Association of alcohol consumption with selected cardiovascular disease outcomes: a systematic review and meta-analysis

Objective To conduct a comprehensive systematic review and meta-analysis of studies assessing the effect of alcohol consumption on multiple cardiovascular outcomes

Effect of alcohol consumption on biological markers associated with risk of coronary heart disease: systematic review and meta-analysis of interventional studies

Objective To systematically review interventional studies of the effects of alcohol consumption on 21 biological markers associated with risk of coronary heart disease in adults without known cardiovascular disease

Linking Emergency Medical Services and Health System Data: Optimal Strategy and Bias Mitigation

Introduction Emergency Medical Services (EMS) systems dispatch paramedics to emergencies in the community. For critically ill patients, paramedic interventions and transport destination decisions may impact outcomes. Research is needed to inform paramedic care, but linking EMS data to health system outcomes is a barrier. Limited research exists on EMS data linkage. Objectives and Approach To optimize linkage of EMS data (fiscal year 2016/17) to the National Ambulatory Care Reporting System/Sunrise Clinical Manager datasets and assess bias. A random sample of EMS records were deterministically linked on provincial health number (PHN), transport destination, and EMS/emergency department arrival/presentation times ≤2hrs. Linked data were manually verified using last name, sex, date of birth, and hospital file number. For patients that remained unlinked (based on the variables listed above), further linkage attempts were made using additional variables. The combination of variables that optimized sensitivity/positive predictive value/f-measure were used to link the fiscal year. Linked/unlinked groups were descriptively compared. Results While results are still pending (available April, 2018), we hypothesize that there may be inherent differences in the clinical and encounter characteristics of patients that were linked versus unlinked. Patient identifiers such as PHN and name are important for linkage, but are not always collected on EMS events that require immediate treatment and rapid transport, yet these patients may be the most critically ill. Conclusion/Implications As more EMS systems attempt to systematically link their data to health system outcome, these results will be important to mitigate potential bias

Using the Revised Cardiac Risk Index to predict major postoperative events for people with kidney failure : An external validation and update

Funding Information: T.G.H. is supported by a Kidney Research Scientist Core Education and National Training Program postdoctoral fellowship (cosponsored by the Kidney Foundation of Canada and Canadian Institutes of Health Research) and the Clinician Investigator Program at the University of Calgary. These funding sources had no role in study design, data collection, analysis, reporting, or the decision to submit for publication. Funding Information: Ethics Statement: We followed the Transparent Reporting of a Multivariable Prediction Model for Individual Prognosis or Diagnosis (TRIPOD) checklist19 for prediction-model validation (Supplemental Table S1) and were granted ethics approval by the University of Calgary and the University of Alberta.Preoperative risk-prediction tools that are used to predict risk of perioperative death and CV events, and are supported by North American guidelines, include the revised cardiac risk index (RCRI),5 the American College of Surgeons National Surgical Quality Improvement Program (ACS NSQIP) tool,6,7 and the National Surgical Quality Improvement Program Myocardial Infarction or Cardiac Arrest (NSQIP MICA) tool.8 The RCRI has been recommended over others for use in Canada for all adults over the age of 45 years, and for those aged 18-45 years with CV disease, who are undergoing elective, noncardiac surgery.3 The RCRI incorporates 6 criteria based on surgical and comorbidity characteristics of the patient and derives an estimated probability of postoperative myocardial infarction, cardiac arrest, or death.5 Additionally, the RCRI is used to guide perioperative decision-making.3The Alberta Kidney Disease Network database includes person-level linkages of administrative health data, laboratory data, prescription information, and kidney disease-specific data from the province of Alberta, Canada.17 Alberta has approximately 4.4 million residents, and with universal public health insurance, health data capture is near complete.17,18 From this database, we derived a retrospective cohort of adults with kidney failure who underwent ambulatory or inpatient surgery. We used this cohort to externally validate and examine the performance of the RCRI for this population. We followed the Transparent Reporting of a Multivariable Prediction Model for Individual Prognosis or Diagnosis (TRIPOD) checklist19 for prediction-model validation (Supplemental Table S1) and were granted ethics approval by the University of Calgary and the University of Alberta.Peer reviewedPublisher PD

Linking Antimicrobial Resistance Surveillance Data to Provincial Hospital Records: A Descriptive Study of Patient and Facility-level Characteristics

