{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,13]],"date-time":"2026-05-13T05:13:32Z","timestamp":1778649212899,"version":"3.51.4"},"reference-count":47,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2026,5,13]],"date-time":"2026-05-13T00:00:00Z","timestamp":1778630400000},"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. Neurol."],"abstract":"<jats:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>Myasthenia gravis (MG) and Guillain\u2013Barr\u00e9 syndrome (GBS) are immune mediated neuromuscular disorders that may require intensive immunotherapy and respiratory support. Although inflammatory biomarkers have been explored in both conditions, their diagnosis specific prognostic value remains unclear. We aimed to compare hemogram-derived inflammatory indices and metabolic injury-related biomarkers in hospitalized MG and GBS patients and to evaluate their associations with disease severity and clinical outcomes.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>This retrospective cohort study included 162 patients (88 MG, 74 GBS) treated with intravenous immunoglobulin and\/or plasma exchange. Hemogram-derived indices (neutrophil-to-lymphocyte ratio [NLR], systemic immune\u2013inflammation index [SII]), classical inflammatory markers, and metabolic biomarkers including lactate dehydrogenase (LDH) and the LDH to albumin ratio (LAR) were analyzed in relation to neurological severity, length of hospital stay (LOS), and mechanical ventilation (MV). Receiver operating characteristic analyses and diagnosis-specific multivariable logistic regression models were performed.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>\n                      Mechanical ventilation occurred in 10.5% of patients and was strongly associated with baseline neurological severity in both disorders (\n                      <jats:italic>p<\/jats:italic>\n                      &amp;lt; 0.001). In MG, hemogram-derived indices (particularly NLR and SII) demonstrated good discriminatory performance for severe disease and were associated with adverse outcomes. LDH-based parameters, particularly LAR, which may reflect metabolic stress, were associated with disease severity and respiratory involvement in MG. In GBS, outcomes were predominantly determined by neurological severity measures, whereas inflammatory indices showed limited and inconsistent prognostic value. Post-treatment transaminase elevations were modestly associated with more severe disease in GBS. In multivariable models, baseline clinical severity remained the most consistent determinant of mechanical ventilation across both conditions.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>Biomarker utility differs between MG and GBS. In MG, inflammatory indices and LDH-based parameters, particularly the LAR, were associated with disease severity and may support risk stratification, including identification of patients at risk for respiratory deterioration. These findings are exploratory and require prospective validation. In GBS, outcomes remain primarily determined by neurological severity.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.3389\/fneur.2026.1820825","type":"journal-article","created":{"date-parts":[[2026,5,13]],"date-time":"2026-05-13T04:46:21Z","timestamp":1778647581000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["Disease-specific divergence of inflammatory and metabolic biomarkers in neurocritical neuromuscular disorders"],"prefix":"10.3389","volume":"17","author":[{"given":"Sezgin","family":"Kehaya","sequence":"first","affiliation":[{"name":"Department of Neurology, Faculty of Medicine, Trakya University","place":["Edirne, T\u00fcrkiye"]}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Erdi","family":"\u015eens\u00f6z","sequence":"additional","affiliation":[{"name":"Department of Neurology, Faculty of Medicine, Trakya University","place":["Edirne, T\u00fcrkiye"]}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1965","published-online":{"date-parts":[[2026,5,13]]},"reference":[{"key":"B1","doi-asserted-by":"publisher","first-page":"1214","DOI":"10.1016\/S0140-6736(21)00517-1","article-title":"Guillain-barr\u00e9 syndrome","volume":"397","author":"Shahrizaila","year":"2021","journal-title":"Lancet."},{"key":"B2","doi-asserted-by":"publisher","first-page":"1023","DOI":"10.1016\/S1474-4422(15)00145-3","article-title":"Myasthenia gravis: subgroup classification and therapeutic strategies","volume":"14","author":"Gilhus","year":"2015","journal-title":"Lancet Neurol."},{"key":"B3","doi-asserted-by":"publisher","first-page":"117","DOI":"10.1016\/j.jocn.2022.10.017","article-title":"Feng, J. 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