Biology subjects

Newton-Cheh, C.

Publications and source records attributed to Newton-Cheh, C..

4 recordsLinked to original sources

bioRxiv2019

Multicenter Analysis of Dosing Protocols for Sotalol Initiation

Sotalol is a Vaughan-Williams Class III antiarrhythmic medication that is commonly used in the management of both atrial and ventricular arrhythmias. Like others in this class, sotalol carries a risk of the potentially lethal arrhythmia torsade de pointes due to its effect of prolonging the QT interval on ECG. For this reason, many centers admit patients for telemetry monitoring during the initial 2-3 days of dosing. However, despite its widespread use, little information is available about the dosing protocols used during this initiation process. In this multicenter investigation, we examine the characteristics of various dose protocols in 213 patients who initiated sotalol over a 4-year period. Of these patients, over 90% were able to successfully complete the dosing regimen (i.e., were discharged on the medication). Significant bradycardia, excessive QT prolongation, and ineffectiveness were the main reasons for failed completion. We found that any dose adjustment was one of the strongest univariate predictors of successful initiation (OR 6.6, 95%CI 1.3 - 32.7, p = 0.021), while initial dose, indication, and resting heart rate or QT interval on baseline ECG did not predict successful initiation. Several predictors of any dose adjustment were identified, and included diabetes, hypertension, presence of pacemaker, heart failure diagnosis, and depressed LV ejection fraction. Using marginal structural models (i.e., inverse probability weighting based on probability of a dose adjustment), we verified that these factors also predicted successful initiation via preventing any dose adjustment, and suggests that consideration of these factors may result in higher likelihood of successful initiation in future investigations. In conclusion, we found that the majority of patients admitted for sotalol initiation are successfully discharged on the medication, often without a single adjustment in the dose. Our findings suggest that several factors predicting lack of dose adjustment could be used clinically to identify patients who could potentially undergo outpatient initiation, although prospective studies are needed to verify this approach.

pharmacology and toxicology↗

bioRxiv2019

Applications of Machine Learning in Decision Analysis for Dose Management for Dofetilide

Initiation of the antiarrhythmic medication dofetilide requires an FDA-mandated 3 days of telemetry monitoring due to heightened risk of toxicity within this time period. Although a recommended dose management algorithm for dofetilide exists, there is a range of real-world approaches to dosing the medication. In this multicenter investigation, we examined the decision process for dose adjustment of dofetilide during the observation period using machine-learning approaches, including supervised, unsupervised, and reinforcement learning applications. Logistic regression approaches identified any dose-adjustment as a strong negative predictor of successful loading (i.e., discharged on dofetilide) of the medication (OR 0.19, 95%CI 0.12 - 0.31, p < 0.001 for discharge on dofetilide), indicating that these adjustments are strong determinants of whether patients "tolerate" the medication. Using multiple supervised approaches, including regularized logistic regression, random forest, boosted gradient decision trees, and neural networks, we were unable to identify any model that predicted dose adjustments better than a naive approach. A reinforcement-learning algorithm, in contrast, predicted which patient characteristics and dosing decisions that resulted in the lowest risk of failure to be discharged on the medication. Future studies could apply this algorithm prospectively to examine improvement over standard approaches.

pharmacology and toxicology↗

bioRxiv2017

A Comprehensive Evaluation of the Genetic Architecture of Sudden Cardiac Arrest

BackgroundSudden cardiac arrest (SCA) accounts for 10% of adult mortality in Western populations. While several risk factors are observationally associated with SCA, the genetic architecture of SCA in the general population remains unknown. Furthermore, understanding which risk factors are causal may help target prevention strategies.\n\nMethodsWe carried out a large genome-wide association study (GWAS) for SCA (n=3,939 cases, 25,989 non-cases) to examine common variation genome-wide and in candidate arrhythmia genes. We also exploited Mendelian randomization methods using cross-trait multi-variant genetic risk score associations (GRSA) to assess causal relationships of 18 risk factors with SCA.\n\nResultsNo variants were associated with SCA at genome-wide significance, nor were common variants in candidate arrhythmia genes associated with SCA at nominal significance. Using cross-trait GRSA, we established genetic correlation between SCA and (1) coronary artery disease (CAD) and traditional CAD risk factors (blood pressure, lipids, and diabetes), (2) height and BMI, and (3) electrical instability traits (QT and atrial fibrillation), suggesting etiologic roles for these traits in SCA risk.\n\nConclusionsOur findings show that a comprehensive approach to the genetic architecture of SCA can shed light on the determinants of a complex life-threatening condition with multiple influencing factors in the general population. The results of this genetic analysis, both positive and negative findings, have implications for evaluating the genetic architecture of patients with a family history of SCA, and for efforts to prevent SCA in highrisk populations and the general community.

genetics↗

bioRxiv2017

Genome-wide analysis yields new loci associating with aortic valve stenosis

Aortic valve stenosis (AS) is the most common valvular heart disease, characterized by a thickened and calcified valve causing left ventricular outflow obstruction. Severe AS is a significant cause of morbidity and mortality, affecting approximately 5% of those over 70 years of age1,2,3. Little is known about the genetics of AS, although recently a variant at the LPA locus4 and a rare MYH6 missense variant were found to associate with AS5. We report a large genome-wide association study (GWAS) with a follow-up in up to 7,307 AS cases and 801,073 controls. We identified two new AS loci, on chromosome 1p21 near PALMD (rs7543130; OR=1.20, P=1.2x10-22) and on chromosome 2q22 in TEX41 (rs1830321; OR=1.15, P=1.8x10-13). Rs7543130 also associates with bicuspid aortic valve (BAV) (OR=1.28, P=6.6x10-10) and aortic root diameter (P=1.30x10-8) and rs1830321 associates with BAV (OR=1.12, P=5.3x10-3 and coronary artery disease (CAD) (OR=1.05, P=9.3x10-5). These results indicate that AS is partly rooted in the same processes as cardiac development and atherosclerosis.

genetics↗