QT-prolonging Medications Research Articles

The Impact of QT-Prolonging Medications and Drug-Drug Interactions on QTc Interval Prolongation in Hospitalized Patients: A Case-Crossover Study.

Researchers have studied potential corrected QT interval (QTc) prolongation from drug-drug interactions (DDIs), raising unresolved questions about their real-world impact. This retrospective case-crossover study investigated the effects of QT-prolonging drugs and DDIs on QTc prolongation in hospitalized patients aged 45 years and above. The cohort comprised patients who had multiple hospitalizations and developed QTc prolongation (QTc > 500 ms or an increase of >60 ms from baseline) at least 24 hours after admission between 2011 and 2019. Conditional logistic regression compared drug exposure between hospitalizations with QTc prolongation (case window) and those without (reference window). Among 2,276 patients (mean age 71; 43.8% female), the use of QT-prolonging drugs significantly increased the risk of QTc prolongation (odds ratio: 2.42 (95% confidence interval: 1.95-3.02)). The risk was higher with drugs of "known risks" (OR: 3.78 (2.91-4.90)) and "conditional risk" (OR: 2.08 (1.65-2.62)). DDIs, particularly involving multiple "known risk" drugs (OR: 7.86 (4.96-12.45)), strong cytochrome P450 enzyme inhibitors (OR: 5.57 (2.75-11.30)), or the concurrent use of ≥4 QT-prolonging drugs with any risk (OR: 5.28 (3.96-7.03)) substantially increased the risk. Cautious prescribing for patients with multiple risk factors is important to minimize the likelihood of QTc prolongation. However, when considering enhanced monitoring or drug choices, it is crucial to carefully evaluate the overall risk of QT prolongation against the benefits of treatment to ensure optimal patient care.

Impact of Azithromycin on the Predisposition to Cardiac Arrhythmias in Adult Patients: A Systematic Review

Background: Azithromycin is a macrolide antibiotic that can lead to QT interval prolongation, which may trigger ventricular tachycardia, also known as torsades de pointes (TdP), the most common cardiac arrhythmia associated with these drugs. All macrolides are linked to QTc interval prolongation, with apparently higher risk with erythromycin and clarithromycin compared to azithromycin. Macrolides can extend QT and QTc intervals and cause cardiac arrhythmias, including TdP, ventricular tachycardia, and ventricular fibrillation, through their affinity for binding to the delayed rectifier potassium channel, IKr, inducing QT prolongation and risk of TdP. However, it is crucial to assess the risk-benefit ratio of prescribing azithromycin, especially in patients with preexisting cardiovascular disease or taking concomitant medications that prolong the QT interval. Objectives: The aim of this study is to determine whether azithromycin is genuinely associated with the occurrence of ventricular arrhythmias in adult patients. Materials and Methods: This systematic review is based on meticulous searching across Medline and Google Scholar databases, analysis of publications, and synthesis of available evidence regarding the risk of arrhythmias with the use of azithromycin. Results: We reviewed 6 articles that met the criteria, including 20.510.653 patients and 66 articles. While some studies suggest an increased risk of ventricular arrhythmias in certain subgroups of patients, others have not found a significant association between azithromycin and these arrhythmias. These discrepancies could be attributed to differences in the definition of arrhythmias, the duration of follow-up, or the characteristics of the groups of patients evaluated. The results point toward the need for a more thorough risk assessment before initiating this antibiotic in adult patients, especially those with known cardiovascular risk factors or those with a history of heart disease. Several risk factors, such as hypokalemia, pre-existing heart conditions, and concomitant use of other QT-prolonging medications, have been identified as increasing vulnerability to macrolide-induced arrhythmias. Conclusion: The results of the systematic review and cohort studies analyzed consistently suggest an association between the use of azithromycin and an increased risk of developing ventricular arrhythmias. This risk appears to be most evident in the elderly, with different studies showing variations in the magnitude of the risk. It is crucial to evaluate the risks and benefits of these antibiotics in each clinical situation, considering the information provided by observational studies and systematic reviews

QT-prolonging medications commonly prescribed in patients on dialysis

QT-prolonging medications commonly prescribed in patients on dialysis

QTNet: Predicting Drug-Induced QT Prolongation With Artificial Intelligence–Enabled Electrocardiograms

