Department of Otolaryngology, Head and Neck Surgery, Hyogo Prefectural Amagasaki General Medical Center, Higashinaniwachou, 2-17-77, Amagasaki, Hyogo, 6608550, Japan.
Sci Rep. 2021 Nov 3;11(1):21586. doi: 10.1038/s41598-021-01153-1.
Pupillary light reflex (PLR) and heart rate variability (HRV) parameters can be objective indicators of chronic rhinosinusitis (CRS) status from the viewpoint of autonomic nervous system activity. This study aimed to establish objective indicators for CRS using the 22-item Sino-Nasal Outcome Test (SNOT-22) and PLR/HRV parameters. Sixty-seven patients were prospectively and longitudinally followed up after surgical treatment. We investigated changes in SNOT-22 scores, representing CRS-specific quality of life (QOL). We prepared two models: linear regression model adjusting clinical factors as predictor variables (model 1) and linear mixed-effects model adjusting clinical factors and among-individual variability (model 2). We compared Akaike's information criterion (AIC) values and regression coefficients. The model with lower AIC values was defined as the better-fit model. Model 2 showed lower AIC values in all parameters (better-fit model). Three parameters showed opposite results between the two models. The better-fit models showed significances in the five PLR parameters but not in any HRV parameters. Among these PLR parameters, constriction latency can be the most robust indicator because of the narrowest 95% confidence intervals. Adjusting the among-individual variability while investigating clinical potential of PLR/HRV parameters to reflect CRS-specific QOL can improve the model fit, thereby reaching robust conclusions from obtained data.
瞳孔对光反射（PLR）和心率变异性（HRV）参数可以从自主神经系统活动的角度作为慢性鼻-鼻窦炎（CRS）状态的客观指标。本研究旨在使用 22 项鼻-鼻窦结局测试（SNOT-22）和 PLR/HRV 参数为 CRS 建立客观指标。67 例患者在手术后进行了前瞻性和纵向随访。我们研究了 SNOT-22 评分的变化，该评分代表 CRS 特定的生活质量（QOL）。我们准备了两个模型：线性回归模型，将临床因素作为预测变量进行调整（模型 1）和线性混合效应模型，将临床因素和个体间变异性进行调整（模型 2）。我们比较了赤池信息量准则（AIC）值和回归系数。AIC 值较低的模型被定义为拟合更好的模型。在所有参数中，模型 2 的 AIC 值均较低（拟合更好的模型）。两个模型中有三个参数的结果相反。在这五个 PLR 参数中，收缩潜伏期可以作为最稳健的指标，因为其 95%置信区间最窄。在研究 PLR/HRV 参数反映 CRS 特定 QOL 的临床潜力时，调整个体间变异性可以改善模型拟合度，从而从获得的数据中得出可靠的结论。
