{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,11,3]],"date-time":"2026-11-03T02:51:29Z","timestamp":1793674289585,"version":"4.5.1"},"reference-count":39,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2023,7,27]],"date-time":"2023-07-27T00:00:00Z","timestamp":1690416000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Neurosci."],"abstract":"<jats:sec><jats:title>Background<\/jats:title><jats:p>Cognitive impairment is a common sequela following traumatic brain injury (TBI). This study aimed to identify risk factors for cognitive impairment after 3 and 12 months of TBI and to create nomograms to predict them.<\/jats:p><\/jats:sec><jats:sec><jats:title>Methods<\/jats:title><jats:p>A total of 305 mild-to-moderate TBI patients admitted to the First Affiliated Hospital with Nanjing Medical University from January 2018 to January 2022 were retrospectively recruited. Risk factors for cognitive impairment after 3 and 12 months of TBI were identified by univariable and multivariable logistic regression analyses. Based on these factors, we created two nomograms to predict cognitive impairment after 3 and 12 months of TBI, the discrimination and calibration of which were validated by plotting the receiver operating characteristic (ROC) curve and calibration curve, respectively.<\/jats:p><\/jats:sec><jats:sec><jats:title>Results<\/jats:title><jats:p>Cognitive impairment was detected in 125\/305 and 52\/305 mild-to-moderate TBI patients after 3 and 12 months of injury, respectively. Age, the Glasgow Coma Scale (GCS) score, &amp;gt;12 years of education, hyperlipidemia, temporal lobe contusion, traumatic subarachnoid hemorrhage (tSAH), very early rehabilitation (VER), and intensive care unit (ICU) admission were independent risk factors for cognitive impairment after 3 months of mild-to-moderate TBI. Meanwhile, age, GCS score, diabetes mellitus, tSAH, and surgical treatment were independent risk factors for cognitive impairment after 12 months of mild-to-moderate TBI. Two nomograms were created based on the risk factors identified using logistic regression analyses. The areas under the curve (AUCs) of the two nomograms to predict cognitive impairment after 3 and 12 months of mild-to-moderate TBI were 0.852 (95% CI [0.810, 0.895]) and 0.817 (95% CI [0.762, 0.873]), respectively.<\/jats:p><\/jats:sec><jats:sec><jats:title>Conclusion<\/jats:title><jats:p>Two nomograms are created to predict cognitive impairment after 3 and 12 months of TBI. Age, GCS score, &amp;gt;12 years of education, hyperlipidemia, temporal lobe contusion, tSAH, VER, and ICU admission are independent risk factors for cognitive impairment after 3 months of TBI; meanwhile, age, the GCS scores, diabetes mellitus, tSAH, and surgical treatment are independent risk factors of cognitive impairment after 12 months of TBI. Two nomograms, based on both groups of factors, respectively, show strong discriminative abilities.<\/jats:p><\/jats:sec>","DOI":"10.3389\/fnins.2023.1222541","type":"journal-article","created":{"date-parts":[[2023,7,27]],"date-time":"2023-07-27T09:44:49Z","timestamp":1690451089000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":3,"title":["Utilization of clinical and radiological parameters to predict cognitive prognosis in patients with mild-to-moderate traumatic brain injury"],"prefix":"10.3389","volume":"17","author":[{"given":"Xi","family":"Wang","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xiaobo","family":"Hui","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xiangyu","family":"Wang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Baosheng","family":"Huang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xiaokui","family":"Gan","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xingdong","family":"Liu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zhiyan","family":"Shen","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yi","family":"Sun","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Lixin","family":"Li","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1965","published-online":{"date-parts":[[2023,7,27]]},"reference":[{"key":"B1","doi-asserted-by":"publisher","first-page":"e1239","DOI":"10.1212\/wnl.0000000000200928","article-title":"Moderating role of cognitive reserve markers between childhood cognition and cognitive aging: evidence from the 1946 British Birth Cohort","volume":"99","author":"Almeida-Meza","year":"2022","journal-title":"Neurology"},{"key":"B2","doi-asserted-by":"publisher","first-page":"1392","DOI":"10.1212\/wnl.0000000000002034","article-title":"Interaction between years of education and APOE \u03b54 status on frontal and temporal metabolism","volume":"85","author":"Arenaza-Urquijo","year":"2015","journal-title":"Neurology"},{"key":"B3","doi-asserted-by":"publisher","first-page":"E1","DOI":"10.1097\/HTR.0b013e318289ede5","article-title":"Corpus callosum integrity and neuropsychological performance after traumatic brain injury: a diffusion tensor imaging study","volume":"29","author":"Arenth","year":"2014","journal-title":"J. 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