ArticleClinical infectious diseases : an official publication of the Infectious Diseases Society of America2024
Misclassification of Loss to Care Among Persons With Human Immunodeficiency Virus: Improved Capture of Silent Transfers Through Surveillance Linkage Using Statewide Mandatorily Reported Laboratory Measures.
Article in Clinical infectious diseases : an official publication of the Infectious Diseases Society of America, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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
2 citing papers in PubMed.
- New to cohort, not new to care: leveraging historical data in HIV clinical cohorts in the United States.American journal of epidemiology · 2026Article
- Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors.
Funding
Abstract
Human Immunodeficiency Virus (HIV)-positive individuals lost to follow-up from particular clinics may not be lost to care (LTC). After linking Vanderbilt's Comprehensive Care Clinic cohort to Tennessee's statewide HIV surveillance database, LTC decreased from 48.4% to 35.0% at 10 years. Routine surveillance linkage by domestic HIV clinics would improve LTC and retention measure accuracy.
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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.