Introduction Antimicrobial resistance (AMR) is an emerging phenomenon where microorganisms develop resistance against treatment antimicrobials, resulting in ineffective clinical interventions. The recent development of AMR surveillance systems at global and national stages highlights the growing importance of this topic from a public health perspective. Objectives and Approach The objective was to link standardized population-based hospital AMR surveillance data with hospitalizationrecords to inform patient safety practices in Alberta, Canada. Incident inpatient cases of Methicillin-Resistant Staphylococcus aureus (MRSA),identified by Alberta Health Services Provincial Infection Prevention and Control(IPC) Surveillance from five acute care facilities in the Calgary zone (April 2011 to March 2016),were deterministically linked to the Discharge Abstract Database using Provincial Healthcare Number and gender. The incident cohort was stratified into hospital-acquired (HA-MRSA) and community-acquired MRSA (CA-MRSA) cases. Descriptive statistics were used to describe the patient outcomes and facility characteristics of these two groups. Results A total of 2550 unique patients, representing 93.5% of the surveillance cohort, were successfully linked to hospitalization records. A total of 1259 patients belonged to HA-MRSA categories and 1291 patients belonged to CA-MRSA categories. Patients with HA-MRSA had longer hospital stays, were older, were more likely to have prior hospitalizations, had higher Charlson Comorbidity Scores, and were more likely to die in hospital when compared to patients with CA-MRSA. HA-MRSA results emphasized the important roles of in-hospital patient safety practices whereas CA-MRSA results alluded to the impact of community public health and primary care services onthe risk of hospitalization, although detected CA-MRSA numbers were likely underestimated due to selection bias within our linked cohort. Conclusion/Implications This is first Canadian study describing HA-MRSA and CA-MRSA using linked population databases. It offers a glimpse into the intricate relationship between patient health and our healthcare system. This knowledge represents an important step forwarding building IPC strategies for managing AMR and improving outcomes in Alberta and in Canada

Prenatal allostatic load and preterm birth: A systematic review

Objective: Allostatic load refers to cumulative neuroendocrine burden and has been postulated to mediate and moderate physiological and psychological stress-related responses. This may have important implications for the risk of preterm birth. This systematic review examines the evidence on the association between prenatal allostatic load and preterm birth. Data sources: A comprehensive search of seven electronic databases was conducted from inception to August 23, 2022 to identify all English-language observational and mixed methods studies examining allostatic load and preterm birth with no year or geographic restrictions. Study eligibility criteria: Studies were included if they measured allostatic load, evaluated as the cumulative effect of any combination of more than one allostatic load biomarker, during pregnancy. Studies must have observed preterm birth, defined as \u3c 37 weeks\u27 gestational age, as a primary or secondary outcome of interest. Study appraisal and synthesis methods: The Quality In Prognosis Studies tool was used to evaluate risk of bias within included studies. A narrative synthesis was conducted to explore potential associations between allostatic load and preterm birth, and sources of heterogeneity. Results: Three prospective cohort studies were identified and revealed mixed evidence for an association between allostatic load and preterm birth. One study reported a statistically significant association while the other two studies reported little to no evidence for an association. Heterogeneity in when and how allostatic load was measured, limitations in study design and cohort socio-demographics may have contributed to the mixed evidence. Conclusions: This review provides insight into key individual-, community-, and study-level characteristics that may influence the association between allostatic load and preterm birth. Knowledge gaps are identified as foci for future research, including heterogeneity in allostatic load biomarkers and allostatic load index algorithms as well as pregnancy-specific considerations for allostatic load measurement. Further investigation of the allostatic load framework in the context of perinatal mental health is needed to advance understandings of maternal, infant, and child health

Harmonization of epidemiology of acute kidney injury and acute kidney disease produces comparable findings across four geographic populations

Acknowledgements: We acknowledge the support of the Grampian Data Safe Haven (DaSH) facility within the Aberdeen Centre for Health Data Science and the associated financial support of the University of Aberdeen, and NHS Research Scotland (through NHS Grampian investment in DaSH). For more information, visit the DaSH website: http://www.abdn.ac.uk/iahs/facilities/grampian-data-safe-haven.php Dr Sawhney is supported by a Starter Grant for Clinical Lecturers from the Academy of Medical Sciences, Wellcome Trust, Medical Research Council, British Heart Foundation, Arthritis Research UK, the Royal College of Physicians and Diabetes UK [SGL020\1076]. Drs James and Tonelli are supported by Canadian Institutes of Health Research Foundation Grants. Dr Black is supported by Health Data Research UK, which is funded by the UK Medical Research Council, Engineering and Physical Sciences Research Council, Economic and Social Research Council, Department of Health and Social Care (England), Chief Scientist Office of the Scottish Government Health and Social Care Directorates, Health and Social Care Research and Development Division (Welsh Government), Public Health Agency (Northern Ireland), British Heart Foundation and the Wellcome Trust.Peer reviewedPublisher PD

A national surveillance project on chronic kidney disease management in Canadian primary care: a study protocol.

