Pharmacist-Led Optimisation Significantly Reduces Health Inequalities and Improves Lipid Control in Deprived Post-Acute Coronary Syndrome Patients

Pharmacist-Led Optimisation Significantly Reduces Health Inequalities and Improves Lipid Control in Deprived Post-Acute Coronary Syndrome Patients | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Pharmacist-Led Optimisation Significantly Reduces Health Inequalities and Improves Lipid Control in Deprived Post-Acute Coronary Syndrome Patients Matthew Hart, Ahai Luvai, Jon Rees, Hamde Nazar, Azfar Zaman This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8733006/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 7 You are reading this latest preprint version Abstract Background Atherosclerotic cardiovascular disease remains a leading cause of morbidity and mortality, with outcomes disproportionately worse in socioeconomically deprived populations. Despite clear guideline recommendations, therapeutic inertia frequently prevents high-risk patients from achieving optimal lipid targets following acute coronary syndrome. This service evaluation assessed the impact of a pharmacist-led lipid optimisation clinic on lipid control and health inequalities in a high-risk post-acute coronary syndrome population. Methods This service evaluation was conducted at a tertiary cardiothoracic centre in the North East of England. A cohort of 816 post-acute coronary syndrome patients who had not achieved lipid targets were reviewed in a pharmacist-led clinic delivered by an independent prescriber. Lipid-lowering therapy was intensified in accordance with national guidance through face-to-face or telephone consultations. Primary outcomes were changes in non-high-density lipoprotein cholesterol and low-density lipoprotein cholesterol across three time points: baseline, following cardiology-led optimisation, and following pharmacist-led intervention. Planned comparisons using analysis of variance assessed changes over time. A secondary factorial analysis of variance examined differential effects by socioeconomic deprivation status, defined using the CORE20 metric. Results Of the 816 patients included, 698 (85%) were classified within the most deprived CORE20 group. Following pharmacist-led optimisation, mean non-high-density lipoprotein cholesterol decreased from 3.91 mmol/L to 2.32 mmol/L and mean low-density lipoprotein cholesterol decreased from 3.02 mmol/L to 1.60 mmol/L. Overall, 70% of patients achieved guideline-directed lipid targets, corresponding to a number needed to treat of four. Factorial analysis demonstrated a significant interaction between intervention stage and deprivation status, with patients in the CORE20 group experiencing greater absolute lipid reductions than non-CORE20 patients (mean low-density lipoprotein cholesterol reduction 1.55 mmol/L vs 1.29 mmol/L). Conclusions A pharmacist-led lipid optimisation clinic significantly improved lipid target attainment and disproportionately benefited patients from the most socioeconomically deprived backgrounds. This model represents a scalable strategy to reduce therapeutic inertia and mitigate health inequalities in secondary cardiovascular prevention. Trial Registration ​Clinical trial number: not applicable. This study was conducted as a service evaluation and quality improvement initiative and was not prospectively registered. acute coronary syndrome lipid optimisation pharmacist-led intervention health inequalities secondary prevention CORE20PLUS5 LDL cholesterol non-HDL cholesterol Figures Figure 1 Figure 2 Figure 3 Contributions to the Literature Text box 1. Contributions to the Literature ● Cardiovascular prevention strategies often fail to reach socioeconomically deprived populations, contributing to persistent health inequalities despite clear clinical guidelines. ● This study provides real-world public health evidence that pharmacist-led services can reduce treatment gaps in high-risk, deprived communities following acute coronary events. ● It demonstrates how targeted service design aligned with national health-equity frameworks can deliver greater benefit to the most disadvantaged groups. ● The findings support scalable, workforce-based interventions as a practical approach to improving equity in chronic disease management. Background Atherosclerotic cardiovascular disease (ASCVD) remains the leading cause of mortality globally. In the United Kingdom, ASCVD is responsible for a substantial burden, contributing approximately 25–28% of all cardiovascular disease (CVD) deaths 1 . Low-density lipoprotein cholesterol (LDL-C) is a major modifiable risk factor, and the cornerstone of secondary prevention is intensive lipid-lowering therapy (LLT). Contemporary guidelines advocate for aggressive targets, often below 1.4 mmol/L or 1.8 mmol/L for LDL-C 2,3 , given the proven proportional reduction in major ASCVD events for every 1.0 mmol/L LDL-C decrease 4 . Despite the clear evidence and established treatment pathways, global data, such as from the SANTORINI study, repeatedly demonstrate that many high-risk patients fail to achieve guideline-recommended targets 5 , a phenomenon termed therapeutic inertia 6 . This failure to escalate therapy is particularly concerning in the immediate post-ACS period when the risk of recurrence is highest. The Challenge of Health Inequalities Therapeutic inertia is compounded by profound socio-economic health inequalities 7 . Evidence indicates that individuals residing in deprived areas face a higher burden of cardiovascular risk factors and are less likely to adhere to long-term preventive strategies. Within the North East of England, patients in the two most deprived deciles, often referred to as the CORE20 population 8 , suffer disproportionately from cardiovascular morbidity and mortality. Identifying and addressing effective service delivery models for this vulnerable population is a major public health priority. Rationale and Aims To address both therapeutic inertia and health inequalities, a dedicated, pharmacist-led post-ACS optimisation clinic was established. Pharmacists, functioning as independent prescribers, are ideally positioned to deliver this intensive, evidence-based care due to their expertise in medication review, titration, and patient-centred counselling. This service evaluation aimed to: Evaluate the efficacy of the pharmacist-led clinic in achieving guideline-directed lipid targets (non-HDL-C and LDL-C) in high-risk post-ACS patients. Determine the impact of the intervention on health inequalities by assessing the differential response to treatment based on CORE20 deprivation status. Methods Study Design and Setting This project was conducted as a service evaluation and quality improvement initiative within a tertiary cardiothoracic centre in the North East of England between May 2023 and October 2024. Reporting follows the SQUIRE 2.0 guidelines 9 for quality improvement reporting excellence. The clinic was based at a tertiary cardiothoracic centre covering a large geographical area within the North East of England, serving a diverse patient population with high rates of socioeconomic deprivation. It was developed through collaborative input between cardiology, the lipid clinic, and pharmacy, and represents an adaptation of a previously implemented model used for secondary prevention care in vascular surgery and diabetic foot patients. On a monthly basis, the electronic prescribing system generated a report of all patients who had undergone invasive coronary angiography in the preceding month. Two filters were applied to identify high-risk cardiovascular patients: A modified PEGASUS trial criteria, and Failure to achieve target lipid levels on existing therapy (see Fig. 1 : Inclusion and Exclusion Flowchart). For patients meeting inclusion criteria, relevant data were captured using an Excel spreadsheet. This included: Demographics (age, sex, postcode, ethnicity) Lipid-modifying therapy Previous lipid measurements Documented medication intolerance Comorbidities The clinic operated two face-to-face and two telephone clinics per week, delivered by a trained clinical pharmacist (MH) who was an independent prescriber authorised to prescribe the full range of NICE-approved lipid-lowering therapies. Management followed both local and national guidelines, with patients prioritised based on individualised cardiovascular risk. The service was staffed solely by one pharmacist working 37.5 hours per week (five working days), with nursing support for injectable administration. Funding was provided through a collaborative agreement between the hospital and a pharmaceutical company for a limited two-year period. Once identified, patients were contacted by the pharmacist for a face-to-face consultation. This included: Full medication history Review of lipid profiles Discussion of secondary prevention targets, risks, and medication side effects Therapy changes were made in consultation with patients and either prescribed directly or communicated to the patient’s primary care team. Outcomes were documented in the electronic patient record, with copies sent to primary care. At three-monthly follow-ups, therapies were reviewed for: Adherence Adverse