Estimating ectopic beat probability with simplified statistical models that account for experimental uncertainty

• Published in: PLoS computational biology 2021-10, Vol.17 (10), p.e1009536-e1009536
• Main Authors: Jin, Qingchu, Greenstein, Joseph L, Winslow, Raimond L
• Format: Article
• Language: English
• Subjects: Animals; Arrhythmia; Arrhythmias, Cardiac - physiopathology; Biology and Life Sciences; Calcium (reticular); Calcium - metabolism; Calcium ions; Cardiac arrhythmia; Cardiac muscle; Cell culture; Computational Biology - methods; Computer applications; Congestive heart failure; Diagnosis; Dogs; Heart cells; Heart failure; Mathematical models; Medicine and Health Sciences; Models, Cardiovascular; Models, Statistical; Monte Carlo simulation; Muscle cells; Myocytes; Myocytes, Cardiac - physiology; Parameters; Physical Sciences; Physiological aspects; Probability; Regression analysis; Regression models; Research and Analysis Methods; Ryanodine receptors; Sarcoplasmic reticulum; Sarcoplasmic Reticulum - physiology; Sensitivity analysis; Statistical analysis; Statistical models; Uncertainty
• ISSN: 1553-7358; 1553-734X; 1553-7358
• DOI: 10.1371/journal.pcbi.1009536

Ectopic beats (EBs) are cellular arrhythmias that can trigger lethal arrhythmias. Simulations using biophysically-detailed cardiac myocyte models can reveal how model parameters influence the probability of these cellular arrhythmias, however such analyses can pose a huge computational burden. Here, we develop a simplified approach in which logistic regression models (LRMs) are used to define a mapping between the parameters of complex cell models and the probability of EBs (P(EB)). As an example, in this study, we build an LRM for P(EB) as a function of the initial value of diastolic cytosolic Ca2+ concentration ([Ca2+]iini), the initial state of sarcoplasmic reticulum (SR) Ca2+ load ([Ca2+]SRini), and kinetic parameters of the inward rectifier K+ current (IK1) and ryanodine receptor (RyR). This approach, which we refer to as arrhythmia sensitivity analysis, allows for evaluation of the relationship between these arrhythmic event probabilities and their associated parameters. This LRM is also used to demonstrate how uncertainties in experimentally measured values determine the uncertainty in P(EB). In a study of the role of [Ca2+]SRini uncertainty, we show a special property of the uncertainty in P(EB), where with increasing [Ca2+]SRini uncertainty, P(EB) uncertainty first increases and then decreases. Lastly, we demonstrate that IK1 suppression, at the level that occurs in heart failure myocytes, increases P(EB).