BackgroundPrediction of drug-induced long QT syndrome (diLQTS) is of critical importance given its association with torsades de pointes. There is no reliable method for the outpatient prediction of diLQTS. ObjectivesThis study sought to evaluate the use of a convolutional neural network (CNN) applied to electrocardiograms (ECGs) to predict diLQTS in an outpatient population. MethodsWe identified all adult outpatients newly prescribed a QT-prolonging medication between January 1, 2003, and March 31, 2022, who had a 12-lead sinus ECG in the preceding 6 months. Using risk factor data and the ECG signal as inputs, the CNN QTNet was implemented in TensorFlow to predict diLQTS. ResultsModels were evaluated in a held-out test dataset of 44,386 patients (57% female) with a median age of 62 years. Compared with 3 other models relying on risk factors or ECG signal or baseline QTc alone, QTNet achieved the best (P < 0.001) performance with a mean area under the curve of 0.802 (95% CI: 0.786-0.818). In a survival analysis, QTNet also had the highest inverse probability of censorship–weighted area under the receiver-operating characteristic curve at day 2 (0.875; 95% CI: 0.848-0.904) and up to 6 months. In a subgroup analysis, QTNet performed best among males and patients ≤50 years or with baseline QTc <450 ms. In an external validation cohort of solely suburban outpatient practices, QTNet similarly maintained the highest predictive performance. ConclusionsAn ECG-based CNN can accurately predict diLQTS in the outpatient setting while maintaining its predictive performance over time. In the outpatient setting, our model could identify higher-risk individuals who would benefit from closer monitoring.

Prescription and Dispensation of QT-Prolonging Medications in Individuals Receiving Hemodialysis

Individuals with dialysis-dependent kidney failure have numerous risk factors for medication-related adverse events, including receipt of care by multiple clinicians and initiation of some QT-prolonging medications with known risk of torsades de pointes (TdP), which is associated with higher risk of sudden cardiac death. Little is known about the prescription and dispensation patterns of QT-prolonging medications among people receiving dialysis, hindering efforts to reduce drug-related harm from these and other medications in this high-risk population. To examine prescription and dispensation patterns of QT-prolonging medications with known TdP risk and selected interacting medications prescribed to individuals receiving hemodialysis. This cross-sectional study included patients 60 years or older who were enrolled in Medicare Parts A, B, and D receiving in-center hemodialysis from January 1 to December 31, 2019. Analyses were conducted from October 20, 2022, to June 16, 2023. New-user prescriptions for the 7 most frequently filled QT-prolonging medications characterized by the timing of the new prescription relative to acute care encounters, the type of prescribing clinician and pharmacy that dispensed the medication, and concomitant use of selected medications known to interact with the 7 most frequently filled QT-prolonging medications with known TdP risk. The main outcomes were the frequencies of the most commonly filled and new-use episodes of QT-prolonging medications; the timing of medication fills relative to acute care events; prescribers and dispensing pharmacy characteristics for new use of medications; and the frequency and types of new-use episodes with concurrent use of potentially interacting medications. Of 20 761 individuals receiving hemodialysis in 2019 (mean [SD] age, 74 [7] years; 51.1% male), 10 992 (52.9%) filled a study drug prescription. Approximately 80% (from 78.6% for odansetron to 93.9% for escitalopram) of study drug new-use prescriptions occurred outside of an acute care event. Between 36.8% and 61.0% of individual prescriptions originated from general medicine clinicians. Between 16.4% and 26.2% of these prescriptions occurred with the use of another QT-prolonging medication. Most potentially interacting drugs were prescribed by different clinicians (46.3%-65.5%). In this cross-sectional study, QT-prolonging medications for individuals with dialysis-dependent kidney failure were commonly prescribed by nonnephrology clinicians and from nonacute settings. Prescriptions for potentially interacting medications often originated from different prescribers. Strategies aimed at minimizing high-risk medication-prescribing practices in the population undergoing dialysis are needed.

Smart devices to measure and monitor QT intervals

Careful observation of the QT interval is important to monitor patients with long QT syndrome and during treatment with potentially QT-prolonging medication. It is also crucial in the development of novel drugs, in particular in case of a potential side effect of QT prolongation and in patients with increased risk of QT prolongation. The 12-lead electrocardiogram (ECG) is the gold standard to evaluate cardiac conduction and repolarization times. Smartwatches and smart devices offer possibilities for ambulatory ECG recording and therefore measuring and monitoring the QT interval. We performed a systematic review of studies on smartwatches and smart devices for QTc analysis. We reviewed PubMed for smartwatches and smart devices that can measure and monitor the QT interval. A total of 31 studies were included. The most frequent devices were (1) KardiaMobile 6L, a Food and Drug Administration-approved device for QTc analyses that provides a 6-lead ECG, (2) an Apple Watch, a smartwatch with an integrated ECG tool that allows recording of a single-lead ECG, and (3) the Withings Move ECG ScanWatch, an analog watch with a built-in single-lead ECG. The KardiaMobile 6L device and the Apple Watch provide accurate measurements of the QT interval, although the Apple Watch is studied in standard and non-standard positions, and the accuracy of QT measurements increased when the smartwatch was moved to alternative positions. Most studies were performed on patients, and limited results were available from healthy volunteers.