effects Efficacy based on updated lipid profiles Progress was evaluated against secondary prevention targets (LDL-C < 1.8 mmol/L or non-HDL cholesterol ≤ 2.5 mmol/L). If targets were not met, further medication adjustments were made in line with guidelines and patient agreement (see Fig. 2 : Patient Flow in the Lipid Optimisation Clinic). Patient Cohort and Definitions The study included 816 patients who had experienced an ACS event (STEMI, NSTEMI or unstable angina). CORE20 Definition: Socio-economic deprivation status was defined using the national CORE20 (Communicate, Organise, Recruit, Empower) metric, which identifies the 20% of the local population residing in the most deprived deciles of the Index of Multiple Deprivation (IMD) 8 . Patients were categorized as CORE20 or non-CORE20. Intervention: Pharmacist-Led Clinic The clinic was managed by a clinical pharmacist who held an Independent Prescriber (IP) qualification and was trained in advanced lipid management protocols. Targeted Follow-up: Patients were reviewed either face-to-face or via telephone consultation, typically every 4–12 weeks until target achievement. Therapeutic Strategy: The pharmacist implemented a structured, guideline-driven escalation pathway for lipid-lowering therapy, initiating with high-intensity statins, advancing to combination regimens, and incorporating injectable agents where clinically appropriate 10 , 11 . Patient Empowerment: Consultations included detailed discussions on adherence, side-effect management, and lifestyle modification, acting as a crucial touchpoint for reinforcement and education. Data Collection and Outcomes Patient data were extracted from the electronic health record (EHR) system, including demographics, comorbidities, prescribed lipid-lowering therapies, and lipid profile results. Lipid measurements were collected at three distinct time points to assess the impact of sequential optimisation: Baseline – at hospital discharge, prior to any outpatient intervention. Time 1 – following cardiology-led optimisation. Time 2 – after pharmacist-led intervention in the lipid optimisation clinic. For each time point, lipid parameters recorded included total cholesterol, triglycerides, HDL-C, non-HDL-C, and calculated LDL-C. Blood test results were available for 214 patients across all three time points, enabling repeated measures analysis to evaluate the incremental effect of each intervention phase. Primary outcomes : Reduction in non-HDL-C and LDL-C levels across the three time points. Proportion of patients achieving guideline-directed lipid targets (non-HDL-C ≤ 2.5 mmol/L or LDL-C ≤ 1.8 mmol/L). Secondary outcomes : Change in prescribing patterns, including increased use of high-intensity statins, combination oral therapies, and injectable agents. Stratified analysis of lipid improvements among patients in the CORE20 most deprived group. Statistical Analysis Statistical analysis was performed using JASP 0.19.3. Descriptive statistics were used to summarize patient characteristics. Analysis of Variance (ANOVA) with a-priori planned comparisons (baseline v time1, time 1 v time 2) was used to compare lipid parameters at each time point. Factorial Analysis of Variance (ANOVA) was employed to test the hypothesis of differential effectiveness, specifically by assessing the interaction effect between the intervention (Baseline, Time 1, Time 2) and the deprivation status (Group: CORE20 vs. Non-CORE20). Statistical significance was set at p < 0.05. Results Baseline Demographics and Status The final cohort included 816 patients, with a mean age of 68.1 years (SD ± 11.2). The profound socio-economic bias in the referral population was confirmed: 85% (698 patients) were classified as CORE20. The CORE20 group were significantly younger and presented with higher baseline total cholesterol, triglycerides, and non-HDL-C compared to the non-CORE20 group, indicating a greater clinical and social risk burden at referral. (See Table 1 ) Table 1 Baseline Demographics and Clinical Characteristics by CORE20 Deprivation Status Total Sample (n = 816) CORE20 (n = 698) Not CORE20 (n = 118) Sex (n, %) M 571(69.9%) F 254 (30.1%) M 471 (67.5%), F 227 (32.5%) M 91 (77.1%), F 27 (22.9%) Age (SD), years M 66.6 (10.9), F 71.1 (11.1) M 66.1 (11.2), F 70.3 (11.2) M 70.2 (9.7), F 76.0 (8.4) Ethnicity 708 (87%) White British 605 (87%) White British 103 (87%) White British IMD decile Mode 1 Median 4 - - Mean (SD) Total Cholesterol (mmol/L) 5.12 (1.17) 5.16 (1.21) 4.92 (0.99) Mean (SD) Triglycerides (mmol/L) 2.16 (1.50) 2.24 (1.58) 1.88 (1.05) Mean (SD) HDL-C (mmol/L) 1.22 (0.35) 1.20 (0.35) 1.26 (0.36) Mean (SD) non-HDL-C (mmol/L) 3.92 (1.14) 3.97 (1.18) 3.65 (0.89) Mean (SD) LDL-C (S) 3.04 (1.01) 3.09 (1.04) 2.91 (0.92) Number (%) at target 15 (1.8%) 12 (1.8%) 3 (2.8%) Mean (SD) distance of non-HDL from target (mmol/L) + 1.42 (1.14) + 1.47 (1.18) + 1.15 (0.89) Number (%) on high intensity statin 650 (79.6%) 567 (81.2%) 83 (70.3%) At the baseline review, 97% (748/769) of patients had a non-HDL-C greater than the 2.5 mmol/L or 1.8 mmol/L LDL- C target. Overall Efficacy and Target Attainment The pharmacist-led intervention (Time 2) produced statistically and clinically significant reductions across all primary lipid parameters (see Table 2 ). The mean absolute LDL-C reduction from baseline was 1.42 mmol/L, comprising an initial 0.39 mmol/L decrease following cardiology-led optimisation and a further 1.03 mmol/L reduction attributable to pharmacist-led care. This structured, intensive management approach enabled 70% of patients (154/210) to achieve guideline-directed lipid targets, yielding a compelling Number Needed to Treat (NNT) of 4. Table 2 Lipid Parameter Changes Across Baseline, Cardiology, and Pharmacist Interventions. Baseline mean (SD) Time 1 mean (SD) Time 2 mean (SD) p Total Cholesterol (mmol/L) 5.08 (1.20) *** 4.72 (0.96) *** 3.55 (0.92) *** < .001 Triglycerides (n = 209) (mmol/L) 2.28 (1.51) 2.23 (1.44) *** 1.89 (1.09) *** 0.006 HDL-C (mmol/L) 1.18 (0.36) ** 1.22 (0.35) ** 1.21 (0.36) 0.017 Non-HDL-C (mmol/L) 3.91 (1.15) *** 3.50 (0.90) *** 2.32 (0.84) *** < .001 LDL-C (Sampson) (n = 205) (mmol/L) 3.02 (1.05) *** 2.63 (0.76) *** 1.60 (0.70) *** < .001 LDL-C reduction (Sampson) (n = 205) (mmol/L) N/A 0.39 (1.06)*** 1.03 (0.99)*** < .001 Note: asterisks indicate significance of a-priori planned comparisons of neighbouring columns. ** p<.01, ***p<.001 As illustrated in Fig. 3 , the proportion of patients reaching lipid targets increased markedly after pharmacist involvement compared to cardiology-led care alone. This visual trend underscores the additive value of pharmacist-led optimisation in overcoming therapeutic inertia and achieving aggressive lipid goals—particularly in high-risk populations. Impact on Health Inequalities (CORE20 Analysis) The secondary analysis using Factorial ANOVA revealed a statistically significant interaction F(1, 814) = 12.56, p < 0.001, between time (pre- and post-intervention) and deprivation status (CORE20 vs. non-CORE20), confirming that the pharmacist-led intervention had a disproportionately greater impact on patients from the most socioeconomically deprived backgrounds. Patients in the CORE20 group experienced a mean LDL-C reduction of 1.55 mmol/L, compared to 1.29 mmol/L in the non-CORE20 group. This difference underscores the clinic’s effectiveness in narrowing the gap in lipid control between deprived and non-deprived populations as shown in Fig. 3 indicating that the intervention's benefit was not uniform but amplified in the most disadvantaged cohort. Medication Escalation Therapeutic success correlated directly with the escalation of lipid-lowering therapy (LLT): At baseline, 792 patients (96%) were receiving LLT, with 743 on statins and 650 (87%) of those on high-intensity statin therapy. Additional agents included Ezetimibe (128 patients), Inclisiran (12), Alirocumab (2), Evolocumab (1), Bempedoic acid (7), and Icosapent ethyl (11). Following pharmacist-led optimisation, among the 541 patients who remained on statins, 499 (92%) were prescribed high-intensity therapy—a statistically significant increase (p < .001). Use of non-statin therapies also rose substantially: Ezetimibe was prescribed to 250 patients, Inclisiran to 102, Alirocumab to 6, Evolocumab to 4, Bempedoic acid to 16, and Icosapent ethyl to 20. These changes reflect a marked intensification of lipid-lowering strategies, contributing to improved target attainment and cardiovascular risk reduction. Discussion Principal Findings and Clinical Significance This service evaluation demonstrates that a pharmacist-led, dedicated optimisation clinic is highly effective at achieving aggressive secondary prevention lipid targets in a real-world, high-risk post-ACS population. The mean LDL-C attainment of 1.60 mmol/L and the impressive 70% target attainment rate significantly outperform those reported in major international registries like SANTORINI, which noted target attainment rates as low as 26.8% across Europe 5 . This substantial difference underscores the success of a targeted, intensive approach in overcoming widespread clinical therapeutic inertia 6 . The calculated NNT of 4 is a compelling metric that strongly supports