title: Analysis of three different equations for predicting quadriceps femoris muscle strength in patients with COPD.
abstract: OBJECTIVE
  To compare equations for predicting peak quadriceps femoris (QF) muscle force; to determine the agreement among the equations in identifying QF muscle weakness in COPD patients; and to assess the differences in characteristics among the groups of patients classified as having or not having QF muscle weakness by each equation.
  
  
  METHODS
  Fifty-six COPD patients underwent assessment of peak QF muscle force by dynamometry (maximal voluntary isometric contraction of knee extension). Predicted values were calculated with three equations: an age-height-weight-gender equation (Eq-AHWG); an age-weight-gender equation (Eq-AWG); and an age-fat-free mass-gender equation (Eq-AFFMG).
  
  
  RESULTS
  Comparison of the percentage of predicted values obtained with the three equations showed that the Eq-AHWG gave higher values than did the Eq-AWG and Eq-AFFMG, with no difference between the last two. The Eq-AHWG showed moderate agreement with the Eq-AWG and Eq-AFFMG, whereas the last two also showed moderate, albeit lower, agreement with each other. In the sample as a whole, QF muscle weakness (< 80% of predicted) was identified by the Eq-AHWG, Eq-AWG, and Eq-AFFMG in 59%, 68%, and 70% of the patients, respectively (p > 0.05). Age, fat-free mass, and body mass index are characteristics that differentiate between patients with and without QF muscle weakness.
  
  
  CONCLUSIONS
  The three equations were statistically equivalent in classifying COPD patients as having or not having QF muscle weakness. However, the Eq-AHWG gave higher peak force values than did the Eq-AWG and the Eq-AFFMG, as well as showing greater agreement with the other equations.
authors.affiliation: Departamento de Fisioterapia, Universidade Estadual de Londrina, Londrina, PR, BR.
authors.forename: Aline Gonçalves
authors.initials: AG
authors.lastname: Nellessen
authors.affiliation: Departamento de Fisioterapia, Universidade Estadual de Londrina, Londrina, PR, BR.
authors.forename: Leila
authors.initials: L
authors.lastname: Donária
authors.affiliation: Departamento de Fisioterapia, Universidade Estadual de Londrina, Londrina, PR, BR.
authors.forename: Nidia Aparecida
authors.initials: NA
authors.lastname: Hernandes
authors.affiliation: Departamento de Fisioterapia, Universidade Estadual de Londrina, Londrina, PR, BR.
authors.forename: Fabio
authors.initials: F
authors.lastname: Pitta
mesh_terms: D050154:Adiposity; D000367:Age Factors; D000368:Aged; D000465:Algorithms; D001827:Body Height; D015992:Body Mass Index; D001835:Body Weight; D003430:Cross-Sectional Studies; D005260:Female; D006301:Health Services Needs and Demand; D006801:Humans; D007537:Isometric Contraction / Q000502:physiology; D007717:Knee / Q000503:physiopathology; D008297:Male; D008875:Middle Aged; D053580:Muscle Strength / Q000502:physiology*; D053581:Muscle Strength Dynamometer / Q000639:trends; D018908:Muscle Weakness / Q000175:diagnosis*; D011237:Predictive Value of Tests; D029424:Pulmonary Disease, Chronic Obstructive / Q000503:physiopathology*; D052097:Quadriceps Muscle / Q000503:physiopathology*; D012129:Respiratory Function Tests; D012737:Sex Factors