同步报告病例2（第十回）：截肢截肢，激起一圈迷茫：一个标准糖尿病足患者的处理经过

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15 10月 2019

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Author : 伤口世界

中山二院糖尿病足中心

这只熟悉的脚

已经在一些会议上得到了展示

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现在到底如何？

2018年12月5日

2018年12月8日

等再长几天

足背就痊愈了

足底再观察观察！

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Evidence-based interventions for identifying candidate quality indicators to assess quality of care in diabetic foot clinics: a scoping review 2025-08-27 00:00

Flora Mbela Lusendi1,2* , An‑Sofie Vanherwegen1 , Kris Doggen1 , Frank Nobels3 and Giovanni Arnoldo Matricali2,4 *Correspondence: Flora Mbela Lusendi 该Email地址已收到反垃圾邮件插件保护。要显示它您需要在浏览器中启用JavaScript。

1 Health Services Research, Sciensano, Rue Juliette Wytsmanstraat 14, Brussels 1050, Belgium

2 Department of Development and Regeneration, KU Leuven, Leuven, Belgium

3 Multidisciplinary Diabetic Foot Clinic, Onze-Lieve-Vrouwziekenhuis, Aalst, Belgium

4 Multidisciplinary Diabetic Foot Clinic, University Hospital Leuven, Leuven, Belgium

© The Author(s) 2024. Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecom‑ mons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

Abstract

Background Foot ulcers in people with diabetes are a serious complication requiring a complex management and have a high societal impact. Quality monitoring systems to optimize diabetic foot care exist, but a formal and more evidence-based approach to develop quality indicators (QIs) is lacking. We aimed to identify a set of candi‑ date indicators for diabetic foot care by adopting an evidence-based methodology.

Methods A systematic search was conducted across four academic databases: PubMed, Embase CINAHL and Cochrane Library. Studies that reported evidence-based interventions related to organization or delivery of dia‑ betic foot care were searched. Data from the eligible studies were summarized and used to formulate process and structure indicators. The evidence for each candidate QI was described in a methodical and transparent manner. The review process was reported according to the “Preferred Reported Items for Systematic reviews and Meta-Analy‑ sis” (PRISMA) statements and its extension for scoping reviews.

Results In total, 981 full-text articles were screened, and 322 clinical studies were used to formulate 42 candidate QIs.

Conclusions An evidence-based approach could be used to select candidate indicators for diabetic foot ulcer care, relating to the following domains: wound healing interventions, peripheral artery disease, offloading, secondary pre‑ vention, and interventions related to organization of care. In a further step, the feasibility of the identified set of indica‑ tors will be assessed by a multidisciplinary panel of diabetic foot care stakeholders.

Keywords Diabetic foot ulcer, Quality of healthcare, Quality indicators, Evidence-based medicine, Health service research
Sex and APOE ε4 allele differences in longitudinal white matter microstructure in multiple cohorts of aging and Alzheimer’s disease 2025-08-26 00:00

Amalia Peterson1,2 | Aditi Sathe1 | Dimitrios Zaras1 | Yisu Yang1 | Alaina Durant1 | Kacie D. Deters3 | Niranjana Shashikumar1 | Kimberly R. Pechman1 | Michael E. Kim4 | Chenyu Gao5 | Nazirah Mohd Khairi5 | Zhiyuan Li5 | Tianyuan Yao4 | Yuankai Huo4,5 | Logan Dumitrescu1,2,6,7 | Katherine A. Gifford1,2 | Jo Ellen Wilson1,8,9 | Francis E. Cambronero1 | Shannon L. Risacher10,11 | Lori L. Beason-Held12 | Yang An12 | Konstantinos Arfanakis13,14,15 | Guray Erus16 | Christos Davatzikos16 | Duygu Tosun17 | Arthur W. Toga18 | Paul M. Thompson19 | Elizabeth C. Mormino20 | Mohamad Habes21 | Di Wang21 | Panpan Zhang1,22 | Kurt Schilling23,24 | Alzheimer’s Disease Neuroimaging Initiative (ADNI) | The BIOCARD | Study Team | The Alzheimer’s Disease Sequencing Project (ADSP) | Marilyn Albert25 | Walter Kukull26 | Sarah A. Biber26 | Bennett A. Landman2,4,5,7,23,24,27 | Sterling C. Johnson28,29 | Julie Schneider14 | Lisa L. Barnes14 | David A. Bennett14 | Angela L. Jefferson1,2,4 | Susan M. Resnick12 | Andrew J. Saykin10,11 | Timothy J. Hohman1,2,6,7 | Derek B. Archer1,2,6,7

Correspondence

Derek B. Archer, Vanderbilt Memory and Alzheimer’s Center, 3319 West End Ave., Nashville, TN 37203, USA. Email: 该Email地址已收到反垃圾邮件插件保护。要显示它您需要在浏览器中启用JavaScript。

