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Regular internet access is suggested to facilitate Comprehensive Correct HIV/AIDS Knowledge (CCAK). We assessed this association using the 2018 Nigeria Demographic Health Survey data, including 30,...

Background Hepatitis C virus (HCV) causes life-threatening chronic infections. Implementation of novel, economical or widely available screening tools can help detect unidentified cases and facilitate their linkage to care. We investigated the relationship between chronic HCV infection and a potential complete blood count biomarker (the monocyte-to-platelet ratio) in the United States. Methods The analytic dataset was selected from cycle years 2009–2016 of the National Health and Nutrition Examination Survey. Complete case data- with no missingness- was available for n = 5281 observations, one-hundred and twenty-two (n = 122) of which were exposed to chronic HCV. The primary analysis used survey-weighted logistic regression to model the effect of chronic HCV on the monocyte-to-platelet ratio adjusting for demographic and biological confounders in a causal inference framework. Missing data and propensity score methods were respectively performed as a secondary and sensitivity analysis. Results In the analytic dataset, outcome data was available for n = 5281 (n = 64,245,530 in the weighted sample) observations of which n = 122 (n = 1,067,882 in the weighted sample) tested nucleic acid positive for HCV. Those exposed to chronic HCV infection in the United States have 3.10 times the odds of a high monocyte-to-platelet ratio than those not exposed (OR = 3.10, [95% CI: 1.55–6.18]). Conclusion A relationship exists between chronic HCV infection and the monocyte-to-platelet ratio in the general population of the United States. Reversing the direction of this association to predict chronic HCV infection from complete blood counts, could provide an economically feasible and universal screening tool, which would help link patients with care.

Participants in pragmatic clinical trials often partially adhere to treatment. However, to simplify the analysis, most studies dichotomize adherence (supposing that subjects received either full or no treatment), which can introduce biases in the results. For example, the popular approach of principal stratification is based on the concept that the population can be separated into strata based on how they will react to treatment assignment, but this framework does not include strata in which a partially adhering participant would belong. We expanded the principal stratification framework to allow partial adherers to have their own principal stratum and treatment level. The expanded approach is feasible in pragmatic settings. We have designed a Monte Carlo posterior sampling method to obtain the relevant parameter estimates. Simulations were completed under a range of settings where participants partially adhered to treatment, including a hypothetical setting from a published simulation trial on the topic of partial adherence. The inference method is additionally applied to data from a real randomized clinical trial that features partial adherence. Comparison of the simulation results indicated that our method is superior in most cases to the biased estimators obtained through standard principal stratification. Simulation results further suggest that our proposed method may lead to increased accuracy of inference in settings where study participants only partially adhere to assigned treatment.

Background: Administrative databases do not contain Body Mass Index (BMI) informa- tion. In proportion-based imputation (PBI) technique, a BMI category is assigned to an individual according to the proportions observed in external survey data. Alternatively, BMI can be imputed using Multiple Imputation (MI). Objectives: To compare MI with PBI to impute BMI variable in osteoarthritis (OA)- cardiovascular disease (CVD) relationship. Research Design: plasmode simulation study. Subjects: used publicly available data from the Canadian Community Health Survey (CCHS) cycles 1.1, 2.1, and 3.1. Measures: BMI was set missing for everyone in the 500 simulated data created from CCHS 3.1 data. Dataset compiled from CCHS cycles 1.1 and 2.1 served as the external data (BMI observed). BMI missing in copies of simulated data was imputed using MI and PBI accessing observed BMI information in external data. After imputation, distribution of BMI variable and the adjusted odds ratio (aOR) estimated from multivariable logistic regression model were compared. Results: Compared to PBI, MI produced proportions of individuals closer to the known proportions across the BMI categories except for the overweight category. Considering the known aOR of 1.59 (1.36, 1.82), BMI imputed using MI introduced less bias in OA- CVD association compared to PBI, the aOR was 1.62 (1.39, 1.86) and 1.66 (1.41, 1.90), respectively. Conclusions: This is the first study to compare MI with PBI in the context of imputing BMI information that is not recorded at the database level. MI was superior to imputation method based on population-level proportions in imputing BMI missing for everyone in the simulated datasets.

Vitamin A deficiency (VAD) may cause anemia. The research aimed at evaluating the effect of Vitamin A supplementation (VAS) on hemoglobin (Hb) is, however, limited and, conclusions drawn from a few...

Background Current human papillomavirus (HPV) vaccine coverage in the United States (in 2019, 66–70%), remains below the Healthy People 2020 coverage goal of 80%. HPV vaccine misinformation, including parental concerns of sexual risk-compensation influence vaccine uptake. We examined the association between HPV vaccination and sexually transmitted infection (STI) outcomes. Methods Of the 20,146 participants from 2013 to 2014 and 2015–2016 cycles of the National Health and Nutrition Examination Survey, 1050 females aged 18–35 with a history of sexual activity had complete case data. Roa-Scott Chi-squared and F-tests assessed survey-weighted socio-demographic differences between vaccinated and unvaccinated participants. Weighted logistic regression assessed crude and adjusted associations between self-reported HPV vaccination (none vs. ≥ 1dose) and lab-confirmed STIs (trichomonas and chlamydia) and vaccine-type HPV (6/11/16/18). As a sensitivity analysis, we conducted weighted-propensity score (PS) models and inverse probability weighting by vaccination status. PS and logistic regression were estimated through survey-weighted logistic regression on variables including race, education, income, marital status, US citizenship, cycle year and age. Results Overall, 325 (31.8%) females with a history of sexual activity were HPV vaccinated, of which 22 (6.1%) received the vaccine at the routine-recommended ages of 11–12, 65.7% were vaccinated after their self-reported sexual debut, 3.8% had a lab-confirmed STI and 3.5% had vaccine-type HPV. There was no association between HPV vaccination and any STIs (adjusted odds ratio [aOR] 0.67, 95%CI:0.38–1.20), and vaccinated participants had 61% reduced odds of vaccine-type HPV (vs. unvaccinated; aOR 0.39, 95%CI:0.19–0.83). Results from the PS sensitivity analysis were similar to the main findings. Conclusion Among females who reported a history of sexual activity, HPV vaccination status was protective against vaccine-type HPV and not associated with lab-based STI outcomes. Although findings may be susceptible to reporting bias, results indicating low vaccine uptake at routine-recommended ages requires additional efforts promoting HPV vaccination before sexual-debut.