INTRODUCTION: Effective chronic disease care is dependent on well-organised quality improvement (QI) strategies that monitor processes of care and outcomes for optimal care delivery. Although healthcare is provincially/territorially structured in Canada, there are national networks such as the Canadian Primary Care Sentinel Surveillance Network (CPCSSN) as important facilitators for national QI-based studies to improve chronic disease care. The goal of our study is to improve the understanding of how patients with chronic kidney disease (CKD) are managed in primary care and the variation across practices and provinces and territories to drive improvements in care delivery. METHODS AND ANALYSIS: The CPCSSN database contains anonymised health information from the electronic medical records for patients of participating primary care practices (PCPs) across Canada (n=1200). The dataset includes information on patient sociodemographics, medications, laboratory results and comorbidities. Leveraging validated algorithms, case definitions and guidelines will help define CKD and the related processes of care, and these enable us to: (1) determine prevalent CKD burden; (2) ascertain the current practice pattern on risk identification and management of CKD and (3) study variation in care indicators (eg, achievement of blood pressure and proteinuria targets) and referral pattern for specialist kidney care. The process of care outcomes will be stratified across patients' demographics as well as provider and regional (provincial/territorial) characteristics. The prevalence of CKD stages 3-5 will be presented as age-sex standardised prevalence estimates stratified by province and as weighted averages for population rates with 95% CIs using census data. For each PCP, age-sex standardised prevalence will be calculated and compared with expected standardised prevalence estimates. The process-based outcomes will be defined using established methods. ETHICS AND DISSEMINATION: The CPCSSN is committed to high ethical standards when dealing with individual data collected, and this work is reviewed and approved by the Network Scientific Committee. The results will be published in peer-reviewed journals and presented at relevant national and international scientific meetings

Evaluation of interventions to improve inpatient hospital documentation within electronic health records: A Systematic Review

Introduction Despite increased use of electronic health records (EHRs), EHR documentation quality remains poor. Consequently, EHR data quality is also negatively affected. Many services, including disease surveillance and health services research, utilize EHR data. Accordingly, several studies have attempted to improve EHR documentation quality in the inpatient setting using various interventions. Objectives and Approach The purpose of this systematic review was to synthesize the literature, and assess the effectiveness of interventions seeking to improve inpatient EHR documentation quality. To identify relevant experimental, quasi-experimental and observational studies, a search strategy was developed based on elaborate inclusion/exclusion criteria using four main themes: EHR, documentation, interventions, and type of study. Four databases, Cochrane, Medline, EMBASE, and CINAHL, were searched. Study quality assessment and data extraction from selected studies were performed using a Downs and Black and Newcastle-Ottawa Scale hybrid tool, and a REDCap form, respectively. Data was then analyzed and synthesized in a narrative semi-quantitative manner. Results An in-depth search of the identified databases, grey literature and reference lists, revealed a final 20 studies for inclusion in this systematic review. Due to high heterogeneity in study design, population, interventions, comparators, document types and outcomes, data could not be standardized for a quantitative comparison. However, statistically significant results in interventions and affected outcomes were further presented and discussed. A higher number of studies reported significantly improved EHR documentation when using the interventions: ‘Education’ and ‘Implementing a new EHR Reporting System’. When implementing two or more interventions, more outcome measures were affected. There was no association between study quality or study design and number of interventions used. Only one of the 20 studies found EHR documentation worsened with the interventions used. Conclusion/Implications Interventions implemented to enhance EHR documentation are highly variable and require standardization. Emphasis should be placed on this novel area of research to improve communication between healthcare providers, enhance continuity of care, reduce the burden in health information management, and to facilitate data sharing between centers, provinces, and countries

Estimating the effect of referral for nephrology care on the survival of adults with advanced chronic kidney disease in a real-world clinical setting

Introduction Longitudinal 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 Approach We 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.” Results We 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/Implications We 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