SwePub
Sök i SwePub databas

  Utökad sökning

Träfflista för sökning "WFRF:(Krumholz Harlan M) ;spr:eng"

Sökning: WFRF:(Krumholz Harlan M) > Engelska

  • Resultat 1-8 av 8
Sortera/gruppera träfflistan
   
NumreringReferensOmslagsbildHitta
1.
  • Pennells, Lisa, et al. (författare)
  • Equalization of four cardiovascular risk algorithms after systematic recalibration : individual-participant meta-analysis of 86 prospective studies
  • 2019
  • Ingår i: European Heart Journal. - : Oxford University Press (OUP). - 0195-668X .- 1522-9645. ; 40:7, s. 621-
  • Tidskriftsartikel (refereegranskat)abstract
    • Aims: There is debate about the optimum algorithm for cardiovascular disease (CVD) risk estimation. We conducted head-to-head comparisons of four algorithms recommended by primary prevention guidelines, before and after ‘recalibration’, a method that adapts risk algorithms to take account of differences in the risk characteristics of the populations being studied.Methods and results: Using individual-participant data on 360 737 participants without CVD at baseline in 86 prospective studies from 22 countries, we compared the Framingham risk score (FRS), Systematic COronary Risk Evaluation (SCORE), pooled cohort equations (PCE), and Reynolds risk score (RRS). We calculated measures of risk discrimination and calibration, and modelled clinical implications of initiating statin therapy in people judged to be at ‘high’ 10 year CVD risk. Original risk algorithms were recalibrated using the risk factor profile and CVD incidence of target populations. The four algorithms had similar risk discrimination. Before recalibration, FRS, SCORE, and PCE over-predicted CVD risk on average by 10%, 52%, and 41%, respectively, whereas RRS under-predicted by 10%. Original versions of algorithms classified 29–39% of individuals aged ≥40 years as high risk. By contrast, recalibration reduced this proportion to 22–24% for every algorithm. We estimated that to prevent one CVD event, it would be necessary to initiate statin therapy in 44–51 such individuals using original algorithms, in contrast to 37–39 individuals with recalibrated algorithms.Conclusion: Before recalibration, the clinical performance of four widely used CVD risk algorithms varied substantially. By contrast, simple recalibration nearly equalized their performance and improved modelled targeting of preventive action to clinical need.
  •  
2.
  • Wood, Angela M., et al. (författare)
  • Risk thresholds for alcohol consumption : combined analysis of individual-participant data for 599 912 current drinkers in 83 prospective studies
  • 2018
  • Ingår i: The Lancet. - : Elsevier. - 0140-6736 .- 1474-547X. ; 391:10129, s. 1513-1523
  • Tidskriftsartikel (refereegranskat)abstract
    • Background: Low-risk limits recommended for alcohol consumption vary substantially across different national guidelines. To define thresholds associated with lowest risk for all-cause mortality and cardiovascular disease, we studied individual-participant data from 599 912 current drinkers without previous cardiovascular disease.Methods: We did a combined analysis of individual-participant data from three large-scale data sources in 19 high-income countries (the Emerging Risk Factors Collaboration, EPIC-CVD, and the UK Biobank). We characterised dose-response associations and calculated hazard ratios (HRs) per 100 g per week of alcohol (12.5 units per week) across 83 prospective studies, adjusting at least for study or centre, age, sex, smoking, and diabetes. To be eligible for the analysis, participants had to have information recorded about their alcohol consumption amount and status (ie, non-drinker vs current drinker), plus age, sex, history of diabetes and smoking status, at least 1 year of follow-up after baseline, and no baseline history of cardiovascular disease. The main analyses focused on current drinkers, whose baseline alcohol consumption was categorised into eight predefined groups according to the amount in grams consumed per week. We assessed alcohol consumption in relation to all-cause mortality, total cardiovascular disease, and several cardiovascular disease subtypes. We corrected HRs for estimated long-term variability in alcohol consumption using 152 640 serial alcohol assessments obtained some years apart (median interval 5.6 years [5th-95th percentile 1.04-13.5]) from 71 011 participants from 37 studies.Findings: In the 599 912 current drinkers included in the analysis, we recorded 40 310 deaths and 39 018 incident cardiovascular disease events during 5.4 