Background: Propensity score (PS) analyses are increasingly used in multiple sclerosis (MS) research, largely owing to the greater availability of large observational cohorts and registry databases. Objective: To evaluate the use and quality of reporting of PS methods in the recent MS literature. Methods: We searched the PubMed database for articles published between January 2013 and July 2019. We restricted the search to comparative effectiveness studies of two disease-modifying therapies. Results: Thirty-nine studies were included in the review, with most studies (62%) published within the past 3 years. All studies reported the list of covariates used for the PS model, but only 21% of studies mentioned how those covariates were selected. Most studies used PS matching (72%), followed by PS adjustment (18%), weighting (15%), and stratification (3%), with some overlap. Most studies using matching or weighting reported checking post-PS covariate imbalance (91%), although about 45% of these studies relied on p values from various statistical tests. Only 25% of studies using matching reported calculating robust standard errors for the PS analyses. Conclusions: The quality of reporting of PS methods in the MS literature is sub-optimal in general, and in some cases, inappropriate methods are used.

The beta-interferons are widely prescribed platform therapies for patients with multiple sclerosis (MS). We accessed a cohort of patients with relapsing-onset MS from British Columbia, Canada (1995–2013), to examine the potential survival advantage associated with beta-interferon exposure using a marginal structural model. Accounting for potential treatment-confounder feedback between comorbidity, MS disease progression, and beta-interferon exposure, we found an association between beta-interferon exposure of at least 6 contiguous months and improved survival (hazard ratio (HR) = 0.63, 95% confidence interval 0.47, 0.86). We also assessed potential effect modifications by sex, baseline age, or baseline disease duration, and found these factors to be important effect modifiers. Sparse follow-up due to variability in patient contact with the health system is one of the biggest challenges in longitudinal analyses. We considered several single-level and multilevel multiple imputation approaches to deal with sparse follow-up and disease progression information; both types of approach produced similar estimates. Compared to ad hoc imputation approaches, such as linear interpolation (HR = 0.63), and last observation carried forward (HR = 0.65), all multiple imputation approaches produced a smaller hazard ratio (HR = 0.53), although the direction of effect and conclusions drawn concerning the survival advantage remained the same.

Despite Canada's universal health-care system, millions of Canadians experience unmet health-care needs (UHCN). People with mood disorders may be at higher risk of UHCN due to barriers such as stigma and gaps in health-care services.We aimed to examine the relationship between having a diagnosed mood disorder and experiencing UHCN using a recent, nationally representative survey.Using the 2014 Canadian Community Health Survey, we used multivariate logistic regression to estimate the association between mood disorder and UHCN in the past 12 months, adjusting for sociodemographic variables and health status.Among 52,825 respondents, 11.8% reported UHCN. Respondents with a diagnosed mood disorder were more likely to report UHCN [adjusted odds ratio (OR) 1.61, 95% confidence interval (CI) 1.38, 1.89]. Among respondents with a regular doctor, people with mood disorders were still more likely to report UHCN (OR 1.63, 95% CI 1.38, 1.93). Sensitivity analyses using propensity score and missing data imputation approaches resulted in similar estimates.Adults diagnosed with a mood disorder are more likely to report UHCN in the past year, even those with a regular doctor. Our findings suggest that barriers beyond physician attachment may impact access to care for people with mood disorders.

To compare non-tuberculosis (non-TB)-cause mortality risk overall and cause-specific mortality risks within the immigrant population of British Columbia (BC) with and without TB diagnosis through time-dependent Cox regressions.All people immigrating to BC during 1985-2015 (N = 1,030,873) were included with n = 2435 TB patients, and the remaining as non-TB controls. Outcomes were time-to-mortality for all non-TB causes, respiratory diseases, cardiovascular diseases, cancers, and injuries/poisonings, and were ascertained using ICD-coded vital statistics data. Cox regressions were used, with a time-varying exposure variable for TB diagnosis.The non-TB-cause mortality hazard ratio (HR) was 4.01 (95% CI 3.57-4.51) with covariate-adjusted HR of 1.69 (95% CI 1.50-1.91). Cause-specific covariate-adjusted mortality risk was elevated for respiratory diseases (aHR = 2.96; 95% CI 2.18-4.00), cardiovascular diseases (aHR = 1.63; 95% CI 1.32-2.02), cancers (aHR = 1.40; 95% CI 1.13-1.75), and injuries/poisonings (aHR = 1.85; 95% CI 1.25-2.72).In any given year, if an immigrant to BC was diagnosed with TB, their risk of non-TB mortality was 69% higher than if they were not diagnosed with TB. Healthcare providers should consider multiple potential threats to the long-term health of TB patients during and after TB treatment. TB guidelines in high-income settings should address TB survivor health.RéSUMé: OBJECTIF: Au moyen de régressions de Cox avec une covariable temporalisée, comparer le risque global de mortalité non due à la tuberculose et les risques de mortalité par cause au sein de la population immigrante de la Colombie-Britannique (C.-B.) avec et sans diagnostic de tuberculose. MéTHODE: Toutes les personnes ayant immigré en C.-B. entre 1985 et 2015 (N = 1 030 873) ont été incluses, dont n = 2 435 patients tuberculeux, le reste étant des témoins non tuberculeux. Nos résultats incluaient le temps jusqu’à la mortalité de toute cause autre que la tuberculose, soit les maladies respiratoires, les maladies cardiovasculaires, les cancers et les blessures/empoisonnements, déterminé à l’aide des statistiques de l’état civil codées selon la CIM. Nous avons utilisé des régressions de Cox avec une variable d’exposition temporalisée pour le diagnostic de tuberculose. RéSULTATS: Le coefficient de danger (CD) de mortalité non due à la tuberculose était de 4,01 (IC de 95 % : 3,57-4,51) avec un CD ajusté selon la covariable de 1,69 (IC de 95 % : 1,50-1,91). Le risque de mortalité par cause ajusté selon la covariable était élevé pour : les maladies respiratoires (CDa = 2,96; IC de 95 % : 2,18-4,00), les maladies cardiovasculaires (CDa = 1,63; IC de 95 % : 1,32-2,02), les cancers (CDa = 1,40; IC de 95 % : 1,13-1,75) et les blessures/empoisonnements (CDa = 1,85; IC de 95 % : 1,25-2,72). CONCLUSIONS: Chaque année, si une personne ayant immigré en C.-B. avait un diagnostic de tuberculose, son risque de mortalité non due à la tuberculose était supérieur de 69 % à celui d’une personne sans diagnostic de tuberculose. Les professionnels de santé devraient tenir compte des multiples menaces possibles à la santé à long terme de leurs patients tuberculeux pendant et après le traitement de la tuberculose. Les lignes directrices sur la tuberculose dans les milieux à revenu élevé devraient tenir compte de la santé des survivants de la tuberculose.

