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Deaney C, Donaldson M, Meskauskiene A. Implementing an Innovative Lipid Management Technique Using siRNA LDL-C Lowering Therapy: Lessons Learned in an NHS Primary Care Practice With Worked Case Examples. J Prim Care Community Health 2023; 14:21501319231172709. [PMID: 37191000 DOI: 10.1177/21501319231172709] [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] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/17/2023] Open
Abstract
INTRODUCTION The UK Government partnered with industry to tackle cardiovascular disease (CVD) in the first NHS population health agreement. The ambition was to prevent 150 000 strokes, heart attacks and dementia cases over the next 10 years with a new siRNA LDL-C lowering therapy (Inclisiran) delivered within Integrated Care Services by primary care to support a comprehensive approach to lipid management. Following the approval of inclisiran, and guidance published by the National Institute for Health & Care Excellence (NICE) on its use, this paper has been created by a UK general practice to share real-world observations of cases and the potential service benefits of rolling out this innovative drug treatment. The process of identifying patients at risk of atherosclerotic cardiovascular disease (ASCVD) and lessons learned from implementing in practice is also addressed. Workstreams were developed to rapidly roll out a low clinical burden enhanced lipid management program incorporating siRNA LDL-C lowering therapy into primary care practice. APPROACH/METHOD (1) Multi-disciplinary team (MDT) education program based on freely available Academic Health Science Network (AHSN), National Institute for Health & Care Excellence (NICE), and commercial materials. (2) Automated searches using a software program were run to identify "at-risk" patients alongside manual case-finding in everyday clinics. (3) Patients were invited for review using multi-channel modalities. (4) Where appropriate, treatment was commenced after consent was obtained. (5) Automated recall systems are used to ensure follow-up; initially at 3 months, then every 6 months. DISCUSSION AND CONCLUSIONS Enhanced lipid management as a secondary prevention measure is achievable in line with national guidance and objectives. The methodology and education/training processes used in combination with reconstructing the management process can help practice staff realize the program benefits, which in turn can lead to a shift in behavior where all staff embed manual case-finding of high-risk patients into everyday consultations and reviews; enabling rapid identification of eligible patients. Taking a multi-disciplinary, holistic approach to new initiatives reduces service burden, particularly for GPs. Leveraging resources from the AHSN and others removes additional training pressures often associated with new initiatives and provides a wealth of educational material to support primary care MDT upskilling.
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Affiliation(s)
- Carl Deaney
- Marsh Medical Practice, Louth, Lincolnshire, UK
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Cykert S, Keyserling TC, Pignone M, DeWalt D, Weiner BJ, Trogdon JG, Wroth T, Halladay J, Mackey M, Fine J, In Kim J, Cene C. A controlled trial of dissemination and implementation of a cardiovascular risk reduction strategy in small primary care practices. Health Serv Res 2020; 55:944-953. [PMID: 33047340 DOI: 10.1111/1475-6773.13571] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/23/2022] Open
Abstract
OBJECTIVE To assess the effect of dissemination and implementation of an intervention consisting of practice facilitation and a risk-stratified, population management dashboard on cardiovascular risk reduction for patients at high risk in small, primary care practices. STUDY SETTING A total of 219 small primary care practices (≤10 clinicians per site) across North Carolina with primary data collection from electronic health records (EHRs) from the fourth quarter of 2015 through the second quarter of 2018. STUDY DESIGN We performed a stepped-wedge, stratified, cluster randomized trial of a one-year intervention consisting of practice facilitation utilizing quality improvement techniques coupled with a cardiovascular dashboard that included lists of risk-stratified adults, aged 40-79 years and their unmet treatment opportunities. The primary outcome was change in 10-Year ASCVD Risk score among all patients with a baseline score ≥10 percent from baseline to 3 months postintervention. DATA COLLECTION/ EXTRACTION METHODS Data extracts were securely transferred from practices on a nightly basis from their EHR to the research team registry. PRINCIPLE FINDINGS ASCVD risk scores were assessed on 437 556 patients and 146 826 had a calculated 10-year risk ≥10 percent. The mean baseline risk was 23.4 percent (SD ± 12.6 percent). Postintervention, the absolute risk reduction was 6.3 percent (95% CI 6.3, 6.4). Models considering calendar time and stepped-wedge controls revealed most of the improvement (4.0 of 6.3 percent) was attributable to the intervention and not secular trends. In multivariate analysis, male gender, age >65 years, low-income (<$40 000), and Black race (P < .001 for all variables) were each associated with greater risk reductions. CONCLUSION A risk-stratified, population management dashboard combined with practice facilitation led to substantial reductions of 10-year ASCVD risk for patients at high risk. Similar approaches could lead to effective dissemination and implementation of other new evidence, especially in rural and other under-resourced practices. Registration: ClinicalTrials.Gov 15-0479.
