Electrocardiographic Screening for Prolonged QT Interval to Reduce Sudden Cardiac Death in Psychiatric Patients: A Cost-Effectiveness Analysis

Determining sensitivity and specificity of risk scores for QTc interval prolongation in hemato-oncology patients prescribed systemic antifungal therapy: a retrospective cross-sectional study

BACKGROUND

QTc interval prolongation can result in potentially lethal arrhythmias. One risk factor is QTc-prolonging drugs, including some antifungals often used in hemato-oncology patients. Screening tools for patients at risk have not yet been investigated in this patient population.

AIM

Our aim was to evaluate the sensitivity and specificity of five QTc risk scores in hemato-oncology patients receiving systemic antifungal therapy.

METHOD

Data were retrieved from an internal study database including adult hemato-oncology patients prescribed systemic antifungal therapy. Data on QTc-prolonging medication, risk factors for QTc prolongation, and electrocardiograms (ECG) were collected retrospectively for a period of 12 months. The QTc risk scores according to Tisdale, Vandael, Berger, Bindraban, and Aboujaoude as well as their sensitivity and specificity were calculated.

RESULTS

During the evaluated period, 77 patients were prescribed systemic antifungals resulting in 187 therapy episodes. Regarding therapy episodes, median age was 56 years (IQR 44-68), 41% (77) were female, and a median of 3 QTc-prolonging drugs were prescribed (range 0-6). ECGs were available for 45 (24%) of the therapy episodes 3-11 days after initiation of the antifungal therapy, 22 of which showed QTc prolongation. Regarding these 45 therapy episodes, sensitivity and specificity of the risk scores were calculated as follows: Tisdale 86%/22%, Vandael 91%/35%, Berger 32%/83%, Bindraban 50%/78%, Aboujaoude 14%/87%.

CONCLUSION

The QTc risk scores according to Tisdale and Vandael showed sufficient sensitivity for risk stratification in the studied patient population. In contrast, risk scores according to Berger, Bindraban, and Aboujaoude cannot be considered suitable due to poor sensitivity.

A polygenic risk score for the QT interval is an independent predictor of drug-induced QT prolongation

Drug-induced QT prolongation (diLQTS), and subsequent risk of torsade de pointes, is a major concern with use of many medications, including for non-cardiac conditions. The possibility that genetic risk, in the form of polygenic risk scores (PGS), could be integrated into prediction of risk of diLQTS has great potential, although it is unknown how genetic risk is related to clinical risk factors as might be applied in clinical decision-making. In this study, we examined the PGS for QT interval in 2500 subjects exposed to a known QT-prolonging drug on prolongation of the QT interval over 500ms on subsequent ECG using electronic health record data. We found that the normalized QT PGS was higher in cases than controls (0.212±0.954 vs. -0.0270±1.003, P = 0.0002), with an unadjusted odds ratio of 1.34 (95%CI 1.17-1.53, P<0.001) for association with diLQTS. When included with age and clinical predictors of QT prolongation, we found that the PGS for QT interval provided independent risk prediction for diLQTS, in which the interaction for high-risk diagnosis or with certain high-risk medications (amiodarone, sotalol, and dofetilide) was not significant, indicating that genetic risk did not modify the effect of other risk factors on risk of diLQTS. We found that a high-risk cutoff (QT PGS ≥ 2 standard deviations above mean), but not a low-risk cutoff, was associated with risk of diLQTS after adjustment for clinical factors, and provided one method of integration based on the decision-tree framework. In conclusion, we found that PGS for QT interval is an independent predictor of diLQTS, but that in contrast to existing theories about repolarization reserve as a mechanism of increasing risk, the effect is independent of other clinical risk factors. More work is needed for external validation in clinical decision-making, as well as defining the mechanism through which genes that increase QT interval are associated with risk of diLQTS.

Electrocardiogram abnormalities and associated factors among psychiatric patients attending follow up at Jimma Medical Center Psychiatry Clinic, Jimma, Ethiopia: an institution-based cross-sectional study

BACKGROUND

Psychiatric patients have two to three-fold higher risk of cardiovascular morbidity and mortality as compared to the general population. Despite the high rate of cardiovascular disease, about 80% of patients with psychiatric disorders have fewer opportunities for cardiovascular disease screening. Early detection of subclinical cardiovascular disease using an electrocardiogram can improve the clinical outcomes of these patients. However, in Ethiopia, no previous study had been conducted on electrocardiogram abnormalities and associated factors among psychiatric patients. Hence, this study aimed to assess the electrocardiogram abnormalities and associated factors among psychiatric patients attending follow-up at Jimma Medical Center, Jimma, Ethiopia.

