{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,31]],"date-time":"2026-10-31T01:26:42Z","timestamp":1793410002733,"version":"4.5.0"},"reference-count":14,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2025,7,10]],"date-time":"2025-07-10T00:00:00Z","timestamp":1752105600000},"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><jats:title>Background<\/jats:title><jats:p>Hospital-acquired pneumonia (HBP) is a common and serious infections disease that affects the patients with traumatic brain injury (TBI). Severe pneumonia can lead to high mortality and morbidity in TBI patients. Therefore, it is important to investigate the risk factors and develop a prediction model for HBP following TBI.<\/jats:p><\/jats:sec><jats:sec><jats:title>Methods<\/jats:title><jats:p>The clinical data of 285 patients with TBI, admitted to Shanxi Bethune Hospital and Shanxi Provincial People\u2019s Hospital, were collected. Patients were divided into two groups based on the presence or absence of pneumonia. Risk factors for HBP were identified, a predictive model was constructed, and its performance was validated.<\/jats:p><\/jats:sec><jats:sec><jats:title>Results<\/jats:title><jats:p>Significant differences were observed between the pneumonia and non-pneumonia groups regarding several factors, including age, history of diabetes, smoking history, white blood cell count, platelet count, albumin levels, Glasgow Coma Scale (GCS) score upon admission, thoracic trauma, craniocerebral surgery, and the need for tracheal intubation post-admission (<jats:italic>p<\/jats:italic>\u202f&amp;lt;\u202f0.05). Among these, age, smoking history, thoracic trauma, white blood cell count, albumin levels, and admission GCS score were identified as independent risk factors for HBP following TBI. The predictive model based on these six factors demonstrated high accuracy.<\/jats:p><\/jats:sec><jats:sec><jats:title>Conclusion<\/jats:title><jats:p>Age, smoking history, thoracic trauma, white blood cell count, albumin levels, and admission GCS score are independent risk factors for HBP after TBI. The predictive model developed based on these factors shows strong predictive accuracy and clinical utility.<\/jats:p><\/jats:sec>","DOI":"10.3389\/fneur.2025.1518599","type":"journal-article","created":{"date-parts":[[2025,7,10]],"date-time":"2025-07-10T04:12:19Z","timestamp":1752120739000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":3,"title":["Risk factors analysis and prediction model construction of hospital-acquired pneumonia after traumatic brain injury"],"prefix":"10.3389","volume":"16","author":[{"given":"Xiao-Cong","family":"Wei","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yi-Zi","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Min","family":"Guo","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hai-Bo","family":"Tong","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yong-Hong","family":"Wang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xiao-Qin","family":"Wang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hong-Ming","family":"Ji","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Bin","family":"Ren","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hao","family":"Wu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1965","published-online":{"date-parts":[[2025,7,10]]},"reference":[{"key":"ref1","doi-asserted-by":"publisher","first-page":"886","DOI":"10.1016\/s1474-4422(20)30345-8","article-title":"Management 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diagnosis and treatment of hospital-acquired pneumonia and ventilator-associated pneumonia in adults (2018 edition)","volume":"11","author":"Shi","year":"2019","journal-title":"J Thorac Dis"},{"key":"ref11","doi-asserted-by":"publisher","first-page":"1883","DOI":"10.1089\/neu.2014.3454","article-title":"Mortality following traumatic brain injury among individuals unable to follow commands at the time of rehabilitation admission: a National Institute on Disability and Rehabilitation Research traumatic brain injury model systems study","volume":"32","author":"Greenwald","year":"2015","journal-title":"J Neurotrauma"},{"key":"ref12","doi-asserted-by":"publisher","first-page":"68","DOI":"10.1177\/0885066620972001","article-title":"Epidemiology and outcomes of acute respiratory distress syndrome following isolated severe traumatic brain injury","volume":"37","author":"Komisarow","year":"2022","journal-title":"J Intensive Care Med"},{"key":"ref13","doi-asserted-by":"publisher","first-page":"3156","DOI":"10.1161\/strokeaha.120.030429","article-title":"Infection as a stroke risk factor and determinant of outcome after stroke","volume":"51","author":"Elkind","year":"2020","journal-title":"Stroke"},{"key":"ref14","doi-asserted-by":"publisher","first-page":"63","DOI":"10.1016\/j.bbi.2019.04.034","article-title":"Infections after a traumatic brain injury: the complex interplay between the immune and neurological systems","volume":"79","author":"Sharma","year":"2019","journal-title":"Brain Behav Immun"}],"container-title":["Frontiers in 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