Neurological sciences : official journal of the Italian Neurological Society and of the Italian Society of Clinical Neurophysiology · 2023
An S-like curve relationship between systemic inflammation response index (SIRI) and respiratory failure in GBS patients.
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Shen Qiuyan, Mu Xin, Bao Yi, Xu Fang, Zhang Dan, Luo Anling, Liu Ling, Huang Hongyan, Xu Yanming
Аннотация
BACKGROUND: Our study examined the association between the initial systemic inflammation response index (SIRI) and respiratory failure in patients with Guillain-Barré syndrome (GBS).
METHODS: The weighted linear regression model, weighted chi-square test, logistic regression models, smooth curve fittings, and the two-piece linear regression model were utilized for data analysis.
RESULTS: Among the 443 GBS patients, 75 (6.9%) had experienced respiratory failure. According to logistic regression models, there existed no consistent linear relationship between respiratory failure and SIRI in model 1 (OR = 1.2, p < 0.001), model 2 (OR = 1.2, p < 0.001), and model 3 (OR = 1.3, p = 0.017). However, smooth curve fittings found an S-like curve relationship between SIRI and respiratory failure. Furthermore, when SIRI was < 6.4, there existed a positive correlation between SIRI and respiratory failure in model 1 (OR = 1.5, 95% CI = (1.3, 1.8), p < 0.0001), higher correlation in model 2 (OR = 1.6, 95% CI = (1.3, 1.8), p < 0.0001), and highest correlation in model 3 (OR = 1.6, 95% CI = (1.3, 2.5), p < 0.0001).
CONCLUSIONS: SIRI can be used as a predictor of respiratory failure in GBS, and an S-like relationship exists between SIRI and respiratory failure at an infliction point of 6.4. When the SIRI was less than 6.4 and increased, SIRI was associated with a higher occurrence of respiratory failure. The risk of respiratory failure was no longer increased when the SIRI was over 6.4.
METHODS: The weighted linear regression model, weighted chi-square test, logistic regression models, smooth curve fittings, and the two-piece linear regression model were utilized for data analysis.
RESULTS: Among the 443 GBS patients, 75 (6.9%) had experienced respiratory failure. According to logistic regression models, there existed no consistent linear relationship between respiratory failure and SIRI in model 1 (OR = 1.2, p < 0.001), model 2 (OR = 1.2, p < 0.001), and model 3 (OR = 1.3, p = 0.017). However, smooth curve fittings found an S-like curve relationship between SIRI and respiratory failure. Furthermore, when SIRI was < 6.4, there existed a positive correlation between SIRI and respiratory failure in model 1 (OR = 1.5, 95% CI = (1.3, 1.8), p < 0.0001), higher correlation in model 2 (OR = 1.6, 95% CI = (1.3, 1.8), p < 0.0001), and highest correlation in model 3 (OR = 1.6, 95% CI = (1.3, 2.5), p < 0.0001).
CONCLUSIONS: SIRI can be used as a predictor of respiratory failure in GBS, and an S-like relationship exists between SIRI and respiratory failure at an infliction point of 6.4. When the SIRI was less than 6.4 and increased, SIRI was associated with a higher occurrence of respiratory failure. The risk of respiratory failure was no longer increased when the SIRI was over 6.4.