{"title":"The trends of neutrophil-to-lymphocyte ratio, platelet-to-lymphocyte ratio, and systemic immunoinflammatory index in patients with intracerebral hemorrhage and clinical value in predicting pneumonia 30 days after surgery","authors":"Jian Zhang, Chunlong Liu, Xiong Xiao, Haojie Xie, Yonghui Zhang, Yang Hong, Yong Zhang","doi":"10.1016/j.wneu.2024.05.048","DOIUrl":"https://doi.org/10.1016/j.wneu.2024.05.048","url":null,"abstract":"","PeriodicalId":508491,"journal":{"name":"World Neurosurgery","volume":"134 18","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141034718","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-01-01DOI: 10.1016/j.wneu.2024.01.056
H. Karabağ, A. Iplikcioglu
{"title":"Analysis of Spinopelvic Parameters and Lumbar Lordosis in Patients with Transitional Lumbosacral Vertebrae, with Special Reference to Sacralization and Lumbarization","authors":"H. Karabağ, A. Iplikcioglu","doi":"10.1016/j.wneu.2024.01.056","DOIUrl":"https://doi.org/10.1016/j.wneu.2024.01.056","url":null,"abstract":"","PeriodicalId":508491,"journal":{"name":"World Neurosurgery","volume":"38 8","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139454892","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-04-01Epub Date: 2021-01-12DOI: 10.1016/j.wneu.2021.01.002
Martin Hanko, Marián Grendár, Pavol Snopko, René Opšenák, Juraj Šutovský, Martin Benčo, Jakub Soršák, Kamil Zeleňák, Branislav Kolarovszki
Background: Various prognostic models are used to predict mortality and functional outcome in patients after traumatic brain injury with a trend to incorporate machine learning protocols. None of these models is focused exactly on the subgroup of patients indicated for decompressive craniectomy. Evidence regarding efficiency of this surgery is still incomplete, especially in patients undergoing primary decompressive craniectomy with evacuation of traumatic mass lesions.
Methods: In a prospective study with a 6-month follow-up period, we assessed postoperative outcome and mortality of 40 patients who underwent primary decompressive craniectomy for traumatic brain injuries during 2018-2019. The results were analyzed in relation to a wide spectrum of preoperatively available demographic, clinical, radiographic, and laboratory data. Random forest algorithms were trained for prediction of both mortality and unfavorable outcome, with their accuracy quantified by area under the receiver operating curves (AUCs) for out-of-bag samples.
Results: At the end of the follow-up period, we observed mortality of 57.5%. Favorable outcome (Glasgow Outcome Scale [GOS] score 4-5) was achieved by 30% of our patients. Random forest-based prediction models constructed for 6-month mortality and outcome reached a moderate predictive ability, with AUC = 0.811 and AUC = 0.873, respectively. Random forest models trained on handpicked variables showed slightly decreased AUC = 0.787 for 6-month mortality and AUC = 0.846 for 6-month outcome and increased out-of-bag error rates.
Conclusions: Random forest algorithms show promising results in prediction of postoperative outcome and mortality in patients undergoing primary decompressive craniectomy. The best performance was achieved by Classification Random forest for 6-month outcome.
{"title":"Random Forest-Based Prediction of Outcome and Mortality in Patients with Traumatic Brain Injury Undergoing Primary Decompressive Craniectomy.","authors":"Martin Hanko, Marián Grendár, Pavol Snopko, René Opšenák, Juraj Šutovský, Martin Benčo, Jakub Soršák, Kamil Zeleňák, Branislav Kolarovszki","doi":"10.1016/j.wneu.2021.01.002","DOIUrl":"https://doi.org/10.1016/j.wneu.2021.01.002","url":null,"abstract":"<p><strong>Background: </strong>Various prognostic models are used to predict mortality and functional outcome in patients after traumatic brain injury with a trend to incorporate machine learning protocols. None of these models is focused exactly on the subgroup of patients indicated for decompressive craniectomy. Evidence regarding efficiency of this surgery is still incomplete, especially in patients undergoing primary decompressive craniectomy with evacuation of traumatic mass lesions.</p><p><strong>Methods: </strong>In a prospective study with a 6-month follow-up period, we assessed postoperative outcome and mortality of 40 patients who underwent primary decompressive craniectomy for traumatic brain injuries during 2018-2019. The results were analyzed in relation to a wide spectrum of preoperatively available demographic, clinical, radiographic, and laboratory data. Random forest algorithms were trained for prediction of both mortality and unfavorable outcome, with their accuracy quantified by area under the receiver operating curves (AUCs) for out-of-bag samples.