Keyword search (4,163 papers available)

"Screening" Keyword-tagged Publications:

Title Authors PubMed ID
1 PARPAL: PARalog Protein Redistribution using Abundance and Localization in Yeast Database Greco BM; Zapata G; Dandage R; Papkov M; Pereira V; Lefebvre F; Bourque G; Parts L; Kuzmin E; 40580499
BIOLOGY
2 Imaging flow cytometry-based cellular screening elucidates pathophysiology in individuals with Variants of Uncertain Significance Muffels IJJ; Waterham HR; D' Alessandro G; Zagnoli-Vieira G; Sacher M; Lefeber DJ; Van der Vinne C; Roifman CM; Gassen KLI; Rehmann H; Van Haaften-Visser DY; Nieuwenhuis ESS; Jackson SP; Fuchs SA; Wijk F; van Hasselt P; 39920830
BIOLOGY
3 Automated abdominal aortic calcification and major adverse cardiovascular events in people undergoing osteoporosis screening: the Manitoba Bone Mineral Density Registry Smith C; Sim M; Ilyas Z; Gilani SZ; Suter D; Reid S; Monchka BA; Jozani MJ; Figtree G; Schousboe JT; Lewis JR; Leslie WD; 39749990
ENCS
4 Validation and Reliability of the Dyslexia Adult Checklist in Screening for Dyslexia Stark Z; Elalouf K; Soldano V; Franzen L; Johnson AP; 39660384
PSYCHOLOGY
5 Exploring the Qualitative Experiences of Administering and Participating in Remote Research via Telephone Using the Montreal Cognitive Assessment-Blind: Cross-Sectional Study of Older Adults Dumassais S; Grewal KS; Aubin G; O' Connell M; Phillips NA; Wittich W; 39546346
PSYCHOLOGY
6 Are MEDLINE searches sufficient for systematic reviews and meta-analyses of the diagnostic accuracy of depression screening tools? A review of meta-analyses Rice DB; Kloda LA; Levis B; Qi B; Kingsland E; Thombs BD; 27411746
LIBRARY
7 Reporting quality in abstracts of meta-analyses of depression screening tool accuracy: a review of systematic reviews and meta-analyses Rice DB; Kloda LA; Shrier I; Thombs BD; 27864250
LIBRARY
8 Depression Screening and Health Outcomes in Children and Adolescents: A Systematic Review Roseman M; Saadat N; Riehm KE; Kloda LA; Boruff J; Ickowicz A; Baltzer F; Katz LY; Patten SB; Rousseau C; Thombs BD; 28851234
LIBRARY
9 Simultaneous automated ascertainment of prevalent vertebral fracture and abdominal aortic calcification in clinical practice: role in fracture risk assessment Schousboe JT; Lewis JR; Monchka BA; Reid SB; Davidson MJ; Kimelman D; Jozani MJ; Smith C; Sim M; Gilani SZ; Suter D; Leslie WD; 38699950
ENCS
10 Screening for parent and child ADHD in urban pediatric primary care: pilot implementation and stakeholder perspectives Lui JHL; Danko CM; Triece T; Bennett IM; Marschall D; Lorenzo NE; Stein MA; Chronis-Tuscano A; 37442955
PSYCHOLOGY
11 A "biphasic glycosyltransferase high-throughput screen" identifies novel anthraquinone glycosides in the diversification of phenolic natural products Mohideen FI; Kwan DH; 36682498
CHEMBIOCHEM
12 Microfluidics for long-term single-cell time-lapse microscopy: Advances and applications Allard P; Papazotos F; Potvin-Trottier L; 36312536
BIOLOGY
13 Transparency and completeness of reporting of depression screening tool accuracy studies: A meta-research review of adherence to the Standards for Reporting of Diagnostic Accuracy Studies statement Nassar EL; Levis B; Neyer MA; Rice DB; Booij L; Benedetti A; Thombs BD; 36047034
PSYCHOLOGY
14 Perfluoroalkyl and polyfluoroalkyl substances (PFASs) in groundwater: current understandings and challenges to overcome Zhao Z; Li J; Zhang X; Wang L; Wang J; Lin T; 35593984
CHEMBIOCHEM
15 Sample size and precision of estimates in studies of depression screening tool accuracy: A meta-research review of studies published in 2018-2021 Nassar EL; Levis B; Neyer MA; Rice DB; Booij L; Benedetti A; Thombs BD; 35362161
PSYCHOLOGY
16 Inclusion of currently diagnosed or treated individuals in studies of depression screening tool accuracy: a meta-research review of studies published in 2018-2021 Nassar EL; Levis B; Rice DB; Booij L; Benedetti A; Thombs BD; 35334411
PSYCHOLOGY
17 Osseointegration Pharmacology: A Systematic Mapping Using Artificial Intelligence Mahri M; Shen N; Berrizbeitia F; Rodan R; Daer A; Faigan M; Taqi D; Wu KY; Ahmadi M; Ducret M; Emami E; Tamimi F; 33181361
CONCORDIA
18 Equivalency of the diagnostic accuracy of the PHQ-8 and PHQ-9: a systematic review and individual participant data meta-analysis Wu Y; Levis B; Riehm KE; Saadat N; Levis AW; Azar M; Rice DB; Boruff J; Cuijpers P; Gilbody S; Ioannidis JPA; Kloda LA; McMillan D; Patten SB; Shrier I; Ziegelstein RC; Akena DH; Arroll B; Ayalon L; Baradaran HR; Baron M; Bombardier CH; Butterworth P; Carter G; Chagas MH; Chan JCN; Cholera R; Conwell Y; de Man-van Ginkel JM; Fann JR; Fischer FH; Fung D; Gelaye B; Goodyear-Smith F; Greeno CG; Hall BJ; Harrison PA; Härter M; Hegerl U; Hides L; Hobfoll SE; Hudson M; Hyphantis T; Inagaki M; Jetté N; Khamseh ME; Kiely KM; Kwan Y; Lamers F; Liu SI; Lotrakul M; Loureiro SR; Löwe B; McGuire A; Mohd-Sidik S; Munhoz TN; Muramatsu K; Osório FL; Patel V; Pence BW; Persoons P; Picardi A; Reuter K; Rooney AG; Santos IS; Shaaban J; Sidebottom A; Simning A; Stafford L; Sung S; Tan PLL; Turner A; van Weert HC; White J; Whooley MA; Winkley K; Yamada M; Benedetti A; Thombs BD; 31298180
LIBRARY
19 Virtual screening, docking, and dynamics of potential new inhibitors of dihydrofolate reductase from Yersinia pestis. Bastos Lda C, de Souza FR, Guimarães AP, Sirouspour M, Cuya Guizado TR, Forgione P, Ramalho TC, França TC 26494420
CHEMISTRY
20 Diagnostic accuracy of the Depression subscale of the Hospital Anxiety and Depression Scale (HADS-D) for detecting major depression: protocol for a systematic review and individual patient data meta-analyses. Thombs BD, Benedetti A, Kloda LA, Levis B, Azar M, Riehm KE, Saadat N, Cuijpers P, Gilbody S, Ioannidis JP, McMillan D, Patten SB, Shrier I, Steele RJ, Ziegelstein RC, Loiselle CG, Henry M, Ismail Z, Mitchell N, Tonelli M 27075844
LIBRARY
21 Evolutionary Adaptation to Generate Mutants. de Vries RP, Lubbers R, Patyshakuliyeva A, Wiebenga A, Benoit-Gelber I 29876815
BIOLOGY