A shortened electrocardiographic diastolic interval is involved in diastolic dysfunction and HFpEF

Abstract Background Heart failure with preserved ejection fraction (HFpEF) is a clinical syndrome characterized by left ventricular diastolic dysfunction (LVDD). We hypothesized that a short electrocardiographic diastolic time predisposes to LVDD and HFpEF by deteriorating diastolic function. This effect may be more pronounced in women than men, given longer QT interval in women. Methods To experimentally test if incremental shortening of the diastolic interval indeed worsens the diastolic function, we shortened electrical diastole using right atrial (RA) pacing and QT-prolonging medication (sotalol) in six pigs. We used 12-lead ECG and echocardiography to assess electrical diastole (TQ interval) and diastolic function. We next analyzed electrocardiograms and corresponding information on LVDD and HF in electronic health record data from 85,145 patients that visited one of 13 Cardiology Centers of the Netherlands. We sex-specifically assessed the association between TQ interval on the one hand and LVDD or HFpEF on the other. Results In pigs, baseline TQ interval was 257 (±SD 66) ms, which decreased to 232 (±SD 36) ms during RA pacing (100 bpm), and further to 193 (±SD 52) ms with concomitant sotalol administration (2 mg/kg iv, bolus). These changes in TQ interval resulted in reversal of E/A ratio, with a significant correlation between TQ interval and decreasing e’/a’ ratio (r=0.382, p=0.024) (Figure 1). In patients who underwent cardiac evaluation with ECG and echocardiography, diastolic abnormalities were documented as LVDD (n=26,009 (30%)) and HFpEF (n=2,551 (3%)). TQ intervals were significantly shorter in patients with LVDD and HFpEF (479 (±SD 128) and 485 ms (±SD 138), respectively) compared to the ones without LVDD or HFpEF (523 (±SD 137) ms). A shorter TQ interval increased the risk for having LVDD and HFpEF when adjusted for confounders (LVDD; ORadjusted= 1.37 (95% CI: 1.28, 1.45), HFpEF; ORadjusted= and 1.16 (95% CI: 1.01, 1.35) (Table 1). There was significant sex-interaction (p= 0.039) for TQ and LVDD risk, with stronger associations in women (ORadjusted= 1.43 (95% CI: 1.32, 1.56) compared to men (ORadjusted= 1.35 (95% CI: 1.10, 1.64) (Table 1). Conclusion Experimentally decreasing the electrical diastolic interval leads to diastolic function abnormalities in pigs. In humans, a shorter diastolic interval is associated with a higher risk of having either LVDD or HFpEF. Our findings imply that a shortened electrical diastolic interval may precede diastolic dysfunction and HFpEF. Therefore, prolonging or preserving electrical diastole may be effective in preventing or treating HFpEF, especially in women.Figure 1Table 1

Abstract 13409: Maintaining a High Total Serum Magnesium Level With Intravenous Magnesium Sulfate

Introduction: Understanding how intravenous magnesium sulfate (MgSO4) administration affects total serum magnesium concentration (TsMg) is important in maintaining a target TsMg level in acute heart failure patients on loop diuretics. Hypothesis: Describe how TsMg changes after single dose of MgSO4 and estimate how often MgSO4 should be given to maintain TsMg above 2 mg/dL. Methods: We studied hospitalizations of veterans from the Veterans Health Administration (VHA) aged ≥ 65 without severe renal disease (EGFR &gt; 15 cc/min per 1.73 m2) from 2013-2017 with a primary diagnosis of acute heart failure. We constructed linear and logistic mixed-effects models with values of TsMg at level 1, nested within dose, hospitalization, and patient. Results: There were 27,474 doses of intravenous MgSO4 administered in 16,139 hospitalizations to 13,439 unique veterans across 145 hospitals in the VHA. Veterans were elderly (mean age 76), 98% male, 72% non-Hispanic white. Mean TsMg was initially high and leveled off 24-48 hours after MgSO4 administration, with an average TsMg increase of 0.2 mg/dL regardless of dose administered (Figure) . The probability of maintaining a TsMg above 2.0 mg/dL just one day after MgSO4 ranged from 49-54% (Table) . Conclusions: TsMg is often targeted above 2.0 gm/dL, especially in the setting of arrhythmias or QT-prolonging medications. As MgSO4 is frequently administered in heart failure patients on diuretics, understanding that TsMg may be misleadingly elevated for the first 48 hours after MgSO4 is important. We recommend administering MgSO4 at least once per day if the goal TsMg level is ≥ 2.0 gm/dL.

