Genetic QT Score and Sleep Apnea as Predictors of Sudden Cardiac Death in the UK Biobank.

Introduction: The goal of this study was to evaluate the association between a polygenic risk score (PRS) for QT prolongation (QTc-PRS), QTc intervals and mortality in patients enrolled in the UK Biobank with and without sleep apnea. Methods: The QTc-PRS was calculated using allele copy number and previously reported effect estimates for each single nuclear polymorphism SNP. Competing-risk regression models adjusting for age, sex, BMI, QT prolonging medication, race, and comorbid cardiovascular conditions were used for sudden cardiac death (SCD) analyses. Results: 500,584 participants were evaluated (56.5 ±8 years, 54% women, 1.4% diagnosed with sleep apnea). A higher QTc-PRS was independently associated with the increased QTc interval duration (p<0.0001). The mean QTc for the top QTc-PRS quintile was 15 msec longer than the bottom quintile (p<0.001). Sleep apnea was found to be an effect modifier in the relationship between QTc-PRS and SCD. The adjusted HR per 5-unit change in QTc-PRS for SCD was 1.64 (95% CI 1.16 - 2.31, p=0.005) among those with sleep apnea and 1.04 (95% CI 0.95 - 1.14, p=0.44) among those without sleep apnea (p for interaction =0.01). Black participants with sleep apnea had significantly elevated adjusted risk of SCD compared to White participants (HR=9.6, 95% CI 1.24 - 74, p=0.03). Conclusion: In the UK Biobank population, the QTc-PRS was associated with SCD among participants with sleep apnea but not among those without sleep apnea, indicating that sleep apnea is a significant modifier of the genetic risk. Black participants with sleep apnea had a particularly high risk of SCD.

A QTc risk score in patients with obstructive sleep apnea.

INTRODUCTION: Patients with obstructive sleep apnea (OSA) are at risk for QTc prolongation, a known risk factor for increased mortality. The pro-QTc score can help identify individuals at increased risk for mortality associated with increased QTc however, it has not been evaluated in patients with OSA. The goal of this study was to evaluate the pro-QTc score in patients with OSA. METHODS: Medical records of patients undergoing a sleep study at our sleep center from February 2012 to August 2020 were analyzed. Presence or absence of OSA was determined by polysomnography. The pro-QTc score was calculated with 1 point assigned for each of the following: female sex, QT-prolonging diagnoses and conditions, QT-prolonging electrolyte abnormalities, and medications with known risk for QT-prolongation. Mortality was determined from the electronic medical record of an integrated healthcare system. RESULTS: There were 2246 patients (age 58 ± 15 years, 54% male, 82 dead) with OSA and 421 patients (age 54 ± 18 years, 43% male, 18 dead) without OSA. Of those with OSA, 1628 (72.5%) had at least one risk factor for QTc prolongation. A higher pro-QTc score was associated with greater mortality in patients with OSA (HR 1.48 per pro-QTc score, p < 0.001, 95% CI 1.3-1.7) but not in patients without OSA (HR 1.25 per pro-QTc score, p = 0.30, 95% CI 0.82-1.9), after adjusting for age, body mass index (BMI), and smoking status. CONCLUSION: In patients with OSA, a higher pro-QTc score was associated with greater mortality.

Relationship between a risk score for QT interval prolongation and mortality across rural and urban inpatient facilities.

