痛风患者如何选择饮食疗法？

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12 10月 2019

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Author : 伤口世界

原创：卢魁

痛风之痛:
尿酸盐在体内大量沉积形成结晶，体表、手脚关节部位会慢慢长出痛风石，时间长了会导致关节破坏、关节畸形，影响正常功能。尿酸盐长期沉积在肾脏，会引发痛风性肾病，严重的甚至导致尿毒症。

痛风患者还常伴发有高脂血血症、高血压、糖尿病及冠心病。痛风久治不愈、反复发作也会形成慢性伤口。一般人正常膳食每天摄人嘌呤600~1000毫克，痛风急性发作期摄人量应控制在150 毫克以内，缓解期也应遵循低嘌呤饮食。
食物嘌呤含量参考
嘌呤含量> 150 毫克/100克。动物内脏：肝、肾、脑、脾、肠；部分水产：带鱼、鲶鱼、鲢鱼、沙丁鱼、凤尾鱼、基围虾等。肉汤、鱼汤、海鲜火锅汤。
嘌呤含量在75-150毫克|100克。猪、牛、羊肉、鸡鸭等；鲈鱼、鲤鱼、鲫鱼、草鱼；螃蟹；黑豆、黄豆、绿豆等。
嘌呤含量在30-75毫克/100克。菠菜、芦笋、毛豆、豌豆、三文鱼、金枪鱼及豆浆、豆干、豆皮、腐竹、豆腐等。
嘌呤含量< 30毫克/100克。大白菜、土豆、芋头、白薯、木薯、番茄、茄子、冬瓜。部分杂粮：小米、荞麦、燕麦；葡萄、苹果、草莓；米饭、馒头等。

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Comprehensive cost-of-illness analysis of pressure ulcer treatment: A real-world study at a Czech university hospital 2025-08-28 00:00

Lenka Krupova1 | Andrea Pokorna2,3 | Miroslav Krupa4 | Klara Bene sov ˇ a3

1 Department of Dermatology, University Hospital Ostrava, Ostrava, Czech Republic

2 Department of Health Sciences, Faculty of Medicine, Masaryk University, Brno, Czech Republic

3 Institute of Biostatistics and Analyses, Faculty of Medicine, Masaryk University, Brno, Czech Republic

4 Faculty of Business Administration, Prague University of Economics and Business, Prague, Czech Republic

Correspondence

Andrea Pokorna, Department of Health Sciences, Faculty of Medicine, Masaryk University, Kamenice 753/5, 625 00 Brno, Czech Republic. 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

Ministerstvo Zdravotnictví Ceské Republiky, Grant/Award Number: NU20-09-00094

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.

© 2025 The Author(s). International Wound Journal published by Medicalhelplines.com Inc and John Wiley & Sons Ltd.

Abstract

Pressure ulcers (PUs) impose a significant economic burden on healthcare sys tems, affecting patient quality of life and leading to substantial treatment costs. This study presents a cost-of-illness analysis of PU treatment in hospitalized patients in the Czech Republic, based on real-world clinical data. The analysis was conducted using a comprehensive methodology at a Czech university hos pital, involving 304 hospitalizations. The study included all hospitalized patients with PUs. Data were collected employing a bottom-up, person-based approach, which refers to the collection and analysis of cost data at the individ ual patient level. This method captures detailed resource utilization for each patient. The methodology accounted for both systemic and local costs, includ ing materials, medications, caregiver time, and procedures. The study involved 304 hospitalizations, with a mean length of stay of 13 days. The total cost of PU treatment, excluding pharmacotherapy, had a median of €678, while including pharmacotherapy, the median cost rose to €929. Younger patients incurred higher treatment costs. Significant cost variations were observed among different departments. We developed and applied a novel cost model to quantify the expenses associated with PUs, which accurately highlighted the financial burden in the hospital care setting. We present a rigorous methodol ogy for PU cost-of-illness analysis, providing a valuable tool for future research and clinical practice. This comprehensive approach supports the development of targeted interventions to reduce the incidence and severity of PUs, ulti mately improving patient care and reducing healthcare costs.

KEYWORDS

cost analysis, healthcare costs, patients, pressure ulcers, treatment costs

Key Messages

Accurate cost-of-illness analysis of pressure ulcer treatment is crucial for improving patient outcomes and reducing healthcare costs.

This study developed a methodology to calculate PU treatment costs, using data from 304 hospitalizations at a Czech university hospital.

The median PU treatment cost was €678 (excluding pharmacotherapy) and €929 (including pharmacotherapy), with significant cost variations across

The cost model provides a tool for targeting interventions in pressure ulcers' management to reduce financial burden and enhance patient care.
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.

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