Effect of QT interval-prolonging drugs taken in pregnancy on the neonatal QT interval.

Introduction: Acquired QT interval prolongations due to drug side effects can result in detrimental arrhythmia. Maternal use of placenta-permeable drugs may lead to fetal exposure, thus leading to an increased risk of neonatal QT prolongation and arrhythmia. Objectives: This study aimed to evaluate the influence of maternal QT-prolonging medication on the neonatal QT interval. Methods: In the prospective KUNO-Kids health study, an ongoing population-based birth cohort, we classified maternal medications according to the known risk of QT interval prolongation. Effects on the neonatal QT interval were tested by linear regression analyses, correcting for perinatal confounders (birth weight, gestational age, birth mode, and age at ECG recording). Subgroup analyses were performed for selective serotonin reuptake inhibitors, proton pump inhibitors, and antihistamine dimenhydrinate. Logistic regression analysis was performed using a QTc of 450ms as the cut-off value. Results: A total of 2,550 pregnant women received a total of 3,990 medications, of which 315 were known to increase the risk of QT prolongation, resulting in 105 (4.1%) neonates exposed in the last month of pregnancy. Overall, the mean age of the neonates at ECG was 1.9 days and the mean QTc (Bazett) was 414ms. Univariate (regression coefficient -2.62, p = 0.288) and multivariate (regression coefficient -3.55, p = 0.146) regression analyses showed no significant effect of fetal medication exposure on the neonatal QT interval, neither in the overall nor in the subgroup analysis. Logistic regression analysis showed no association of exposure to maternal medication with an increased risk of neonatal QT interval prolongation (OR (odds ratio) 0.34, p = 0.14). Conclusion: The currently used maternal medication results in a relevant number of fetuses exposed to QT interval-prolonging drugs. In our cohort, exposure was found to have no effect on the neonatal QT interval.

Review of electrocardiogram ordering in the context of prescribing combinations of known QT prolonging medicines

Abstract Funding Acknowledgements Type of funding sources: None. Background The risk of medication-induced QT prolongation can be mitigated by reviewing electrocardiograms (ECG) in a hospital inpatient setting. Currently, within the Electronic Medical Record (EMR), decision support tools do not exist to conduct ECG monitoring when prescribing multiple QT prolonging medications. This retrospective review of prescribing data from 2021 looked to assess if we are appropriately ordering ECGs. The results could potentially guide developing decision support tools within the EMR to influence the prescribing of QT-prolonging medications and reduce the risk of QT-prolongation in hospitalised patients. Purpose To ascertain the prevalence of baseline and follow-up ECGs when three or more known QT prolonging medications were concurrently administered. Methods QT prolonging medications were defined using Crediblemeds [1], an online resource aimed to support the safe prescribing of QT prolonging medications. Known QT prolonging medications were defined as medications which prolong the QT interval and are associated with Torsades de Pointes. A retrospective review of inpatient prescribing in 2021 was conducted by extracting data from the EMR. Patients who received three or more of these medications on the same calendar day were included. Information reported included patient demographics, details of QT prolonging medication and whether ECGs were performed. Certain intra-operative medications were excluded from review due to the short patient exposure time to the medication. ECGs were reviewed independently by two pharmacists and the QTc interval was calculated using the Bazett formula. Results A total of 70 patients received three or more QT prolonging medications. In total, 30 (43%) patients had a baseline ECG performed within seven days of medication commencement and 6 (9%) patients received both a baseline and follow-up ECG within 24 hours of medication administration. One patient had a prolonged QTc (&amp;gt;500msec) on their baseline ECG. Baseline ECGs were not performed in 29 (41%) of patients whereas Eleven patients (16%) had an ECG on record, but it was older than seven days prior to medication administration. Three patients without a baseline ECG had a follow-up ECG within 24 hours after medication administration. Overall, 28 different medications were identified with Ondansetron, Ciprofloxacin and Escitalopram appearing most commonly. Conclusions This audit indicates that clinicians are not consistently ordering ECGs at baseline or utilising follow up ECGs when prescribing concurrent QT prolonging medications which may increase the risk of preventable patient harm. Though QT prolongation was not detected on follow-up ECGs, this may be impacted by the low prevalence of follow-up ECGs. The utilisation of decision support tools within the EMR may improve ECG monitoring in patients at risk of QT prolongation.