OBJECTIVES: To evaluate the relationship between a modified Tisdale QTc-risk score (QTc-RS) and inpatient mortality and length of stay in a broad inpatient population with an order for a medication with a known risk of torsades de pointes (TdP). BACKGROUND: Managing the risk of TdP is challenging due to the number of medications with known risk of TdP and the complexity of precipitating factors. A model to predict risk of mortality may be useful to guide treatment decisions. METHODS: This was a retrospective observational study using inpatient data from 28 healthcare facilities in the western United States. This risk score ranges from zero to 23 with weights applied to each risk factor based on a previous validation study. Logistic regression and a generalized linear model were performed to assess the relationship between QTc-RS and mortality and length of stay. RESULTS: Between April and December 2020, a QTc-RS was calculated for 92,383 hospitalized patients. Common risk factors were female (55.0%); age > 67 years (32.1%); and receiving a medication with known risk of TdP (24.5%). A total of 2770 (3%) patients died during their hospitalization. Relative to patients with QTc-RS < 7, the odds ratio for mortality was 4.80 (95%CI:4.42-5.21) for patients with QTc-RS = 7-10 and 11.51 (95%CI:10.23-12.94) for those with QTc-RS ≥ 11. Length of hospital stay increased by 0.7 day for every unit increase in the risk score (p < 0.0001). CONCLUSION: There is a strong relationship between increased mortality as well as longer duration of hospitalization with an increasing QTc-RS.

Clinician Responses to a Clinical Decision Support Advisory for High Risk of Torsades de Pointes.

Background Torsade de pointes (TdP) is a potentially fatal cardiac arrhythmia that is often drug induced. Clinical decision support (CDS) may help minimize TdP risk by guiding decision making in patients at risk. CDS has been shown to decrease prescribing of high-risk medications in patients at risk of TdP, but alerts are often ignored. Other risk-management options can potentially be incorporated in TdP risk CDS. Our goal was to evaluate actions clinicians take in response to a CDS advisory that uses a modified Tisdale QT risk score and presents management options that are easily selected (eg, single click). Methods and Results We implemented an inpatient TdP risk advisory systemwide across a large health care system comprising 30 hospitals. This CDS was programmed to appear when prescribers attempted ordering medications with a known risk of TdP in a patient with a QT risk score ≥12. The CDS displayed patient-specific information and offered relevant management options including canceling offending medications and ordering electrolyte replacement protocols or ECGs. We retrospectively studied the actions clinicians took within the advisory and separated by drug class. During an 8-month period, 7794 TdP risk advisories were issued. Antibiotics were the most frequent trigger of the advisory (n=2578, 33.1%). At least 1 action was taken within the advisory window for 2700 (34.6%) of the advisories. The most frequent action taken was ordering an ECG (n=1584, 20.3%). Incoming medication orders were canceled in 793 (10.2%) of the advisories. The frequency of each action taken varied by drug class (P<0.05 for all actions). Conclusions A modified Tisdale QT risk score-based CDS that offered relevant single-click management options yielded a high action/response rate. Actions taken by clinicians varied depending on the class of the medication that evoked the TdP risk advisory, but the most frequent was ordering an ECG.

Limited Genomics Training Among Physicians Remains a Barrier to Genomics-Based Implementation of Precision Medicine.

The field of precision medicine has undergone significant growth over the past 10 years. Despite increasing applications of clinical genetic and genomic testing, studies consistently report limited knowledge of genetics and genomics among healthcare providers. This study explored barriers to the implementation of precision medicine by surveying physicians working in a large academic medical center. We assessed prior training in genetics, use of genetic testing in the clinic, desire for additional resources in genetics and genomic medicine and perceived barriers to successful integration of precision medicine. Only 20% of respondents reported moderate or extensive training in genetics. Physicians with limited or no training in genetics were less likely to have ordered a genetic test for any purpose. Furthermore, 41% of physicians responded that their lack of training identifying appropriate genetic tests and how to interpret genetic testing results was the most significant barrier to ordering genetic testing for their patients. These findings suggest that future efforts to realize the promise of precision medicine should focus on the integration of training programs for non-genetics trained healthcare providers.

Clinician Satisfaction With Advanced Clinical Decision Support to Reduce the Risk of Torsades de Pointes.

