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Objectives. To study the effects of several survey features on response rates in a general population health survey. Methods. In 2012 and 2013, 8000 households in British Columbia, Canada, were randomly allocated to 1 of 7 survey variants, each containing a different combination of survey features. Features compared included administration modes (paper vs online), prepaid incentive ($2 coin vs none), lottery incentive (instant vs end-of-study), questionnaire length (10 minutes vs 30 minutes), and sampling frame (InfoCanada vs Canada Post). Results. The overall response rate across the 7 groups was 27.9% (range = 17.1–43.4). All survey features except the sampling frame were associated with statistically significant differences in response rates. The survey mode elicited the largest effect on the odds of response (odds ratio [OR] = 2.04; 95% confidence interval [CI] = 1.61, 2.59), whereas the sampling frame showed the least effect (OR = 1.14; 95% CI = 0.98, 1.34). The highest response was achieved by mailing a short paper survey with a prepaid incentive. Conclusions. In a mailed general population health survey in Canada, a 40% to 50% response rate can be expected. Questionnaire administration mode, survey length, and type of incentive affect response rates.

To review the reliability and validity of the CAGE questionnaire across different patient populations and discuss its role in the detection of alcohol-related problems. The Cochrane Database for Systematic Reviews, Medline, Embase, and Psychinfo were searched. No systematic reviews were found on the Cochrane Database. Search of the other databases yielded one systematic review and one meta-analysis, on different aspects of CAGE. Three articles on reliability and 16 on validity of CAGE were found and used. Studies generally yielded Level II evidence. CAGE has demonstrated high test-retest reliability (0.80-0.95), and adequate correlations (0.48-0.70) with other screening instruments. The questionnaire is a valid tool for detecting alcohol abuse and dependence in medical and surgical inpatients, ambulatory medical patients, and psychiatric inpatients (average sensitivity 0.71, specificity 0.90). Its performance in primary care patients has been varied, while it has not performed well in white women, prenatal women, and college students. Furthermore, it is not an appropriate screening test for less severe forms of drinking. CAGE is short, feasible to use, and easily applied in clinical practice. However, users should be aware of its limitations when interpreting the results. A positive screen should be followed by a proper diagnostic evaluation using standard clinical criteria.

Background The use of tramadol among osteoarthritis (OA) patients has been increasing rapidly around the world, but population-based studies on its safety profile among OA patients are scarce. We sought to determine if tramadol use in OA patients is associated with increased risks of all-cause mortality, cardiovascular diseases (CVD), venous thromboembolism (VTE), and hip fractures compared with commonly prescribed nonsteroidal anti-inflammatory drugs (NSAIDs) or codeine. Methods Using administrative health datasets from British Columbia, Canada, we conducted a sequential propensity score-matched cohort study among all OA patients between 2005 and 2013. The tramadol cohort (i.e., tramadol initiation) was matched with four comparator cohorts (i.e., initiation of naproxen, diclofenac, cyclooxygenase-2 [Cox-2] inhibitors, or codeine). Outcomes are all-cause mortality, first-ever CVD, VTE, and hip fractures within the year after the treatment initiation. Patients were followed until they either experienced an event, left the province, or the 1-year follow-up period ended, whichever occurred first. Cox proportional hazard models were used to estimate hazard ratios after adjusting for competing risk of death. Results Overall, 100,358 OA patients were included (mean age: 68 years, 63% females). All-cause mortality was higher for tramadol compared to NSAIDs with rate differences (RDs/1000 person-years, 95% CI) ranging from 3.3 (0.0–6.7) to 8.1 (4.9–11.4) and hazard ratios (HRs, 95% CI) ranging from 1.2 (1.0–1.4) to 1.5 (1.3–1.8). For CVD, no differences were observed between tramadol and NSAIDs. Tramadol had a higher risk of VTE compared to diclofenac, with RD/1000 person-years (95% CI) of 2.2 (0.7–3.7) and HR (95% CI) of 1.7 (1.3–2.2). Tramadol also had a higher risk of hip fractures compared to diclofenac and Cox-2 inhibitors with RDs/1000 person-years (95% CI) of 1.9 (0.4–3.4) and 1.7 (0.2–3.3), respectively, and HRs (95% CI) of 1.6 (1.2–2.0) and 1.4 (1.1–1.9), respectively. No differences were observed between tramadol and NSAIDs for all events. Conclusions OA patients initiating tramadol have an increased risk of mortality, VTE, and hip fractures within 1 year compared with commonly prescribed NSAIDs, but not with codeine.

