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Sun Z, Dong S, Fu L, Miao X, Duan X, Xue F. Factors Affecting Development of Infection After Implantation of Ventriculoperitoneal Shunts in Patients with Posttraumatic Hydrocephalus. World Neurosurg 2022; 166:e435-e442. [PMID: 35843578 DOI: 10.1016/j.wneu.2022.07.022] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/16/2022] [Revised: 07/05/2022] [Accepted: 07/06/2022] [Indexed: 12/15/2022]
Abstract
BACKGROUND Patients with posttraumatic hydrocephalus (PTH) have a high incidence of infection after ventriculoperitoneal shunt (VPS). In this study, we investigated different risk factors affecting infection after VPS in PTH patients. METHODS Clinical data on PTH patients with VPS in Shaanxi Provincial People's Hospital from March 2012 to November 2020 were collected and analyzed retrospectively. We evaluated the relevance of patients' sex, age, cause of hydrocephalus, severity of hydrocephalus, types of hydrocephalus, hypertension, diabetes, decompressive craniectomy (DC), abdominal surgery, and duration of VPS surgery in the development of postoperative infection. Predictive values of different risk factors for the development of postoperative infection were analyzed using the receiver operating characteristic curve. RESULTS Shunt infection occurred in 38 patients (10.2% of cases). We found that patients >60 years of age with severe hydrocephalus, hypertension, diabetes, DC, and duration of surgery for VPS >60 minutes were at a significantly higher risk of developing an infection after VPS (P < 0.05). The area under the curve was used to predict shunt infection using age (0.611), severe hydrocephalus (0.589), hypertension (0.641), diabetes (0.657), DC (0.640), and duration of operation (0.600) as independent risk factors. The area under the curve of shunt infection predicted by whole index was 0.871. CONCLUSIONS Age, severe hydrocephalus, hypertension, diabetes, DC, as well as duration of operation for VPS (>60 minutes) were factors that significantly and independently correlated with the incidence of infection after VPS. The receiver operating characteristic curve that we have developed can predict the occurrence of shunt infection.
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Affiliation(s)
- Zhen Sun
- Shaanxi Provincial People's Hospital, Xi'an, Shaanxi, China
| | - Shengpu Dong
- Shaanxi Provincial People's Hospital, Xi'an, Shaanxi, China
| | - Lei Fu
- Shaanxi Provincial People's Hospital, Xi'an, Shaanxi, China
| | - Xingyu Miao
- Shaanxi Provincial People's Hospital, Xi'an, Shaanxi, China
| | - Xianglong Duan
- Shaanxi Provincial People's Hospital, Xi'an, Shaanxi, China; Affiliated Hospital of Northwestern Polytechnical University, Xi'an, Shaanxi, China
| | - Fei Xue
- Shaanxi Provincial People's Hospital, Xi'an, Shaanxi, China; Affiliated Hospital of Northwestern Polytechnical University, Xi'an, Shaanxi, China.
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Pease M, Arefan D, Barber J, Yuh E, Puccio A, Hochberger K, Nwachuku E, Roy S, Casillo S, Temkin N, Okonkwo DO, Wu S. Outcome Prediction in Patients with Severe Traumatic Brain Injury Using Deep Learning from Head CT Scans. Radiology 2022; 304:385-394. [PMID: 35471108 PMCID: PMC9340242 DOI: 10.1148/radiol.212181] [Citation(s) in RCA: 29] [Impact Index Per Article: 14.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/23/2022]
Abstract
Background After severe traumatic brain injury (sTBI), physicians use long-term prognostication to guide acute clinical care yet struggle to predict outcomes in comatose patients. Purpose To develop and evaluate a prognostic model combining deep learning of head CT scans and clinical information to predict long-term outcomes after sTBI. Materials and Methods This was a retrospective analysis of two prospectively collected databases. The model-building set included 537 patients (mean age, 40 years ± 17 [SD]; 422 men) from one institution from November 2002 to December 2018. Transfer learning and curriculum learning were applied to a convolutional neural network using admission head CT to predict mortality and unfavorable outcomes (Glasgow Outcomes Scale scores 1-3) at 6 months. This was combined with clinical input for a holistic fusion model. The models were evaluated using an independent internal test set and an external cohort of 220 patients with sTBI (mean age, 39 years ± 17; 166 men) from 18 institutions in the Transforming Research and Clinical Knowledge in Traumatic Brain Injury (TRACK-TBI) study from February 2014 to April 2018. The models were compared with the International Mission on Prognosis and Analysis of Clinical Trials in TBI (IMPACT) model and the predictions of three neurosurgeons. Area under the receiver operating characteristic curve (AUC) was used as the main model performance metric. Results The fusion model had higher AUCs than did the IMPACT model in the prediction of mortality (AUC, 0.92 [95% CI: 0.86, 0.97] vs 0.80 [95% CI: 0.71, 0.88]; P < .001) and unfavorable outcomes (AUC, 0.88 [95% CI: 0.82, 0.94] vs 0.82 [95% CI: 0.75, 0.90]; P = .04) on the internal data set. For external TRACK-TBI testing, there was no evidence of a significant difference in the performance of any models compared with the IMPACT model (AUC, 0.83; 95% CI: 0.77, 0.90) in the prediction of mortality. The Imaging model (AUC, 0.73; 95% CI: 0.66-0.81; P = .02) and the fusion model (AUC, 0.68; 95% CI: 0.60, 0.76; P = .02) underperformed as compared with the IMPACT model (AUC, 0.83; 95% CI: 0.77, 0.89) in the prediction of unfavorable outcomes. The fusion model outperformed the predictions of the neurosurgeons. Conclusion A deep learning model of head CT and clinical information can be used to predict 6-month outcomes after severe traumatic brain injury. © RSNA, 2022 Online supplemental material is available for this article. See also the editorial by Haller in this issue.