METHODS

An institution-based cross-sectional study was carried out among psychiatric patients attending Jimma Medical Center Psychiatry Clinic from October 14 to December 10, 2021. An interviewer-administered structured questionnaire was used to collect socio-demographic data, behavioral factors, disease-related and medication-related data. Anthropometry and blood pressure were measured following the standard protocols. A resting 12 lead ECG was recorded according to the standard recording protocol of the Minnesota code. Data were entered into Epi data version 4.6 and exported to SPSS version 25. Results of the descriptive analysis were summarized by frequencies, means, and proportions, and presented by using tables and figures. Bivariable and multivariable logistic regressions were performed. p value < 0.05 was considered statistically significant.

RESULT

A total of 315 psychiatric patients were included in the present study. The mean age (SD) of the respondents was 36.27 ± 10.85 years. ECG abnormalities were identified among 191 (60.6%) respondents. Age older than 40 years [AOR = 3.31: 95% CI 1.58-6.89], treatment with antipsychotics [AOR = 4.16: 95% CI 1.25-13.79], polytherapy [AOR = 3.13: 95% CI 1.15-8.62], having schizophrenia [AOR = 3.11: 95% CI 1.20-8.11], and illness duration of > 10 years [AOR = 4.25: 95% CI 1.72-10.49] were significantly associated with ECG abnormalities.

CONCLUSIONS

In the present study, six out of ten respondents had ECG abnormalities. Age of the respondents, treatment with antipsychotics, having schizophrenia, polytherapy and illness duration of > 10 years were significant predictors of ECG abnormalities. Routine ECG investigation should be performed in the psychiatry treatment setting and further studies are recommended to delineate factors affecting ECG abnormalities.

The Use of Expert Elicitation among Computational Modeling Studies in Health Research: A Systematic Review

BACKGROUND

Expert elicitation (EE) has been used across disciplines to estimate input parameters for computational modeling research when information is sparse or conflictual.

OBJECTIVES

We conducted a systematic review to compare EE methods used to generate model input parameters in health research.

DATA SOURCES

PubMed and Web of Science.

STUDY ELIGIBILITY

Modeling studies that reported the use of EE as the source for model input probabilities were included if they were published in English before June 2021 and reported health outcomes.

DATA ABSTRACTION AND SYNTHESIS

Studies were classified as "formal" EE methods if they explicitly reported details of their elicitation process. Those that stated use of expert opinion but provided limited information were classified as "indeterminate" methods. In both groups, we abstracted citation details, study design, modeling methodology, a description of elicited parameters, and elicitation methods. Comparisons were made between elicitation methods.

STUDY APPRAISAL

Studies that conducted a formal EE were appraised on the reporting quality of the EE. Quality appraisal was not conducted for studies of indeterminate methods.

RESULTS

The search identified 1520 articles, of which 152 were included. Of the included studies, 40 were classified as formal EE and 112 as indeterminate methods. Most studies were cost-effectiveness analyses (77.6%). Forty-seven indeterminate method studies provided no information on methods for generating estimates. Among formal EEs, the average reporting quality score was 9 out of 16.

LIMITATIONS

Elicitations on nonhealth topics and those reported in the gray literature were not included.

CONCLUSIONS

We found poor reporting of EE methods used in modeling studies, making it difficult to discern meaningful differences in approaches. Improved quality standards for EEs would improve the validity and replicability of computational models.

HIGHLIGHTS

We find extensive use of expert elicitation for the development of model input parameters, but most studies do not provide adequate details of their elicitation methods.Lack of reporting hinders greater discussion of the merits and challenges of using expert elicitation for model input parameter development.There is a need to establish expert elicitation best practices and reporting guidelines.

Improving Corrected QT Interval Monitoring in Critical Care Units: A Single Center Report

BACKGROUND

Corrected QT (QTc) interval prolongation is a type of ventricular tachyarrhythmia. Recommendations for QTc interval monitoring for critical care nurses are limited and variable.

LOCAL PROBLEM

The intensive care unit at the study institution had no policies for QTc interval monitoring. A quality improvement initiative for identifying and monitoring at-risk patients was begun.

