Evidence map›Paper›PMID 36739589›Full record

ArticleAIDS and behavior2023

Strategies of Managing Repeated Measures: Using Synthetic Random Forest to Predict HIV Viral Suppression Status Among Hospitalized Persons with HIV.

Jingxin Liu, Yue Pan, Mindy C Nelson, Lauren K Gooden, Lisa R Metsch, Allan E Rodriguez, Susan Tross, Carlos Del Rio, Raul N Mandler, Daniel J Feaster

Open access · greenAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in AIDS and behavior, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact, top 98% of its field
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

1 citing paper in PubMed, 0 citations in OpenAlex.

  1. The Utility of Machine Learning-Enhanced Developmental Cascade Models in Prevention Science.Prevention science : the official journal of the Society for Prevention Research · 2026
    Article
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

10 authors at 5 institutions in 1 country.

Jingxin LiuDepartment of Public Health, Miller School of Medicine, University of Miami, Coral Gables, USA. JXL1830@miami.edu.ORCID http://orcid.org/0000-0003-0191-9329
Yue PanDepartment of Public Health, Miller School of Medicine, University of Miami, Coral Gables, USA.
Mindy C NelsonDepartment of Public Health, Miller School of Medicine, University of Miami, Coral Gables, USA.
Lauren K GoodenDepartment of Sociomedical Sciences, Mailman School of Public Health, Columbia University, New York, USA.
Lisa R MetschDepartment of Sociomedical Sciences, Mailman School of Public Health, Columbia University, New York, USA.
Allan E RodriguezMiller School of Medicine, University of Miami, Coral Gables, USA.
Susan TrossHIV Center for Clinical and Behavioral Studies, New York State Psychiatric Institute and Columbia University Irving Medical Center, New York, NY, USA.
Carlos Del RioDivision of Infectious Diseases, Department of Medicine, Emory University School of Medicine and Hubert Department of Global Health, Rollins School of Public Health, Emory University, Atlanta, GA, USA.
Raul N MandlerCenter for the Clinical Trials Network, National Institute on Drug Abuse, National Institutes of Health, Bethesda, MD, USA.
Daniel J FeasterDepartment of Public Health, Miller School of Medicine, University of Miami, Coral Gables, USA.
University of Miami · USColumbia University · USEmory University · USNational Institutes of Health · USNew York Psychoanalytic Society and Institute · US

Funding

Project-003UG1DA013035 · NIDA · NEW YORK UNIVERSITY SCHOOL OF MEDICINE · PI Aimee N Campbell, Jennifer McNeely · 2015 to 2026
$130.3M
The National Drug Abuse Treatment Clinical Trials NetworkUG1DA015831 · NIDA · YALE UNIVERSITY · PI Gail D'Onofrio, Roger D. Weiss · 2015 to 2026
$110.8M
Project-004UG1DA020024 · NIDA · UT SOUTHWESTERN MEDICAL CENTER · PI Steven J Shoptaw, MADHUKAR H. TRIVEDI · 2015 to 2026
$71.6M
FLORIDA NODE OF THE DRUG ABUSE CLINICAL TRIALS NETWORKU10DA013720 · NIDA · UNIVERSITY OF MIAMI SCHOOL OF MEDICINE · PI METSCH, LISA R, SZAPOCZNIK, JOSE · 2000 to 2015
$56.9M
The Florida Node Alliance of the National Drug Abuse Treatment Clinical Trials NetworkUG1DA013720 · NIDA · UNIVERSITY OF MIAMI SCHOOL OF MEDICINE · PI Daniel J Feaster, Viviana Elizabeth Horigian · 2015 to 2026
$50.6M
The Ohio Valley Node of the Clinical Trials Network (CTN-0153)UG1DA013732 · NIDA · UNIVERSITY OF CINCINNATI · PI T John WINHUSEN · 2015 to 2026
$42.5M
University of Miami Developmental Center for AIDS Research (D-CFAR)P30AI073961 · NIAID · UNIVERSITY OF MIAMI SCHOOL OF MEDICINE · PI ALLAN E RODRIGUEZ · 2007 to 2026
$33.8M
Western States Node of the National Drug Abuse Treatment Clinical Trials NetworkU10DA015815 · NIDA · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI MCCARTY, DENNIS, SORENSEN, JAMES L · 2002 to 2015
$25.2M
Southern Consortium Node of the Clinical Trials Network (Varenicline)UG1DA013727 · NIDA · MEDICAL UNIVERSITY OF SOUTH CAROLINA · PI KATHLEEN T. BRADY, Kelly S. Barth · 2015 to 2026
$24.8M
Western States Node of the National Drug Abuse Treatment Clinical Trials Network (TMS for CUD) UG1DA015815 · NIDA · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI Keith N. Humphreys, Philip Todd Korthuis · 2015 to 2026
$24.6M
Concept ProjectU10DA020024 · NIDA · UT SOUTHWESTERN MEDICAL CENTER · PI TRIVEDI, MADHUKAR H. · 2005 to 2015
$22.6M
Institute for Integration of Medicine & Science: A Partnership to Improve HealthUM1TR004538 · NCATS · UNIVERSITY OF TEXAS HLTH SCIENCE CENTER · PI ROBERT A CLARK, Kenneth M Hargreaves · 2023 to 2026
$22.3M
NCATS NIH HHS UM1 TR004538NIAID NIH HHS P30 AI073961NIDA NIH HHS T32 DA037801NIDA NIH HHS U10 DA013720NIDA NIH HHS U10 DA015815NIDA NIH HHS U10 DA020024NIDA NIH HHS U10 DA020036NIDA NIH HHS UG1 DA013034NIDA NIH HHS UG1 DA013035NIDA NIH HHS UG1 DA013720NIDA NIH HHS UG1 DA013727NIDA NIH HHS UG1 DA013732NIDA NIH HHS UG1 DA015815NIDA NIH HHS UG1 DA015831NIDA NIH HHS UG1 DA020024NIMH NIH HHS P30 MH116867NIMH NIH HHS P30 MH133399
6 · The paper itself

Abstract

The HIV/AIDS epidemic remains a major public health concern since the 1980s; untreated HIV infection has numerous consequences on quality of life. To optimize patients' health outcomes and to reduce HIV transmission, this study focused on vulnerable populations of people living with HIV (PLWH) and compared different predictive strategies for viral suppression using longitudinal or repeated measures. The four methods of predicting viral suppression are (1) including the repeated measures of each feature as predictors, (2) utilizing only the initial (baseline) value of the feature as predictor, (3) using the last observed value as the predictors and (4) using a growth curve estimated from the features to create individual-specific prediction of growth curves as features. This study suggested the individual-specific prediction of the growth curve performed the best in terms of lowest error rate on an independent set of test data.

Indexed as

Acquired Immunodeficiency SyndromeHIV InfectionsHumansQuality of LifeRandom ForestResearch DesignHIV/AIDSLongitudinal measurementMachine learningPredictive model

Identifiers

PMID36739589
PMCPMC10403627
OpenAlexW4319262343

What OpenQuestion holds

Textmetadata
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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.