Research Article A Dynamic Model of Rescuer Parameters for Optimizing Blood Gas Delivery during Cardiopulmonary Resuscitation Ali Jalali , 1 Allan F. Simpao , 2 JorgeA.G´ alvez, 2 Robert A. Berg, 2 Vinay M. Nadkarni, 2 and Chandrasekhar Nataraj 3 1 Health Informatics Core, Johns Hopkins All Children’s Hospital, 501 6th Avenue South, St. Petersburg, FL 33701, USA 2 Department of Anesthesiology & Critical Care Medicine, Children’s Hospital of Philadelphia, Perelman School of Medicine at the University of Pennsylvania, 3401 Civic Center Blvd., Philadelphia, PA 19104, USA 3 Villanova Center for Analytics of Dynamic Systems, Department of Mechanical Engineering, Villanova University, Villanova, PA 19085, USA CorrespondenceshouldbeaddressedtoAliJalali;jalali@jhmi.edu Received 29 August 2018; Accepted 11 November 2018; Published 29 November 2018 AcademicEditor:omasDesaive Copyright©2018AliJalalietal.isisanopenaccessarticledistributedundertheCreativeCommonsAttributionLicense,which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Introduction.equalityofcardiopulmonaryresuscitation(CPR)hasbeenshowntoimpactpatientoutcomes.However,post-CPR morbidityandmortalityremainhigh,andCPRoptimizationisanareaofactiveresearch.OneapproachtooptimizingCPRinvolves establishingreliableCPRperformancemeasuresandthenmodifyingCPRparameters,suchascompressionsandventilatorbreaths, toenhancethesemeasures.WeaimedtodefineareliableCPRperformancemeasure,optimizetheCPRperformancebasedonthe definedmeasureanddesignadynamicallyoptimizedschemethatvariesCPRparameterstooptimizeCPRperformance. Materials and Methods.Weselectedtotalbloodgasdelivery(systemicoxygendeliveryandcarbondioxidedeliverytothelungs)asanobjective functionformaximization.CPRparametersweredividedintothreecategories:rescuerdependent,patientdependent,andconstant parameters. Two optimization schemes were developed using simulated annealing method: a global optimization scheme and a sequential optimization scheme. Results and Discussion.VariationsofCPRparametersoverCPRsequences(cycles)wereanalyzed. Across all patient groups, the sequential optimization scheme resulted in significant enhancement in the effectiveness of the CPR procedurewhencomparedtotheglobaloptimizationscheme. Conclusions.Ourstudyillustratesthepotentialbenefitofconsidering dynamic changes in rescuer-dependent parameters during CPR in order to improve performance. e advantage of the sequential optimization technique stemmed from its dynamically adapting effect. Our CPR optimization findings suggest that as CPR progresses,thecompressiontoventilationratioshoulddecrease,andthesequentialoptimizationtechniquecanpotentiallyimprove CPR performance. Validation in vivo is needed before implementing these changes in actual practice. 1. Introduction Cardiopulmonary resuscitation (CPR) involves delivering chest compressions and positive pressure ventilation to car- diac arrest victims to maintain circulatory blood flow and oxygen delivery [1]. Studies have shown that the quality of CPRcanimpactpost-CPRoutcomesandsurvival[2–7].CPR optimizationremainsanactivetopicofresuscitationresearch becausesurvivalratesforpost-CPRhospitalinpatientsremain low [8]. Various approaches have been proposed to modify and optimize the CPR process. Simultaneous ventilation and compressionaswellasinterposedabdominalcompressionare two examples of CPR modification [9–11]. Another approach to optimizing CPR involves defining and establishing reliable, appropriate CPR performance measures and then modifying CPR parameters to enhance these measures. Brain ischemia is a primary contributor to postarrest morbidity; thus, oxygen delivery and carbon di- oxideelimination(end-tidalcarbondioxide[ETCO 2 ])have been established as important factors for measuring CPR performance [12, 13]. Other performance measures include meancoronaryperfusionpressure(CPP),nitricoxide(NO), and balance of systemic and pulmonary perfusion with ventilation [14–17]. e CPR compression to ventilation ratiohasbeenshowntobeaCPRparameterthatinfluences postarrest outcomes [18–21]. Another important CPR Hindawi Computational and Mathematical Methods in Medicine Volume 2018, Article ID 3569346, 6 pages https://doi.org/10.1155/2018/3569346