Development of a risk model for predicting QTc interval prolongation in patients using QTc-prolonging drugs

Developing a Model for Quantifying QTc-Prolongation Risk to Enhance Medication Safety Assessment: A Retrospective Analysis

There are currently no established methods to predict quantitatively whether the start of a drug with the potential to prolong the QTc interval poses patients at risk for relevant QTc prolongation. Therefore, this retrospective study aimed to pave the way for the development of models for estimating QTc prolongation in patients newly exposed to medications with QTc-prolonging potential. Data of patients with a documented QTc prolongation after initiation of a QTc-prolonging drug were extracted from hospital charts. Using a standard model-building approach, general linear mixed models were identified as the best models for predicting both the extent of QTc prolongation and its absolute value after the start of a QTc-time-prolonging drug. The cohort consisted of 107 adults with a mean age of 64.2 years. Patients were taking an average of 2.4 drugs associated with QTc prolongation, with amiodarone, propofol, pipamperone, ondansetron, and mirtazapine being the most frequently involved. There was a significant but weak correlation between measured and predicted absolute QTc values under medication (r2 = 0.262, p < 0.05), as well as for QTc prolongation (r2 = 0.238, p < 0.05). As the developed models are based on a relatively small number of subjects, further research is necessary to ensure their applicability and reliability in real-world scenarios. Overall, this research contributes to the understanding of QTc prolongation and its association with medications, providing insight into the development of predictive models. With improvements, these models could potentially aid healthcare professionals in assessing the risk of QTc prolongation before adding a new drug and in making informed decisions in clinical settings.

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.

Determinants of severe QTc prolongation in a real-world gerontopsychiatric setting

Introduction

QT_c prolongation carries the risk of ventricular tachyarrhythmia (Torsades de Pointes) and sudden cardiac death. Psychotropic drugs can affect ventricular repolarization and thus prolong the QT_c interval. The present study sought to investigate the risk factors (pharmacological and non-pharmacological) of severe QT_c prolongation in gerontopsychiatric patients.

Methods

Electrocardiograms of patients on a gerontopsychiatric ward were screened for QT_c prolongation. Medication lists were examined utilizing the AzCERT classification. Potential drug interactions were identified with the electronic drug interaction program mediQ.

Results

The overall prevalence of QT_c prolongation was 13.6%, with 1.9% displaying severe QT_c prolongation (≥ 500 ms). No statistically significant differences between patients with moderate and severe QT_c prolongation were identified; however, patients with severe QT_c prolongation tended to take more drugs (p = 0.063). 92.7% of patients with QT_c prolongation took at least one AzCERT-listed drug, most frequently risperidone and pantoprazole. Risperidone and pantoprazole, along with pipamperone, were also most frequently involved in potential drug interactions. All patients displayed additional risk factors for QT_c prolongation, particularly cardiac diseases.

Conclusion

In addition to the use of potentially QT_c-prolonging drugs, other risk factors, especially cardiac diseases, appear to be relevant for the development of QT_c prolongation in gerontopsychiatric patients. Pantoprazole was frequently involved in potential drug interactions and should generally not be used for more than 8 weeks in geriatric populations. As clinical consequences of QT_c prolongation were rare, potentially QT_c-prolonging drugs should not be used overcautiously; their therapeutic benefit should be considered as well. It is paramount to perform diligent benefit-risk analyses prior to the initiation of potentially QT_c-prolonging drugs and to closely monitor their clinical (side) effects.

Risk assessment tools for QT prolonging pharmacotherapy in older adults: a systematic review

Purpose

Many drugs are associated with the risk of QT prolongation and torsades de pointes (TdP), and different risk assessment tools (RATs) are developed to help clinicians to manage related risk. The aim of this systematic review was to summarize the evidence of different RATs for QT prolonging pharmacotherapy.

Methods

A systematic review was conducted using PubMed and Scopus databases. Studies concerning risk assessment tools for QT prolonging pharmacotherapy, including older adults, were included. Screening and selection of the studies, data extraction, and risk of bias assessment were undertaken.

Results

A total of 21 studies were included, involving different risk assessment tools. Most commonly used tools were risk scores (n = 9), computerized physician order entry systems (n = 3), and clinical decision support systems (n = 6). The tools were developed mainly for physicians and pharmacists. Risk scores included a high number of risk factors, both pharmacological and non-pharmacological, for QT prolongation and TdP. The inclusion of patients’ risk factors in computerized physician order entry and clinical decision support systems varied.

Conclusion

Most of the risk assessment tools for QT prolonging pharmacotherapy give a comprehensive overview of patient-specific risks of QT prolongation and TdP and reduce modifiable risk factors and actual events. The risk assessment tools could be better adapted to different health information systems to help in clinical decision-making. Further studies on clinical validation of risk assessment tools with randomized controlled trials are needed.

Supplementary Information

The online version contains supplementary material available at 10.1007/s00228-022-03285-3.

Content Validation of an Algorithm for the Assessment, Management and Monitoring of Drug-Induced QTc Prolongation in the Psychiatric Population

BACKGROUND

QTc interval (QTcI) prolongation leads to serious complications, making it a concern for clinicians. Assessing the risk of QTcI prolongation in the psychiatric population is important because they are exposed to multiple medications known to increase the risk of life-threatening arrhythmias.

AIM

The study aims to validate the content of an algorithm for the assessment, management and monitoring of drug-induced QTc prolongation in the psychiatric population.

METHODOLOGY

Qualitative semi-structured interviews of cardiologists, to gather information regarding their approach in assessing the risk of drug-induced QTc prolongation at the time of prescribing. After the interview, an orientation to the algorithm was provided with a link to a cross-sectional, anonymous survey. The online survey included quantitative and qualitative components to gather feedback on the relevance and appropriateness of each step in the algorithm.

