Factors Associated With Discordance Between Absolute CD4 Cell Count and CD4 Cell Percentage in Patients Coinfected With HIV and Hepatitis C Virus
Bibliographic record
Abstract
BACKGROUND: Liver cirrhosis has been associated with decreased absolute CD4 cell counts but preserved CD4 cell percentage in human immunodeficiency virus (HIV)-negative persons. We evaluated factors associated with discordance between the absolute CD4 cell count and the CD4 cell percentage in a cohort of patients coinfected with HIV and hepatitis C virus (HCV). METHODS: Baseline data from 908 participants in a prospective, Canadian, multisite cohort of individuals with HIV-HCV coinfection were analyzed. Absolute CD4 cell count and CD4 cell percentage relationships were evaluated. We defined low and high discordance between absolute CD4 cell count/CD4 cell percentage relationships as CD4 cell percentages that differed from the expected CD4 cell percentage, given the observed absolute CD4 cell count, by ±7 percentage points; we defined very low and very high discordance as differences of ±14 percentage points. Factors associated with high or very high discordance, including either end-stage liver disease or aspartate transaminase to platelet ratio index (APRI) of >1.5, were analyzed using multivariate logistic regression models and compared to groups with concordant and low discordant results. RESULTS: High/very high discordance was seen in 31% (n = 286), while 35% (n = 321) had concordant values. Factors associated with very high discordance at baseline included history of end-stage liver disease (adjusted odds ratio [aOR], 6.52; 95% confidence interval [CI], 2.27-18.67) and APRI of >1.5 (aOR 4.69; 95% CI, 1.64-13.35). Compared with those with detectable HCV RNA, those who cleared HCV spontaneously were less likely to have very high discordance. CONCLUSIONS: Discordance between absolute CD4 cell count and CD4 cell percentage is common in an HIV/HCV-coinfected population and is associated with advanced liver disease and ongoing HCV replication.
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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 | 0.005 |
| 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 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".