Cognition and Mobility Rehabilitation Following Lower Limb Amputation

2007 ◽  
pp. 53-65 ◽  
Author(s):  
Brian O’Neill
Keyword(s):  
Lower Limb ◽  
Lower Limb Amputation ◽  
Limb Amputation

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

BJS Open ◽  
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.

scholarly journals Socio-economic outcome of paraplegia compared to lower limb amputation

Spinal Cord ◽  
2002 ◽  
Vol 40 (4) ◽  
pp. 174-177 ◽  
Author(s):  
A Cavigelli ◽  
R Fischer ◽  
V Dietz
Keyword(s):  
Lower Limb ◽  
Lower Limb Amputation ◽  
Economic Outcome ◽  
Limb Amputation

scholarly journals Geographic Variation of the Incidence Rate of Lower Limb Amputation in Australia from 2007-12

PLoS ONE ◽  
2017 ◽  
Vol 12 (1) ◽  
pp. e0170705 ◽  
Author(s):  
Michael P. Dillon ◽  
Lauren V. Fortington ◽  
Muhammad Akram ◽  
Bircan Erbas ◽  
Friedbert Kohler
Keyword(s):  
Incidence Rate ◽  
Geographic Variation ◽  
Lower Limb ◽  
Lower Limb Amputation ◽  
Limb Amputation

Mobility after lower-limb amputation

1996 ◽  
Vol 83 (1) ◽  
pp. 134-134 ◽  
Author(s):  
J. R. Kulkarni ◽  
C. Collin ◽  
J. Collin
Keyword(s):  
Lower Limb ◽  
Lower Limb Amputation ◽  
Limb Amputation

scholarly journals Rates and risk factors for amputation in people with diabetes in Japan: a historical cohort study using a nationwide claims database

2021 ◽  
Vol 14 (1) ◽  
Author(s):  
Masanori Kaneko ◽  
Kazuya Fujihara ◽  
Mayuko Yamada Harada ◽  
Taeko Osawa ◽  
Masahiko Yamamoto ◽  
...  
Keyword(s):  
Lower Limb ◽  
Cox Regression ◽  
Lower Limb Amputation ◽  
Limb Amputation ◽  
Historical Cohort ◽  
Cox Regression Analysis ◽  
Claims Database ◽  
Younger Age

Abstract Background The prevalence of diabetes is rising, and diabetes develops at a younger age in East Asia. Although lower limb amputation negatively affects quality of life and increases the risk of cardiovascular events, little is known about the rates and predictors of amputation among persons with diabetes from young adults to those in the “young-old” category (50–72 y). Methods We analyzed data from a nationwide claims database in Japan accumulated from 2008 to 2016 involving 17,288 people with diabetes aged 18–72 y (mean age 50.2 y, HbA1c 7.2%). Amputation occurrence was determined according to information from the claims database. Cox regression model identified variables related to lower limb amputation. Results The mean follow-up time was 5.3 years, during which time 16 amputations occurred (0.17/1000 person-years). Multivariate Cox regression analysis showed that age (hazard ratio [HR] 1.09 [95% confidence intervals] 1.02–1.16, p = 0.01) and HbA1c (HR 1.46 [1.17–1.81], p < 0.01) were independently associated with amputations. Compared with those aged < 60 years with HbA1c < 8.0%, the HR for amputation was 27.81 (6.54–118.23) in those aged ≥60 years and HbA1c ≥8.0%. Conclusions Age and HbA1c were associated with amputations among diabetic individuals, and the rates of amputation were significantly greater in those ≥60 years old and with HbA1c ≥8.0%.

Sign in / Sign up

Export Citation Format

Share Document