million person-years of follow-up. For all-cause mortality, we recorded a positive and curvilinear association with the level of alcohol consumption, with the minimum mortality risk around or below 100 g per week. Alcohol consumption was roughly linearly associated with a higher risk of stroke (HR per 100 g per week higher consumption 1.14, 95% CI, 1.10-1.17), coronary disease excluding myocardial infarction (1.06, 1.00-1.11), heart failure (1.09, 1.03-1.15), fatal hypertensive disease (1.24, 1.15-1.33); and fatal aortic aneurysm (1.15, 1.03-1.28). By contrast, increased alcohol consumption was loglinearly associated with a lower risk of myocardial infarction (HR 0.94, 0.91-0.97). In comparison to those who reported drinking >0-<= 100 g per week, those who reported drinking >100-<= 200 g per week, >200-<= 350 g per week, or >350 g per week had lower life expectancy at age 40 years of approximately 6 months, 1-2 years, or 4-5 years, respectively.Interpretation: In current drinkers of alcohol in high-income countries, the threshold for lowest risk of all-cause mortality was about 100 g/week. For cardiovascular disease subtypes other than myocardial infarction, there were no clear risk thresholds below which lower alcohol consumption stopped being associated with lower disease risk. These data support limits for alcohol consumption that are lower than those recommended in most current guidelines.
  •  
3.
  • Morales, Daniel R, et al. (författare)
  • Renin-angiotensin system blockers and susceptibility to COVID-19: an international, open science, cohort analysis.
  • 2021
  • Ingår i: The Lancet Digital health. - 2589-7500. ; 3:2, s. e98-e114
  • Tidskriftsartikel (refereegranskat)abstract
    • Angiotensin-converting enzyme inhibitors (ACEIs) and angiotensin receptor blockers (ARBs) have been postulated to affect susceptibility to COVID-19. Observational studies so far have lacked rigorous ascertainment adjustment and international generalisability. We aimed to determine whether use of ACEIs or ARBs is associated with an increased susceptibility to COVID-19 in patients with hypertension.In this international, open science, cohort analysis, we used electronic health records from Spain (Information Systems for Research in Primary Care [SIDIAP]) and the USA (Columbia University Irving Medical Center data warehouse [CUIMC] and Department of Veterans Affairs Observational Medical Outcomes Partnership [VA-OMOP]) to identify patients aged 18 years or older with at least one prescription for ACEIs and ARBs (target cohort) or calcium channel blockers (CCBs) and thiazide or thiazide-like diuretics (THZs; comparator cohort) between Nov 1, 2019, and Jan 31, 2020. Users were defined separately as receiving either monotherapy with these four drug classes, or monotherapy or combination therapy (combination use) with other antihypertensive medications. We assessed four outcomes: COVID-19 diagnosis; hospital admission with COVID-19; hospital admission with pneumonia; and hospital admission with pneumonia, acute respiratory distress syndrome, acute kidney injury, or sepsis. We built large-scale propensity score methods derived through a data-driven approach and negative control experiments across ten pairwise comparisons, with results meta-analysed to generate 1280 study effects. For each study effect, we did negative control outcome experiments using a possible 123 controls identified through a data-rich algorithm. This process used a set of predefined baseline patient characteristics to provide the most accurate prediction of treatment and balance among patient cohorts across characteristics. The study is registered with the EU Post-Authorisation Studies register, EUPAS35296.Among 1 355 349 antihypertensive users (363 785 ACEI or ARB monotherapy users, 248 915 CCB or THZ monotherapy users, 711 799 ACEI or ARB combination users, and 473 076 CCB or THZ combination users) included in analyses, no association was observed between COVID-19 diagnosis and exposure to ACEI or ARB monotherapy versus CCB or THZ monotherapy (calibrated hazard ratio [HR] 0·98, 95% CI 0·84-1·14) or combination use exposure (1·01, 0·90-1·15). ACEIs alone similarly showed no relative risk difference when compared with CCB or THZ monotherapy (HR 0·91, 95% CI 0·68-1·21; with heterogeneity of >40%) or combination use (0·95, 0·83-1·07). Directly comparing ACEIs with ARBs demonstrated a moderately lower risk with ACEIs, which was significant with combination use (HR 0·88, 95% CI 0·79-0·99) and non-significant for monotherapy (0·85, 0·69-1·05). We