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Holtrop J, Bhatt DL, Ray KK, Mach F, Smulders YM, Carballo D, Steg PG, Visseren FLJ, Dorresteijn JAN. Impact of the 2021 European Society for Cardiology prevention guideline's stepwise approach for cardiovascular risk factor treatment in patients with established atherosclerotic cardiovascular disease. Eur J Prev Cardiol 2024; 31:754-762. [PMID: 38324720 DOI: 10.1093/eurjpc/zwae038] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/16/2023] [Revised: 01/24/2024] [Accepted: 01/27/2024] [Indexed: 02/09/2024]
Abstract
AIMS This study aimed to evaluate the stepwise approach for cardiovascular (CV) risk factor treatment as outlined by the European Society for Cardiology 2021 guidelines on CV disease (CVD) prevention in patients with established atherosclerotic CVD (ASCVD). METHODS AND RESULTS In patients with ASCVD, included in UCC-SMART (n = 8730) and European parts of the REACH registry (n = 18 364), the 10-year CV risk was estimated using SMART2. Treatment effects were derived from meta-analyses and trials. Step 1 recommendations were LDL cholesterol (LDLc) < 1.8 mmol/L, systolic blood pressure (SBP) < 140 mmHg, using any antithrombotic medication, sodium-glucose co-transporter 2 (SGLT2) inhibition, and smoking cessation. Step 2 recommendations were LDLc < 1.4 mmol/L, SBP < 130 mmHg, dual-pathway inhibition (DPI, aspirin plus low-dose rivaroxaban), colchicine, glucagon-like peptide (GLP)-1 receptor agonists, and eicosapentaenoic acid. Step 2 was modelled accounting for Step 1 non-attainment. With current treatment, residual CV risk was 22%, 32%, and 60% in the low, moderate, and pooled (very) high European risk regions, respectively. Step 2 could prevent up to 198, 223 and 245 events per 1000 patients treated, respectively. Intensified LDLc reduction, colchicine, and DPI could be applied to most patients, preventing up to 57, 74, and 59 events per 1000 patients treated, respectively. Following Step 2, the number of patients with a CV risk of <10% could increase from 20%, 6.4%, and 0.5%, following Step 1, to 63%, 48%, and 12%, in the respective risk regions. CONCLUSION With current treatment, residual CV risk in patients with ASCVD remains high across all European risk regions. The intensified Step 2 treatment options result in marked further reduction of residual CV risk in patients with established ASCVD. KEY FINDINGS Guideline-recommended intensive treatment of patients with cardiovascular disease could prevent additional 198-245 new cardiovascular events for every 1000 patients treated.
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Affiliation(s)
- Joris Holtrop
- Department of Vascular Medicine, University Medical Centre Utrecht, Heidelberglaan 100, Utrecht, 3584 CX, The Netherlands
| | - Deepak L Bhatt
- Mount Sinai Fuster Heart Hospital, Icahn School of Medicine at Mount Sinai Health System, New York, NY, USA
| | - Kausik K Ray
- Imperial Centre for Cardiovascular Disease Prevention, ICTU-Global, Imperial College London, London, UK
| | - François Mach
- Division of Cardiology, Faculty of Medicine, Geneva University Hospitals, Geneva, Switzerland
| | - Yvo M Smulders
- Department of Internal Medicine, VU University Medical Center, Amsterdam, The Netherlands
| | - David Carballo
- Division of Cardiology, Faculty of Medicine, Geneva University Hospitals, Geneva, Switzerland
| | - Philippe Gabriel Steg
- Department of Cardiology, Université Paris-Cité, FACT (French Alliance for Cardiovascular Trials) NSERM1148/LVTS, AP-HP, Hôpital Bichat, Paris, France
| | - Frank L J Visseren
- Department of Vascular Medicine, University Medical Centre Utrecht, Heidelberglaan 100, Utrecht, 3584 CX, The Netherlands
| | - Jannick A N Dorresteijn
- Department of Vascular Medicine, University Medical Centre Utrecht, Heidelberglaan 100, Utrecht, 3584 CX, The Netherlands
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van der Vaart TW, Prins JM, Goorhuis A, Lemkes BA, Sigaloff KCE, Spoorenberg V, Stijnis C, Bonten MJM, van der Meer JTM. The Utility of Risk Factors to Define Complicated Staphylococcus aureus Bacteremia in a Setting With Low Methicillin-Resistant S. aureus Prevalence. Clin Infect Dis 2024; 78:846-854. [PMID: 38157401 PMCID: PMC11006106 DOI: 10.1093/cid/ciad784] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/19/2023] [Revised: 12/06/2023] [Accepted: 12/17/2023] [Indexed: 01/03/2024] Open