the clinical value of this dedicated service model 4 . Addressing Health Inequalities One of the most compelling outcomes of this service evaluation is the demonstrable impact on health inequalities, particularly among patients from the most socioeconomically deprived backgrounds. The pharmacist-led clinic was not only clinically effective but also strategically aligned with the NHS England CORE20PLUS5 framework, which prioritizes targeted interventions for the most deprived 20% of the population 8 . The significant interaction effect observed in the CORE20 group highlights that patients facing the greatest barriers to care—such as limited access, lower health literacy, and higher baseline cardiovascular risk—benefited most from the intervention. This suggests that intensive, personalised care models can reverse entrenched disparities in therapeutic outcomes. Several factors contributed to this success: Enhanced Accessibility: Flexible appointment formats (face-to-face and telephone) reduced logistical barriers for patients in deprived areas. Immediate Prescribing Authority: The pharmacist’s independent prescriber status enabled rapid escalation of therapy, bypassing delays common in traditional care pathways. Focused Patient Engagement: Consultations emphasized education, adherence, and shared decision-making, fostering trust and empowerment in populations often underserved by mainstream services. This outcome is particularly important given the well-documented association between deprivation and poor cardiovascular outcomes 12 , 13 . By delivering targeted, intensive lipid optimisation, the pharmacist-led clinic not only improved clinical metrics but also actively reduced therapeutic inequalities—a core objective of the NHS England CORE20PLUS5 framework. These findings support the integration of pharmacist-led models into broader health equity strategies, demonstrating that precision service delivery can be both clinically effective and socially transformative. Limitations and Strengths This project is subject to the limitations of a non-randomized service evaluation. It is not a clinical trial and thus lacks a contemporary control group. Furthermore, data on long-term adherence beyond the intervention period were not collected. However, the study’s strengths are substantial: it represents a large, real-world cohort from a high-volume center; it focuses on a clinically and socially high-risk population (CORE20) 8 ; and it utilizes robust statistical methods (Factorial ANOVA) to definitively demonstrate the impact on socio-economic inequalities. Conclusions The implementation of a pharmacist-led post-ACS lipid optimisation clinic resulted in superior target attainment rates (NNT of 4) compared to routine care, demonstrating a highly effective clinical pathway for secondary prevention. Crucially, this intensive model successfully mitigated health inequalities by being most effective in the most socio-economically deprived (CORE20) patients. We strongly recommend that dedicated, pharmacist-led advanced prescribing clinics be considered as a core component of national strategies to achieve aggressive lipid targets and address disparities in cardiovascular outcomes. Abbreviations ACS acute coronary syndrome ASCVD atherosclerotic cardiovascular disease CORE20 most deprived 20% group by Index of Multiple Deprivation LDL-C low-density lipoprotein cholesterol LLT lipid-lowering therapy. Declarations Ethics Approval and Consent to Participate This study was conducted in accordance with the principles of the Declaration of Helsinki. It was reviewed by the Newcastle upon Tyne Hospitals NHS Foundation Trust Clinical Audit and Service Evaluation Committee and classified as a Service Evaluation/Quality Improvement initiative; therefore, formal Research Ethics Committee approval was not required. The analysis used routinely collected clinical data and all data were anonymised prior to analysis. The requirement for individual informed consent was waived by the committee for this retrospective evaluation of clinical care processes. Consent for Publication Not applicable. The manuscript does not contain any individual person's data in any form that would allow identification. Availability of Data and Materials The datasets generated and analyzed during the current study are stored within the confidential clinical database of the Newcastle upon Tyne Hospitals NHS Foundation Trust. The data are not publicly available due to patient confidentiality restrictions but are available from the corresponding author upon reasonable request and with appropriate institutional data governance approval. Competing Interests The authors declare that they have no competing interests relevant to the content of this manuscript. Funding This service evaluation was funded via a Collaborative Working Agreement between the Newcastle upon Tyne Hospitals NHS Foundation Trust and Novartis. The funder (Novartis) provided financial support for the service delivery but had no role in the study design, data collection, data analysis, data interpretation, manuscript writing, or the decision to submit the manuscript for publication. Authors' Contributions MH: Conceptualization, methodology, design of the clinical service, data curation, formal analysis, and primary manuscript drafting. AL: Clinical input, critical review of the methodology, and manuscript editing. JR: Provided consultation on the statistical analysis (Factorial ANOVA) and critical review of the manuscript's statistical interpretation. HN: Contributed expertise on health inequalities (CORE20) and patient safety research; critical review and editing. AZ: Supervision, clinical validation of the findings, and final critical review of the manuscript. All authors read and approved the final manuscript. Acknowledgments The authors would like to thank the Outpatient department nursing team and administrative staff at the Freeman Hospital for their invaluable support in the delivery of this clinic. References British Heart Foundation. Heart & Circulatory Disease Statistics 2025 [Internet]. London: British Heart Foundation; 2025 Jun [cited 2025 Nov 06]. Available from: https://www.bhf.org.uk/what-we-do/our-research/heart-statistics/heart-statistics-publications/cardiovascular-disease-statistics-2025 Mach F, Baigent C, Catapano AL, Koskinas KC, Casula M, Badimon L, et al. 2019 ESC/EAS Guidelines for the management of dyslipidaemias: lipid modification to reduce cardiovascular risk. Eur Heart J. 2020 Jan;41(1):111–88. Available from: https://doi.org/10.1093/eurheartj/ehz455 National Institute for Health and Care Excellence (NICE). Cardiovascular disease: risk assessment and reduction, including lipid modification (NG238) [Internet]. London: NICE; 2023 Dec [cited 2025 Nov 06]. Available from: https://www.nice.org.uk/guidance/ng238 Webb J, Gonna H, Ray KK. Lipid management: maximising reduction of cardiac risk. Clin Med. 2013;13(6):618–20. Available from: http://dx.doi.org/10.7861/clinmedicine.13-6-618 Ray KK, Aguiar C, Arca M, Connolly DL, Eriksson M, Ferrières J, et al. Use of combination therapy is associated with improved LDL cholesterol management: 1‑year follow‑up results from the European observational SANTORINI study. Eur J Prev Cardiol. 2024 Jun 11;31(15):1792–803. Available from: https://doi.org/10.1093/eurjpc/zwae199 Steen DL, Khan I, Ansell D, Sanchez RJ, Ray KK. Retrospective examination of lipid‑lowering treatment patterns in a real‑world high‑risk cohort in the UK in 2014: comparison with the NICE 2014 lipid modification guidelines. BMJ Open. 2017;7(2):e013255. National Health Equity Evidence Centre. What works: Achieving equitable lipid management [Internet]. London: Health Equity Evidence Centre; May 2024 [cited 2025 Nov 06]. Available from: https://www.heec.co.uk/wp-content/uploads/2024/05/Evidence-brief-equitable-lipid-management.pdf NHS England. Core20PLUS5: An Approach to Reducing Health Inequalities [Internet]. London: NHS England; 2021. Available from:https://www.england.nhs.uk/about/equality/equality-hub/core20plus5/ Ogrinc G, Davies L, Goodman D, Batalden P, Davidoff F, Stevens D. SQUIRE 2.0 (Standards for Quality Improvement Reporting Excellence): Revised publication guidelines from a detailed consensus process. BMJ Qual Saf. 2016 Dec;25(12):986–92. Available from: https://qualitysafety.bmj.com/content/25/12/986 Khatib R, Neely D. National Guidance for Lipid Management: Improving Lipid Management in Secondary Care [Internet]. London: NHS England; 2022 Dec. Available from: https://www.england.nhs.uk/wp-content/uploads/2022/12/national-guidance-for-lipid-management-secondary-care.pdf National Expert and Education Lead in Lipidology (NEELI). Primary Care Lipid Management Guideline [Internet]. London: NEELI; 2023. Available from: https://www.neeli.co.uk/guidelines NHS England. The NHS Long Term Plan [Internet]. London: NHS England; 2019. Available from: https://www.longtermplan.nhs.uk/publication/nhs-long-term-plan/ HEART UK. Cardiovascular Disease Prevention Policy Paper [Internet]. London: HEART UK; 2022. Available from: https://www.heartuk.org.uk/ Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Review Version 1 posted Reviews received at journal 03 Mar, 