METHODS

A QTc interval monitoring protocol was developed according to current recommendations for electrocardiogram monitoring and input from experts. Nursing staff received education on the QTc monitoring protocol. Numbers of patients with indications for monitoring were collected for 60 days before and 60 days after implementation. The rate of protocol adherence was collected for 60 days after implementation. Aknowledge assessment was administered to nurses at baseline, immediately after education, and 4 months after education.

RESULTS

Before protocol implementation, 537 patients had indications for monitoring. No QTc intervals were documented by nurses. After protocol implementation, 544 patients had indications for monitoring. Protocol adherence was higher during day shifts than during night shifts (45.3% and 38.4%, respectively). Of 170 documented QTc prolongation events, 26 (15%) were reported to physicians. Nurses' knowledge significantly improved after education and was retained 4 months after education (correct responses to assessment questions: 59% at baseline, 96% immediately after education, and 86% at 4 months after education).

CONCLUSIONS

This QTc interval monitoring protocol improved nurses' ability to identify and monitor patients with increased risk of QTc interval prolongation. Adherence was less than desired, suggesting that further protocol revisions are required.

Drug-Induced QTc Prolongation: What We Know and Where We Are Going

Drug-induced QTc prolongation is a concerning electrocardiogram (ECG) abnormality. This cardiac disturbance carries a 10% risk of sudden cardiac death due to the malignant arrhythmia, Torsades de Pointes. The Arizona Center for Education and Research on Therapeutics (AzCERT) has classified QTc prolonging therapeutic classes such as antiarrhythmics, antipsychotics, anti-infectives, and others. AzCERT criteria categorizes medications into three risk categories: "known," "possible," and "conditional risk" of QTc prolongation and Torsades de Pointes. The list of QTc prolonging medications continues to expand as new drug classes are approved and studied. Risk factors for QTc prolongation can be delineated into modifiable or non-modifiable. A validated risk scoring tool may be utilized to predict the likelihood of prolongation in patients receiving AzCERT classified medication. The resultant risk score may be applied to a clinical decision support system which offers mitigation strategies. Mitigation strategies including discontinuation of possible offending agents with selection of an alternative agent, assessment of potential drug interactions or dose adjustments through pharmacokinetic and pharmacodynamic monitoring, and initiation of both ECG and electrolyte monitoring are essential to prevent a drug-induced arrhythmia. The challenges presented by the COVID-19 pandemic have led to the development of innovative continuous monitoring technology, increasing protection for both patients and healthcare workers. Early intervention strategies may reduce adverse events and improve clinical outcomes in patients identified to be at risk of QTc prolongation.

Developing a reference protocol for structured expert elicitation in health-care decision-making: a mixed-methods study

BACKGROUND

Many decisions in health care aim to maximise health, requiring judgements about interventions that may have higher health effects but potentially incur additional costs (cost-effectiveness framework). The evidence used to establish cost-effectiveness is typically uncertain and it is important that this uncertainty is characterised. In situations in which evidence is uncertain, the experience of experts is essential. The process by which the beliefs of experts can be formally collected in a quantitative manner is structured expert elicitation. There is heterogeneity in the existing methodology used in health-care decision-making. A number of guidelines are available for structured expert elicitation; however, it is not clear if any of these are appropriate for health-care decision-making.

OBJECTIVES

The overall aim was to establish a protocol for structured expert elicitation to inform health-care decision-making. The objectives are to (1) provide clarity on methods for collecting and using experts' judgements, (2) consider when alternative methodology may be required in particular contexts, (3) establish preferred approaches for elicitation on a range of parameters, (4) determine which elicitation methods allow experts to express uncertainty and (5) determine the usefulness of the reference protocol developed.

METHODS

A mixed-methods approach was used: systemic review, targeted searches, experimental work and narrative synthesis. A review of the existing guidelines for structured expert elicitation was conducted. This identified the approaches used in existing guidelines (the 'choices') and determined if dominant approaches exist. Targeted review searches were conducted for selection of experts, level of elicitation, fitting and aggregation, assessing accuracy of judgements and heuristics and biases. To sift through the available choices, a set of principles that underpin the use of structured expert elicitation in health-care decision-making was defined using evidence generated from the targeted searches, quantities to elicit experimental evidence and consideration of constraints in health-care decision-making. These principles, including fitness for purpose and reflecting individual expert uncertainty, were applied to the set of choices to establish a reference protocol. An applied evaluation of the developed reference protocol was also undertaken.