Abstract
INTRODUCTION Recommended duration of antibiotic treatment of Staphylococcus aureus bacteremia (SAB) is frequently based on distinguishing uncomplicated and complicated SAB, and several risk factors at the onset of infection have been proposed to define complicated SAB. Predictive values of risk factors for complicated SAB have not been validated, and consequences of their use on antibiotic prescriptions are unknown. METHODS In a prospective cohort, patients with SAB were categorized as complicated or uncomplicated through adjudication (reference definition). Associations and predictive values of 9 risk factors were determined, compared with the reference definition, as was accuracy of Infectious Diseases Society of America (IDSA) criteria that include 4 risk factors, and the projected consequences of applying IDSA criteria on antibiotic use. RESULTS Among 490 patients, 296 (60%) had complicated SAB. In multivariable analysis, persistent bacteremia (odds ratio [OR], 6.8; 95% confidence interval [CI], 3.9-12.0), community acquisition of SAB (OR, 2.9; 95% CI, 1.9-4.7) and presence of prosthetic material (OR, 2.3; 95% CI, 1.5-3.6) were associated with complicated SAB. Presence of any of the 4 risk factors in the IDSA definition of complicated SAB had a positive predictive value of 70.9% (95% CI, 65.5-75.9) and a negative predictive value of 57.5% (95% CI, 49.1-64.8). Compared with the reference, IDSA criteria yielded 24 (5%) false-negative and 90 (18%) false-positive classifications of complicated SAB. Median duration of antibiotic treatment of these 90 patients was 16 days (interquartile range, 14-19), all with favorable clinical outcome. CONCLUSIONS Risk factors have low to moderate predictive value to identify complicated SAB and their use may lead to unnecessary prolonged antibiotic use.
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Affiliation(s)
- Thomas W van der Vaart
- Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands
- Department of Internal Medicine, Division of Infectious Diseases, Amsterdam UMC, University of Amsterdam, Amsterdam, The Netherlands
| | - Jan M Prins
- Department of Internal Medicine, Division of Infectious Diseases, Amsterdam UMC, University of Amsterdam, Amsterdam, The Netherlands
| | - Abraham Goorhuis
- Department of Internal Medicine, Division of Infectious Diseases, Amsterdam UMC, University of Amsterdam, Amsterdam, The Netherlands
| | - Bregtje A Lemkes
- Department of Internal Medicine, Division of Infectious Diseases, Amsterdam UMC, University of Amsterdam, Amsterdam, The Netherlands
| | - Kim C E Sigaloff
- Department of Internal Medicine, Division of Infectious Diseases, Amsterdam UMC, University of Amsterdam, Amsterdam, The Netherlands
| | - Veroniek Spoorenberg
- Department of Internal Medicine, Division of Infectious Diseases, Amsterdam UMC, University of Amsterdam, Amsterdam, The Netherlands
| | - Cornelis Stijnis
- Department of Internal Medicine, Division of Infectious Diseases, Amsterdam UMC, University of Amsterdam, Amsterdam, The Netherlands
| | - Marc J M Bonten
- Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands
| | - Jan T M van der Meer
- Department of Internal Medicine, Division of Infectious Diseases, Amsterdam UMC, University of Amsterdam, Amsterdam, The Netherlands
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Jukema BN, de Hond TAP, Kroon M, Maranus AE, Koenderman L, Kaasjager KAH. Point-of-care neutrophil and monocyte surface markers differentiate bacterial from viral infections at the emergency department within 30 min. J Leukoc Biol 2024; 115:714-722. [PMID: 38169315 DOI: 10.1093/jleuko/qiad163] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/11/2023] [Revised: 11/21/2023] [Accepted: 12/12/2023] [Indexed: 01/05/2024] Open
Abstract
