{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,2,21]],"date-time":"2025-02-21T14:25:20Z","timestamp":1740147920022,"version":"3.37.3"},"reference-count":31,"publisher":"Wiley","license":[{"start":{"date-parts":[[2018,11,29]],"date-time":"2018-11-29T00:00:00Z","timestamp":1543449600000},"content-version":"unspecified","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/100000002","name":"National Institutes of Health","doi-asserted-by":"publisher","award":["1 R01 NS 72338 01A1"],"award-info":[{"award-number":["1 R01 NS 72338 01A1"]}],"id":[{"id":"10.13039\/100000002","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Computational and Mathematical Methods in Medicine"],"published-print":{"date-parts":[[2018,11,29]]},"abstract":"<jats:p><jats:italic>Introduction<\/jats:italic>. The quality of cardiopulmonary resuscitation (CPR) has been shown to impact patient outcomes. However, post-CPR morbidity and mortality remain high, and CPR optimization is an area of active research. One approach to optimizing CPR involves establishing reliable CPR performance measures and then modifying CPR parameters, such as compressions and ventilator breaths, to enhance these measures. We aimed to define a reliable CPR performance measure, optimize the CPR performance based on the defined measure and design a dynamically optimized scheme that varies CPR parameters to optimize CPR performance. <jats:italic>Materials and Methods<\/jats:italic>. We selected total blood gas delivery (systemic oxygen delivery and carbon dioxide delivery to the lungs) as an objective function for maximization. CPR parameters were divided into three categories: rescuer dependent, patient dependent, and constant parameters. Two optimization schemes were developed using simulated annealing method: a global optimization scheme and a sequential optimization scheme. <jats:italic>Results and Discussion<\/jats:italic>. Variations of CPR parameters over CPR sequences (cycles) were analyzed. Across all patient groups, the sequential optimization scheme resulted in significant enhancement in the effectiveness of the CPR procedure when compared to the global optimization scheme. <jats:italic>Conclusions<\/jats:italic>. Our study illustrates the potential benefit of considering dynamic changes in rescuer-dependent parameters during CPR in order to improve performance. The advantage of the sequential optimization technique stemmed from its dynamically adapting effect. Our CPR optimization findings suggest that as CPR progresses, the compression to ventilation ratio should decrease, and the sequential optimization technique can potentially improve CPR performance. Validation <jats:italic>in vivo<\/jats:italic> is needed before implementing these changes in actual practice.<\/jats:p>","DOI":"10.1155\/2018\/3569346","type":"journal-article","created":{"date-parts":[[2018,11,29]],"date-time":"2018-11-29T18:30:29Z","timestamp":1543516229000},"page":"1-6","source":"Crossref","is-referenced-by-count":1,"title":["A Dynamic Model of Rescuer Parameters for Optimizing Blood Gas Delivery during Cardiopulmonary Resuscitation"],"prefix":"10.1155","volume":"2018","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-9894-3071","authenticated-orcid":true,"given":"Ali","family":"Jalali","sequence":"first","affiliation":[{"name":"Health Informatics Core, Johns Hopkins All Children\u2019s Hospital, 501 6th Avenue South, St. Petersburg, FL 33701, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8871-2579","authenticated-orcid":true,"given":"Allan F.","family":"Simpao","sequence":"additional","affiliation":[{"name":"Department of Anesthesiology & Critical Care Medicine, Children\u2019s Hospital of Philadelphia, Perelman School of Medicine at the University of Pennsylvania, 3401 Civic Center Blvd., Philadelphia, PA 19104, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jorge A.","family":"G\u00e1lvez","sequence":"additional","affiliation":[{"name":"Department of Anesthesiology & Critical Care Medicine, Children\u2019s Hospital of Philadelphia, Perelman School of Medicine at the University of Pennsylvania, 3401 Civic Center Blvd., Philadelphia, PA 19104, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Robert A.","family":"Berg","sequence":"additional","affiliation":[{"name":"Department of Anesthesiology & Critical Care Medicine, Children\u2019s Hospital of Philadelphia, Perelman School of Medicine at the University of Pennsylvania, 3401 Civic Center Blvd., Philadelphia, PA 19104, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Vinay M.","family":"Nadkarni","sequence":"additional","affiliation":[{"name":"Department of Anesthesiology & Critical Care Medicine, Children\u2019s Hospital of Philadelphia, Perelman School of Medicine at the University of Pennsylvania, 3401 Civic Center Blvd., Philadelphia, PA 19104, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5816-3932","authenticated-orcid":true,"given":"Chandrasekhar","family":"Nataraj","sequence":"additional","affiliation":[{"name":"Villanova Center for Analytics of Dynamic Systems, Department of Mechanical Engineering, Villanova University, Villanova, PA 19085, 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