477. Evaluation of Electrocardiogram (ECG) Monitoring Practice in Newly Initiated Azole Antifungal Therapy

Abstract Background Azole antifungals are first-line options in the management of many fungal infections, but most are known to cause corrected Q-T interval (QTc) prolongation. There is a lack of guidance on which patients on azoles warrant ECG monitoring, potentially leading to discordant clinical practices. We aimed to determine factors associated with ECG monitoring of patients on systemic azole therapy. Methods We performed a retrospective cohort study of hospitalized adult patients who received at least five days of inpatient azole therapy. Pregnant patients, those on azoles prior to admission or with a gap in azole therapy &amp;gt; 3 days were excluded. Only the first admission with azole use per patient over the study period was included. The primary outcome was any ECG measurement within 5 days of starting azole therapy. We calculated adjusted odds ratios (aOR) for the association between patient and treatment characteristics and likelihood of ECG measurement using multivariable logistic regression. Figure 1.Study Flow Diagram Results 4,126 patients met inclusion criteria over 9 years (Figure 1). Most were admitted to the Hematology/Oncology service (49%), followed by Transplant (20.4%). Azole therapy was initiated for medical prophylaxis in 61.7% and for treatment in 27.9%. Fluconazole (FLU) was the most utilized azole (75.2%), followed by voriconazole (VOR) (18%). Overall, 1,454 patients (35.24%) had at least one ECG measured within 5 days of starting azole therapy. Patients were more likely to have an ECG monitored if they received VOR (48.1%) compared to FLU (31.1%), or were on the transplant service (53.9%) vs medicine (37%). On multivariate analysis (Figure 2), likelihood of having an ECG measured was greater among patients (1) receiving posaconazole (POS, aOR 1.75, 95% CI 1.31-2.34) or VOR (aOR 1.34, 95% CI 1.10-1.63) versus FLU, (2) with a baseline ECG (aOR 2.07 (1.76-2.43), and (3) who received concomitant QT-prolonging medications (aOR 1.22, 95% CI 1.01-1.48) or diuretics (aOR 1.38 95% CI 1.16-1.63). Figure 2.Odds Ratio for Primary Outcome QT-prolonging medication use during azole therapy: Antibiotics (ciprofloxacin, levofloxacin, moxifloxacin, clarithromycin, azithromycin), HIV meds (protease inhibitors), CV meds (amiodarone, disopyramide, dofetilide, procainamide, quinidine, sotalol), anti-emetics (chlorpromazine, metoclopramide, ondansetron), chemotherapy (nilotinib, sunitinib), psychiatric meds (haloperidol, risperidone, ziprasidone), miscellaneous (methadone); Diuretics/electrolyte disturbing agents used during azole therapy: Furosemide, bumetanide, torsemide, sulfamethoxazole-trimethoprim, amphotericin Conclusion Use of POS or VOR, baseline ECG monitoring, concomitant QT-prolonging medications, and electrolyte abnormalities, were associated with greater likelihood of ECG monitoring. These results can help target guidance for ECG monitoring in patients on azoles. Disclosures Conan MacDougall, PharmD, MAS, Merck: Advisor/Consultant Sarah B. Doernberg, MD, MAS, Basilea: Clincal events committee|Genentech: Advisor/Consultant|Gilead: Grant/Research Support|Regeneron: Grant/Research Support|Shinogi: Clincal events committee.

Abstract 11452: EHR-Based Machine Learning Model Predicts Drug-Induced QT Prolongation With Superior Performance Compared to Clinical Risk Predictors

