Browsing by Author "Ronksley, Paul E."

Now showing 1 - 7 of 7
  • Thumbnail Image
    ItemOpen Access
    20-year trends in multimorbidity by race/ethnicity among hospitalized patient populations in the United States
    (2023-07-24) Mohamud, Mursal A.; Campbell, David J.; Wick, James; Leung, Alexander A.; Fabreau, Gabriel E.; Tonelli, Marcello; Ronksley, Paul E.
    Abstract Background The challenges presented by multimorbidity continue to rise in the United States. Little is known about how the relative contribution of individual chronic conditions to multimorbidity has changed over time, and how this varies by race/ethnicity. The objective of this study was to describe trends in multimorbidity by race/ethnicity, as well as to determine the differential contribution of individual chronic conditions to multimorbidity in hospitalized populations over a 20-year period within the United States. Methods This is a serial cross-sectional study using the Nationwide Inpatient Sample (NIS) from 1993 to 2012. We identified all hospitalized patients aged ≥ 18 years old with available data on race/ethnicity. Multimorbidity was defined as the presence of 3 or more conditions based on the Elixhauser comorbidity index. The relative change in the proportion of hospitalized patients with multimorbidity, overall and by race/ethnicity (Black, White, Hispanic, Asian/Pacific Islander, Native American) were tabulated and presented graphically. Population attributable fractions were estimated from modified Poisson regression models adjusted for sex, age, and insurance type. These fractions were used to describe the relative contribution of individual chronic conditions to multimorbidity over time and across racial/ethnic groups. Results There were 123,613,970 hospitalizations captured within the NIS between 1993 and 2012. The prevalence of multimorbidity increased in all race/ethnic groups over the 20-year period, most notably among White, Black, and Native American populations (+ 29.4%, + 29.7%, and + 32.0%, respectively). In both 1993 and 2012, Black hospitalized patients had a higher prevalence of multimorbidity (25.1% and 54.8%, respectively) compared to all other race/ethnic groups. Native American populations exhibited the largest overall increase in multimorbidity (+ 32.0%). Furthermore, the contribution of metabolic diseases to multimorbidity increased, particularly among Hispanic patients who had the highest population attributable fraction values for diabetes without complications (15.0%), diabetes with complications (5.1%), and obesity (5.8%). Conclusions From 1993 to 2012, the secular increases in the prevalence of multimorbidity as well as changes in the differential contribution of individual chronic conditions has varied substantially by race/ethnicity. These findings further elucidate the racial/ethnic gaps prevalent in multimorbidity within the United States. Prior presentations Preliminary finding of this study were presented at the Society of General Internal Medicine (SGIM) Annual Conference, Washington, DC, April 21, 2017.
  • Thumbnail Image
    ItemOpen Access
    Antimicrobial resistance (AMR) in COVID-19 patients: a systematic review and meta-analysis (November 2019–June 2021)
    (2022-03-07) Kariyawasam, Ruwandi M.; Julien, Danielle A.; Jelinski, Dana C.; Larose, Samantha L.; Rennert-May, Elissa; Conly, John M.; Dingle, Tanis C.; Chen, Justin Z.; Tyrrell, Gregory J.; Ronksley, Paul E.; Barkema, Herman W.
    Abstract Background Pneumonia from SARS-CoV-2 is difficult to distinguish from other viral and bacterial etiologies. Broad-spectrum antimicrobials are frequently prescribed to patients hospitalized with COVID-19 which potentially acts as a catalyst for the development of antimicrobial resistance (AMR). Objectives We conducted a systematic review and meta-analysis during the first 18 months of the pandemic to quantify the prevalence and types of resistant co-infecting organisms in patients with COVID-19 and explore differences across hospital and geographic settings. Methods We searched MEDLINE, Embase, Web of Science (BioSIS), and Scopus from November 1, 2019 to May 28, 2021 to identify relevant articles pertaining to resistant co-infections in patients with laboratory confirmed SARS-CoV-2. Patient- and study-level analyses were conducted. We calculated pooled prevalence estimates of co-infection with resistant bacterial or fungal organisms using random effects models. Stratified meta-analysis by hospital and geographic setting was also performed to elucidate any differences. Results Of 1331 articles identified, 38 met inclusion criteria. A total of 1959 unique isolates were identified with 29% (569) resistant organisms identified. Co-infection with resistant bacterial or fungal organisms ranged from 0.2 to 100% among included studies. Pooled prevalence of co-infection with resistant bacterial and fungal organisms was 24% (95% CI 8–40%; n = 25 studies: I2 = 99%) and 0.3% (95% CI 0.1–0.6%; n = 8 studies: I2 = 78%), respectively. Among multi-drug resistant organisms, methicillin-resistant Staphylococcus aureus, carbapenem-resistant Acinetobacter baumannii, Klebsiella pneumoniae, Pseudomonas aeruginosa and multi-drug resistant Candida auris were most commonly reported. Stratified analyses found higher proportions of AMR outside of Europe and in ICU settings, though these results were not statistically significant. Patient-level analysis demonstrated > 50% (n = 58) mortality, whereby all but 6 patients were infected with a resistant organism. Conclusions During the first 18 months of the pandemic, AMR prevalence was high in COVID-19 patients and varied by hospital and geography although there was substantial heterogeneity. Given the variation in patient populations within these studies, clinical settings, practice patterns, and definitions of AMR, further research is warranted to quantify AMR in COVID-19 patients to improve surveillance programs, infection prevention and control practices and antimicrobial stewardship programs globally.