Although machine learning is increasingly being applied to support clinical decision making, there is a significant gap in understanding what it is and how nurses should adopt it in practice. The purpose of this case study is to show how one application of machine learning may support nursing work and to discuss how nurses can contribute to improving its relevance and performance. Using data from 130 specialized hospitals with 101 766 patients with diabetes, we applied various advanced statistical methods (known as machine learning algorithms) to predict early readmission. The best-performing machine learning algorithm showed modest predictive ability with opportunities for improvement. Nurses can contribute to machine learning algorithms by (1) filling data gaps with nursing-relevant data that provide personalized context about the patient, (2) improving data preprocessing techniques, and (3) evaluating potential value in practice. These findings suggest that nurses need to further process the information provided by machine learning and apply "Wisdom-in-Action" to make appropriate clinical decisions. Nurses play a pivotal role in ensuring that machine learning algorithms are shaped by their unique knowledge of each patient's personalized context. By combining machine learning with unique nursing knowledge, nurses can provide more visibility to nursing work, advance nursing science, and better individualize patient care. Therefore, to successfully integrate and maximize the benefits of machine learning, nurses must fully participate in its development, implementation, and evaluation.

Background: Different methods to prevent contrast-associated acute kidney injury (CA-AKI) have been proposed in recent years. We performed a mixed treatment comparison to evaluate and rank suggested interventions. Methods: A comprehensive Systematic review and a Bayesian network meta-analysis of randomised controlled trials was completed. Results were tabulated and graphically represented using a network diagram; forest plots and league tables were shown to rank treatments by the surface under the cumulative ranking curve (SUCRA). A stacked bar chart rankogram was generated. We performed main analysis with 200 RCTs and three analyses according to contrast media and high or normal baseline renal profile that includes 173, 112 & 60 RCTs respectively. Results: We have included 200 trials with 42,273 patients and 44 interventions. The primary outcome was CI-AKI, defined as ≥25% relative increase or ≥ 0.5 mg/dl increase from baseline creatinine one to 5 days post contrast exposure. The top ranked interventions through different analyses were Allopurinol, Prostaglandin E1 (PGE1) & Oxygen (0.9647, 0.7809 & 0.7527 in the main analysis). Comparatively, reference treatment intravenous hydration was ranked lower but better than Placebo (0.3124 VS 0.2694 in the main analysis). Conclusion: Multiple CA-AKI preventive interventions have been tested in RCTs. This network evaluates data for all the explored options. The results suggest that some options (particularly allopurinol, PGE1 & Oxygen) deserve further evaluation in a larger well-designed RCTs.

Purpose To estimate the risk of tuberculosis (TB)-associated depression. A second aim was to estimate the extent to which any increased risk of depression among TB patients may be mediated by the length of hospital length stay (LOS) Methods Retrospective cohort study of linked healthcare claims and public health surveillance data. Our primary outcome, time-to-depression, was analyzed using Cox proportional hazards (PH) regressions. Causal mediation analysis was used to estimate the natural direct and indirect effect of TB mediated by hospital LOS. Results Among 755,836 participants (52.2% female, median age=35 years, median follow-up=8.75 years), 2295 were diagnosed with TB (exposure), and 128,963 were diagnosed with depression (outcome). We observed a covariate-adjusted hazard ratio (aHR) of 1.24 (95% CI, 1.14–1.34) for depression by TB. The total effect of TB on depression was decomposed into a natural direct effect of TB of aHR=1.11 (95% CI, 1.02–1.21) and an indirect effect through hospital LOS of aHR=1.11 (95% CI, 1.10–1.12), indicating that TB's total effect was mediated by 50% (95% CI, 35–82%) through hospital LOS. Conclusions TB patients had a 24% higher risk of developing depression. TB's effect was mediated substantially by hospital LOS, requiring further study. Depression screening among TB patients is warranted.

and KeywordsAimSmall studies have shown reduced sodium sensitivity of blood pressure in obese adolescents on caloric restriction. However, no study at the population level has studied such an effect. We aimed to explore the association between mean daily sodium intake and prevalent hypertension among a nationally representative sample of U.S. adults on caloric restriction who participated in the National Health Examination and Nutrition Survey over the last twelve years.Methods and ResultsWe used a design-based regression model to explore the association between sodium intake and prevalent hypertension. We also conducted sensitivity analyses using multiple imputation chained equations and propensity score matching. We also measured the effect of a binary exposure derived from two widely recommended thresholds of sodium intake: 2.3 and 5.0 grams per day. Among 5,756 individuals, we did not detect any significant association between increased sodium and the odds of hypertension (OR: 0.97; CI 95%: 0.90; 1.05). All our sensitivity analyses are consistent with our main findings.ConclusionOur findings suggest that people on caloric restriction—a component of healthy weight loss—would see no benefit in reducing sodium intake to lower blood pressure. These results highlight the need to explore new population-specific strategies for sodium intake reduction, including new dietary prescription approaches to improve dietary adherence and reduce the risk associated with sodium-deficient diets.

Background To inform World Health Organization (WHO) global guidelines, we updated and expanded the evidence base to assess the comparative efficacy, tolerability, and safety of first-line antiretroviral therapy (ART) regimens. Methods We searched Embase, Medline and CENTRAL on 28 February 2020 to update the systematic literature review of clinical trials comparing recommended first-line ART that informed previous WHO guidelines. Outcomes included viral suppression, change in CD4 cell counts, mortality, serious and overall adverse events (AEs), discontinuation, discontinuations due to AEs (DAEs); and new outcomes: drug-resistance, neuropsychiatric AEs, early viral suppression, weight gain and birth outcomes. Comparative effects were assessed through network meta-analyses and certainty in the evidence was assessed using the GRADE framework. Findings We identified 156 publications pertaining to 68 trials for the primary population. Relative to efavirenz, dolutegravir had improved odds of viral suppression across all time points (odds ratio [OR]: 1·94; 95% credible interval [CrI]: 1·48–2·56 at 96 weeks); was protective of drug-resistance (OR: 0·13; 95%CrI: 0·04–0·48); and led to fewer discontinuations (OR: 0·58; 95%CrI: 0·48–0·70). Evidence supported dolutegravir use among TB-HIV co-infected persons and pregnant women. Adverse birth outcomes were observed in 33.2% of dolutegravir-managed pregnancies and 35.0% of efavirenz-managed pregnancies. Low-dose efavirenz had comparable efficacy and safety to standard-dose efavirenz, but led to fewer DAEs (OR: 0·70; 95%CrI: 0·50–0·92). Interpretation The evidence supports choosing dolutegravir in combination with lamivudine/emtricitabine and tenofovir disoproxil fumarate as the preferred first-line regimen and low-dose efavirenz-based regimens as an alternative. Dolutegravir can be considered to be effective, safe and tolerable. Funding WHO.

