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. 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. 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 V and Odds-Ratio (OR) 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 50 patients were included in the study, of whom 75% were men. Age had values between 14 and 89 years old (median = 61) with a mean of 58.36 ±18.8 years old. Men were approximatively 8.69 years younger on average than men (Mann-Whitney test: p=0.054, showing a tendency towards statistical significane). Most cases were from Cluj (77.8%) and some were from neighboring places (Salaj, Baia Mare and Satu Mare counties, Dej, Turda).
Table 1: Demographic parameters of the sample.
Figure 1: Sex and age groups distribution (| mean, ¦ median).
Figure 2: Residence distribution.
Only 27.2% of tha victims had consumed alcohol. Of them, the average concentration was 1.65 ±0.97, with values ranging from 0.3 to 4.
Table 2: Blood alcohol.
There were no differences by gender, neither regarding alcohol consumption (25% of women and 27.9% of men, OR=0.86 [0.27, 2.74], p>0.999), nor the concentration in those who consumed alcohol (1.60 ±0.636 in women and 1.66 ±1.06 in men, p=0.907).
Table 3: Blood alcohol, by sex.
Age was not correlated to neither alcohol consumtion (T-test p=0.118), nor the concentration of blood alcohol (R=-0.297, p=0.180).
Table 4: Blood alcohol, by age.
Figure 3: Blood alcohol (| mean, ¦ median).
Most patients died due to head trauma (71.6%), followed by polytrauma (19.8%), asphyxia (5%) and head & neck trauma (3.7%). There seems to be no significant diference by sex (V=0.08, p=0.926).
Table 6: Cause of death, by Sex.
Figure 4: Cause of death, by Sex.
After examination the most comomon diagoses were intracranial hemorhage (64.2%) and cranial fractures (24.7%). There seems to be no significant diference by sex (V=0.19, p=0.730).
Table 8: Definite diagnosis, by Sex.
Figure 5: Definite diagnosis, by Sex.
Most people died in road accidents (61.7% overall, 60.0% among women and 62.3% among men), in streets or public places (19.8% overall, 15.0% among women and 21.3% among men) or in hospitals (7.4% overall, 25.0% among women and 1.6% among men). All other circumstances were only found in men: train accident (3.7%), fall (4.9%) and home or work accident (1.2% each). There seems to be a significant relation to sex (V=0.42, p=0.026).
Table 10: Circumstances, by Sex.