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Affiliation(s)
- Matthew Pease
- From the Department of Neurosurgery, University of Pittsburgh Medical Center, Pittsburgh, Pa (M.P., A.P., K.H., E.N., S.R., S.C., D.O.O.); Departments of Radiology (D.A., S.W.), Biomedical Informatics (S.W.), and Bioengineering (S.W.), and Intelligent Systems Program (S.W.), University of Pittsburgh, 3240 Craft Pl, Room 322, Pittsburgh, PA 15213; Department of Neurosurgery, University of Washington, Seattle, Wash (J.B., N.T.); Department of Radiology, University of California San Francisco, San Francisco, Calif (E.Y.)
| | - Dooman Arefan
- From the Department of Neurosurgery, University of Pittsburgh Medical Center, Pittsburgh, Pa (M.P., A.P., K.H., E.N., S.R., S.C., D.O.O.); Departments of Radiology (D.A., S.W.), Biomedical Informatics (S.W.), and Bioengineering (S.W.), and Intelligent Systems Program (S.W.), University of Pittsburgh, 3240 Craft Pl, Room 322, Pittsburgh, PA 15213; Department of Neurosurgery, University of Washington, Seattle, Wash (J.B., N.T.); Department of Radiology, University of California San Francisco, San Francisco, Calif (E.Y.)
| | - Jason Barber
- From the Department of Neurosurgery, University of Pittsburgh Medical Center, Pittsburgh, Pa (M.P., A.P., K.H., E.N., S.R., S.C., D.O.O.); Departments of Radiology (D.A., S.W.), Biomedical Informatics (S.W.), and Bioengineering (S.W.), and Intelligent Systems Program (S.W.), University of Pittsburgh, 3240 Craft Pl, Room 322, Pittsburgh, PA 15213; Department of Neurosurgery, University of Washington, Seattle, Wash (J.B., N.T.); Department of Radiology, University of California San Francisco, San Francisco, Calif (E.Y.)
| | - Esther Yuh
- From the Department of Neurosurgery, University of Pittsburgh Medical Center, Pittsburgh, Pa (M.P., A.P., K.H., E.N., S.R., S.C., D.O.O.); Departments of Radiology (D.A., S.W.), Biomedical Informatics (S.W.), and Bioengineering (S.W.), and Intelligent Systems Program (S.W.), University of Pittsburgh, 3240 Craft Pl, Room 322, Pittsburgh, PA 15213; Department of Neurosurgery, University of Washington, Seattle, Wash (J.B., N.T.); Department of Radiology, University of California San Francisco, San Francisco, Calif (E.Y.)
| | - Ava Puccio
- From the Department of Neurosurgery, University of Pittsburgh Medical Center, Pittsburgh, Pa (M.P., A.P., K.H., E.N., S.R., S.C., D.O.O.); Departments of Radiology (D.A., S.W.), Biomedical Informatics (S.W.), and Bioengineering (S.W.), and Intelligent Systems Program (S.W.), University of Pittsburgh, 3240 Craft Pl, Room 322, Pittsburgh, PA 15213; Department of Neurosurgery, University of Washington, Seattle, Wash (J.B., N.T.); Department of Radiology, University of California San Francisco, San Francisco, Calif (E.Y.)
