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Clinical Trial Details — Status: Not yet recruiting

Administrative data

NCT number NCT06444711
Other study ID # 343919
Secondary ID
Status Not yet recruiting
Phase N/A
First received
Last updated
Start date July 2024
Est. completion date April 2045

Study information

Verified date June 2024
Source University of Leeds
Contact Chris Gale
Phone 07779413379
Email c.p.gale@leeds.ac.uk
Is FDA regulated No
Health authority
Study type Interventional

Clinical Trial Summary

Cardiovascular disease (CVD) causes a quarter of all deaths in the United Kingdom (UK). This is the single biggest area where the National Health Service (NHS) can save lives by detecting and treating risk factors early. Improvements in control of blood pressure, cholesterol, diabetes, kidney disease, as well as weight loss in individuals who are obese, have been shown to reduce the risk of CVD and death. The NHS has guidelines for investigations and treatments for risk factors recommended by the National Institute for Health and Care Excellence (NICE). Though it is known that better control of risk factors will reduce the risk of CVD the investigators do not know whether having extra appointments in primary care with heart specialists can lead to better treatment and better control of risk factors. The OPTIMISE trial (OPTIMISation of Cardio-renal-metabolic-pulmonary Disease Guideline Adherence in High Risk Community Dwelling Individuals) will compare patients who have consultations at a local General Practitioner (GP) practice by a cardiology professional to optimise the treatment of their risk factors (OPTIMISE) with those patients who receive standard care (Standard care). Standard care is patients being seen by their GP at routine care appointments. Participants in the OPTIMISE arm will be reviewed by the cardiology professional and recommended treatment in line with current NICE guidance. They will be seen at 3 months to review their treatment and potentially adjusted to ensure it meets NICE guidelines. Participants in the standard arm will have data related to their cardiovascular, renal, metabolic and pulmonary risk factors collected through their Electronic Health Record (EHR). At 6 months, all participants will be seen to find out changes to their prescribed medication and the effect of this on their blood pressure, cholesterol, blood sugar level, and body mass index (BMI). All participants will also complete a quality of life questionnaire prior to randomisation study and at 6 months to identify any differences between the arms and time points.


Description:

