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Importance: Previous studies on the comparative effectiveness between buprenorphine and methadone provided limited evidence on differences in treatment effects across key subgroups and were drawn from populations who use primarily heroin or prescription opioids, although fentanyl use is increasing across North America., Objective: To assess the risk of treatment discontinuation and mortality among individuals receiving buprenorphine/naloxone vs methadone for the treatment of opioid use disorder., Design, Setting, and Participants: Population-based retrospective cohort study using linked health administrative databases in British Columbia, Canada. The study included treatment recipients between January 1, 2010, and March 17, 2020, who were 18 years or older and not incarcerated, pregnant, or receiving palliative cancer care at initiation., Exposures: Receipt of buprenorphine/naloxone or methadone among incident (first-time) users and prevalent new users (including first and subsequent treatment attempts)., Main Outcomes and Measures: Hazard ratios (HRs) with 95% compatibility (confidence) intervals were estimated for treatment discontinuation (lasting ≥5 days for methadone and ≥6 days for buprenorphine/naloxone) and all-cause mortality within 24 months using discrete-time survival models for comparisons of medications as assigned at initiation regardless of treatment adherence ("initiator") and received according to dosing guidelines (approximating per-protocol analysis)., Results: A total of 30 891 incident users (39% receiving buprenorphine/naloxone; 66% male; median age, 33 [25th-75th, 26-43] years) were included in the initiator analysis and 25 614 in the per-protocol analysis. Incident users of buprenorphine/naloxone had a higher risk of treatment discontinuation compared with methadone in initiator analyses (88.8% vs 81.5% discontinued at 24 months; adjusted HR, 1.58 [95% CI, 1.53-1.63]), with limited change in estimates when evaluated at optimal dose in per-protocol analysis (42.1% vs 30.7%; adjusted HR, 1.67 [95% CI, 1.58-1.76]). Per-protocol analyses of mortality while receiving treatment exhibited ambiguous results among incident users (0.08% vs 0.13% mortality at 24 months; adjusted HR, 0.57 [95% CI, 0.24-1.35]) and among prevalent users (0.08% vs 0.09%; adjusted HR, 0.97 [95% CI, 0.54-1.73]). Results were consistent after the introduction of fentanyl and across patient subgroups and sensitivity analyses., Conclusions and Relevance: Receipt of methadone was associated with a lower risk of treatment discontinuation compared with buprenorphine/naloxone. The risk of mortality while receiving treatment was similar for buprenorphine/naloxone and methadone, although the CI estimate for the hazard ratio was wide.

Background: HCV infection is associated with mortality due to extrahepatic manifestations (EHM). Sustained virologic response (SVR) following direct-acting antiviral (DAA) therapy has been linked to decreased all-cause and liver-related mortality. However, evidence regarding the impact of DAA on EHM-related deaths is lacking. This study aimed to assess the impact of DAA and SVR on EHM-related mortality., Methods: The British Columbia Hepatitis Testers Cohort comprises ∼1.7 million people tested for HCV between 1990 and 2015 and is linked with administrative health data. Among individuals diagnosed with HCV by 12/31/2020, those who received at least one DAA treatment were matched to those who never received treatment by the year of their first HCV RNA positive date. We compared three groups: treated & SVR, treated & no-SVR, and untreated; and generated EHM mortality rates and incidence curves. To account for differences in baseline characteristics, we used inverse probability of treatment weights (IPTW). IPTW-weighted multivariable cause-specific Cox regression models were adjusted for competing risk and confounders., Findings: Study population included 12,815 treated (12,287 SVR, 528 no-SVR) and 12,815 untreated individuals (median follow-up 3.4 years, IQR 2.9). The untreated group had the highest EHM mortality rate (30.9 per 1000 person-years [PY], 95% CI 29.2-32.8), followed by the treated & no-SVR group (21.2 per 1000 PY, 95% CI 14.9-30.1), while the treated & SVR group had the lowest EHM mortality rate (7.9 per 1000 PY, 95% CI 7.1-8.7). In the multivariable model, EHM mortality in the treated & SVR group was significantly decreased (adjusted cause-specific hazard ratio [acsHR] 0.20, 95% CI 0.18-0.23). The treated & SVR group had significant reductions in mortality related to each of the EHMs (78-84%)., Interpretation: Treatment of HCV with DAA was associated with significant reductions in EHM-related mortality. These findings emphasize the critical importance of timely diagnosis and treatment of HCV to prevent deaths associated with EHM, and have important implications for clinical practice and public health., Funding: This work was supported by the BC Centre for Disease Control and the Canadian Institutes of Health Research (CIHR) [Grant # NHC-348216, PJT-156066, and PHE-337680]. DJ has received Doctoral Research Award (#201910DF1-435705-64343) from the Canadian Institutes of Health Research (CIHR) and Doctoral fellowship from the Canadian Network on Hepatitis C (CanHepC). CanHepC is funded by a joint initiative of the Canadian Institutes of Health Research (CIHR) (NHC-142832) and the Public Health Agency of Canada (PHAC)., Competing Interests: MK has received grant/research support from Roche, Merck, Siemens, Boeringer Ingelheim and Hologic. SRB has consulted for Cepheid, Gilead, and Abbvie, but no personal payments accepted, and has received investigator-initiated grants from Gilead and Abbvie through her institution. NZJ participated in advisory boards and has spoken for AbbVie and Gilead, not related to current work. DJ, SW, MEK, ARM, JDM, HAVG, DL, PA, MB and AY have no conflicts of interest to declare., (© 2023 The Author(s).)

