Factors Predictors of Vascular Events with Antiphospholipids Antibodies.
Bibliographic record
Abstract
Abstract Background. The Montreal Antiphospholipid Study is an ongoing cohort study that began in 1997 that includes 415 persons followed prospectively for arterial (AE) and venous (VE) events. Objectives. To determine predictors of new thrombotic events in the presence of antiphospholipid antibodies. Methods. Blood samples were collected at baseline and annually for four years. Baseline assays included: IgG/IgM anticardiolipin antibodies (aCL), lupus anticoagulant (LA), and IgG/IgM anti-ß2-glycoprotein I antibodies (β2-GPI), activated protein C resistance (APCR), hyperhomocysteinemia (Hhcy), DDimer (DD), Factor VIII (FVIII), von Willebrand Factor (vWF), fibrinogen (FIB), high sensitivity C reactive Protein (hsCRP) levels were performed on the plasma or sera available at the visit closest to and prior to the date of new AE or VE. Demographic and clinical data were obtained at baseline and by telephone interview semi-annually. All events were confirmed by a panel of physicians. A nested case-control study was performed with 45 cases with new AE and VE during a mean follow-up period of 7.4 years [IQR = 0.5, 8.5] and 170 controls without new AE or VE matched for age, gender and visit date in a ratio of 4:1. Statistical analysis. Univariate regression models for case-control study were performed using new AE or VE as the outcome variable and aPL positivity (defined as either/or aCL IgG/IgM >40 PL units, LA or β2GPI positivity as predictor variable and DD, FVIII, vWF, FIB, hsCRP, APCR, Hhcy, family history of CVD (FMH), smoking, SLE or diabetes mellitus (DM) as covariables. Variables found to be predictors in the univariate analyses were then evaluated in multivariate regression models. Results. Mean age was 51.0; 77.7% female, 59.6% FMH, 25.1% SLE, 26.1% smokers, 5.1% DM. Thirty six (16.7%) individuals were aPL positive and 37 (17.2%) had abnormal APCR. A high degree of correlation between acquired APCR and aPL was observed. aPL positivity, smoking, DM and previous AE and VE were more frequent in cases than controls: 33% vs 12.3%, 42.2% vs 21.8%, 17.8% vs 1.8% and 53.3% vs 12.4%, respectively. Multivariate regression analyses revealed aPL positivity, previous AE, DM and smoking were predictors of new AE while predictors for new VE were APCR and vWF. Conclusions. Our findings in this nested-case control study demonstrate that aPL positivity predicts new AE. aPL positivity predicted new VE in the univariate analysis, but not in the multivariate model where APCR and vWF were the only factors retained. It is possible that APCR captures the effect of aPL as acquired APCR may be attributable to the presence of aPL. Besides vWF, APCR may be a better risk factor for VE than aPL, however more research is needed to determine their relationship. aPL is an important risk factor in AE, along with previous AE, smoking and DM. Predictor AE Univariate HR (95% CI) AE Multivariate HR (95% CI) VE Univariate HR (95% CI) VE Multivariate HR (95% CI) aPL 3.6(1.4,8.8) 3.8(1.0,14.7) 4.8(1.4,17.2) 2.2(0.3,15.0) APCR 1.8(0.8,3.9) - 5.7(1.7,18.6) 5.5(1.1,26.6) vWF 1.5(0.9,2.4) 1.0(0.4,2.6) 6.4(1.8,21.8) 5.0(1.2,19.8) DM 7.8(2.0,30.5) 9.9(1.5,64.6) - - Previous AE 7.2(2.7,19.1) 10.4(2.8,39.0) - - Previous VE - - 11.1(2.3,54.1) 1.8(0.2,16.4)
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".