Article in Sleep, 2025. 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
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.
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
9 authors.
Naresh M PunjabiDepartment of Medicine, Miller School of Medicine, University of Miami, Miami, FL, USA.
Todd T BrownDepartment of Medicine, School of Medicine, Johns Hopkins University, Baltimore, MD, USA.
Darko StefanovskiClinical Studies-New Bolton Center, University of Pennsylvania, Philadelphia, PA, USA.
Rashmi Nisha AuroraDepartment of Medicine, Grossman School of Medicine, NYU, New York City, NY, USA.
Sanjay R PatelDepartment of Medicine, School of Medicine, University of Pittsburgh, Pittsburgh, PA, USA.ORCID 0000-0002-9142-5172
Valentina StosorDepartment of Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL, USA.ORCID 0000-0002-0388-5460
Joshua Hyong-Jin ChoDepartment of Psychiatry, University of California (Los Angeles, David Geffen School of Medicine), Los Angeles, CA, USA.ORCID 0000-0002-8629-8500
Gypsyamber D'SouzaMolecular Microbiology and Immunology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA.
Joseph B MargolickMolecular Microbiology and Immunology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA.ORCID 0000-0002-4210-9093
Funding
UCLA Clinical Translational Science InstituteUL1TR001881 · NCATS · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI ARLEEN F. BROWN, ARASH NAEIM · 2016 to 2026
$118.1M
QAQC Johns Hopkins Institute for Clinical and Translational ResearchUL1TR003098 · NCATS · JOHNS HOPKINS UNIVERSITY · PI FORD, DANIEL ERNEST · 2019 to 2023
$57.7M
SF Bay Area MACS/WIHS Combined Cohort StudyU01HL146242 · NHLBI · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI Bradley E Aouizerat, Jennifer Cohen Price · 2019 to 2026
$36.3M
Sex differences in the role of multi-omicsin HIV-associated carotid artery atherosclerosisU01HL146193 · NHLBI · JOHNS HOPKINS UNIVERSITY · PI Stephen J Gange, Elizabeth Topper · 2019 to 2026
$35.8M
Clinical Research Sites for the MACS/WIHS Combined Cohort Study (MACS/WIHS-CCS) - Baltimore/Wash DC Center - Admin Supplement: Vision and dual sensory loss in HIV-infected older adultsU01HL146201 · NHLBI · JOHNS HOPKINS UNIVERSITY · PI TODD T BROWN, Joseph B. Margolick · 2019 to 2026
$33.7M
Study of Hearing and Balance in Middle Aged and Aging Men and Women in the MACS-WIHS Combined Cohort StudyU01HL146333 · NHLBI · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI Roger Detels, Matthew James Mimiaga · 2019 to 2026
$32.2M
Implications of Obstructive Sleep Apnea for Fat MetabolismR01HL146709 · NHLBI · UNIVERSITY OF MIAMI SCHOOL OF MEDICINE · PI PUNJABI, NARESH M · 2019 to 2022
$3.0M
Obstructive Sleep Apnea and Glycemic Variability in Type 2 DiabetesK23HL118414 · NHLBI · RBHS-ROBERT WOOD JOHNSON MEDICAL SCHOOL · PI AURORA, RASHMI NISHA · 2014 to 2018
$883k
Baltimore CRS (Todd Brown and Joseph Margolick) U01-HL146201Chicago-Northwestern CRS U01-HL146242Data Analysis and Coordination Center U01-HL146193Eunice Kennedy Shriver National Institute of Child Health & Human DevelopmentJHU ICTR UL1-TR003098Los Angeles CRS U01-HL146333National Institute of Allergy and Infectious DiseasesNational Institute of Dental & Craniofacial ResearchNCATS NIH HHS UL1 TR001881NCATS NIH HHS UL1 TR003098NCI NIH HHSNHLBI NIH HHS HL11716NHLBI NIH HHS HL118414NHLBI NIH HHS HL146709NHLBI NIH HHS K23 HL118414NHLBI NIH HHS R01 HL146709NHLBI NIH HHS U01 HL146193NHLBI NIH HHS U01 HL146201NHLBI NIH HHS U01 HL146242NHLBI NIH HHS U01 HL146333NIAAA NIH HHSNIA NIH HHSNIDA NIH HHSNIDCD NIH HHSNIDDK NIH HHSNIH HHSNIMHD NIH HHSNIMH NIH HHSNINDS NIH HHSNINR NIH HHSOffice of AIDS ResearchPittsburgh CRSUCLA CTSI UL1-TR001881
6 · The paper itself
Abstract
STUDY
objectivesThe landscape of HIV infection has shifted dramatically over the last few decades. An extended lifespan has led to an increase in comorbidities, including disorders of sleep. While self-reported sleep disturbances in people living with HIV are common, differences in sleep architecture between those living with and without HIV have not been previously described.
methodsPolysomnography data from the Multicenter AIDS Cohort Study were used to characterize differences in sleep architecture between men living with and without HIV. Parameters assessed included total sleep time, sleep stage distribution, arousal index, and frequency of sleep stage transitions. Multivariable regression was employed to adjust for demographic variables and explore effect modification by sleep-disordered breathing (SDB) severity.
resultsCompared to men without HIV (N = 349), men with HIV (N = 447) exhibited comparable total sleep time, but lower sleep efficiency and greater wake time after sleep onset. Independent of HIV status, SDB was associated with a greater percentage of N1 sleep and lower percentages of N2 and REM sleep. However, those with both HIV and severe SDB displayed the lowest sleep efficiency, the highest percentage of N1 sleep, and the lowest frequency of sleep stage transitions from nonrapid eye movement (non-REM)-to-REM sleep compared to all other HIV and SDB subgroups.
conclusionsThis study found an independent association between HIV, SDB, and altered sleep architecture, characterized by lower sleep efficiency, greater time in stage N1 sleep, and higher sleep stage instability. Further research is needed on the potential health implications of disrupted sleep in those with HIV and SDB.
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.
Differences in sleep architecture between men living with and without HIV. · full record | OpenQuestion