Background: We examined the 11 month longitudinal antibody decay among two-dose mRNA vaccinees, and identified factors associated with faster decay., Methods: The study included samples from the COVID-19 Occupational Risk, Seroprevalence and Immunity among Paramedics (CORSIP) longitudinal observational study of paramedics in Canada. Participants were included if they had received two mRNA vaccines without prior SARS-CoV-2 infection and provided two blood samples post-vaccination. The outcomes of interest were quantitative SARS-CoV-2 antibody concentrations. We employed spaghetti and scatter plots (with kernel-weighted local polynomial smoothing curve) to describe the trend of the antibody decay over 11 months post-vaccine and fit a mixed effect exponential decay model to examine the loss of immunogenicity and factors associated with antibody waning over time., Results: This analysis included 652 blood samples from 326 adult paramedics. Total anti-spike antibody levels peaked on the twenty-first day (antibody level 9042 U ml -1 ) after the second mRNA vaccine dose. Total anti-spike antibody levels declined thereafter, with a half-life of 94 [95 % CI: 70, 143] days, with levels plateauing at 295 days (antibody level 1021 U ml -1 ). Older age, vaccine dosing interval <35 days, and the BNT162b2 vaccine (compared to mRNA-1273 vaccine) were associated with faster antibody decay., Conclusion: Antibody levels declined after the initial mRNA series with a half-life of 94 days, plateauing at 295 days. These findings may inform the timing of booster vaccine doses and identifying individuals with faster antibody decay., Competing Interests: The authors declare no conflict of interest., (© 2023 The Authors.)

Background: Cognitive impairment occurs in 40%-70% of persons with multiple sclerosis (MS)., Objective: To examine the effectiveness of natalizumab compared with other disease-modifying treatments (DMTs) on improving cognition as measured by the Symbol Digit Modalities Test (SDMT)., Methods: Data were collected as part of Swedish nationwide phase IV surveillance studies (2007-2020). An increase in SDMT score by ⩾10% of the difference between maximum score possible (110) and the baseline value was defined as cognitive improvement. The likelihood of improvement was compared between natalizumab-treated individuals and individuals treated with other DMTs using mixed effect logistic regression. Trend in odds of improvement was investigated using slope analyses., Results: We included 2100 persons with relapsing-remitting MS treated with natalizumab and 2622 persons treated with other DMTs. At 6 months, 45% reached improvement. The natalizumab group showed largest odds of improvement during follow-up (odds ratio: 2.3, 95% confidence interval (CI): 1.5-3.5). The odds of improvement increased by 7% (95% CI: 6-7) per month of natalizumab treatment. The equivalent estimate was 4% (95% CI: 2-5) for other monoclonal antibodies and nonsignificant for oral or platform therapies., Conclusion: Treatment with natalizumab or other monoclonal antibodies is associated with a significantly faster likelihood of cognitive improvement than platform or oral DMTs.