  • Thumbnail Image
    ItemOpen Access
    Characteristics of new users of recent antidiabetic drugs in Canada and the United Kingdom
    (2022-09-29) Brunetti, Vanessa C.; St-Jean, Audray; Dell’Aniello, Sophie; Fisher, Anat; Yu, Oriana H. Y.; Bugden, Shawn C.; Daigle, Jean-Marc; Hu, Nianping; Alessi-Severini, Silvia; Shah, Baiju R.; Ronksley, Paul E.; Lix, Lisa M.; Ernst, Pierre; Filion, Kristian B.
    Abstract Background Characteristics of patients using newer 2nd and 3rd line antidiabetic drugs in a real-world setting are poorly understood. We described the characteristics of new users of sodium-glucose co-transporter-2 inhibitors (SGLT-2i), dipeptidyl peptidase-4 inhibitors (DPP-4i), and glucagon-like peptide-1 receptor agonists (GLP-1 RA) in Canada and the United Kingdom (UK) between 2016 and 2018. Methods We conducted a multi-database cohort study using administrative health databases from 7 Canadian provinces and the UK Clinical Practice Research Datalink. We assembled a base cohort of antidiabetic drug users between 2006 and 2018, from which we constructed 3 cohorts of new users of SGLT-2i, DPP-4i, and GLP-1 RA between 2016 and 2018. Results Our cohorts included 194,070 new users of DPP-4i, 166,722 new users of SGLT-2i, and 27,719 new users of GLP-1 RA. New users of GLP-1 RA were more likely to be younger (mean ± SD: 56.7 ± 12.2 years) than new users of DPP-4i (67.8 ± 12.3 years) or SGLT-2i (64.4 ± 11.1 years). In Canada, new users of DPP-4i were more likely to have a history of coronary artery disease (22%) than new users of SGLT-2i (20%) or GLP-1 RA (15%). Conclusion Although SGLT-2i, DPP-4i, and GLP-1 RAs are recommended as 2nd or 3rd line therapy for type 2 diabetes, important differences exist in the characteristics of users of these drugs. Contrary to existing guidelines, new users of DPP-4i had a higher prevalence of cardiovascular disease at baseline than new users of SGLT2i or GLP-1RA.
  • Thumbnail Image
    ItemOpen Access
    Mortality and cardiovascular events in adults with kidney failure after major non-cardiac surgery: a population-based cohort study
    (2021-11-04) Harrison, Tyrone G.; Ronksley, Paul E.; James, Matthew T.; Ruzycki, Shannon M.; Tonelli, Marcello; Manns, Braden J.; Zarnke, Kelly B.; McCaughey, Deirdre; Schneider, Prism; Wick, James; Hemmelgarn, Brenda R.