Introduction: Many medications are associated with QTc prolongation (LQT). Current LQT predictors, including Tisdale and RISQ-PATH, have limited utility due to lack of generalizability to key use cases and modest model performance. A highly accurate LQT risk predictor utilizing data often available at the time of drug starts could broadly support LQT risk management. Hypothesis: An electronic health record (EHR)-based machine learning (ML) model is superior in predicting drug-induced LQT in a clinical population vs. Tisdale and RISQ-PATH. Methods: We identified all patients who began taking QT-prolonging medications (‘QTdrug’, per CredibleMeds) at Geisinger and had a follow-up 12-lead ECG within 1 year of medication start date while still on the drug. In case of multiple QTdrugs with overlapping dates, the last start date was used. Using 5-fold cross-validation, we trained an XGBoost ML model to predict LQT (QTc &gt;500 ms) within 1 year of QTdrug start date using EHR data as input, including 131 features across age, sex, smoking history, vitals, lab tests, comorbidities, baseline ECG metrics (within 3 years before drug start date) and QTdrug usage (ever on QTdrug, number of current QTdrugs). Results: QTdrug records were identified for 362,086 patients, and 6% had LQT within 1 year. The ML model demonstrated superior performance (Figure A) in predicting LQT (area under the curve (AUROC): 0.86, average precision score (AUPRC): 0.41) compared to RISQ-PATH (AUROC: 0.70, AUPRC: 0.19) and Tisdale (AUROC: 0.76, AUPRC: 0.21, calculated in a hospitalized subset N=113544). At the same specificity as RISQ-PATH (98%), the ML model had higher sensitivity (30% vs 10%) and positive predictive value (55% vs 29%). Similar comparisons were observed for Tisdale (Figure B). Conclusions: An EHR-based ML model outperforms commonly used risk calculators for predicting drug-induced LQT. This model can be used to stratify patients by risk of developing drug-induced LQT in a clinical setting.

Abstract 11953: Sudden Death Associated With Therapeutic Levels of Methadone: Significance of Drug Interactions

Introduction: Methadone for treatment of addiction or chronic pain can be complicated by QT interval prolongation and increased risk of sudden cardiac death (SCD). The concurrent use of additional QT-prolonging medications, such as selective serotonin reuptake inhibitors (SSRIs), may contribute to additional increased risk. We conducted a community-based study to assess the potential role of drug combinations in SCD. Methods: We ascertained residents of Multnomah Co., OR (2002-18) and Ventura Co., CA (2015-21) who suffered SCD and had toxicology reports available. We excluded those under age 18 and those with evidence of recreational drug use or drug overdose. Methadone levels and medications were captured on toxicology reports from the medical examiner. We used logistic regression to compare characteristics and the presence of select medications in those with and without therapeutic levels of methadone at the time of SCD. Results: Of the 789 subjects who met our criteria, the mean (25th-75th percentile) age was 49 (39-59) years, 34% were females, and 85 (11%) had therapeutic levels of methadone. Subjects on methadone were younger, more likely to be female, and had a higher prevalence of SSRIs and benzodiazepines compared to those without methadone (Table). Subjects with methadone had a 3.37 higher odds of SSRI use compared to those without methadone (95% CI: 1.87-6.09). When stratified by mechanistic category, those with methadone had higher odds of QT-prolonging SSRIs [OR (95% CI) = 2.87 (1.35-6.13)] and higher odds of other SSRIs [OR (95% CI) = 3.20 (1.40-7.32)] compared to those without methadone. Combinations of methadone with other selected drug classes did not reach statistical significance. Conclusion: These postmortem findings suggest that the combination of methadone with SSRIs may be associated with additional risk of SCD and warrant further investigation. Drug interactions are a potentially avoidable risk factor for SCD in patients receiving methadone.

Incorporation of Pharmacist in Conducting Medication Reviews for Identification of Risk of QT Prolongation: A Neglecting Latent Approach in Cardiology

Sudden cardiac arrest correlates with QT-interval prolongation and torsade de points (TdP). Several medicines frequently used in geriatric aged care populations can cause QT prolongation. Major predisposing factors and QT-prolonging medications enhance QT interval prolongation incidence in medical inpatients. Pharmacists can help ensure safe drug therapy and in-hospital patient safety by paying attention to QT prolongation and extra risk factors for prolonged QT intervals during medication reconciliation. We recommend pharmacists improve knowledge and awareness of corrected QT prolongation (QTc) when conducting drug reviews. Implementation of Pharmacist-driven QTc monitoring is required to lower the risk of QTc prolongation.

COVID-19 and arrhythmias - is there a relationship?

COVID-19 infection is associated with many different systemic complications. Among these, cardiovascular system complications are particularly important as these are associated with significant mortality. There are many different subgroups of cardiovascular complications, with arrhythmias being one of them. Arrhythmias are especially important as there are a substantial percentage of patients who have arrhythmia after a COVID-19 infection, and these patients are seen with an increased mortality rate. Arrhythmias in COVID-19 patients are associated with inflammation, electrolyte abnormalities, hypoxia, myocardial ischemia, cytokines, pro-arrhythmic or QT-prolonging medications, and underlying heart conditions such as severe congestive heart failure, inherited arrhythmia syndromes, or congenital heart conditions. In addition, arrhythmias and cardiac arrests are most prevalent in the critically ill intensive care unit COVID-19 patient population. This review of PubMed/MedLine articled presents an overview of the association between COVID-19 and arrhythmias by detailing possible pathophysiological mechanisms, existing knowledge of pro-arrhythmic factors, and results from studies in adult COVID-19 populations.