</p><p><strong>Results: </strong>At the end of the follow-up period, we observed mortality of 57.5%. Favorable outcome (Glasgow Outcome Scale [GOS] score 4-5) was achieved by 30% of our patients. Random forest-based prediction models constructed for 6-month mortality and outcome reached a moderate predictive ability, with AUC = 0.811 and AUC = 0.873, respectively. Random forest models trained on handpicked variables showed slightly decreased AUC = 0.787 for 6-month mortality and AUC = 0.846 for 6-month outcome and increased out-of-bag error rates.</p><p><strong>Conclusions: </strong>Random forest algorithms show promising results in prediction of postoperative outcome and mortality in patients undergoing primary decompressive craniectomy. The best performance was achieved by Classification Random forest for 6-month outcome.</p>","PeriodicalId":508491,"journal":{"name":"World Neurosurgery","volume":" ","pages":"e450-e458"},"PeriodicalIF":2.0,"publicationDate":"2021-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/j.wneu.2021.01.002","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"38819028","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-07-01Epub Date: 2019-04-10DOI: 10.1016/j.wneu.2019.04.042
Kyle P O'Connor, Allison E Strickland, Bradley N Bohnstedt
Background: The PulseRider (Pulsar Vascular, Inc, Los Gatos, California, USA) device was developed to treat wide-neck aneurysms, and the Adjunctive Neurovascular Support of Wide-neck aneurysm Embolization and Reconstruction (ANSWER) Trial showed efficacy in the treatment of unruptured wide-neck aneurysms. Our case series demonstrates the use of the PulseRider device in the treatment of ruptured wide-neck aneurysms.
Case description: The 2 patients in our series presented with subarachnoid hemorrhage secondary to ruptured basilar apex aneurysms. The patients were taken to the neurointervention suite for embolization of their aneurysms with the PulseRider and platinum microcoils.
Conclusions: In both cases, a Roy Raymond class III embolization was achieved. The patients recovered from their subarachnoid hemorrhage and were discharged with resolution of their symptoms. The presented cases document the safety and efficacy of treating ruptured aneurysms with the PulseRider device.
背景:PulseRider (Pulsar Vascular, Inc, Los Gatos, California, USA)装置被开发用于治疗宽颈动脉瘤，并且辅助神经血管支持的宽颈动脉瘤栓塞和重建(ANSWER)试验显示治疗未破裂的宽颈动脉瘤有效。我们的病例系列展示了PulseRider装置在治疗破裂的宽颈动脉瘤中的应用。病例描述:我们报告的2例患者均为颅底动脉瘤破裂后的蛛网膜下腔出血。患者被带到神经介入组，用PulseRider和铂微线圈栓塞他们的动脉瘤。结论:两例患者均行Roy Raymond III级栓塞术。患者均从蛛网膜下腔出血中恢复，症状缓解出院。这些病例证明了使用PulseRider装置治疗动脉瘤破裂的安全性和有效性。
{"title":"PulseRider Use in Ruptured Basilar Apex Aneurysms.","authors":"Kyle P O'Connor, Allison E Strickland, Bradley N Bohnstedt","doi":"10.1016/j.wneu.2019.04.042","DOIUrl":"https://doi.org/10.1016/j.wneu.2019.04.042","url":null,"abstract":"<p><strong>Background: </strong>The PulseRider (Pulsar Vascular, Inc, Los Gatos, California, USA) device was developed to treat wide-neck aneurysms, and the Adjunctive Neurovascular Support of Wide-neck aneurysm Embolization and Reconstruction (ANSWER) Trial showed efficacy in the treatment of unruptured wide-neck aneurysms. Our case series demonstrates the use of the PulseRider device in the treatment of ruptured wide-neck aneurysms.</p><p><strong>Case description: </strong>The 2 patients in our series presented with subarachnoid hemorrhage secondary to ruptured basilar apex aneurysms. The patients were taken to the neurointervention suite for embolization of their aneurysms with the PulseRider and platinum microcoils.</p><p><strong>Conclusions: </strong>In both cases, a Roy Raymond class III embolization was achieved. The patients recovered from their subarachnoid hemorrhage and were discharged with resolution of their symptoms. The presented cases document the safety and efficacy of treating ruptured aneurysms with the PulseRider device.</p>","PeriodicalId":508491,"journal":{"name":"World Neurosurgery","volume":" ","pages":"346-349"},"PeriodicalIF":2.0,"publicationDate":"2019-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/j.wneu.2019.04.042","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"37149025","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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