    Abstract Background People with kidney failure have a high incidence of major surgery, though the risk of perioperative outcomes at a population-level is unknown. Our objective was to estimate the proportion of people with kidney failure that experience acute myocardial infarction (AMI) or death within 30 days of major non-cardiac surgery, based on surgery type. Methods In this retrospective population-based cohort study, we used administrative health data to identify adults from Alberta, Canada with major surgery between April 12,005 and February 282,017 that had preoperative estimated glomerular filtration rates (eGFRs) < 15 mL/min/1.73m2 or received chronic dialysis. The index surgical procedure for each participant was categorized within one of fourteen surgical groupings based on Canadian Classification of Health Interventions (CCI) codes applied to hospitalization administrative datasets. We estimated the proportion of people that had AMI or died within 30 days of the index surgical procedure (with 95% confidence intervals [CIs]) following logistic regression, stratified by surgery type. Results Overall, 3398 people had a major surgery (1905 hemodialysis; 590 peritoneal dialysis; 903 non-dialysis). Participants were more likely male (61.0%) with a median age of 61.5 years (IQR 50.0–72.7). Within 30 days of surgery, 272 people (8.0%) had an AMI or died. The probability was lowest following ophthalmologic surgery at 1.9% (95%CI: 0.5, 7.3) and kidney transplantation at 2.1% (95%CI: 1.3, 3.2). Several types of surgery were associated with greater than one in ten risk of AMI or death, including retroperitoneal (10.0% [95%CI: 2.5, 32.4]), intra-abdominal (11.7% [8.7, 15.5]), skin and soft tissue (12.1% [7.4, 19.1]), musculoskeletal (MSK) (12.3% [9.9, 15.5]), vascular (12.6% [10.2, 15.4]), anorectal (14.7% [6.3, 30.8]), and neurosurgical procedures (38.1% [20.3, 59.8]). Urgent or emergent procedures had the highest risk, with 12.1% experiencing AMI or death (95%CI: 10.7, 13.6) compared with 2.6% (1.9, 3.5) following elective surgery. Conclusions After major non-cardiac surgery, the risk of death or AMI for people with kidney failure varies significantly based on surgery type. This study informs our understanding of surgery type and risk for people with kidney failure. Future research should focus on identifying high risk patients and strategies to reduce these risks.
  • Thumbnail Image
    ItemOpen Access
    Prediction of major postoperative events after non-cardiac surgery for people with kidney failure: derivation and internal validation of risk models
    (2023-03-10) Harrison, Tyrone G.; Hemmelgarn, Brenda R.; James, Matthew T.; Sawhney, Simon; Manns, Braden J.; Tonelli, Marcello; Ruzycki, Shannon M.; Zarnke, Kelly B.; Wilson, Todd A.; McCaughey, Deirdre; Ronksley, Paul E.
    Abstract Background People with kidney failure often require surgery and experience worse postoperative outcomes compared to the general population, but existing risk prediction tools have excluded those with kidney failure during development or exhibit poor performance. Our objective was to derive, internally validate, and estimate the clinical utility of risk prediction models for people with kidney failure undergoing non-cardiac surgery. Design, setting, participants, and measures This study involved derivation and internal validation of prognostic risk prediction models using a retrospective, population-based cohort. We identified adults from Alberta, Canada with pre-existing kidney failure (estimated glomerular filtration rate [eGFR] < 15 mL/min/1.73m2 or receipt of maintenance dialysis) undergoing non-cardiac surgery between 2005–2019. Three nested prognostic risk prediction models were assembled using clinical and logistical rationale. Model 1 included age, sex, dialysis modality, surgery type and setting. Model 2 added comorbidities, and Model 3 added preoperative hemoglobin and albumin. Death or major cardiac events (acute myocardial infarction or nonfatal ventricular arrhythmia) within 30 days after surgery were modelled using logistic regression models. Results The development cohort included 38,541 surgeries, with 1,204 outcomes (after 3.1% of surgeries); 61% were performed in males, the median age was 64 years (interquartile range [IQR]: 53, 73), and 61% were receiving hemodialysis at the time of surgery. All three internally validated models performed well, with c-statistics ranging from 0.783 (95% Confidence Interval [CI]: 0.770, 0.797) for Model 1 to 0.818 (95%CI: 0.803, 0.826) for Model 3. Calibration slopes and intercepts were excellent for all models, though Models 2 and 3 demonstrated improvement in net reclassification. Decision curve analysis estimated that use of any model to guide perioperative interventions such as cardiac monitoring would result in potential net benefit over default strategies. Conclusions We developed and internally validated three novel models to predict major clinical events for people with kidney failure having surgery. Models including comorbidities and laboratory variables showed improved accuracy of risk stratification and provided the greatest potential net benefit for guiding perioperative decisions. Once externally validated, these models may inform perioperative shared decision making and risk-guided strategies for this population.
  • Thumbnail Image
    ItemOpen Access
    The neighbourhood built environment and health-related fitness: a narrative systematic review
    (2022-09-24) Frehlich, Levi; Christie, Chelsea D.; Ronksley, Paul E.; Turin, Tanvir C.; Doyle-Baker, Patricia; McCormack, Gavin R.
