Evaluation of mean corpuscular volume among anemic people with HIV in North America following ART initiation
Bibliographic record
Abstract
Anemia is common and associated with increased morbidity among people with HIV (PWH). Classification of anemia using the mean corpuscular volume (MCV) can help investigate the underlying causative factors of anemia. We characterize anemia using MCV among PWH receiving antiretroviral therapy (ART), and identify the risk factors for normocytic, macrocytic, and microcytic anemias. Including PWH with anemia (hemoglobin measure < 12.9 g/dL among men and < 11.9 g/dL among women) in the NA-ACCORD from 01/01/2007 to 12/31/2017, we estimated the annual distribution of normocytic (80–100 femtolitre (fL)), macrocytic (> 100 fL) or microcytic (< 80 fL) anemia based on the lowest hemoglobin within each year. Poisson regression models with robust variance and general estimating equations were used to estimate crude and adjusted prevalence ratios and 95% confidence intervals for risk factors for macrocytic (vs. normocytic) and microcytic (vs. normocytic) anemia stratified by sex. Among 37,984 hemoglobin measurements that identified anemia in 14,590 PWH, 27,909 (74%) were normocytic, 4257 (11%) were microcytic, and 5818 (15%) were macrocytic. Of the anemic PWH included over the study period, 1910 (13%) experienced at least one measure of microcytic anemia and 3208 (22%) at least one measure of macrocytic anemia. Normocytic anemia was most common among both males and females, followed by microcytic among females and macrocytic among males. Over time, the proportion of anemic PWH who have macrocytosis decreased while microcytosis increased. Macrocytic (vs. normocytic) anemia is associated with increasing age and comorbidities. With increasing age, microcytic anemia decreased among females but not males. A greater proportion of PWH with normocytic anemia had CD4 counts $$\le$$ 200 cells/mm3 and had recently initiated ART. In anemic PWH, normocytic anemia was most common. Over time macrocytic anemia decreased, and microcytic anemia increased irrespective of sex. Normocytic anemia is often due to chronic disease and may explain the greater risk for normocytic anemia among those with lower CD4 counts or recent ART initiation. Identified risk factors for type-specific anemias including sex, age, comorbidities, and HIV factors, can help inform targeted investigation into the underlying causes.
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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 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".