{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,22]],"date-time":"2026-06-22T23:48:20Z","timestamp":1782172100517,"version":"3.54.5"},"reference-count":23,"publisher":"SAGE Publications","license":[{"start":{"date-parts":[[2026,6,19]],"date-time":"2026-06-19T00:00:00Z","timestamp":1781827200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/journals.sagepub.com\/page\/policies\/text-and-data-mining-license"}],"content-domain":{"domain":["journals.sagepub.com"],"crossmark-restriction":true},"short-container-title":["J Intensive Care Med"],"abstract":"<jats:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>Tachycardia, defined by SIRS criteria as a heart rate above 90, is commonly seen in numerous unrelated conditions, making its utility for screening in conditions like sepsis poor due to lack of sensitivity or specificity. Rather than using a single tachycardia value as a criterion, we evaluated the use of age-predicted maximal heart rate to individualize excessive tachycardia as a function of estimated physiologic reserve and to stratify mortality risk.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>A retrospective analysis was performed on a cohort of 62,327 admitted ICU patients from the MIMIC-IV dataset, with the primary point of interest being in-hospital mortality. Utilizing the Fox formula, each patient's admission heart rate was divided by their APMHR, yielding %APMHR. Significant increases in mortality were observed with increasing %APMHR, with the most pronounced increase starting at %APMHR\u2009\u2265\u200960. A multinomial logistic regression model was then used to evaluate the replacement of tachycardia \u2009&gt;\u200990 with %APMHR \u226560 as a new SIRS model (nSIRS) to compare mortality prediction to traditional SIRS criterion.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>HRs at %APMHR\u2009\u2265\u200960 was similar to HR\u2009&gt;\u200990 in predicting mortality (16.54% vs 15.06%) in this ICU cohort, with notable further increases in mortality associated with %APMHR\u2009\u2265\u200970, and decreases below %APMHR\u2009\u2264\u200950. The nSIRS model utilizing %APMHR\u2009\u2265\u200960 was a better predictor of mortality with a larger log-likelihood, and smaller AIC\/BIC when the nSIRS score was\u2009\u2265\u20092; with a similar RRR of 3.227 versus 3.335. Slightly fewer patients met these nSIRS\u2009\u2265\u20092 criteria versus the original SIRS.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>%APMHR is similar to HR\u2009&gt;\u200990 in predicting mortality, but the analysis also highlights that tachycardia alone poses significantly higher mortality risks, especially with increasing patient age. %APMHR\u2009\u2265\u200960, when substituted into the SIRS criteria for HR\u2009&gt;\u200990, performs comparably as a predictor of in-hospital mortality in this patient cohort. Further evaluation of incorporating %APMHR into other mortality\/screening tools is needed.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1177\/08850666261457341","type":"journal-article","created":{"date-parts":[[2026,6,19]],"date-time":"2026-06-19T13:45:20Z","timestamp":1781876720000},"update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":0,"title":["Evaluating Age-Predicted Maximal Heart Rate Versus Tachycardia in SIRS Criterion"],"prefix":"10.1177","author":[{"ORCID":"https:\/\/orcid.org\/0009-0004-9016-4398","authenticated-orcid":false,"given":"Ethan","family":"Flathers","sequence":"first","affiliation":[{"name":"Macon & Joan Brock Virginia Health Sciences at Old Dominion University"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Fang","family":"Fang","sequence":"additional","affiliation":[{"name":"VHS Healthcare Analytics Institute, Macon & Joan Brock Virginia Health Sciences at Old Dominion University"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Bryan","family":"Fitzgerald","sequence":"additional","affiliation":[{"name":"Macon & Joan Brock Virginia Health Sciences at Old Dominion University"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Timothy","family":"Ori","sequence":"additional","affiliation":[{"name":"Macon & Joan Brock Virginia Health Sciences at Old Dominion University"},{"name":"Department of Pulmonary Disease, Dayton VA Medical Center, Dayton, OH, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"179","published-online":{"date-parts":[[2026,6,19]]},"reference":[{"key":"e_1_3_4_2_2","doi-asserted-by":"publisher","DOI":"10.1161\/01.CIR.8.6.920"},{"key":"e_1_3_4_3_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.ajem.2018.10.058"},{"key":"e_1_3_4_4_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.ajem.2021.04.006"},{"key":"e_1_3_4_5_2","doi-asserted-by":"publisher","DOI":"10.1080\/14787210.2023.2237192"},{"key":"e_1_3_4_6_2","doi-asserted-by":"publisher","DOI":"10.1164\/rccm.201502-0275OC"},{"key":"e_1_3_4_7_2","doi-asserted-by":"publisher","DOI":"10.1016\/s0735-1097(00)01054-8"},{"key":"e_1_3_4_8_2","doi-asserted-by":"publisher","DOI":"10.1007\/bf00421445"},{"key":"e_1_3_4_9_2","unstructured":"Montenegro A Monares E S\u00e1nchez J Alejo G Granillo J. 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