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Imogen Stamford
Research has shown that use of continuous glucose monitoring (CGM) is associated with improved time in range, improved HbA1c, and decreased risk of long-term complications secondary to type 1 diabetes. There are, however, several barriers that can lead to discontinuation of CGM, including pain, skin reactions, concerns around accuracy, sensor loss, interference with daily activity, and alarm fatigue. This review paper will outline the impact of decision fatigue and alarm fatigue in children and young people using CGM.
Citation: Stamford I (2022) CGM for children and young people with type 1 diabetes: NICE criteria and effects of decision fatigue and alarm fatigue. Diabetes Care for Children & Young People 12: [Early view publication]
Article points
1. While the advantages of continuous glucose monitoring (CGM) are well recognised, as practitioners it is important to be aware of the implications of CGM use.
2. People with diabetes can never have a day without checking and responding to ever-changing glucose levels, which puts them at an increased risk of developing decision fatigue.
3. It is important for practitioners to support patients in creating balance between setting alarm limits that are narrow enough to ensure patient safety, but not so narrow that alarms will be repeatedly triggered can lead to the risk of alarms being ignored.
Key words
- Alarm fatigue - Continuous glucose monitoring - Decision fatigue - Type 1 diabetes
Author
Imogen Stamford, Paediatric Diabetes Specialist Nurse, Oxford University Hospitals NHS Foundation Trust
Ellen K. White and Elizabeth A. Grice
Department of Dermatology, University of Pennsylvania, Perelman School of Medicine, Philadelphia,
Pennsylvania 19104, USA
Correspondence: 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。
Breach of the skin barrier and subsequent wound healing occur in the context of microbial communities of bacteria, fungi, and viruses. These polymicrobial communities are dynamic and important components of the wound environment and are associated with differential healing outcomes. Here, we highlight both culture-dependent and -independent methods that have furthered our understanding of the wound microbiome. We discuss common themes that have developed from such studies about the microbial inhabitants of diverse wound types.We additionally explore the wide range of microbial mechanisms that influence healing, from invading pathogens to beneficial commensals. These insights can be leveraged to better predict healing outcomes and derive novel microbial-based therapies for chronic wounds.
Editors: Xing Dai, Sabine Werner, Cheng-Ming Chuong, and Maksim Plikus Additional Perspectives on Wound Healing: From Bench to Bedside available at www.cshperspectives.org Copyright © 2022 Cold Spring Harbor Laboratory Press; all rights reserved Advanced Online Article. Cite this article as Cold Spring Harb Perspect Biol doi: 10.1101/cshperspect.a041218
Qinghan Tang a,1 , Nannan Xue a,b,1 , Xiaofeng Ding c,d , Kevin H.-Y. Tsai e , Jonathan J. Hew f , Ruihan Jiang a ,
Rizhong Huang a , Xuxi Cheng a , Xiaotong Ding a , Yuen Yee Cheng g , Jun Chen a,b,⇑ , Yiwei Wang a,b,e,⇑
a Jiangsu Provincial Engineering Research Center of TCM External Medication Development and Application, Nanjing University of Chinese Medicine, Nanjing 210023, PR China
b Jiangsu Collaborative Innovation Center of Chinese Medicinal Resources Industrialization, Nanjing University of Chinese Medicine, Nanjing 210023, PR China
c Department of Burns and Plastic Surgery, Nanjing Drum Tower Hospital Clinical College of Traditional Chinese and Western Medicine, Nanjing University of Chinese Medicine, Nanjing 210023, PR China
d Department of Plastic Surgery, Shanghai Fourth People’s Hospital, School of Medicine, Tongji University, Shanghai 200434, PR China
e Burns and Reconstructive Surgery Group, ANZAC Research Institute, Concord Hospital, The University of Sydney, Concord West, NSW 2137, Australia
f General Surgery, Lesimore Hospital, NSW 2480, Australia
g Institute for Biomedical Materials and Devices, School of Mathematical and Physical Sciences, University of Technology Sydney, NSW 2007 Australia
abstract
Delayed wound healing is one of the most global public health threats affecting nearly 100 million people each year, particularly the chronic wounds. Many confounding factors such as aging, diabetic disease, medication, peripheral neuropathy, immunocompromises or arterial and venous insuffificiency hyperglycaemia are considered to inhibit wound healing. Therapeutic approaches for slow wound healing include anti-infection, debridement and the use of various wound dressings. However, the current clinical outcomes are still unsatisfified. In this review, we discuss the role of skin and wound commensal microbiota in the different healing stages, including inflflammation, cell proliferation, re-epithelialization and remodelling phase, followed by multiple immune cell responses to commensal microbiota. Current clinical management in treating surgical wounds and chronic wounds was also reviewed together with potential controlled delivery systems which may be utilized in the future for the topical administration of probiotics and microbiomes. This review aims to introduce advances, novel strategies, and pioneer ideas in regulating the wound microbiome and the design of controlled delivery systems.