To develop a whole-joint, unidimensional, irreversible, and fine-grained MRI knee osteoarthritis (OA) severity score, based on cartilage, osteophytes and meniscus (OA-COM), and to predict progression across different severity states using OA-COM as outcome and clinical variables as predictors. Optimal OA-COM thresholds were 12, 18, 24 and 30, for KL grades 1 to 4. Significant predictors of progression (depending on threshold) included physical exam effusion, malalignment and female sex, with other selected predictors age, BMI and crepitus. OA-COM (0-54 range) is a whole-joint, unidimensional, irreversible, and fine-grained MRI OA severity score reflecting cartilage, osteophytes and menisci. OA-COM scores 12, 18, 24 and 30 are equivalent to KL grades 1 to 4, while offering fine-grained differentiation of states between KL grades, and within pre-radiographic disease (KL = 0) or late-stage disease (KL = 4). In modeling, several clinical variables predicted progression across different states over 7 years.

The purpose of this study was to compare three strategies for reducing population health burden of osteoarthritis (OA): improved pharmacological treatment of OA-related pain, improved access to joint replacement surgery, and prevention of OA by reducing obesity and overweight. We applied a validated computer microsimulation model of OA in Canada. The model simulated a Canadian-representative open population aged 20 years and older. Variables in the model included demographics, body mass index, OA diagnosis, OA treatment, mortality, and health-related quality of life. Model parameters were derived from analyses of national surveys, population-based administrative data, a hospital-based cohort study, and the literature. We compared 8 what-if intervention scenarios in terms of disability-adjusted life years (DALYs) relative to base-case, over a wide range of time horizons. Reductions in DALYs depended on the type of intervention, magnitude of the intervention, and the time horizon. Medical interventions (a targeted increase in the use of painkillers) tended to produce effects quickly and were, therefore, most effective over a short time horizon (a decade). Surgical interventions (increased access to joint replacement) were most effective over a medium time horizon (two decades or longer). Preventive interventions required a substantial change in BMI to generate a significant impact, but produced more reduction in DALYs than treatment strategies over a very long time horizon (several decades). In this population-based modeling study we assessed the potential impact of three different burden reduction strategies in OA. Data generated by our model may help inform the implementation of strategies to reduce the burden of OA in Canada and elsewhere.

To determine associations between features of osteoarthritis (OA) on MRI and knee pain severity and knee pain progression. Baseline, 3.3- and 7.5-year assessments were performed for 122 subjects with baseline knee pain (age 40-79), sample-weighted for population (with knee pain) representativeness. MRIs were scored for: osteophytes (0:absent to 3:large); cartilage (0:normal to 4:full thickness defect; 0/1 collapsed); subchondral sclerosis (0:none to 3:>50% of site), subchondral cyst (0:absent to 3:severe), bone marrow lesions (0:none to 3:≥50% of site); and meniscus (0:normal to 3:maceration/resection), in 6-8 regions each. Per feature, scores were averaged across regions. Effusion/synovitis (0:absent to 3:severe) was analyzed as ≥2 vs. <2. Linear models predicted WOMAC knee pain severity (0-100), and binary models predicted 10+ (minimum perceptible clinical improvement [MPCI]) and 20+ (minimum clinically important difference [MCID]) increases. Models were adjusted for age, sex, BMI (and follow-up time for longitudinal models). Pain severity was associated with osteophytes (7.17 per unit average; 95% CI = 3.19, 11.15) and subchondral sclerosis (11.03; 0.68, 21.39). MPCI-based pain increase was associated with osteophytes (odds ratio per unit average 3.20; 1.36, 7.55), subchondral sclerosis (5.69; 1.06, 30.44), meniscal damage (1.68; 1.08, 2.61) and effusion/synovitis ≥2 (2.25; 1.07, 4.71). MCID-based pain increase was associated with osteophytes (3.79; 1.41, 10.20) and cartilage defects (2.42; 1.24, 4.74). Of the features investigated, only osteophytes were consistently associated with pain cross-sectionally and longitudinally in all models. This suggests an important role of bone in early knee osteoarthritis.

