Evidence map›Paper›PMID 40243191›Full record

ArticleJournal of acquired immune deficiency syndromes (1999)2025

Approaches to optimally target frailty screening among people with HIV in clinical care: findings from the Centers for AIDS Research Network of Integrated Clinical Systems (CNICS).

Heidi M Crane, Stephanie A Ruderman, Robin M Nance, Lydia N Drumright, Bridget M Whitney, L Sarah Mixson, Kenneth H Mayer, Joseph J Eron, Sonia Napravnik, Katerina Christopoulos and 15 more

Abstract read
In one paragraph

Article in Journal of acquired immune deficiency syndromes (1999), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–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

3 citing papers in PubMed.

  1. Article
  2. Article
  3. 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

25 authors.

Heidi M CraneDepartment of Medicine, University of Washington School of Medicine, Seattle, WA.
Stephanie A RudermanDepartment of Medicine, University of Washington School of Medicine, Seattle, WA.
Robin M NanceDepartment of Medicine, University of Washington School of Medicine, Seattle, WA.
Lydia N DrumrightDepartment of Biobehavioral Nursing and Health Informatics, University of Washington School of Nursing, Seattle, WA.
Bridget M WhitneyDepartment of Medicine, University of Washington School of Medicine, Seattle, WA.
L Sarah MixsonDepartment of Medicine, University of Washington School of Medicine, Seattle, WA.
Kenneth H MayerFenway Health/The Fenway Institute, Boston, MA.
Joseph J EronDepartment of Medicine, University of North Carolina, Chapel Hill, NC.
Sonia NapravnikDepartment of Medicine, University of North Carolina, Chapel Hill, NC.
Katerina ChristopoulosDepartment of Medicine, University of California San Francisco, San Francisco, CA.
Edward R CachayDepartment of Medicine, University of California San Diego Health System, San Diego, CA.
Laura BamfordDepartment of Medicine, University of California San Diego Health System, San Diego, CA.
Geetanjali ChanderDepartment of Medicine, University of Washington School of Medicine, Seattle, WA.
Allison WebelDepartment of Child, Family, and Population Health Nursing, University of Washington School of Nursing, Seattle, WA.
Michael S SaagDepartment of Medicine, University of Alabama Birmingham School of Medicine, Birmingham, AL.
Amanda L WilligDepartment of Medicine, University of Alabama Birmingham School of Medicine, Birmingham, AL.
Greer BurkholderDepartment of Medicine, University of Alabama Birmingham School of Medicine, Birmingham, AL.
Chintan PandyaCenter for Population Health Information Technology, Johns Hopkins University, Baltimore, MD.
Francisco Cartujano-BarreraDepartment of Public Health Sciences, University of Rochester Medical Center, Rochester, NY.
Charles KamenDepartment of Surgery, University of Rochester Medical Center, Rochester, NY.
Andrew W HahnDepartment of Medicine, University of Washington School of Medicine, Seattle, WA.
Jimmy MaDepartment of Medicine, University of Washington School of Medicine, Seattle, WA.
Mari M KitahataDepartment of Medicine, University of Washington School of Medicine, Seattle, WA.
William B LoberDepartment of Medicine, University of Washington School of Medicine, Seattle, WA.
Joseph Ac DelaneyDepartment of Medicine, University of Washington School of Medicine, Seattle, WA.

Funding

University of Washington/Fred Hutch Center for AIDS ResearchP30AI027757 · NIAID · UNIVERSITY OF WASHINGTON · PI CONNIE L CELUM · 1988 to 2026
$104.9M
Unsolicited R24 for the CFAR-Network of Integrated Clinical Sciences, CNICSR24AI067039 · NIAID · UNIVERSITY OF ALABAMA AT BIRMINGHAM · PI Michael S. Saag · 2006 to 2026
$99.4M
Substance use patterns and contexts: impact on epigenetic age and prevention strategies in an HIV clinical care cohortR01DA047045 · NIDA · UNIVERSITY OF WASHINGTON · PI Heidi M. Crane, Joseph Austin Delaney · 2018 to 2026
$5.1M
Links between Cardiovascular disease, Lung disease, and Obstructive sleep apnea in HIV: Understanding complex patientsR01HL126538 · NHLBI · UNIVERSITY OF WASHINGTON · PI CRANE, HEIDI M., CROTHERS, KRISTINA ANNE · 2015 to 2025
$5.1M
HIV and Aging Research Consortium (HARC)R33AG067069 · NIA · UNIVERSITY OF WASHINGTON · PI STEVEN N. AUSTAD, Heidi M. Crane · 2020 to 2026
$4.8M
Understanding Health Inequities at the Intersection of the HIV and substance use epidemics across racial/ethnic and other underserved populationsR01DA058938 · NIDA · UNIVERSITY OF WASHINGTON · PI Heidi M. Crane, Rob Fredericksen · 2023 to 2026
$2.8M
NHLBI NIH HHS R01 HL126538NIAID NIH HHS P30 AI027757NIAID NIH HHS R24 AI067039NIA NIH HHS R33 AG067069NIDA NIH HHS R01 DA047045NIDA NIH HHS R01 DA058938
6 · The paper itself

Abstract

backgroundFrailty screening in HIV care has been recommended, however, screening adds burden to busy clinics. We compared criteria that predict concurrent frailty to identify approaches to optimally target frailty screening.

methodsThe development cohort included people with HIV (PWH) at six U.S. sites. Frailty was assessed based on four components of a modified Fried phenotype: fatigue, unintentional weight loss, low mobility, and poor physical activity. We evaluated demographic and clinical characteristics, comorbidities, and substance use as predictors of who should be screened using selection approaches for simple and complex frailty screening tools, including machine learning approaches. We compared discrimination and calibration including area under the receiver operator characteristic (ROC) curve (AUC), sensitivity, and specificity in a validation cohort (7th site).

resultsAmong the 9,592 PWH in the development cohort, 11% were frail. AUC ranged from 0.52 for simple screening approaches such as age-based to 0.84 for complex approaches in the development and validation cohorts. Using an age cutoff >50 years reduced the percentage of PWH needing screening by over half but also reduced the sensitivity to 58% in the validation cohort. Complex approaches required 47% to be screened and had a sensitivity of 89%.

conclusionsAge-based frailty screening approaches (e.g., >50 years) miss many frail PWH. Complex tools had marginally better testing characteristics but would be more difficult to implement in clinical care. Simple targeted screening based on three characteristics (age, gender, and depressive symptoms) identified 89% of frail PWH and reduced the number who needed screened by 52%.

Indexed as

Clinical careFrailtyFrailty screeningHIV

Identifiers

PMID40243191
PMCPMC12951880

What Socratic holds

Textmetadata
LicenceTDM
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 Socratic graph.