The modifying effect of the serum-to-dialysate potassium gradient on the cardiovascular safety of SSRIs in the hemodialysis population: a pharmacoepidemiologic study.

Hypokalemia is a risk factor for drug-induced QT prolongation. Larger serum-to-dialysate potassium gradients during hemodialysis (HD) may augment the proarrhythmic risks of selective serotonin reuptake inhibitors (SSRIs). We conducted a cohort study using 2007-2017 data from the United States Renal Data System and a large dialysis provider to examine if the serum-to-dialysate potassium gradient modifies SSRI cardiac safety. Using a new-user design, we compared 1-year sudden cardiac death (SCD) risk among HD patients newly treated with higher (citalopram, escitalopram) versus lower (fluoxetine, fluvoxamine, paroxetine, sertraline) QT-prolonging potential SSRIs, overall and stratified by baseline potassium gradient (≥4versus &lt;4mEq/l). Weusedinverseprobability of treatment-weighted survival models to estimate weighted hazard ratios (HRs) and 95% confidence intervals (CIs) and conducted a confirmatory nested case-control study. The study included 25 099 patients: 11 107 (44.3%) higher QT-prolonging potential SSRI new users and 13 992 (55.7%) lower QT-prolonging potential SSRI new users. Overall, higher versus lower QT-prolonging potential SSRI use was not associated with SCD [weighted HR 1.03 (95% CI 0.86-1.24)]. However, a greater risk of SCD was associated with higher versus lower QT-prolonging potential SSRI use among patients with baseline potassium gradients ≥4mEq/l but not among those with gradients &lt;4mEq/l [weighted HR 2.17 (95% CI 1.16-4.03) versus 0.95 (0.78-1.16)]. Nested case-control analyses yielded analogous results. The serum-to-dialysate potassium gradient may modify the association between higher versus lower QT-prolonging SSRI use and SCD among people receiving HD. Minimizing the potassium gradient in the setting of QT-prolonging medication use may be warranted.

0696 The Application of a QTc Risk Score in Patients with Obstructive Sleep Apnea

Abstract Introduction Evidence suggests that patients with obstructive sleep apnea (OSA) are at risk for QTc prolongation which, is a known risk factor for arrhythmias, sudden cardiac death and all cause mortality. QTc risk scores have been implemented widely to help physicians identify patients at risk for mortality however, these risk scores have not been routinely implemented in patients undergoing sleep studies or those diagnosed with OSA. The goal of this study was to evaluate the distribution of pro-QTc risk scores for patients with and without OSA diagnosed at our facility and its relationship to mortality. Methods Medical records of all patients undergoing a sleep study at our sleep center from 2/2012 through 8/2020 were analyzed. Patients were identified with or without OSA based on polysomnography or Type III home sleep study. The pro-QTc risk score was calculated with 1 point assigned for: female sex, QT-prolonging diagnoses and conditions, QT-prolonging electrolyte abnormalities, and QT-prolonging medications defined as medications with known and possible risk of torsades de Pointes based on the CredibleMeds website. Mortality was determined if a death date was noted in the electronic medical record. Results A total of 2,834 patient records (54% male, age 58 ± 16 years, n=106 dead) were evaluated. A total of 2,265 patients (age 58 ±15, 54% male, 89 dead) were identified as having OSA and 428 patients (age 54 ± 18, 41% male, 17 dead) did not have OSA. The remaining patients (n=141) had either central sleep apnea or a combination of both obstructive and central sleep apnea. A higher pro-QTc score was associated with greater mortality regardless of presence of OSA (HR 1.3, p&amp;lt;0.0001, 95% CI 1.12 -1.46) after adjusting for age. The association of pro-QTc with mortality was not increased in the moderate or severe OSA groups compared to those without OSA or mild OSA (p=0.36). Conclusion Increased pro-QTc scores were associated with greater mortality in all patients undergoing sleep studies. OSA status did not affect this association. Support (If Any) American Academy of Sleep Medicine Foundation (203-JF-18), National Institutes of Health (HL126140, 2L30HL154400-023), University of Arizona Health Sciences Career Development Award (5299903), and University of Arizona Faculty Seed Grant (5833261)

Electrocardiogram Monitoring Practices for Hospitalized Adults Receiving Antipsychotics: A Retrospective Cohort Study.