2026 Reviewers agreed at journal 24 Feb, 2026 Reviewers invited by journal 24 Feb, 2026 Editor invited by journal 02 Feb, 2026 Editor assigned by journal 30 Jan, 2026 Submission checks completed at journal 30 Jan, 2026 First submitted to journal 29 Jan, 2026 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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Trust","correspondingAuthor":false,"prefix":"","firstName":"Ahai","middleName":"","lastName":"Luvai","suffix":""},{"id":596394573,"identity":"3f93d1c0-ffc2-49ee-85cc-622bdaae4150","order_by":2,"name":"Jon Rees","email":"","orcid":"","institution":"University of Sunderland","correspondingAuthor":false,"prefix":"","firstName":"Jon","middleName":"","lastName":"Rees","suffix":""},{"id":596394574,"identity":"e948048c-de72-42cd-a0b4-a24cd59aaa35","order_by":3,"name":"Hamde Nazar","email":"","orcid":"","institution":"Newcastle University","correspondingAuthor":false,"prefix":"","firstName":"Hamde","middleName":"","lastName":"Nazar","suffix":""},{"id":596394575,"identity":"dae60626-92ba-48c5-aeb2-329030fa9950","order_by":4,"name":"Azfar Zaman","email":"","orcid":"","institution":"Freeman Hospital, Newcastle Upon Tyne Hospitals NHS Foundation Trust","correspondingAuthor":false,"prefix":"","firstName":"Azfar","middleName":"","lastName":"Zaman","suffix":""}],"badges":[],"createdAt":"2026-01-29 15:25:01","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-8733006/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8733006/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":103583712,"identity":"d08e9be0-f671-4268-a288-d71bf9d70721","added_by":"auto","created_at":"2026-02-27 10:44:07","extension":"jpeg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":353809,"visible":true,"origin":"","legend":"\u003cp\u003eInclusion and Exclusion flowchart\u003c/p\u003e","description":"","filename":"floatimage1.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-8733006/v1/211df75150f73593aacf8674.jpeg"},{"id":103583711,"identity":"212e6e69-271c-484b-aae1-1455e78c7cd7","added_by":"auto","created_at":"2026-02-27 10:44:07","extension":"jpeg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":337757,"visible":true,"origin":"","legend":"\u003cp\u003ePatient flow in the lipid optimisation clinic.\u003c/p\u003e","description":"","filename":"floatimage2.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-8733006/v1/8daecd1316638387bb430c38.jpeg"},{"id":103583710,"identity":"62066a0f-3cbb-4e7d-a80a-adc8dc41628f","added_by":"auto","created_at":"2026-02-27 10:44:07","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":134409,"visible":true,"origin":"","legend":"\u003cp\u003eProgression of Patients Achieving Lipid Targets (non-HDL ≤2.5 mmol/L or LDL-C ≤1.8 mmol/L) Across Study Stages\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCaption:\u003c/strong\u003e \u003cstrong\u003eFigure 3. \u003c/strong\u003eNumber of patients (achieving or above target non-HDL ≤2.5 mmol/L or LDL-C ≤1.8 mmol/L) at each stage of the study.\u003c/p\u003e","description":"","filename":"floatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-8733006/v1/dcbaaca6a070c81fdce52924.png"},{"id":104399438,"identity":"b42338d0-8f78-4e27-b280-b752bd438a83","added_by":"auto","created_at":"2026-03-11 12:06:07","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1670842,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8733006/v1/de3f86a4-2eef-4afd-b83f-c2ee728a9c7f.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Pharmacist-Led Optimisation Significantly Reduces Health Inequalities and Improves Lipid Control in Deprived Post-Acute Coronary Syndrome Patients","fulltext":[{"header":"Contributions to the Literature","content":" \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"No\" id=\"Taba\" border=\"1\"\u003e \u003ccolgroup cols=\"1\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cdiv class=\"SimplePara\"\u003eText box 1. Contributions to the Literature\u003c/div\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cdiv class=\"SimplePara\"\u003e● \u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003eCardiovascular prevention strategies often fail to reach socioeconomically deprived populations, contributing to persistent health inequalities despite clear clinical guidelines.\u003c/span\u003e\u003c/div\u003e \u003cdiv class=\"SimplePara\"\u003e● \u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003eThis study provides real-world public health evidence that pharmacist-led services can reduce treatment gaps in high-risk, deprived communities following acute coronary events.\u003c/span\u003e\u003c/div\u003e \u003cdiv class=\"SimplePara\"\u003e● \u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003eIt demonstrates how targeted service design aligned with national health-equity frameworks can deliver greater benefit to the most disadvantaged groups.\u003c/span\u003e\u003c/div\u003e \u003cdiv class=\"SimplePara\"\u003e● \u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003eThe findings support scalable, workforce-based interventions as a practical approach to improving equity in chronic disease management.\u003c/span\u003e\u003c/div\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003cbr/\u003e"},{"header":"Background","content":"\u003cp\u003eAtherosclerotic cardiovascular disease (ASCVD) remains the leading cause of mortality globally. In the United Kingdom, ASCVD is responsible for a substantial burden, contributing approximately 25\u0026ndash;28% of all cardiovascular disease (CVD) deaths\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e. Low-density lipoprotein cholesterol (LDL-C) is a major modifiable risk factor, and the cornerstone of secondary prevention is intensive lipid-lowering therapy (LLT). Contemporary guidelines advocate for aggressive targets, often below 1.4 mmol/L or 1.8 mmol/L for LDL-C\u003csup\u003e2,3\u003c/sup\u003e, given the proven proportional reduction in major ASCVD events for every 1.0 mmol/L LDL-C decrease\u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eDespite the clear evidence and established treatment pathways, global data, such as from the SANTORINI study, repeatedly demonstrate that many high-risk patients fail to achieve guideline-recommended targets\u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e, a phenomenon termed therapeutic inertia\u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e. This failure to escalate therapy is particularly concerning in the immediate post-ACS period when the risk of recurrence is highest.\u003c/p\u003e\n\u003ch3\u003eThe Challenge of Health Inequalities\u003c/h3\u003e\n\u003cp\u003eTherapeutic inertia is compounded by profound socio-economic health inequalities\u003csup\u003e\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e. Evidence indicates that individuals residing in deprived areas face a higher burden of cardiovascular risk factors and are less likely to adhere to long-term preventive strategies. Within the North East of England, patients in the two most deprived deciles, often referred to as the CORE20 population\u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e, suffer disproportionately from cardiovascular morbidity and mortality. Identifying and addressing effective service delivery models for this vulnerable population is a major public health priority.\u003c/p\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eRationale and Aims\u003c/h2\u003e \u003cp\u003eTo address both therapeutic inertia and health inequalities, a dedicated, pharmacist-led post-ACS optimisation clinic was established. Pharmacists, functioning as independent prescribers, are ideally positioned to deliver this intensive, evidence-based care due to their expertise in medication review, titration, and patient-centred counselling.\u003c/p\u003e \u003cp\u003eThis service evaluation aimed to:\u003c/p\u003e \u003cp\u003e\u003col\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003e Evaluate the efficacy of the pharmacist-led clinic in achieving guideline-directed lipid targets (non-HDL-C and LDL-C) in high-risk post-ACS patients.\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003eDetermine the impact of the intervention on health inequalities by assessing the differential response to treatment based on CORE20 deprivation status.\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003c/ol\u003e\u003c/p\u003e \u003c/div\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eStudy Design and Setting\u003c/h2\u003e \u003cp\u003eThis project was conducted as a service evaluation and quality improvement initiative within a tertiary cardiothoracic centre in the North East of England between May 2023 and October 2024. Reporting follows the SQUIRE 2.0 guidelines\u003csup\u003e\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u003c/sup\u003e for quality improvement reporting excellence.\u003c/p\u003e \u003cp\u003eThe clinic was based at a tertiary cardiothoracic centre covering a large geographical area within the North East of England, serving a diverse patient population with high rates of socioeconomic deprivation. It was developed through collaborative input between cardiology, the lipid clinic, and pharmacy, and represents an adaptation of a previously implemented model used for secondary prevention care in vascular surgery and diabetic foot patients.