Table 3:
Univariate and Stepwise logistic regression of predictor variables and functional assay positivity
| Cohort - Variable | Odds Ratio (95%CI) | P-value |
|---|---|---|
| Univariate Regression | ||
| McMaster | ||
| Anti-PF4/heparin IgG antibody1 | 51.84 (37.27-74.34) | <2*10−16 |
| Sex (female) | 1.47 (1.19,1.82) | 0.00035 |
| Age (per year) | 1.003 (0.996,1.01) | 0.442 |
| Surgery | 1.30 (0.94,1.78) | 0.107 |
| Greifswald | ||
| Anti-PF4/heparin IgG antibody1 | 15.475 (13.185,18.284) | <2*10−16 |
| Sex (female) | 1.12 (0.975,1.276) | 0.112 |
| Age (per year) | 0.999 (0.994-1.004) | 0.89 |
| Immunoglobulin A (IgA)2 | 4.578 (3.867-5.444) | <2*10−16 |
| Immunoglobulin M (IgM)2 | 3.989 (2.47-3.625) | <2*10−16 |
| Tours | ||
| Anti-PF4/heparin IgG antibody1 | 15.82 (10.21-25.87) | <2*10−16 |
| Sex (female) | 2.89 (2.08-4.04) | 3.49*10−10 |
| Age (per year) | 0.98 (0.96-0.997) | 0.024 |
| Platelet Count Before Heparin Therapy (1x109 platelets/L) | 1.003 (1.00-1.006) | 0.0184 |
| Stepwise Regression 3 | ||
| McMaster | ||
| Anti-PF4/heparin IgG antibody1 | 37.78 (24.99, 60.40) | <2*10−16 |
| Sex (female) | 1.74 (0.94, 3.26) | 0.0791 |
| Greifswald | ||
| Anti-PF4/heparin IgG antibody1 | 15.66 (13.33-18.52) | <2*10−16 |
| Sex (female) | 1.23 (1.01-1.49) | 0.0327 |
| Tours | ||
| Anti-PF4/heparin IgG antibody1 | 21.81 (13.7-37.26) | <2*10−16 |
| Sex (female) | 2.25 (1.21-4.22) | 0.011 |
Logistic regression summary statistics for association of antibodies, sex, or age and functional assay positivity across all three cohorts. Case status was determined via the results of the function assay tests. 95%CI indicates 95% confidence interval; LMWH, low molecular weight heparin; OD, optical density; PF4 platelet factor 4.
Polyspecific anti-PF4/heparin antibody levels were determined using enzyme-linked immunosorbent assay (ELISA) and ORs are calculated per 1 OD unit increase.
Anti-PF4/heparin antibody IgA and IgM levels were determined via ELISA and ORs are calculated per 1 OD unit increase.
Stepwise regression variables were retained based on AIC and model improvement, while p-values were calculated for each variable in the final model, p-values were not used for variable inclusion and as such may be greater than 0.05 for this reason.