Predictive model for preoperative risk calculation of cerebrospinal fluid leak after resection of midline craniofacial mass lesions
Background: Complex anterior skull base defects produced by resection of mass lesions vary in size and configuration and may be extensive. We analyzed the largest single-center series of midline craniofacial lesions extending intra- and extracranially. The study aims at the development of a predicti...
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| Format: | Article |
| Language: | English |
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Elsevier
2023-04-01
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| Series: | World Neurosurgery: X |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S2590139723000121 |
| _version_ | 1797850250813112320 |
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| author | Denis A. Golbin Alexander V. Vecherin Vasily A. Cherekaev Nikolay V. Lasunin Tatyana V. Tsukanova Sergey N. Mindlin Michael A. Shifrin |
| author_facet | Denis A. Golbin Alexander V. Vecherin Vasily A. Cherekaev Nikolay V. Lasunin Tatyana V. Tsukanova Sergey N. Mindlin Michael A. Shifrin |
| author_sort | Denis A. Golbin |
| collection | DOAJ |
| description | Background: Complex anterior skull base defects produced by resection of mass lesions vary in size and configuration and may be extensive. We analyzed the largest single-center series of midline craniofacial lesions extending intra- and extracranially. The study aims at the development of a predictive model for preoperative measurement of the risk of the postoperative cerebrospinal fluid (CSF) leak based on patients' characteristics and surgical plans. Methods: 166 male and 149 female patients with mean age 40,5 years (1 year and – 81 years) operated for benign and tumor-like midline craniofacial mass lesions were retrospectively analyzed using logistic regression method (Ridge regression algorithm was selected). The overall CSF leak rate was 9.6%. The ROSE algorithm and ‘glmnet’ software suite in R were used to overcome the cohort's disbalance and avoid overtraining the model. Results: The most influential modifiable negative predictor of the postoperative CSF leak was the use of extracranial and combined approaches. Use of transbasal approaches, gross total resection, utilization of one or two vascularized flaps for skull base reconstruction were the foremost modifiable predictors of a good outcome. Criterium of elevated risk was established at 50% with a specificity of the model as high as 0.83. Conclusions: The performed study has allowed for identifying the most significant predictors of postoperative CSF leak and developing an effective formula to estimate the risk of this complication using data known for each patient. We believe that the suggested web-based online calculator can be helpful for decision making support in off-pattern clinical situations. |
| first_indexed | 2024-04-09T18:58:26Z |
| format | Article |
| id | doaj.art-aa0a23dd987245a6bc8a806622a3b4b7 |
| institution | Directory Open Access Journal |
| issn | 2590-1397 |
| language | English |
| last_indexed | 2024-04-09T18:58:26Z |
| publishDate | 2023-04-01 |
| publisher | Elsevier |
| record_format | Article |
| series | World Neurosurgery: X |
| spelling | doaj.art-aa0a23dd987245a6bc8a806622a3b4b72023-04-09T05:49:53ZengElsevierWorld Neurosurgery: X2590-13972023-04-0118100163Predictive model for preoperative risk calculation of cerebrospinal fluid leak after resection of midline craniofacial mass lesionsDenis A. Golbin0Alexander V. Vecherin1Vasily A. Cherekaev2Nikolay V. Lasunin3Tatyana V. Tsukanova4Sergey N. Mindlin5Michael A. Shifrin6Department of Craniofacial and Skull Base Surgery, N.N. Burdenko National Medical Research Center for Neurosurgery, Moscow, Russia; Corresponding author. Department of Craniofacial and Skull Base Surgery, N.N. Burdenko National Medical Research Center for Neurosurgery, 4th Tverskaya-Yamskaya, 16 125047 Moscow, Russia.Department of Psychology, Faculty of Social Sciences, National Research University Higher School of Economics, Moscow, RussiaDepartment of Craniofacial and Skull Base Surgery, N.N. Burdenko National Medical Research Center for Neurosurgery, Moscow, RussiaDepartment of Craniofacial and Skull Base Surgery, N.N. Burdenko National Medical Research Center for Neurosurgery, Moscow, RussiaLaboratory of Information Technologies and Artificial Intelligence, N.N. Burdenko National Medical Research Center for Neurosurgery, Moscow, RussiaLaboratory of Neuroanatomy and Cryopreservation, N.N. Burdenko National Medical Research Center for Neurosurgery, Moscow, RussiaLaboratory of Information Technologies and Artificial Intelligence, N.N. Burdenko National Medical Research Center for Neurosurgery, Moscow, RussiaBackground: Complex anterior skull base defects produced by resection of mass lesions vary in size and configuration and may be extensive. We analyzed the largest single-center series of midline craniofacial lesions extending intra- and extracranially. The study aims at the development of a predictive model for preoperative measurement of the risk of the postoperative cerebrospinal fluid (CSF) leak based on patients' characteristics and surgical plans. Methods: 166 male and 149 female patients with mean age 40,5 years (1 year and – 81 years) operated for benign and tumor-like midline craniofacial mass lesions were retrospectively analyzed using logistic regression method (Ridge regression algorithm was selected). The overall CSF leak rate was 9.6%. The ROSE algorithm and ‘glmnet’ software suite in R were used to overcome the cohort's disbalance and avoid overtraining the model. Results: The most influential modifiable negative predictor of the postoperative CSF leak was the use of extracranial and combined approaches. Use of transbasal approaches, gross total resection, utilization of one or two vascularized flaps for skull base reconstruction were the foremost modifiable predictors of a good outcome. Criterium of elevated risk was established at 50% with a specificity of the model as high as 0.83. Conclusions: The performed study has allowed for identifying the most significant predictors of postoperative CSF leak and developing an effective formula to estimate the risk of this complication using data known for each patient. We believe that the suggested web-based online calculator can be helpful for decision making support in off-pattern clinical situations.http://www.sciencedirect.com/science/article/pii/S2590139723000121Cerebrospinal fluid leakCraniofacialDecision supportModelsSkull base |
| spellingShingle | Denis A. Golbin Alexander V. Vecherin Vasily A. Cherekaev Nikolay V. Lasunin Tatyana V. Tsukanova Sergey N. Mindlin Michael A. Shifrin Predictive model for preoperative risk calculation of cerebrospinal fluid leak after resection of midline craniofacial mass lesions World Neurosurgery: X Cerebrospinal fluid leak Craniofacial Decision support Models Skull base |
| title | Predictive model for preoperative risk calculation of cerebrospinal fluid leak after resection of midline craniofacial mass lesions |
| title_full | Predictive model for preoperative risk calculation of cerebrospinal fluid leak after resection of midline craniofacial mass lesions |
| title_fullStr | Predictive model for preoperative risk calculation of cerebrospinal fluid leak after resection of midline craniofacial mass lesions |
| title_full_unstemmed | Predictive model for preoperative risk calculation of cerebrospinal fluid leak after resection of midline craniofacial mass lesions |
| title_short | Predictive model for preoperative risk calculation of cerebrospinal fluid leak after resection of midline craniofacial mass lesions |
| title_sort | predictive model for preoperative risk calculation of cerebrospinal fluid leak after resection of midline craniofacial mass lesions |
| topic | Cerebrospinal fluid leak Craniofacial Decision support Models Skull base |
| url | http://www.sciencedirect.com/science/article/pii/S2590139723000121 |
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