Should heart age calculators be used alongside absolute cardiovascular disease risk assessment?

"They are saying it's high, but I think it's quite low": exploring cardiovascular disease risk communication in NHS health checks through video-stimulated recall interviews with patients - a qualitative study

BACKGROUND

NHS Health Check (NHSHC) is a national cardiovascular disease (CVD) risk identification and management programme. However, evidence suggests a limited understanding of the most used metric to communicate CVD risk with patients (10-year percentage risk). This study used novel application of video-stimulated recall interviews to understand patient perceptions and understanding of CVD risk following an NHSHC that used one of two different CVD risk calculators.

METHODS

Qualitative, semi-structured video-stimulated recall interviews were conducted with patients (n = 40) who had attended an NHSHC using either the QRISK2 10-year risk calculator (n = 19) or JBS3 lifetime CVD risk calculator (n = 21). Interviews were transcribed and analysed using reflexive thematic analysis.

RESULTS

Analysis resulted in the development of four themes: variability in understanding, relief about personal risk, perceived changeability of CVD risk, and positive impact of visual displays. The first three themes were evident across the two patient groups, regardless of risk calculator; the latter related to JBS3 only. Patients felt relieved about their CVD risk, yet there were differences in understanding between calculators. Heart age within JBS3 prompted more accessible risk appraisal, yet mixed understanding was evident for both calculators. Event-free survival age also resulted in misunderstanding. QRISK2 patients tended to question the ability for CVD risk to change, while risk manipulation through JBS3 facilitated this understanding. Displaying information visually also appeared to enhance understanding.

CONCLUSIONS

Effective communication of CVD risk within NHSHC remains challenging, and lifetime risk metrics still lead to mixed levels of understanding in patients. However, visual presentation of information, alongside risk manipulation during NHSHCs can help to increase understanding and prompt risk-reducing lifestyle changes.

TRIAL REGISTRATION

ISRCTN10443908. Registered 7th February 2017.

A new method for vascular age estimation based on relative risk difference in vascular aging

OBJECTIVE

The current models of estimating vascular age (VA) primarily rely on the regression label expressed with chronological age (CA), which does not account individual differences in vascular aging (IDVA) that are difficult to describe by CA. This may lead to inaccuracies in assessing the risk of cardiovascular disease based on VA. To address this limitation, this work aims to develop a new method for estimating VA by considering IDVA. This method will provide a more accurate assessment of cardiovascular disease risk.

METHODS

Relative risk difference in vascular aging (RRDVA) is proposed to replace IDVA, which is represented as the numerical difference between individual predicted age (PA) and the corresponding mean PA of healthy population. RRDVA and CA are regard as the influence factors to acquire VA. In order to acquire PA of all samples, this work takes CA as the dependent variable, and mines the two most representative indicators from arteriosclerosis data as the independent variables, to establish a regression model for obtaining PA.

RESULTS

The proposed VA based on RRDVA is significantly correlated with 27 indirect indicators for vascular aging evaluation. Moreover, VA is better than CA by comparing the correlation coefficients between VA, CA and 27 indirect indicators, and RRDVA greater than zero presents a higher risk of disease.

CONCLUSION

The proposed VA overcomes the limitation of CA in characterizing IDVA, which may help young groups with high disease risk to promote healthy behaviors.

Guideline-Based Cardiovascular Risk Assessment Delivered by an mHealth App: Development Study

BACKGROUND

Identifying high-risk individuals is crucial for preventing cardiovascular diseases (CVDs). Currently, risk assessment is mostly performed by physicians. Mobile health apps could help decouple the determination of risk from medical resources by allowing unrestricted self-assessment. The respective test results need to be interpretable for laypersons.

OBJECTIVE

Together with a patient organization, we aimed to design a digital risk calculator that allows people to individually assess and optimize their CVD risk. The risk calculator was integrated into the mobile health app HerzFit, which provides the respective background information.

METHODS

To cover a broad spectrum of individuals for both primary and secondary prevention, we integrated the respective scores (Framingham 10-year CVD, Systematic Coronary Risk Evaluation 2, Systematic Coronary Risk Evaluation 2 in Older Persons, and Secondary Manifestations Of Arterial Disease) into a single risk calculator that was recalibrated for the German population. In primary prevention, an individual's heart age is estimated, which gives the user an easy-to-understand metric for assessing cardiac health. For secondary prevention, the risk of recurrence was assessed. In addition, a comparison of expected to mean and optimal risk levels was determined. The risk calculator is available free of charge. Data safety is ensured by processing the data locally on the users' smartphones.

