Evidence map›Paper›PMID 22286876›Full record

ReviewIntervirology2012

The HIVdb system for HIV-1 genotypic resistance interpretation.

Michele W Tang, Tommy F Liu, Robert W Shafer

Abstract readReview
In one paragraph

Review in Intervirology, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 84 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
84citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from 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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

84 citing papers in PubMed, 1 synthesis or guideline pooled it.

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  15. Analysis of HIV Drug Resistance Mutations Along With Treatment Outcomes of Efavirenz-Based Regimens in Patients With V179D/E Mutations in Guangzhou, China.The Canadian journal of infectious diseases & medical microbiology = Journal canadien des maladies infectieuses et de la microbiologie medicale · 2026
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24 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Michele W TangDivision of Infectious Diseases and Geographic Medicine, Stanford School of Medicine, 300 Pasteur Drive, Grant Building, Room S-101D Stanford, CA 94305-5107, USA. mimitang@ stanford.edu
Tommy F Liu
Robert W Shafer

Funding

PUBLIC HIV DRUG RESISTANCE DATABASER01AI068581 · NIAID · STANFORD UNIVERSITY · PI SHAFER, ROBERT WILLIAM · 2006 to 2017
$6.2M
NIAID NIH HHS R01 AI068581
6 · The paper itself

Abstract

The Stanford HIV Drug Resistance Database hosts a freely available online genotypic resistance interpretation system called HIVdb to help clinicians and laboratories interpret HIV-1 genotypic resistance tests. These tests are designed to assess susceptibility to nucleoside and nonnucleoside reverse transcriptase inhibitors (NRTI and NNRTI), protease inhibitors and integrase inhibitors. The HIVdb genotypic resistance interpretation system output consists of (1) a list of penalty scores for each antiretroviral (ARV) resistance mutation in a submitted sequence, (2) estimates of decreased NRTI, NNRTI, protease and integrase inhibitor susceptibility, and (3) comments about each ARV resistance mutation in the submitted sequence. The application's strengths are its convenience for submitting sequences, its quality control analysis, its transparency and its extensive comments. The Sierra Web service is an extension that enables laboratories analyzing many sequences to individualize the format of their results. The algorithm specification interface compiler makes it possible for HIVdb to provide results using a variety of different HIV-1 genotypic resistance interpretation algorithms.

Indexed as

Anti-HIV AgentsComputational BiologyDatabases, FactualDatabases, GeneticHIV-1HIV InfectionsHumansInternetMicrobial Sensitivity TestsMolecular TypingAnti-HIV Agents

Identifiers

PMID22286876
PMCPMC7068798

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.