\u003c/p\u003e \u003cp\u003eOn a monthly basis, the electronic prescribing system generated a report of all patients who had undergone invasive coronary angiography in the preceding month. Two filters were applied to identify high-risk cardiovascular patients:\u003c/p\u003e \u003cp\u003e \u003col\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eA modified PEGASUS trial criteria, and\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eFailure to achieve target lipid levels on existing therapy (see Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e: Inclusion and Exclusion Flowchart).\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003c/ol\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eFor patients meeting inclusion criteria, relevant data were captured using an Excel spreadsheet. This included:\u003c/p\u003e \u003cp\u003e \u003cul\u003e \u003cli\u003e \u003cp\u003eDemographics (age, sex, postcode, ethnicity)\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eLipid-modifying therapy\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003ePrevious lipid measurements\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eDocumented medication intolerance\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eComorbidities\u003c/p\u003e \u003c/li\u003e \u003c/ul\u003e \u003c/p\u003e \u003cp\u003eThe clinic operated two face-to-face and two telephone clinics per week, delivered by a trained clinical pharmacist (MH) who was an independent prescriber authorised to prescribe the full range of NICE-approved lipid-lowering therapies. Management followed both local and national guidelines, with patients prioritised based on individualised cardiovascular risk.\u003c/p\u003e \u003cp\u003eThe service was staffed solely by one pharmacist working 37.5 hours per week (five working days), with nursing support for injectable administration. Funding was provided through a collaborative agreement between the hospital and a pharmaceutical company for a limited two-year period.\u003c/p\u003e \u003cp\u003eOnce identified, patients were contacted by the pharmacist for a face-to-face consultation. This included:\u003c/p\u003e \u003cp\u003e \u003cul\u003e \u003cli\u003e \u003cp\u003eFull medication history\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eReview of lipid profiles\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eDiscussion of secondary prevention targets, risks, and medication side effects\u003c/p\u003e \u003c/li\u003e \u003c/ul\u003e \u003c/p\u003e \u003cp\u003eTherapy changes were made in consultation with patients and either prescribed directly or communicated to the patient\u0026rsquo;s primary care team. Outcomes were documented in the electronic patient record, with copies sent to primary care.\u003c/p\u003e \u003cp\u003eAt three-monthly follow-ups, therapies were reviewed for:\u003c/p\u003e \u003cp\u003e \u003cul\u003e \u003cli\u003e \u003cp\u003eAdherence\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eAdverse effects\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eEfficacy based on updated lipid profiles\u003c/p\u003e \u003c/li\u003e \u003c/ul\u003e \u003c/p\u003e \u003cp\u003eProgress was evaluated against secondary prevention targets (LDL-C\u0026thinsp;\u0026lt;\u0026thinsp;1.8 mmol/L or non-HDL cholesterol\u0026thinsp;\u0026le;\u0026thinsp;2.5 mmol/L). If targets were not met, further medication adjustments were made in line with guidelines and patient agreement (see Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e: Patient Flow in the Lipid Optimisation Clinic).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003ePatient Cohort and Definitions\u003c/h3\u003e\n\u003cp\u003eThe study included 816 patients who had experienced an ACS event (STEMI, NSTEMI or unstable angina).\u003c/p\u003e \u003cp\u003eCORE20 Definition: Socio-economic deprivation status was defined using the national CORE20 (Communicate, Organise, Recruit, Empower) metric, which identifies the 20% of the local population residing in the most deprived deciles of the Index of Multiple Deprivation (IMD)\u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e. Patients were categorized as CORE20 or non-CORE20.\u003c/p\u003e\n\u003ch3\u003eIntervention: Pharmacist-Led Clinic\u003c/h3\u003e\n\u003cp\u003eThe clinic was managed by a clinical pharmacist who held an Independent Prescriber (IP) qualification and was trained in advanced lipid management protocols.\u003c/p\u003e \u003cp\u003e\u003cul\u003e\u003cli\u003e\u003cp\u003eTargeted Follow-up: Patients were reviewed either face-to-face or via telephone consultation, typically every 4\u0026ndash;12 weeks until target achievement.\u003c/p\u003e\u003c/li\u003e\u003cli\u003e\u003cp\u003eTherapeutic Strategy: The pharmacist implemented a structured, guideline-driven escalation pathway for lipid-lowering therapy, initiating with high-intensity statins, advancing to combination regimens, and incorporating injectable agents where clinically appropriate\u003csup\u003e\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e,\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003c/li\u003e\u003cli\u003e\u003cp\u003ePatient Empowerment: Consultations included detailed discussions on adherence, side-effect management, and lifestyle modification, acting as a crucial touchpoint for reinforcement and education.\u003c/p\u003e\u003c/li\u003e\u003c/ul\u003e\u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eData Collection and Outcomes\u003c/h2\u003e \u003cp\u003ePatient data were extracted from the electronic health record (EHR) system, including demographics, comorbidities, prescribed lipid-lowering therapies, and lipid profile results. Lipid measurements were collected at three distinct time points to assess the impact of sequential optimisation:\u003c/p\u003e \u003cp\u003e \u003col\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eBaseline \u0026ndash; at hospital discharge, prior to any outpatient intervention.\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eTime 1 \u0026ndash; following cardiology-led optimisation.\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eTime 2 \u0026ndash; after pharmacist-led intervention in the lipid optimisation clinic.\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003c/ol\u003e \u003c/p\u003e \u003cp\u003eFor each time point, lipid parameters recorded included total cholesterol, triglycerides, HDL-C, non-HDL-C, and calculated LDL-C. Blood test results were available for 214 patients across all three time points, enabling repeated measures analysis to evaluate the incremental effect of each intervention phase.\u003c/p\u003e \u003c/div\u003e\n\u003cdiv class=\"Heading\"\u003e\u003cb\u003ePrimary outcomes\u003c/b\u003e:\u003c/div\u003e \u003cp\u003e\u003cul\u003e\u003cli\u003e\u003cp\u003eReduction in non-HDL-C and LDL-C levels across the three time points.\u003c/p\u003e\u003c/li\u003e\u003cli\u003e\u003cp\u003e Proportion of patients achieving guideline-directed lipid targets (non-HDL-C\u0026thinsp;\u0026le;\u0026thinsp;2.5 mmol/L or LDL-C\u0026thinsp;\u0026le;\u0026thinsp;1.8 mmol/L).\u003c/p\u003e\u003c/li\u003e\u003c/ul\u003e\u003c/p\u003e\n\u003cdiv class=\"Heading\"\u003e\u003cb\u003eSecondary outcomes\u003c/b\u003e:\u003c/div\u003e \u003cp\u003e \u003cul\u003e \u003cli\u003e \u003cp\u003eChange in prescribing patterns, including increased use of high-intensity statins, combination oral therapies, and injectable agents.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eStratified analysis of lipid improvements among patients in the CORE20 most deprived group.\u003c/p\u003e \u003c/li\u003e \u003c/ul\u003e \u003c/p\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eStatistical Analysis\u003c/h2\u003e \u003cp\u003eStatistical analysis was performed using JASP 0.19.3. Descriptive statistics were used to summarize patient characteristics. Analysis of Variance (ANOVA) with a-priori planned comparisons (baseline v time1, time 1 v time 2) was used to compare lipid parameters at each time point. Factorial Analysis of Variance (ANOVA) was employed to test the hypothesis of differential effectiveness, specifically by assessing the interaction effect between the intervention (Baseline, Time 1, Time 2) and the deprivation status (Group: CORE20 vs. Non-CORE20). Statistical significance was set at p\u0026thinsp;\u0026lt;\u0026thinsp;0.05.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eBaseline Demographics and Status\u003c/h2\u003e \u003cp\u003eThe final cohort included 816 patients, with a mean age of 68.1 years (SD\u0026thinsp;\u0026plusmn;\u0026thinsp;11.2). The profound socio-economic bias in the referral population was confirmed: 85% (698 patients) were classified as CORE20. The CORE20 group were significantly younger and presented with higher baseline total cholesterol, triglycerides, and non-HDL-C compared to the non-CORE20 group, indicating a greater clinical and social risk burden at referral. (See Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e)\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eBaseline Demographics and Clinical Characteristics by CORE20 Deprivation Status\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTotal Sample (n\u0026thinsp;=\u0026thinsp;816)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCORE20 (n\u0026thinsp;=\u0026thinsp;698)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNot CORE20 (n\u0026thinsp;=\u0026thinsp;118)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSex (n, %)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eM 571(69.9%) F 254 (30.