Diagnostic Testing in Central Nervous System Infection

Time to Confirmed Neuroinfectious Diagnoses: Diagnostic Testing and Resource Allocation

Background and Objectives

In a retrospective study evaluating the diagnostic approach of definitive neurological infections at a tertiary referral center, we assessed the time to diagnosis from presentation, number of diagnostic tests ordered, and modality of etiologic diagnosis.

Methods

A total of 111 confirmed clinical cases of neurological infections from 2010-2018 were reviewed. Definitive neuroinfectious diagnoses were defined by positive cerebrospinal (CSF) polymerase chain reaction (PCR)/antigen, CSF culture, CSF antibody, serology, or pathology tests.

Results

An etiologic diagnosis was determined at an average (SD) of 3.1 (5.9) days after presentation with an average (SD) of 27.7 (15.6) diagnostic tests ordered per workup.Viral neuro-infections were associated with lower intensive care unit (ICU) admission rates, shorter length of hospitalization, and fewer diagnostic tests ordered, as well as shorter time to definitive diagnosis (P < .05). Longer hospitalizations were associated with immunosuppression status regardless of infectious etiology (P < .001).

Discussion

Given the high morbidity and mortality of neuroinfectious disease, specifically meningitis and encephalitis, efficient diagnostic testing is imperative to facilitate the most appropriate clinical course of action with special attention to the specific patient population.

Square the Circle: Diversity of Viral Pathogens Causing Neuro-Infectious Diseases

Neuroinfections rank among the top ten leading causes of child mortality globally, even in high-income countries. The crucial determinants for successful treatment lie in the timing and swiftness of diagnosis. Although viruses constitute the majority of infectious neuropathologies, diagnosing and treating viral neuroinfections remains challenging. Despite technological advancements, the etiology of the disease remains undetermined in over half of cases. The identification of the pathogen becomes more difficult when the infection is caused by atypical pathogens or multiple pathogens simultaneously. Furthermore, the modern surge in global passenger traffic has led to an increase in cases of infections caused by pathogens not endemic to local areas. This review aims to systematize and summarize information on neuroinvasive viral pathogens, encompassing their geographic distribution and transmission routes. Emphasis is placed on rare pathogens and cases involving atypical pathogens, aiming to offer a comprehensive and structured catalog of viral agents with neurovirulence potential.

[High-throughput sequencing for infectious disease diagnoses: Example of shotgun metagenomics in central nervous system infections]

The advent of high-throughput sequencing in clinical microbiology is opening the way to new diagnostic and prognostic approaches in infectious diseases. Detection, identification and characterisation of pathogenic microorganisms are essential steps in diagnosis and implementation of appropriate antimicrobial therapy. However, standard methods of microbiological diagnosis are failing in some cases. In addition, the emergence of new infections, facilitated by international travel and global warming, requires the implementation of innovative diagnostic methods. Among the different strategies used in clinical microbiology and reviewed in this article, shotgun metagenomics is the only technique that allows today a panpathogenic and unbiased detection of all microorganisms potentially responsible for an infectious disease, including those still unknown. The aims of this article are to present the different possible strategies of high-throughput sequencing used in the microbiological diagnosis of infectious diseases and to highlight the diagnostic contribution of shotgun metagenomics in the field of central nervous system infections.

Infectious Myelopathies

OBJECTIVE

Infectious myelopathy of any stage and etiology carries the potential for significant morbidity and mortality. This article details the clinical presentation, risk factors, and key diagnostic components of infectious myelopathies with the goal of improving the recognition of these disorders and guiding subsequent management.

LATEST DEVELOPMENTS

Despite our era of advanced multimodal imaging and laboratory diagnostic technology, a causative organism often remains unidentified in suspected infectious and parainfectious myelopathy cases. To improve diagnostic capability, newer technologies such as metagenomics are being harnessed to develop diagnostic assays with a greater breadth of data from each specimen and improvements in infection identification. Conventional assays have been optimized for improved sensitivity and specificity.

ESSENTIAL POINTS

Prompt recognition and treatment of infectious myelopathy decreases morbidity and mortality. The key diagnostic tools include serologies, CSF analysis, and imaging; however clinical presentation, epidemiologic risk factors, and history of recent illness are all vital to making the proper diagnosis because current laboratory and imaging modalities are often inconclusive. The cornerstone of recommended treatment is targeted antimicrobials with appropriate immune modulation, surgical intervention, supportive care, and interdisciplinary involvement, all of which further improve outcomes for patients with infectious myelopathy.

