Eline Vandael

Which QT Correction Formulae to Use for QT Monitoring

Background Drug safety precautions recommend monitoring of the corrected QT interval. To determine which QT correction formula to use in an automated QT‐monitoring algorithm in our electronic medical record, we studied rate correction performance of different QT correction formulae and their impact on risk assessment for mortality. Methods and Results All electrocardiograms (ECGs) in patients >18 years with sinus rhythm, normal QRS duration and rate <90 beats per minute (bpm) in the University Hospitals of Leuven (Leuven, Belgium) during a 2‐month period were included. QT correction was performed with Bazett, Fridericia, Framingham, Hodges, and Rautaharju formulae. In total, 6609 patients were included (age, 59.8±16.2 years; 53.6% male and heart rate 68.8±10.6 bpm). Optimal rate correction was observed using Fridericia and Framingham; Bazett performed worst. A healthy subset showed 99% upper limits of normal for Bazett above current clinical standards: men 472 ms (95% CI, 464–478 ms) and women 482 ms (95% CI 474–490 ms). Multivariate Cox regression, including age, heart rate, and prolonged QTc, identified Framingham (hazard ratio [HR], 7.31; 95% CI, 4.10–13.05) and Fridericia (HR, 5.95; 95% CI, 3.34–10.60) as significantly better predictors of 30‐day all‐cause mortality than Bazett (HR, 4.49; 95% CI, 2.31–8.74). In a point‐prevalence study with haloperidol, the number of patients classified to be at risk for possibly harmful QT prolongation could be reduced by 50% using optimal QT rate correction. Conclusions Fridericia and Framingham correction formulae showed the best rate correction and significantly improved prediction of 30‐day and 1‐year mortality. With current clinical standards, Bazett overestimated the number of patients with potential dangerous QTc prolongation, which could lead to unnecessary safety measurements as withholding the patient of first‐choice medication.

Incidence of Torsade de Pointes in a tertiary hospital population

BACKGROUND Multiple risk factors play a role in the development of QTc-prolongation and Torsade de Pointes (TdP). Cases of TdP are underreported and data on the incidence of TdP is scarce. The aim of this study was to investigate the incidence of TdP in a Belgian university hospital and describe the characteristics of TdP-cases using a risk score. METHODS All cases from 2011 till 2013 coded with the ICD-9 code 427.1 in the University Hospitals of Leuven were selected. The medical files were reviewed and demographical, medical, medication and electrocardiographic data were collected. We focused on TdP-cases that were probably caused by the acquired long QT-syndrome. The RISQ-PATH score was used to quantify the risk in these cases (≥10 points as high risk for QTc-prolongation/TdP). RESULTS Over three years, 41 TdP-cases were identified of which 19 cases were secondary to the acquired long QT-syndrome (52.6% females, mean age of 74±12years). This corresponds with an incidence of 0.16‰/year in a hospital population. Most of the patients (N=17) were treated with at least one QTc-prolonging drug (most frequently amiodarone, sotalol and furosemide) of whom 12 patients with ≥1 QTc-prolonging drug of list 1 of CredibleMeds. Fifteen patients had an electrocardiogram in a 24-hours interval before the TdP with a prolonged QTc-interval (≥450/470ms). All the patients had a RISQ-PATH score≥10. CONCLUSIONS Although the incidence of 0.16‰/year might seem low, this means that approximately 173 possibly lethal TdP-cases can be expected in Belgian hospitals each year. All TdP-cases were associated with a high RISQ-PATH score.

Cases of drug-induced Torsade de Pointes: a review of Belgian cases in the EudraVigilance database

Objectives: Post-marketing surveillance is very important, especially for rare adverse drug reactions like QTc-prolongation and Torsade de Pointes (TdP). The objective of this study was to investigate the characteristics of Belgian cases of drug-related TdP reported in the EudraVigilance database. Methods: The EudraVigilance database was searched for Belgian post-marketing cases of TdP reported between December 2001–April 2015. These cases were identified with MedDRA preferred terms. Duplicate reports were excluded. Each included case report was reviewed to collect data about age, gender, seriousness, suspected drug, concomitant drugs, causality, and other known risk factors for QTc-prolongation. Results: Between 2001 and 2015, only 31 cases coded as TdP were identified; 16 cases were also coded as ‘prolonged QT’ and 2 patients died. In total, 21 suspected drugs were implicated and most of them (N = 11) were part of list 1 of CredibleMeds. The most common suspected drugs were citalopram (N = 4) and amiodarone (N = 3). In 18 cases, a pharmacodynamic drug-drug interaction with risk of QTc-prolongation was present. Most patients (N = 25) had ≥2 other risk factors for QTc-prolongation. Conclusion: Over 15 years, only a low number of Belgian cases of TdP were identified in the EudraVigilance database. In most case reports, multiple risk factors for QTc-prolongation could be detected. This illustrates that there is a clear underreporting of QTc-prolongation and TdP in Belgium. Initiatives are needed to improve the awareness and knowledge of health care professionals regarding the risk of QTc-prolongation and TdP, both to prevent cases of TdP and to stimulate the reporting of these cases.

QT correction across the heart rate spectrum, in atrial fibrillation and ventricular conduction defects

Incorporation of QTc in clinical decision support systems requires accurate QT‐interval correction, also during common electrocardiogram abnormalities as ventricular conduction defects (VCD). We compared the performance and predictive value of QT correction formulas to design a patient‐specific QT correction algorithm (QTcA).

A smart algorithm for the prevention and risk management of QTc‐prolongation based on the optimized RISQ‐PATH model

QTc prolongation is a complex problem linked with multiple risk factors. The RISQ‐PATH score was previously developed to identify high‐risk patients for QTc prolongation. The aim of this study was to optimize and validate this risk score in a large patient cohort, and to propose an algorithm to generate smart QT signals in the electronic medical record.

Drug interactions with QT-prolonging antibiotics: an epidemiological study in community pharmacies.

Methods An epidemiological study on data of a dispensing database of Flemish community pharmacies (Surplus network; N=100) was performed. The patients who received a QT-prolonging antibiotic in the last week of May 2014 were selected and their medication histories (FebruaryMay 2014) were screened for other QT-prolonging drugs and concomitant risk factors (summarized in a risk score: = 65 years, female, cardiovascular disease, diabetes, thyroid disturbances, each 1 point; potassium-lowering diuretics: 3 points; antiarrhythmic drugs: 4 point). Furthermore, the management of QT-signals by the pharmacist was analyzed.