ArticleSystematic reviews2016
Predictors of human immunodeficiency virus (HIV) infection in primary care: a systematic review protocol.
Article in Systematic reviews, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 1 of them a synthesis that pooled it.
What it found
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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, 1 synthesis or guideline pooled it, 14 citations in OpenAlex.
- Predictors of human immunodeficiency virus (HIV) infection in primary care among adults living in developed countries: a systematic review.Systematic reviews · 2018Pooled it
- The Potential Use of the CRISPR-Cas System for HIV-1 Gene Therapy.International journal of genomics · 2019Review
- Computational Prediction of Subjective Human Immunodeficiency Virus Status in Malawi Using a Random Forest Approach.AIDS research and treatment · 2019Article
- Community perceptions of the socio-economic structural context influencing HIV and TB risk, prevention and treatment in a high prevalence area in the era of antiretroviral therapy.African journal of AIDS research : AJAR · 2018Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundAntiretroviral therapies for human immunodeficiency virus are more effective if infected individuals are diagnosed early, before they have irreversible immunologic damage. A large proportion of patients that are diagnosed with HIV, in United Kingdom, would have seen a general practitioner (GP) within the previous year. Determining the demographic and clinical characteristics of HIV-infected patients prior to diagnosis of HIV may be useful in identifying patients likely to be HIV positive in primary care. This could help inform a strategy of early HIV testing in primary care. This systematic review aims to identify characteristics of HIV-infected adults prior to diagnosis that could be used in a prediction model for early detection of HIV in primary care.
methodsThe systematic review will search for literature, mainly observational (cohort and case-control) studies, with human participants aged 18 years and over. The exposures are demographic, socio-economic or clinical risk factors or characteristics associated with HIV infection. The comparison group will be patients with no risk factors or no comparison group. The outcome is laboratory-confirmed HIV/AIDS infection. Evidence will be identified from electronic searches of online databases of EMBASE, MEDLINE, The Cochrane Library and grey literature search engines of Open Grey, Web of Science Conference Proceedings Citation Index and examination of reference lists from selected studies (reference searching). Two reviewers will be involved in quality assessment and data extraction of the review. A data extraction form will be developed to collate data from selected studies. A checklist for quality assessment will be adapted from the Scottish Intercollegiate Guidelines Network (SIGN). DISCUSSION: This systematic review will identify and consolidate existing scientific evidence on characteristics of HIV infected individuals that could be used to inform decision-making in prognostic model development. SYSTEMATIC REVIEW REGISTRATION: PROSPERO CRD42016042427.
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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.