Utilising biosensor-based approaches for identifying neurotropic viruses

Neurotropic viruses, with their ability to invade the central nervous system, present a significant public health challenge, causing a spectrum of neurological diseases. Clinical manifestations of neurotropic viral infections vary widely, from mild to life-threatening conditions, such as HSV-induced encephalitis or poliovirus-induced poliomyelitis. Traditional diagnostic methods, including polymerase chain reaction, serological assays, and imaging techniques, though valuable, have limitations. To address these challenges, biosensor-based methods have emerged as a promising approach. These methods offer advantages such as rapid results, high sensitivity, specificity, and potential for point-of-care applications. By targeting specific biomarkers or genetic material, biosensors utilise technologies like surface plasmon resonance and microarrays, providing a direct and efficient means of diagnosing neurotropic infections. This review explores the evolving landscape of biosensor-based methods, highlighting their potential to enhance the diagnostic toolkit for neurotropic viruses.

Case report: A toxoplasmic encephalitis in an immunocompromised child detected through metagenomic next-generation sequencing

There exist numerous pathogens that are capable of causing infections within the central nervous system (CNS); however, conventional detection and analysis methods prove to be challenging. Clinical diagnosis of CNS infections often depends on clinical characteristics, cerebrospinal fluid (CSF) analysis, imaging, and molecular detection assays. Unfortunately, these methods can be both insensitive and time consuming, which can lead to missed diagnoses and catastrophic outcomes, especially in the case of infrequent diseases. Despite the application of appropriate prophylactic regimens and evidence-based antimicrobial agents, CNS infections continue to result in significant morbidity and mortality in hospital settings. Metagenomic next-generation sequencing (mNGS) is a novel tool that enables the identification of thousands of pathogens in a target-independent manner in a single run. The role of this innovative detection method in clinical pathogen diagnostics has matured over time. In this particular research, clinicians employed mNGS to investigate a suspected CNS infection in a child with leukemia, and unexpectedly detected Toxoplasma gondii.

Case

A 3-year-old child diagnosed with T-cell lymphoblastic lymphoma was admitted to our hospital due to a 2-day history of fever and headache, along with 1 day of altered consciousness. Upon admission, the patient's Glasgow Coma Scale score was 14. Brain magnetic resonance imaging revealed multiple abnormal signals. Due to the patient's atypical clinical symptoms and laboratory test results, determining the etiology and treatment plan was difficulty.Subsequently, the patient underwent next-generation sequencing examination of cerebrospinal fluid. The following day, the results indicated the presence of Toxoplasma gondii. The patient received treatment with a combination of sulfamethoxazole (SMZ) and azithromycin. After approximately 7 days, the patient's symptoms significantly improved, and they were discharged from the hospital with oral medication to continue at home. A follow-up polymerase chain reaction (PCR) testing after about 6 weeks revealed the absence of Toxoplasma.

Conclusion

This case highlights the potential of mNGS as an effective method for detecting toxoplasmic encephalitis (TE). Since mNGS can identify thousands of pathogens in a single run, it may be a promising detection method for investigating the causative pathogens of central nervous system infections with atypical features.

The clinical application of metagenomic next-generation sequencing in infectious diseases at a tertiary hospital in China

Background

Compared with traditional diagnostic methods (TDMs), rapid diagnostic methods for infectious diseases (IDs) are urgently needed. Metagenomic next-generation sequencing (mNGS) has emerged as a promising diagnostic technology for clinical infections.

Methods

This retrospective observational study was performed at a tertiary hospital in China between May 2019 and August 2022. The chi-square test was used to compare the sensitivity and specificity of mNGS and TDMs. We also performed a subgroup analysis of the different pathogens and samples.

Results

A total of 435 patients with clinical suspicion of infection were enrolled and 372 (85.5%) patients were finally categorized as the ID group. The overall sensitivity of mNGS was significantly higher than that of the TDMs (59.7% vs. 30.1%, P < 0.05). However, there was no significant difference in the overall specificity between the two methods (83.3% vs. 89.6%, P = 0.37). In patients with identified pathogens, the positive rates of mNGS for detecting bacteria (88.7%), fungi (87.9%), viruses (96.9%), and Nontuberculous mycobacteria (NTM; 100%) were significantly higher than those of TDMs (P < 0.05). The positive rate of mNGS for detecting Mycobacterium tuberculosis was not superior to that of TDMs (77.3% vs. 54.5%, P = 0.11). The sensitivity rates of mNGS for pathogen identification in bronchoalveolar lavage fluid, blood, cerebrospinal fluid, pleural fluid, and tissue were 72.6%, 39.3%, 37.5%, 35.0% and 80.0%, respectively.

