Browsing by Author "Singer, Joel"

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    Community versus academic hospital community-acquired pneumonia patients: a nested cohort study
    (2024-11-25) Tsang, Jennifer L.; Rego, Kian; Binnie, Alexandra; Lee, Terry; Mccarthy, Anne; Cowan, Juthaporn; Archambault, Patrick; Lellouche, Francois; Turgeon, Alexis F.; Yoon, Jennifer; Lamontagne, Francois; Mcgeer, Allison; Douglas, Josh; Daley, Peter; Fowler, Robert; Maslove, David M.; Winston, Brent W.; Lee, Todd C.; Tran, Karen C.; Cheng, Matthew P.; Vinh, Donald C.; Boyd, John H.; Walley, Keith R.; Singer, Joel; Marshall, John C.; Haljan, Gregory; Jain, Fagun; Russell, James A.
    Abstract Background Most Canadians receive their care in community hospitals, yet most clinical research is conducted in academic hospitals. This study aims to compare patients with community acquired pneumonia (CAP) treated in academic and community hospitals with respect to their demographics, clinical characteristics, treatments and outcomes. Methods This nested observational cohort substudy of the Community Acquired Pneumonia: Toward InnoVAtive Treatment (CAPTIVATE) trial included 1,329 hospitalized adults with CAP recruited between March 1st, 2018 and September 31st, 2023 from 15 Canadian hospitals. Unadjusted and adjusted analyses for age, sex and co-morbidities using logistic, Cox and censored quantile regressions were conducted. Results Patients in community hospitals were older (mean [SD] 75.0 [15.7] years vs. 68.3 [16.2] years; p < 0.001), were more likely to be female (49.7% vs. 41.0%, p = 0.002), and had more comorbidities (75.9% vs. 64.8%, p < 0.001). More patients in community hospitals received corticosteroids (49.2% vs. 37.4%, p < 0.001). Community hospital patients had a higher likelihood of developing acute respiratory distress syndrome (OR 3.13, 95% CI: 1.87, 5.24, p = < 0.001), and acute cardiac injury (OR 2.53, 95% CI: 1.33, 4.83, p = 0.005). In unadjusted and adjusted analyses, 28-day mortality difference did not meet statistical significance (OR 1.43, 95% CI: 0.98, 20.7, p = 0.062 and OR 1.23, 95% CI: 0.81, 1.87, p = 0.332, respective). Conclusion Patients with CAP in Canadian community and academic hospitals differed with respect to their age, clinical characteristics, treatments and outcomes, emphasizing the importance of including more community hospitals in clinical research studies to ensure the generalizability of results.
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    Magnetic resonance imaging predictors (cartilage, osteophytes and meniscus) of prevalent and 3-year incident medial and lateral tibiofemoral knee joint tenderness and patellofemoral grind
    (2022-12-02) Sayre, Eric C.; Guermazi, Ali; Nicolaou, Savvas; Esdaile, John M.; Kopec, Jacek A.; Singer, Joel; Wong, Hubert; Thorne, Anona; Cibere, Jolanda
    Abstract Objective To identify magnetic resonance imaging (MRI) predictors (cartilage [C], osteophytes [O] and meniscus [M] scores) of prevalent and 3-year incident medial tibiofemoral (MTF) and lateral tibiofemoral (LTF) knee joint tenderness and patellofemoral (PF) grind.  Methods Population-based knee pain cohort aged 40–79 was assessed at baseline (N = 255), 3- and 7-year follow-up (N = 108 × 2 = 216). COM scores were measured at 6/8/6 subregions respectively. Age-sex-BMI adjusted logistic models predicted prevalence versus relevant COM predictors (medial, lateral or patellar / trochlear groove scores). Fully adjusted models also included all relevant COM predictors. Binary generalized estimating equations models predicting 3-year incidence were also adjusted for individual follow-up time between cycles. Results Significant predictors of prevalent MTF tenderness: medial femoral cartilage (fully adjusted odds ratio [aOR] 1.84; 95% confidence interval [CI] 1.11, 3.05), female (aOR = 3.05; 1.67, 5.58), BMI (aOR = 1.53 per 5 units BMI; 1.10, 2.11). Predictors of prevalent LTF tenderness: female (aOR = 2.18; 1.22, 3.90). There were no predictors of prevalent PF grind in the fully adjusted model. However, medial patellar osteophytes was predictive in the age-sex-BMI adjusted model. There were no predictors of 3-year incident MTF tenderness. Predictors of 3-year incident LTF tenderness: female (aOR = 3.83; 1.25, 11.77). Predictors of 3-year incident PF grind: lateral patellar osteophytes (aOR = 4.82; 1.69, 13.77). In the age-sex-BMI adjusted model, patellar cartilage was also a predictor. Conclusion We explored potential MRI predictors of prevalent and 3-year incident MTF/LTF knee joint tenderness and PF grind. These findings could guide preemptive strategies aimed at reducing these symptoms in the present and future (3-year incidence).
