Haptoglobin 2-2 genotype is associated with presence and progression of MRI depicted atherosclerotic intraplaque hemorrhage
Bibliographic record
Abstract
BACKGROUND: Atherosclerotic intraplaque hemorrhage (IPH) is a source of free hemoglobin that binds the haptoglobin protein and forms a complex cleared by CD163 macrophages. Compared to the other common haptoglobin genotypes, hemoglobin-haptoglobin2-2 complex has the lowest affinity for tissue macrophages resulting in lower rate of hemoglobin uptake and increased oxidative burden. We hypothesized that haptoglobin2-2 patients' failure to clear hemoglobin results in a greater prevalence and progression of IPH. METHODS: Prevalence and volume of IPH were measured in eighty patients with advanced vascular disease using MRI. Haptoglobin was genotyped using PCR. Mixed Models Repeated Measures Analyses were performed to detect any differences in prevalence and volume of IPH between the haptoglobin genotypes. RESULTS: Haptoglobin2-2 patients had a statistically significant higher prevalence of baseline IPH (OR = 4.34, p-value: 0.01, 95% CI: 1.31-14.35). Longitudinal analysis of 48 IPH positive carotids indicated a statistically significant progression of IPH volume over time in haptoglobin2-2 patients (Type 3 test for fixed effect p-value = 0.0106; baseline vs. year 3: β = 0.11, SE = 0.05, p-value = 0.03; year 2 vs. year 3: β = 0.05, SE = 0.02, p-value = 0.03). CONCLUSIONS: Patients with the Hp2-2 genotype had a significantly higher prevalence of carotid baseline IPH, which progressed over a two year follow up period. Detection of pre-symptomatic vascular disease using haptoglobin genotyping may allow for better risk stratification of populations at risk of stroke and in need of more targeted imaging investigations.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".