Economic Impact of Metagenomic Next-generation Sequencing Versus Traditional Bacterial Culture Directed CNSIs Diagnosis and Therapy in Post-neurosurgical Patients Using a Decision Analysis Model

Central nervous system infections (CNSIs) are severe complications after neurosurgery, that can lead to a poor prognosis. The incidence of postoperative central nervous system infections (PCNSIs) ranges from 2.8% to 14%, and there are differences between different regions. The incidence rate in developed countries is lower than that in developing countries. The most common manifestations of PCNSIs include meningitis, ventriculitis, subdural abscess, epidural abscesses, and brain abscesses. Studies have shown that the most common pathogens of PCNSIs are Staphylococcus aureus, and coagulase-negative staphylococcus, followed by gram-negative bacteria. In China, the pathogen detection rate of traditional cerebrospinal fluid (CSF) culture can only reach 5.4-10%. In addition, culture as the gold standard is time-consuming and susceptible to the use of antibiotics. PCNSIs is related to increased treatment costs, prolonged hospitalization time, psychological trauma and delayed postoperative adjuvant treatment, which places a substantial economic and psychological burden on society and patients' families.

Given the seriousness of PCNSIs, it is challenging to choose the appropriate antibiotic treatment for PCNSIs and should be guided by pathogens and their drug sensitivity. Thus, early and efficient diagnosis of pathogens is crucial for PCNSIs. Compared with traditional pathogenic microbial detection methods, metagenomic next-generation sequencing (mNGS) has faster, more accurate, and more complete advantages. Currently, it is widely used in CNSIs, respiratory infections, blood infections, etc., especially suitable for the diagnosis of acute, critical, and complicated infections. Studies have shown that the positive rate of mNGS is much higher than that of culture, and it is less affected by the use of antibiotics, which can provide more accurate feedback on the patient's infection status. At the same time, it can detect a variety of pathogen types, providing more effective guidance for treatment. In addition, the fast detection speed of mNGS can effectively shorten the patient's course of the disease and significantly improve the prognosis of infected patients.

Most published mNGS studies are evaluations of their clinical diagnostic value. However, there is still some controversy over the full clinical use of mNGS, and one of the main reasons is cost constraints. The overall cost of mNGS detection reagents and labor in each sample is much higher than that of traditional detection methods. There are still no reports on health economics research on the use of mNGS to diagnose CNSIs after neurosurgery. Therefore, prospective clinical trials are needed to evaluate the cost-effectiveness of mNGS, a relatively expensive new detection method.

In summary, this study intends to conduct a health economics study of mNGS to diagnose postoperative central nervous system infections and evaluate whether mNGS, as a relatively expensive new technology, can identify the pathogen at the early stage, shorten the time of anti-infective treatment, reduce the overall medical cost, and improve the cure rate of patients. In addition, this study provides theoretical guidance for clinical and public health departments to make cost-effective decisions more scientifically, make more effective use of medical resources, and improve the social and economic benefits of etiological diagnosis.