    Abstract Background There is increasing evidence demonstrating the importance of the neighbourhood built environment in supporting physical activity. Physical activity provides numerous health benefits including improvements in health-related fitness (i.e., muscular, cardiorespiratory, motor, and morphological fitness). Emerging evidence also suggests that the neighbourhood built environment is associated with health-related fitness. Our aim was to summarize evidence on the associations between the neighbourhood built environment and components of health-related fitness in adults. Methods We undertook a systematic review following PRISMA guidelines. Our data sources included electronic searches in MEDLINE, Embase, CINAHL, Web of Science, SPORTDiscus, Environment Complete, ProQuest Dissertations and Theses, and Transport Research International Documentation from inception to March 2021. Our eligibility criteria consisted of observational and experimental studies estimating associations between the neighbourhood built environment and health-related fitness among healthy adults (age ≥ 18 years). Eligible studies included objective or self-reported measures of the neighbourhood built environment and included either objective or self-reported measures of health-related fitness. Data extraction included study design, sample characteristics, measured neighbourhood built environment characteristics, and measured components of health-related fitness. We used individual Joanna Briggs Institute study checklists based on identified study designs. Our primary outcome measure was components of health-related fitness (muscular; cardiorespiratory; motor, and morphological fitness). Results Twenty-seven studies (sample sizes = 28 to 419,562; 2002 to 2020) met the eligibility criteria. Neighbourhood destinations were the most consistent built environment correlate across all components of health-related fitness. The greatest number of significant associations was found between the neighbourhood built environment and morphological fitness while the lowest number of associations was found for motor fitness. The neighbourhood built environment was consistently associated with health-related fitness in studies that adjusted for physical activity. Conclusion The neighbourhood built environment is associated with health-related fitness in adults and these associations may be independent of physical activity. Longitudinal studies that adjust for physical activity (including resistance training) and sedentary behaviour, and residential self-selection are needed to obtain rigorous causal evidence for the link between the neighbourhood built environment and health-related fitness. Trial registration Protocol registration: PROSPERO number CRD42020179807.
  • Thumbnail Image
    ItemOpen Access
    Validity of an algorithm to identify cardiovascular deaths from administrative health records: a multi-database population-based cohort study
    (2021-07-31) Lix, Lisa M.; Sobhan, Shamsia; St-Jean, Audray; Daigle, Jean-Marc; Fisher, Anat; Yu, Oriana H. Y.; Dell’Aniello, Sophie; Hu, Nianping; Bugden, Shawn C.; Shah, Baiju R.; Ronksley, Paul E.; Alessi-Severini, Silvia; Douros, Antonios; Ernst, Pierre; Filion, Kristian B.
    Abstract Background Cardiovascular death is a common outcome in population-based studies about new healthcare interventions or treatments, such as new prescription medications. Vital statistics registration systems are often the preferred source of information about cause-specific mortality because they capture verified information about the deceased, but they may not always be accessible for linkage with other sources of population-based data. We assessed the validity of an algorithm applied to administrative health records for identifying cardiovascular deaths in population-based data. Methods Administrative health records were from an existing multi-database cohort study about sodium-glucose cotransporter-2 (SGLT2) inhibitors, a new class of antidiabetic medications. Data were from 2013 to 2018 for five Canadian provinces (Alberta, British Columbia, Manitoba, Ontario, Quebec) and the United Kingdom (UK) Clinical Practice Research Datalink (CPRD). The cardiovascular mortality algorithm was based on in-hospital cardiovascular deaths identified from diagnosis codes and select out-of-hospital deaths. Sensitivity, specificity, and positive and negative predictive values (PPV, NPV) were calculated for the cardiovascular mortality algorithm using vital statistics registrations as the reference standard. Overall and stratified estimates and 95% confidence intervals (CIs) were computed; the latter were produced by site, location of death, sex, and age. Results The cohort included 20,607 individuals (58.3% male; 77.2% ≥70 years). When compared to vital statistics registrations, the cardiovascular mortality algorithm had overall sensitivity of 64.8% (95% CI 63.6, 66.0); site-specific estimates ranged from 54.8 to 87.3%. Overall specificity was 74.9% (95% CI 74.1, 75.6) and overall PPV was 54.5% (95% CI 53.7, 55.3), while site-specific PPV ranged from 33.9 to 72.8%. The cardiovascular mortality algorithm had sensitivity of 57.1% (95% CI 55.4, 58.8) for in-hospital deaths and 72.3% (95% CI 70.8, 73.9) for out-of-hospital deaths; specificity was 88.8% (95% CI 88.1, 89.5) for in-hospital deaths and 58.5% (95% CI 57.3, 59.7) for out-of-hospital deaths. Conclusions A cardiovascular mortality algorithm applied to administrative health records had moderate validity when compared to vital statistics data. Substantial variation existed across study sites representing different geographic locations and two healthcare systems. These variations may reflect different diagnostic coding practices and healthcare utilization patterns.