{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,23]],"date-time":"2026-09-23T05:07:06Z","timestamp":1790140026418,"version":"4.0.1"},"reference-count":22,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2026,9,23]],"date-time":"2026-09-23T00:00:00Z","timestamp":1790121600000},"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. Neurol."],"abstract":"<jats:sec>\n                    <jats:title>Objective<\/jats:title>\n                    <jats:p>To explore independent risk factors for 30-day all-cause mortality in severe cerebral infarction and construct a nomogram prediction model incorporating inflammation-related indicators and APACHE II score.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>A total of 312 patients with severe cerebral infarction from Chongqing University Qianjiang Hospital and 134 external validation cases from the First Affiliated Hospital of Changsha Medical University were retrospectively analyzed. Demographic, comorbidity, laboratory, and APACHE II data were collected from all patients. The endpoint was 30-day all-cause mortality. Univariate and multivariate logistic regression were used to identify independent risk factors, and a nomogram was developed.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>\n                      In this cohort, age distribution differed notably between the two subgroups: participants who did not survive had a higher mean age than those who survived. Regarding clinical and laboratory markers, non-survivors exhibited elevated NIHSS scores, NLR, hs-CRP, IL-6 levels, and APACHE II scores when compared with survivors, and the between-group differences were statistically significant (\n                      <jats:italic>p<\/jats:italic>\n                      \u202f&amp;lt;\u202f0.05). After adjusting for confounding factors, multivariate logistic regression modeling further identified that NIHSS score, NLR, hs-CRP, IL-6, and APACHE II score were independent factors linked to fatal outcomes in cases of severe cerebral infarction (all\n                      <jats:italic>p<\/jats:italic>\n                      \u202f&amp;lt;\u202f0.05). The ROC curve analysis showed that the combined use of the NIHSS, hs-CRP, IL-6, NLR, and APACHE II scores had a higher AUC value for predicting mortality in patients with severe cerebral infarction than individual tests (\n                      <jats:italic>Z<\/jats:italic>\n                      \u202f=\u202f6.879, 6.454, 6.693, 5.480, 5.407,\n                      <jats:italic>p<\/jats:italic>\n                      \u202f&amp;lt;\u202f0.05). Based on Logistic regression analysis, a prediction nomogram for the risk of 30-day mortality in patients with severe cerebral infarction was established. The nomogram included five variables, NIHSS score, NLR, hs-CRP, IL-6, and APACHE II score, and this model had high calibration ability and clinical practicability.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>NIHSS, NLR, hs-CRP, IL-6, and APACHE II are independent risk factors for 30-day mortality in patients with severe cerebral infarction. The integrated model offers excellent predictive performance, aiding early risk screening and personalizing treatment.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.3389\/fneur.2026.1918006","type":"journal-article","created":{"date-parts":[[2026,9,23]],"date-time":"2026-09-23T04:46:21Z","timestamp":1790138781000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["A nomogram prediction model for 30-day mortality risk in severe cerebral infarction patients integrating inflammation-related indicators and APACHE II score"],"prefix":"10.3389","volume":"17","author":[{"given":"Zhou","family":"Shu","sequence":"first","affiliation":[{"name":"Department of Intensive Care Medicine, Chongqing University Qianjiang Hospital","place":["Chongqing, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Fengbo","family":"Fu","sequence":"additional","affiliation":[{"name":"Department of Intensive Care Medicine, the First Affiliated Hospital of Changsha Medical University","place":["Changsha, Hunan, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jinyi","family":"Tian","sequence":"additional","affiliation":[{"name":"Department of Neurology, Chongqing University Qianjiang Hospital","place":["Chongqing, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1965","published-online":{"date-parts":[[2026,9,23]]},"reference":[{"key":"ref1","doi-asserted-by":"publisher","first-page":"e008961","DOI":"10.1161\/CIRCOUTCOMES.122.008961","article-title":"Patterns and outcomes of intensive care on acute ischemic stroke patients in the US","volume":"16","author":"Santos","year":"2023","journal-title":"Circ Cardiovasc Qual Outcomes"},{"key":"ref2","doi-asserted-by":"publisher","first-page":"131","DOI":"10.3126\/ajms.v13i5.43985","article-title":"Study of APACHE II score and National Institutes of Health stroke scale as prognostic indicators in cerebrovascular 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