Abstract
BACKGROUND: Metagenomic high-throughput sequencing (mNGS) represents a powerful tool for detecting nucleic acids from various pathogens, such as bacteria, fungi, viruses and parasites, in clinical samples. Despite its extensively employed in the pathogen diagnosis for various infectious diseases, its application in diagnosing stroke-related infection, and its potential impact on clinical decision-making, anti-infection treatment, clinical intervention, and patient prognosis remain insufficiently explored. Additionally, while mNGS offers promising potential, it facts limitations related to sensitivity, specificity, cost, and standardization, which could influence its integration into routine clinical practice. METHODS: We retrospectively analyzed 18 stroke patients admitted to the First Affiliated Hospital of Medical College of Shantou University from January to February 2023, comparing culture-based methods with mNGS detection, and assessing its significance in etiological diagnosis. Additionally, we evaluated the performance differences among various sequencing platforms. RESULTS: Among the 18 stroke patients enrolled, pulmonary infections were identified in 7 cases, urinary tract infections in 1 case, central nervous system infections in 10 cases, and combined pulmonary and central nervous system infections in 2 cases, with 2 cases yielding negative results. mNGS detected pathogens in 13 cases, aligning with clinical diagnoses (75% concordance), whereas culture-based methods yielded positive results in only 6 cases (22% concordance). Importantly, for 9 of the 18 patients, adjustments to anti-infective treatment regimens based on mNGS results led to improved symptomatic relief and infection control. This suggests that mNGS can contribute to more timely and precise treatment modifications, particularly for infections with low pathogen loads, potentially enhancing clinical outcomes. CONCLUSION: Our findings highlights the utility of mNGS in diagnosing stroke-associated infections by providing a more comprehensive etiological diagnosis compared to traditional method. While mNGS shows promise in enhancing diagnostic accuracy and guiding clinical treatment, it high cost and technical challenges need addressing before widespread clinical adoption. Future research should focus on optimizing mNGS protocols, integration it with convertional diagnostic tools, and evaluating its cost-effectiveness and clinical impact through larger, multicentric studies.