Conclusion

With the potential for screening multiple clinical samples, mNGS has an overall advantage over TDMs. It can effectively identify pathogens, especially those that are difficult to identify using TDMs, such as NTM, chlamydia, and parasites.

Evaluation of vancomycin pharmacokinetics in patients with augmented renal clearances: A randomized clinical trial

Purpose: Vancomycin is a narrow therapeutic window glycopeptide antibiotic that acts against Gram-positive bacteria. As it is renally eliminated, therapeutic drug monitoring is recommended for vancomycin, especially in case of kidney function alteration. Augmented renal clearance (ARC), defined as a creatinine clearance of more than 130 ml/min, is a risk factor for sub-therapeutic concentrations of vancomycin. This study aimed to evaluate the vancomycin pharmacokinetics following the administration of two different regimens in ARC patients.

Methods: A randomized clinical trial (IRCT20180802040665N1) was conducted on patients in need of vancomycin therapy. Eight hours of urine was collected and 56 patients divided into two groups with creatinine clearance of more than 130 ml/min were included in the study. The first group received 15 mg/kg of vancomycin every 12 h and the second group 15 mg/kg every 8 h. After four doses, the peak and trough concentrations were measured from two blood samples. The primary outcome was the percentage of patients who attainted AUC more than 400. The occurrence of acute kidney injury also was evaluated after seven days.

Results: The mean age of patients in the every 12 h and every 8 h groups was 44.04 ± 16.55 and 42.86 ± 11.83 years, respectively. While neurosurgical issues were the most common causes of hospitalization, central nervous infections were the most common indications for vancomycin initiation. Urinary creatinine clearance was 166.94 ± 41.32 ml/min in the every 12 h group and 171.78 ± 48.56 ml/min in the every 8 h group. 46.42% of patients in the every 12 h group and 82.14% of patients in the every 8 h group attained AUC/MIC of more than 400 mg × hr/L. None of the patients in the every 12 h group reached more than 15 mcg/ml concentration. At the 7-day follow-up, 10.7% patients in the BD group and 28.6% patients in the TDS group developed acute kidney injury (p = 0.089).

Conclusion: Administration of vancomycin at a dose of 15 mg/kg every 8 h is associated with higher pharmacokinetic attainment in ARC patients. The occurrence of acute kidney injury also was not significantly higher in this therapeutic regimen. AUC/MIC monitoring is necessary in this population.

Inconsistency analysis between metagenomic next-generation sequencing results of cerebrospinal fluid and clinical diagnosis with suspected central nervous system infection

Background

Recently, with the rapid progress of metagenomic next-generation sequencing (mNGS), inconsistency between mNGS results and clinical diagnoses has become more common. There is currently no reasonable explanation for this, and the interpretation of mNGS reports still needs to be standardised.

Methods

A retrospective analysis was conducted on 47 inpatients with suspected central nervous system (CNS) infections, and clinical data were recorded. The final diagnosis was determined by an expert group based on the patient’s clinical manifestation, laboratory examination, and response to treatment. mNGS results were compared with the final diagnosis, and any inconsistencies that occurred were investigated. Finally, the credibility of mNGS results was evaluated using the integral approach, which consists of three parts: typical clinical features, positive results with the traditional method, and cerebrospinal fluid cells ≥ 100 (× 10⁶/L) or protein ≥ 500 mg/L, with one point for each item.

Results

Forty-one patients with suspected CNS infection were assigned to infected (ID, 31/41, 75.61%) and non-infected groups (NID, 10/41, 24.39%) after assessment by a panel of experts according to the composite diagnostic criteria. For mNGS-positive results, 20 of the 24 pathogens were regarded as contaminants when the final score was ≤ 1. The remaining 11 pathogens detected by mNGS were all true positives, which was consistent with the clinical diagnosis when the score was ≥ 2. For mNGS negative results, when the score was ≥ 2, the likelihood of infection may be greater than when the score is ≤ 1.

Conclusion

The integral method is effective for evaluating mNGS results. Regardless of whether the mNGS result was positive or negative, the possibility of infection was greater when the score was ≥ 2. A negative mNGS result does not necessarily indicate that the patient was not clinically infected, and, therefore, clinical features are more important.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12879-022-07729-0.

