Research has linked many drugs to QT prolongation and decision support tools could alert clinicians to the risk and guide prescribing decisions to safer alternatives.
In early 2020, the FDA temporarily approved the drugs hydroxychloroquine and chloroquine as potential prophylaxis or treatment for hospitalized patients with COVID-19-related illness. At the time, it was understandable that the FDA would grant Emergency Use Authorization given the early pre-publication data from Europe, in vitro study information, and paucity of known effective treatments for the highly contagious and deadly virus.
Even then, though, the FDA cautioned providers about the use of these agentsdue to their association with a dangerous risk of QT-prolongation and torsades des pointes (TdP), a type of tachycardia that can lead to cardiac arrest. These risks and adverse reactions in patients with COVID-19 as well as lagging evidence of efficacy were the reasons the authorization was later revoked.
Hydroxychloroquine and chloroquine, however, are not the only noncardiac drugs linked with an increased risk of QT-prolongation and TdP. A recent study published in Drugs – Real World Outcomes found that common antibiotics, antidepressants, antinausea and antiplatelet drugs are associated with an increased risk of cardiac arrhythmia and sudden death in older patients.
Since physiologic monitoring is often unreliable at predicting such drug-induced cardiac events, utilizing medication decision support systems that present data related to patient-specific risk factors as well as contextual clinical information at the point of care could help clinicians identify patients that require therapy switches or closer monitoring to prevent adverse events and save lives.
The study, “Using Medicare Data to Assess the Proarrhythmic Risk of Non-Cardiac Treatment Drugs that Prolong the QT Interval in Older Adults: An Observational Cohort Study,” of which I was an author, was based on an analysis of 1.2 million deidentified Medicare beneficiaries over 5 million patient-years of follow-up.
Researchers from the National Library of Medicine and our company, FDB (First Databank), did not include antiarrhythmic drugs, medications that were pulled from the market due to drug-induced QT prolongation and TdP risk, or low-use drugs. Rather, we strategically selected drugs that were commonly prescribed in both inpatient and outpatient environments associated with TdP risk.
Our findings were concerning. Nearly all — 14 out of 17 — drugs studied were associated with a higher risk of adverse or fatal outcomes in elderly patients. In the hospital, clinicians can use electrocardiograms (ECG) to detect QT prolongation, but this type of monitoring can be an unreliable predictor of the likelihood of this evolving into a serious ventricular arrhythmia and is not available for ambulatory, outpatient patients. A 2016 study in the Journal of the American College of Cardiology acknowledged this fact. The authors concluded that there is a growing body of evidence that suggests that both genetic and clinical predictors (e. g., electrolyte disturbances or underlying conditions) should be included in clinical decision support systems to help prevent drug-induced QT prolongation, rather than relying on physiologic monitoring to alert clinicians, which can be even more challenging for ambulatory patients.
A later study echoed these findings, highlighting the challenges and risks in relying on ECG in clinical research environments to evaluate the safety of new drugs. The latter study also cited a landmark 2005 paper that found only 62% of arrhythmia experts and less than 42% of cardiologists and non-cardiologists were correct in their QT diagnoses based on ECG reviews.
These studies, as well as our findings, demonstrate the need to offer medication decision support systems that help clinicians more precisely identify patients based on their history and status who require therapy switches or closer monitoring to prevent adverse events and save lives. Such a tool is even more important given the industry shift to more telehealth and remote patient monitoring and less frequent hospitalizations.
Our analysis of a large cohort of Medicare data concerned short-term (or short-course therapy) use drugs: three fluoroquinolone antibiotics (ciprofloxacin, levofloxacin, and moxifloxacin, analyzed individually); three macrolide antibiotics (azithromycin, clarithromycin, and erythromycin, analyzed individually); one antifungal (fluconazole); and one antiemetic (ondansetron).
In addition, nine chronic usage drugs (also known as maintenance drugs) were analyzed: two selective serotonin reuptake inhibitor (SSRI) antidepressants (citalopram and escitalopram); three antipsychotics (haloperidol, thioridazine, and chlorpromazine); two antiplatelet agents (cilostazol and anagrelide); one antirheumatic drug (hydroxychloroquine); and one anti-Alzheimer's disease drug (donepezil).
Of the short-term drugs, we found the antibiotic levofloxacin increased the risk of cardiac arrhythmia or sudden death by 51% compared with the amoxicillin control, while erythromycin was associate wiht an increased risk of 63%. The antinausea drug ondansetron increased the risk of a cardiac adverse event by 205%, while the antifungal fluconazole increased the risk by 123%. The riskiest of this group, ondansetron, was prescribed more than 12.2 million times in 2018, while fluconazole was prescribed more than 4.1 million times.
Chronic condition or maintenance drugs carried similar high risks, according to our analysis. Patients prescribed the antipsychotics showed an increased risk of arrhythmia or sudden death of 118% compared to patients who never received the drug. Current users of both antiplatelet drugs had an increased risk of 156%, while hydroxychloroquine showed an increased risk of 68% when comparing patient controls. Current users of both SSRI antidepressants studied showed increased risks, except if the patient had been taking the medication for more than a year. This appeared to reduce the risk (or perhaps stratified those patients that did not have genetic predisposition who tolerated longer therapy duration).
Medication decision support tools can help aid prescribers in tandem with ECGs and offer preventive guidance at the point of ordering. Similar tools can notify pharmacists as another safety stopgap in the prescribing process. These tools leverage patient-specific information within the electronic health record to identify patients who have a higher risk. The tools consider risk factors such as patient age, gender, and congenital history of long QT syndrome, as well as comorbidities such as hypokalemia and cardiac conditions, along with the patient’s current medication list.
QT prolongation risk can be additive in nature: Multiple drugs causing this risk may result in a higher individual patient risk. Accurate and relevant guidance would utilize the most up-to-date,curated drug knowledge and seamless integration into clinical workflows.
Joan Kapusnik-Uner, PharmD, FCSHP, FASHP, is vice president of clinical content for FDB.