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Affiliation(s)
- Samuel Cykert
- The Cecil G. Sheps Center for Health Services Research, The University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA.,Division of General Internal Medicine and Clinical Epidemiology, The University of North Carolina School of Medicine, Chapel Hill, North Carolina, USA
| | - Thomas C Keyserling
- Division of General Internal Medicine and Clinical Epidemiology, The University of North Carolina School of Medicine, Chapel Hill, North Carolina, USA.,Center for Health Promotion and Disease Prevention, The Gillings School of Global Public Health, The University of North Carolina, Chapel Hill, North Carolina, USA
| | - Michael Pignone
- Department of Internal Medicine, The Dell Medical School, University of Texas, Austin, Texas, USA
| | - Darren DeWalt
- The Cecil G. Sheps Center for Health Services Research, The University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA.,Division of General Internal Medicine and Clinical Epidemiology, The University of North Carolina School of Medicine, Chapel Hill, North Carolina, USA
| | - Bryan J Weiner
- Department of Global Public Health, School of Public Health, University of Washington, Seattle, Washington, USA
| | - Justin G Trogdon
- Department of Health Policy and Management, The Gillings School of Global Public Health, The University of North Carolina, Chapel Hill, North Carolina, USA
| | - Thomas Wroth
- Community Care of North Carolina, Raleigh, North Carolina, USA
| | - Jacqueline Halladay
- The Cecil G. Sheps Center for Health Services Research, The University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA.,Department of Family Medicine, The University of North Carolina School of Medicine, Chapel Hill, North Carolina, USA
| | - Monique Mackey
- The North Carolina Area Health Education Centers Program, Chapel Hill, North Carolina, USA
| | - Jason Fine
- Department of Biostatistics, The Gillings School of Global Public Health, The University of North Carolina, Chapel Hill, North Carolina, USA
| | - Jung In Kim
- Department of Statistics, Eberly College of Science, The Pennsylvania State University, University Park, Pennsylvania, USA.,Department of Nutritional Sciences, College of Health and Human Development, The Pennsylvania State University, University Park, Pennsylvania, USA
| | - Crystal Cene
- The Cecil G. Sheps Center for Health Services Research, The University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA.,Division of General Internal Medicine and Clinical Epidemiology, The University of North Carolina School of Medicine, Chapel Hill, North Carolina, USA
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Ho HVT, Jovanovski E, Zurbau A, Blanco Mejia S, Sievenpiper JL, Au-Yeung F, Jenkins AL, Duvnjak L, Leiter L, Vuksan V. A systematic review and meta-analysis of randomized controlled trials of the effect of konjac glucomannan, a viscous soluble fiber, on LDL cholesterol and the new lipid targets non-HDL cholesterol and apolipoprotein B. Am J Clin Nutr 2017; 105:1239-1247. [PMID: 28356275 DOI: 10.3945/ajcn.116.142158] [Citation(s) in RCA: 57] [Impact Index Per Article: 8.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/23/2016] [Accepted: 02/21/2017] [Indexed: 11/14/2022] Open
Abstract
