{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,15]],"date-time":"2026-06-15T05:55:09Z","timestamp":1781502909926,"version":"3.54.1"},"reference-count":44,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2026,6,15]],"date-time":"2026-06-15T00:00:00Z","timestamp":1781481600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Cell. Infect. Microbiol."],"abstract":"<jats:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>Bloodstream infections (BSI) in intensive care unit (ICU) patients are associated with high morbidity and mortality, necessitating rapid and accurate pathogen identification to guide early antimicrobial therapy. However, traditional blood culture (BC) is limited by the long turnaround time and low sensitivity. Metagenomic next-generation sequencing (mNGS) has been applied in infectious disease diagnostics, but its clinical utility for perioperative ICU patients with BSI requires further evaluation.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>\n                      This\n                      <jats:italic>post-hoc<\/jats:italic>\n                      analysis included 219 perioperative ICU patients (from a prospective, multi-center cohort, July 2020\u2013June 2023) who underwent concurrent mNGS and BC testing. The study compared pathogen detection differences between the two methods, and evaluated the diagnostic value of mNGS for clinical BSI based on mNGS-assisted clinical diagnostic criteria. Additionally, the impact of mNGS findings on clinical antimicrobial management was assessed.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>\n                      mNGS demonstrated a higher overall pathogen detection rate than BC in the 219 enrolled patients (25.1% vs. 9.6%,\n                      <jats:italic>p<\/jats:italic>\n                      \u00a0&amp;lt;\u00a00.001), with significant advantages in detecting Gram-negative bacteria (13.2% vs. 5.9%,\n                      <jats:italic>p<\/jats:italic>\n                      \u00a0=\u00a00.009), anaerobes (3.6% vs. 0.5%,\n                      <jats:italic>p<\/jats:italic>\n                      \u00a0=\u00a00.018), and fungi (6.4% vs. 0.9%,\n                      <jats:italic>p<\/jats:italic>\n                      \u00a0=\u00a00.002). Mixed-pathogen infections were identified in 20% of mNGS-positive clinical BSI cases, whereas BC-positive cases exclusively had single-pathogen infections. Ultimately, 64 patients (29.2%) were diagnosed with clinical BSIs. The sensitivity and specificity of the mNGS were 85.9% (95% CI: 74.5%\u201393.0%), and 80.6% (95% CI: 73.4%\u201386.4%), respectively, and the area under the receiver operating characteristic curve was 0.833 (95% CI: 0.772\u20130.894). The positive predictive value and negative predictive value were 64.7% (95% CI: 53.5%\u201374.6%) and 93.3% (95% CI: 87.3%\u201396.7%), respectively. Additionally, mNGS led to a positive impact in 56 patients (25.6%), manifested by the identification of new pathogens and guidance for targeted therapy, a negative impact in 11 patients (5.0%), and no clinical impact in 152 patients (69.4%).\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>For perioperative ICU patients, mNGS demonstrated superior pathogen detection rates, broader microbial spectrum coverage, and enhanced polymicrobial infection detection capability versus BC. mNGS exhibited high diagnostic value for clinical BSI, with the potential to facilitate targeted antimicrobial therapy adjustments.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.3389\/fcimb.2026.1814969","type":"journal-article","created":{"date-parts":[[2026,6,15]],"date-time":"2026-06-15T05:33:52Z","timestamp":1781501632000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["Performance of metagenomic next-generation sequencing for bloodstream infections in perioperative critically ill patients- a post-hoc analysis of a prospective, multi-center cohort study"],"prefix":"10.3389","volume":"16","author":[{"given":"Qiao","family":"Qin","sequence":"first","affiliation":[{"name":"Department of Critical Care Medicine, Peking University First Hospital","place":["Beijing, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ya-Chan","family":"Ning","sequence":"additional","affiliation":[{"name":"Department of Critical Care Medicine, Xuanwu Hospital, Capital Medical University","place":["Beijing, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Sai-Nan","family":"Zhu","sequence":"additional","affiliation":[{"name":"Department of Clinical Epidemiology, Peking University First Hospital","place":["Beijing, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jia-Hui","family":"Ma","sequence":"additional","affiliation":[{"name":"Department of Anesthesiology, Peking University First Hospital","place":["Beijing, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Wei","family":"Chen","sequence":"additional","affiliation":[{"name":"Department of Intensive Care Unit, Beijing Shijitan Hospital, Capital Medical University","place":["Beijing, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Wei","family":"Tian","sequence":"additional","affiliation":[{"name":"Department of Geriatrics, Beijing Jishuitan Hospital, Capital Medical University","place":["Beijing, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Chun-Mei","family":"Wang","sequence":"additional","affiliation":[{"name":"Department of Critical Care Medicine, Xuanwu Hospital, Capital Medical University","place":["Beijing, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ying-Feng","family":"Wu","sequence":"additional","affiliation":[{"name":"Department of Critical Care Medicine, Xuanwu Hospital, Capital Medical University","place":["Beijing, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Shuang-Ling","family":"Li","sequence":"additional","affiliation":[{"name":"Department of Critical Care Medicine, Peking University First Hospital","place":["Beijing, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1965","published-online":{"date-parts":[[2026,6,15]]},"reference":[{"key":"B1","doi-asserted-by":"publisher","first-page":"D690","DOI":"10.1093\/nar\/gkac920","article-title":"CARD 2023: expanded curation, support for machine learning, and resistome prediction at the Comprehensive Antibiotic Resistance Database","volume":"51","author":"Alcock","year":"2023","journal-title":"Nucleic Acids Res."},{"key":"B2","doi-asserted-by":"publisher","first-page":"500","DOI":"10.1016\/j.bja.2019.01.009","article-title":"Systematic review and consensus definitions for the Standardised Endpoints in Perioperative Medicine (StEP) initiative: infection and sepsis","volume":"122","author":"Barnes","year":"2019","journal-title":"Br. 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