Objectives: Multimorbidity is the presence of two or more chronic health conditions. Tuberculosis (TB) survivors are known to have higher prevalence of multimorbidity, although prevalence estimates from high-income low-TB incidence jurisdictions are not available and potential differences in the patterns of chronic disease among TB survivors with multimorbidity are poorly understood. In this study, we aimed to (1) compare the prevalence of multimorbidity among TB survivors with matched non-TB controls in a high-income setting; (2) assess the robustness of aim 1 analyses to different modelling strategies, unmeasured confounding, and misclassification bias; and (3) among people with multimorbidity, elucidate chronic disease patterns specific to TB survivors., Methods: A population-based cohort study of people immigrating to British Columbia, Canada, 1985-2015, using health administrative data. Participants were divided into two groups: people diagnosed with TB (TB survivors) and people not diagnosed with TB (non-TB controls) in British Columbia. Coarsened exact matching (CEM) balanced demographic, immigration, and socioeconomic covariates between TB survivors and matched non-TB controls. Our primary outcome was multimorbidity, defined as ≥2 chronic diseases from the Elixhauser comorbidity index., Results: In the CEM-matched sample (n=1962 TB survivors; n=1962 non-TB controls), we estimated that 21.2% of TB survivors (n=416), compared with 12% of non-TB controls (n=236), had multimorbidity. In our primary analysis, we found a double-adjusted prevalence ratio of 1.74 (95% CI: 1.49-2.05) between TB survivors and matched non-TB controls for multimorbidity. Among people with multimorbidity, differences were observed in chronic disease frequencies between TB survivors and matched controls., Conclusion: TB survivors had a 74% higher prevalence of multimorbidity compared with CEM-matched non-TB controls. TB-specific multimorbidity patterns were observed through differences in chronic disease frequencies between the matched samples. These findings suggest a need for TB-specific multimorbidity interventions in high-income settings such as Canada. We suggest TB survivorship as a framework for developing person-centred interventions for multimorbidity among TB survivors., (© 2022. The Author(s) under exclusive license to The Canadian Public Health Association.)

Purpose: to directly compare the risk of neonatal death between traditional birth attendant (TBA)-assisted and unassisted deliveries in Nigeria., Methods: Using data on live births from the 2008, 2013, and 2018 Nigeria Demographic and Health Surveys, this cross-sectional study compared risk of neonatal death for TBA-assisted versus unassisted births. We used survey-featured logistic regression to estimate the odds of neonatal death. Survey year-stratified and propensity score-matched (PSM) estimates were obtained. Multivariate imputation by chained equation (MICE) for missing data was conducted., Results: A total of 28, 922 births were included. Regression and PSM analysis of pooled data showed that unassisted births had lower odds of neonatal death compared to TBA-assisted births, (aOR 0.81, 95% CI: 0.65,1.00) and (aOR 0.80, 95% CI: 0.64,1.00), respectively. Regression analysis by survey year yielded non-significant higher odds of neonatal death for TBA-assisted births. Pooled estimates from MICE showed non-significant higher odds of death for TBA-assisted births., Conclusions: These findings indicate that birth care by TBAs do not necessarily lead to better neonatal survival. Jurisdictions seeking to allow continued operation of TBAs need to consider measures such as training, supervision, and regulation to ensure the safety of newborns., (Copyright © 2022 Elsevier Inc. All rights reserved.)

The optimal dosing interval for severe acute respiratory syndrome coronavirus 2 vaccines remains controversial. In this prospective study, we compared serology results of paramedics vaccinated with mRNA vaccines at the recommended short (17-28 days) vs long (42-49 days) interval. We found that a long dosing interval resulted in higher spike, receptor binding domain, and spike N terminal domain antibody concentrations., (© The Author(s) 2021. Published by Oxford University Press for the Infectious Diseases Society of America. All rights reserved. For permissions, e-mail: journals.permissions@oup.com.)