observed no significant difference between drug classes for risk of hospital admission with COVID-19, hospital admission with pneumonia, or hospital admission with pneumonia, acute respiratory distress syndrome, acute kidney injury, or sepsis across all comparisons.No clinically significant increased risk of COVID-19 diagnosis or hospital admission-related outcomes associated with ACEI or ARB use was observed, suggesting users should not discontinue or change their treatment to decrease their risk of COVID-19.Wellcome Trust, UK National Institute for Health Research, US National Institutes of Health, US Department of Veterans Affairs, Janssen Research & Development, IQVIA, South Korean Ministry of Health and Welfare Republic, Australian National Health and Medical Research Council, and European Health Data and Evidence Network.
  •  
4.
  • Sangha, Veer, et al. (författare)
  • Detection of Left Ventricular Systolic Dysfunction From Electrocardiographic Images
  • 2023
  • Ingår i: Circulation. - : Wolters Kluwer. - 0009-7322 .- 1524-4539. ; 148:9, s. 765-777
  • Tidskriftsartikel (refereegranskat)abstract
    • BACKGROUND: Left ventricular (LV) systolic dysfunction is associated with a >8-fold increased risk of heart failure and a 2-fold risk of premature death. The use of ECG signals in screening for LV systolic dysfunction is limited by their availability to clinicians. We developed a novel deep learning-based approach that can use ECG images for the screening of LV systolic dysfunction.METHODS: Using 12-lead ECGs plotted in multiple different formats, and corresponding echocardiographic data recorded within 15 days from the Yale New Haven Hospital between 2015 and 2021, we developed a convolutional neural network algorithm to detect an LV ejection fraction <40%. The model was validated within clinical settings at Yale New Haven Hospital and externally on ECG images from Cedars Sinai Medical Center in Los Angeles, CA; Lake Regional Hospital in Osage Beach, MO; Memorial Hermann Southeast Hospital in Houston, TX; and Methodist Cardiology Clinic of San Antonio, TX. In addition, it was validated in the prospective Brazilian Longitudinal Study of Adult Health. Gradient-weighted class activation mapping was used to localize class-discriminating signals on ECG images.RESULTS: Overall, 385 601 ECGs with paired echocardiograms were used for model development. The model demonstrated high discrimination across various ECG image formats and calibrations in internal validation (area under receiving operation characteristics [AUROCs], 0.91; area under precision-recall curve [AUPRC], 0.55); and external sets of ECG images from Cedars Sinai (AUROC, 0.90 and AUPRC, 0.53), outpatient Yale New Haven Hospital clinics (AUROC, 0.94 and AUPRC, 0.77), Lake Regional Hospital (AUROC, 0.90 and AUPRC, 0.88), Memorial Hermann Southeast Hospital (AUROC, 0.91 and AUPRC 0.88), Methodist Cardiology Clinic (AUROC, 0.90 and AUPRC, 0.74), and Brazilian Longitudinal Study of Adult Health cohort (AUROC, 0.95 and AUPRC, 0.45). An ECG suggestive of LV systolic dysfunction portended >27-fold higher odds of LV systolic dysfunction on transthoracic echocardiogram (odds ratio, 27.5 [95% CI, 22.3-33.9] in the held-out set). Class-discriminative patterns localized to the anterior and anteroseptal leads (V2 and V3), corresponding to the left ventricle regardless of the ECG layout. A positive ECG screen in individuals with an LV ejection fraction & GE;40% at the time of initial assessment was associated with a 3.9-fold increased risk of developing incident LV systolic dysfunction in the future (hazard ratio, 3.9 [95% CI, 3.3-4.7]; median follow-up, 3.2 years).CONCLUSIONS: We developed and externally validated a deep learning model that identifies LV systolic dysfunction from ECG images. This approach represents an automated and accessible screening strategy for LV systolic dysfunction, particularly in low-resource settings.
  •  
5.
  •  
6.
  • Madhavan, Mahesh V, et al. (författare)
  • Antiplatelet strategies in acute coronary syndromes: design and methodology of an international collaborative network meta-analysis of randomized controlled trials.
  • 2021
  • Ingår i: Minerva cardioangiologica. - 1827-1618. ; 69:4, s. 398-407
  • Tidskriftsartikel (refereegranskat)abstract