Trends and Developments in the Detection of Pathogens in Central Nervous System Infections: A Bibliometric Study

Introduction

Rapid, sensitive, and specific laboratory assays are critical for the diagnosis and management of central nervous system (CNS) infections. The purpose of this study is to explore the intellectual landscape of research investigating methods for the detection of pathogens in patients with CNS infections and to identify the development trends and research frontier in this field.

Methods

A bibliometric study is conducted by analyzing literature retrieved from the Web of Science (WoS) Core Collection Database for the years 2000 to 2021. CiteSpace software is used for bibliometric analysis and network visualization, including co-citation analysis of references, co-occurrence analysis of keywords, and cooperation network analysis of authors, institutions, and countries/regions.

Results

A total of 2,282 publications are eventually screened, with an upward trend in the number of publications per year. The majority of papers are attributed to the disciplines of MICROBIOLOGY, INFECTIOUS DISEASES, IMMUNOLOGY, NEUROSCIENCES & NEUROLOGY, and VIROLOGY. The co-citation analysis of references shows that recent research has focused on the largest cluster “metagenomic next-generation sequencing”; the results of the analysis of the highest-cited publications and the citation burst of publications reveal that there is a strong interest stimulated in metagenomic next-generation sequencing. The co-occurrence analysis of keywords indicates that “infection”, “pathogen”, “diagnosis”, “gene”, “virus”, “polymerase chain reaction”, “cerebrospinal fluid”, “epidemiology”, and “metagenomic next-generation sequencing” are the main research priorities in the field of pathogen detection for CNS infections, and the keyword with the highest strength of burst is “metagenomic next-generation sequencing”. Collaborative network analysis reveals that the USA, the Centers for Disease Control and Prevention of USA, and XIN WANG and JENNIFER DIEN BARD are the most influential country, institution, and researchers, respectively.

Conclusions

Exploring more advanced laboratory assays to improve the diagnostic accuracy of pathogens is essential for CNS infection research. Metagenomic next-generation sequencing is emerging as a novel useful unbiased approach for diagnosing infectious diseases of the CNS.

Value of lipocalin 2 as a potential biomarker for bacterial meningitis

OBJECTIVES

Central nervous system (CNS) infections are common causes of morbidity and mortality worldwide. We aimed to discover protein biomarkers that could rapidly and accurately identify the likely cause of the infections, essential for clinical management and improving outcome.

METHODS

We applied liquid chromatography tandem mass spectrometry on 45 cerebrospinal fluid (CSF) samples from a cohort of adults with and without CNS infections to discover potential diagnostic biomarkers. We then validated the diagnostic performance of a selected biomarker candidate in an independent cohort of 364 consecutively treated adults with CNS infections admitted to a referral hospital in Vietnam.

RESULTS

In the discovery cohort, we identified lipocalin 2 (LCN2) as a potential biomarker of bacterial meningitis (BM) other than tuberculous meningitis. The analysis of the validation cohort showed that LCN2 could discriminate BM from other CNS infections (including tuberculous meningitis, cryptococcal meningitis and virus/antibody-mediated encephalitis), with sensitivity of 0.88 (95% confident interval (CI), 0.77-0.94), specificity of 0.91 (95% CI, 0.88-0.94) and diagnostic odds ratio of 73.8 (95% CI, 31.8-171.4). LCN2 outperformed other CSF markers (leukocytes, glucose, protein and lactate) commonly used in routine care worldwide. The combination of LCN2, CSF leukocytes, glucose, protein and lactate resulted in the highest diagnostic performance for BM (area under the receiver operating characteristics curve, 0.96; 95% CI, 0.93-0.99). Data are available via ProteomeXchange with identifier PXD020510.

CONCLUSIONS

LCN2 is a sensitive and specific biomarker for discriminating BM from a broad spectrum of other CNS infections. A prospective study is needed to assess the diagnostic utility of LCN2 in the diagnosis and management of CNS infections.

Molecular and Histologic Diagnosis of Central Nervous System Infections

Infections of the central nervous system cause significant morbidity and mortality in immunocompetent and immunocompromised individuals. A wide variety of microorganisms can cause infections, including bacteria, mycobacteria, fungi, viruses, and parasites. Although less invasive testing is preferred, surgical biopsy may be necessary to collect diagnostic tissue. Histologic findings, including special stains and immunohistochemistry, can provide a morphologic diagnosis in many cases, which can be further classified by molecular testing. Correlation of molecular, culture, and other laboratory results with histologic findings is essential for an accurate diagnosis, and to minimize false positives from microbial contamination.