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Development and validation of a nomogram for suspected post-neurosurgical bacterial ventriculitis/meningitis
Min Ni1, Yu-Ying Yan1, Song-Yu Chen2
1Department of Pharmacy, Shanghai Tenth People's Hospital, School of Life Sciences and Technology,Tongji University, Shanghai, China.
Objective:
The diagnosis of post-neurosurgical bacterial ventriculitis/meningitis (BV/M) remains challenging, particularly in the patients with leukocytic pleocytosis and hypoglycorrhachia. This study aimed to establish a nomogram identifying the high-risk and low-risk post-neurosurgical BV/M and evaluate the utility of this risk scoring system.
Methods:
Adult patients with CSF leukocytes ≥ 100/mm3 and glucose ≤ 2.2 mmol/L experienced neurosurgical or invasive procedures in three hospitals were divided into training and validation cohort, patients from Medical Information Mart for Intensive Care (MIMIC)-III and MIMIC-IV were also used as validation cohort. Multivariate logistic regression was performed to identify independent predictors and establish a nomogram to predict the occurrence of BV/M.
Results:
Totally, 271 patients (150 confirmed BV/M and 121 confirmed non-BV/M) selected from 711 suspected post-neurosurgical BV/M patients with leukocytic pleocytosis and hypoglycorrhachia were used as training cohort. CSF glucose, CSF leukocytes, CSF erythrocytes, CSF neutrophil proportions, blood lymphocyte proportions, and external ventricular drainage filtered out from 20 easily available parameters were used as independent predictors to develop the nomogram for BV/M. The high discriminative power of this nomogram was assessed by two independent validation cohorts (84 and 58 patients respectively).
Conclusion:
The nomogram uses six easily available indexes to predict BV/M risk. High-risk patients should receive immediate antibiotics, increasing CSF examination frequency is recommended before antibiotic treatment in low-risk patients.
Insights
A new nomogram aids in diagnosing post-neurosurgical bacterial ventriculitis/meningitis (BV/M) by identifying high-risk patients. This tool helps guide timely antibiotic treatment for bacterial infections after neurosurgery.
Area of Science:
- Neuroscience
- Infectious Diseases
- Medical Diagnostics
Background:
- Post-neurosurgical bacterial ventriculitis/meningitis (BV/M) diagnosis is challenging, especially with confounding factors like leukocytic pleocytosis and hypoglycorrhachia.
- Accurate and timely diagnosis is crucial for effective treatment and improved patient outcomes.
Purpose of the Study:
- To develop and validate a predictive nomogram for identifying patients at high risk of post-neurosurgical BV/M.
- To evaluate the clinical utility of this risk scoring system in managing post-neurosurgical infections.
Main Methods:
- A multivariate logistic regression model was employed to identify independent predictors of BV/M.
- A nomogram was constructed using six easily accessible parameters: CSF glucose, CSF leukocytes, CSF erythrocytes, CSF neutrophil proportion, blood lymphocyte proportion, and external ventricular drainage.
- The nomogram's predictive performance was validated using independent training and external cohorts.
Main Results:
- The developed nomogram demonstrated high discriminative power in predicting BV/M across validation cohorts.
- Six key parameters were identified as significant predictors for BV/M risk.
- The nomogram effectively stratified patients into high-risk and low-risk categories.
Conclusions:
- The nomogram provides a valuable tool for risk stratification of post-neurosurgical BV/M.
- High-risk patients identified by the nomogram require immediate antibiotic intervention.
- Low-risk patients may benefit from increased cerebrospinal fluid examination frequency prior to antibiotic initiation.
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