BACKGROUND: 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. METHODS: 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. RESULTS: 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). CONCLUSIONS: 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.
BACKGROUND: 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. METHODS: 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. RESULTS: 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). CONCLUSIONS: 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.
Authors: Marian Christoph Neidert; Michael Sprenger; Heini Wernli; Jan-Karl Burkhardt; Niklaus Krayenbühl; Oliver Bozinov; Luca Regli; Christoph Michael Woernle Journal: PLoS One Date: 2013-12-02 Impact factor: 3.240
Authors: Robert Gürkov; Ralf Strobl; Nina Heinlin; Eike Krause; Bernhard Olzowy; Christina Koppe; Eva Grill Journal: PLoS One Date: 2016-04-20 Impact factor: 3.240
Authors: Ignasi Garcia-Olivé; Jose Antonio Fiz; Jose Sanz-Santos; Felipe Andreo; Estefanía Sánchez-Martínez; Jaume Sampere; Jordi Muchart; Josep Maria Michavila; Juan Ruiz-Manzano Journal: Multidiscip Respir Med Date: 2012-12-05