| | - Kerri Hochberger
- From the Department of Neurosurgery, University of Pittsburgh Medical Center, Pittsburgh, Pa (M.P., A.P., K.H., E.N., S.R., S.C., D.O.O.); Departments of Radiology (D.A., S.W.), Biomedical Informatics (S.W.), and Bioengineering (S.W.), and Intelligent Systems Program (S.W.), University of Pittsburgh, 3240 Craft Pl, Room 322, Pittsburgh, PA 15213; Department of Neurosurgery, University of Washington, Seattle, Wash (J.B., N.T.); Department of Radiology, University of California San Francisco, San Francisco, Calif (E.Y.)
| | - Enyinna Nwachuku
- From the Department of Neurosurgery, University of Pittsburgh Medical Center, Pittsburgh, Pa (M.P., A.P., K.H., E.N., S.R., S.C., D.O.O.); Departments of Radiology (D.A., S.W.), Biomedical Informatics (S.W.), and Bioengineering (S.W.), and Intelligent Systems Program (S.W.), University of Pittsburgh, 3240 Craft Pl, Room 322, Pittsburgh, PA 15213; Department of Neurosurgery, University of Washington, Seattle, Wash (J.B., N.T.); Department of Radiology, University of California San Francisco, San Francisco, Calif (E.Y.)
| | - Souvik Roy
- From the Department of Neurosurgery, University of Pittsburgh Medical Center, Pittsburgh, Pa (M.P., A.P., K.H., E.N., S.R., S.C., D.O.O.); Departments of Radiology (D.A., S.W.), Biomedical Informatics (S.W.), and Bioengineering (S.W.), and Intelligent Systems Program (S.W.), University of Pittsburgh, 3240 Craft Pl, Room 322, Pittsburgh, PA 15213; Department of Neurosurgery, University of Washington, Seattle, Wash (J.B., N.T.); Department of Radiology, University of California San Francisco, San Francisco, Calif (E.Y.)
| | - Stephanie Casillo
- From the Department of Neurosurgery, University of Pittsburgh Medical Center, Pittsburgh, Pa (M.P., A.P., K.H., E.N., S.R., S.C., D.O.O.); Departments of Radiology (D.A., S.W.), Biomedical Informatics (S.W.), and Bioengineering (S.W.), and Intelligent Systems Program (S.W.), University of Pittsburgh, 3240 Craft Pl, Room 322, Pittsburgh, PA 15213; Department of Neurosurgery, University of Washington, Seattle, Wash (J.B., N.T.); Department of Radiology, University of California San Francisco, San Francisco, Calif (E.Y.)
| | - Nancy Temkin
- From the Department of Neurosurgery, University of Pittsburgh Medical Center, Pittsburgh, Pa (M.P., A.P., K.H., E.N., S.R., S.C., D.O.O.); Departments of Radiology (D.A., S.W.), Biomedical Informatics (S.W.), and Bioengineering (S.W.), and Intelligent Systems Program (S.W.), University of Pittsburgh, 3240 Craft Pl, Room 322, Pittsburgh, PA 15213; Department of Neurosurgery, University of Washington, Seattle, Wash (J.B., N.T.); Department of Radiology, University of California San Francisco, San Francisco, Calif (E.Y.)
| | - David O Okonkwo
- From the Department of Neurosurgery, University of Pittsburgh Medical Center, Pittsburgh, Pa (M.P., A.P., K.H., E.N., S.R., S.C., D.O.O.); Departments of Radiology (D.A., S.W.), Biomedical Informatics (S.W.), and Bioengineering (S.W.), and Intelligent Systems Program (S.W.), University of Pittsburgh, 3240 Craft Pl, Room 322, Pittsburgh, PA 15213; Department of Neurosurgery, University of Washington, Seattle, Wash (J.B., N.T.); Department of Radiology, University of California San Francisco, San Francisco, Calif (E.Y.)
| | - Shandong Wu
- From the Department of Neurosurgery, University of Pittsburgh Medical Center, Pittsburgh, Pa (M.P., A.P., K.H., E.N., S.R., S.C., D.O.O.); Departments of Radiology (D.A., S.W.), Biomedical Informatics (S.W.), and Bioengineering (S.W.), and Intelligent Systems Program (S.W.), University of Pittsburgh, 3240 Craft Pl, Room 322, Pittsburgh, PA 15213; Department of Neurosurgery, University of Washington, Seattle, Wash (J.B., N.T.); Department of Radiology, University of California San Francisco, San Francisco, Calif (E.Y.)