Background: Evidence from randomized controlled trials (RCTs) suggests the consumption of konjac glucomannan (KJM), a viscous soluble fiber, for improving LDL-cholesterol concentrations. It has also been suggested that the cholesterol-lowering potential of KJM may be greater than that of other fibers. However, trials have been relatively scarce and limited in sample size and duration, and the effect estimates have been inconsistent. The effect of KJM on new lipid targets of cardiovascular disease (CVD) risk is also unknown.Objective: This systematic review and meta-analysis aimed to assess the effect of KJM on LDL cholesterol, non-HDL cholesterol, and apolipoprotein B.Design: Medline, Embase, CINAHL, and the Cochrane Central databases were searched. We included RCTs with a follow-up of ≥3 wk that assessed the effect of KJM on LDL cholesterol, non-HDL cholesterol, or apolipoprotein B. Data were pooled by using the generic inverse-variance method with random-effects models and expressed as mean differences (MDs) with 95% CIs. Heterogeneity was assessed by the Cochran Q statistic and quantified by the I2 statistic.Results: Twelve studies (n = 370), 8 in adults and 4 in children, met the inclusion criteria. KJM significantly lowered LDL cholesterol (MD: -0.35 mmol/L; 95% CI: -0.46, -0.25 mmol/L) and non-HDL cholesterol (MD: -0.32 mmol/L; 95% CI: -0.46, -0.19 mmol/L). Data from 6 trials suggested no impact of KJM on apolipoprotein B.Conclusions: Our findings support the intake of ∼3 g KJM/d for reductions in LDL cholesterol and non-HDL cholesterol of 10% and 7%, respectively. The information may be of interest to health agencies in crafting future dietary recommendations related to reduction in CVD risk. This study was registered at clinicaltrials.gov as NCT02068248.
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Affiliation(s)
- Hoang Vi Thanh Ho
- Clinical Nutrition and Risk Factor Modification Centre.,Department of Nutritional Sciences, Faculty of Medicine, University of Toronto, Toronto, Canada
| | - Elena Jovanovski
- Clinical Nutrition and Risk Factor Modification Centre.,Department of Nutritional Sciences, Faculty of Medicine, University of Toronto, Toronto, Canada
| | - Andreea Zurbau
- Clinical Nutrition and Risk Factor Modification Centre.,Department of Nutritional Sciences, Faculty of Medicine, University of Toronto, Toronto, Canada
| | - Sonia Blanco Mejia
- Clinical Nutrition and Risk Factor Modification Centre.,Toronto 3D Knowledge Synthesis and Clinical Trials Unit, St. Michael's Hospital, Toronto, Canada.,Department of Nutritional Sciences, Faculty of Medicine, University of Toronto, Toronto, Canada
| | - John L Sievenpiper
- Clinical Nutrition and Risk Factor Modification Centre.,Department of Nutritional Sciences, Faculty of Medicine, University of Toronto, Toronto, Canada
| | - Fei Au-Yeung
- Clinical Nutrition and Risk Factor Modification Centre.,Department of Nutritional Sciences, Faculty of Medicine, University of Toronto, Toronto, Canada
| | | | - Lea Duvnjak
- Clinic for Diabetes, Endocrinology and Metabolic Diseases Vuk Vrhovac, University Hospital Merkur, University of Zagreb, School of Medicine, Zagreb, Croatia; and
| | - Lawrence Leiter
- Clinical Nutrition and Risk Factor Modification Centre.,Li Ka Shing Knowledge Institute.,Division of Endocrinology and Medicine, and.,Department of Nutritional Sciences, Faculty of Medicine, University of Toronto, Toronto, Canada
| | - Vladimir Vuksan
- Clinical Nutrition and Risk Factor Modification Centre, .,Department of Nutritional Sciences, Faculty of Medicine, University of Toronto, Toronto, Canada
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