Singh, Jasvinder A.

ObjectiveTo develop updated guidelines for the perioperative management of disease‐modifying medications for patients with rheumatic diseases, specifically those with inflammatory arthritis (IA) and those with systemic lupus erythematosus (SLE), undergoing elective total hip arthroplasty (THA) or elective total knee arthroplasty (TKA).MethodsWe convened a panel of rheumatologists, orthopedic surgeons, and infectious disease specialists, updated the systematic literature review, and included currently available medications for the clinically relevant population, intervention, comparator, and outcomes (PICO) questions. We used the Grading of Recommendations Assessment, Development and Evaluation (GRADE) methodology to rate the quality of evidence and the strength of recommendations using a group consensus process.ResultsThis guideline updates the 2017 recommendations for perioperative use of disease‐modifying antirheumatic therapy, including traditional disease‐modifying antirheumatic drugs, biologic agents, targeted synthetic small‐molecule drugs, and glucocorticoids used for adults with rheumatic diseases, specifically for the treatment of patients with IA, including rheumatoid arthritis and spondyloarthritis, those with juvenile idiopathic arthritis, or those with SLE who are undergoing elective THA or TKA. It updates recommendations regarding when to continue, when to withhold, and when to restart these medications and the optimal perioperative dosing of glucocorticoids.ConclusionThis updated guideline includes recently introduced immunosuppressive medications to help decision‐making by clinicians and patients regarding perioperative disease‐modifying medication management for patients with IA and SLE at the time of elective THA or TKA.

Background Past research in population health trends has shown that injuries form a substantial burden of population health loss. Regular updates to injury burden assessments are critical. We report Global Burden of Disease (GBD) 2017 Study estimates on morbidity and mortality for all injuries. Methods We reviewed results for injuries from the GBD 2017 study. GBD 2017 measured injury-specific mortality and years of life lost (YLLs) using the Cause of Death Ensemble model. To measure non-fatal injuries, GBD 2017 modelled injury-specific incidence and converted this to prevalence and years lived with disability (YLDs). YLLs and YLDs were summed to calculate disability-adjusted life years (DALYs). Findings In 1990, there were 4 260 493 (4 085 700 to 4 396 138) injury deaths, which increased to 4 484 722 (4 332 010 to 4 585 554) deaths in 2017, while age-standardised mortality decreased from 1079 (1073 to 1086) to 738 (730 to 745) per 100 000. In 1990, there were 354 064 302 (95% uncertainty interval: 338 174 876 to 371 610 802) new cases of injury globally, which increased to 520 710 288 (493 430 247 to 547 988 635) new cases in 2017. During this time, age-standardised incidence decreased non-significantly from 6824 (6534 to 7147) to 6763 (6412 to 7118) per 100 000. Between 1990 and 2017, age-standardised DALYs decreased from 4947 (4655 to 5233) per 100 000 to 3267 (3058 to 3505). Interpretation Injuries are an important cause of health loss globally, though mortality has declined between 1990 and 2017. Future research in injury burden should focus on prevention in high-burden populations, improving data collection and ensuring access to medical care.

Background The epidemiological transition of non-communicable diseases replacing infectious diseases as the main contributors to disease burden has been well documented in global health literature. Less focus, however, has been given to the relationship between sociodemographic changes and injury. The aim of this study was to examine the association between disability-adjusted life years (DALYs) from injury for 195 countries and territories at different levels along the development spectrum between 1990 and 2017 based on the Global Burden of Disease (GBD) 2017 estimates. Methods Injury mortality was estimated using the GBD mortality database, corrections for garbage coding and CODEm—the cause of death ensemble modelling tool. Morbidity estimation was based on surveys and inpatient and outpatient data sets for 30 cause-of-injury with 47 nature-of-injury categories each. The Socio-demographic Index (SDI) is a composite indicator that includes lagged income per capita, average educational attainment over age 15 years and total fertility rate. Results For many causes of injury, age-standardised DALY rates declined with increasing SDI, although road injury, interpersonal violence and self-harm did not follow this pattern. Particularly for self-harm opposing patterns were observed in regions with similar SDI levels. For road injuries, this effect was less pronounced. Conclusions The overall global pattern is that of declining injury burden with increasing SDI. However, not all injuries follow this pattern, which suggests multiple underlying mechanisms influencing injury DALYs. There is a need for a detailed understanding of these patterns to help to inform national and global efforts to address injury-related health outcomes across the development spectrum.

ObjectiveThe Outcome Measures in Rheumatology (OMERACT) 3×3 method analyzes the occurrence of benefit and harm simultaneously at the individual patient level. We applied this method to 2 recent rheumatoid arthritis (RA) trial data sets.MethodsThe Treatment of Early Aggressive Rheumatoid Arthritis (TEAR) and the Rheumatoid Arthritis Comparison of Active Therapies (RACAT) randomized trial outcomes for safety were defined according to OMERACT as having no adverse events (AEs), non‐serious AEs, and serious AEs. Treatment efficacy was defined as good, moderate, or no response. A good treatment response without any AEs was labeled an unqualified success, and no treatment response but at least 1 AE was considered an unmitigated failure. The association between benefit and harm was assessed by chi‐square or exact tests, as appropriate.ResultsIn TEAR, 612 of 755 patients had response data at 48 weeks: 14% of patients experienced unqualified success and 9% had unmitigated failure, with no difference between the treatment arms. Treatment response and AE rates were not correlated. In RACAT, 309 of 353 patients had response data at 48 weeks: 6% of patients experienced unqualified success and 11% had unmitigated failure, with no differences between the treatment arms. Response and AE rates were negatively correlated. The frequency of AEs and serious AEs increased as response decreased (P = 0.008).ConclusionWe found some evidence that clinical response may be reduced by the co‐occurrence of AEs.