ReviewHealth technology assessment (Winchester, England)2020
Risk assessments and structured care interventions for prevention of foot ulceration in diabetes: development and validation of a prognostic model.
Review in Health technology assessment (Winchester, England), 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 1 of them a synthesis that pooled it.
What it found
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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.
The 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.
Who cites it
7 citing papers in PubMed, 1 synthesis or guideline pooled it, 32 citations in OpenAlex.
- Australian guideline on wound classification of diabetes-related foot ulcers: part of the 2021 Australian evidence-based guidelines for diabetes-related foot disease.Journal of foot and ankle research · 2021Guideline
- Comparative Analysis of Three Types of Therapeutic Offloading Diabetic Shoes With Custom Made Insole on Plantar Pressure Distribution in Severe Diabetic Charcot Foot.Canadian prosthetics & orthotics journal · 2024Article
- Prognostic models for short-term annual risk of severe complications and mortality in patients living with type 2 diabetes using a national medical claim database.Diabetology & metabolic syndrome · 2023Article
- Reliability of the evidence to guide decision-making in foot ulcer prevention in diabetes: an overview of systematic reviews.BMC medical research methodology · 2022Review
- Racial Disparities in Health Care With Timing to Amputation Following Diabetic Foot Ulcer.Diabetes care · 2022Article
- Don't overthink it: The paradoxical nature of expertise for the detection of errors in conceptual business process models.Frontiers in neuroscience · 2022Article
- Prevalence and Associated Factors of Complains on Depression, Anxiety, and Stress in University Students: An Extensive Population-Based Survey in China.Frontiers in psychology · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
16 authors at 6 institutions in 1 country.
Funding
Abstract
backgroundDiabetes-related foot ulcers give rise to considerable morbidity, generate a high monetary cost for health and social care services and precede the majority of diabetes-related lower extremity amputations. There are many clinical prediction rules in existence to assess risk of foot ulceration but few have been subject to validation.
objectivesOur objectives were to produce an evidence-based clinical pathway for risk assessment and management of the foot in people with diabetes mellitus to estimate cost-effective monitoring intervals and to perform cost-effectiveness analyses and a value-of-information analysis.
designWe developed and validated a prognostic model using predictive modelling, calibration and discrimination techniques. An overview of systematic reviews already completed was followed by a review of randomised controlled trials of interventions to prevent foot ulceration in diabetes mellitus. A review of the health economic literature was followed by the construction of an economic model, an analysis of the transitional probability of moving from one foot risk state to another, an assessment of cost-effectiveness and a value-of-information analysis.
interventionsThe effects of simple and complex interventions and different monitoring intervals for the clinical prediction rules were evaluated.
main outcome measureThe main outcome was the incidence of foot ulceration. We compared the new clinical prediction rules in conjunction with the most effective preventative interventions at different monitoring intervals with a 'treat-all' strategy. DATA SOURCES: Data from an electronic health record for 26,154 people with diabetes mellitus in one Scottish health board were used to estimate the monitoring interval. The Prediction Of Diabetic foot UlcerationS (PODUS) data set was used to develop and validate the clinical prediction rule. REVIEW
methodsWe searched for eligible randomised controlled trials of interventions using search strategies created for Ovid
resultsThe clinical prediction rule was found to accurately assess the risk of foot ulceration. Digital infrared thermometry, complex interventions and therapeutic footwear with offloading devices were found to be effective in preventing foot ulcers. The risk of developing a foot ulcer did not change over time for most people. We found that interventions to prevent foot ulceration may be cost-effective but there is uncertainty about this. Digital infrared thermometry and therapeutic footwear with offloading devices may be cost-effective when used to treat all people with diabetes mellitus regardless of their ulcer risk. LIMITATIONS: The threats to the validity of the results in some randomised controlled trials in the review and the large number of missing data in the electronic health record mean that there is uncertainty in our estimates.
conclusionsThere is evidence that interventions to prevent foot ulceration are effective but it is not clear who would benefit most from receiving the interventions. The ulceration risk does not change over an 8-year period for most people with diabetes mellitus. A change in the monitoring interval from annually to every 2 years for those at low risk would be acceptable. FUTURE WORK RECOMMENDATIONS: Improving the completeness of electronic health records and sharing data would help improve our knowledge about the most clinically effective and cost-effective approaches to prevent foot ulceration in diabetes mellitus. STUDY REGISTRATION: This study is registered as PROSPERO CRD42016052324.
fundingThis project was funded by the National Institute for Health Research (NIHR) Health Technology Assessment programme and will be published in full in
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.