Study design Protocol for a pragmatic randomized controlled trial (the Exercise guideline Promotion and Implementation in Chronic SCI [EPIC-SCI] Trial). Primary objectives To test if home-/community-based exercise, prescribed according to the international SCI exercise guidelines, significantly reduces chronic bodily pain in adults with SCI. Secondary objectives To investigate: (1) the effects of exercise on musculoskeletal and neuropathic chronic pain; (2) if reduced inflammation and increased descending inhibitory control are viable pathways by which exercise reduces pain; (3) the effects of chronic pain reductions on subjective well-being; and (4) efficiency of a home-/community-based exercise intervention. Setting Exercise in home-/community-based settings; assessments in university-based laboratories in British Columbia, Canada. Method Eighty-four adults with chronic SCI, reporting chronic musculoskeletal or neuropathic pain, and not meeting the current SCI exercise guidelines, will be recruited and randomized to a 6-month Exercise or Wait-List Control condition. Exercise will occur in home/community settings and will be supported through behavioral counseling. All measures will be taken at baseline, 3-months and 6-months. Analyses will consist of linear mixed effect models, multiple regression analyses and a cost-utility analysis. The economic evaluation will examine the incremental costs and health benefits generated by the intervention compared with usual care. Ethics and dissemination The University of British Columbia Clinical Research Ethics Board approved the protocol (#H19-01650). Using an integrated knowledge translation approach, stakeholders will be engaged throughout the trial and will co-create and disseminate evidence-based recommendations and messages regarding the use of exercise to manage SCI chronic pain.

Background Maternal and child mortality remain a global health concern despite different interventions that have been implemented to address this issue. Adequate antenatal care (ANC) is crucial in reducing maternal and neonatal morbidity and mortality. However, in Rwanda, there is still suboptimal utilization of ANC services. This study aims to assess the relationship between perceived barriers to accessing health care and inadequate ANC visits among women of reproductive age in Rwanda. Methods This study is cross-sectional using secondary data from the 2014–15 Rwanda demographic and health survey (RDHS). The study included 5876 women aged 15–49 years, and the primary outcome of the investigation was inadequate ANC visits defined as delayed first ANC visit and non-completion of at least four recommended visits during the pregnancy period. The primary exposure was perceived barriers to accessing health care, operationalized using the following 4 variables: distance to the health facility, getting money for treatment, not wanting to go alone and getting permission to go for treatment. A survey-weighted multivariable logistic regression analysis and backward elimination method based on Akaike information criterion (AIC) was used to select the final model. We conducted a number of sensitivity analyses using stratified and weighting propensity score methods and investigated the relationship between the outcome and each barrier to care separately. Results Of 5, 876 women included in the analysis, 53% (3132) aged 20 to 34 years, and 44% (2640) were in the lowest wealth index. Overall, 64% (2375) of women who perceived to have barriers to health care had inadequate ANC visits. In multivariable analysis, women who perceived to have barriers to health care had higher odds of having inadequate ANC visits (OR: 1.14; 95% CI: 0.99, 1.31). However, the association was borderline statistically significant. The findings from sensitivity analyses were consistent with the main analysis results. Conclusion The study suggests a positive association between perceived barriers to health care access and inadequate ANC visits. The findings speak to a need for interventions that focus on improving access to health care in Rwanda to increase uptake of ANC services.

Background Interruptions in healthcare services contribute to an elevated risk of overdose in the weeks following release from incarceration. This study examined the association of use of community healthcare with nonfatal and fatal overdose in the 30 days following release. Methods We conducted a retrospective cohort study using linked administrative data from a random sample of 20% of the population of British Columbia. We examined releases from provincial correctional facilities between January 1, 2015 – December 1, 2018. We fit multivariate Andersen-Gill models to examine nonfatal overdoses after release from incarceration and applied Standard Cox regression for analyses of fatal overdoses. Results There were a combined 16,809 releases of 6,721 people in this study. At least one overdose occurred in 2.8% of releases. A community healthcare visit preceded the first nonfatal overdose in 86.4% of releases with a nonfatal overdose event. Only 48.4% of people who had a fatal overdose used community healthcare. In adjusted analysis, people who had used community healthcare had a higher hazard of healthcare-attended nonfatal overdose (aHR 2.83 95% CI 2.13, 3.78) and lower hazard of fatal overdose (aHR 0.58, 95%CI 0.28, 1.19). Conclusions Community healthcare visits after release from custody may be an important opportunity to provide overdose prevention and harm reduction supports. Policies and resourcing are needed to facilitate better connection to primary healthcare during the transition to community. Providers in community should be equipped to offer care to people who have recently experienced incarceration in a way that is accessible, acceptable and trauma-informed.

ObjectiveTo assess the association between long term prescription opioid treatment medically dispensed for non-cancer pain and the initiation of injection drug use (IDU) among individuals without a history of substance use.DesignRetrospective cohort study.SettingLarge administrative data source (containing information for about 1.7 million individuals tested for hepatitis C virus or HIV in British Columbia, Canada) with linkage to administrative health databases, including dispensations from community pharmacies.ParticipantsIndividuals age 11-65 years and without a history of substance use (except alcohol) at baseline.Main outcome measuresEpisodes of prescription opioid use for non-cancer pain were identified based on drugs dispensed between 2000 and 2015. Episodes were classified by the increasing length and intensity of opioid use (acute (lasting Results59 804 participants (14 951 people from each opioid use category) were included in the matched cohort, and followed for a median of 5.8 years. 1149 participants initiated IDU. Cumulative probability of IDU initiation at five years was highest for participants with chronic opioid use (4.0%), followed by those with episodic use (1.3%) and acute use (0.7%), and those who were opioid naive (0.4%). In the inverse probability of treatment weighted Cox model, risk of IDU initiation was 8.4 times higher for those with chronic opioid use versus those who were opioid naive (95% confidence interval 6.4 to 10.9). In a sensitivity analysis limited to individuals with a history of chronic pain, cumulative risk for those with chronic use (3.4% within five years) was lower than the primary results, but the relative risk was not (hazard ratio 9.7 (95% confidence interval 6.5 to 14.5)). IDU initiation was more frequent at higher opioid doses and younger ages.ConclusionsThe rate of IDU initiation among individuals who received chronic prescription opioid treatment for non-cancer pain was infrequent overall (3-4% within five years) but about eight times higher than among opioid naive individuals. These findings could have implications for strategies to prevent IDU initiation, but should not be used as a reason to support involuntary tapering or discontinuation of long term prescription opioid treatment.

