Setzer Matthias, Beck Jürgen, Hermann Elvis, Raabe Andreas, Seifert Volker, Vatter Hartmut, Marquardt Gerhard
Department of Neurosurgery, Johann Wolfgang Goethe University, 60526 Frankfurt/Main, Germany.
Surg Neurol. 2007 Mar;67(3):264-72; discussion 272. doi: 10.1016/j.surneu.2006.06.060.
The purpose of this study was to examine a possible association between standard meteorological variables and their changes and the occurrence and clinical features of SAH.
Univariate association between the clinical/radiographic variables of patients with SAH and standard meteorological variables was evaluated. Next, a multivariate analysis was performed to find independent meteorological predictors for the occurrence of SAH by using a binary logistic regression analysis.
Univariate analysis showed significant differences between bleeding days and non-bleeding days for the number of change days (maximal atmospheric difference of the day >10 hPa) (P < .001); for the maximal relative humidity (P < .05); for the maximal difference of vapor pressure of the day 24 hours before the bleeding day (P < .006) and between cluster days and noncluster days for the number of change days (P < .001); for the maximal difference of temperature of the day (P < .035); and for the maximal, minimal, and mean relative humidity (P < .027, P < .018, and P < .03, respectively). In the multivariate models, the variable "change day" (OR, 3.7; 95% CI, 1.2-11.3) and direction of the atmospheric pressure difference of the day (OR, 2.6; 95% CI, 1.8-7.8) were retained as independent predictors for the occurrence of SAH. For the variable cluster day as dependent variable, only change day was maintained in the model (OR, 6.9; 95% CI, 4.7-10.8).
Atmospheric pressure changes of more than 10 hPa within 24 hours are an independent predictor of clustering of patients with SAH. Hypertension is an independent risk factor for the occurrence of SAH at change day.
本研究旨在探讨标准气象变量及其变化与蛛网膜下腔出血(SAH)的发生及临床特征之间可能存在的关联。
评估SAH患者的临床/影像学变量与标准气象变量之间的单变量关联。接下来,通过二元逻辑回归分析进行多变量分析,以寻找SAH发生的独立气象预测因素。
单变量分析显示,出血日与非出血日在变化天数(当日最大气压差>10 hPa)方面存在显著差异(P<.001);在最大相对湿度方面(P<.05);在出血日前24小时当日水汽压的最大差值方面(P<.006);以及在聚集日与非聚集日在变化天数方面(P<.001);在当日温度的最大差值方面(P<.035);在最大、最小和平均相对湿度方面(分别为P<.027、P<.018和P<.03)。在多变量模型中,变量“变化日”(比值比[OR],3.7;95%置信区间[CI],1.2 - 11.3)和当日气压差方向(OR,2.6;95% CI,1.8 - 7.8)被保留为SAH发生的独立预测因素。对于以聚集日为因变量的情况,模型中仅保留了变化日(OR,6.9;95% CI,4.7 - 10.8)。
24小时内气压变化超过10 hPa是SAH患者聚集的独立预测因素。高血压是变化日SAH发生的独立危险因素。