Background: With many disease-modifying therapies currently approved for the management of multiple sclerosis, there is a growing need to evaluate the comparative effectiveness and safety of those therapies from real-world data sources. Propensity score methods have recently gained popularity in multiple sclerosis research to generate real-world evidence. Recent evidence suggests, however, that the conduct and reporting of propensity score analyses are often suboptimal in multiple sclerosis studies., Objectives: To provide practical guidance to clinicians and researchers on the use of propensity score methods within the context of multiple sclerosis research., Methods: We summarize recommendations on the use of propensity score matching and weighting based on the current methodological literature, and provide examples of good practice., Results: Step-by-step recommendations are presented, starting with covariate selection and propensity score estimation, followed by guidance on the assessment of covariate balance and implementation of propensity score matching and weighting. Finally, we focus on treatment effect estimation and sensitivity analyses., Conclusion: This comprehensive set of recommendations highlights key elements that require careful attention when using propensity score methods.

Study Objective: SARS-CoV-2 represents an occupational risk to paramedics, who work in uncontrolled environments. We sought to identify the occupation-specific risk to paramedics by comparing their seroprevalence of SARS-CoV-2 infection-specific antibodies to that of blood donors in Canada., Methods: In this prospective cohort study, we performed serology testing (Elecsys Anti-SARS-CoV-2 nucleocapsid assay) on samples from paramedics and blood donors (January to July 2021) in Canada. Paramedic samples were compared to blood donor samples through 1:1-matched (based on age, sex, location, date of blood collection, and vaccination status) and raking weighted comparisons. We compared the seroprevalence with a risk difference (and 95% confidence interval [CI]) and performed secondary analyses within subgroups defined by vaccination status., Results: The 1:1 match included 1,627 cases per group; in both groups, 723 (44%) were women, with a median age of 38. The raking weighted comparison included 1,713 paramedic samples and 19,515 blood donor samples, with similar characteristics. In the 1:1 match, the seroprevalence was similar (difference 1.2; 95% CI -0.20 to 2.7) between paramedics (5.2%) and blood donors (3.9%). The raking weighted comparison was consistent (difference 0.97; 95% CI -0.10 to 2.0). The unvaccinated paramedic samples, in comparison to the blood donor samples, demonstrated a higher seroprevalence in the 1:1 (difference 5.9; 95% CI 1.8 to 10) and weighted (difference 6.5; 95% CI 1.8 to 10) comparisons. Among vaccinated cases, the between-group seroprevalence was similar., Conclusion: Overall, paramedics demonstrated similar evidence of prior SARS-CoV-2 infection to that of blood donors. However, among unvaccinated individuals, evidence of prior infection was higher among paramedics compared to blood donors., (Copyright © 2022 American College of Emergency Physicians. Published by Elsevier Inc. All rights reserved.)

Purpose: To explore the rheumatoid arthritis (RA)-cardiovascular diseases (CVD) association in relative and absolute risk scales among US adults aged ≥20 years over time and the effect modification of the association by age., Methods: We analyzed aggregated data from all ten continuous National Health and Nutrition Examination Survey cycles. A sample of 35,062 complete-case subjects was considered. The design-based regressions were used to investigate the associations in relative and absolute scales., Results: In relative scale, the CVD odds ratio was 2.32, 2.19, and 1.97 among adults with RA than no arthritis in 1999-2006, 2007-2012, and 2013-2018 cycles, respectively. This time trend was not statistically significant. The absolute risk estimates were 11, 10, and 9 per 100 CVD events. We also observed a significant effect modification by age; the higher relative risk among younger adults (<50 years) with RA and higher absolute risk in older adults (≥80 years) with RA were consistent across survey cycles., Conclusions: There is a significant association between RA and CVD among US adults in both relative and absolute risks. Moreover, age is a significant effect modifier for this association; but with opposing age-related trends in relative and absolute scales., (Copyright © 2022. Published by Elsevier Inc.)