IntroductionIncreasing evidence indicates that chronic hepatitis C virus (HCV) infection is associated with higher risk of diabetes. Previous studies showed ethnic disparities in the disease burden of diabetes, with increased risk in Asian population. We described the incidence of type 2 diabetes related to HCV infection and assessed the concurrent impact of HCV infection and ethnicity on the risk of diabetes.Research design and methodsIn British Columbia Hepatitis Testers Cohort, individuals were followed from HCV diagnosis to the earliest of (1) incident type 2 diabetes, (2) death or (3) end of the study (December 31, 2015). Study population included 847 021 people. Diabetes incidence rates in people with and without HCV were computed. Propensity scores (PS) analysis was used to assess the impact of HCV infection on newly acquired diabetes. PS-matched dataset included 117 184 people. We used Fine and Gray multivariable subdistributional hazards models to assess the effect of HCV and ethnicity on diabetes while adjusting for confounders and competing risks.ResultsDiabetes incidence rates were higher among people with HCV infection than those without. The highest diabetes incidence rate was in South Asians with HCV (14.7/1000 person-years, 95% CI 12.87 to 16.78). Compared with Others, South Asians with and without HCV and East Asians with HCV had a greater risk of diabetes. In the multivariable stratified analysis, HCV infection was associated with increased diabetes risk in all subgroups: East Asians, adjusted HR (aHR) 3.07 (95% CI 2.43 to 3.88); South Asians, aHR 2.62 (95% CI 2.10 to 3.26); and Others, aHR 2.28 (95% CI 2.15 to 2.42).ConclusionsIn a large population-based linked administrative health data, HCV infection was associated with higher diabetes risk, with a greater relative impact in East Asians. South Asians had the highest risk of diabetes. These findings highlight the need for care and screening for HCV-related chronic diseases such as type 2 diabetes among people affected by HCV.

OBJECTIVES To describe the criteria that currently guide empiric antibiotic treatment in children admitted to Canadian PICUs. DESIGN Cross-sectional survey. SETTING Canadian PICUs. SUBJECTS Pediatric intensivists and pediatric infectious diseases specialists. INTERVENTIONS None. MEASUREMENTS AND MAIN RESULTS We used focus groups and literature review to design the survey questions and its four clinical scenarios (sepsis, pneumonia, meningitis, and intra-abdominal infections). We analyzed our results using descriptive statistics and multivariate linear regression. Our response rate was 60% for pediatric intensivists (62/103) and 36% for pediatric infectious diseases specialists (37/103). Variables related to patient characteristics, disease severity, pathogens, and clinical, laboratory, and radiologic infection markers were associated with longer courses of antibiotics, with median increment ranging from 1.75 to 7.75 days. The presence of positive viral polymerase chain reaction result was the only variable constantly associated with a reduction in antibiotic use (median decrease from, -3.25 to -8.25 d). Importantly, 67-92% of respondents would still use a full course of antibiotics despite positive viral polymerase chain reaction result and marked clinical improvement for patients with suspected sepsis, pneumonia, and intra-abdominal infection. Clinical experience was associated with shorter courses of antibiotics for meningitis and sepsis (-1.3 d [95% CI, -2.4 to -0.2] and -1.8 d [95% CI, -2.8 to -0.7] per 10 extra years of clinical experience, respectively). Finally, site and specialty also influenced antibiotic practices. CONCLUSIONS Decisions about antibiotic management for PICU patients are complex and involve the assessment of several different variables. With the exception of a positive viral polymerase chain reaction, our findings suggest that physicians rarely consider reducing the duration of antibiotics despite clinical improvement. In contrast, they will prolong the duration when faced with a nonreassuring characteristic. The development of objective and evidence-based criteria to guide antibiotic therapy in critically ill children is crucial to ensure the rational use of these agents in PICUs.

Health researchers are familiar with the concept of trial power, a number that prior to the start of a trial is intended to describe the probability that the results of the trial will correctly conclude that the intervention has an effect. Trial power, as calculated using standard software, is an expected power that arises from averaging hypothetical trial results over all possible treatment allocations that could be generated by the randomization algorithm. However, in the trial that ultimately is conducted, only one treatment allocation will occur, and the corresponding attained power (conditional on the allocation that occurred) is not guaranteed to be equal to the expected power and may be substantially lower. We provide examples illustrating this issue, discuss some circumstances when this issue is a concern, define and advocate the examination of the pre-randomization power distribution for evaluating the risk of obtaining unacceptably low attained power, and suggest the use of randomization restrictions to reduce this risk. In trials that randomize only a modest number of units, we recommend that trial designers evaluate the risk of getting low attained power and, if warranted, modify the randomization algorithm to reduce this risk.

BACKGROUND: Guidelines recommend nephrology referral for people with advanced non–dialysis-dependent chronic kidney disease, based mostly on survival benefits seen in retrospective studies of dialysis patients, which may not be generalizable to the broader population with chronic kidney disease. We aimed to examine the association between outpatient nephrology consultation and survival in adults with stage 4 chronic kidney disease. METHODS: We linked population-based laboratory and administrative data from 2002 to 2014 in Alberta, Canada, on adults with stage 4 chronic kidney disease (sustained estimated glomerular filtration rate ≥ 15 to < 30 mL/min/1.73 m(2) for > 90 d), who had never had kidney failure and had had no outpatient nephrology encounter in the 2 years preceding study entry. Participants who had never had an outpatient nephrology visit before renal replacement treatment were considered “unexposed.” Participants who saw a nephrologist during follow-up were considered “unexposed” before the first outpatient nephrology visit and “exposed” thereafter. The primary outcome was all-cause mortality. RESULTS: Of the 14 382 study participants (median follow-up 2.7 yr), 64% were aged ≥ 80 years, 35% saw a nephrologist and 66% died during follow-up. Nephrology consultation was associated with lower mortality (hazard ratio [HR] 0.88, 95% confidence interval [CI] 0.82–0.93). The association was strongest in people < 70 years (HR 0.78, 95% CI, 0.65–0.92), progressively weaker with increasing age, and absent in people ≥ 90 years (HR 1.05, 95% CI 0.88–1.25). INTERPRETATION: The survival benefit of nephrology consultation in adults with stage 4 chronic kidney disease may be smaller than expected and appears to attenuate with increasing age. These findings should inform recommendations for nephrology referral considering the advanced age of the patient population meeting current referral criteria.

