Evidence map›Paper›PMID 33236718›Full record

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.

Fay Crawford, Francesca M Chappell, James Lewsey, Richard Riley, Neil Hawkins, Donald Nicolson, Robert Heggie, Marie Smith, Margaret Horne, Aparna Amanna and 6 more

Open access · diamondAbstract readReview
In one paragraph

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.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed, 1 pooled it
2.8field-weighted citation impact, top 8% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

7 citing papers in PubMed, 1 synthesis or guideline pooled it, 32 citations in OpenAlex.

  1. Guideline
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

16 authors at 6 institutions in 1 country.

Fay CrawfordNHS Fife, R&D Department, Queen Margaret Hospital, Dunfermline, UK.ORCID 0000-0002-0473-9959
Francesca M ChappellNeuroimaging Sciences, Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK.ORCID 0000-0002-7742-1757
James LewseyNeuroimaging Sciences, Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK.ORCID 0000-0002-3811-8165
Richard RileyResearch Institute for Primary Care and Health Sciences, Keele University, Keele, UK.ORCID 0000-0001-8699-0735
Neil HawkinsHealth Economics and Health Technology Assessment (HEHTA), Institute of Health & Wellbeing, University of Glasgow, Glasgow, UK.ORCID 0000-0003-3199-221X
Donald NicolsonNHS Fife, R&D Department, Queen Margaret Hospital, Dunfermline, UK.ORCID 0000-0003-4190-6434
Robert HeggieHealth Economics and Health Technology Assessment (HEHTA), Institute of Health & Wellbeing, University of Glasgow, Glasgow, UK.ORCID 0000-0001-7396-4773
Marie SmithLibrary & Knowledge Service, Victoria Hospital, NHS Fife, Kirkcaldy, UK.ORCID 0000-0002-1572-0268
Margaret HorneUsher Institute, University of Edinburgh, Edinburgh, UK.ORCID 0000-0001-7621-2462
Aparna AmannaNHS Fife, R&D Department, Queen Margaret Hospital, Dunfermline, UK.
Angela MartinDiabetes Centre, Victoria Hospital, NHS Fife, Kirkcaldy, UK.
Saket GuptaDiabetes Centre, Victoria Hospital, NHS Fife, Kirkcaldy, UK.ORCID 0000-0003-2643-626X
Karen GrayNHS Fife, R&D Department, Queen Margaret Hospital, Dunfermline, UK.ORCID 0000-0001-7091-7568
David WellerUsher Institute, University of Edinburgh, Edinburgh, UK.ORCID 0000-0002-8112-718X
Julie BrittendenInstitute of Cardiovascular & Medical Sciences, University of Glasgow, Glasgow, UK.ORCID 0000-0002-1441-6774
Graham LeeseDiabetes and Endocrinology, Ninewells Hospital, NHS Tayside, Dundee, UK.ORCID 0000-0003-0570-5678
NHS Fife · GBUniversity of Edinburgh · GBUniversity of Glasgow · GBKeele University · GBNHS Tayside · GBUniversity of St Andrews · GB

Funding

Department of Health 15/171/01
6 · The paper itself

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

Indexed as

Cost-Benefit AnalysisCritical PathwaysDiabetic FootHumansModels, EconomicPractice Guidelines as TopicPrognosisQuality-Adjusted Life YearsRandomized Controlled Trials as TopicReproducibility of ResultsRisk AssessmentState MedicineTechnology Assessment, BiomedicalTime FactorsUnited KingdomCLINICAL PATHWAYCLINICAL PREDICTION RULECOST–BENEFIT ANALYSISCOST-EFFECTIVENESSDIABETES, FOOT ULCERSECONOMIC MODELSRISK ASSESSMENTS

Identifiers

PMID33236718
PMCPMC7768791
OpenAlexW3107317679

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.