Objective To identify magnetic resonance imaging (MRI) predictors (cartilage [C], osteophytes [O] and meniscus [M] scores) of prevalent and 3-year incident medial tibiofemoral (MTF) and lateral tibiofemoral (LTF) knee joint tenderness and patellofemoral (PF) grind.  Methods Population-based knee pain cohort aged 40–79 was assessed at baseline ( N  = 255), 3- and 7-year follow-up ( N  = 108 × 2 = 216). COM scores were measured at 6/8/6 subregions respectively. Age-sex-BMI adjusted logistic models predicted prevalence versus relevant COM predictors (medial, lateral or patellar / trochlear groove scores). Fully adjusted models also included all relevant COM predictors. Binary generalized estimating equations models predicting 3-year incidence were also adjusted for individual follow-up time between cycles. Results Significant predictors of prevalent MTF tenderness: medial femoral cartilage (fully adjusted odds ratio [aOR] 1.84; 95% confidence interval [CI] 1.11, 3.05), female (aOR = 3.05; 1.67, 5.58), BMI (aOR = 1.53 per 5 units BMI; 1.10, 2.11). Predictors of prevalent LTF tenderness: female (aOR = 2.18; 1.22, 3.90). There were no predictors of prevalent PF grind in the fully adjusted model. However, medial patellar osteophytes was predictive in the age-sex-BMI adjusted model. There were no predictors of 3-year incident MTF tenderness. Predictors of 3-year incident LTF tenderness: female (aOR = 3.83; 1.25, 11.77). Predictors of 3-year incident PF grind: lateral patellar osteophytes (aOR = 4.82; 1.69, 13.77). In the age-sex-BMI adjusted model, patellar cartilage was also a predictor. Conclusion We explored potential MRI predictors of prevalent and 3-year incident MTF/LTF knee joint tenderness and PF grind. These findings could guide preemptive strategies aimed at reducing these symptoms in the present and future (3-year incidence).

Two-phase noble liquid detectors, with large target masses and effective background reduction, are currently leading the dark matter direct detection for WIMP masses above a few GeV. Due to their sensitivity to single ionized electron signals, these detectors were shown to also have strong constraints for sub-GeV dark matter via their scattering on electrons. In fact, the most stringent direct detection constraints for sub-GeV dark matter down to as low as 5 MeV come from noble liquid detectors, namely XENON10, DarkSide-50, XENON100 and XENON1T, although these experiments still suffer from high background at single or a few electron level. LBECA is a planned 100-kg scale liquid xenon detector with significant reduction of the single and a few electron background. The experiment will improve the sensitivity to sub-GeV dark matter by three orders of magnitude compared to the current best constraints.

Background Men with gout have been found to have an increased risk of acute myocardial infarction (AMI), but no corresponding data are available among women. Objective To evaluate the potential independent association between gout and the risk of AMI among elderly women, aged ≥65 years. Methods A population-based cohort study was conducted using the British Columbia Linked Health Database and compared incidence rates of AMI between 9642 gout patients and 48 210 controls, with no history of ischaemic heart disease. Cox proportional hazards models stratified by gender were used to estimate the relative risk (RR) for AMI, adjusting for age, comorbidities and prescription drug use. Results Over a 7-year median follow-up, 3268 incident AMI cases, were identified, 996 among women. Compared with women without gout, the multivariate RRs among women with gout were 1.39 (95% CI 1.20 to 1.61) for all AMI and 1.41 (95% CI 1.19 to 1.67) for non-fatal AMI. These RRs were significantly larger than those among men (multivariate RRs for all AMI and non-fatal AMI, 1.11 and 1.11; p values for interaction, 0.003 and 0.005, respectively). Conclusion These population-based data suggest that women with gout have an increased risk for AMI and the magnitude of excess risk is higher than in men.

ObjectiveThis modelling study aimed to estimate the comorbidity burden for four common non-communicable diseases with ischaemic heart diseases (IHD) in Iran during a period of 28 years.DesignAnalysis of the burden of comorbidity with IHD based on data included prevalence rates and the disability weight (DW) average for calculating years lived with disability (YLDs) from the Iran population based on the Global Burden of Disease (GBD) study.SettingPopulation-based available data in GBD 2017 study of Iran population.ParticipantThe source of data was the GBD 2017 Study. We evaluated IHD, major depressive disorder (MDD), diabetes mellitus (DM), ischaemic stroke (IS), and osteoarthritis (OA) age-standardised prevalence rates and their DW.Main outcome measuresA new formula that modified the GBD calculator was used to measure the comorbidity YLDs. In the new formula, some multipliers were considered, measuring the departure from independence.ResultThe contribution of total comorbidity for each combination of IHD with DM, MDD, IS and OA was 2.5%, 2.0%, 1.6% and 2.9%, respectively. The highest YLD rates were observed for IHD_MDD, 16.5 in 1990 and 17.0 in 2017. This was followed by IHD_DM, from 11.5 to 16.9 per 100 000. The YLD rates for IHD_OA changed slightly (6.5–6.7) per 100 000, whereas there was a gradual reduction in the trends of IHD-IS, from 4.0–4.5 per 100 000.ConclusionOf the four comorbidities studied, the highest burden was due to the coexistence of MDD with IHD. Our results highlight the importance of addressing the burden of comorbidities when studying the burden of IHD or any other non-communicable disease.