Citations

Abstract Therapy for polymyalgia rheumatica (PMR) varies widely in clinical practice as international recommendations for PMR treatment are not currently available. In this paper, we report the 2015 European League Against Rheumatism (EULAR)/American College of Rheumatology (ACR) recommendations for the management of PMR. We used the Grading of Recommendations, Assessment, Development and Evaluation (GRADE) methodology as a framework for the project. Accordingly, the direction and strength of the recommendations are based on the quality of evidence, the balance between desirable and undesirable effects, patients’ and clinicians’ values and preferences, and resource use. Eight overarching principles and nine specific recommendations were developed covering several aspects of PMR, including basic and follow‐up investigations of patients under treatment, risk factor assessment, medical access for patients and specialist referral, treatment strategies such as initial glucocorticoid (GC) doses and subsequent tapering regimens, use of intramuscular GCs and disease modifying anti‐rheumatic drugs (DMARDs), as well as the roles of non‐steroidal anti‐rheumatic drugs and non‐pharmacological interventions. These recommendations will inform primary, secondary and tertiary care physicians about an international consensus on the management of PMR. These recommendations should serve to inform clinicians about best practices in the care of patients with PMR.

AbstractRationale, aims and objectivesAchieving control over elevated lipid parameters, particularly low‐density lipoprotein (LDL)‐cholesterol, is an acknowledged quality indicator in primary care. The Centers for Disease Control and Prevention (CDC)'s model for investigation of outbreaks (person–place–time) can be applied to the analysis of quality indicators.MethodsA sample of 322 family medicine patients for whom lipid levels were ordered was extracted. LDL > 100 mg/dL was cross‐tabulated by personal characteristics [age group, gender, body mass index (BMI), diagnoses], month (time) and ordering department (place).ResultsAge (except one age category), gender, time and location were not related to LDL > 100 mg/dL after adjustment for covariates. All levels of BMI above normal elevated the risk of LDL > 100 mg/dL [BMI 25–29.9: odds ratio (OR) = 3.41, confidence interval (CI) = 1.61–7.23, P = 0.0014; BMI 30–34.9: OR = 2.93, CI = 1.28–6.70, P = 0.0109; BMI ≥ 35: OR = 2.75, CI = 1.19–6.37, P = 0.0181]. Patients with coronary artery disease (CAD) and diabetes mellitus (DM) were at reduced risk for LDL > 100 mg/dL (CAD: OR = 0.47, CI = 0.24–0.91, P = 0.0254; DM: OR = 0.28, CI = 0.14–0.55, P = 0.0002).ConclusionAn outbreak investigation model is useful for analysing variations in this quality indicator. Patients with higher BMI and those not diagnosed with CAD or DM type I/II may be considered for intensified lipid lowering using quality improvement efforts. These might include counselling for lifestyle changes or medication therapy depending upon their calculated cardiac risk.

AbstractRationale, aims and objectivesThis study was undertaken to assess the frequency of lipid screening in comparison with the United States Preventive Services Task Force guideline in a sample of family medicine patients. In addition, we sought to determine the association between testing frequency and achievement of lipid targets.MethodsA random sample was extracted from 271 patients from among all patients cared for in our Department of Family Medicine for whom lipid screening was ordered from March to September 2012 and who had ≥2 well‐defined cardiovascular risk factors. Lipid testing frequency was classified in three ways: semi‐annual or less often (0–12 tests over 6 years), annual or less often (0–6 tests), or biennial (0–3 tests).ResultsMultiple logistic regression analysis revealed that the predictors of lipid screening more often than semi‐annually were age ≥60 years [odds ratio (OR) = 3.7] and diabetes mellitus (DM) (OR = 30.6). Predictors of screening more often than annually were DM (OR = 4.3), hypertension (OR = 2.1), family history of premature coronary artery disease (OR = 5.6) and statin treatment (OR = 3.5). Lipid goal attainment was not associated with testing frequency except with regard to low‐density lipoprotein levels (P = 0.043, P < 0.001, P = 0.005, by semi‐annual, annual and biennial, respectively) and total cholesterol levels (P = 0.015, P = 0.025 by semi‐annual and annual, respectively).ConclusionsQuestionable high frequency of lipid testing was detected even when the more conservative approach of annual monitoring was assumed. Frequency of testing was not associated with goal attainment for most parameters. Physicians should request the lipid testing based on overall risk assessment and person variability in accordance with published guidelines.

Objective: To assess how physical limitations relate to self-rated health among family medicine patients after adjustment for severity of illness. Design: A telephone survey of family medicine patients, linked with medical record information. Setting: A large family medicine department in Rochester, Minnesota, USA. Subjects: Self-ratings of health were linked to medical records for 804 adult patients. Results: Adjusting for severity and other confounders using multiple logistic regression analysis revealed that having physical limitations was inversely and independently related to good self-rated health (adjusted odds ratio = 0.20, P<0.001). Odds ratios also were lower for high severity of illness (adjusted odds = 0.43). Morbidly obese patients and patients older than 65 years of age also had reduced odds of good self-rated health. Conclusions: In our sample of family medicine patients, part of the disparity in health status experienced by people with physical limitations is attributable to greater severity of illness, age and obesity.