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eM 471 (67.5%), F 227 (32.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eM 91 (77.1%), F 27 (22.9%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge (SD), years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eM 66.6 (10.9), F 71.1 (11.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eM 66.1 (11.2), F 70.3 (11.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eM 70.2 (9.7), F 76.0 (8.4)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEthnicity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e708 (87%) White British\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e605 (87%) White British\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e103 (87%) White British\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIMD decile\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMode 1 Median 4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMean (SD) Total Cholesterol (mmol/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5.12 (1.17)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.16 (1.21)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4.92 (0.99)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMean (SD) Triglycerides (mmol/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.16 (1.50)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.24 (1.58)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.88 (1.05)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMean (SD) HDL-C (mmol/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.22 (0.35)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.20 (0.35)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.26 (0.36)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMean (SD) non-HDL-C (mmol/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.92 (1.14)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.97 (1.18)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.65 (0.89)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMean (SD) LDL-C (S)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.04 (1.01)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.09 (1.04)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.91 (0.92)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNumber (%) at target\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e15 (1.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e12 (1.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3 (2.8%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMean (SD) distance of non-HDL from target (mmol/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e+\u0026thinsp;1.42 (1.14)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e+\u0026thinsp;1.47 (1.18)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e+\u0026thinsp;1.15 (0.89)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNumber (%) on high intensity statin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e650 (79.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e567 (81.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e83 (70.3%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eAt the baseline review, 97% (748/769) of patients had a non-HDL-C greater than the 2.5 mmol/L or 1.8 mmol/L LDL- C target.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003eOverall Efficacy and Target Attainment\u003c/h2\u003e \u003cp\u003eThe pharmacist-led intervention (Time 2) produced statistically and clinically significant reductions across all primary lipid parameters (see Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). The mean absolute LDL-C reduction from baseline was 1.42 mmol/L, comprising an initial 0.39 mmol/L decrease following cardiology-led optimisation and a further 1.03 mmol/L reduction attributable to pharmacist-led care. This structured, intensive management approach enabled 70% of patients (154/210) to achieve guideline-directed lipid targets, yielding a compelling Number Needed to Treat (NNT) of 4.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eLipid Parameter Changes Across Baseline, Cardiology, and Pharmacist Interventions.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBaseline mean (SD)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eTime 1 mean (SD)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eTime 2 mean (SD)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003ep\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTotal Cholesterol (mmol/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5.08 (1.20) ***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4.72 (0.96) ***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3.55 (0.92) ***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTriglycerides (n\u0026thinsp;=\u0026thinsp;209) (mmol/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.28 (1.51)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2.23 (1.44) ***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.89 (1.09) ***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.006\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHDL-C (mmol/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.18 (0.36) **\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.22 (0.35) **\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.21 (0.36)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.017\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNon-HDL-C (mmol/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.91 (1.15) ***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3.50 (0.90) ***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2.32 (0.84) ***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLDL-C (Sampson) (n\u0026thinsp;=\u0026thinsp;205) (mmol/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.02 (1.05) ***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2.63 (0.76) ***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.60 (0.70) ***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLDL-C reduction (Sampson) (n\u0026thinsp;=\u0026thinsp;205) (mmol/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.39 (1.06)***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.03 (0.99)***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003eNote: asterisks indicate significance of \u003cem\u003ea-priori\u003c/em\u003e planned comparisons of neighbouring columns. ** p\u0026lt;.01, ***p\u0026lt;.001\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eAs illustrated in Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e, the proportion of patients reaching lipid targets increased markedly after pharmacist involvement compared to cardiology-led care alone. This visual trend underscores the additive value of pharmacist-led optimisation in overcoming therapeutic inertia and achieving aggressive lipid goals\u0026mdash;particularly in high-risk populations.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003eImpact on Health Inequalities (CORE20 Analysis)\u003c/h2\u003e \u003cp\u003eThe secondary analysis using Factorial ANOVA revealed a statistically significant interaction F(1, 814)\u0026thinsp;=\u0026thinsp;12.56, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001, between time (pre- and post-intervention) and deprivation status (CORE20 vs. non-CORE20), confirming that the pharmacist-led intervention had a disproportionately greater impact on patients from the most socioeconomically deprived backgrounds.\u003c/p\u003e \u003cp\u003ePatients in the CORE20 group experienced a mean LDL-C reduction of 1.55 mmol/L, compared to 1.29 mmol/L in the non-CORE20 group. This difference underscores the clinic\u0026rsquo;s effectiveness in narrowing the gap in lipid control between deprived and non-deprived populations as shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e indicating that the intervention's benefit was not uniform but amplified in the most disadvantaged cohort.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003eMedication Escalation\u003c/h2\u003e \u003cp\u003eTherapeutic success correlated directly with the escalation of lipid-lowering therapy (LLT):\u003c/p\u003e \u003cp\u003e \u003cul\u003e \u003cli\u003e \u003cp\u003eAt baseline, 792 patients (96%) were receiving LLT, with 743 on statins and 650 (87%) of those on high-intensity statin therapy. Additional agents included Ezetimibe (128 patients), Inclisiran (12), Alirocumab (2), Evolocumab (1), Bempedoic acid (7), and Icosapent ethyl (11).\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eFollowing pharmacist-led optimisation, among the 541 patients who remained on statins, 499 (92%) were prescribed high-intensity therapy\u0026mdash;a statistically significant increase (p \u0026lt; .001). Use of non-statin therapies also rose substantially: Ezetimibe was prescribed to 250 patients, Inclisiran to 102, Alirocumab to 6, Evolocumab to 4, Bempedoic acid to 16, and Icosapent ethyl to 20. These changes reflect a marked intensification of lipid-lowering strategies, contributing to improved target attainment and cardiovascular risk reduction.