    • The optimal choice of oral P2Y12 receptor inhibitors has the potential to significantly influence outcomes. We seek to compare the safety and efficacy of the three most commonly used oral P2Y12 receptor inhibitors (clopidogrel, prasugrel, and ticagrelor) in acute coronary syndromes (ACS) via a comprehensive systematic review and network meta-analysis.We will perform a comprehensive search for randomized clinical trials which compared cardiovascular and hemorrhagic outcomes after use of at least two of the distinct oral P2Y12 receptor inhibitors (i.e. clopidogrel, prasugrel, and ticagrelor). In addition, key inclusion criteria will be trial size of at least 100 patients and at least 1 month of follow-up time. Several pre-specified subgroups will be explored, including Asian patients, patients presenting with ST-elevation myocardial infarction, patients of advanced age, and others.Exploratory frequentist pairwise meta-analyses will be based primarily on a random-effects method, relying on relative risks (RR) for short-term endpoints and incidence rate ratios (IRR) for long-term endpoints. Inferential frequentist network meta-analysis will be based primarily on a random-effects method, relying on RR and IRR as specified above. Results will be reported as point summary of effect, 95% CI, and p-values for effect, and graphically represented using forest plots.An international collaborative network meta-analysis has begun to comprehensively analyze the safety and efficacy of prasugrel, ticagrelor and clopidogrel, each on a background of aspirin, for management of patients with ACS. It is our hope that the rigor and breadth of the undertaking described herein will provide novel insights that will inform optimal patient care for patients with ACS treated conservatively, or undergoing revascularization.
  •  
7.
  • Sangha, Veer, et al. (författare)
  • Automated multilabel diagnosis on electrocardiographic images and signals
  • 2022
  • Ingår i: Nature Communications. - : Springer Nature. - 2041-1723. ; 13:1
  • Tidskriftsartikel (refereegranskat)abstract
    • The application of artificial intelligence for automated diagnosis of electrocardiograms can improve care in remote settings but is limited by the reliance on infrequently available signal-based data. Here, the authors report the development of a multi-label automated diagnosis model for electrocardiographic images. The application of artificial intelligence (AI) for automated diagnosis of electrocardiograms (ECGs) can improve care in remote settings but is limited by the reliance on infrequently available signal-based data. We report the development of a multilabel automated diagnosis model for electrocardiographic images, more suitable for broader use. A total of 2,228,236 12-lead ECGs signals from 811 municipalities in Brazil are transformed to ECG images in varying lead conformations to train a convolutional neural network (CNN) identifying 6 physician-defined clinical labels spanning rhythm and conduction disorders, and a hidden label for gender. The image-based model performs well on a distinct test set validated by at least two cardiologists (average AUROC 0.99, AUPRC 0.86), an external validation set of 21,785 ECGs from Germany (average AUROC 0.97, AUPRC 0.73), and printed ECGs, with performance superior to signal-based models, and learning clinically relevant cues based on Grad-CAM. The model allows the application of AI to ECGs across broad settings.
  •  
8.
  • Sochalski, Julie, et al. (författare)
  • What works in chronic care management : the case of heart failure.
  • 2009
  • Ingår i: Health affairs (Project Hope). - : Health Affairs (Project Hope). - 1544-5208 .- 0278-2715. ; 28:1, s. 179-89
  • Tidskriftsartikel (refereegranskat)abstract
    • The evidence base of what works in chronic care management programs is underdeveloped. To fill the gap, we pooled and reanalyzed data from ten randomized clinical trials of heart failure care management programs to discern how program delivery methods contribute to patient outcomes. We found that patients enrolled in programs using multi-disciplinary teams and in programs using in-person communication had significantly fewer hospital readmissions and readmission days than routine care patients had. Our study offers policymakers and health plan administrators important guideposts for developing an evidence base on which to build effective policy and programmatic initiatives for chronic care management.
  •  
Skapa referenser, mejla, bekava och länka
  • Resultat 1-8 av 8

Kungliga biblioteket hanterar dina personuppgifter i enlighet med EU:s dataskyddsförordning (2018), GDPR. Läs mer om hur det funkar här.
Så här hanterar KB dina uppgifter vid användning av denna tjänst.

 
pil uppåt Stäng

Kopiera och spara länken för att återkomma till aktuell vy