title: Predicting prosthetic use in elderly patients after major lower limb amputation.
abstract: BACKGROUND
  The main determinants of prosthetic use known from literature apply to the younger patient with lower limb amputation. Studies aimed at identifying determinants of outcome of lower limb amputation in elderly patients with multimorbidity that rehabilitate in skilled nursing facilities (SNFs) are scarce.
  
  
  OBJECTIVE
  To predict prosthetic use and physical mobility in geriatric patients admitted to SNFs for rehabilitation after lower limb amputation and the impact of multimorbidity.
  
  
  METHODS
  Prospective design.
  
  
  METHODS
  Univariate and multivariate logistic and linear regression analyses were used to identify determinants that were independently related to prosthetic use and the timed-up-and-go test (TUG test).
  
  
  RESULTS
  Of 55 eligible patients, 38 had complete assessments on admission and at discharge. Fifty per cent was provided with a prosthesis. Multimorbidity was present in 53% of the patients. Being able to ambulate independently, and having a transtibial amputation (rather than a higher level of amputation), without phantom pain determined prosthetic use (R(2)=56%), while cognitive abilities, low amputation level, and pre-operative functional abilities were independently associated with the TUG test (R(2)=82%).
  
  
  CONCLUSIONS
  Elderly patients referred to an SNF for prosthetic training have a high probability of using a prosthesis when having an independent ambulation after transtibial amputation, without phantom pain. These patients should be considered for prosthetic training.
authors.affiliation: Department of Primary and Community Care, Centre for Family Medicine, Geriatric Care and Public Health, Radboud University Nijmegen, Medical Centre, the Netherlands. m.spruit-vaneijk@elg.umcn.nl
authors.forename: Monica Spruit-
authors.initials: MS
authors.lastname: van Eijk
authors.forename: Harmen
authors.initials: H
authors.lastname: van der Linde
authors.forename: Bianca
authors.initials: B
authors.lastname: Buijck
authors.forename: Alexander
authors.initials: A
authors.lastname: Geurts
authors.forename: Sytse
authors.initials: S
authors.lastname: Zuidema
authors.forename: Raymond
authors.initials: R
authors.lastname: Koopmans
mesh_terms: D000368:Aged; D000369:Aged, 80 and over; D000674:Amputees / Q000523:psychology / Q000534:rehabilitation*; D001186:Artificial Limbs / Q000706:statistics & numerical data*; D003071:Cognition; D005260:Female; D006299:Health Services for the Aged / Q000706:statistics & numerical data*; D006801:Humans; D015994:Incidence; D016014:Linear Models; D016015:Logistic Models; D035002:Lower Extremity / Q000601:surgery*; D008297:Male; D015233:Models, Statistical; D010591:Phantom Limb / Q000453:epidemiology; D011446:Prospective Studies; D012866:Skilled Nursing Facilities / Q000706:statistics & numerical data*; D013977:Tibia / Q000601:surgery