Cardiovascular disease (CVD) causes a quarter of all deaths in the UK and is the largest cause of premature mortality in deprived areas. The National Health Service (NHS) Long Term Plan emphasises that this is the single biggest area where the NHS can save lives and that better detection and treatment of cardiovascular, renal, metabolic and pulmonary risk factors is a priority. Treatment of blood pressure, cholesterol, diabetes, kidney disease, as well as weight loss in individuals who are obese, have been shown in randomised clinical trials (RCT) to reduce the risk of CVD and cardiovascular death. Many risk factors for patients with CVD do not occur in isolation, but often co-exist in clusters and increase the risk of other risk factors such as obesity, high blood pressure and diabetes. In the NHS CVD risk factors identification and improvement is through contact with a healthcare professional in primary care. It is from primary care that the prescription of medications and monitoring to control cardio-renal-metabolic-pulmonary risk factors is delivered. Research has demonstrated that, especially during the Coronavirus disease 2019 (COVID-19) pandemic, the management of cardio-renal-metabolic-pulmonary risk factors, through monitoring of observations and blood tests and prescription of medications, deteriorated. That is, patients in the community may not be receiving the full extent of NICE guideline directed care and prescriptions of medications for cardiovascular, renal, metabolic and pulmonary risk factors to reduce their risk of future cardiovascular events like heart attack, stroke and death. The investigator's research has demonstrated that individuals identified as at higher predicted risk of Atrial Fibrillation (AF) are also at increased risk of other conditions such as chronic kidney disease, heart failure, diabetes mellitus, stroke/transient ischaemic attack, myocardial infarction and peripheral vascular disease. The investigators have also shown in their study Future Innovations in Novel Detection of Atrial Fibrillation (FIND AF) that high FIND-AF predicted risk individuals are also at higher risk of death, the majority of which are of cardiovascular cause during 10 years of follow up. Accordingly, individuals at higher FIND-AF predicted risk may have comorbidities and cardiovascular risk factors that are undiagnosed or under-treated during routine practice that may be potential targets for guideline directed treatment to reduce the risk of future adverse events. The study will take advantage of the FIND AF Primary Care network and processes by recruiting from the FIND AF participants who have already been identified as having a high FIND AF predicted risk score. OPTIMISE (OPTIMISation of Cardio-renal-metabolic-pulmonary Disease Guideline Adherence in High Risk Community Dwelling Individuals) will compare General Practitioner (GP) based clinic appointments with a cardiovascular healthcare professional compared to usual care on therapeutic interventions for cardio-renal-metabolic-pulmonary disease and risk factors. It will determine the effect of the differing approaches over a follow up of six months to find out if GP based clinic appointments with a cardiovascular healthcare provides better outcomes for patients than standard care. OPTIMISE is a multicentre pragmatic prospective randomised open-label blinded-endpoint strategy trial (PROBE). Eligible patients will have consented to take part in the FIND AF pilot study and be assessed as at high risk of developing Atrial Fibrillation in the next 6 months by the FIND AF algorithm. For patients who have consented to the optional follow up visit for the FIND AF pilot study, prior to their visit they will be posted the OPTIMISE patient information sheet. At the visit the patient will have the opportunity to ask questions, provide consent and complete a questionnaire. They will then undergo randomisation into either the standard care arm or the Optimisation arm. The aim is to recruit 1:1 between the two arms. If the participant is randomised to the Optimisation arm, the patient will undergo the Optimise baseline appointment at the same time as the FIND AF pilot study optional visit. Combining the visits will reduce the overall time required by the participant as it will avoid duplication of any clinical observations. For patients who have consented to further contact from the research team and have either already undergone the FIND AF pilot study optional visit or have declined to attend the visit, they will be sent the patient information sheet, consent, questionnaire and a reply paid envelope. They will be supplied with the study team's contact information so if they have any questions they can contact the team. Upon receipt of the consent and questionnaire, the study team will randomise the participant. The study team will then contact the participant with the results of the randomisation and if the patient has been randomised to the Optimisation arm, arrange the baseline appointment. It will be clearly stated that the participant has the right to refuse participation without giving a reason and can withdraw from the study at any time without prejudicing their further treatment or their legal rights. The participant will be allowed as much time as wished to consider the information, and the opportunity to question the research team, their GP, or family and friends to decide whether they will participate in the study. For the baseline assessment, the research team cardiology doctor will review the data stored in the participant's GP records with relation to previous cardiovascular disease, hypertension, dyslipidaemia, chronic kidney disease, diabetes, Body Mass Index (BMI), Chronic obstructive pulmonary disease (COPD) and smoking history. At the baseline appointment they will conduct observations and blood tests that are recommended in National Institute for Health and Care Excellence (NICE) guidance if the results are not already available in the GP medical records. They will also carry out an ambulatory lung test (to screen for risk of pulmonary diseases). For patients in the Optimisation arm, the research team cardiology doctor will recommend changes to treatment if the treatment the patient is currently on does not adhere to NICE guidelines. The research team will not directly initiate treatment, but will provide a letter and verbal communication with the participant's GP of the recommendations. Patients in the standard arm will have consented to their data being reviewed in their GP's record as per the Optimisation arm however they will not undergo an appointment with the research team cardiology doctor and no recommendations for changes to treatment will be identified. For patients in the Optimisation arm, at three months following their baseline appointment, they will attend their second visit and undergo the same tests as at the baseline appointment and again, will recommend changes in line with NICE guidance. At six months both participants in the Optimisation arm and the standard arm will have their observations (e.g. blood pressure, BMI) and an ambulatory lung test taken during an appointment by a research team suitably qualified health professional, as well as any blood tests that are indicated by the patient's known comorbidities (e.g. HBA1c if known to have diabetes), as well as completing a patient-reported outcome measure (EQ-5D-5L). All visits will take place at the participant's primary care site. An endpoint adjudication committee, blinded to allocation, will review observations, laboratory measures and GP medical records data for the participant to establish adherence of care to guidelines.