Introduction: Unmeasured confounding poses a serious threat to observational studies of post-TB health outcomes. E-values have been recently proposed as a method to assess the magnitude of unmeasured confounding necessary to nullify, or to render non-significant, relative effect estimates from observational studies., Methods: We calculated E-values for both the risk ratio (RR) point estimates and their lower 95% confidence limits (LCL) from studies of post-TB mortality, respiratory disease, and cardiovascular disease (CVD) included in published systematic reviews within and across post-TB outcome domains. We also employed a meta-analytic E-value approach to estimate the proportion of unconfounded study RRs greater than 1.1 at different levels of unmeasured confounding., Results: Across post-TB health outcome domains, we observed a median E-value of 5.59 (IQR = 3.19-7.35) for RRs, and 2.95 (IQR = 1.71-4.61) for LCLs. Post-TB mortality studies had higher median E-values (E-value RR  = 6.90 and E-value LCL  = 4.54) than studies of respiratory disease (E-value RR  = 5.59, E-value LCL  = 2.94) or CVD (E-value RR  = 3.90, E-value LCL  = 1.81). The E-value at which the estimated proportion of studies with unconfounded RRs greater than 1.1 would remain over 0.7 was 3.45 for post-TB mortality, 3.96 for post-TB respiratory disease, and 1.71 for post-TB CVD meta-analyses., Conclusions: Unmeasured confounding with an association of 2.95 or greater with both the exposure (TB) and outcome, on the risk ratio scale, could render most post-TB health studies' findings statistically non-significant. Post-TB mortality and respiratory disease studies had higher E-values than TB-CVD studies, indicating that either (a) TB-CVD studies may be more susceptible to unmeasured confounding bias, or (b) the true effect of TB on CVD is lower., Competing Interests: Declaration of Competing Interest CAB declares no conflicts or competing interests. MEK has received consulting fees from Biogen, Inc., unrelated to this manuscript., (Copyright © 2021 Elsevier Inc. All rights reserved.)

Purpose: To examine the association between diabetes and excessive daytime sleepiness (EDS)., Methods: Using the 2015-2018 cycles of the National Health and Nutrition Examination Survey, we applied survey-featured modified Poisson regression to estimate the association between diabetes and EDS among American adults aged 20-79 years, adjusting for confounding demographic, clinical and lifestyle variables. Effect modification by age, sex, race, education, income, sleep apnea and inadequate sleep was assessed. We performed sensitivity analyses using propensity score matched (PS) data and applied ordinal logistic regression using multiple levels of daytime sleepiness. Among people with diabetes, we assessed the association between EDS and diabetes care variables., Results: Of the 6289 participants, 895 (10%) had diabetes. The estimated prevalence of EDS was higher among adults with diabetes (30.6%) than counterparts without diabetes (26.3%). After adjusting for confounding variables, diabetes remained associated with EDS (aPR:1.20; 95%CI:1.06 1.36). There was no statistically significant effect modification. Sensitivity analyses confirmed our main results. Among people with diabetes, there was limited evidence that the diabetes care variables were related to EDS., Conclusions: Among American adults, diabetes is associated with EDS after controlling for confounding variables. Although the cross-sectional design is a limitation, our findings support further exploration of the role of diabetes in EDS., Competing Interests: Declaration of interests The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 Elsevier Inc. All rights reserved.)

Background and Purpose: Studies of carotid endarterectomy (CEA) require stratification by symptomatic vs asymptomatic status because of marked differences in benefits and harms. In administrative datasets, this classification has been done using hospital discharge diagnosis codes of uncertain accuracy. This study aims to develop and evaluate algorithms for classifying symptomatic status using hospital discharge and physician claims data., Methods: A single center's administrative database was used to assemble a retrospective cohort of participants with CEA. Symptomatic status was ascertained by chart review prior to linkage with physician claims and hospital discharge data. Accuracy of rule-based classification by discharge diagnosis codes was measured by sensitivity and specificity. Elastic net logistic regression and random forest models combining physician claims and discharge data were generated from the training set and assessed in a test set of final year participants. Models were compared to rule-based classification using sensitivity at fixed specificity., Results: We identified 971 participants undergoing CEA at the Vancouver General Hospital (Vancouver, Canada) between January 1, 2008 and December 31, 2016. Of these, 729 met inclusion/exclusion criteria (n = 615 training, n = 114 test). Classification of symptomatic status using hospital discharge diagnosis codes was 32.8% (95% CI 29-37%) sensitive and 98.6% specific (96-100%). At matched 98.6% specificity, models that incorporated physician claims data were significantly more sensitive: elastic net 69.4% (59-82%) and random forest 78.8% (69-88%)., Conclusion: Discharge diagnoses were specific but insensitive for the classification of CEA symptomatic status. Elastic net and random forest machine learning algorithms that included physician claims data were sensitive and specific, and are likely an improvement over current state of classification by discharge diagnosis alone., (© 2022. The Author(s).)

