The Role of Human Immunodeficiency Virus–Associated Vasculopathy in the Etiology of Stroke
Bibliographic record
Abstract
Human immunodeficiency virus (HIV) infection is a recognized risk factor for stroke among young populations, but the exact mechanisms are poorly understood. We studied the clinical, radiologic, and histologic features of HIV-related ischemic stroke to gain insight into the disease mechanisms. We conducted a prospective, in-depth analysis of adult ischemic stroke patients presenting to Queen Elizabeth Central Hospital, Blantyre, Malawi, in 2011. We recruited 64 HIV-infected and 107 HIV-uninfected patients. Those with HIV were significantly younger (P < .001) and less likely to have established vascular risk factors. Patients with HIV were more likely to have large artery disease (21% vs 10%; P < .001). The commonest etiology was HIV-associated vasculopathy (24 [38%]), followed by opportunistic infections (16 [25%]). Sixteen of 64 (25%) had a stroke soon after starting antiretroviral therapy (ART), suggesting an immune reconstitution–like syndrome. In this group, CD4+ T-lymphocyte count was low, despite a significantly lower HIV viral load in those recently started on treatment (P < .001). HIV-associated vasculopathy and opportunistic infections are common causes of HIV-related ischemic stroke. Furthermore, subtypes of HIV-associated vasculopathy may manifest as a result of an immune reconstitution–like syndrome after starting ART. A better understanding of this mechanism may point toward new treatments.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".