In longitudinal studies, if the time-dependent covariates are affected by the past treatment, time-dependent confounding may be present. For a time-to-event response, marginal structural Cox models are frequently used to deal with such confounding. To avoid some of the problems of fitting marginal structural Cox model, the sequential Cox approach has been suggested as an alternative. Although the estimation mechanisms are different, both approaches claim to estimate the causal effect of treatment by appropriately adjusting for time-dependent confounding. We carry out simulation studies to assess the suitability of the sequential Cox approach for analyzing time-to-event data in the presence of a time-dependent covariate that may or may not be a time-dependent confounder. Results from these simulations revealed that the sequential Cox approach is not as effective as marginal structural Cox model in addressing the time-dependent confounding. The sequential Cox approach was also found to be inadequate in the presence of a time-dependent covariate. We propose a modified version of the sequential Cox approach that correctly estimates the treatment effect in both of the above scenarios. All approaches are applied to investigate the impact of beta-interferon treatment in delaying disability progression in the British Columbia Multiple Sclerosis cohort (1995–2008).

In time-to-event analyses of observational studies of drug effectiveness, incorrect handling of the period between cohort entry and first treatment exposure during follow-up may result in immortal time bias. This bias can be eliminated by acknowledging a change in treatment exposure status with time-dependent analyses, such as fitting a time-dependent Cox model. The prescription time-distribution matching (PTDM) method has been proposed as a simpler approach for controlling immortal time bias. Using simulation studies and theoretical quantification of bias, we compared the performance of the PTDM approach with that of the time-dependent Cox model in the presence of immortal time. Both assessments revealed that the PTDM approach did not adequately address immortal time bias. Based on our simulation results, another recently proposed observational data analysis technique, the sequential Cox approach, was found to be more useful than the PTDM approach (Cox: bias = −0.002, mean squared error = 0.025; PTDM: bias = −1.411, mean squared error = 2.011). We applied these approaches to investigate the association of β-interferon treatment with delaying disability progression in a multiple sclerosis cohort in British Columbia, Canada (Long-Term Benefits and Adverse Effects of Beta-Interferon for Multiple Sclerosis (BeAMS) Study, 1995–2008).

IntroductionLongitudinal studies ascertain exposure, covariates, and outcomes over time. For estimating treatment effect on mortality, ignoring the time-varying nature of an exposure may lead to immortal time bias. Time-dependent confounding that affects future treatment may bias the estimated effects. Differences in baseline prognosis between treatment groups further complicate this issue. Objectives and ApproachWe applied sequential Cox modeling to estimate the causal effect of referral for nephrology care on the survival of adults with advanced chronic kidney disease, linking laboratory and administrative data from Alberta, Canada. We created pseudo-data by mimicking successive randomized controlled trials. To address immortal time bias, each “mini-trial” consisted of individuals starting treatment, and those not yet treated, in each 3-month time interval. We incorporated inverse-probability-of-treatment-weights (IPTW) to minimize treatment selection bias for each “mini-trial. ” We fit a “mini-trial”-stratified, weighted Cox model to estimate the overall hazard ratio for death by averaging the effect estimates across “mini-trials.” ResultsWe included 9,675 patients who entered the cohort between 2002 and 2013. The mean age was 82 years; 35% were male; and 33% were ultimately referred to a nephrologist after a median wait-period of 6 months. Compared to non-referred patients, those referred were younger and had fewer comorbidities at baseline. Referral was associated with a significant 45% lower hazard for death in an adjusted Cox model. The effect was attenuated in a multivariate Cox model with a time-varying exposure and in a sequential Cox model further controlling for potential time-dependent confounding by measures reflecting kidney-, cardiovascular-, and cerebrovascular-health. After incorporating IPTW for addressing treatment selection bias in the same sequential Cox model, the effect estimate was toward the null and no longer significant. Conclusion/ImplicationsWe found that applying analytical strategies that addressed immortal time bias, time-dependent confounding, and treatment selection bias, the survival benefit associated with nephrology referral was attenuated. Inverse-probability-of treatment weighted sequential Cox approach may be used to address these important biases and confounding that are common in real-world clinical settings.

Background Worldwide, osteoarthritis (OA) is a major musculoskeletal disorder. Recent research suggests that OA is an independent risk factor for cardiovascular disease (CVD). 1 The relationship is complicated because non-steroidal anti-inflammatory drugs (NSAIDs), a proven risk factor for CVD, are frequently used for the treatment of OA. 2 Researchers have hypothesised that NSAID use in the causal pathway between OA and CVD is what may ultimately impact these patients to develop CVD, this pathway has yet to be studied. 3,4 Objectives The objective of this study was to disentangle the role of NSAID in the increased risk of CVD among OA patients. Methods This longitudinal study was based on linked health administrative data from British Columbia, Canada. From a population-based cohort of 720,055 British Columbians, we matched on age and sex to assemble 7,743 OA patients and 23 229 non-OA controls (1:3 ratio). We used multivariable Cox proportional hazards models to estimate the risk of developing incident CVD (primary outcome) as well as ischaemic heart disease (IHD), congestive heart failure (CHF) and stroke (secondary outcomes). To estimate the mediating effect of NSAIDs, defined as current use of NSAID using linked prescription dispensing records, in the OA-CVD relationship, we implemented a marginal structural model. Results People with OA had 23% higher risk of developing CVD compared to people without OA after adjusting for SES, BMI, hypertension, diabetes, hyperlipidemia, COPD, and Romano comorbidity score, adjusted HR (95% CI) was 1.23 (1.17, 1.29). Adjusted HR (95% CI) was 1.42 (1.33, 1.52), 1.17 (1.10, 1.27), 1.14 (1.08, 1.24) for CHF, IHD and stroke, respectively. Approximately 67.51% of the total effect of OA on the increased risk of CVD was mediated through current NSAID use. Among the secondary outcomes, approximately 44.77% of increased CHF risk was mediated through current NSAID use. More than 90% of the total effects on IHD and stroke was mediated through the current NSAID use. Conclusions Our study is the first to evaluate the mediating role of NSAID use in the OA-CVD relationship based on population-based health administrative data. The results of this study also indicate that OA is an independent risk factor for CVD. Our findings suggest that the mediating role of NSAID use substantially contributes to the OA-CVD association. References [1] Wang H, Bai J, He B, Hu X, Liu D. Osteoarthritis and the risk of cardiovascular disease: A meta-analysis of observational studies. Sci Rep [Internet] 2016Dec [cited 2017 Sep 6];6(1). Available from http://www.nature.com/articles/srep39672 [2] Trelle S, Reichenbach S, Wandel S, Hildebrand P, Tschannen B, Villiger PM, et al. Cardiovascular safety of non-steroidal anti-inflammatory drugs: network meta-analysis. BMJ. 2011Jan 11;342:c7086. [3] Rahman MM, Kopec JA, Anis AH, Cibere J, Goldsmith CH. Risk of Cardiovascular Disease in Patients With Osteoarthritis: A Prospective Longitudinal Study: Cardiovascular Disease in Osteoarthritis Patients. Arthritis Care Res. 2013Dec;65(12):1951–8. [4] Link Between OAand CVD Risk [Internet]. arthritis.org. [cited 2017 Oct 23]. Available from: http://www.arthritis.org/living-with-arthritis/comorbidities/heart-disease/osteoarthritis-ups-cvd-risk.php Disclosure of Interest None declared

