Weather variables definitions
We collected weather data from the National Centers for Environmental Information (NCEI) - National Oceanic and Atmospheric Administration (NOAA) website
(https://www.ncei.noaa.gov/). We obtained daily and hourly weather data by accessing the Local Climatological Data (LCD) dataset (gov.noaa.ncdc:C00684) for the station of Philadelphia International Airport (KPHL), PA US (WBAN: 72408013739, Elev: 10 ft. Lat: 39.8733° N Lon:
-75.2268° W).
Hourly data were for the past hour closest to the arrival at the hub, while daily were for the day when the transportation took place. We used the dry-bulb temperature in Fahrenheit in whole degrees for temperature measurements. Daily precipitation (Total Liquid Content) was the water equivalent amount of precipitation in inches, including all types of precipitation (melted and frozen). Trace precipitation amount or snow depth less than 0.005 inches was reported as zero.
Station pressure was used for atmospheric pressure in inches of mercury (in Hg). Visibility (in whole miles) was defined as the horizontal distance an object can be seen and identified.
Statistical Analysis
Continuous data were presented as means and standard deviations (SD), or medians and interquartile ranges (IQR), depending on normality, while categorical variables were presented as percentages. Differences between outcomes, mode of transportation, and COVID-19 periods were assessed with chi-squared, Fisher exact tests, t-tests, or Wilcoxon rank sum tests. Linear regression was used to assess the association between weather data and time from last known normal to puncture. Binary logistic regression models were used to assess the probability of a poor functional outcome and air transportation. In both models, a backward stepwise
multivariable logistic regression was utilized, with p≥0.100 for removal and p<0.050 for addition to the model. Collinear independent variables were removed based on variance inflation factors and tolerance values prior to entry. We divided the cohort in 2 groups and did subgroup analyses for outcomes; Group A included all spoke centers that used ground transport only, and Group B included centers that used air transport in at least half of cases and/or the line distance was equal or greater than the average (26.8 miles). Logistic and linear regression models were used to
compare outcomes between modes of transportation, adjusted for covariates. Missing data were not imputed. Statistical significance was set at p<0.05. We used the mapline.com website to create a map of our stroke network. This map contains information from OpenStreetMap and OpenStreetMap Foundation, which is made available under the Open Database License.
Analyses were performed using the Stata Statistical software (version 17.0, College Station, TX).
