Analysis of associated factors affecting hematoma evacuation rates in spontaneous intracerebral hemorrhage with stereotactic aspiration combined with catheter drainage

Abstract Due to the absence of direct visualization during the operative field in stereotactic surgery for sICH, there exists individual variability in hematoma evacuation (HE) rates, with about 42% of patients not attaining the expected threshold for HE. The aim of this study was to find the releva...

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Main Authors: Xinqun Luo, Keming Song, Lingyun Zhuo, Fuxin Lin, Zhuyu Gao, Qiu He, Yan Zheng, Kunbin Lian, Huangcheng Shangguan, Xingguang Luo, Yuanxiang Lin, Dezhi Kang, Wenhua Fang
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Language:English
Published: Nature Portfolio 2025-05-01
Series:Scientific Reports
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Online Access:https://doi.org/10.1038/s41598-025-01754-0
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author Xinqun Luo
Keming Song
Lingyun Zhuo
Fuxin Lin
Zhuyu Gao
Qiu He
Yan Zheng
Kunbin Lian
Huangcheng Shangguan
Xingguang Luo
Yuanxiang Lin
Dezhi Kang
Wenhua Fang
author_facet Xinqun Luo
Keming Song
Lingyun Zhuo
Fuxin Lin
Zhuyu Gao
Qiu He
Yan Zheng
Kunbin Lian
Huangcheng Shangguan
Xingguang Luo
Yuanxiang Lin
Dezhi Kang
Wenhua Fang
author_sort Xinqun Luo
collection DOAJ
description Abstract Due to the absence of direct visualization during the operative field in stereotactic surgery for sICH, there exists individual variability in hematoma evacuation (HE) rates, with about 42% of patients not attaining the expected threshold for HE. The aim of this study was to find the relevant factors affecting HE during the treatment of sICH with stereotactic surgery. We pooled individual data from our prospective ICH database, encompassing patients who underwent stereotactic aspiration and catheter drainage. The primary outcome was HE rates prior to extubation. Multivariate logistic regression using the stepwise forward method to identify the independent risk factors. A predictive scoring model was developed based on regression coefficients. To evaluate its discrimination performance, we conducted ROC curve analysis and calculated the AUC. Additionally, we employed calibration curves as an indicator of concordance. The bootstrap internal validation was used to ascertain the model’s stability. DCA was performed to determine the clinical utility. The study included 90 patients, of whom 43 (47.8%) patients achieved HE rates ≥ 70%. The multivariate logistic analysis showed that blend sign (OR 7.003, 95% CI 2.118–23.161, P = 0.001), irregular shape (OR 0.235, 95% CI 0.067–0.821, P = 0.023), two drainage tubes (OR 28.643, 95% CI 1.872–438.181, P = 0.016), diabetes (OR 0.078, 95% CI 0.006–0.948, P = 0.045), and hematoma edge linked to ventricle (OR 0.145, 95% CI 0.032–0.659, P = 0.012) were independent risk factors. For clinical use, the Model-score was established, with a total score ranging from -6 to 5. The AUC values of the Model-logit and Model-score were 0.820 (95% CI 0.733–0.906) and 0.822 (95% CI 0.737–0.908) respectively. The cutoff values were 0.275 and -0.5. Calibration curves demonstrated excellent agreement between predicted probabilities and observed outcomes in both models. Utilizing the bootstrap method for internal validation, the mean AUC values were determined to be 0.819 (95% CI 0.736–0.903) for Model-logit and 0.823 (95% CI 0.742–0.903) for Model-score, demonstrating stability across the resampled datasets. The DCA confirmed that both models provide superior net benefit for predicting HE rates ≥ 70% when the individualized threshold ranges from 10 to 82%. The predictive model of HE rates ≥ 70% prior to extuation has demonstrated predictive capability, holds the potential to assist clinicians in optimizing surgical efficiency.