Rapid discrimination between viral and bacterial infections in a point-of-care setting will improve clinical outcome. Expression of CD64 on neutrophils (neuCD64) increases during bacterial infections, whereas expression of CD169 on classical monocytes (cmCD169) increases during viral infections. The diagnostic value of automated point-of-care neuCD64 and cmCD169 analysis was assessed for detecting bacterial and viral infections at the emergency department. Additionally, their value as input for machine learning models was studied. A prospective observational cohort study in patients suspected of infection was performed at an emergency department. A fully automated point-of-care flow cytometer measured neuCD64, cmCD169, and additional leukocyte surface markers. Flow cytometry data were gated using the FlowSOM algorithm. Bacterial and viral infections were assessed in standardized clinical care. The sole and combined diagnostic value of the markers was investigated. Clustering based on unsupervised machine learning identified unique patient clusters. Eighty-six patients were included. Thirty-five had a bacterial infection, 30 had a viral infection, and 21 had no infection. neuCD64 was increased in bacterial infections (P < 0.001), with an area under the receiver operating characteristic curve (AUROC) of 0.73. cmCD169 was higher in virally infected patients (P < 0.001; AUROC 0.79). Multivariate analyses incorporating additional markers increased the AUROC for bacterial and viral infections to 0.86 and 0.93, respectively. The additional clustering identified 4 distinctive patient clusters based on infection type and outcome. Automated neuCD64 and cmCD169 determination can discriminate between bacterial and viral infections. These markers can be determined within 30 min, allowing fast infection diagnostics in the acute clinical setting.
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Affiliation(s)
- Bernard N Jukema
- Department of Respiratory Medicine, University Medical Centre Utrecht, Utrecht University, Heidelberglaan 100, Utrecht, 3584 CX, The Netherlands
- Centre for Translational Immunology, University Medical Centre Utrecht, Utrecht University, Heidelberglaan 100, Utrecht, 3584 CX, The Netherlands
| | - Titus A P de Hond
- Department of Internal Medicine and Acute Medicine, University Medical Centre Utrecht, Utrecht University, Heidelberglaan 100, Utrecht, 3584 CX, The Netherlands
| | - Martijn Kroon
- Centre for Translational Immunology, University Medical Centre Utrecht, Utrecht University, Heidelberglaan 100, Utrecht, 3584 CX, The Netherlands
| | - Anna E Maranus
- Centre for Translational Immunology, University Medical Centre Utrecht, Utrecht University, Heidelberglaan 100, Utrecht, 3584 CX, The Netherlands
| | - Leo Koenderman
- Department of Respiratory Medicine, University Medical Centre Utrecht, Utrecht University, Heidelberglaan 100, Utrecht, 3584 CX, The Netherlands
- Centre for Translational Immunology, University Medical Centre Utrecht, Utrecht University, Heidelberglaan 100, Utrecht, 3584 CX, The Netherlands
| | - Karin A H Kaasjager
- Department of Internal Medicine and Acute Medicine, University Medical Centre Utrecht, Utrecht University, Heidelberglaan 100, Utrecht, 3584 CX, The Netherlands
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Castelijns MC, Helmink MAG, Hageman SHJ, Asselbergs FW, de Borst GJ, Bots ML, Cramer MJ, Dorresteijn JAN, Emmelot-Vonk MH, Geerlings MI, de Jong PA, van der Kaaij NP, Kappelle LJ, Lely AT, van der Meer MG, Mol BM, Nathoe HM, Onland-Moret NC, van Petersen RB, Ruigrok YM, van Smeden M, Teraa M, Vandersteen A, Verhaar MC, Westerink J, Visseren FLJ. Cohort profile: the Utrecht Cardiovascular Cohort-Second Manifestations of Arterial Disease (UCC-SMART) Study-an ongoing prospective cohort study of patients at high cardiovascular risk in the Netherlands. BMJ Open 2023; 13:e066952. [PMID: 36806141 PMCID: PMC9944278 DOI: 10.1136/bmjopen-2022-066952] [Citation(s) in RCA: 15] [Impact Index Per Article: 15.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/22/2023] Open
Abstract
