[Pubmed] The systemic inflammation markers as possible indices for predicting respiratory failure and outcome in patient

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[Pubmed] The systemic inflammation markers as possible indices for predicting respiratory failure and outcome in patient

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Ann Clin Transl Neurol. 2022 Dec 1. doi: 10.1002/acn3.51706. Online ahead of print.

ABSTRACT

OBJECTIVE: This study aimed to explore the relationship between systemic inflammation markers and clinical activity, respiratory failure, and prognosis in patients with myasthenia gravis (MG).

METHODS: One hundred and seventeen MG patients and 120 controls were enrolled in this study. Differences in the four immune-related markers of two groups based on blood cell counts: neutrophil to lymphocyte ratio (NLR), platelet to lymphocyte ratio (PLR), lymphocyte to monocyte ratio (LMR), and systemic immune-inflammation index (SII) were measured. The stability of the associations between systemic inflammation markers and respiratory failure in MG patients was confirmed by adjusted logistic regression analysis. Moreover, Kaplan-Meier curve and multivariate COX regression models were applied to assess the factors affecting the outcome of MG.

RESULTS: NLR, PLR, and SII were higher in MG patients than those in controls and were positively associated with MGFA classification, but not LMR. Adjusted logistic regression analysis showed that PLR was an independent predictor of MG with respiratory failure. The ROC curve demonstrated that PLR showed good sensitivity and specificity for the diagnosis of MG with respiratory failure. Kaplan-Meier curve showed that GMG, positive AchR-Ab, respiratory failure, high NLR, PLR, SII, and IVIg exposure correlated with the risk for poor outcomes in MG patients. The multivariate COX regression models indicated that GMG and high SII was a risk factor for poor outcome of MG.

INTERPRETATION: The systemic inflammation markers expressed abnormally in MG patients, in which PLR may be an independent predictor of respiratory failure, and high SII and GMG were predictive risk factors for poor outcomes in MG patients.

PMID:36453129 | DOI:10.1002/acn3.51706


Source: https://pubmed.ncbi.nlm.nih.gov/3645312 ... 7&v=2.17.8
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