Haemophilus influenzae Meningitis Direct Diagnosis by Metagenomic Next-Generation Sequencing: A Case Report.
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ABSTRACT:
SUBMITTER: Morsli M
PROVIDER: S-EPMC8069228 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:The current point-of-care diagnosis of enterovirus meningitis does not identify the viral genotype, which is prognostic. In this case report, more than 81% of an Echovirus 12 genome were detected and identified by metagenomic next-generation sequencing, directly from the cerebrospinal fluid collected in a 6-month-old child with meningeal syndrome and meningitis: introducing Echovirus 12 as an etiological agent of acute meningitis in the pediatric population.
| S-EPMC8156364 | biostudies-literature
Project description:Abstract Background Metagenomic next-generation sequencing (mNGS) of CSF can identify nearly all pathogens in a single test. We previously validated a CSF mNGS assay in a licensed clinical laboratory. To date, the utility of mNGS for infectious disease diagnosis has been described in case reports and small case series, but not in a large-scale clinical trial. Methods The PDAID (“Precision Diagnosis of Acute Infectious Diseases”) study was a 1-year nationwide prospective study across 8 tertiary care hospitals to evaluate the performance and utility of a clinical metagenomic sequencing assay for diagnosis of meningitis, encephalitis, or myelitis from cerebrospinal fluid (CSF) (ClinicalTrials.gov number NCT02910037). We recruited acutely ill hospitalized inpatients lacking a diagnosis at the time of enrollment. CSF samples were processed and analyzed by mNGS testing within 1 week of receipt in the clinical microbiology laboratory, with sequencing results reported in the patient medical record and used to make contemporaneous treatment decisions. Weekly clinical microbial sequencing boards were convened to discuss mNGS results with treating physicians, and clinical impact evaluated by surveys, chart review, and direct clinician feedback. Results A total of 204 patients were enrolled. Patients were severely ill (ICU 48%, average length of stay 26 days, overall 30-day mortality 7.4%). Fifty-nine neurologic infections were diagnosed in 57 patients (27.9%). mNGS identified 15 (25.4%) infections that were missed by all conventional microbiological tests, including emerging and/or uncommon pathogens such as St. Louis encephalitis virus, hepatitis E virus acquired by lung transplant, and Nocardia farcinica. Twelve of the 15 mNGS-only diagnoses (80%) had clinical impact, with 9 of 15 (60%) guiding appropriate treatment. For diagnosis of infections by direct detection CSF testing, mNGS had 79.1% sensitivity and 98.8% specificity, versus 65.1% sensitivity and 99.4% specificity by conventional testing. Conclusion A significant proportion of neurologic infections are missed despite extensive diagnostic testing performed in tertiary care hospitals. Clinical metagenomic CSF testing was found to be useful in increasing the number of diagnosed neurologic infections and providing actionable information for physicians. Disclosures All authors: No reported disclosures.
| S-EPMC6252609 | biostudies-literature
Project description:Importance:Identifying infectious causes of subacute or chronic meningitis can be challenging. Enhanced, unbiased diagnostic approaches are needed. Objective:To present a case series of patients with diagnostically challenging subacute or chronic meningitis using metagenomic next-generation sequencing (mNGS) of cerebrospinal fluid (CSF) supported by a statistical framework generated from mNGS of control samples from the environment and from patients who were noninfectious. Design, Setting, and Participants:In this case series, mNGS data obtained from the CSF of 94 patients with noninfectious neuroinflammatory disorders and from 24 water and reagent control samples were used to develop and implement a weighted scoring metric based on z scores at the species and genus levels for both nucleotide and protein alignments to prioritize and rank the mNGS results. Total RNA was extracted for mNGS from the CSF of 7 participants with subacute or chronic meningitis who were recruited between September 2013 and March 2017 as part of a multicenter study of mNGS pathogen discovery among patients with suspected neuroinflammatory conditions. The neurologic infections identified by mNGS in these 7 participants represented a diverse array of pathogens. The patients were referred from the University of California, San Francisco Medical Center (n = 2), Zuckerberg San Francisco General Hospital and Trauma Center (n = 2), Cleveland Clinic (n = 1), University of Washington (n = 1), and Kaiser Permanente (n = 1). A weighted z score was used to filter out environmental contaminants and facilitate efficient data triage and analysis. Main Outcomes and Measures:Pathogens identified by mNGS and the ability of a statistical model to prioritize, rank, and simplify mNGS results. Results:The 7 participants ranged in age from 10 to 55 years, and 3 (43%) were female. A parasitic worm (Taenia solium, in 2 participants), a virus (HIV-1), and 4 fungi (Cryptococcus neoformans, Aspergillus oryzae, Histoplasma capsulatum, and Candida dubliniensis) were identified among the 7 participants by using mNGS. Evaluating mNGS data with a weighted z score-based scoring algorithm reduced the reported microbial taxa by a mean of 87% (range, 41%-99%) when taxa with a combined score of 0 or less were removed, effectively separating bona fide pathogen sequences from spurious environmental sequences so that, in each case, the causative pathogen was found within the top 2 scoring microbes identified using the algorithm. Conclusions and Relevance:Diverse microbial pathogens were identified by mNGS in the CSF of patients with diagnostically challenging subacute or chronic meningitis, including a case of subarachnoid neurocysticercosis that defied diagnosis for 1 year, the first reported case of CNS vasculitis caused by Aspergillus oryzae, and the fourth reported case of C dubliniensis meningitis. Prioritizing metagenomic data with a scoring algorithm greatly clarified data interpretation and highlighted the problem of attributing biological significance to organisms present in control samples used for metagenomic sequencing studies.
| S-EPMC5933460 | biostudies-literature
Project description:Whole genome sequencing direct diagnosis of Haemophilus influenzae meningitis: a case report.
| PRJEB41766 | ENA
Project description:Haemophilus influenzae meningitis direct diagnosis by whole genome sequencing: a case report.
| PRJEB41704 | ENA
Project description:Whole genome sequencing direct diagnosis of Haemophilus influenzae meningitis: a case report.
| PRJEB41765 | ENA
Project description:BackgroundTuberculous meningitis (TBM) is a severe form of extrapulmonary tuberculosis and its early diagnosis is very difficult leading to present with severe disability or die. The current study aimed to assess the accuracy of metagenomic next generation sequencing (mNGS) for TBM, and to identify a new test for the early diagnosis of TBM.MethodsWe searched for articles published in Embase, PubMed, Cochrane Library, China National Knowledge Infrastructure, and Wanfang Data up to June 30, 2020 for studies that assessed the efficacy of mNGS for the diagnosis of TBM. Then, the accuracy between mNGS and a composite reference standard (CRS) in these articles was compared using the meta-analysis approach.ResultsFour independent studies with 342 samples comparing mNGS and a CRS were included in this study. The sensitivity of mNGS for TBM diagnosis ranged from 27% to 84%. The combined sensitivity of mNGS was 61%, and the I2 value was 92%. Moreover, the specificity of mNGS for TBM diagnosis ranged from 96% to 100%. The combined specificity of mNGS was 98%, and the I2 value was 74%. The heterogeneity between studies in terms of sensitivity and specificity was significant. The area under the curve (AUC) of the summary receiver operating characteristic curve (SROC) of mNGS for TBM was 0.98.ConclusionsThe sensitivity of mNGS for TBM diagnosis was moderate. Furthermore, the specificity was extremely high, and the AUC of the SROC indicated a very good diagnostic efficacy. mNGS could be used as an early diagnostic method for TBM, however, the results should be treated with caution for the heterogeneity between studies was extremely significant.Systematic review registrationINPLASY202070100.
| S-EPMC7707562 | biostudies-literature
Project description:Background: Talaromycosis is a serious fungal infection which is rare in immunocompetent people. Since its clinical manifestations lack specificity, it is easy to escape diagnosis or be misdiagnosed leading to high mortality and poor prognosis. It is necessary to be alert to the disease when broad-spectrum antibiotics do not work well in immunocompetent patients. Case Presentation: A 79-year-old man was admitted to our Infectious Diseases Department for recurrent fever and cough. Before admission he has been treated with piperacillin-tazobactam, moxifloxacin followed by antituberculous agents in other hospitals while his symptoms were not thoroughly eased. During the first hospitalization in another hospital, he has been ordered a series of examination including radionuclide whole body bone imaging, transbronchial needle aspiration for subcarinal nodes. However, the results were negative showing no neoplasm. After being admitted to our hospital, he underwent various routine examinations. The initial diagnosis was bacterial pneumonia, and he was given meropenem injection and tigecycline injection successively, but there were no improvement of symptoms and inflammatory indicators. In the end, the main pathogen Talaromyces marneffei was confirmed using Metagenomic Next-Generation Sequencing (mNGS), and his clinical symptoms gradually relieved after targeted antifungal treatment using voriconazole. Conclusion: When empirical anti-infective treatment is ineffective, it is necessary to consider the possibility of opportunistic fungal infections on immunocompetent patients. mNGS, as a new generation of pathogenic testing methods, can often detect pathogenic bacteria faster than traditional methods, providing important help for clinical decision-making.
