BACKGROUND: Cartilage therapy for focal articular lesions has been implemented for more than a decade, and it is becoming increasingly available. What is still lacking, however, is analysis of patient characteristics to help improve outcome or select patients for specific treatment. PURPOSE: To analyze the prognostic value of patient age and defect size, age, and location on clinical outcome 3 years after cartilage therapy. STUDY DESIGN: Cohort study; Level of evidence, 3. METHODS: Fifty-five patients (age, 35 +/- 9 years) were randomly selected from a prospective database. Each had a traumatic knee injury, each was treated for a focal cartilage lesion, and each was assessed with the Knee injury and Osteoarthritis Outcome Score (KOOS) 3 years after surgery. Patient characteristics (ie, patient age and defect size, age, and location) were tested for valid inclusion in the regression model. Multiple linear regression was used to determine which variables influenced clinical improvement. Binary KOOS scores were generated on the basis of age-matched healthy patients and assessed in a logistic regression analysis. RESULTS: Normality tests confirmed normal distribution for each variable (P < .05). Defect size did not influence clinical improvement (P > .05). Clinical outcome regarding the treatment of medial defects was better than that of the lateral defects (10.38-25.26 points for the different KOOS subscales; P < .05). The KOOS improvement from baseline was better for patients > or =30 years compared with patients > or =30 years (7.31-29.24 points for the different KOOS subscales; P < .05). Patients with defects <24 months were more likely to report the age-matched healthy reference KOOS (odds ratio, 1.8-4.0; P < .05). CONCLUSION: This study illustrates the influence of patient age and defect location and age on clinical outcome 3 years after treatment of a focal cartilage lesion in patients with a traumatic knee injury.
BACKGROUND: Cartilage therapy for focal articular lesions has been implemented for more than a decade, and it is becoming increasingly available. What is still lacking, however, is analysis of patient characteristics to help improve outcome or select patients for specific treatment. PURPOSE: To analyze the prognostic value of patient age and defect size, age, and location on clinical outcome 3 years after cartilage therapy. STUDY DESIGN: Cohort study; Level of evidence, 3. METHODS: Fifty-five patients (age, 35 +/- 9 years) were randomly selected from a prospective database. Each had a traumatic knee injury, each was treated for a focal cartilage lesion, and each was assessed with the Knee injury and Osteoarthritis Outcome Score (KOOS) 3 years after surgery. Patient characteristics (ie, patient age and defect size, age, and location) were tested for valid inclusion in the regression model. Multiple linear regression was used to determine which variables influenced clinical improvement. Binary KOOS scores were generated on the basis of age-matched healthy patients and assessed in a logistic regression analysis. RESULTS: Normality tests confirmed normal distribution for each variable (P < .05). Defect size did not influence clinical improvement (P > .05). Clinical outcome regarding the treatment of medial defects was better than that of the lateral defects (10.38-25.26 points for the different KOOS subscales; P < .05). The KOOS improvement from baseline was better for patients > or =30 years compared with patients > or =30 years (7.31-29.24 points for the different KOOS subscales; P < .05). Patients with defects <24 months were more likely to report the age-matched healthy reference KOOS (odds ratio, 1.8-4.0; P < .05). CONCLUSION: This study illustrates the influence of patient age and defect location and age on clinical outcome 3 years after treatment of a focal cartilage lesion in patients with a traumatic knee injury.
Authors: Peter Bollars; Marc Bosquet; Bruno Vandekerckhove; François Hardeman; Johan Bellemans Journal: Knee Surg Sports Traumatol Arthrosc Date: 2011-11-11 Impact factor: 4.342
Authors: A H Gomoll; G Filardo; L de Girolamo; J Espregueira-Mendes; J Esprequeira-Mendes; M Marcacci; W G Rodkey; J R Steadman; R J Steadman; S Zaffagnini; E Kon Journal: Knee Surg Sports Traumatol Arthrosc Date: 2011-11-24 Impact factor: 4.342
Authors: Jonathan C Riboh; Gregory L Cvetanovich; Brian J Cole; Adam B Yanke Journal: Knee Surg Sports Traumatol Arthrosc Date: 2016-09-07 Impact factor: 4.342