significantly higher atherothrombotic event risk compared with prasugrel/ticagrelor-treated patients (adjusted HR 1.56, 95% CI, 1.12-2.16, P = 0.008). When comparing clopidogrel-treated rapid or ultrarapid metabolizers to normal metabolizers, no difference in atherothrombotic (adjusted HR 0.97, 95% CI, 0.73-1.29, P = 0.808) or bleeding events (adjusted HR 1.34, 95% CI, 0.83-2.17, P = 0.224) were observed. In a real-world setting of genotype-guided antiplatelet therapy, the CYP2C19*17 allele did not significantly impact post-PCI prescribing decisions or clinical outcomes. These results suggest the CYP2C19 *1/*17 and *17/*17 genotypes have limited clinical utility to guide antiplatelet therapy after PCI.

Risk Factors for Cardiovascular Events in Patients on Antidementia Medications.

OBJECTIVE: To identify characteristics associated with an increased risk of cardiovascular events in patients diagnosed with Alzheimer disease (AD) and treated with antidementia medications. METHODS: Demographics, diagnoses, and medication usage of 30 433 Medicare patients were analyzed using 2006 to 2013 claims data and a combined model of screening, ranking and stepwise logistic regressions to evaluate factors associated with composite outcomes of 6 cardiovascular events. RESULTS: Incidence rate of at least 1 cardiovascular event was 25.1%. Fifty-five factors were identified from the 10 381 candidate variables by the combined model with a c-statistic of 67% and an accuracy of 75%. Factors associated with increased risk of cardiovascular events include history of heart rhythm disorders, alteration of consciousness (odds ratio [OR]: 1.25; 95% confidence interval [CI]: 1.14-1.36), and usage of ß-blockers (OR: 1.19; 95% CI: 1.13-1.27). CONCLUSIONS: Clinicians should consider the increased risk of cardiovascular events in patients with AD with heart rhythm disorders and on ß-blockers.

Effect of Selective Serotonin Reuptake Inhibitors on Cardiovascular Outcomes After Percutaneous Coronary Intervention: A Retrospective Cohort Study.

BACKGROUND: Depression and coronary artery disease (CAD) are leading causes of death and disability and commonly co-occur. Different antidepressant classes have similar efficacy for depressed patients with CAD, but cardiovascular implications are unclear. Selective serotonin reuptake inhibitors (SSRIs) and mirtazapine are first-line options for depressed patients with CAD. SSRIs, but not mirtazapine, have known antiplatelet effects. Whether this affects risk of bleeding and major adverse cardiac events (MACE) in patients requiring dual antiplatelet therapy (DAPT) after percutaneous coronary intervention (PCI) is unknown. OBJECTIVE: The aim of this analysis is to examine the impact of SSRI treatment on the co-primary endpoints of composite MACE (death, myocardial infarction, or stroke) and composite bleeding events in patients treated with clopidogrel-based DAPT after PCI. METHODS: We conducted a retrospective study with co-primary endpoints of bleeding and MACE within 1 year of PCI. Three groups were compared: SSRI patients, mirtazapine patients, and patients on neither agent. Mirtazapine acted as a comparator to control for depression, for which diagnosis coding was inadequate. Time-to-event analyses were performed with Kaplan-Meier estimators and adjusted analyses utilized Cox proportional hazards. There were 6874 (820 SSRI, 55 mirtazapine, 5999 neither) patients included. RESULTS: SSRI patients had lower MACE risk than mirtazapine patients (hazard ratio [HR] 0.61, 95% confidence interval [CI] 0.38-0.97, p = 0.036) but higher MACE risk than patients on neither agent (HR 1.21, 95% CI 1.02-1.43, p = 0.030) in adjusted analyses. No significant differences were associated with bleeding risk (SSRI vs. neither adjusted HR 1.07, 95% CI 0.93-1.24, p = 0.36). CONCLUSION: SSRI use was associated with a significant decrease in MACE rates compared with patients receiving mirtazapine. Bleeding risk was not affected by either antidepressant treatment. SSRIs may have cardioprotective benefits compared with mirtazapine.