| S-EPMC8039304 | biostudies-literature
Project description:BackgroundMetagenomic next-generation sequencing (mNGS) is emerging as a promising technique for pathogens detection. However, reports on the application of mNGS in mixed pulmonary infection remain scarce.MethodsFrom July 2018 to March 2019, 55 cases were enrolled in this retrospective analysis. Cases were classified into mixed pulmonary infection (36 [65.5%]) and non-mixed pulmonary infection (19 [34.5%]) according to primary diagnoses. The performances of mNGS and conventional test on mixed pulmonary infection diagnosis and pathogen identification were compared.ResultsThe sensitivity of mNGS in mixed pulmonary infection diagnosis was much higher than that of conventional test (97.2% vs 13.9%; P?< 0.01), but the specificity was the opposite (63.2% vs 94.7%; P?= 0.07). The positive predictive value of mNGS was 83.3% (95% CI, 68.0-92.5%), and the negative predictive value was 92.3% (95% CI, 62.1-99.6%). A total of 5 (9.1%) cases were identified as mixed pulmonary infection by both conventional tests and mNGS, however, the pathogens identification results were consistent between these two methods in only 1 (1.8%) case. In summary, the pathogens detected by mNGS in 3 (5.5%) cases were consistent with those by conventional test, and only 1 (1.8%) case was mixed pulmonary infection. According to our data, mNGS had a broader spectrum for pathogen detection than conventional tests. In particular, application of mNGS improved the diagnosis of pulmonary fungal infections. Within the 55 cases, mNGS detected and identified fungi in 31 (56.4%) cases, of which only 10 (18.2%) cases were positive for the same fungi by conventional test. The most common pathogen detected by mNGS was Human cytomegalovirus in our study, which was identified in 19 (34.5%) cases of mixed pulmonary infection. Human cytomegalovirus and Pneumocystis jirovecii, which were detected in 7 (12.7%) cases, were the most common co-pathogens in the group of mixed pulmonary infection.ConclusionsmNGS is a promising technique to detect co-pathogens in mixed pulmonary infection, with potential benefits in speed and sensitivity.Trial registration(retrospectively registered): ChiCTR1900023727. Registrated 9 JUNE 2019.
| S-EPMC6921575 | biostudies-literature
Project description:Disseminated tuberculosis (TB) is a rare disease and mainly occurs in immunodeficient patients. It is marked by hematogenous or lymphatic dissemination of Mycobacterium tuberculosis, causing tuberculous infection involving any organ system. Here, we report a case of disseminated TB involving lung, liver, spine, mediastinum, and prostate in an immunocompetent man. The present patient found a hepatic mass without any symptom during health examination. In the next 2 years, further examinations revealed multiple lesions in the lung, mediastinum, spine, and prostate. Imaging examinations, such as contrast-enhanced abdominal CT, F-18 FDG-PET/CT, and radionuclide bone scan, suggested the diagnosis of malignancy or metastatic tumor. Furthermore, histopathological results of the biopsies of the hepatic mass, mediastinal mass, and prostatic mass demonstrated granulomatous inflammation. Therefore, metagenomic next-generation sequencing (mNGS) was utilized to confirm the diagnosis. Mycobacterium tuberculosis complex was simultaneously detected in the spinal surgical resection specimens and bronchoalveolar lavage fluid (BALF), indicating the diagnosis of disseminated TB. mNGS is an emerging molecular diagnostic technology, and its application in disseminated TB has been rarely reported. We highlight that disseminated TB should be considered even in an immunocompetent patient, and mNGS can be performed when the diagnosis is difficult.
| S-EPMC8310911 | biostudies-literature