RESULTS

For many elements of structured expert elicitation, there was a lack of consistency across the existing guidelines. In almost all choices, there was a lack of empirical evidence supporting recommendations, and in some circumstances the principles are unable to provide sufficient justification for discounting particular choices. It is possible to define reference methods for health technology assessment. These include a focus on gathering experts with substantive skills, eliciting observable quantities and individual elicitation of beliefs. Additional considerations are required for decision-makers outside health technology assessment, for example at a local level, or for early technologies. Access to experts may be limited and in some circumstances group discussion may be needed to generate a distribution.

LIMITATIONS

The major limitation of the work conducted here lies not in the methods employed in the current work but in the evidence available from the wider literature relating to how appropriate particular methodological choices are.

CONCLUSIONS

The reference protocol is flexible in many choices. This may be a useful characteristic, as it is possible to apply this reference protocol across different settings. Further applied studies, which use the choices specified in this reference protocol, are required.

FUNDING

This project was funded by the NIHR Health Technology Assessment programme and will be published in full in Health Technology Assessment; Vol. 25, No. 37. See the NIHR Journals Library website for further project information. This work was also funded by the Medical Research Council (reference MR/N028511/1).

Assessing Prescriber Behavior with a Clinical Decision Support Tool to Prevent Drug-Induced Long QT Syndrome

OBJECTIVE

Clinical decision support (CDS) alerts built into the electronic health record (EHR) have the potential to reduce the risk of drug-induced long QT syndrome (diLQTS) in susceptible patients. However, the degree to which providers incorporate this information into prescription behavior and the impact on patient outcomes is often unknown.

METHODS

We examined provider response data over a period from October 8, 2016 until November 8, 2018 for a CDS alert deployed within the EHR from a 13-hospital integrated health care system that fires when a patient with a QTc ≥ 500 ms within the past 14 days is prescribed a known QT-prolonging medication. We used multivariate generalized estimating equations to analyze the impact of therapeutic alternatives, relative risk of diLQTS for specific medications, and patient characteristics on provider response to the CDS and overall patient mortality.

RESULTS

The CDS alert fired 15,002 times for 7,510 patients for which the most common response (51.0%) was to override the alert and order the culprit medication. In multivariate models, we found that patient age, relative risk of diLQTS, and presence of alternative agents were significant predictors of adherence to the CDS alerts and that nonadherence itself was a predictor of mortality. Risk of diLQTS and presence of an alternative agent are major factors in provider adherence to a CDS to prevent diLQTS; however, provider nonadherence was associated with a decreased risk of mortality.

CONCLUSION

Surrogate endpoints, such as provider adherence, can be useful measures of CDS value but attention to hard outcomes, such as mortality, is likely needed.

Prediction of Drug-Induced Long QT Syndrome Using Machine Learning Applied to Harmonized Electronic Health Record Data

BACKGROUND

Drug-induced QT prolongation is a potentially preventable cause of morbidity and mortality, however there are no widespread clinical tools utilized to predict which individuals are at greatest risk. Machine learning (ML) algorithms may provide a method for identifying these individuals, and could be automated to directly alert providers in real time.

OBJECTIVE

This study applies ML techniques to electronic health record (EHR) data to identify an integrated risk-prediction model that can be deployed to predict risk of drug-induced QT prolongation.

METHODS

We examined harmonized data from the UCHealth EHR and identified inpatients who had received a medication known to prolong the QT interval. Using a binary outcome of the development of a QTc interval >500 ms within 24 hours of medication initiation or no ECG with a QTc interval >500 ms, we compared multiple machine learning methods by classification accuracy and performed calibration and rescaling of the final model.

RESULTS

We identified 35,639 inpatients who received a known QT-prolonging medication and an ECG performed within 24 hours of administration. Of those, 4,558 patients developed a QTc > 500 ms and 31,081 patients did not. A deep neural network with random oversampling of controls was found to provide superior classification accuracy (F1 score 0.404; AUC 0.71) for the development of a long QT interval compared with other methods. The optimal cutpoint for prediction was determined and was reasonably accurate (sensitivity 71%; specificity 73%).

CONCLUSIONS

We found that deep neural networks applied to EHR data provide reasonable prediction of which individuals are most susceptible to drug-induced QT prolongation. Future studies are needed to validate this model in novel EHRs and within the physician order entry system to assess the ability to improve patient safety.

