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Pilot Biomarker Analysis and Decision Tree Algorithm Modeling of Patients with Chronic Subdural Hematomas

The elderly population are at high risk for developing chronic subdural hematoma (cSDH). Surgical evacuation of cSDH is one of the most common procedures performed in neurosurgery. The present study aims to identify potential inflammatory biomarkers associated with its development and recurrence. Pa...

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Autores principales: Puccio, David J., Deng, Hansen, Eagle, Shawn R., Okonkwo, David O., Nwachuku, Enyinna L.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Mary Ann Liebert, Inc., publishers 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10039273/
https://www.ncbi.nlm.nih.gov/pubmed/36974123
http://dx.doi.org/10.1089/neur.2022.0062
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author Puccio, David J.
Deng, Hansen
Eagle, Shawn R.
Okonkwo, David O.
Nwachuku, Enyinna L.
author_facet Puccio, David J.
Deng, Hansen
Eagle, Shawn R.
Okonkwo, David O.
Nwachuku, Enyinna L.
author_sort Puccio, David J.
collection PubMed
description The elderly population are at high risk for developing chronic subdural hematoma (cSDH). Surgical evacuation of cSDH is one of the most common procedures performed in neurosurgery. The present study aims to identify potential inflammatory biomarkers associated with its development and recurrence. Patients (>65 years of age) who presented with symptomatic cSDH (≥1 cm thickness or ≥5 mm midline shift [MLS]), requiring surgical intervention, were prospectively enrolled. The collected cSDH fluid was analyzed for inflammatory markers. Computed tomography (CT) scan data included pre-operative cSDH thickness and MLS. Outcome data included Glasgow Outcome Scale-Extended (GOS-E) score at 3, 6, and 12 months post-surgery, as well as cSDH recurrence. A decision tree model was used to determine the predictive power of extracted analytes for MLS, cSDH thickness, and recurrence. This pilot study includes 20 enrolled patients (mean age 77.9 ± 7.4 years and 85% falls). Rate of cSDH recurrence was 42%, with 21% requiring reoperation. Chemokine (C-X-C motif) ligand 9 (CXCL9) concentrations correlated with cSDH thickness (r = 0.975, p = 0.040). Interleukin (IL)-6 and vascular endothelial growth factor (VEGF)-A concentrations correlated with MLS (r = 0.974, p = 0.005; r = 0.472, p = 0.036, respectively). IL-5 concentrations correlated with more favorable GOS-E scores at 3, 6, and 12 months (r = 0.639, p = 0.006; r = 0.727, p = 0.003; r = 0.693, p = 0.026, respectively). Regulated on activation, normal T-cell expressed and secreted (RANTES) concentrations correlated with complete cSDH resolution (r = 0.514, p = 0.021). The decision tree model identified that higher concentrations of CXCL9 were predictive of MLS (risk ratio [RR] = 12.0), higher concentrations of IL-5 were predictive of cSDH thickness (RR = 4.5), and lower concentrations of RANTES were predictive of cSDH recurrence (RR = 2.2). CXCL9, IL-6, VEGF, IL-5, and RANTES are associated with recurrence after surgery and may be potential biomarkers for predicting cSDH recurrence and neurological outcomes.
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spelling pubmed-100392732023-03-26 Pilot Biomarker Analysis and Decision Tree Algorithm Modeling of Patients with Chronic Subdural Hematomas Puccio, David J. Deng, Hansen Eagle, Shawn R. Okonkwo, David O. Nwachuku, Enyinna L. Neurotrauma Rep Original Article The elderly population are at high risk for developing chronic subdural hematoma (cSDH). Surgical evacuation of cSDH is one of the most common procedures performed in neurosurgery. The present study aims to identify potential inflammatory biomarkers associated with its development and recurrence. Patients (>65 years of age) who presented with symptomatic cSDH (≥1 cm thickness or ≥5 mm midline shift [MLS]), requiring surgical intervention, were prospectively enrolled. The collected cSDH fluid was analyzed for inflammatory markers. Computed tomography (CT) scan data included pre-operative cSDH thickness and MLS. Outcome data included Glasgow Outcome Scale-Extended (GOS-E) score at 3, 6, and 12 months post-surgery, as well as cSDH recurrence. A decision tree model was used to determine the predictive power of extracted analytes for MLS, cSDH thickness, and recurrence. This pilot study includes 20 enrolled patients (mean age 77.9 ± 7.4 years and 85% falls). Rate of cSDH recurrence was 42%, with 21% requiring reoperation. Chemokine (C-X-C motif) ligand 9 (CXCL9) concentrations correlated with cSDH thickness (r = 0.975, p = 0.040). Interleukin (IL)-6 and vascular endothelial growth factor (VEGF)-A concentrations correlated with MLS (r = 0.974, p = 0.005; r = 0.472, p = 0.036, respectively). IL-5 concentrations correlated with more favorable GOS-E scores at 3, 6, and 12 months (r = 0.639, p = 0.006; r = 0.727, p = 0.003; r = 0.693, p = 0.026, respectively). Regulated on activation, normal T-cell expressed and secreted (RANTES) concentrations correlated with complete cSDH resolution (r = 0.514, p = 0.021). The decision tree model identified that higher concentrations of CXCL9 were predictive of MLS (risk ratio [RR] = 12.0), higher concentrations of IL-5 were predictive of cSDH thickness (RR = 4.5), and lower concentrations of RANTES were predictive of cSDH recurrence (RR = 2.2). CXCL9, IL-6, VEGF, IL-5, and RANTES are associated with recurrence after surgery and may be potential biomarkers for predicting cSDH recurrence and neurological outcomes. Mary Ann Liebert, Inc., publishers 2023-03-24 /pmc/articles/PMC10039273/ /pubmed/36974123 http://dx.doi.org/10.1089/neur.2022.0062 Text en © David J. Puccio et al., 2023; Published by Mary Ann Liebert, Inc. https://creativecommons.org/licenses/by/4.0/This Open Access article is distributed under the terms of the Creative Commons License [CC-BY] (http://creativecommons.org/licenses/by/4.0 (https://creativecommons.org/licenses/by/4.0/) ), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Original Article
Puccio, David J.
Deng, Hansen
Eagle, Shawn R.
Okonkwo, David O.
Nwachuku, Enyinna L.
Pilot Biomarker Analysis and Decision Tree Algorithm Modeling of Patients with Chronic Subdural Hematomas
title Pilot Biomarker Analysis and Decision Tree Algorithm Modeling of Patients with Chronic Subdural Hematomas
title_full Pilot Biomarker Analysis and Decision Tree Algorithm Modeling of Patients with Chronic Subdural Hematomas
title_fullStr Pilot Biomarker Analysis and Decision Tree Algorithm Modeling of Patients with Chronic Subdural Hematomas
title_full_unstemmed Pilot Biomarker Analysis and Decision Tree Algorithm Modeling of Patients with Chronic Subdural Hematomas
title_short Pilot Biomarker Analysis and Decision Tree Algorithm Modeling of Patients with Chronic Subdural Hematomas
title_sort pilot biomarker analysis and decision tree algorithm modeling of patients with chronic subdural hematomas
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10039273/
https://www.ncbi.nlm.nih.gov/pubmed/36974123
http://dx.doi.org/10.1089/neur.2022.0062
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