Recruitment information / eligibility

Status Not yet recruiting
Enrollment 138
Est. completion date April 2045
Est. primary completion date April 2025
Accepts healthy volunteers No
Gender All
Age group 18 Years and older
Eligibility Inclusion Criteria: - Consented participants in the FIND-AF study - Higher predicted FIND-AF risk according to the FIND-AF score Exclusion Criteria: - Unable to give written informed consent for participation in the study - Unable to adhere to the study requirements

Study Design


Intervention

Other:
NICE guidance
Patients will be assessed to determine whether their current treatment is in line with NICE guidelines. Changes will be made to their treatment plan in order for them to comply with NICE guidelines with the aim of reducing the number of serious adverse events in the group. They will be followed up until 6 months to identify improvements in their conditions

Locations

Country Name City State
n/a

Sponsors (1)

Lead Sponsor Collaborator
University of Leeds

References & Publications (12)

A Language and Environment for Statistical Computing_. R Foundation for Statistical Computing, Vienna, Austria. https://www.R-project.org/.

Dale CE, Takhar R, Carragher R, Katsoulis M, Torabi F, Duffield S, Kent S, Mueller T, Kurdi A, Le Anh TN, McTaggart S, Abbasizanjani H, Hollings S, Scourfield A, Lyons RA, Griffiths R, Lyons J, Davies G, Harris D, Handy A, Mizani MA, Tomlinson C, Thygesen — View Citation

Herrett E, Gallagher AM, Bhaskaran K, Forbes H, Mathur R, van Staa T, Smeeth L. Data Resource Profile: Clinical Practice Research Datalink (CPRD). Int J Epidemiol. 2015 Jun;44(3):827-36. doi: 10.1093/ije/dyv098. Epub 2015 Jun 6. — View Citation

Marx N, Federici M, Schutt K, Muller-Wieland D, Ajjan RA, Antunes MJ, Christodorescu RM, Crawford C, Di Angelantonio E, Eliasson B, Espinola-Klein C, Fauchier L, Halle M, Herrington WG, Kautzky-Willer A, Lambrinou E, Lesiak M, Lettino M, McGuire DK, Mulle — View Citation

Nadarajah R, Wu J, Hogg D, Raveendra K, Nakao YM, Nakao K, Arbel R, Haim M, Zahger D, Parry J, Bates C, Cowan C, Gale CP. Prediction of short-term atrial fibrillation risk using primary care electronic health records. Heart. 2023 Jun 26;109(14):1072-1079. — View Citation

Nakao YM, Gale CP, Miyazaki K, Kobayashi H, Matsuda A, Nadarajah R, Motonishi T. Impact of a national screening programme on obesity and cardiovascular risk factors. Eur J Prev Cardiol. 2023 Mar 1;30(4):331-339. doi: 10.1093/eurjpc/zwac283. — View Citation

Odutayo A, Wong CX, Hsiao AJ, Hopewell S, Altman DG, Emdin CA. Atrial fibrillation and risks of cardiovascular disease, renal disease, and death: systematic review and meta-analysis. BMJ. 2016 Sep 6;354:i4482. doi: 10.1136/bmj.i4482. — View Citation

Ortiz A, Wanner C, Gansevoort R; ERA Council. Chronic kidney disease as cardiovascular risk factor in routine clinical practice: a position statement by the Council of the European Renal Association. Eur J Prev Cardiol. 2022 Dec 7;29(17):2211-2215. doi: 1 — View Citation

Visseren FLJ, Mach F, Smulders YM, Carballo D, Koskinas KC, Back M, Benetos A, Biffi A, Boavida JM, Capodanno D, Cosyns B, Crawford C, Davos CH, Desormais I, Di Angelantonio E, Franco OH, Halvorsen S, Hobbs FDR, Hollander M, Jankowska EA, Michal M, Sacco — View Citation

Williams B, Mancia G, Spiering W, Agabiti Rosei E, Azizi M, Burnier M, Clement DL, Coca A, de Simone G, Dominiczak A, Kahan T, Mahfoud F, Redon J, Ruilope L, Zanchetti A, Kerins M, Kjeldsen SE, Kreutz R, Laurent S, Lip GYH, McManus R, Narkiewicz K, Ruschi — View Citation

Yumuk V, Tsigos C, Fried M, Schindler K, Busetto L, Micic D, Toplak H; Obesity Management Task Force of the European Association for the Study of Obesity. European Guidelines for Obesity Management in Adults. Obes Facts. 2015;8(6):402-24. doi: 10.1159/000 — View Citation