Prevalence of QTc interval prolongation and its associated risk factors among psychiatric patients: a prospective observational study

BACKGROUND

QT interval prolongation is a growing concern worldwide, posing psychiatric patients to life-threatening fatal arrhythmias i.e., torsade de pointes. This study aimed to identify the prevalence of QT interval prolongation, its associated risk factors and prescribing patterns of QT prolonging drugs among psychiatric patients.

METHOD

A prospective observational study was conducted that included psychiatric patients from a tertiary care hospital and a psychiatry clinic in Peshawar, Khyber Pakhtunkhwa, Pakistan. Electrocardiogram was recorded of those patients who were using psychotropic medications for ≥7 days, aged 18 years or more, and of either gender, male or female. The Fredericia correction formula was used for measuring QTc values (corrected QT). Chi-square test was applied to estimate differences between patients with or without prolonged QTc interval whereas, logistic regression analysis was performed to identify various predictors of QT interval prolongation.

RESULTS

Out of 405 patients, the QTc interval was prolonged in 23 (5.7%) patients including 1 (0.2%) patient with highly abnormal prolonged QTc interval (> 500 ms). QT drugs (91.6%), female sex (38.7%) and hypertension (10.6%) were the most common QT prolonging risk factors. Prolonged QTc interval was significantly higher among male patients (p = 0.007).

CONCLUSION

In the present study, QT interval prolongation was observed in a considerable number of psychiatric patients. While, the high prevalence of QT prolonging risk factors among these patients warrants the increased risk of fatal arrhythmias. Therefore, risk assessment and electrocardiographic monitoring, and prescription of safer alternatives are highly recommended.

Population Prevalence and Correlates of Prolonged QT Interval: Cross-Sectional, Population-Based Study From Rural Uganda

OBJECTIVES

We aimed to estimate the prevalence and correlates of QT interval prolongation in rural Uganda.

BACKGROUND

Major electrocardiographic abnormalities, including prolonged QT interval, have been shown to be independently predictive of adverse cardiovascular events among Western populations. Cardiovascular diseases are on the rise in sub-Saharan Africa with poorly characterized context-specific risk factors. An important question is whether ECG screening might have value in cardiovascular disease risk stratification in SSA.

METHODS

We conducted a cross-sectional survey in a sample of adults participating in an ongoing whole-population cohort in Mbarara, Uganda, in 2015. Of 1,814 subjects enrolled in the parent whole-population cohort, 856 (47%) participated in the study. Participants completed 12-lead electrocardiography and cardiovascular disease risk factors assessment. We summarized sex-specific, heart rate variation-adjusted QT (QTa) defining prolonged QTa as >460 ms in women and >450 ms in men. We fit linear and logistic regression models to estimate correlates of (continuous) QTa interval length and (dichotomous) prolonged QTa. Models included inverse probability of sampling weights to generate population-level estimates accounting for study nonparticipation.

RESULTS

We assessed data from 828 participants with electrocardiograms. The weighted population mean age was 38.4 years (95% confidence interval: 36.3-40.4). The weighted population was 50.4% female, 11.5% had elevated blood pressure, and 57.6% had a high-sensitivity C-reactive protein >1 mg/dl. The population mean QTa was 409.1 ms (95% confidence interval: 405.1-413.1), and 10.3% (95% confidence interval: 7.8-13.5) met criteria for prolonged QTa. Women had a higher mean QTa (421.6 ms vs. 396.3 ms; p < 0.001), and a higher proportion of women had a prolonged QTa (14.0% vs. 9.3%; p = 0.122) than did men. In multivariable-adjusted regression models, female sex and hypertension correlated with higher mean QTa and meeting criteria for prolonged QTa, respectively.

CONCLUSIONS

QT interval prolongation is highly prevalent in rural Uganda and may be more common than in high-income settings. Female sex, age, and high blood pressure correlated with QT interval prolongation. Future work should assess whether genetic predisposition or environmental factors in sub-Saharan African populations contribute to prolonged QT and clarify consequences.

A literature-based algorithm for the assessment, management, and monitoring of drug-induced QTc prolongation in the psychiatric population

BACKGROUND

Certain psychotropics and a number of other medications used to treat medical conditions in psychiatric patients can increase the risk of prolonging the corrected QT (QTc) interval on the electrocardiogram, which puts patients at risk of life-threatening ventricular arrhythmias such as torsades de pointes. Pharmacists are often consulted about medications which are known to prolong the QTc interval. Although this information is often accessible, advising how to identify, assess, manage, and refer psychiatric patients at risk for drug-induced QTc prolongation is more challenging.