OBJECTIVES: Clinical decision support (CDS) can potentially help clinicians identify and manage patients who are at risk for torsades de pointes (TdP). However, computer alerts are often ignored and might contribute to alert fatigue. The goals of this project were to create an advanced TdP CDS advisory that presents patient-specific, relevant information, including 1-click management options, and to determine clinician satisfaction with the CDS. METHODS: The advanced TdP CDS was developed and implemented across a health system comprising 29 hospitals. The advisory presents patient-specific information including relevant risk factors, laboratory values, and 1-click options to help manage the condition in high-risk patients. A short electronic survey was created to gather clinician feedback on the advisory. RESULTS: After implementation, an email invitation to complete the anonymous advisory-related survey was sent to 442 clinicians who received the advisory. Among the 38 respondents, feedback was generally positive, with 79% of respondents reporting that the advisory helps them care for their patients and 87% responding that alternative actions for them to consider were clearly specified. However, 46% of respondents indicated the alert appeared too frequently. CONCLUSIONS: Advanced TdP risk CDS that provides relevant, patient-specific information and 1-click management options can be generally viewed favorably by clinicians who receive the advisory.

Linking Technology to Address the Social and Medical Determinants of Health for Safe Medicines Use.

OBJECTIVES: Both social and medical factors can negatively affect health outcomes, especially in vulnerable populations. To address these 2 types of factors in a postdischarge population, 2 nonprofit organizations collaborated to combine their novel decision support programs and address the question: Could combined programs have greater potential for improved health outcomes? METHODS: HomeMeds, a social health program in which trained social services staff make home visits to vulnerable clients, was combined with MedSafety Scan, a medical health, clinical decision support tool. Data captured in the home visits were entered into the HomeMeds and MedSafety Scan programs to detect those patients at the greatest risk of adverse health outcomes because of medications. RESULTS: Patients (n = 108; mean age, 77 years; multiple comorbidities and LACE+ (length of stay, acuity, comorbidities, emergency department visits [hospital index]; score >29) received a postdischarge home visit by trained social services staff. The number of drugs reported as being taken was 10.4 ± 5.1 (range, 1-26), which was less than prescribed at discharge in 62% of patients (range, 1-8). Both programs detected a serious risk of medication-induced harm, mostly from different causes such as drug-drug interactions or for use not recommended in the elderly. CONCLUSIONS: Combined analysis of data from 2 novel decision support programs yielded complementary findings that together address both medical and social determinants of health. These have the potential to reduce medication-induced harm, costly rehospitalization, and/or emergency department visits and support the further evaluation of this combined approach in other vulnerable populations such as the seriously mentally ill, frail, those confined to home, opioid dependent, or otherwise impaired.

Assisted prescribing: Clinical decision support with MedSafety Scan now available.

Too often, adverse events due to prescription medications are a cause of death and disability. Many of these events could be prevented, but most efforts to do so have had limited success, mainly due to the challenges of having the information that is necessary for safe prescribing available at the time when prescriptions are being written. Hospital-based Clinical Decision Support (CDS) systems are being developed to manage this information, identify at- risk patients, and help mitigate their risk of medication-induced harm. AZCERT, a non-profit created in 1999 with federal funding has helped hospitals develop these systems and has released an internet-based CDS program to assist in the safe prescribing of medications. This CDS program, MedSafety Scan, can be customized for any clinical venue and is available as an open-source program for all healthcare providers at www.medsafetyscan.org.

Investigating the Impact of Gadolinium-Based Contrast Agents on the Corrected QT Interval.