 

Title:Automated abdominal aortic calcification and major adverse cardiovascular events in people undergoing osteoporosis screening: the Manitoba Bone Mineral Density Registry
Authors:Smith CSim MIlyas ZGilani SZSuter DReid SMonchka BAJozani MJFigtree GSchousboe JTLewis JRLeslie WD
Link:https://pubmed.ncbi.nlm.nih.gov/39749990/
DOI:10.1093/jbmr/zjae208
Publication:Journal of bone and mineral research : the official journal of the American Society for Bone and Mineral Research
Keywords:Aortovascular diseaseDual-energy x-ray absorptiometryOsteoporosis screeningVascular calcification
PMID:39749990 Category: Date Added:2025-01-03
Dept Affiliation: ENCS
1 Nutrition & Health Innovation Research Institute, Edith Cowan University, Perth, Australia.
2 Medical School, the University of Western Australia, Perth, Australia.
3 Centre for AI&ML, School of Science, Edith Cowan University, Perth, Australia.
4 Computer Science and Software Engineering, University of Western Australia, Perth, Australia.
5 Department of Computer Science, Concordia University, Montreal, Canada.
6 George and Fay Yee Centre for Healthcare Innovation, University of Manitoba, Winnipeg, Canada.
7 Department of Statistics, University of Manitoba, Winnipeg, Canada.
8 Faculty of Health and Medicine, The University of Sydney, Sydney, NSW 2050, Australia.
9 Kolling Institute of Medical Research, Sydney, NSW 2064, Australia.
10 Park Nicollet Clinic and HealthPartners Institute, HealthPartners, Minneapolis, MN 55416, United States.
11 Centre for Kidney Research, Children's Hospital at Westmead School of Public Health, Sydney Medical School, the University of Sydney, Sydney, Australia.
12 Departments of Medicine and Radiology, University of Manitoba, Winnipeg, Canada.

Description:

Vertebral fracture assessment (VFA) images from bone density machines enable the automated machine learning assessment of abdominal aortic calcification (ML-AAC), a marker of cardiovascular disease (CVD) risk. The objective of this study was to describe the risk of a major adverse cardiovascular event (MACE, from linked health records) in patients attending routine bone mineral density (BMD) testing and meeting specific criteria based on age, BMD, height loss, or glucocorticoid use have a VFA in the Manitoba Bone Mineral Density Registry. The cohort included 10 250 individuals (mean 75.5 years, 94% women without CVD) with VFA (February 2010 to March 2017) were included. ML-AAC24 scores were categorized (low <2; moderate 2- < 6; high =6). Over follow-up (mean 3.9 years), 1265 people (12.3%) experienced a MACE. Among those with low, moderate, and high ML-AAC24, MACE rates per 1000 person-years were 18.4 (95% CI 16.4-20.5), 34.1 (95% CI 30.9-37.4), and 55.6 (95% CI 50.8-60.1), respectively. A similar gradient was observed after stratifying by age and sex. Incidence rate ratios (IRRs) for low vs. moderate and high groups were 1.9 (95% CI 1.6-2.2) and 3.0 (95% CI 2.6-3.5), respectively. In those most likely to benefit from pharmaceutical intervention (<80 years, not on statins), MACE rates among those with low, moderate and high ML-AAC24 were 13.5 (95% CI 11.5-15.8), 26.0 (95% CI 22.1-30.3) and 44.1 (95% CI 37.0-52.0). Corresponding IRRs for low vs moderate 1.9 (95% CI 1.5-2.4) and high ML-AAC24 was 3.3 (95% CI 2.6-4.1]), respectively. In routine osteoporosis screening, individuals with moderate and high ML-AAC24 had substantially greater MACE rates compared to those with low ML-AAC24. Consequently, AAC detection during osteoporosis screening (especially in women) may guide intensification of preventative cardiovascular strategies.





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