OBJECTIVES

The objective of this project was first to review the literature, which describes guidelines and recommendations for the assessment and management of drug-induced QTc prolongation, and then to design an algorithm to be used by pharmacists working closely with mental health professionals or who provide care to psychiatric patients.

METHODS

A review of the literature was undertaken. Predefined keywords were used to perform the database search in MEDLINE, EMBASE, and International Pharmaceutical Abstracts to identify reviews, reports and guidelines on the assessment, prevention and monitoring of drug-induced QTc prolongation with an emphasis on psychotropic medications and management in the psychiatric population.

RESULTS

The electronic database search retrieved 637 relevant citations. These were initially screened by title and all duplicates were removed. The abstracts were then reviewed for relevancy based on the inclusion/exclusion criteria. Additional citations were retrieved from the bibliography of the articles identified in the initial search. A total of 79 articles describing QTc prolongation in the psychiatric population were thoroughly examined, but only 31 articles were selected to guide the development of the algorithm.

CONCLUSION

The literature-based algorithm developed provides a stepped-based approach for the assessment, monitoring, and management of drug-induced QTc prolongation in the psychiatric population. The algorithm may assist mental health clinicians in the decision-making process when psychiatric patients are prescribed medications known to increase the QTc interval.

Prevalence of ECG abnormalities and risk factors for QTc interval prolongation in hospitalized psychiatric patients

BACKGROUND

Psychiatric patients are at risk of cardiovascular diseases, and many psychotropic drugs can prolong QTc interval. Requirements for electrocardiogram (ECG) monitoring have been set up in our psychiatric university hospital. The objective of this study was to determine the proportion of adult patients who had an ECG during their hospitalization, the prevalence of ECG abnormalities, the evolution of the QTc after admission, and the risk factors for QTc prolongation.

METHODS

Retrospective analysis of ECGs and clinical data of all patients with a complete hospitalization in 2015. Assessment of the influence of covariates on QTc using linear mixed-effects models.

RESULTS

At least one ECG (n = 600) was performed during 37.6% of the stays (n = 1198) and in 45.5% of the patients (n = 871). Among the patients with an ECG, 17.9% had significant ECG abnormalities, including 7.6% with a prolonged QTc. QTc measured at admission and during hospitalization did not change significantly (n = 46, 419.4 ± 29.7 ms, 417.2 ± 27.6 ms, p = 0.71). In the multivariate model (292 patients, 357 ECGs), the covariates significantly associated with the QTc were gender (+15.9 ms if female, p < 0.0001), age (+0.4 ms/year, p = 0.0001), triglyceride levels (+5.7 ms/mmol/l, p = 0.005), and drugs with known risk of torsades de pointes (+6.2 ms if ⩾1 drug, p = 0.028).

CONCLUSIONS

The prevalence of hospitalized psychiatric patients with an abnormal ECG indicates that ECGs should be performed systematically in this population. Prescription of psychotropic drugs should be done cautiously, particularly in patients with QTc prolongation risk factors.

Cardiovascular Safety of Psychiatric Agents: A Cautionary Tale

Psychiatric agents are among the most commonly prescribed medications. Despite the advent of newer generation agents, patients receiving them still experience cardiovascular (CV) side effects. However, these agents may have heterogeneous properties, calling for an individualized approach based on efficacy and also on the particular side effect profile of each specific agent. Proarrhythmic effects arising from drug-induced long-QT syndrome and consequent potentially life-threatening polymorphic ventricular arrhythmias in the form of torsade de pointes, the metabolic syndrome contributing to atherosclerosis and acute coronary syndromes, and drug-induced orthostatic hypotension raise major concerns. Of course, it is also crucial that fear of potential CV adverse effects does not deprive psychiatric patients of appropriate drug therapy. Modification of CV risk factors in psychiatric patients together with optimal management of their CV diseases and appropriate selection of psychotropic agents with greater efficacy and least CV toxicity are of paramount importance in mitigating CV risks and enhancing safety. Identifying patients at high risk of CV complications and close monitoring of all patients receiving these agents are crucial steps to prevent and manage such complications. All these issues are herein reviewed, relevant guidelines are discussed, and schemas are depicted that illustrate the interrelated connections among the psychotropic agents and their CV effects.