\u003c/p\u003e \u003c/li\u003e \u003c/ul\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cdiv id=\"Sec18\" class=\"Section2\"\u003e \u003ch2\u003ePrincipal Findings and Clinical Significance\u003c/h2\u003e \u003cp\u003eThis service evaluation demonstrates that a pharmacist-led, dedicated optimisation clinic is highly effective at achieving aggressive secondary prevention lipid targets in a real-world, high-risk post-ACS population. The mean LDL-C attainment of 1.60 mmol/L and the impressive 70% target attainment rate significantly outperform those reported in major international registries like SANTORINI, which noted target attainment rates as low as 26.8% across Europe\u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e. This substantial difference underscores the success of a targeted, intensive approach in overcoming widespread clinical therapeutic inertia\u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e. The calculated NNT of 4 is a compelling metric that strongly supports the clinical value of this dedicated service model\u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec19\" class=\"Section2\"\u003e \u003ch2\u003eAddressing Health Inequalities\u003c/h2\u003e \u003cp\u003eOne of the most compelling outcomes of this service evaluation is the demonstrable impact on health inequalities, particularly among patients from the most socioeconomically deprived backgrounds. The pharmacist-led clinic was not only clinically effective but also strategically aligned with the NHS England CORE20PLUS5 framework, which prioritizes targeted interventions for the most deprived 20% of the population\u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eThe significant interaction effect observed in the CORE20 group highlights that patients facing the greatest barriers to care\u0026mdash;such as limited access, lower health literacy, and higher baseline cardiovascular risk\u0026mdash;benefited most from the intervention. This suggests that intensive, personalised care models can reverse entrenched disparities in therapeutic outcomes.\u003c/p\u003e \u003cp\u003eSeveral factors contributed to this success:\u003c/p\u003e \u003cp\u003e \u003cul\u003e \u003cli\u003e \u003cp\u003eEnhanced Accessibility: Flexible appointment formats (face-to-face and telephone) reduced logistical barriers for patients in deprived areas.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eImmediate Prescribing Authority: The pharmacist\u0026rsquo;s independent prescriber status enabled rapid escalation of therapy, bypassing delays common in traditional care pathways.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eFocused Patient Engagement: Consultations emphasized education, adherence, and shared decision-making, fostering trust and empowerment in populations often underserved by mainstream services.\u003c/p\u003e \u003c/li\u003e \u003c/ul\u003e \u003c/p\u003e \u003cp\u003eThis outcome is particularly important given the well-documented association between deprivation and poor cardiovascular outcomes\u003csup\u003e\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e,\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003e. By delivering targeted, intensive lipid optimisation, the pharmacist-led clinic not only improved clinical metrics but also actively reduced therapeutic inequalities\u0026mdash;a core objective of the NHS England CORE20PLUS5 framework.\u003c/p\u003e \u003cp\u003eThese findings support the integration of pharmacist-led models into broader health equity strategies, demonstrating that precision service delivery can be both clinically effective and socially transformative.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec20\" class=\"Section2\"\u003e \u003ch2\u003eLimitations and Strengths\u003c/h2\u003e \u003cp\u003eThis project is subject to the limitations of a non-randomized service evaluation. It is not a clinical trial and thus lacks a contemporary control group. Furthermore, data on long-term adherence beyond the intervention period were not collected. However, the study\u0026rsquo;s strengths are substantial: it represents a large, real-world cohort from a high-volume center; it focuses on a clinically and socially high-risk population (CORE20)\u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e; and it utilizes robust statistical methods (Factorial ANOVA) to definitively demonstrate the impact on socio-economic inequalities.\u003c/p\u003e \u003c/div\u003e"},{"header":"Conclusions","content":"\u003cp\u003eThe implementation of a pharmacist-led post-ACS lipid optimisation clinic resulted in superior target attainment rates (NNT of 4) compared to routine care, demonstrating a highly effective clinical pathway for secondary prevention. Crucially, this intensive model successfully mitigated health inequalities by being most effective in the most socio-economically deprived (CORE20) patients. We strongly recommend that dedicated, pharmacist-led advanced prescribing clinics be considered as a core component of national strategies to achieve aggressive lipid targets and address disparities in cardiovascular outcomes.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cdiv class=\"DefinitionList\"\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eACS\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eacute coronary syndrome\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eASCVD\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eatherosclerotic cardiovascular disease\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eCORE20\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003emost deprived 20% group by Index of Multiple Deprivation\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eLDL-C\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003elow-density lipoprotein cholesterol\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eLLT\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003elipid-lowering therapy.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"Declarations","content":"\u003ch3\u003eEthics Approval and Consent to Participate\u003c/h3\u003e\n\u003cp\u003eThis study was conducted in accordance with the principles of the Declaration of Helsinki. It was reviewed by the Newcastle upon Tyne Hospitals NHS Foundation Trust Clinical Audit and Service Evaluation Committee and classified as a Service Evaluation/Quality Improvement initiative; therefore, formal Research Ethics Committee approval was not required. The analysis used routinely collected clinical data and all data were anonymised prior to analysis. The requirement for individual informed consent was waived by the committee for this retrospective evaluation of clinical care processes.\u003c/p\u003e\n\u003ch3\u003eConsent for Publication\u003c/h3\u003e\n\u003cp\u003eNot applicable. The manuscript does not contain any individual person\u0026apos;s data in any form that would allow identification.\u003c/p\u003e\n\u003ch3\u003eAvailability of Data and Materials\u003c/h3\u003e\n\u003cp\u003eThe datasets generated and analyzed during the current study are stored within the confidential clinical database of the Newcastle upon Tyne Hospitals NHS Foundation Trust. The data are not publicly available due to patient confidentiality restrictions but are available from the corresponding author upon reasonable request and with appropriate institutional data governance approval.\u003c/p\u003e\n\u003ch3\u003eCompeting Interests\u003c/h3\u003e\n\u003cp\u003eThe authors declare that they have no competing interests relevant to the content of this manuscript.\u003c/p\u003e\n\u003ch3\u003eFunding\u003c/h3\u003e\n\u003cp\u003eThis service evaluation was funded via a Collaborative Working Agreement between the Newcastle upon Tyne Hospitals NHS Foundation Trust and Novartis. The funder (Novartis) provided financial support for the service delivery but had no role in the study design, data collection, data analysis, data interpretation, manuscript writing, or the decision to submit the manuscript for publication.\u003c/p\u003e\n\u003ch3\u003eAuthors\u0026apos; Contributions\u003c/h3\u003e\n\u003cul\u003e\n \u003cli\u003e\u003cstrong\u003eMH:\u003c/strong\u003e Conceptualization, methodology, design of the clinical service, data curation, formal analysis, and primary manuscript drafting.\u003c/li\u003e\n \u003cli\u003e\u003cstrong\u003eAL:\u003c/strong\u003e Clinical input, critical review of the methodology, and manuscript editing.\u003c/li\u003e\n \u003cli\u003e\u003cstrong\u003eJR:\u003c/strong\u003e Provided consultation on the statistical analysis (Factorial ANOVA) and critical review of the manuscript\u0026apos;s statistical interpretation.\u003c/li\u003e\n \u003cli\u003e\u003cstrong\u003eHN:\u003c/strong\u003e Contributed expertise on health inequalities (CORE20) and patient safety research; critical review and editing.\u003c/li\u003e\n \u003cli\u003e\u003cstrong\u003eAZ:\u003c/strong\u003e Supervision, clinical validation of the findings, and final critical review of the manuscript. All authors read and approved the final manuscript.