Hydroxychloroquine has recently received attention as a treatment for COVID-19. However, it may prolong the QTc interval. Furthermore, when hydroxychloroquine is administered concomitantly with other drugs, it can exacerbate the risk of QT prolongation. Nevertheless, the risk of QT prolongation due to drug-drug interactions (DDIs) between hydroxychloroquine and concomitant medications has not yet been identified. To evaluate the risk of QT prolongation due to DDIs between hydroxychloroquine and 118 concurrent drugs frequently used in real-world practice, we analyzed the electrocardiogram results obtained for 447,632 patients and their relevant electronic health records in a tertiary teaching hospital in Korea from 1996 to 2018. We repeated the case–control analysis for each drug. In each analysis, we performed multiple logistic regression and calculated the odds ratio (OR) for each target drug, hydroxychloroquine, and the interaction terms between those two drugs. The DDIs were observed in 12 drugs (trimebutine, tacrolimus, tramadol, rosuvastatin, cyclosporin, sulfasalazine, rofecoxib, diltiazem, piperacillin/tazobactam, isoniazid, clarithromycin, and furosemide), all with a p value of < 0.05 (OR 1.70–17.85). In conclusion, we found 12 drugs that showed DDIs with hydroxychloroquine in the direction of increasing QT prolongation.

Objectives: Drug-induced QT prolongation can lead to life-threatening arrhythmia. In the intensive care unit (ICU), various drugs are administered concurrently, which can increase the risk of QT prolongation. However, no well-validated method to evaluate the risk of QT prolongation in real-world clinical practice has been established. We developed a risk scoring model to continuously evaluate the quantitative risk of QT prolongation in real-world clinical practice in the ICU.Methods: Continuous electrocardiogram (ECG) signals measured by patient monitoring devices and Electronic Medical Records data were collected for ICU patients. QT and RR intervals were measured from raw ECG data, and a corrected QT interval (QTc) was calculated by Bazett’s formula. A case-crossover study design was adopted. A case was defined as an occurrence of QT prolongation ≥12 hours after any previous QT prolongation. The patients served as their own controls. Conditional logistic regression was conducted to analyze prescription, surgical history, and laboratory test data. Based on the regression analysis, a QTc prolongation risk scoring model was established.Results: In total, 811 ICU patients who experienced QT prolongation were included in this study. Prescription information for 13 drugs was included in the risk scoring model. In the validation dataset, the high-risk group showed a higher rate of QT prolongation than the low-and low moderate-risk groups.Conclusions: Our proposed model may facilitate risk stratification for QT prolongation during ICU care as well as the selection of appropriate drugs to prevent QT prolongation.

Drug-induced QT prolongation is one of the most common side effects of drug use and can cause fatal outcomes such as sudden cardiac arrest. This study adopts the data-driven approach to assess the QT prolongation risk of all the frequently used drugs in a tertiary teaching hospital using both standard 12-lead ECGs and intensive care unit (ICU) continuous ECGs. We used the standard 12-lead ECG results (n = 1,040,752) measured in the hospital during 1994–2019 and the continuous ECG results (n = 4,835) extracted from the ICU’s patient-monitoring devices during 2016–2019. Based on the drug prescription frequency, 167 drugs were analyzed using 12-lead ECG data under the case-control study design and 60 using continuous ECG data under the retrospective cohort study design. Whereas the case-control study yielded the odds ratio, the cohort study generated the hazard ratio for each candidate drug. Further, we observed the possibility of inducing QT prolongation in 38 drugs in the 12-lead ECG analysis and 7 drugs in the continuous ECG analysis. The seven drugs (vasopressin, vecuronium, midazolam, levetiracetam, ipratropium bromide, nifedipine, and chlorpheniramine) that showed a significantly higher risk of QT prolongation in the continuous ECG analysis were also identified in the 12-lead ECG data analysis. The use of two different ECG sources enabled us to confidently assess drug-induced QT prolongation risk in clinical practice. In this study, seven drugs showed QT prolongation risk in both study designs.

Drug-induced QT prolongation is attributed to several mechanisms, including hERG channel blockage. However, the risks, mechanisms, and the effects of rosuvastatin-induced QT prolongation remain unclear. Therefore, this study assessed the risk of rosuvastatin-induced QT prolongation using (1) real-world data with two different settings, namely case–control and retrospective cohort study designs; (2) laboratory experiments using human-induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CM); (3) nationwide claim data for mortality risk evaluation. Real-world data showed an association between QT prolongation and the use of rosuvastatin (OR [95% CI], 1.30 [1.21–1.39]) but not for atorvastatin (OR [95% CI], 0.98 [0.89–1.07]). Rosuvastatin also affected the sodium and calcium channel activities of cardiomyocytes in vitro. However, rosuvastatin exposure was not associated with a high risk of all-cause mortality (HR [95% CI], 0.95 [0.89–1.01]). Overall, these results suggest that rosuvastatin use increased the risk of QT prolongation in real-world settings, significantly affecting the action potential of hiPSC-CMs in laboratory settings. Long-term rosuvastatin treatment was not associated with mortality. In conclusion, while our study links rosuvastatin use to potential QT prolongation and possible influence on the action potential of hiPSC-CMs, long-term use does not show increased mortality, necessitating further research for conclusive real-world applications.