Detecting meniscal tears in primary care

Research output: PhD ThesisPhd-Thesis - Research and graduation internal

Abstract

Although meniscal tears are a very common phenomenon uncertainty exists about the diagnosis and treatment of meniscal tears in primary care. This thesis aims to provide evidence for general practitioners and physical therapists regarding the diagnosis and management of patients with a suspected meniscal tear, to reduce the uncertainty about the diagnosis and to improve successful management of meniscal tears in primary care.
The management of suspected meniscal tears in primary care differs substantially between general practitioners, with large variation between conservative treatment and referral to secondary care. Diagnostic strategies are needed to improve patient selection for MRI. We identified risk factors for meniscal tears which, when combined with diagnostic meniscal tests, aid in establishing a correct diagnosis. Two weight-bearing meniscal tests and one non-weight-bearing test were investigated for interexaminer agreement and accuracy. We conclude that diagnostic meniscal tests on their own are not sufficient to detect meniscal tears in primary care. We combined patient variables, risk factors, and one diagnostic test to develop a clinical prediction model. We externally validated the clinical prediction model, and updated the model based on the combination of two samples. We conclude that this clinical prediction model is a first step to improve the detection of meniscal tears in primary care, leading to an informed selection for magnetic resonance imaging referral. Finally, a systematic review was conducted to compare the effectiveness of exercise therapy for meniscal tears to that of arthroscopic partial meniscectomy and meniscal repair and found no difference in short-term and long-term consequences. We concluded that for patients with degenerative meniscal tears clinicians must opt for exercise therapy over surgery.
Original languageEnglish
QualificationDoctor of Philosophy
Awarding Institution
Supervisors/Advisors
  • Zwinderman, Koos, Supervisor
  • Lucas, C., Supervisor
  • Lindeboom, Robert, Co-supervisor
Award date12 Dec 2017
Publication statusPublished - 2017

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