Funding information

BAL, Grant/Award Number: R01-EB017230; DBA, Grant/Award Number: K01-AG073584; TJH, Grant/Award Number: U24-AG074855; Vanderbilt Clinical Translational Science Award, Grant/Award Numbers: UL1-TR000445, UL1-TR002243; Vanderbilt’s High-Performance Computer Cluster for Biomedical Research, Grant/Award Numbers: R01-AG080821, S10-OD023680; Alzheimer’s Association, Grant/Award Number: IIRG-08-88733(ALJ); NIH, Grant/Award Numbers: K01-EB032898 (KGS), R01-EB017230 (BAL), K01-AG073584 (DBA), U24-AG074855 (TJH), R01-AG059716 (TJH), UL1-TR000445 (Vanderbilt Clinical Translational Science Award), UL1-TR002243 (Vanderbilt Clinical Translational Science Award), S10-OD02380 (Vanderbilt’s High-Performance Computer Cluster for Biomedical Research), R01-AG080821 (MH), R01-AG034962 (ALJ), R01-AG056534 (ALJ), R01-AG062826 (KAG), U19-AG03655 (MA); Intramural NIH, Grant/Award Number: 75N95D22P00141

This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

© 2024 The Author(s). Alzheimer’s & Dementia published by Wiley Periodicals LLC on behalf of Alzheimer’s Association.

Abstract

INTRODUCTION: The effects of sex and apolipoprotein E (APOE)—Alzheimer’s disease (AD) risk factors—on white matter microstructure are not well characterized.

METHODS: Diffusion magnetic resonance imaging data from nine well-established longitudinal cohorts of aging were free water (FW)–corrected and harmonized. This dataset included 4741 participants (age = 73.06 ± 9.75) with 9671 imaging sessions over time. FW and FW-corrected fractional anisotropy (FAFWcorr) were used to assess differences in white matter microstructure by sex and APOE ε4 carrier status.

RESULTS: Sex differences in FAFWcorr in projection tracts and APOE ε4 differences in FW limbic and occipital transcallosal tracts were most pronounced.

DISCUSSION: There are prominent differences in white matter microstructure by sex and APOE ε4 carrier status. This work adds to our understanding of disparities in AD. Additional work to understand the etiology of these differences is warranted.

KEYWORDS

aging, Alzheimer’s disease, sex differences, white matter disease

Highlights

∙ Sex and apolipoprotein E (APOE) ε4 carrier status relate to white matter microstruc tural integrity.

∙ Females generally have lower free water–corrected fractional anisotropy compared to males.

∙ APOE ε4 carriers tended to have higher free water than non-carriers.
Overview of Alzheimer’s Disease Neuroimaging Initiative and future clinical trials 2025-08-25 00:00

Michael W. Weiner1,2,3,4,5,6 | Shaveta Kanoria1,6 | Melanie J. Miller1,6 | Paul S. Aisen7 | Laurel A. Beckett8 | Catherine Conti1,6 | Adam Diaz1,6 | Derek Flenniken6 | Robert C. Green9 | Danielle J. Harvey8 | Clifford R. Jack Jr.10 | William Jagust11 | Edward B. Lee12 | John C. Morris13,14,15 | Kwangsik Nho16,17 | Rachel Nosheny1,4 | Ozioma C. Okonkwo18 | Richard J. Perrin13,14,15 | Ronald C. Petersen19 | Monica Rivera-Mindt20,21 | Andrew J. Saykin16,22 | Leslie M. Shaw23 | Arthur W. Toga24 | Duygu Tosun1,2 | Dallas P. Veitch1,6 for the Alzheimer’s Disease Neuroimaging Initiative

1 Department of Veterans Affairs Medical Center, Center for Imaging of Neurodegenerative Diseases, San Francisco, California, USA

2 Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, California, USA

3 Department of Medicine, University of California San Francisco, San Francisco, California, USA

4 Department of Psychiatry and Behavioral Sciences, University of California San Francisco, San Francisco, California, USA

5 Department of Neurology, University of California San Francisco, San Francisco, California, USA

6 Northern California Institute for Research and Education (NCIRE), San Francisco, California, USA

7 Alzheimer’s Therapeutic Research Institute, University of Southern California, San Diego, California, USA

8 Division of Biostatistics, Department of Public Health Sciences, University of California, Medical Sciences 1C, Davis, California, USA

9 Division of Genetics, Department of Medicine, Brigham and Women’s Hospital, Broad Institute Ariadne Labs and Harvard Medical School, Boston, Massachusetts, USA

10 Department of Radiology, Mayo Clinic, Rochester, Minnesota, USA

11 Helen Wills Neuroscience Institute, University of California Berkeley, Berkeley, California, USA

12 Translational Neuropathology Research Laboratory, Department of Pathology and Laboratory Medicine, Perelman School of Medicine at the University of