\u003c/li\u003e\n\u003c/ul\u003e\n\u003ch3\u003eAcknowledgments\u003c/h3\u003e\n\u003cp\u003eThe authors would like to thank the Outpatient department nursing team and administrative staff at the Freeman Hospital for their invaluable support in the delivery of this clinic.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eBritish Heart Foundation. Heart \u0026amp; Circulatory Disease Statistics 2025 [Internet]. London: British Heart Foundation; 2025 Jun [cited 2025 Nov 06]. Available from: https://www.bhf.org.uk/what-we-do/our-research/heart-statistics/heart-statistics-publications/cardiovascular-disease-statistics-2025\u003c/li\u003e\n\u003cli\u003eMach F, Baigent C, Catapano AL, Koskinas KC, Casula M, Badimon L, et al. 2019 ESC/EAS Guidelines for the management of dyslipidaemias: lipid modification to reduce cardiovascular risk. Eur Heart J. 2020 Jan;41(1):111\u0026ndash;88. Available from: https://doi.org/10.1093/eurheartj/ehz455\u003c/li\u003e\n\u003cli\u003eNational Institute for Health and Care Excellence (NICE). Cardiovascular disease: risk assessment and reduction, including lipid modification (NG238) [Internet]. London: NICE; 2023 Dec [cited 2025 Nov 06]. Available from: https://www.nice.org.uk/guidance/ng238\u003c/li\u003e\n\u003cli\u003eWebb J, Gonna H, Ray KK. Lipid management: maximising reduction of cardiac risk. Clin Med. 2013;13(6):618\u0026ndash;20. Available from: http://dx.doi.org/10.7861/clinmedicine.13-6-618\u003c/li\u003e\n\u003cli\u003eRay KK, Aguiar C, Arca M, Connolly DL, Eriksson M, Ferri\u0026egrave;res J, et al. Use of combination therapy is associated with improved LDL cholesterol management: 1‑year follow‑up results from the European observational SANTORINI study. Eur J Prev Cardiol. 2024 Jun 11;31(15):1792\u0026ndash;803. Available from: https://doi.org/10.1093/eurjpc/zwae199\u003c/li\u003e\n\u003cli\u003eSteen DL, Khan I, Ansell D, Sanchez RJ, Ray KK. Retrospective examination of lipid‑lowering treatment patterns in a real‑world high‑risk cohort in the UK in 2014: comparison with the NICE 2014 lipid modification guidelines. BMJ Open. 2017;7(2):e013255.\u003c/li\u003e\n\u003cli\u003eNational Health Equity Evidence Centre. What works: Achieving equitable lipid management [Internet]. London: Health Equity Evidence Centre; May 2024 [cited 2025 Nov 06]. Available from: https://www.heec.co.uk/wp-content/uploads/2024/05/Evidence-brief-equitable-lipid-management.pdf\u003c/li\u003e\n\u003cli\u003eNHS England. Core20PLUS5: An Approach to Reducing Health Inequalities [Internet]. London: NHS England; 2021. Available from:https://www.england.nhs.uk/about/equality/equality-hub/core20plus5/\u003c/li\u003e\n\u003cli\u003eOgrinc G, Davies L, Goodman D, Batalden P, Davidoff F, Stevens D. SQUIRE 2.0 (Standards for Quality Improvement Reporting Excellence): Revised publication guidelines from a detailed consensus process. BMJ Qual Saf. 2016 Dec;25(12):986\u0026ndash;92. Available from: https://qualitysafety.bmj.com/content/25/12/986\u003c/li\u003e\n\u003cli\u003eKhatib R, Neely D. National Guidance for Lipid Management: Improving Lipid Management in Secondary Care [Internet]. London: NHS England; 2022 Dec. Available from: https://www.england.nhs.uk/wp-content/uploads/2022/12/national-guidance-for-lipid-management-secondary-care.pdf\u003c/li\u003e\n\u003cli\u003eNational Expert and Education Lead in Lipidology (NEELI). Primary Care Lipid Management Guideline [Internet]. London: NEELI; 2023. Available from: https://www.neeli.co.uk/guidelines\u003c/li\u003e\n\u003cli\u003eNHS England. The NHS Long Term Plan [Internet]. London: NHS England; 2019. Available from: https://www.longtermplan.nhs.uk/publication/nhs-long-term-plan/\u003c/li\u003e\n\u003cli\u003eHEART UK. Cardiovascular Disease Prevention Policy Paper [Internet]. London: HEART UK; 2022. Available from: https://www.heartuk.org.uk/\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-cardiovascular-disorders","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bcar","sideBox":"Learn more about [BMC Cardiovascular Disorders](http://bmccardiovascdisord.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bcar/default.aspx","title":"BMC Cardiovascular Disorders","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"acute coronary syndrome, lipid optimisation, pharmacist-led intervention, health inequalities, secondary prevention, CORE20PLUS5, LDL cholesterol, non-HDL cholesterol","lastPublishedDoi":"10.21203/rs.3.rs-8733006/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8733006/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eAtherosclerotic cardiovascular disease remains a leading cause of morbidity and mortality, with outcomes disproportionately worse in socioeconomically deprived populations. Despite clear guideline recommendations, therapeutic inertia frequently prevents high-risk patients from achieving optimal lipid targets following acute coronary syndrome. This service evaluation assessed the impact of a pharmacist-led lipid optimisation clinic on lipid control and health inequalities in a high-risk post-acute coronary syndrome population.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eThis service evaluation was conducted at a tertiary cardiothoracic centre in the North East of England. A cohort of 816 post-acute coronary syndrome patients who had not achieved lipid targets were reviewed in a pharmacist-led clinic delivered by an independent prescriber. Lipid-lowering therapy was intensified in accordance with national guidance through face-to-face or telephone consultations. Primary outcomes were changes in non-high-density lipoprotein cholesterol and low-density lipoprotein cholesterol across three time points: baseline, following cardiology-led optimisation, and following pharmacist-led intervention. Planned comparisons using analysis of variance assessed changes over time. A secondary factorial analysis of variance examined differential effects by socioeconomic deprivation status, defined using the CORE20 metric.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eOf the 816 patients included, 698 (85%) were classified within the most deprived CORE20 group. Following pharmacist-led optimisation, mean non-high-density lipoprotein cholesterol decreased from 3.91 mmol/L to 2.32 mmol/L and mean low-density lipoprotein cholesterol decreased from 3.02 mmol/L to 1.60 mmol/L. Overall, 70% of patients achieved guideline-directed lipid targets, corresponding to a number needed to treat of four. Factorial analysis demonstrated a significant interaction between intervention stage and deprivation status, with patients in the CORE20 group experiencing greater absolute lipid reductions than non-CORE20 patients (mean low-density lipoprotein cholesterol reduction 1.55 mmol/L vs 1.29 mmol/L).\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e \u003cp\u003eA pharmacist-led lipid optimisation clinic significantly improved lipid target attainment and disproportionately benefited patients from the most socioeconomically deprived backgrounds. This model represents a scalable strategy to reduce therapeutic inertia and mitigate health inequalities in secondary cardiovascular prevention.\u003c/p\u003e\u003ch2\u003eTrial Registration\u003c/h2\u003e \u003cp\u003e​Clinical trial number: not applicable. This study was conducted as a service evaluation and quality improvement initiative and was not prospectively registered.\u003c/p\u003e","manuscriptTitle":"Pharmacist-Led Optimisation Significantly Reduces Health Inequalities and Improves Lipid Control in Deprived Post-Acute Coronary Syndrome Patients","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-02-27 10:44:02","doi":"10.21203/rs.3.rs-8733006/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"editorInvitedReview","content":"","date":"2026-03-03T22:37:24+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"156679047463026189232335715532333712924","date":"2026-02-24T08:06:49+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-02-24T07:09:36+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2026-02-02T10:06:39+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-01-31T02:38:41+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-01-31T02:37:51+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Cardiovascular Disorders","date":"2026-01-29T14:47:08+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-cardiovascular-disorders","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bcar","sideBox":"Learn more about [BMC Cardiovascular Disorders](http://bmccardiovascdisord.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bcar/default.aspx","title":"BMC Cardiovascular Disorders","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"33fa0477-0eb8-43a1-bdba-6f0643413576","owner":[],"postedDate":"February 27th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-02-27T10:44:02+00:00","versionOfRecord":[],"versionCreatedAt":"2026-02-27 10:44:02","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8733006","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8733006","identity":"rs-8733006","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}