ArticleTherapeutic innovation & regulatory science2022
Risk Prediction of Central Nervous System Infection Secondary to Intraventricular Drainage in Patients with Intracerebral Hemorrhage: Development and Evaluation of a New Predictive Model Nomogram.
Article in Therapeutic innovation & regulatory science, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed, 7 citations in OpenAlex.
- Nomogram for Predicting the Risk of Post-Craniotomy Intracranial Infection in Patients With Brain Tumors.Cancer medicine · 2026Article
- A Novel Model for Predicting Post-Craniotomy Meningitis Using Early Postoperative Risk Stratification: A Multi-Center Retrospective Study.Infection and drug resistance · 2026Article
- [Central Nervous System Infection After Neuroendoscopic and Microscopic Combined Hematoma Removal: Risk Factors and Construction of a Nomogram Prediction Model].Sichuan da xue xue bao. Yi xue ban = Journal of Sichuan University. Medical science edition · 2025Article
- Multimodal deep learning model for prediction of prognosis in central nervous system inflammation.Brain communications · 2025Article
- Diagnostic performance and clinical utility of metagenomic next-generation sequencing in suspected central nervous system infections: a prospective comparative study.Frontiers in cellular and infection microbiology · 2025Article
- Predictive value of cerebrospinal fluid heparin-binding protein and CD64 expression for postoperative central nervous system infection following intracerebral hemorrhage surgery.American journal of translational research · 2025Article
- Development and Validation of a Nomograph Model for Post-Operative Central Nervous System Infection after Craniocerebral Surgery.Diagnostics (Basel, Switzerland) · 2023Article
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Authors and funding
5 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundCurrently no reliable tools are available for predicting the risk of central nervous system (CNS) infections in patients with intracerebral hemorrhage after undergoing ventriculostomy drainage. The current study sought to develop and validate a nomogram to identify high-risk factors of CNS infection after ventriculomegaly drain placement for intracerebral hemorrhage.
methodsA total of 185 patients with intracerebral hemorrhage who underwent ventriculoperitoneal drainage were enrolled to the current study. Patients were divided into a CNS infection group (20 patients) and a non-CNS infection group (165 patients). The baseline data from both groups was used to develop and evaluate a model for predicting the likelihood of developing CNS infection after ventriculoperitoneal drain placement for intracerebral hemorrhage.
resultsThe finding showed that operative time, intraventricular drainage duration, postoperative temperature, white blood cell count in cerebrospinal fluid (CSF), neutrophils ratio in CSF, Red blood cell count in CSF, and glucose content in CSF were correlated with CNS infection. A nomogram for predicting the risk of CNS infection was constructed based on these variables. The c-index and the AUC of the ROC curve was 0.961, showing good discrimination. Clinical decision curve analysis indicated that the nomogram clinical application ranged between 1 and 100%. The clinical impact curve was generated to set with a threshold probability of 0.5.
conclusionThe nomogram reported in the current study can be used by clinicians to identify patients likely to have secondary CNS infections, so that clinicians can better treat these patients at earlier stages.
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