Summary
Background
At present, central nervous system (CNS) infection in patients with traumatic brain
injury is usually diagnosed according to the clinical manifestations and results of
cerebrospinal fluid (CSF) bacterial culture. However, there are difficulties in obtaining
specimens in the early stage.
Aim
To develop and evaluate a nomogram to predict CNS infections in patients with severe
traumatic brain injury (sTBI) after craniotomy.
Methods
This retrospective study was conducted in consecutive adult patients with sTBI who
were admitted to the neurointensive care unit (NCU) between January 2014 and September
2020. The least absolute shrinkage and selection operator (LASSO) and multivariate
logistic regression analysis were applied to construct the nomogram, and k-fold cross-validation (k = 10) to validate it.
Findings
A total of 471 patients with sTBI who underwent surgical treatment were included,
of whom 75 patients (15.7%) were diagnosed with CNS infections. The serum level of
albumin, cerebrospinal fluid (CSF) otorrhoea at admission, CSF leakage, CSF sampling,
and postoperative re-bleeding were associated with CNS infections and incorporated
into the nomogram. Our model yielded satisfactory prediction performance with an area
under the curve value of 0.962 in the training set and 0.942 in the internal validation.
The calibration curve exhibited satisfactory concordance between the predicted and
actual outcomes. The model had good clinical use since the DCA covered a large threshold
probability.
Conclusion
Individualized nomograms for CNS infections in sTBI patients could help physicians
screen for high-risk patients to perform early interventions, reducing the incidence
of CNS infections.
Keywords
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Article info
Publication history
Published online: April 16, 2023
Accepted:
April 9,
2023
Received:
December 20,
2022
Identification
Copyright
© 2023 The Healthcare Infection Society. Published by Elsevier Ltd. All rights reserved.