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    Specific manifestations of knee osteoarthritis predict depression and anxiety years in the future: Vancouver Longitudinal Study of Early Knee Osteoarthritis
    (2020-07-16) Sayre, Eric C; Esdaile, John M; Kopec, Jacek A; Singer, Joel; Wong, Hubert; Thorne, Anona; Guermazi, Ali; Nicolaou, Savvas; Cibere, Jolanda
    Abstract Background To evaluate whether knee osteoarthritis (OA) manifestations predict depression and anxiety using cross-sectional and longitudinal prediction models. Methods A population-based cohort (n = 122) with knee pain, aged 40–79, was evaluated at baseline, 3 and 7 years. Baseline predictors were: age decade; sex; BMI ≥ 25; physical exam knee effusion; crepitus; malalignment; quadriceps atrophy; flexion; flexion contracture; Kellgren-Lawrence (KL) x-ray grade (0/1/2/3+); WOMAC pain ≥25; WOMAC stiffness ≥25; self-reported knee swelling; and knee OA diagnosis (no/probable/definite). Depression and anxiety, cutoffs 5+ and 7+ respectively, were measured via the Hospital Anxiety and Depression Scale. We fit logistic models at each cycle using multivariable models selected via lowest Akaike’s information criterion. Results Baseline depression model: sex (female OR = 0.27; 0.10, 0.76) and KL grade (KL 1 OR = 4.21; 1.31, 13.48). Three-year depression model: KL grade (KL 1 OR = 18.92; 1.73, 206.25). Seven-year depression model: WOMAC stiffness ≥25 (OR = 3.49; 1.02, 11.94) and flexion contracture ≥1 degree (OR = 0.23; 0.07, 0.81). Baseline anxiety model: knee swelling (OR = 4.11; 1.51, 11.13) and age (50–59 vs. 40–49 OR = 0.31 [0.11, 0.85]; 60–69 OR = 0.07 [0.01, 0.42]). Three-year anxiety model: WOMAC stiffness ≥25 (OR = 5.80; 1.23, 27.29) and KL grade (KL 1 OR = 6.25; 1.04, 37.65). Seven-year anxiety model: sex (female OR = 2.71; 0.87, 8.46). Conclusion Specific knee OA-related manifestations predict depression and anxiety cross-sectionally, 3 years in the future, and for depression, 7 years in the future. This information may prove useful to clinicians in helping to identify patients most at risk of present or future depression and anxiety, thus facilitating preemptive discussions that may help counter that risk.
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    Using a targeted metabolomics approach to explore differences in ARDS associated with COVID-19 compared to ARDS caused by H1N1 influenza and bacterial pneumonia
    (2024-02-27) Lee, Chel H.; Banoei, Mohammad M.; Ansari, Mariam; Cheng, Matthew P.; Lamontagne, Francois; Griesdale, Donald; Lasry, David E.; Demir, Koray; Dhingra, Vinay; Tran, Karen C.; Lee, Terry; Burns, Kevin; Sweet, David; Marshall, John; Slutsky, Arthur; Murthy, Srinivas; Singer, Joel; Patrick, David M.; Lee, Todd C.; Boyd, John H.; Walley, Keith R.; Fowler, Robert; Haljan, Greg; Vinh, Donald C.; Mcgeer, Alison; Maslove, David; Mann, Puneet; Donohoe, Kathryn; Hernandez, Geraldine; Rocheleau, Genevieve; Trahtemberg, Uriel; Kumar, Anand; Lou, Ma; dos Santos, Claudia; Baker, Andrew; Russell, James A.; Winston, Brent W.