Introduction The manufacturing labels for all currently marketed gadolinium-based MRI contrast agents describe adverse cardiac events reported during post-market use. The goal of this study was to determine prolongation of the rate-corrected QT interval occurs in the immediate setting after gadolinium-based MRI contrast agent injection. Methods This study enrolled adults scheduled to have a gadolinium-based MRI contrast agent injection as part of a diagnostic MRI. A single-lead electrocardiogram was recorded using the AliveCor Kardia® ECG (Mountain View, CA) device before and after injection. The rate-corrected QT interval was subsequently measured by two independent investigators. The QT interval was corrected for rate using the two most common formulas, originally cited by Bazett and Fridericia. These rate-corrected QT intervals from before and after gadolinium-based MRI contrast agent injection were compared using the Wilcoxon signed-rank test paired analysis. Results A total of 24 consenting adults had electrocardiogram that were free of motion artifact. The mean age of the final patient cohort was 59.4 years. There was an equal split of 12 men and 12 women. The mean pre-injection, rate-corrected QT interval, corrected using Bazett's formula, was 395 msec. The mean post-injection, rate-corrected QT interval, corrected using Bazett's formula, was 396 msec. The corrections using Fridericia's formula were 384 and 381 msec, respectively. There was no statistically significant change in Bazett-corrected QT interval (QTc-B) when pre-injection and post-injection values were directly compared. Discussion The results of the present investigation support the conclusion that gadolinium-based MRI contrast agents do not commonly affect rate-corrected QT interval in routine clinical use. While the frequency of rate-corrected QT interval prolongation might be overstated, the severity of adverse events is definitively not. A role for concomitant rate-corrected QT interval-prolonging drugs or unidentified rare factors such as genetic predisposition cannot be ruled out. The limitations of this study include its relatively small size and the implementation of a single-lead electrocardiogram to measure rate-corrected QT interval. Conclusion The present investigation revealed that significant rate-corrected QT interval prolongation, while previously reported in as many as 55% of patients after gadolinium-based MRI contrast agent injection, is not a common occurrence in the routine clinical setting.

Identification of populations likely to benefit from pharmacogenomic testing.

OBJECTIVES: Pharmacogenomic testing (PGX) implementation is rapidly expanding, including pre-emptive testing funded by health systems. PGX continues to develop an evidence base that it saves money and improves clinical outcomes. Identifying the potential impact of pre-emptive testing in specific populations may aid in the development of a business case. METHODS: We utilized a software tool that can evaluate patient drug lists and identified groups of patients most likely to benefit from implementation of a PGX testing program in a major medical system population. RESULTS: Medication lists were obtained for sixteen patient groups with a total of 82 613 patients. The percent of patients in each group with testing 'Recommended', 'Strongly recommended', or 'Required' ranged from 12.7% in the outpatient pediatric psychiatry group to 75.7% in the any adult inpatient age >50 years group. Some of the highest yield drugs identified were citalopram, simvastatin, escitalopram, metoprolol, clopidogrel, tramadol, and ondansetron. CONCLUSION: We demonstrate a significant number of patients in each group may have benefit, but targeting certain ones for pre-emptive testing may result in the initial highest yield for a health system.

Arrhythmogenic foods - A growing medical problem.

Arrhythmogenic ingredients in our diet such as mushrooms, licorice, toxic honey, liquid protein drinks, etc. have long been recognized as rare but important considerations in the differential diagnosis of arrhythmias. Anecdotal reports of torsades de pointes (TdP), arrhythmias and/or sudden death and small studies in normal subjects have suggested that simple ingredients such as grapefruit juice or ingredients in energy drinks marketed as dietary supplements could have direct arrhythmogenic actions, especially in patients with congenital long QT syndrome (cLQTS). Two recent studies that employed the industry-standard "thorough QT" trial design leave no doubt that grapefruit juice and some energy drinks can prolong the QTc interval and to exceed 500 msec. in some patients with cLQTS, a threshold known to signal imminent danger. These reports raise numerous clinically important questions such as which other patients may be at risk of arrhythmias. For example, patients with multiple clinical risk factors for TdP (hypokalemia, bradycardia, female sex, etc.) may be at risk from these and possibly other dietary ingredients ingested by millions of people each day. It is essential that further research evaluate the safety of these and similar food products and that vulnerable patients, especially those with cLQTS, be warned of this serious and emerging threat.

