Hui Su , Hao Wang , Shuai Su , Yuan Liu , Zhitao Fan
{"title":"应用CT灌注成像的预测护理模型可改善急性脑出血的预后","authors":"Hui Su , Hao Wang , Shuai Su , Yuan Liu , Zhitao Fan","doi":"10.1016/j.jrras.2025.101906","DOIUrl":null,"url":null,"abstract":"<div><h3>Purpose</h3><div>To evaluate the impact of a predictive nursing model (CTP-PNM) based on CT perfusion imaging parameters compared to routine nursing (RN). Specifically, we assessed prognosis, neurological recovery, biochemical markers, symptom relief, quality of life, and complications in patients with acute cerebral hemorrhage (ACH).</div></div><div><h3>Methods</h3><div>A retrospective cohort study included 225 ACH patients (RN group: n = 121; CTP-PNM group: n = 104) treated between May 2021 and May 2023. The RN group received standard care. The CTP-PNM group received RN plus targeted interventions, such as intensified intracranial pressure (ICP) monitoring and anti-inflammatory measures, guided by individual CTP-defined risks. Baseline characteristics, biochemical markers, symptoms, neurological, cognitive, emotional, functional, and quality-of-life scales, overall treatment effectiveness, and complications were compared.</div></div><div><h3>Results</h3><div>Groups were comparable at baseline. After nursing, the CTP-PNM group demonstrated significant improvements across neurological function (e.g., NIHSS score), inflammatory markers, emotional state, and quality of life (all P < 0.05). CTP-PNM had higher total efficacy (P < 0.001) and significantly lower total complication rates (P = 0.016), particularly infections, deep vein thrombosis (DVT), pressure sores, and Gastrointestinal (GI) hemorrhage.</div></div><div><h3>Conclusion</h3><div>The CT perfusion parameter-based predictive nursing model represents a significant advance over routine care for ACH patients. It not only enhances neurological recovery, reduces inflammatory markers, alleviates symptoms, improves emotional state and quality of life but also increases overall treatment effectiveness and decreases complications. This approach has the potential to set a new standard for managing ACH patients.</div></div>","PeriodicalId":16920,"journal":{"name":"Journal of Radiation Research and Applied Sciences","volume":"18 4","pages":"Article 101906"},"PeriodicalIF":2.5000,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A predictive nursing model using CT perfusion imaging improves outcomes in acute cerebral hemorrhage\",\"authors\":\"Hui Su , Hao Wang , Shuai Su , Yuan Liu , Zhitao Fan\",\"doi\":\"10.1016/j.jrras.2025.101906\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><h3>Purpose</h3><div>To evaluate the impact of a predictive nursing model (CTP-PNM) based on CT perfusion imaging parameters compared to routine nursing (RN). Specifically, we assessed prognosis, neurological recovery, biochemical markers, symptom relief, quality of life, and complications in patients with acute cerebral hemorrhage (ACH).</div></div><div><h3>Methods</h3><div>A retrospective cohort study included 225 ACH patients (RN group: n = 121; CTP-PNM group: n = 104) treated between May 2021 and May 2023. The RN group received standard care. The CTP-PNM group received RN plus targeted interventions, such as intensified intracranial pressure (ICP) monitoring and anti-inflammatory measures, guided by individual CTP-defined risks. Baseline characteristics, biochemical markers, symptoms, neurological, cognitive, emotional, functional, and quality-of-life scales, overall treatment effectiveness, and complications were compared.</div></div><div><h3>Results</h3><div>Groups were comparable at baseline. After nursing, the CTP-PNM group demonstrated significant improvements across neurological function (e.g., NIHSS score), inflammatory markers, emotional state, and quality of life (all P < 0.05). CTP-PNM had higher total efficacy (P < 0.001) and significantly lower total complication rates (P = 0.016), particularly infections, deep vein thrombosis (DVT), pressure sores, and Gastrointestinal (GI) hemorrhage.</div></div><div><h3>Conclusion</h3><div>The CT perfusion parameter-based predictive nursing model represents a significant advance over routine care for ACH patients. It not only enhances neurological recovery, reduces inflammatory markers, alleviates symptoms, improves emotional state and quality of life but also increases overall treatment effectiveness and decreases complications. This approach has the potential to set a new standard for managing ACH patients.</div></div>\",\"PeriodicalId\":16920,\"journal\":{\"name\":\"Journal of Radiation Research and Applied Sciences\",\"volume\":\"18 4\",\"pages\":\"Article 101906\"},\"PeriodicalIF\":2.5000,\"publicationDate\":\"2025-09-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Radiation Research and Applied Sciences\",\"FirstCategoryId\":\"103\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S1687850725006181\",\"RegionNum\":4,\"RegionCategory\":\"综合性期刊\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"MULTIDISCIPLINARY SCIENCES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Radiation Research and Applied Sciences","FirstCategoryId":"103","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1687850725006181","RegionNum":4,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"MULTIDISCIPLINARY SCIENCES","Score":null,"Total":0}
A predictive nursing model using CT perfusion imaging improves outcomes in acute cerebral hemorrhage
Purpose
To evaluate the impact of a predictive nursing model (CTP-PNM) based on CT perfusion imaging parameters compared to routine nursing (RN). Specifically, we assessed prognosis, neurological recovery, biochemical markers, symptom relief, quality of life, and complications in patients with acute cerebral hemorrhage (ACH).
Methods
A retrospective cohort study included 225 ACH patients (RN group: n = 121; CTP-PNM group: n = 104) treated between May 2021 and May 2023. The RN group received standard care. The CTP-PNM group received RN plus targeted interventions, such as intensified intracranial pressure (ICP) monitoring and anti-inflammatory measures, guided by individual CTP-defined risks. Baseline characteristics, biochemical markers, symptoms, neurological, cognitive, emotional, functional, and quality-of-life scales, overall treatment effectiveness, and complications were compared.
Results
Groups were comparable at baseline. After nursing, the CTP-PNM group demonstrated significant improvements across neurological function (e.g., NIHSS score), inflammatory markers, emotional state, and quality of life (all P < 0.05). CTP-PNM had higher total efficacy (P < 0.001) and significantly lower total complication rates (P = 0.016), particularly infections, deep vein thrombosis (DVT), pressure sores, and Gastrointestinal (GI) hemorrhage.
Conclusion
The CT perfusion parameter-based predictive nursing model represents a significant advance over routine care for ACH patients. It not only enhances neurological recovery, reduces inflammatory markers, alleviates symptoms, improves emotional state and quality of life but also increases overall treatment effectiveness and decreases complications. This approach has the potential to set a new standard for managing ACH patients.
期刊介绍:
Journal of Radiation Research and Applied Sciences provides a high quality medium for the publication of substantial, original and scientific and technological papers on the development and applications of nuclear, radiation and isotopes in biology, medicine, drugs, biochemistry, microbiology, agriculture, entomology, food technology, chemistry, physics, solid states, engineering, environmental and applied sciences.