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Prediction of Intracranial Infection in Patients under External Ventricular Drainage and Neurological Intensive Care: A Multicenter Retrospective Cohort Study.

ABSTRACT: Objective: To generate an optimal prediction model along with identifying major contributors to intracranial infection among patients under external ventricular drainage and neurological intensive care. Methods: A retrospective cohort study was conducted among patients admitted into neurointensive care units between 1 January 2015 and 31 December 2020 who underwent external ventricular drainage due to traumatic brain injury, hydrocephalus, and nonaneurysmal spontaneous intracranial hemorrhage. Multivariate logistic regression in combination with the least absolute shrinkage and selection operator regression was applied to derive prediction models and optimize variable selections. Other machine-learning algorithms, including the support vector machine and K-nearest neighbor, were also applied to derive alternative prediction models. Five-fold cross-validation was used to train and validate each model. Model performance was assessed by calibration plots, receiver operating characteristic curves, and decision curves. A nomogram analysis was developed to explicate the weights of selected features for the optimal model. Results: Multivariate logistic regression showed the best performance among the three tested models with an area under curve of 0.846 ± 0.006. Six variables, including hemoglobin, albumin, length of operation time, American Society of Anesthesiologists grades, presence of traumatic subarachnoid hemorrhage, and a history of diabetes, were selected from 37 variable candidates as the top-weighted prediction features. The decision curve analysis showed that the nomogram could be applied clinically when the risk threshold is between 20% and 100%. Conclusions: The occurrence of external ventricular-drainage-associated intracranial infections could be predicted using optimal models and feature-selection approaches, which would be helpful for the prevention and treatment of this complication in neurointensive care units.

SUBMITTER: Fu P

PROVIDER: S-EPMC9317602 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:Objectives: Multiple risk factors have been described to be related to external ventricular drain (EVD) associated infections, with results varying between studies. Former studies were limited by a non-uniform definition of EVD associated infection, thus complicating a comparison between studies. In this regard, we assessed risk factors promoting EVD associated infections and propose a modified practice-oriented definition of EVD associated infections. Methods: We performed a retrospective, single-center study on patients who were treated with an EVD, at the neurosurgical intensive care unit (ICU) at a tertiary center between 2008 and 2019. Based on microbiological findings and laboratory results, patients were assigned into an infection and a non-infection group. Patient characteristics and potential risk factors were compared between the two groups (p < 0.05). Receiver operating characteristics (ROC) for significant clinical, serum laboratory and cerebrospinal fluid (CSF) parameters were calculated. Results: In total, 396 patients treated with an EVD were included into the study with a mean age of 54.3 (range: 18-89) years. EVD associated infections were observed in 32 (8.1%) patients. EVD insertion at another hospital (OR 3.86), and an increased CSF sampling frequency of more than every third day (OR 12.91) were detected as major risk factors for an EVD associated infection. The indication for EVD insertion, surgeon's experience, the setting of EVD insertion (ICU vs. operating room) and the operating time did not show any significant differences between the two groups. Furthermore, ROC analysis showed that clinical, serum laboratory and CSF parameters did not provide specific prediction of EVD associated infections (specificity 44.4%). This explains the high overtreatment rate in our cohort with the majority of our patients who received intrathecal vancomycin (63.3%), having either negative microbiological results (n = 12) or were defined as contaminations (n = 7). Conclusions: Since clinical parameters and blood analyzes are not very predictive to detect EVD associated infections in neurosurgical patients, sequential but not too frequent microbiological and laboratory analysis of CSF are still necessary. Furthermore, we propose a uniform classification for EVD associated infections to allow comparability between studies and to sensitize the treating physician in determining the right treatment.

Dataset Information

Prediction of Intracranial Infection in Patients under External Ventricular Drainage and Neurological Intensive Care: A Multicenter Retrospective Cohort Study.

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