ReviewFuture virology2018
Molecular evolution methods to study HIV-1 epidemics.
Review in Future virology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
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Authors and funding
2 authors.
Funding
Abstract
Nucleotide sequences of HIV isolates are obtained routinely to evaluate the presence of resistance mutations to antiretroviral drugs. But, beyond their clinical use, these and other viral sequences include a wealth of information that can be used to better understand and characterize the epidemiology of HIV in relevant populations. In this review, we provide a brief overview of the main methods used to analyze HIV sequences, the data bases where reference sequences can be obtained, and some caveats about the possible applications for public health of these analyses, along with some considerations about their limitations and correct usage to derive robust and reliable conclusions.
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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.