Pennsylvania, Philadelphia, Pennsylvania, USA

13 Knight Alzheimer’s Disease Research Center, Washington University School of Medicine, Saint Louis, Missouri, USA

14 Department of Neurology, Washington University School of Medicine, Saint Louis, Missouri, USA

15 Department of Pathology and Immunology, Washington University School of Medicine, St. Louis, Missouri, USA

16 Department of Radiology and Imaging Sciences and the Indiana Alzheimer’s Disease Research Center, Indiana University School of Medicine, Indianapolis, Indiana, USA

17 Center for Computational Biology and Bioinformatics, Indiana University School of Medicine, Indianapolis, Indiana, USA

18 Wisconsin Alzheimer’s Disease Research Center and Department of Medicine, University of Wisconsin School of Medicine and Public Health, Clinical Science Center, Madison, Wisconsin, USA

19 Department of Neurology, Mayo Clinic, Rochester, Minnesota, USA

20 Department of Psychology, Latin American and Latino Studies Institute, African and African American Studies, Fordham University, Bronx, New York, USA

21 Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, New York, USA

22 Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, Indiana, USA

23 Department of Pathology and Laboratory Medicine and the PENN Alzheimer’s Disease Research Center, Center for Neurodegenerative Research, Perelman School of Medicine, University of Pennsylvania, Philadelphia, USA

24 Laboratory of Neuro Imaging, Institute of Neuroimaging and Informatics, Keck School of Medicine of the University of Southern California, San Diego, California, USA

Correspondence

Michael W. Weiner, Department of Veterans Affairs Medical Center, Center for Imaging of Neurodegenerative Diseases, 4150 Clement St, San Francisco, CA 94121, USA. Email: 该Email地址已收到反垃圾邮件插件保护。要显示它您需要在浏览器中启用JavaScript。 Data used in preparation of this article were obtained from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) database (adni.loni.usc.edu). As such, the investigators within the ADNI contributed to the design and implementation of ADNI and/or provided data. Some ADNI investigators participated in analysis or writing of this report. A complete listing of ADNI investigators can be found at: http://adni.loni.usc.edu/wp content/uploads/how_to_apply/ ADNI_Acknowledgement_List.pd

Funding information

NIH, Grant/Award Number: U19 -AG 024904; National Institute on Aging, Grant/Award Number: U19AG024904

This is an open access article under the terms of the Creative Commons Attribution-NonCommercial License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited and is not used for commercial purposes.

© 2024 The Author(s). Alzheimer’s & Dementia published by Wiley Periodicals LLC on behalf of Alzheimer’s Association.

Abstract

The overall goal of the Alzheimer’s Disease Neuroimaging Initiative (ADNI) is to opti mize and validate biomarkers for clinical trials while sharing all data and biofluid samples with the global scientific community. ADNI has been instrumental in stan dardizing and validating amyloid beta (Aβ) and tau positron emission tomography (PET) imaging. ADNI data were used for the US Food and Drug Administration (FDA) approval of the Fujirebio and Roche Elecsys cerebrospinal fluid diagnostic tests. Additionally, ADNI provided data for the trials of the FDA-approved treatments aducanumab, lecanemab, and donanemab. More than 6000 scientific papers have been published using ADNI data, reflecting ADNI’s promotion of open science and data sharing. Despite its enormous success, ADNI has some limitations, particularly in generalizing its data and findings to the entire US/Canadian population. This introduction provides a historical overview of ADNI and highlights its significant accomplishments and future vision to pioneer “the clinical trial of the future” focusing on demographic inclusivity.

KEYWORDS

Alzheimer’s disease, Alzheimer’s disease biomarkers, Alzheimer’s disease clinical trials, Alzheimer’s Disease Neuroimaging Initiative, Alzheimer’s disease progression, amyloid, Lab oratory of Neuro Imaging, magnetic resonance imaging, neurodegeneration, positron emission tomography, post-traumatic stress disorder, tau, underrepresented populations

Highlights

∙ The Alzheimer’s Disease Neuroimaging Initiative (ADNI) introduced a novel model for public-private partnerships and data sharing.

∙ It successfully validated amyloid and Tau PET imaging, as well as CSF and plasma biomarkers, for diagnosing Alzheimer’s disease.

∙ ADNI generated and disseminated vital data for designing AD clinical trials.

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同步报告病例2（第十回）：截肢截肢，激起一圈迷茫：一个标准糖尿病足患者的处理经过

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主任医师、教授、博导，南方医科大学第三附属医院（广东省骨科医院）院长

同步报告病例2（第十回）：截肢截肢，激起一圈迷茫：一个标准糖尿病足患者的处理经过

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