Objective. To determine the 5-year outcome of treatment for meniscal tear in osteoarthritis. Methods. We examined 5-year follow-up data from the Meniscal Tear in Osteoarthritis Research trial (METEOR) of physical therapy versus arthroscopic partial meniscectomy. We performed primary intent-to-treat (ITT) and secondary as-treated analyses. The primary outcome measure was the Knee Injury and Osteoarthritis Outcome Score (KOOS) pain scale; total knee replacement (TKR) was a secondary outcome measure. We used piecewise linear mixed models to describe change in KOOS pain. We calculated 5-year cumulative TKR incidence and used a Cox model to estimate hazard ratios (HRs) for TKR, with 95% confidence intervals (95% CIs).Results. Three hundred fifty-one participants were randomized. In the ITT analysis, the KOOS pain scores were ~46 (scale of 0 [no pain] to 100 [most pain]) at baseline in both groups. Pain scores improved substantially in both groups over the first 3 months, continued to improve through the next 24 months (to ~18 in each group), and were stable at 24-60 months. Results of the as-treated analyses of the KOOS pain score were similar. Twenty-five participants (7.1% [95% CI 4.4-9.8%]) underwent TKR over 5 years. In the ITT model, the HR for TKR was 2.0 (95% CI 0.8-4.9) for subjects randomized to the arthroscopic partial meniscectomy group, compared to those randomized to the physical therapy group. In the as-treated analysis, the HR for TKR was 4.9 (95% CI 1.1-20.9) for subjects ultimately treated with arthroscopic partial meniscectomy, compared to those treated nonoperatively.Conclusion. Pain improved considerably in both groups over 60 months. While ITT analysis revealed no statistically significant differences following TKR, greater frequency of TKR in those undergoing arthroscopic partial meniscectomy merits further study.

BackgroundAdministrative health care data are frequently used to study disease burden and treatment outcomes in many conditions including osteoarthritis (OA). OA is a chronic condition with significant disease burden affecting over 27 million adults in the US. There are few studies examining the performance of administrative data algorithms to diagnose OA. The purpose of this study is to perform a systematic review of administrative data algorithms for OA diagnosis; and, to evaluate the diagnostic characteristics of algorithms based on restrictiveness and reference standards.MethodsTwo reviewers independently screened English-language articles published in Medline, Embase, PubMed, and Cochrane databases that used administrative data to identify OA cases. Each algorithm was classified as restrictive or less restrictive based on number and type of administrative codes required to satisfy the case definition. We recorded sensitivity and specificity of algorithms and calculated positive likelihood ratio (LR+) and positive predictive value (PPV) based on assumed OA prevalence of 0.1, 0.25, and 0.50.ResultsThe search identified 7 studies that used 13 algorithms. Of these 13 algorithms, 5 were classified as restrictive and 8 as less restrictive. Restrictive algorithms had lower median sensitivity and higher median specificity compared to less restrictive algorithms when reference standards were self-report and American college of Rheumatology (ACR) criteria. The algorithms compared to reference standard of physician diagnosis had higher sensitivity and specificity than those compared to self-reported diagnosis or ACR criteria.ConclusionsRestrictive algorithms are more specific for OA diagnosis and can be used to identify cases when false positives have higher costs e.g. interventional studies. Less restrictive algorithms are more sensitive and suited for studies that attempt to identify all cases e.g. screening programs.Electronic supplementary materialThe online version of this article (doi:10.1186/s12911-016-0319-y) contains supplementary material, which is available to authorized users.

ObjectiveWe conducted a meta-analysis and systematic review of published randomized controlled trials (RCTs) to evaluate the impact of financial incentives (FI) on objectively-measured physical activity (PA) and weight loss (WL) in adults with sedentary behavior or chronic health conditions.Evidence reviewWe performed a systematic search for RCTs published in English indexed in PubMed, Embase, or Web of Science through July 27, 2017. We limited our search to RCTs that involved an FI intervention with a monetary component, objectively-measured PA or WL outcomes, samples with either sedentary lifestyles or chronic health conditions, and a comparator group that did not receive performance-contingent FI. We calculated the mean difference and standardized mean difference (SMD) for each study and used a random effects model to summarize intervention efficacy. We used the Jadad scoring tool to assess the quality of the identified articles.ResultsWe abstracted data from 11 RCTs. Two of the 11 included studies focused on PA, totaling 126 intervention and 116 control subjects. Nine RCTs evaluated the effect of FI on WL, totaling 1,799 intervention and 1,483 control subjects. The combined estimate for change in daily steps was 940 (95%CI [306–1,574]) more in PA intervention groups than in control groups and 2.36 (95%CI [1.80–2.93]) more kilograms lost by WL intervention groups compared to control groups. The overall estimated SMD for both outcomes combined was 0.395 (95%CI [0.243–0.546; p<0.001]), favoring FI interventions.ConclusionFI interventions are efficacious in increasing PA and WL in adults with chronic conditions or sedentary adults. Public health programs to increase PA or prevent chronic disease should consider incorporating FI to improve outcomes.

Objective: We performed a systematic meta-analysis of safe patient handling and mobilization (SPHM) program evaluations. Methods: Systematic literature review identified published SPHM program evaluations. Injury Rate Ratios (IRR), pre- to post-intervention, were used to estimate intervention effects and to examine the influence of patient care level, program components, and follow-up time using meta-regression. Results: 27 articles reported evaluations from 44 sites. Combined effect estimate for all SPHM programs was 0.44 (95% CI 0.36, 0.54), reflecting substantial injury reductions after program implementation. While specific program components were not associated with greater effectiveness, longer follow-up duration was associated with greater injury rate reduction (p=0.01) and intervention effects varied by level of care (p=0.01), with the greatest effect in intensive care unit interventions (IRR 0.14; 95% CI 0.07, 0.30). Conclusions: SPHM programs appear to be highly effective in reducing injuries. More research is needed to identify the most effective interventions for different patient care levels.