In one paragraphArticle in Nature and science of sleep, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from itWhat 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 registryThe 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 literatureWho cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
4 · The recordCorrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
5 · Who and what moneyAuthors and funding
12 authors.
Chunlin Chen *Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, 100191, People's Republic of China.ORCID 0000-0003-1024-997X Miaoyu Zhang *Henan Mental Hospital, The Second Affiliated Hospital of Xinxiang Medical University; Henan Key Laboratory of Biological Psychiatry, Henan Collaborative Innovation Center of Prevention and Treatment of Mental Disorder, Xinxiang Medical University, Xinxiang, 453003, People's Republic of China.ORCID 0009-0003-7441-3940 Zhilin WangPeking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, 100191, People's Republic of China.ORCID 0009-0008-0743-5142 Shanshan QuPeking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, 100191, People's Republic of China.ORCID 0000-0001-5081-7359 Xinying LiuPeking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, 100191, People's Republic of China.ORCID 0009-0008-1378-0663 Chi ZhangHenan Mental Hospital, The Second Affiliated Hospital of Xinxiang Medical University; Henan Key Laboratory of Biological Psychiatry, Henan Collaborative Innovation Center of Prevention and Treatment of Mental Disorder, Xinxiang Medical University, Xinxiang, 453003, People's Republic of China.ORCID 0009-0008-7096-0118 Jiahui DengPeking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, 100191, People's Republic of China.
Yanping BaoNational Institute on Drug Dependence and Beijing Key Laboratory of Drug Dependence, Peking University, Beijing, 100191, People's Republic of China.
Jie ShiNational Institute on Drug Dependence and Beijing Key Laboratory of Drug Dependence, Peking University, Beijing, 100191, People's Republic of China.
Wenqiang LiHenan Mental Hospital, The Second Affiliated Hospital of Xinxiang Medical University; Henan Key Laboratory of Biological Psychiatry, Henan Collaborative Innovation Center of Prevention and Treatment of Mental Disorder, Xinxiang Medical University, Xinxiang, 453003, People's Republic of China.
Lin LuPeking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, 100191, People's Republic of China.
Le ShiPeking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, 100191, People's Republic of China.ORCID 0000-0003-4827-4003 Funding
Oregon Clinical and Translational Research Institute - The National COVID Cohort Collaborative (N3C)UL1TR002369 · NCATS · OREGON HEALTH & SCIENCE UNIVERSITY · PI Cynthia D Morris, Christopher G. Slatore · 2017 to 2026
$78.4MLong term fracture risk and change in peripheral bone in the oldest old men: The MrOS studyR01AG066671 · NIA · CALIFORNIA PACIFIC MED CTR RES INSTITUTE · PI BOUXSEIN, MARY L, CAWTHON, PEGGY MANNEN · 2020 to 2024
$13.3MOutcomes of Sleep Disorders in Older MenR01HL071194 · NHLBI · UNIVERSITY OF CALIFORNIA SAN FRANCISCO · PI STONE, KATIE L · 2003 to 2013
$12.2MOsteoporotic Fractures in Men (MrOS) - San Francisco Coordinating CenterU01AR066160 · NIAMS · CALIFORNIA PACIFIC MED CTR RES INSTITUTE · PI CUMMINGS, STEVEN RON · 2013 to 2017
$9.3MOsteoporotic Fractures in Men (MrOS) - MinneapolisU01AG042145 · NIA · UNIVERSITY OF MINNESOTA · PI ENSRUD, KRISTINE · 2013 to 2019
$5.3MOsteporotic Fractures in Men (MrOS)- Admin CenterU01AG027810 · NIA · OREGON HEALTH & SCIENCE UNIVERSITY · PI ORWOLL, ERIC S. · 2006 to 2017