    Abstract Rationale Acute respiratory distress syndrome (ARDS) is a life-threatening critical care syndrome commonly associated with infections such as COVID-19, influenza, and bacterial pneumonia. Ongoing research aims to improve our understanding of ARDS, including its molecular mechanisms, individualized treatment options, and potential interventions to reduce inflammation and promote lung repair. Objective To map and compare metabolic phenotypes of different infectious causes of ARDS to better understand the metabolic pathways involved in the underlying pathogenesis. Methods We analyzed metabolic phenotypes of 3 ARDS cohorts caused by COVID-19, H1N1 influenza, and bacterial pneumonia compared to non-ARDS COVID-19-infected patients and ICU-ventilated controls. Targeted metabolomics was performed on plasma samples from a total of 150 patients using quantitative LC–MS/MS and DI-MS/MS analytical platforms. Results Distinct metabolic phenotypes were detected between different infectious causes of ARDS. There were metabolomics differences between ARDSs associated with COVID-19 and H1N1, which include metabolic pathways involving taurine and hypotaurine, pyruvate, TCA cycle metabolites, lysine, and glycerophospholipids. ARDSs associated with bacterial pneumonia and COVID-19 differed in the metabolism of D-glutamine and D-glutamate, arginine, proline, histidine, and pyruvate. The metabolic profile of COVID-19 ARDS (C19/A) patients admitted to the ICU differed from COVID-19 pneumonia (C19/P) patients who were not admitted to the ICU in metabolisms of phenylalanine, tryptophan, lysine, and tyrosine. Metabolomics analysis revealed significant differences between C19/A, H1N1/A, and PNA/A vs ICU-ventilated controls, reflecting potentially different disease mechanisms. Conclusion Different metabolic phenotypes characterize ARDS associated with different viral and bacterial infections.
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    Using a targeted metabolomics approach to explore differences in ARDS associated with COVID-19 compared to ARDS caused by H1N1 influenza and bacterial pneumonia
    (2024-02-27) Lee, Chel H.; Banoei, Mohammad M.; Ansari, Mariam; Cheng, Matthew P.; Lamontagne, Francois; Griesdale, Donald; Lasry, David E.; Demir, Koray; Dhingra, Vinay; Tran, Karen C.; Lee, Terry; Burns, Kevin; Sweet, David; Marshall, John; Slutsky, Arthur; Murthy, Srinivas; Singer, Joel; Patrick, David M.; Lee, Todd C.; Boyd, John H.; Walley, Keith R.; Fowler, Robert; Haljan, Greg; Vinh, Donald C.; Mcgeer, Alison; Maslove, David; Mann, Puneet; Donohoe, Kathryn; Hernandez, Geraldine; Rocheleau, Genevieve; Trahtemberg, Uriel; Kumar, Anand; Lou, Ma; dos Santos, Claudia; Baker, Andrew; Russell, James A.; Winston, Brent W.
    Abstract Rationale Acute respiratory distress syndrome (ARDS) is a life-threatening critical care syndrome commonly associated with infections such as COVID-19, influenza, and bacterial pneumonia. Ongoing research aims to improve our understanding of ARDS, including its molecular mechanisms, individualized treatment options, and potential interventions to reduce inflammation and promote lung repair. Objective To map and compare metabolic phenotypes of different infectious causes of ARDS to better understand the metabolic pathways involved in the underlying pathogenesis. Methods We analyzed metabolic phenotypes of 3 ARDS cohorts caused by COVID-19, H1N1 influenza, and bacterial pneumonia compared to non-ARDS COVID-19-infected patients and ICU-ventilated controls. Targeted metabolomics was performed on plasma samples from a total of 150 patients using quantitative LC–MS/MS and DI-MS/MS analytical platforms. Results Distinct metabolic phenotypes were detected between different infectious causes of ARDS. There were metabolomics differences between ARDSs associated with COVID-19 and H1N1, which include metabolic pathways involving taurine and hypotaurine, pyruvate, TCA cycle metabolites, lysine, and glycerophospholipids. ARDSs associated with bacterial pneumonia and COVID-19 differed in the metabolism of D-glutamine and D-glutamate, arginine, proline, histidine, and pyruvate. The metabolic profile of COVID-19 ARDS (C19/A) patients admitted to the ICU differed from COVID-19 pneumonia (C19/P) patients who were not admitted to the ICU in metabolisms of phenylalanine, tryptophan, lysine, and tyrosine. Metabolomics analysis revealed significant differences between C19/A, H1N1/A, and PNA/A vs ICU-ventilated controls, reflecting potentially different disease mechanisms. Conclusion Different metabolic phenotypes characterize ARDS associated with different viral and bacterial infections.