The use of retrospective health care claims datasets is frequently criticized for the lack of complete information on potential confounders. Utilizing patient's health status-related information from claims datasets as surrogates or proxies for mismeasured and unobserved confounders, the high-dimensional propensity score algorithm enables us to reduce bias. Using a previously published cohort study of postmyocardial infarction statin use (1998-2012), we compare the performance of the algorithm with a number of popular machine learning approaches for confounder selection in high-dimensional covariate spaces: random forest, least absolute shrinkage and selection operator, and elastic net. Our results suggest that, when the data analysis is done with epidemiologic principles in mind, machine learning methods perform as well as the high-dimensional propensity score algorithm. Using a plasmode framework that mimicked the empirical data, we also showed that a hybrid of machine learning and high-dimensional propensity score algorithms generally perform slightly better than both in terms of mean squared error, when a bias-based analysis is used.

Background and purpose Beta-interferons (IFNβ) are the most widely prescribed drugs for patients with multiple sclerosis (MS). However, whether or not treatment with IFNβ can delay secondary progressive MS (SPMS) onset remains unknown. Our aim was to examine the association between IFNβ exposure and SPMS onset in patients with relapsing−remitting MS (RRMS). Methods A retrospective cohort study using British Columbia (Canada) population-based clinical and health administrative data (1985–2008) was conducted. RRMS patients treated with IFNβ (n = 794) were compared with untreated contemporary (n = 933) and historical (n = 837) controls. Cohort entry was the first clinic visit during which patients became eligible for IFNβ treatment (baseline). The outcome was time from baseline to SPMS onset. Cox regression models with IFNβ as a time-dependent exposure were adjusted for sex, and baseline age, disease duration, disability, *socioeconomic status and *comorbidities (*available for the contemporary cohorts only). Additional analyses included propensity score adjustment. Results The median follow-up for the IFNβ-treated, untreated contemporary and historical controls were 5.7, 3.7 and 7.3 years, and the proportions of patients reaching SPMS were 9.2%, 11.8% and 32.9%, respectively. After adjustment for confounders, IFNβ exposure was not associated with the risk of reaching SPMS when either the contemporary or the historical untreated cohorts were considered (hazard ratio 1.07; 95% confidence interval 0.93–1.48, and hazard ratio 1.04; 95% confidence interval 0.74–1.46, respectively). Further adjustments and the propensity score yielded results consistent with the main analysis. Conclusions Amongst patients with RRMS, use of IFNβ was not associated with a delayed onset of SPMS.

A proportion of multiple sclerosis (MS) patients treated with interferon-β (IFNβ) develop neutralizing antibodies (NAbs), which can reduce therapeutic efficacy. In the Betaseron/Betaferon in Newly Emerging MS for Initial Treatment (BENEFIT) study, 88/277 patients developed NAbs, 48 having transient positivity and 29 having sustained positivity. This study aimed to investigate the antibody binding characteristics of serial sera in a subset of these two patient groups. Using Biacore™, a surface plasmon resonance-based technology that monitors biomolecular interactions in real time, we immobilized pure IFNβ-1b and analyzed antibody binding responses and dissociation rates of these sera. NAb titers correlated directly with binding responses and inversely with dissociation rates, and sera from sustained NAb patients demonstrated significantly higher binding responses and slower dissociation rates than sera from transient NAb patients. Thus, transient and sustained NAbs are quantitatively and qualitatively different, and interestingly, binding responses and dissociation rates at month 12 could predict the NAb course.

This paper presents an approach for estimating the relative location and orientation between two or more underwater vehicles operating in tight formation. One of the vehicles is equipped with a camera of wide field of view. The other vehicle(s) are equipped with active light markers to enable the use of computer vision for pose estimation. The pose estimation addresses two scenarios, which are both important from the operational point of view. The first pertains to the availability of an acoustic communication channel which allows for exchanging attitude data and acoustic ranging, and use it in the pose estimation procedure. The second corresponds to the exclusive use of a set of 4 or more optical beacons with no acoustic information exchange, which is a capability that has not been yet proposed nor demonstrated in underwater vehicles. The contributions can be summarize as (1) a novel method of estimating the pose of an autonomous underwater vehicle using light beacons and other sensors when available, (2) an automated marker configuration analysis approach. Performance of the pose estimation approach is evaluated using synthetic and real data.

Longitudinal observational data are required to assess the association between exposure to β-interferon medications and disease progression among relapsing-remitting multiple sclerosis (MS) patients in the “real-world” clinical practice setting. Marginal structural Cox models (MSCMs) can provide distinct advantages over traditional approaches by allowing adjustment for time-varying confounders such as MS relapses, as well as baseline characteristics, through the use of inverse probability weighting. We assessed the suitability of MSCMs to analyze data from a large cohort of 1,697 relapsing-remitting MS patients in British Columbia, Canada (1995–2008). In the context of this observational study, which spanned more than a decade and involved patients with a chronic yet fluctuating disease, the recently proposed “normalized stabilized” weights were found to be the most appropriate choice of weights. Using this model, no association between β-interferon exposure and the hazard of disability progression was found (hazard ratio = 1.36, 95% confidence interval: 0.95, 1.94). For sensitivity analyses, truncated normalized unstabilized weights were used in additional MSCMs and to construct inverse probability weight-adjusted survival curves; the findings did not change. Additionally, qualitatively similar conclusions from approximation approaches to the weighted Cox model (i.e., MSCM) extend confidence in the findings.