Summary of Torsades de Pointes (TdP) Reports Associated with Intravenous Drug Formulations Containing the Preservative Chlorobutanol.

INTRODUCTION: Drug-induced torsades de pointes (TdP) is a potentially lethal ventricular arrhythmia that is associated with drugs that prolong the QT interval on the electrocardiogram (ECG) due to their interference with the cardiac potassium current, IKR. Intravenous (IV) formulations of methadone have been associated with TdP and contain the preservative chlorobutanol, which, like methadone, blocks IKR. The combinations of chlorobutanol with methadone or terfenadine, another IKR blocker, produce synergistic IKR block. OBJECTIVE: The aim of this study was to examine and summarize the evidence available to address the question: what other IV drug formulations contain chlorobutanol and are they associated with TdP? METHODS: IV drug products containing the preservative chlorobutanol were identified by searching the websites DailyMed ( https://dailymed.nlm.nih.gov/dailymed/index.cfm ) and Drugs@FDA ( https://www.accessdata.fda.gov/scripts/cder/daf/ ). For each drug identified, PubMed and the FDA's Adverse Event Reporting System (FAERS) were searched for reports of TdP and/or QT prolongation and FAERS data were analyzed for disproportionality of reports. RESULTS: The search found nine drugs (methadone, epinephrine, papaverine, oxytocin, vasopressin, testosterone, estradiol, isoniazid, and desmopressin) that contain chlorobutanol 2.5 (n = 1) or 5.0 mg/mL. All nine drugs had reports of QT prolongation or TdP reported in FAERS and all but estradiol, testosterone, desmopressin, and isoniazid had reports of QT prolongation or TdP in PubMed. Two of the nine drugs (epinephrine and methadone) had positive signals (by disproportionality analysis) for TdP in FAERS (EB05 2.88 and 23.81, respectively) and four (methadone, epinephrine, papaverine, and vasopressin) were reported in published articles as the suspect drugs in cases of TdP. CONCLUSION: The pharmacologic profile of chlorobutanol (synergistic IKR block) and its association with reports of TdP and QT prolongation suggest the need for a full evaluation of its cardiac safety when used as a preservative in IV drug and vitamin formulations.

CredibleMeds.org: What does it offer?

Since the 1990s, when numerous non-cardiac drugs were first recognized to have the potential to prolong the QT interval and cause torsades de pointes (TdP), clinicians, drug regulators, drug developers, and clinical investigators have become aware of the complexities of assessing evidence and determining TdP causality for the many drugs being marketed or under development. To facilitate better understanding, the Arizona Center for Education and Research on Therapeutics, known as AZCERT, has developed the CredibleMeds.org website which includes QTdrugs, a listing of over 220 drugs placed in four risk categories based on their association with QT prolongation and TdP. Since the site was launched in 1999, it has become the single and most reliable source of information of its kind for patients, healthcare providers, and research scientists. Over 96,000 registered users rely on the QTdrugs database as their primary resource to inform their medication use, their prescribing or their clinical research into the impact of QT-prolonging drugs and drug-induced arrhythmias. The QTdrugs lists are increasingly used as the basis for clinical decision support systems in healthcare and for metrics of prescribing quality by healthcare insurers. A free smartphone app and an application program interface enable rapid and mobile access to the lists. Also, the CredibleMeds website offers numerous educational resources for patients, educators and healthcare providers that foster the safe use of medications.

Adverse Drug Event Causality Analysis (ADECA): A Process for Evaluating Evidence and Assigning Drugs to Risk Categories for Sudden Death.

