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Four categories of bleeding are then defined according to the total integer score: low (<10), moderate (10 to 14), high (15 to 19), and very high (>20) [ 12].
As this can only partly be achieved, we used a mixed model approach to account for remaining patient-specific effects (i.e. consistent inter-individual differences in the assignment of blood loss to categories of bleeding intensity).
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Not all bleeding can or should be controlled surgically, however, and there are various injuries and situations that fall into the category of 'nonsurgical bleeding'.
This included the category of GI bleeding, for which a non-significant RR of 2.1 was reported in three of the meta-analyses [ 9– 11].
Although the other meta-analyses reported numerically higher incidences of a range of bleeding categories with aspirin in patients with diabetes, none of these increases was statistically significant [ 9, 10, 12, 13].
The fourth category was a combination of bleeding patterns, irregular and intermenstrual bleeding or excessive and intermenstrual bleeding.
We computed relative risk (RR) by dividing the incidence rate of bleeding in one category divided by the incidence rate in the reference category.
Several categories include subgroups specifying each type of bleeding.
Each image was classified in one of two categories, namely, bleeding or satisfactory.
The survey questionnaire asked about illness in the following four categories: vaginal bleeding, signs of possible pre-eclampsia and eclampsia, fever, and vaginal discharge.
In both databases, warfarin use generally increased with higher stroke risk among residents in the same bleeding risk category.> -wrap-foot> NNHS NaSmalll Nursing Home Survey aSmall counts (sample, n < 10); age ≥75 years was considered a bleeding risk Figure 1 shows the distribution of residents in each category of stroke and bleeding risk, without regard to warfarin use.
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