To describe the quantitative variables, we used histograms and we calculated the arithmetic means ±standard deviation (SD) [with 95% confidence interval (CI)], as well as the extreme and median values. For the qualitative variables, we used pie or bar charts and calculated the absolute and percentual frequencies of the formed categories.
To study the relationships between quantitative and qualitative variables, we used the T or Mann-Whitney (MW) tests if they were binary, respectively ANOVA or Kruskal-Wallis (KW) if they had more categories. We presented the p values generated by these tests as well as the means ±SD of the groups and the difference of the means with associated 95% CI. We graphically presented the results in the form of box plots. To study the relationships between the quantitative variables we used the Spearman correlation coefficient (R), with the associated p-value and graphically presented the relations as scatter plots, on which we added the regression line. To describe the relationships between the qualitative variables we used the Chi² or Fisher test and the Cramer phi or V and Odds-Ratio (OR) / Relative Risk (RR) indicators with 95% CI. We graphically presented the results in the form of pie or bar charts.
We used Microsoft Excel 2016 for database management. For all statistical analyzes and subsequent graphs we used R 3.6.3 . We considered p <0.05 to be statistically significant and p <0.10 to show only a tendency towards statistical significance.
A total of 231 patients were included in the database. Their age had values between 21.9 and 87.3 years old (median: 63.25) with an average of 62.83 ±9.51 years. Most patients were women (59%). At discharge, only 5.6% died and most were considered cured (24.7%) or at least ameliorated (67.4%). At 1-Oct-2019, 40.3% would have died. About 7% of the patients received reinterventions and 33.8% underwent some vasular operation.
Table 1: Demographic parameters of the sample.
Figure 1: Sex distribution.
Figure 2: Age distribution, colored by sex. (| mean, ¦ median).
Most patients lived in the Cluj county (21.2%) or neighboring counties.