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spelling doaj-art-adc74c6f53e340e9836ff333dde1c7312025-08-20T02:33:24ZengNature PortfolioScientific Reports2045-23222025-05-0115111010.1038/s41598-025-01754-0Analysis of associated factors affecting hematoma evacuation rates in spontaneous intracerebral hemorrhage with stereotactic aspiration combined with catheter drainageXinqun Luo0Keming Song1Lingyun Zhuo2Fuxin Lin3Zhuyu Gao4Qiu He5Yan Zheng6Kunbin Lian7Huangcheng Shangguan8Xingguang Luo9Yuanxiang Lin10Dezhi Kang11Wenhua Fang12Department of Neurosurgery, Neurosurgery Research Institute, The First Affiliated Hospital, Fujian Medical UniversityDepartment of Neurosurgery, Shunchang County General HospitalDepartment of Neurosurgery, Neurosurgery Research Institute, The First Affiliated Hospital, Fujian Medical UniversityDepartment of Neurosurgery, Neurosurgery Research Institute, The First Affiliated Hospital, Fujian Medical UniversityDepartment of Neurosurgery, Neurosurgery Research Institute, The First Affiliated Hospital, Fujian Medical UniversityDepartment of Neurosurgery, Neurosurgery Research Institute, The First Affiliated Hospital, Fujian Medical UniversityDepartment of Neurosurgery, Neurosurgery Research Institute, The First Affiliated Hospital, Fujian Medical UniversityDepartment of Neurosurgery, Neurosurgery Research Institute, The First Affiliated Hospital, Fujian Medical UniversityDepartment of Neurosurgery, Neurosurgery Research Institute, The First Affiliated Hospital, Fujian Medical UniversityBeijing Huilongguan Hospital, Peking University Huilongguan School of Clinical MedicineDepartment of Neurosurgery, Neurosurgery Research Institute, The First Affiliated Hospital, Fujian Medical UniversityDepartment of Neurosurgery, Neurosurgery Research Institute, The First Affiliated Hospital, Fujian Medical UniversityDepartment of Neurosurgery, Neurosurgery Research Institute, The First Affiliated Hospital, Fujian Medical UniversityAbstract Due to the absence of direct visualization during the operative field in stereotactic surgery for sICH, there exists individual variability in hematoma evacuation (HE) rates, with about 42% of patients not attaining the expected threshold for HE. The aim of this study was to find the relevant factors affecting HE during the treatment of sICH with stereotactic surgery. We pooled individual data from our prospective ICH database, encompassing patients who underwent stereotactic aspiration and catheter drainage. The primary outcome was HE rates prior to extubation. Multivariate logistic regression using the stepwise forward method to identify the independent risk factors. A predictive scoring model was developed based on regression coefficients. To evaluate its discrimination performance, we conducted ROC curve analysis and calculated the AUC. Additionally, we employed calibration curves as an indicator of concordance. The bootstrap internal validation was used to ascertain the model’s stability. DCA was performed to determine the clinical utility. The study included 90 patients, of whom 43 (47.8%) patients achieved HE rates ≥ 70%. The multivariate logistic analysis showed that blend sign (OR 7.003, 95% CI 2.118–23.161, P = 0.001), irregular shape (OR 0.235, 95% CI 0.067–0.821, P = 0.023), two drainage tubes (OR 28.643, 95% CI 1.872–438.181, P = 0.016), diabetes (OR 0.078, 95% CI 0.006–0.948, P = 0.045), and hematoma edge linked to ventricle (OR 0.145, 95% CI 0.032–0.659, P = 0.012) were independent risk factors. For clinical use, the Model-score was established, with a total score ranging from -6 to 5. The AUC values of the Model-logit and Model-score were 0.820 (95% CI 0.733–0.906) and 0.822 (95% CI 0.737–0.908) respectively. The cutoff values were 0.275 and -0.5. Calibration curves demonstrated excellent agreement between predicted probabilities and observed outcomes in both models. Utilizing the bootstrap method for internal validation, the mean AUC values were determined to be 0.819 (95% CI 0.736–0.903) for Model-logit and 0.823 (95% CI 0.742–0.903) for Model-score, demonstrating stability across the resampled datasets. The DCA confirmed that both models provide superior net benefit for predicting HE rates ≥ 70% when the individualized threshold ranges from 10 to 82%. The predictive model of HE rates ≥ 70% prior to extuation has demonstrated predictive capability, holds the potential to assist clinicians in optimizing surgical efficiency.https://doi.org/10.1038/s41598-025-01754-0Blend signHematoma evacuation ratesPredictive modelSpontaneous intracerebral hemorrhageStereotactic aspiration
spellingShingle Xinqun Luo
Keming Song
Lingyun Zhuo
Fuxin Lin
Zhuyu Gao
Qiu He
Yan Zheng
Kunbin Lian
Huangcheng Shangguan
Xingguang Luo
Yuanxiang Lin
Dezhi Kang
Wenhua Fang
Analysis of associated factors affecting hematoma evacuation rates in spontaneous intracerebral hemorrhage with stereotactic aspiration combined with catheter drainage
Scientific Reports
Blend sign
Hematoma evacuation rates
Predictive model
Spontaneous intracerebral hemorrhage
Stereotactic aspiration
title Analysis of associated factors affecting hematoma evacuation rates in spontaneous intracerebral hemorrhage with stereotactic aspiration combined with catheter drainage
title_full Analysis of associated factors affecting hematoma evacuation rates in spontaneous intracerebral hemorrhage with stereotactic aspiration combined with catheter drainage
title_fullStr Analysis of associated factors affecting hematoma evacuation rates in spontaneous intracerebral hemorrhage with stereotactic aspiration combined with catheter drainage
title_full_unstemmed Analysis of associated factors affecting hematoma evacuation rates in spontaneous intracerebral hemorrhage with stereotactic aspiration combined with catheter drainage
title_short Analysis of associated factors affecting hematoma evacuation rates in spontaneous intracerebral hemorrhage with stereotactic aspiration combined with catheter drainage
title_sort analysis of associated factors affecting hematoma evacuation rates in spontaneous intracerebral hemorrhage with stereotactic aspiration combined with catheter drainage
topic Blend sign
Hematoma evacuation rates
Predictive model
Spontaneous intracerebral hemorrhage
Stereotactic aspiration
url https://doi.org/10.1038/s41598-025-01754-0
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