Prognostic Risk Modelling for Patients Undergoing Major Lower Limb Amputation: An Analysis of the UK National Vascular Registry

IntroductionIt is estimated that peripheral arterial disease occurs in one in five people aged over 60 years in the UK. Major lower limb amputation is a debilitating and life-changing potential outcome of peripheral arterial disease. A number of risk factors are involved in the development of the disease including smoking and diabetes. There is debate over the prevalence of major lower limb amputation in the UK with regional variations unexplained. The choice of data source can affect the epidemiological calculations and sources can also differ in the ability to explain variation. This study will aim to estimate the prevalence/incidence/number of major lower limb amputation in the UK. It will also identify sources of routinely collected electronic health data which report the epidemiology of major lower limb amputation in the UK.Methods and analysisA systematic search of peer-reviewed journals will be conducted in Medline, Excerpta Medica database, Cumulative Index of Nursing and Allied Health Literature, Allied and Complementary Medicine Database, The Cochrane Library and Scopus. A grey literature search for government and parliament publications, conference abstracts, theses and unpublished articles will be performed. Articles will be screened against the inclusion/exclusion criteria and data extracted using a pretested extraction form by two independent reviewers. Prevalence, incidence or number of cases (depending on data reported) will be extracted. Disagreements will be resolved by discussion. Data synthesis will be performed either as a narrative summary or by meta-analysis. Heterogeneity will be assessed using the I2 statistic. If heterogeneity is low-moderate, pooled estimates will be calculated using random-effects models. If possible, meta-regression for time trends in the incidence of major lower limb amputation will be performed along with subgroup analysis, primarily in regional variation.Ethics and disseminationEthics approval is not required for this study as study data are anonymised and available in the public domain. Dissemination will be by publication in a peer reviewed journal and by appropriate conference presentation.PROSPERO registration numberCRD42020165592

Download Full-text

Metric Charcteristics of Sit-to-stand Tests in Patients After Lower-limb Amputation

Case Medical Research ◽

10.31525/ct1-nct04293237 ◽

2020 ◽

Author(s):

Keyword(s):

Lower Limb ◽

Lower Limb Amputation ◽

Limb Amputation ◽

Sit To Stand

Download Full-text

Prostheses and orthoses. Factors to be considered when specifying a prosthesis for a person who has had a lower limb amputation

10.3403/30178636 ◽

2009 ◽

Keyword(s):

Lower Limb ◽

Lower Limb Amputation ◽

Limb Amputation

Download Full-text

Prostheses and orthoses. Factors to be included when describing physical activity of a person who has had a lower limb amputation(s) or who has a deficiency of a lower limb segment(s) present at birth

10.3403/30178633u ◽

2015 ◽

Keyword(s):

Physical Activity ◽

Lower Limb ◽

Lower Limb Amputation ◽

Limb Amputation ◽

Limb Segment

Download Full-text

Prostheses and orthoses. Factors to be included when describing physical activity of a person who has had a lower limb amputation(s) or who has a deficiency of a lower limb segment(s) present at birth

10.3403/30178633 ◽

2009 ◽

Keyword(s):

Physical Activity ◽

Lower Limb ◽

Lower Limb Amputation ◽

Limb Amputation ◽

Limb Segment

Download Full-text

P90 PERCEIVE: PrEdiction of Risk and Communication of outcome following major lower limb amputation - a collaboratIVE study

BJS Open ◽

10.1093/bjsopen/zrab032.089 ◽

2021 ◽

Vol 5 (Supplement_1) ◽

Author(s):

B Gwilym ◽

C Waldron ◽

E Thomas-Jones ◽

P Pallmann ◽

R Preece ◽

...

Keyword(s):

Risk Prediction ◽

Lower Limb ◽

Health Care Professionals ◽

Healthcare Professionals ◽

Demographic Data ◽

Collaborative Study ◽

Lower Limb Amputation ◽

Research Network ◽

Limb Amputation ◽

Prediction Tools

Abstract Introduction Major Lower Limb Amputation (MLLA) is a life changing event with significant morbidity and mortality. Inaccurate risk prediction can lead to poor decision making, resulting in delay to definitive surgery, or undertaking amputation when not in the patient’s best interest. We aim to answer: In adult patients undergoing MLLA for chronic limb threatening ischaemia or diabetes, how accurately do health care professionals prospectively predict outcomes after MLLA, and how does this compare to existing prediction tools? Methods A multicentre prospective observational cohort study is being delivered through the Vascular and Endovascular Research Network. Dissemination was via an existing network of contacts and social media. Consecutive data will be collected for seven months from site launch date, including demographic data and pre-operative outcome predictions from surgeons, anaesthetists, and allied healthcare professionals. Follow-up data will comprise 30-day (mortality, morbidity, MLLA revision, surgical site infection, and blood transfusion) and 1-year (mortality, MLLA revision and ambulation). The accuracy of surgeons’ predictions will be evaluated and compared to pre-existing risk prediction scoring tools. Results PERCEIVE launched on 01/10/2020 with 23 centres (16 UK, 7 international) registered to collect data. 50 other centres (27 UK, 23 international) have expressed interest/are pursuing local audit/ethical approval. We aim to collect data on clinicians estimate of outcomes for over 500 patients. Discussion This study will utilise a trainee research network to provide data on the accuracy of healthcare professionals’ predictions of outcomes following MLLA and compare this to the utility of existing prediction tools in this patient cohort.

Download Full-text