Zelniker TA, Wiviott SD, Raz I, Im K, Goodrich EL, Bonaca MP, Mosenzon O, Kato ET, Cahn A, Furtado RHM, Bhatt DL, Leiter LA, McGuire DK, Wilding JPH, Sabatine MS. SGLT2 inhibitors for primary and secondary prevention of cardiovascular and renal outcomes i — View Citation

* Note: There are 12 references in allClick here to view all references

Outcome

Type Measure Description Time frame Safety issue
Primary The proportion of patients with any of the following therapeutic intervention to optimise cardio-renal-metabolic-pulmonary risk factor management The proportion of patients with any of the following therapeutic intervention to optimise cardio-renal-metabolic-pulmonary risk factor management including initiation or increase in dose regimen of:
Angiotensin converting enzyme inhibitor / angiotensin 2 receptor blocker
Calcium channel blocker / thiazide-like diuretic / spironolactone / alpha blocker / beta blocker
SGLT2 inhibitor
Glucagon-like peptide (GLP) -1 receptor agonist
Metformin / Dipeptidyl peptidase 4 (DPP4) inhibitor / pioglitazone / sulphonylurea / insulin
Statin / ezetimibe / icosapent ethyl / bempedoic acid / PCSK9 inhibitor
Orlistat
Nicotine replacement therapy / bupropion
Inhaler therapy
6 months
Secondary Components of primary endpoint The proportion of participants who have experienced any of the individual components of primary endpoint which are an initiation or increase in the dose regimen of each of the following:
Angiotensin converting enzyme inhibitor / angiotensin 2 receptor blocker
Calcium channel blocker / thiazide-like diuretic / spironolactone / alpha blocker / beta blocker
SGLT2 inhibitor
Glucagon-like peptide (GLP) -1 receptor agonist
Metformin / Dipeptidyl peptidase 4 (DPP4) inhibitor / pioglitazone / sulphonylurea / insulin
Statin / ezetimibe / icosapent ethyl / bempedoic acid / PCSK9 inhibitor
Orlistat
Nicotine replacement therapy / bupropion
Inhaler therapy
6 months
Secondary Time to primary endpoint The median time to primary endpoint from randomisation reported in days eg the date of initiation or increase in the dose regimen of one of the following:
Angiotensin converting enzyme inhibitor / angiotensin 2 receptor blocker
Calcium channel blocker / thiazide-like diuretic / spironolactone / alpha blocker / beta blocker
SGLT2 inhibitor
Glucagon-like peptide (GLP) -1 receptor agonist
Metformin / Dipeptidyl peptidase 4 (DPP4) inhibitor / pioglitazone / sulphonylurea / insulin
Statin / ezetimibe / icosapent ethyl / bempedoic acid / PCSK9 inhibitor
Orlistat
Nicotine replacement therapy / bupropion
Inhaler therapy
6 months
Secondary Number of participants developing a new cardio-renal-metabolic-pulmonary risk factor Number of patients receiving a diagnosis of new cardio-renal-metabolic-pulmonary risk factor (hypertension, diabetes, chronic kidney disease, obesity, current smoking, COPD) between randomisation and six months. 6 months
Secondary Time to diagnosis of a new cardio-renal-metabolic-pulmonary risk factor Time to diagnosis of a new cardio-renal-metabolic-pulmonary risk factor 6 months
Secondary Number of participants with a new uptake of guideline directed risk factor management Number of participants with a new uptake of guideline directed risk factor management in those with recorded cardio-renal-metabolic-pulmonary risk factors (hypertension, lipid modification, diabetes, chronic kidney disease, obesity, current smoking, COPD), between randomisation and six months 6 months
Secondary Change in EuroQol five dimensional descriptive system (EQ-5D-5L) questionnaire score A comparison of the two arms of the change in EuroQol five dimensional descriptive system (EQ-5D-5L) questionnaire score between randomisation and six months follow-up with a large change indicating a better outcome. Analysis will be carried out as per the EuroQoL guidance and will incorporate both questions and scale participant responses.
The EQ-5D-5L has a maximum index value of 1, representing full health, and a minimum index value of -0.59, which corresponds to the worst health state. The instrument includes five dimensions: mobility, self-care, usual activities, pain/discomfort, and anxiety/depression with each dimension having five levels. We will be measuring the change in index value between baseline and 6 months.
6 months
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