Antipsychotics are frequently used for managing both acute and chronic neuropsychiatric disorders. While antipsychotics are known to be associated with increased mortality due to cardiac arrhythmia, there is a lack of consensus on the timing and frequency of electrocardiogram (ECG) monitoring. The goal of this study was to examine current ECG monitoring practices for adults receiving antipsychotics, specifically during hospital admission. The study involved a multisite retrospective chart review of adults admitted across 8 hospitals between January 2010 and December 2015 who received antipsychotics during hospitalization. The primary outcome was the presence of an ECG after receiving an antipsychotic. During the study period, there were 26,353 hospitalizations during which adults received antipsychotic medication; the average age of the patients was 61.4 years, 50.1% were female, and 64.8% were white. The average comorbidity score was 1.4 with a median length of stay of 8.3 days. Of the 26,353 patients who were hospitalized, 60.6% (n=15,977) of patients in the sample had an ECG during their hospitalization, and 41.2% (n=10,865) had the ECG following antipsychotic administration. Patients who received a follow-up ECG had a longer length of stay (median: 11.3 d) compared with those who did not receive a follow-up ECG (median: 7.0 d). Follow-up ECGs were more likely among patients who had a history of heart failure [odds ratio (OR)=1.17, 95% confidence interval (CI): 1.06-1.30, P=0.002], who were receiving multiple antipsychotics (OR=1.3, 95% CI: 1.24-1.36, P<0.001) or other QT-prolonging medications (OR=1.09, 95% CI: 1.07-1.1, P<0.001), who were receiving risperidone (OR=1.12, 95% CI: 1.004-1.25, P=0.04), and who showed an increase in QTc duration (OR per 10 ms increase=1.02, 95% CI: 1.01-1.04, P=0.003). Follow-up ECGs were less likely to be administered to patients who were receiving antipsychotics before admission (OR=0.93, 95% CI: 0.87-0.997, P=0.04). This study demonstrated that, in a large health system, ECG monitoring is not routinely practiced for hospitalized patients receiving antipsychotics. Further studies are needed to identify patients who would most benefit from ECG monitoring in the acute care setting.

A neonate with acquired long QT from placental transfer of medications

Long QT Syndrome (LQTS) can present in the neonate with bradycardia and AV block and confers significant risk for life threatening ventricular arrhythmias. We report a case of a neonate presenting with complex bradyarrhythmias secondary to acquired LQTS after maternal overdose of QT-prolonging medications (haloperidol and sertraline). When the mother was brought in to the delivery center unconscious, fetal bradycardia was noted and the baby was emergently delivered prematurely. The newborn’s initial ECG showed bradycardia with AV node conduction block, rate related His-Purkinje conduction aberration with varying QRS morphology and a QTc &gt;600 ms. She continued to be bradycardic through her first day of life with echocardiogram showing mild cardiac dysfunction. With the elimination of the offending medication from her circulation, the infant’s rate and function abnormalities resolved and QTc normalized. Both haloperidol and sertraline are known to be strong suppressors of the HERG potassium channel that plays an important role in myocardial repolarization and both medications can cross the placenta. Maternal overdose can cause transient QT-prolonging effect similar to that of inherited LQTS type 2. Given the high risk for sudden death in affected newborns, reporting this case is aimed to raise the awareness of acquired LQTS by placental transfer of medication. Early identification of neonates at risk should prompt ECG testing. If long QT is identified, the newborn should be closely monitored with care to avoid any further QT prolonging medications or conditions, until the toxic medication effect resolves.

Development and early evaluation of clinical decision support for long QT syndrome population screening

Aim: Long QT syndrome (LQTS) is an inherited condition that predisposes individuals to prolongation of the QT interval and increased risk for Torsade de Pointes. Pathogenic variants in three genes - KCNH2, KCNQ1 and SCN5A - are responsible for most cases of LQTS, and recent advances in genetic testing have improved knowledge of the disease, increased access to follow-up, and reduced adverse cardiovascular outcomes. Methods: Based around our preemptive genetic screening platform which includes the three long QT genes listed above, we developed and implemented a clinical decision support (CDS) module that alerts prescribers whenever a QT-prolonging medication is ordered for patients with a genetic predisposition to LQTS. Results: Of the 13,777 individuals screened, twenty-seven tested positive for a pathogenic or likely pathogenic variant of KCNH2, KCNQ1 or SCN5A. In a subsequent early evaluation of the CDS and clinical processes, the number of QT-prolonging medications in this cohort decreased by 20% and new QT-prolonging medications were avoided in approximately 1/3 of new prescription orders. Conclusions: While long-term evaluation is needed, early data support the benefit of utilizing CDS in expanded roles, such as drug-gene-disease interactions where rare genetic variants intersect with everyday prescribing.