Background: Two-stage least square [2SLS] and two-stage residual inclusion [2SRI] are popularly used instrumental variable (IV) methods to address medication nonadherence in pragmatic trials with point treatment settings. These methods require assumptions, e.g., exclusion restriction, although they are known to handle unmeasured confounding. The newer IV-method, nonparametric causal bound [NPCB], showed promise in reducing uncertainty compared to usual IV-methods. The inverse probability-weighted per-protocol [IP-weighted PP] method is useful in the same setting but requires different assumptions, e.g., no unmeasured confounding. Although all of these methods are aimed to address the same nonadherence problem, comprehensive simulations to compare performances of them are absent in the literature., Methods: We performed extensive simulations to compare the performances of the above methods in addressing nonadherence when: (1) exclusion restriction satisfied and no unmeasured confounding, (2) exclusion restriction is met but unmeasured confounding present, and (3) exclusion restriction is violated. Our simulations varied parameters such as, levels of adherence rates, unmeasured confounding, and exclusion restriction violations. Risk differences were estimated, and we compared performances in terms of bias, standard error (SE), mean squared error (MSE), and 95% confidence interval coverage probability., Results: For setting (1), 2SLS and 2SRI have small bias and nominal coverage. IP-weighted PP outperforms these IV-methods in terms of smaller MSE but produces high MSE when nonadherence is very high. For setting (2), IP-weighted-PP generally performs poorly compared to 2SLS and 2SRI in term of bias, and both-stages adjusted IV-methods improve precision than naive IV-methods. For setting (3), IV-methods perform worst in all scenarios, and IP-weighted-PP produces unbiased estimates and small MSE when confounders are adjusted. NPCB produces larger uncertainty bound width in almost all scenarios. We also analyze a two-arm trial to estimate vitamin-A supplementation effect on childhood mortality after addressing nonadherence., Conclusions: Understanding finite sample characteristics of these methods will guide future researchers in determining suitable analysis strategies. Since assumptions are different and often untestable for IP-weighted PP and IV methods, we suggest analyzing data using both IP-weighted PP and IV approaches in search of a robust conclusion., (© 2022. The Author(s).)

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 6721 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., (Copyright © 2021 Elsevier B.V. All rights reserved.)

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., (Copyright © 2021 Elsevier Inc. All rights reserved.)

Background: The attained power, calculated conditional on the realized allocation, of a clinical trial may differ from the expected power, obtained pre-randomization through averaging over all potential allocations that could be generated by the randomization algorithm (RA). For example, a two-arm trial using a RA that is expected to allocate 20 participants to each arm will attain less than the expected power if by chance it allocates 25 and 15 participants to the arms. Cluster randomized trials with unequal cluster sizes have elevated risk of realizing an allocation that yields an attained power much lower than the expected power when modest numbers of clusters are randomized., Method: We developed the R package CRTpowerdist, which implements both simulations and approximate analytic formulae to calculate the attained powers associated with different realized allocations and constructs the pre-randomization power distribution associated with the RA to facilitate assessing the risk of obtaining inadequate power. The package covers unequal cluster-size, cross-sectional stepped-wedge and parallel cluster randomized trials, with or without stratification. Allowed outcome types are: continuous (Gaussian), binary (Binomial) and count (Poisson). The analytic formulae-based calculations are also implemented in a Shiny app., Results: The functionality of the CRTpowerdist is illustrated for each type of trial design. The examples show how to obtain the attained power, the power distribution, and the risk of low attained power, using both simulation and analytic formulae., Conclusion: For cluster randomized trials with unequal cluster sizes, the CRTpowerdist package can assist users in identifying an appropriate randomization algorithm by enabling the user to assess the risk that a randomization algorithm will lead to an allocation with inadequate attained power. The Shiny app makes these assessments accessible to researchers who are unable or do not wish to use the CRTpowerdist package., Competing Interests: Declaration of Competing Interest All authors have no competing interest to declare., (Copyright © 2021. Published by Elsevier B.V.)

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., (© 2021. The Author(s).)