PURPOSE The Utrecht Cardiovascular Cohort-Second Manifestations of Arterial Disease (UCC-SMART) Study is an ongoing prospective single-centre cohort study with the aim to assess important determinants and the prognosis of cardiovascular disease progression. This article provides an update of the rationale, design, included patients, measurements and findings from the start in 1996 to date. PARTICIPANTS The UCC-SMART Study includes patients aged 18-90 years referred to the University Medical Center Utrecht, the Netherlands, for management of cardiovascular disease (CVD) or severe cardiovascular risk factors. Since September 1996, a total of 14 830 patients have been included. Upon inclusion, patients undergo a standardised screening programme, including questionnaires, vital signs, laboratory measurements, an ECG, vascular ultrasound of carotid arteries and aorta, ankle-brachial index and ultrasound measurements of adipose tissue, kidney size and intima-media thickness. Outcomes of interest are collected through annual questionnaires and adjudicated by an endpoint committee. FINDINGS TO DATE By May 2022, the included patients contributed to a total follow-up time of over 134 000 person-years. During follow-up, 2259 patients suffered a vascular endpoint (including non-fatal myocardial infarction, non-fatal stroke and vascular death) and 2794 all-cause deaths, 943 incident cases of diabetes and 2139 incident cases of cancer were observed up until January 2020. The UCC-SMART cohort contributed to over 350 articles published in peer-reviewed journals, including prediction models recommended by the 2021 European Society of Cardiology CVD prevention guidelines. FUTURE PLANS The UCC-SMART Study guarantees an infrastructure for research in patients at high cardiovascular risk. The cohort will continue to include about 600 patients yearly and follow-up will be ongoing to ensure an up-to-date cohort in accordance with current healthcare and scientific knowledge. In the near future, UCC-SMART will be enriched by echocardiography, and a food frequency questionnaire at baseline enabling the assessment of associations between nutrition and CVD and diabetes.
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Affiliation(s)
- Maria C Castelijns
- Department of Vascular Medicine, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Marga A G Helmink
- Department of Vascular Medicine, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Steven H J Hageman
- Department of Vascular Medicine, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Folkert W Asselbergs
- Department of Cardiology, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Gert J de Borst
- Department of Vascular Surgery, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Michiel L Bots
- Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Maarten J Cramer
- Department of Cardiology, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Jannick A N Dorresteijn
- Department of Vascular Medicine, University Medical Center Utrecht, Utrecht, The Netherlands
| | | | - Mirjam I Geerlings
- Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Pim A de Jong
- Department of Radiology, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Niels P van der Kaaij
- Department of Cardiothoracic Surgery, University Medical Center Utrecht, Utrecht, The Netherlands
| | - L Jaap Kappelle
- Department of Neurology, University Medical Center Utrecht, Utrecht, The Netherlands
| | - A Titia Lely
- Department of Gynaecology and Obstetrics, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Manon G van der Meer
- Department of Cardiology, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Barend M Mol
- Department of Vascular Surgery, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Hendrik M Nathoe
- Department of Cardiology, University Medical Center Utrecht, Utrecht, The Netherlands
| | - N Charlotte Onland-Moret
- Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Rutger B van Petersen
- Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Ynte M Ruigrok
- Department of Neurology, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Maarten van Smeden
- Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Martin Teraa
- Department of Vascular Surgery, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Angela Vandersteen
- Department of Vascular Medicine, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Marianne C Verhaar
- Department of Nephrology and Hypertension, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Jan Westerink
- Department of Vascular Medicine, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Frank L J Visseren
- Department of Vascular Medicine, University Medical Center Utrecht, Utrecht, The Netherlands
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