ObjectivesAn obstetric comorbidity index has been developed recently with superior performance characteristics relative to general comorbidity measures in an obstetric population. This study aimed to externally validate this index and to examine the impact of including hospitalisation/delivery records only when estimating comorbidity prevalence and discriminative performance of the obstetric comorbidity index.DesignValidation study.SettingAlberta, Canada.PopulationPregnant women who delivered a live or stillborn infant in hospital (n = 5995).MethodsAdministrative databases were linked to create a population‐based cohort. Comorbid conditions were identified from diagnoses for the delivery hospitalisation, all hospitalisations and all healthcare contacts (i.e. hospitalisations, emergency room visits and physician visits) that occurred during pregnancy and 3 months pre‐conception. Logistic regression was used to test the discriminative performance of the comorbidity index.Main outcome measuresMaternal end‐organ damage and extended length of stay for delivery.ResultsAlthough prevalence estimates for comorbid conditions were consistently lower in delivery records and hospitalisation data than in data for all healthcare contacts, the discriminative performance of the comorbidity index was constant for maternal end‐organ damage [all healthcare contacts area under the receiver operating characteristic curve (AUC) = 0.70; hospitalisation data AUC = 0.67; delivery data AUC = 0.65] and extended length of stay for delivery (all healthcare contacts AUC = 0.60; hospitalisation data AUC = 0.58; delivery data AUC = 0.58).ConclusionsThe obstetric comorbidity index shows similar performance characteristics in an external population and is a valid measure of comorbidity in an obstetric population. Furthermore, the discriminative performance of the comorbidity index was similar for comorbidities ascertained at the time of delivery, in hospitalisation data or through all healthcare contacts.

Individuals with IMID, including IBD, MS and RA are at increased risk of psychiatric comorbidity. This increased risk appears non-specific as it is seen for all three IMIDs and for all psychiatric disorders studied, implying a common underlying biology for psychiatric comorbidity in those with IMID.

BackgroundImmune-mediated inflammatory diseases (IMID), such as inflammatory bowel disease (IBD), multiple sclerosis (MS), and rheumatoid arthritis (RA), are highly prevalent in Canada and the United States and result in substantial personal and societal burden. The prevalence of psychiatric comorbidities, primarily depression and anxiety, in IMID exceeds those in the general population by two- to threefold, but remains underdiagnosed and undertreated. Furthermore, the effects of psychiatric comorbidity on IMID are not well understood.ObjectiveThe objectives of this study were (1) to compare health-related quality of life and work ability in persons with IMID and psychiatric comorbidity with those of persons with IMID without psychiatric comorbidity and with those of persons with depression and anxiety disorders alone, and (2) to validate existing case identification tools for depression and anxiety in persons with IMID to facilitate improved identification of depression and anxiety by clinicians. To achieve these objectives, we designed a prospective 3-year longitudinal study. In this paper, we aim to describe the study rationale and design and the characteristics of study participants.MethodsBetween November 2014 and July 2016, we recruited 982 individuals from multiple clinic and community sources; 18 were withdrawn due to protocol violations.ResultsThe final study sample included 247 participants with IBD, 255 with MS, 154 with RA, and 308 with depression or anxiety. The majority were white, with the proportion ranging from 85.4% (IBD [210/246]; MS [217/254]) to 74.5% (114/153, RA; P=.01). There was a female predominance in all groups, which was highest in the RA cohort (84.4%, 130/154) and least marked in the IBD cohort (62.7%, 155/247). Participants with depression or anxiety were more likely to be single (36.0%, 111/308) than participants in any other group (11.8% [30/255]-22.7% [56/247], P<.001).ConclusionsThis paper presents the rationale for this study, describes study procedures, and characterizes the cohort enrolled. Ultimately, the aim is improved care for individuals affected by IMID.

Objective To determine the safety of direct oral anticoagulant (DOAC) use compared with warfarin use for the treatment of venous thromboembolism. Design Retrospective matched cohort study conducted between 1 January 2009 and 31 March 2016. Setting Community based, using healthcare data from six jurisdictions in Canada and the United States. Participants 59 525 adults (12 489 DOAC users; 47 036 warfarin users) with a new diagnosis of venous thromboembolism and a prescription for a DOAC or warfarin within 30 days of diagnosis. Main outcome measures Outcomes included hospital admission or emergency department visit for major bleeding and all cause mortality within 90 days after starting treatment. Propensity score matching and shared frailty models were used to estimate adjusted hazard ratios of the outcomes comparing DOACs with warfarin. Analyses were conducted independently at each site, with meta-analytical methods used to estimate pooled hazard ratios across sites. Results Of the 59 525 participants, 1967 (3.3%) had a major bleed and 1029 (1.7%) died over a mean follow-up of 85.2 days. The risk of major bleeding was similar for DOAC compared with warfarin use (pooled hazard ratio 0.92, 95% confidence interval 0.82 to 1.03), with the overall direction of the association favouring DOAC use. No difference was found in the risk of death (pooled hazard ratio 0.99, 0.84 to 1.16) for DOACs compared with warfarin use. There was no evidence of heterogeneity across centres, between patients with and without chronic kidney disease, across age groups, or between male and female patients. Conclusions In this analysis of adults with incident venous thromboembolism, treatment with DOACs, compared with warfarin, was not associated with an increased risk of major bleeding or all cause mortality in the first 90 days of treatment. Trial registration Clinical trials NCT02833987.

Background Clinical registries, which capture information about the health and healthcare use of patients with a health condition or treatment, often contain patient-reported outcomes (PROs) that provide insights about the patient’s perspectives on their health. Missing data can affect the value of PRO data for healthcare decision-making. We compared the precision and bias of several missing data methods when estimating longitudinal change in PRO scores. Methods This research conducted analyses of clinical registry data and simulated data. Registry data were from a population-based regional joint replacement registry for Manitoba, Canada; the study cohort consisted of 5631 patients having total knee arthroplasty between 2009 and 2015. PROs were measured using the 12-item Short Form Survey, version 2 (SF-12v2) at pre- and post-operative occasions. The simulation cohort was a subset of 3000 patients from the study cohort with complete PRO information at both pre- and post-operative occasions. Linear mixed-effects models based on complete case analysis (CCA), maximum likelihood (ML) and multiple imputation (MI) without and with an auxiliary variable (MI-Aux) were used to estimate longitudinal change in PRO scores. In the simulated data, bias, root mean squared error (RMSE), and 95% confidence interval (CI) coverage and width were estimated under varying amounts and types of missing data. Results Three thousand two hundred thirty (57.4%) patients in the study cohort had complete data on the SF-12v2 at both occasions. In this cohort, mixed-effects models based on CCA resulted in substantially wider 95% CIs than models based on ML and MI methods. The latter two methods produced similar estimates and 95% CI widths. In the simulation cohort, when 50% of the data were missing, the MI-Aux method, in which a single hypothetical auxiliary variable was strongly correlated (i.e., 0.8) with the outcome, reduced the 95% CI width by up to 14% and bias and RMSE by up to 50 and 45%, respectively, when compared with the MI method. Conclusions Missing data can substantially affect the precision of estimated change in PRO scores from clinical registry data. Inclusion of auxiliary information in MI models can increase precision and reduce bias, but identifying the optimal auxiliary variable(s) may be challenging.