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., (© The Author(s) 2020. Published by Oxford University Press on behalf of the Johns Hopkins Bloomberg School of Public Health. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

Background: The 2018 World Health Organization HIV guidelines were based on the results of a network meta-analysis (NMA) of published trials. This study employed individual patient-level data (IPD) and aggregate data (AgD) and meta-regression methods to assess the evidence supporting the WHO recommendations and whether they needed any refinements., Methods: Access to IPD from three trials was granted through ClinicalStudyDataRequest.com (CSDR). Seven modelling approaches were applied and compared: 1) Unadjusted AgD network meta-analysis (NMA) - the original analysis; 2) AgD-NMA with meta-regression; 3) Two-stage IPD-AgD NMA; 4) Unadjusted one-stage IPD-AgD NMA; 5) One-stage IPD-AgD NMA with meta-regression (one-stage approach); 6) Two-stage IPD-AgD NMA with empirical-priors (empirical-priors approach); 7) Hierarchical meta-regression IPD-AgD NMA (HMR approach). The first two were the models used previously. Models were compared with respect to effect estimates, changes in the effect estimates, coefficient estimates, DIC and model fit, rankings and between-study heterogeneity., Results: IPD were available for 2160 patients, representing 6.5% of the evidence base and 3 of 24 edges. The aspect of the model affected by the choice of modeling appeared to differ across outcomes. HMR consistently generated larger intervals, often with credible intervals (CrI) containing the null value. Discontinuations due to adverse events and viral suppression at 96 weeks were the only two outcomes for which the unadjusted AgD NMA would not be selected. For the first, the selected model shifted the principal comparison of interest from an odds ratio of 0.28 (95% CrI: 10.17, 0.44) to 0.37 (95% CrI: 0.23, 0.58). Throughout all outcomes, the regression estimates differed substantially between AgD and IPD methods, with the latter being more often larger in magnitude and statistically significant., Conclusions: Overall, the use of IPD often impacted the coefficient estimates, but not sufficiently as to necessitate altering the final recommendations of the 2018 WHO Guidelines. Future work should examine the features of a network where adjustments will have an impact, such as how much IPD is required in a given size of network.

Objective: 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., Methods: 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., Results: 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)., Conclusions: 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.

Background: The use of individual patient data (IPD) in network meta-analyses (NMA) is rapidly growing. This study aimed to determine, through simulations, the impact of select factors on the validity and precision of NMA estimates when combining IPD and aggregate data (AgD) relative to using AgD only., Methods: Three analysis strategies were compared via simulations: 1) AgD NMA without adjustments (AgD-NMA); 2) AgD NMA with meta-regression (AgD-NMA-MR); and 3) IPD-AgD NMA with meta-regression (IPD-NMA). We compared 108 parameter permutations: number of network nodes (3, 5 or 10); proportion of treatment comparisons informed by IPD (low, medium or high); equal size trials (2-armed with 200 patients per arm) or larger IPD trials (500 patients per arm); sparse or well-populated networks; and type of effect-modification (none, constant across treatment comparisons, or exchangeable). Data were generated over 200 simulations for each combination of parameters, each using linear regression with Normal distributions. To assess model performance and estimate validity, the mean squared error (MSE) and bias of treatment-effect and covariate estimates were collected. Standard errors (SE) and percentiles were used to compare estimate precision., Results: Overall, IPD-NMA performed best in terms of validity and precision. The median MSE was lower in the IPD-NMA in 88 of 108 scenarios (similar results otherwise). On average, the IPD-NMA median MSE was 0.54 times the median using AgD-NMA-MR. Similarly, the SEs of the IPD-NMA treatment-effect estimates were 1/5 the size of AgD-NMA-MR SEs. The magnitude of superior validity and precision of using IPD-NMA varied across scenarios and was associated with the amount of IPD. Using IPD in small or sparse networks consistently led to improved validity and precision; however, in large/dense networks IPD tended to have negligible impact if too few IPD were included. Similar results also apply to the meta-regression coefficient estimates., Conclusions: Our simulation study suggests that the use of IPD in NMA will considerably improve the validity and precision of estimates of treatment effect and regression coefficients in the most NMA IPD data-scenarios. However, IPD may not add meaningful validity and precision to NMAs of large and dense treatment networks when negligible IPD are used.

