ArticleFrontiers in microbiology2024
Risk factors and clinical prediction models for low-level viremia in people living with HIV receiving antiretroviral therapy: an 11-year retrospective study.
Article in Frontiers in microbiology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers, 1 of them a synthesis that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
8 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Prevalence of low-level viremia and related influencing factors among people living with HIV in China: a systematic review and meta-analysis.Frontiers in public health · 2025Pooled it
- Impact of HIV-1 low-level viremia on virologic and immunologic failure during antiretroviral therapy: a retrospective cohort study from 2005 to 2023 in Qinzhou City, Guangxi, China.AIDS research and therapy · 2026Article
- Article
- Artificial intelligence in HIV research: a structured review and task-oriented clinical framework.Frontiers in digital health · 2026Review
- Development and internal validation of a risk model for hyperuricemia among people living with HIV in Hangzhou, China: a retrospective longitudinal cohort study.Frontiers in endocrinology · 2026Article
- Characterization of Antiretroviral Therapy (ART) Adherence Phenotypes and Psychosocial Symptom Clusters Among Black/African American (AA) and Hispanic/Latine Adolescents and Young Adults (AYAs) with HIV in the Adherence Connection for Counseling, Education, and Support (ACCESS-II) Trial.Tropical medicine and infectious disease · 2025Article
- Risk Factors Associated with Virological Failure in HIV Patients with Low Level Viremia: A Retrospective Study.Infection and drug resistance · 2025Article
- Low-Level Viremia as an Independent Risk Factor for Metabolic Syndrome in People Living with HIV Receiving Antiretroviral Therapy: A 6-Year Retrospective Cohort Study.Infection and drug resistance · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
9 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Objective: This study explores the risk factors for low-level viremia (LLV) occurrence after ART and develops a risk prediction model. Method: Clinical data and laboratory indicators of people living with HIV (PLWH) at Hangzhou Xixi Hospital from 5 April 2011 to 29 December 2022 were collected. LASSO Cox regression and multivariate Cox regression analysis were performed to identify laboratory indicators and establish a nomogram for predicting LLV occurrence. The nomogram's discrimination and calibration were assessed via ROC curve and calibration plots. The concordance index (C-index) and decision curve analysis (DCA) were used to evaluate its effectiveness. Result: Predictive factors, namely, age, ART delay time, white blood cell (WBC) count, baseline CD4 Conclusion: A simple-to-use nomogram containing 6 routinely detected variables was developed for predicting LLV occurrence in PLWH after ART.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.