$5.1MOsteoporotic Fractures in Men (MrOS) - PortlandU01AG042124 · NIA · OREGON HEALTH & SCIENCE UNIVERSITY · PI ORWOLL, ERIC S. · 2013 to 2019
$3.0MOsteoporatic Fractures in Men (MrOS)U01AG042168 · NIA · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI KADO, DEBORAH · 2013 to 2017
$3.0MOsteoporotic Fractures in Men (Mr. Os) Palo AltoU01AG042143 · NIA · STANFORD UNIVERSITY · PI STEFANICK, MARCIA L. · 2013 to 2017
$3.0MOsteoporotic Fractures in Men (Mr.OS)U01AG042139 · NIA · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI CAULEY, JANE ANN · 2013 to 2017
$2.9MOsteoporotic Fractures in Men_MrOS Renewal_BirminghamU01AG042140 · NIA · UNIVERSITY OF ALABAMA AT BIRMINGHAM · PI SHIKANY, JAMES M · 2013 to 2019
$2.7MOutcomes of Sleep Disorders in Older Men-PortlandR01HL070838 · NHLBI · OREGON HEALTH & SCIENCE UNIVERSITY · PI ORWOLL, ERIC S. · 2003 to 2007
$1.8MNCATS NIH HHS UL1 TR002369NHLBI NIH HHS R01 HL070837NHLBI NIH HHS R01 HL070838NHLBI NIH HHS R01 HL070839NHLBI NIH HHS R01 HL070841NHLBI NIH HHS R01 HL070842NHLBI NIH HHS R01 HL070847NHLBI NIH HHS R01 HL070848NHLBI NIH HHS R01 HL071194NIAMS NIH HHS U01 AR066160NIA NIH HHS R01 AG066671NIA NIH HHS U01 AG027810NIA NIH HHS U01 AG042124NIA NIH HHS U01 AG042139NIA NIH HHS U01 AG042140NIA NIH HHS U01 AG042143NIA NIH HHS U01 AG042145NIA NIH HHS U01 AG042168
6 · The paper itselfAbstract
Purpose: Sleep encompasses multiple dimensions, each potentially involving distinct parameters that collectively capture the complex features of sleep health. However, limited studies focused on the construction of objective sleep multidimensions and its associations with cognitive impairment. Patients and Methods: The study included 2670 community-dwelling older men from the Osteoporotic Fractures in Men study. Wrist actigraphy was used to collect sleep data. Latent sleep dimensions were identified from objectively measured sleep parameters using exploratory factor analysis without prespecified structures. Longitudinal associations between sleep domains and cognitive impairment were evaluated using Cox proportional hazards models over a mean follow-up of 7.4 years. XGBoost with SHapley Additive exPlanations (SHAP) was used to rank the predictive importance of each domain. Results: Five dimensions of sleep health framework were identified: rhythmicity, quality, duration, regularity, and timing. Disrupted rhythmicity was significantly associated with an increased risk of cognitive impairment (HR = 1.21, 95% CI: 1.07-1.37, p = 0.002). Longer duration (HR = 1.13, 95% CI: 1.00-1.28, p = 0.043), poorer regularity (HR = 1.13, 95% CI: 1.00-1.27, p = 0.046) and lower quality (HR = 1.13, 95% CI: 1.01-1.27, p = 0.040) were also linked to elevated risk in fully adjusted model. No significant association was observed between timing and cognitive impairment. SHAP analysis indicated that rhythmicity ranked high in predictive importance compared with traditional risk factors and was the most influential domain among the sleep dimensions. After stratification, disrupted rhythmicity remained significantly associated with cognitive impairment in most demographic and lifestyle subgroups. Conclusion: Our integrative modelling approach provides novel insights into the complex relationships between distinct sleep domains and cognitive impairment, highlighting rhythmicity as a key factor for preserving cognitive health in aging men. These findings suggest that sleep-related interventions, especially for management of rhythmicity, may be a promising approach for the prevention of cognitive impairment.
Indexed as
actigraphyagingcognitive impairmentrhythmicitysleep
Identifiers
PMID42445696
PMCPMC13360829
What Socratic holds
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