article info
Article history:
Received 27 September 2022 Revised 23 November 2022 Accepted 14 December 2022 Available online 17 December 2022
Keywords:
Wound healing,Skin microbiome,Inflammation,Clinical wound care,Cell response to microbiome,Probiotic delivery
Abbreviations: 16S-rDNA, 16S ribosomal DNA identifification; b2-AR, b2-adrenergic receptor; ADAM10, A disintegrin and metalloprotease 10; AHR, aryl hydrocarbon receptor; AMP, adenosine monophosphate; B. subtilis, Bacillus subtilis; C. albicans, Candida albicans; CSF, colony-stimulating factor; CXCL2, chemokine (C-X-C motif) ligand 2; CXCL10, chemokine (C-X-C motif) ligand 10; CXCL12, chemokine (C-X-C motif) ligand 12; DFU, diabetic foot ulcer; ECM, extracellular matrix; E. coli, Escherichia coli; EPB, epidermal permeability barrier; EVs, extracellular vesicles; FDA, Food and Drug Administration; hBD, human b-defensin; HF, Hair follicle; HMP, Human Microbiome Project; IL-1, interleukin-1; IL-1R, interleukin-1R; IL-1b, interleukin-1b; IL-6, interleukin-6; IL-23, interleukin-23; K. pneumoniae, Klebsiella pneumoniae; L. acidophilus, Lactobacillus acidophilus; L. lactis, Lactococcus lactis; L. plantarum, Lactobacillus plantarum; L. reuteri, Lactobacillus reuteri; L. rhamnosus, Lactobacillus rhamnosus; M CSF, macrophage colonystimulating factor; MHCII, major histocompatibility complex II; MMP-9, matrix metalloproteinase-9; MRSA, methicillin-resistant Staphylococcus aureus; MYD88, myeloid differentiation factor 88; NETs, neutrophil extracellular traps; NIH, National Institutes of Health; NPWT, negative pressure wound therapy; P. aeruginosa, Pseudomonas aeruginosa; pDCs, plasmacytoid dendritic cells; PEO, polyethylene oxide; PLA, polylactic acid; ROS, reactive oxygen species; PRP, Plat-rich plasma; PVA, polyvinyl alcohol; PVP, polyvinyl pyrrolidone; SadA, serum adenosine deaminase; S. aureus, Staphylococcus aureus; Sbi, staphylococcal immunoglobulin-binding protein; SCMC, sodium carboxymethylcellulose; S. epidermidis, Staphylococcus epidermidis; SLO, streptolysin O; SpA, Staphylococcal protein A; SPF, specifific pathogen-free; SSWI, surgical site wound infection; TAs, trace amines; Tc17, cytotoxic T cells 17; TGF-b1, transforming growth factor-b1; TNF-a, tumor necrosis factor-a; VEGF, vascular endothelial growth factor; WHO, World Health Organisation. ⇑ Corresponding authors at: Jiangsu Provincial Engineering Research Center of TCM External Medication Development and Application, Nanjing University of Chinese Medicine, 138 Xianlin Avenue, Nanjing 210023, PR China. E-mail addresses: 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。, 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。 (J. Chen), 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。 (Y. Wang). 1 These authors contributed equally to these work.
https://doi.org/10.1016/j.addr.2022.114671 0169-409X/ 2022 Published by Elsevier B.V.
Lihong Chen MD1 | Shiyi Sun MD1 | Yunyi Gao MD2 | Xingwu Ran MD1
1 Innovation Center for Wound Repair, Diabetic Foot Care Center, Department of Endocrinology and Metabolism, West China Hospital, Sichuan University, Chengdu, China
2 Department of Medical Affairs, West China Hospital, Sichuan University, Chengdu, China
Correspondence
Xingwu Ran, MD, Innovation Center for Wound Repair, Diabetic Foot Care Center, Department of Endocrinology and Metabolism, West China Hospital, Sichuan University, 37 Guo Xue Lane, Chengdu 610041, China.
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
This study was partially supported by the Science and Technology Bureau of Sichuan Province (grant no. 2021JDKP004), West China Nursing Discipline Development Special Fund Project, Sichuan University (grant no. HXHL20005) and the 1.3.5 Project for disciplines of excellence, West China Hospital, Sichuan University (grant no. ZYGD18025).
Abstract
Aim: To estimate the long-term mortality and risk factors in patients with diabetic foot ulcer (DFU).
Methods: We systematically searched Medline (PubMed), Embase, Scopus, Web of Science, Cochrane Library, China Science and Technology Journal Database (CQVIP), China National Knowledge Infrastructure, the Chinese Biomedical Literature Database (SinoMed) and Wanfang Data from 1 January 2011 to 31 July 2022. All observational studies that reported long-term mortality of patients with DFU were included. Random effect models were used to pool the reconstructed participant data from Kaplan–Meier curves. The primary outcome was the long-term survival of patients with DFU. An aggregate data meta-analysis was also performed.
Results: We identified 34 studies, with 124 376 participants representing 16 countries, among whom there were 51 386 deaths. Of these, 27 studies with 21 171 patients were included in the Kaplan–Meier-based meta-analysis. The estimated Kaplan–Meier-based survival rates were 86.9% (95% confidence interval [CI] 82.6%- 91.5%) at 1 year, 66.9% (95% CI 59.3%-75.6%) at 3 years, 50.9% (95% CI 42.0%- 61.7%) at 5 years and 23.1% (95% CI 15.2%-34.9%) at 10 years. The results of the aggregate data-based meta-analysis were similar. Cardiovascular disease and infection were the most common causes of death, accounting for 46.6% (95% CI 33.5%-59.7%) and 24.8% (95% CI 16.0%-33.5%), respectively. Patients with older age (per1 year, hazard ratio [HR] 1.054, 95% CI 1.045-1.063), peripheral artery disease (HR 1.882, 95% CI 1.592-2.225), chronic kidney disease (HR 1.535, 95% CI 1.227-1.919), end-stage renal disease (HR 3.586, 95% CI 1.333-9.643), amputation (HR 2.415, 95% CI 1.323-4.408) and history of cardiovascular disease (HR 1.449, 95% CI 1.276-1.645) had higher mortality risk.
Conclusions: This meta-analysis found that the overall mortality of DFU was high, with nearly 50% mortality within 5 years. Cardiovascular disease and infection were the two leading causes of death.
KEYWORDS
cardiovascular disease, diabetic foot, mortality