The Prevalence of Human Cytomegalovirus Viremia among HIV-1 Infected Individuals Undergoing Antiretroviral Therapy
Bibliographic record
Abstract
HIV infection is an emerging health issue in Libya, particularly among young adults. Human cytomegalovirus (HCMV) is a prevalent infectious agent that presents with subclinical and fatal diseases in immunosuppressed individuals including HIV-infected individuals. Although the impact of HCMV infection in HIV-positive patients is well documented in several regions, epidemiologic estimates concerning HCMV co-infection among HIV-infected individuals remain limited in Libya. Hence, this cross-sectional study was undertaken to derive data regarding the prevalence of active HCMV viremia among HIV-infected individuals undergoing antiretroviral therapy (ART) from Libya. A total of 90 consented HIV-infected subjects followed by the National Center for Disease Control (NCDC) of Benghazi/Libya were recruited in this study and investigated for HCMV-IgG, HCMV-IgM specific antibodies, detection of HCMV lower matrix phosphoprotein (pp65) antigen, and detection of HCMV-DNA using qPCR to assess the prevalence of HCMV viremia. We determined that 77 (85.56%) of subjects were seropositive for HCMV-IgG antibodies, whereas the seropositivity for HCMV-IgM was 3.33% (3/90 subjects). Our results also revealed that 4.44% (4/90) of participants had viral antigenemia based on the laboratory diagnosis of HCMV-pp65. Regarding the PCR, we were able to detect the DNA of HCMV only in 3/90 subjects (3.33%) suggesting an active viremic condition. The detection of HCMV DNA along with the HCMV-pp65 in HIV-positive individuals highlights the necessity of early diagnosis to manage the progression of the disease. Furthermore, we highly recommend the use of anti-HCMV therapy in viremic individuals in combination with ART to reduce the burden of HCMV complications.
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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 | 0.001 |
| 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 | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".