ArticleBMC infectious diseases2023
Using signal-to-cutoff ratios of HIV screening assay to predict HIV infection.
Article in BMC infectious diseases, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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
4 citing papers in PubMed, 6 citations in OpenAlex.
- Article
- Design and evaluation of a novel direct hemagglutination test based on a recombinant protein for diagnosis of cystic echinococcosis.Parasites & vectors · 2025Article
- Challenges in HIV Diagnosis Algorithm: Experience of the Confirmation Laboratory.Journal of tropical medicine · 2025Article
- Analysis of HIV infection among voluntary blood donors based on HIV ELISA and nucleic acid detection.American journal of translational research · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors at 3 institutions in 1 country.
Funding
Abstract
backgroundThe sensitivity of HIV screening assays often leads to a high rate of false-positive results, requiring retests and confirmatory tests. This study aimed to analyze the capability of signal-to-cutoff (S/CO) ratios of HIV screening assay to predict HIV infection.
methodsA retrospective study on the HIV screening-positive population was performed at Zhongshan Hospital, Xiamen University, the correlation between HIV screening assay S/CO ratios and HIV infection was assessed, and plotted Receiver Operating Characteristic (ROC) curves were generated to establish the optimal cutoff value for predicting HIV infection.
resultsOut of 396,679 patients, 836 were confirmed to be HIV-infected, with an HIV prevalence of 0.21%. The median S/CO ratios in HIV infection were significantly higher than that in non-HIV infection (296.9 vs. 2.41, P < 0.001). The rate of confirmed HIV infection was increased with higher S/CO ratios in the screening assay. The ROC curve based on the HIV screening assay S/CO ratio achieved a sensitivity of 93.78% and a specificity of 93.12% with an optimal cutoff value of 14.09. The area under the ROC curve was 0.9612. Further analysis of the ROC curve indicated that the S/CO ratio thresholds yielding positive predictive values of 99%, 99.5%, and 100% for HIV infection were 26.25, 285.7, and 354.5, respectively.
conclusionUsing HIV screening assay S/CO ratio to predict HIV infection can largely reduce necessitating retests and confirmatory tests. Incorporating the S/CO ratio into HIV testing algorithms can have significant implications for medical and public health practices.
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.