MOESM3 of Impact of gender on post- traumatic intensive care and outcomes

Additional file 3: Table S3. Associations between baseline and injury characteristics and 1-year mortality, unadjusted and adjusted HR (95% CI)

Additional file 1 of Impact of gender on post- traumatic intensive care and outcomes

Additional file 1: Table S1. Associations between patient- and injury characteristics and ICU admission, adjusted OR (95% CI)

Additional file 3 of Impact of gender on post- traumatic intensive care and outcomes

Additional file 3: Table S3. Associations between baseline and injury characteristics and 1-year mortality, unadjusted and adjusted HR (95% CI)

MOESM2 of Impact of gender on post- traumatic intensive care and outcomes

Additional file 2: Table S2. Associations between baseline and injury characteristics and 30-day mortality, unadjusted and adjusted HR (95% CI)

MOESM1 of Impact of gender on post- traumatic intensive care and outcomes

Additional file 1: Table S1. Associations between patient- and injury characteristics and ICU admission, adjusted OR (95% CI)

Additional file 2 of Impact of gender on post- traumatic intensive care and outcomes

Additional file 2: Table S2. Associations between baseline and injury characteristics and 30-day mortality, unadjusted and adjusted HR (95% CI)

Additional file 1: Table S1. of A clinical model for identifying the short-term risk of breast cancer

Relative risk of developing breast cancer in relation to mammographic density, number microcalcifications and number masses. Table S2. Relative risks on developing breast cancer in relation to tumor invasiveness and mode of detection. Table S3. Final model including main effects of risk factors, beta coefficients, standard errors and p-values. Table S4. Number of breast cancer cases diagnosed during study follow-up stratified by predicted risks at baseline in the Karma cohort. Supplementary Method 1. Supplementary Method 2. Supplementary Method 3. (DOCX 59 kb

Additional file 1 of Physical activity is associated with a lower risk of contracting and dying in infection and sepsis: a Swedish population-based cohort study

Additional file 1: Fig. 1. Cohort flowchart

ACR900436 Supplemental Material - Supplemental material for The association of single nucleotide polymorphisms (SNPs) with breast density and breast cancer survival: the Malmö Diet and Cancer Study

Supplemental material, ACR900436 Supplemental Material for The association of single nucleotide polymorphisms (SNPs) with breast density and breast cancer survival: the Malmö Diet and Cancer Study by Hanna Sartor, Jasmine Brandt, Felix Grassmann, Mikael Eriksson, Kamila Czene, Olle Melander and Sophia Zackrisson in Acta Radiologica</p

Supplementary Tables from Assessment of Breast Cancer Risk Factors Reveals Subtype Heterogeneity

Online-only supplementary tables and figures: 1. Supplementary Table 1. Cross-validated Confusion matrix for true vs. predicted subtypes in the subset of data with PAM50 subtypes available. 2. Supplementary Table 2: Case-only analysis with Luminal A as reference group: Genetic background risk. 3. Supplementary Table 3: Case-only analysis with Luminal A as reference group: Reproductive risk factors. 4. Supplementary Table 4: Case-only analysis with Luminal A as reference group: Bodyshape at age 18, Ever hormone replacement therapy (HRT) use, age at menarche, mammographic density (MD), benign breast disease (BBD). 5. Supplementary Table 5: Risk of breast cancer overall and by subtype as defined by the St Gallen IHC proxy: Genetic background risk. 6. Supplementary Table 6: Risk of breast cancer overall and by subtype as defined by the St Gallen IHC proxy: Reproductive risk factors. 7. Supplementary Table 7: Risk for breast cancer overall and by subtype as defined by the St Gallen IHC proxy: Bodyshape at age 18, Ever hormone replacement therapy (HRT) use, age at menarche, mammographic density (MD), benign breast disease (BBD).</p