Background. We examined (1) patient characteristics and disease-modifying drug (DMD) exposure in late-onset (LOMS, ≥50 years at symptom onset) versus adult-onset (AOMS, 18–β) and disability progression in older relapsing-onset MS adults (≥50 years).Methods. This retrospective study (1980–2004, British Columbia, Canada) included 358 LOMS and 5627 AOMS patients. IFNβ-treated relapsing-onset MS patients aged ≥50 (regardless of onset age, 90) were compared with 171 contemporary and 106 historical controls. Times to EDSS 6 from onset and from IFNβeligibility were examined using survival analyses.Results. LOMS patients (6%) were more likely to be male, with motor onset and a primary-progressive course, and exhibit faster progression and were less likely to take DMDs. Nonetheless, 57% were relapsing-onset, of which 31% were prescribed DMDs, most commonly IFNβ. Among older relapsing-onset MS adults, no significant association between IFNβexposure and disability progression was found when either the contemporary (hazard ratio [HR]: 0.46; 95% CI: 0.18–1.22) or historical controls (HR: 0.54; 95% CI: 0.20–1.42) were considered.Conclusion. LOMS differed clinically from AOMS. One-third of older relapsing-onset MS patients were prescribed a DMD. IFNβexposure was not significantly associated with reduced disability in older MS patients.

Background and purpose It was recently reported that there was no significant overall association between interferon beta exposure and disability progression in relapsing−remitting multiple sclerosis (RRMS) patients in an observational study from Canada. In the current study, the potential for heterogeneity in the association between exposure to interferon beta and disability progression across patients' baseline characteristics was investigated. Methods RRMS patients treated with interferon beta (n = 868) and two cohorts of untreated patients (829 contemporary and 959 historical controls) were included. The main outcome was time from interferon beta treatment eligibility (baseline) to a confirmed and sustained Expanded Disability Status Scale (EDSS) score 6 using a multivariable Cox model, with treatment as a time-varying predictor, testing interaction effects for five pre-specified baseline characteristics: sex, age, disease duration, EDSS and annualized relapse rate (ARR) based on the previous 2 years. Results Significant heterogeneity was found in the association of interferon beta exposure and disability progression only across ARR, and only when treated patients were compared with historical controls (P = 0.005 at a Bonferroni-adjusted alpha of 0.01). For patients with ARR>1, treatment-exposed time was associated with a hazard ratio of 0.38 (95%CI 0.20–0.75) for disability progression compared with the unexposed time. Conclusions RRMS patients with more frequent relapses at baseline may be more likely to benefit from interferon beta treatment with respect to long-term disability progression.

Context Interferon beta is widely prescribed to treat multiple sclerosis (MS); however, its relationship with disability progression has yet to be established. Objective To investigate the association between interferon beta exposure and disability progression in patients with relapsing-remitting MS. Design, Setting, and Patients Retrospective cohort study based on prospectively collected data (1985-2008) from British Columbia, Canada. Patients with relapsing-remitting MS treated with interferon beta (n = 868) were compared with untreated contemporary (n = 829) and historical (n = 959) cohorts. Main Outcome Measures The main outcome measure was time from interferon beta treatment eligibility (baseline) to a confirmed and sustained score of 6 (requiring a cane to walk 100 m; confirmed at >150 days with no measurable improvement) on the Expanded Disability Status Scale (EDSS) (range, 0-10, with higher scores indicating higher disability). A multivariable Cox regression model with interferon beta treatment included as a time-varying covariate was used to assess the hazard of disease progression associated with interferon beta treatment. Analyses also included propensity score adjustment to address confounding by indication. Results The median active follow-up times (first to last EDSS measurement) were as follows: for the interferon beta–treated cohort, 5.1 years (interquartile range [IQR], 3.0-7.0 years); for the contemporary control cohort, 4.0 years (IQR, 2.1-6.4 years); and for the historical control cohort, 10.8 years (IQR, 6.3-14.7 years). The observed outcome rates for reaching a sustained EDSS score of 6 were 10.8%, 5.3%, and 23.1% in the 3 cohorts, respectively. After adjustment for potential baseline confounders (sex, age, disease duration, and EDSS score), exposure to interferon beta was not associated with a statistically significant difference in the hazard of reaching an EDSS score of 6 when either the contemporary control cohort (hazard ratio, 1.30; 95% CI, 0.92-1.83; P = .14) or the historical control cohort (hazard ratio, 0.77; 95% CI, 0.58-1.02; P = .07) were considered. Further adjustment for comorbidities and socioeconomic status, where possible, did not change interpretations, and propensity score adjustment did not substantially change the results. Conclusion Among patients with relapsing-remitting MS, administration of interferon beta was not associated with a reduction in progression of disability.

Search and rescue, autonomous construction, and many other semi-autonomous multirobot applications can benefit from proximal interactions between an operator and a swarm of robots. Most research on proximal interaction is based on explicit communication techniques such as gesture and speech. This study proposes a new implicit proximal communication technique to approach the problem of robot selection. We use electroencephalography (EEG) signals to select the robot at which the operator is looking. This is achieved using steady-state visually evoked potential (SSVEP), a repeatable neural response to a regularly blinking visual stimulus that varies predictively based on the blinking frequency. In our experiments, each robot was equipped with LEDs blinking at a different frequency, and the operator’s SSVEP neural response was extracted from the EEG signal to detect and select the robot without requiring any conscious action by the user. This study systematically investigates several parameters affecting the SSVEP neural response: blinking frequency of the LED, distance between the robot and the operator, and color of the LED. Based on these parameters, we study two signal processing approaches and critically analyze their performance on 10 subjects controlling a set of physical robots. Our results show that despite numerous artifacts, it is possible to achieve a recognition rate higher than 85 % on some subjects, while the average over the ten subjects was 75 %.

Can robots in classroom reshape K-12 STEM education, and foster new ways of learning? To sketch an answer, this article reviews, side-by-side, existing literature on robot-based learning activities featuring mathematics and physics (purposefully putting aside the well-studied field of “robots to teach robotics”) and existing robot platforms and toolkits suited for classroom environment (in terms of cost, ease of use, orchestration load for the teacher, etc.). Our survey suggests that the use of robots in classroom has indeed moved from purely technology to education, to encompass new didactic fields. We however identified several shortcomings, in terms of robotic platforms and teaching environments, that contribute to the limited presence of robotics in existing curricula; the lack of specific teacher training being likely pivotal. Finally, we propose an educational framework merging the tangibility of robots with the advanced visibility of augmented reality.