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., Competing Interests: Dr. Karim reports grants from Michael Smith Foundation for Health Research, grants from Natural Sciences and Engineering Research Council, grants from BC SUPPORT Unit, grants from Canadian Institutes of Health Research, personal fees from Biogen Inc., outside the submitted work. Dr. Alexandra reports grants from Unrestriceted Educational Grant (for the Unit) by MSD and Gilead Sciences, grants from Financial support by Gilead Sciences, AbbVie, MSD, ViiV Healthcare and Janssen Cilag for the day hospital, outside the submitted work. All other authors have nothing to declare., (© 2020 Published by Elsevier Ltd.)

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: In a cross-sectional stepped-wedge trial with unequal cluster sizes, attained power in the trial depends on the realized allocation of the clusters. This attained power may differ from the expected power calculated using standard formulae by averaging the attained powers over all allocations the randomization algorithm can generate. We investigated the effect of design factors and allocation characteristics on attained power and developed models to predict attained power based on allocation characteristics., Method: Based on data simulated and analyzed using linear mixed-effects models, we evaluated the distribution of attained powers under different scenarios with varying intraclass correlation coefficient (ICC) of the responses, coefficient of variation (CV) of the cluster sizes, number of cluster-size groups, distributions of group sizes, and number of clusters. We explored the relationship between attained power and two allocation characteristics: the individual-level correlation between treatment status and time period, and the absolute treatment group imbalance. When computational time was excessive due to a scenario having a large number of possible allocations, we developed regression models to predict attained power using the treatment-vs-time period correlation and absolute treatment group imbalance as predictors., Results: The risk of attained power falling more than 5% below the expected or nominal power decreased as the ICC or number of clusters increased and as the CV decreased. Attained power was strongly affected by the treatment-vs-time period correlation. The absolute treatment group imbalance had much less impact on attained power. The attained power for any allocation was predicted accurately using a logistic regression model with the treatment-vs-time period correlation and the absolute treatment group imbalance as predictors., Conclusion: In a stepped-wedge trial with unequal cluster sizes, the risk that randomization yields an allocation with inadequate attained power depends on the ICC, the CV of the cluster sizes, and number of clusters. To reduce the computational burden of simulating attained power for allocations, the attained power can be predicted via regression modeling. Trial designers can reduce the risk of low attained power by restricting the randomization algorithm to avoid allocations with large treatment-vs-time period correlations.

The present study examined the association of residential instability with hospitalizations among homeless and vulnerably housed individuals over a 4-year time period. Survey data were linked to administrative records on hospitalizations. Specifically, we used data from the Health and Housing in Transition study, a prospective cohort study that tracked the health and housing status of homeless and vulnerably housed individuals in Canada. Responses from Vancouver-based participants (n = 378) from baseline and 3 follow-ups were linked to their administrative health records on hospitalizations (Discharge Abstract Database - Hospital Separation Files; 2008-2012). A generalized estimating equations model was used to examine associations between the number of residential moves and any hospitalizations during each year (none versus ≥ 1 hospitalizations). Analyses included demographic and health variables. Survey data were collected via structured interviews. Hospitalizations were derived from provincial administrative health records. A higher number of residential moves were associated with hospitalization over the study period (adjusted odds ratio: 1.14; 95% confidence interval: 1.01, 1.28). Transgender, female gender, perceived social support, better self-reported mental health, and having ≥ 3 chronic health conditions also predicted having been hospitalized over the study period, whereas high school/higher education was negatively associated with hospitalizations. Our results indicate that residential instability is associated with increased risk of hospitalization, illustrating the importance of addressing housing as a social determinant of health.

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.

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: 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., Competing Interests: Competing interests: Robert Quinn has a patent issued, for a Dialysis Measurement Analysis and Reporting system — a Web-based data collection system to measure performance in dialysis programs. Mohammed Karim reports grants from the BC SUPPORT Unit, Michael Smith Foundation for Health Research and Natural Sciences and Engineering Research Council of Canada, and personal fees from Biogen Inc., outside the submitted work. No other competing interests were declared., (© 2019 Joule Inc. or its licensors.)

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.