Interventions for the prediction and management of chronic XXXX after total knee replacement: systematic review of randomised controlled trials.

@entity1 @entity1118 @entity158
OBJECTIVES: Total knee replacement can be a successful operation for @entity158 relief. However, 10-34% of @entity1 experience chronic @entity158 . Our aim was to synthesise evidence on the effectiveness of applying predictive models to guide preventive treatment, and for interventions in the management of @entity1118 after total knee replacement. SETTING: We conducted a systematic review of randomised controlled trials using appropriate search strategies in the Cochrane Library, MEDLINE and EMBASE from inception to October 2014. No language restrictions were applied. @entity1 : Adult @entity1 receiving total knee replacement. INTERVENTIONS: Predictive models to guide treatment for prevention of @entity1118 . Interventions for management of @entity1118 . PRIMARY AND SECONDARY OUTCOME MEASURES: Reporting of specific outcomes was not an eligibility criterion but we sought outcomes relating to @entity158 severity. RESULTS: No studies evaluated the effectiveness of predictive models in guiding treatment and improving outcomes after total knee replacement. One study evaluated an intervention for the management of @entity1118 . The trial evaluated the use of a botulinum toxin A injection with antinociceptive and anticholinergic activity in 49 @entity1 with chronic @entity158 after knee replacement. A single injection provided meaningful @entity158 relief for about 40   days and the authors acknowledged the need for a large trial with repeated injections. No trials of multidisciplinary interventions or individualised treatments were identified. CONCLUSIONS: Our systematic review highlights a lack of evidence about the effectiveness of prediction and management strategies for chronic @entity158 after total knee replacement. As a large number of @entity1 are affected by @entity1118 after total knee replacement, development of an evidence base about care for these @entity1 should be a research priority.