Experiences of Structured Elicitation for Model-Based Cost-Effectiveness Analyses

BACKGROUND

Empirical evidence supporting the cost-effectiveness estimates of particular health care technologies may be limited, or it may even be missing entirely. In these situations, additional information, often in the form of expert judgments, is needed to reach a decision. There are formal methods to quantify experts' beliefs, termed as structured expert elicitation (SEE), but only limited research is available in support of methodological choices. Perhaps as a consequence, the use of SEE in the context of cost-effectiveness modelling is limited.

OBJECTIVES

This article reviews applications of SEE in cost-effectiveness modelling with the aim of summarizing the basis for methodological choices made in each application and recording the difficulties and challenges reported by the authors in the design, conduct, and analyses.

METHODS

The methods used in each application were extracted along with the criteria used to support methodological and practical choices and any issues or challenges discussed in the text. Issues and challenges were extracted using an open field, and then categorised and grouped for reporting.

RESULTS

The review demonstrates considerable heterogeneity in methods used, and authors acknowledge great methodological uncertainty in justifying their choices. Specificities of the context area emerging as potentially important in determining further methodological research in elicitation are between- expert variation and its interpretation, the fact that substantive experts in the area may not be trained in quantitative subjects, that judgments are often needed on various parameter types, the need for some form of assessment of validity, and the need for more integration with behavioural research to devise relevant debiasing strategies.

CONCLUSIONS

This review of experiences of SEE highlights a number of specificities/constraints that can shape the development of guidance and target future research efforts in this area.

Cost-effectiveness of HLA-DQB1/HLA-B pharmacogenetic-guided treatment and blood monitoring in US patients taking clozapine

Less than 1% of adult patients with schizophrenia taking clozapine develop agranulocytosis, and most of these cases occur within the first weeks of treatment. The human leukocyte antigen (HLA) region has been associated with genetic susceptibility to clozapine-induced agranulocytosis (single amino acid changes in HLA-DQB1 (126Q) and HLA-B (158T)). The current study aimed to evaluate the cost-effectiveness, from a healthcare provider’s perspective, of an HLA genotype-guided approach in patients with treatment-resistant schizophrenia who were taking clozapine and to compare the results with the current absolute neutrophil count monitoring (ANCM) schemes used in the USA. A semi-Markovian model was developed to simulate the progress of a cohort of adult men and women who received clozapine as a third-line antipsychotic medication. We compared current practices using two genotype-guided strategies: (1) HLA genotyping followed by clozapine, with ANCM only for patients who tested positive for one or both alleles (genotype-guided blood sampling); (2) HLA genotyping followed by clozapine for low-risk patients and alternative antipsychotics for patients who tested positive (clozapine substitution scheme). Up to a decision threshold of $3.9 million per quality-adjusted life-year (90-fold the US gross domestic product per capita), the base-case results indicate that compared with current ANCM, genotype-guided blood sampling prior to clozapine initiation appeared cost-effective for targeted blood monitoring only in patients with HLA susceptibility alleles. Sensitivity analysis demonstrated that at a cost of genotype testing of up to USD700, HLA genotype-guided blood monitoring remained a cost-effective strategy compared with either current ANCM or clozapine substitution.

Risk Management of Hospitalized Psychiatric Patients Taking Multiple QTc-Prolonging Drugs

PURPOSE/BACKGROUND

Drug-related QTc prolongation has been linked with Torsade de Pointes and sudden cardiac death. The objective of this study was to investigate the impact of starting an additional QTc-prolonging drug on the QTc interval of psychiatric inpatients.

METHODS

An observational study was performed between May 2011 and December 2014 in 6 Belgian psychiatric hospitals. Inpatients who were already taking 1 QTc-prolonging drug or more could be included in the study when an additional QTc-prolonging drug was started. Electrocardiograms were performed at baseline and follow-up. Demographic, medical, medication, and laboratory data were collected. A risk score was used to estimate the risk of QTc prolongation based on patient-specific risk factors. A cutoff value of 8 points was set as high risk for QTc prolongation.