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- From the Department of Neurosurgery, University of Pittsburgh Medical Center, Pittsburgh, Pa (M.P., A.P., K.H., E.N., S.R., S.C., D.O.O.); Departments of Radiology (D.A., S.W.), Biomedical Informatics (S.W.), and Bioengineering (S.W.), and Intelligent Systems Program (S.W.), University of Pittsburgh, 3240 Craft Pl, Room 322, Pittsburgh, PA 15213; Department of Neurosurgery, University of Washington, Seattle, Wash (J.B., N.T.); Department of Radiology, University of California San Francisco, San Francisco, Calif (E.Y.)
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Deng H, Goldschmidt E, Nwachuku E, Yue JK, Angriman F, Wei Z, Agarwal N, Puccio AM, Okonkwo DO. Hydrocephalus and Cerebrospinal Fluid Analysis Following Severe Traumatic Brain Injury: Evaluation of a Prospective Cohort. Neurol Int 2021; 13:527-534. [PMID: 34698266 PMCID: PMC8544497 DOI: 10.3390/neurolint13040052] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/09/2021] [Revised: 10/11/2021] [Accepted: 10/12/2021] [Indexed: 11/17/2022] Open
Abstract
The development of hydrocephalus after severe traumatic brain injury (TBI) is an under-recognized healthcare phenomenon and can increase morbidity. The current study aims to characterize post-traumatic hydrocephalus (PTH) in a large cohort. Patients were prospectively enrolled age 16-80 years old with Glasgow Coma Scale (GCS) score ≤8. Demographics, GCS, Injury Severity Score (ISS), surgery, and cerebrospinal fluid (CSF) were analyzed. Outcomes were shunt failure and Glasgow Outcome Scale (GOS) at 6 and 12-months. Statistical significance was assessed at p < 0.05. In 402 patients, mean age was 38.0 ± 16.7 years and 315 (78.4%) were male. Forty (10.0%) patients developed PTH, with predominant injuries being subdural hemorrhage (36.4%) and diffuse axonal injury (36.4%). Decompressive hemicraniectomy (DHC) was associated with hydrocephalus (OR 3.62, 95% CI (1.62-8.07), p < 0.01). Eighteen (4.5%) patients had shunt failure and proximal obstruction was most common. Differences in baseline CSF cell count were associated with increased shunt failure. PTH was not associated with worse outcomes at 6 (p = 0.55) or 12 (p = 0.47) months. Hydrocephalus is a frequent sequela in 10.0% of patients, particularly after DHC. Shunt placement and revision procedures are common after severe TBI, within the first 4 months of injury and necessitates early recognition by the clinician.
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Affiliation(s)
- Hansen Deng
- Department of Neurological Surgery, University of Pittsburgh Medical Center, Pittsburgh, PA 15213, USA; (E.N.); (Z.W.); (N.A.); (A.M.P.); (D.O.O.)
| | - Ezequiel Goldschmidt
- Department of Neurological Surgery, University of California San Francisco, San Francisco, CA 94143, USA;
| | - Enyinna Nwachuku
- Department of Neurological Surgery, University of Pittsburgh Medical Center, Pittsburgh, PA 15213, USA; (E.N.); (Z.W.); (N.A.); (A.M.P.); (D.O.O.)
| | - John K. Yue
- Department of Critical Care Medicine, Sunnybrook Health Sciences Center, University of Toronto, Toronto, ON M4N 3M5, Canada; (J.K.Y.); (F.A.)
| | - Federico Angriman
- Department of Critical Care Medicine, Sunnybrook Health Sciences Center, University of Toronto, Toronto, ON M4N 3M5, Canada; (J.K.Y.); (F.A.)
| | - Zhishuo Wei
- Department of Neurological Surgery, University of Pittsburgh Medical Center, Pittsburgh, PA 15213, USA; (E.N.); (Z.W.); (N.A.); (A.M.P.); (D.O.O.)
| | - Nitin Agarwal
- Department of Neurological Surgery, University of Pittsburgh Medical Center, Pittsburgh, PA 15213, USA; (E.N.); (Z.W.); (N.A.); (A.M.P.); (D.O.O.)
| | - Ava M. Puccio
- Department of Neurological Surgery, University of Pittsburgh Medical Center, Pittsburgh, PA 15213, USA; (E.N.); (Z.W.); (N.A.); (A.M.P.); (D.O.O.)
- Neurotrauma Clinical Trials Center, University of Pittsburgh Medical Center, Pittsburgh, PA 15213, USA
| | - David O. Okonkwo
- Department of Neurological Surgery, University of Pittsburgh Medical Center, Pittsburgh, PA 15213, USA; (E.N.); (Z.W.); (N.A.); (A.M.P.); (D.O.O.)
- Neurotrauma Clinical Trials Center, University of Pittsburgh Medical Center, Pittsburgh, PA 15213, USA
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