Abstract
Partial meniscectomy patients have a greater likelihood for the development of early osteoarthritis (OA). To prevent the onset of early OA, patient-specific treatment algorithms need to be created that predict patient risk to early OA after meniscectomy. The aim of this work was to identify patient-specific risk factors in partial meniscectomy patients that could potentially lead to early OA.
Partial meniscectomy patients operated between 01/2017 and 12/2019 were evaluated in the study (n=317). Exclusion criteria were other pathologies or surgeries for the evaluated knee and meniscus (n = 114). Following informed consent, an online questionnaire containing demographics and the “Knee Injury and Osteoarthritis Outcome Score” (KOOS) questionnaire was sent to the patient. Based on the KOOS pain score, patients were classified into “low” (> 75) and “high” (< 75) risk patients, indicating risk to symptomatic OA. The “high risk” patients also underwent a follow-up including an MRI scan to understand whether they have developed early OA.
From 203 participants, 96 patients responded to the questionnaire (116 did not respond) with 61 patients considered “low-risk” and 35 “high-risk” patients. Groups that showed a significant increased risk for OA were patients aged > 40 years, females, overweight (BMI >25 kg/m2 ≤ 30 kg/m2), and smokers (*p < 0.05). The “high-risk”-follow-up revealed a progression of early osteoarthritic cartilage changes in seven patients, with the remaining nineteen patients showing no changes in cartilage status or pain since time of operation. Additionally, eighteen patients in the high-risk group showed a varus or valgus axis deviation.
Patient-specific factors for worse postoperative outcomes after partial meniscectomy and indicators for an “early OA” development were identified, providing the basis for a patient-specific treatment approach. Further analysis in a multicentre study and computational analysis of MRI scans is ongoing to develop a patient-specific treatment algorithm for meniscectomy patients.
