{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,29]],"date-time":"2026-10-29T18:20:09Z","timestamp":1793298009577,"version":"4.5.0"},"reference-count":51,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2026,1,8]],"date-time":"2026-01-08T00:00:00Z","timestamp":1767830400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Digit. Health"],"abstract":"<jats:sec>\n                    <jats:title>Introduction<\/jats:title>\n                    <jats:p>Survival after out-of-hospital cardiac arrest decreases by 5%\u201312% for every minute of delay in treatment. Ambulance response times vary widely across Norway, particularly between urban and rural municipalities. Advances in digital health technologies may encourage earlier patient contact with emergency services, potentially mitigating these delays.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>We analyzed official response time data from four Norwegian municipalities representing diverse geographic contexts (Bergen, Tokke, Lur\u00f8y, S\u00f8rfold). Using a survival decay function (Equation), we simulated changes in survival probability under scenarios where emergency calls were placed 1, 5, or 10\u2005min earlier than observed.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>Baseline survival probabilities varied substantially across municipalities, from 47.7% in Bergen (mean response 10.2\u2005min) to 9.3% in Lur\u00f8y (32.8\u2005min). Simulated earlier calls produced marked gains: in Bergen, survival increased from 47.7% to 68.6% with a five-minute advance; in S\u00f8rfold, from 19.4% to 27.9%; and in Tokke, from 29.9% to 43.1%. Even modest improvements (1\u20132\u2005min) yielded meaningful survival benefits.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>Geographic disparities in emergency response times strongly influence survival after cardiac arrest. Wearables and AI-based monitoring cannot predict cardiac arrest but may promote earlier recognition of abnormal physiological states and timelier emergency calls. If widely adopted, such technologies could provide substantial survival gains, particularly in rural and remote regions.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.3389\/fdgth.2025.1695377","type":"journal-article","created":{"date-parts":[[2026,1,8]],"date-time":"2026-01-08T06:33:49Z","timestamp":1767854029000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":2,"title":["Timing is survival: modeling how earlier calls improve cardiac arrest outcomes"],"prefix":"10.3389","volume":"7","author":[{"given":"Marius Ole","family":"Johansen","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Rune Johan","family":"Krumsvik","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Vegard","family":"Slettvoll","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1965","published-online":{"date-parts":[[2026,1,8]]},"reference":[{"key":"B1","doi-asserted-by":"publisher","first-page":"212","DOI":"10.1161\/CIRCEP.113.001034","article-title":"Public health burden of sudden cardiac death in the United States","volume":"7","author":"Stecker","year":"2014","journal-title":"Circ Arrhythm Electrophysiol"},{"key":"B2","doi-asserted-by":"publisher","first-page":"970","DOI":"10.1016\/S0140-6736(18)30472-0","article-title":"Out-of-hospital cardiac arrest: current concepts","volume":"391","author":"Myat","year":"2018","journal-title":"Lancet"},{"key":"B3","doi-asserted-by":"publisher","first-page":"147","DOI":"10.31083\/j.rcm.2021.01.207","article-title":"Sudden cardiac death: epidemiology, pathogenesis and management","volume":"22","author":"Kumar","year":"2021","journal-title":"Rev Cardiovasc Med"},{"key":"B4","doi-asserted-by":"publisher","first-page":"6","DOI":"10.1016\/j.hlc.2018.08.026","article-title":"Epidemiology of sudden cardiac death: global and regional perspectives","volume":"28","author":"Wong","year":"2019","journal-title":"Heart Lung Circ"},{"key":"B5","doi-asserted-by":"publisher","first-page":"e0266969","DOI":"10.1371\/journal.pone.0266969","article-title":"Influence of advanced life support response time on out-of-hospital cardiac arrest patient outcomes in Taipei","volume":"17","author":"Chen","year":"2022","journal-title":"PLoS One"},{"key":"B6","doi-asserted-by":"publisher","first-page":"703","DOI":"10.1136\/emj.2009.086363","article-title":"Role of ambulance response times in the survival of patients with out-of-hospital cardiac arrest","volume":"28","author":"O'Keeffe","year":"2011","journal-title":"Emerg Med J"},{"key":"B7","doi-asserted-by":"publisher","first-page":"1385","DOI":"10.1136\/bmj.322.7299.1385","article-title":"Effect of reducing ambulance response times on deaths from out of hospital cardiac arrest: cohort study","volume":"322","author":"Pell","year":"2001","journal-title":"Br Med J"},{"key":"B8","doi-asserted-by":"publisher","first-page":"652","DOI":"10.1002\/hec.4791","article-title":"How important are delays in treatment for health outcomes? 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