RESULTS

Interview responses were incorporated into 4 themes. Responses indicated a lack of a unified protocol when assessing QTcI prolongation, which supports the need of an algorithm that includes a verified risk scoring tool. Quantitative survey results showed a mean score ranging from 3.08 to 3.67 out of 4 for the appropriateness of the algorithm's steps, 3.08 to 3.58 for the safety and 3.17 to 3.75 for the reliability of references used. Additional analysis using the modified kappa and I-CVI statistical measures indicate high validity of contents and high degree of agreement between raters. As per the open-ended questions, cardiologists supported the implementation of the algorithm; however, they recommended simplification of the steps as they appear to be cumbersome.

CONCLUSION

The results demonstrate that the implementation of the algorithm after minor alterations can prove to be useful as a tool for the risk assessment of QTc prolongation. Further validation of the algorithm with mental health pharmacists and clinicians will be conducted as a separate phase of the study.

Development of a Risk Score for QT Prolongation in the Intensive Care Unit Using Time-Series Electrocardiogram Data and Electronic Medical Records

Objective

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.

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.

Safety of Psychotropic Medications in People With COVID-19: Evidence Review and Practical Recommendations

(Reprinted with permission from the BMC Medicine (2020) 18:215).

Comparison of two algorithms to support medication surveillance for drug-drug interactions between QTc-prolonging drugs

BACKGROUND

QTc-prolongation is an independent risk factor for developing life-threatening arrhythmias. Risk management of drug-induced QTc-prolongation is complex and digital support tools could be of assistance. Bindraban et al. and Berger et al. developed two algorithms to identify patients at risk for QTc-prolongation.

OBJECTIVE

The main aim of this study was to compare the performances of these algorithms for managing QTc-prolonging drug-drug interactions (QT-DDIs).

MATERIALS AND METHODS

A retrospective data analysis was performed. A dataset was created from QT-DDI alerts generated for in- and outpatients at a general teaching hospital between November 2016 and March 2018. ECGs recorded within 7 days of the QT-DDI alert were collected. Main outcomes were the performance characteristics of both algorithms. QTc-intervals of > 500 ms on the first ECG after the alert were taken as outcome parameter, to which the performances were compared. Secondary outcome was the distribution of risk scores in the study cohort.

RESULTS

In total, 10,870 QT-DDI alerts of 4987 patients were included. ECGs were recorded in 26.2 % of the QT-DDI alerts. Application of the algorithms resulted in area under the ROC-curves of 0.81 (95 % CI 0.79-0.84) for Bindraban et al. and 0.73 (0.70-0.75) for Berger et al. Cut-off values of ≥ 3 and ≥ 6 led to sensitivities of 85.7 % and 89.1 %, and specificities of 60.8 % and 44.3 % respectively.

CONCLUSIONS

Both algorithms showed good discriminative abilities to identify patients at risk for QTc-prolongation when using ≥ 2 QTc-prolonging drugs. Implementation of digital algorithms in clinical decision support systems could support the risk management of QT-DDIs.

Managing drug-induced QT prolongation in clinical practice

Many drug therapies are associated with prolongation of the QT interval. This may increase the risk of Torsades de Pointes (TdP), a potentially life-threatening cardiac arrhythmia. As the QT interval varies with a change in heart rate, various formulae can adjust for this, producing a ‘corrected QT’ (QTc) value. Normal QTc intervals are typically <450 ms for men and <460 ms for women. For every 10 ms increase, there is a ~5% increase in the risk of arrhythmic events. When prescribing drugs associated with QT prolongation, three key factors should be considered: patient-related risk factors (eg, female sex, age >65 years, uncorrected electrolyte disturbances); the potential risk and degree of QT prolongation associated with the proposed drug; and co-prescribed medicines that could increase the risk of QT prolongation. To support clinicians, who are likely to prescribe such medicines in their daily practice, we developed a simple algorithm to help guide clinical management in patients who are at risk of QT prolongation/TdP, those exposed to QT-prolonging medication or have QT prolongation.

Safety of psychotropic medications in people with COVID-19: evidence review and practical recommendations

BACKGROUND

The novel coronavirus pandemic calls for a rapid adaptation of conventional medical practices to meet the evolving needs of such vulnerable patients. People with coronavirus disease (COVID-19) may frequently require treatment with psychotropic medications, but are at the same time at higher risk for safety issues because of the complex underlying medical condition and the potential interaction with medical treatments.

METHODS

In order to produce evidence-based practical recommendations on the optimal management of psychotropic medications in people with COVID-19, an international, multi-disciplinary working group was established. The methodology of the WHO Rapid Advice Guidelines in the context of a public health emergency and the principles of the AGREE statement were followed. Available evidence informing on the risk of respiratory, cardiovascular, infective, hemostatic, and consciousness alterations related to the use of psychotropic medications, and drug-drug interactions between psychotropic and medical treatments used in people with COVID-19, was reviewed and discussed by the working group.

RESULTS

All classes of psychotropic medications showed potentially relevant safety risks for people with COVID-19. A set of practical recommendations was drawn in order to inform frontline clinicians on the assessment of the anticipated risk of psychotropic-related unfavorable events, and the possible actions to take in order to effectively manage this risk, such as when it is appropriate to avoid, withdraw, switch, or adjust the dose of the medication.

CONCLUSIONS

The present evidence-based recommendations will improve the quality of psychiatric care in people with COVID-19, allowing an appropriate management of the medical condition without worsening the psychiatric condition and vice versa.