RESULTS

One hundred fifty-two patients (44.7% women; mean age, 44 [SD, 17] years) were included who received a prescription for an additional QTc-prolonging drug. There was a small but significant difference (P = 0.032) in mean QTc interval between baseline (409.1 [SD, 21.8] milliseconds) and follow-up (411.8 [SD, 21.7] milliseconds). Three patients developed a prolonged QTc interval in the follow-up electrocardiogram (QTc, ≥450 [men]/470 [women] milliseconds); 8 patients had a delta QTc of 30 milliseconds or longer. No cases of torsade de pointes or sudden cardiac death were identified. Fifty-eight patients (38.2%) had a risk score of 8 or higher; these patients had a significantly longer QTc interval at follow-up than did patients with a risk score of lower than 8 (P < 0.001).

IMPLICATIONS/CONCLUSIONS

Only a limited number of patients developed a prolonged QTc interval after the start of an additional QTc-prolonging drug. Nevertheless, it is still important to screen for high-risk patients at baseline. A risk score can help to select high-risk patients and to stimulate an appropriate and feasible risk management of QTc prolongation in psychiatry.

Evaluation of the use of electrocardiogram monitoring in patients on psychotropic medications that have a risk of QT prolongation

Introduction:

Many psychotropic medications carry a risk of prolonging the QT interval and increasing the risk of developing Torsade de pointes (TdP). The goal of this study was to evaluate whether patients taking psychotropic agents with a known risk of TdP are being monitored at a community hospital through the use of electrocardiograms (EKGs).

Methods:

This was a retrospective chart review of 100 adult patients—50 from general medicine floors and 50 from psychiatric units—who were taking at least one psychotropic agent with a known risk of TdP during hospitalization.

Results:

The mean number of medications with QT-prolongation risk administered to the psychiatric and general medicine patients was 4.2 ± 1.7 and 3.9 ± 2.0, respectively (P = .7484). Thirty-two of the psychiatric patients (64%) and 48 of the general medicine patients (96%) received EKGs during their hospitalization (P < 0.0001). Of those newly starting the target medications, 58% (18 of 31) of the psychiatric patients and 71% (5 of 7) of the general medicine patients received a baseline EKG. The difference was not statistically significant (P = .6807). Overall, 8 patients (8%) had corrected QT (QTc) intervals >500 ms. Four had repeat EKGs performed, and none had medication changes made to decrease TdP risk.

Discussion:

Many inpatients on psychiatric medications received multiple medications with a risk of TdP, but not all received monitoring through baseline or repeat EKGs when warranted. Patients with QTc intervals >500 ms were not appropriately managed to lower their risk of TdP. Pharmacists thus can help improve the monitoring and management of QT prolongation.

Drug safety of macrolide and quinolone antibiotics in a tertiary care hospital: administration of interacting co-medication and QT prolongation

PURPOSE

Some macrolide and quinolone antibiotics (MQABs) are associated with QT prolongation and life-threatening torsade de pointes (TdP) arrhythmia. MQAB may also inhibit cytochrome P450 isoenzymes and thereby cause pharmacokinetic drug interactions (DDIs). There is limited data on the frequency and management of such risks in clinical practice. We aimed to quantify co-administration of MQAB with interacting drugs and associated adverse drug reactions.

METHODS

We conducted an observational study within our pharmacoepidemiological database derived from electronic medical records of a tertiary care hospital. Among all users of MQAB associated with TdP, we determined the prevalence of additional QT-prolonging drugs and risk factors and identified contraindicated co-administrations of simvastatin, atorvastatin, or tizanidine. Electrocardiographic (ECG) monitoring and associated adverse events were validated in medical records.

RESULTS

Among 3444 administered courses of clarithromycin, erythromycin, azithromycin, ciprofloxacin, levofloxacin, or moxifloxacin, there were 1332 (38.7 %) with concomitant use of additional QT-prolonging drugs. Among those, we identified seven cases of drug-related QT prolongation, but 49.1 % had no ECG monitoring. Of all MQAB users, 547 (15.9 %) had hypokalemia. Forty-four MQAB users had contraindicated co-administrations of simvastatin, atorvastatin, or tizanidine and three of those related adverse drug reactions.

CONCLUSION

In the studied real-life setting, we found a considerable number of MQAB users with additional risk factors for TdP but no ECG monitoring. However, adverse drug reactions were rarely found, and costs vs. benefits of ECG monitoring have to be weighted. In contrast, avoidable risk factors and selected contraindicated pharmacokinetic interactions are clear targets for implementation as automated alerts in electronic prescribing systems.