Growing evidence indicates that many drugs have the ability to cause a potentially lethal cardiac arrhythmia, torsades de pointes (TdP). This necessitates the development of a compilation of drugs that have this potential toxicity. Such a list is helpful in identifying the etiology of TdP in patients taking multiple drugs and assists decision making by those caring for patients at high risk of TdP. The Arizona Center for Education and Research on Therapeutics (AZCERT) has developed a process to standardize the identification of drugs and place them in risk categories for their clinical ability to cause TdP and QT prolongation. AZCERT's Adverse Drug Event Causality Analysis (ADECA) utilizes 16 types of data drawn from four sources to compile an open-source knowledge base, QTdrugs, which is maintained on the CredibleMeds.org website. Because the evidence for most drugs is incomplete, the ADECA process is used to place drugs into one of three categories that represent different levels of certainty: known TdP risk, possible TdP risk, and conditional TdP risk. Each category has strict evidentiary requirements for clinical evidence of TdP and/or QT prolongation. These are described in this paper. Because evidence can evolve over time, the ADECA process includes the continuous gathering and analysis of newly emerging evidence to revise the lists. The QTdrugs lists have proven to be a valued, readily available, commercial influence-free resource for healthcare providers, patients, researchers, and authors of consensus guidelines for the safe use of medicines.

Coupling Data Mining and Laboratory Experiments to Discover Drug Interactions Causing QT Prolongation.

BACKGROUND: QT interval-prolonging drug-drug interactions (QT-DDIs) may increase the risk of life-threatening arrhythmia. Despite guidelines for testing from regulatory agencies, these interactions are usually discovered after drugs are marketed and may go undiscovered for years. OBJECTIVES: Using a combination of adverse event reports, electronic health records (EHR), and laboratory experiments, the goal of this study was to develop a data-driven pipeline for discovering QT-DDIs. METHODS: 1.8 million adverse event reports were mined for signals indicating a QT-DDI. Using 1.6 million electrocardiogram results from 380,000 patients in our institutional EHR, these putative interactions were either refuted or corroborated. In the laboratory, we used patch-clamp electrophysiology to measure the human ether-à-go-go-related gene (hERG) channel block (the primary mechanism by which drugs prolong the QT interval) to evaluate our top candidate. RESULTS: Both direct and indirect signals in the adverse event reports provided evidence that the combination of ceftriaxone (a cephalosporin antibiotic) and lansoprazole (a proton-pump inhibitor) will prolong the QT interval. In the EHR, we found that patients taking both ceftriaxone and lansoprazole had significantly longer QTc intervals (up to 12 ms in white men) and were 1.4 times more likely to have a QTc interval above 500 ms. In the laboratory, we found that, in combination and at clinically relevant concentrations, these drugs blocked the hERG channel. As a negative control, we evaluated the combination of lansoprazole and cefuroxime (another cephalosporin), which lacked evidence of an interaction in the adverse event reports. We found no significant effect of this pair in either the EHR or in the electrophysiology experiments. Class effect analyses suggested this interaction was specific to lansoprazole combined with ceftriaxone but not with other cephalosporins. CONCLUSIONS: Coupling data mining and laboratory experiments is an efficient method for identifying QT-DDIs. Combination therapy of ceftriaxone and lansoprazole is associated with increased risk of acquired long QT syndrome.

Predicting the Unpredictable: Drug-Induced QT Prolongation and Torsades de Pointes.

Drug-induced long QT syndrome (diLQTS) and congenital LQTS (cLQTS) share many features, and both syndromes can result in life-threatening torsades de pointes (TdP). Our understanding of their mechanistic and genetic similarities has led to their improved clinical management. However, our inability to prevent diLQTS has resulted in removal of many medicines from the market and from development. Genetic and clinical risk factors for diLQTS and TdP are well known and raise the possibility of TdP prevention. Clinical decision support systems (CDSS) can scan the patient's electronic health records for clinical risk factors predictive of diLQTS and warn when a drug that can cause TdP is prescribed. CDSS have reduced prescriptions of QT-prolonging drugs, but these relatively small changes lack the power to reduce TdP. The growing genetic evidence linking diLQTS to cLQTS suggests that prevention of TdP in the future may require inclusion of both genetic and clinical predictors into CDSS.