RESULTS

Offering a risk calculator to the general population requires the use of multiple instruments, as each provides only a limited spectrum in terms of age and risk distribution. The integration of 4 internationally recommended scores allows risk calculation in individuals aged 30 to 90 years with and without CVD. Such integration requires recalibration and harmonization to provide consistent and plausible estimates. In the first 14 months after the launch, the HerzFit calculator was downloaded more than 96,000 times, indicating great demand. Public information campaigns proved effective in publicizing the risk calculator and contributed significantly to download numbers.

CONCLUSIONS

The HerzFit calculator provides CVD risk assessment for the general population. The public demonstrated great demand for such a risk calculator as it was downloaded up to 10,000 times per month, depending on campaigns creating awareness for the instrument.

Multimodal Neuroimaging Summary Scores as Neurobiological Markers of Psychosis

BACKGROUND AND HYPOTHESIS

Structural brain alterations are well-established features of schizophrenia but they do not effectively predict disease/disease risk. Similar to polygenic risk scores in genetics, we integrated multifactorial aspects of brain structure into a summary "Neuroscore" and examined its potential as a marker of disease.

STUDY DESIGN

We extracted measures from T1-weighted scans and diffusion tensor imaging (DTI) models from three studies with schizophrenia and healthy individuals. We calculated individual-level summary scores (Neuroscores) for T1-weighted and DTI measures and a combined score (Multimodal Neuroscore-MM). We assessed each score's ability to differentiate schizophrenia cases from controls and its relationship to clinical symptomatology, intelligence quotient (IQ), and medication dosage. We assessed Neuroscore specificity by performing all analyses in a more inclusive psychosis sample and by using scores generated from MDD effect sizes.

STUDY RESULTS

All Neuroscores significantly differentiated schizophrenia cases from controls (T1 d = 0.56, DTI d = 0.29, MM d = 0.64) to a greater degree than individual brain regions. Higher Neuroscores (ie, increased liability) were associated with lower IQ (T1 β = -0.26, DTI β = -0.15, MM β = -0.30). Higher T1-weighted Neuroscores were associated with higher positive and negative symptom severity (Positive β = 0.21, Negative β = 0.16); Higher Multimodal Neuroscores were associated with higher positive symptom severity (β = 0.30). SZ Neuroscores outperformed MDD Neuroscores in predicting IQ (T1: z = 3.5, q = 0.0007; MM: z = 1.8, q = 0.05).

CONCLUSIONS

Neuroscores are a step toward leveraging widespread structural brain alterations in psychosis to identify robust neurobiological markers of disease. Future studies will assess ways to improve neuroscore calculation, including developing the optimal methods to calculate neuroscores and considering disorder overlap.

Comorbidity-stratified estimates of 30-day mortality risk by age for unvaccinated men and women with COVID-19: a population-based cohort study

BACKGROUND

The mortality risk following COVID-19 diagnosis in men and women with common comorbidities at different ages has been difficult to communicate to the general public. The purpose of this study was to determine the age at which unvaccinated men and women with common comorbidities have a mortality risk which exceeds that of 75- and 65-year-old individuals in the general population (Phases 1b/1c thresholds of the Centre for Disease Control Vaccine Rollout Recommendations) following COVID-19 infection during the first wave.

METHODS

We conducted a population-based retrospective cohort study using linked administrative datasets in Ontario, Canada. We identified all community-dwelling adults diagnosed with COVID-19 between January 1 and October 31st, 2020. Exposures of interest were age (modelled using restricted cubic splines) and the following conditions: major cardiovascular disease (recent myocardial infarction or lifetime history of heart failure); 2) diabetes; 3) hypertension; 4) recent cancer; 5) chronic obstructive pulmonary disease; 6) Stages 4/5 chronic kidney disease (CKD); 7) frailty. Logistic regression in the full cohort was used to estimate the risk of 30-day mortality for 75- and 65-year-old individuals. Analyses were repeated after stratifying by sex and medical condition to determine the age at which 30-day morality risk in strata exceed that of the general population at ages 65 and 75 years.

RESULTS

We studied 52,429 individuals (median age 42 years; 52.5% women) of whom 417 (0.8%) died within 30 days. The 30-day mortality risk increased with age, male sex, and comorbidities. The 65- and 75-year-old mortality risks in the general population were exceeded at the youngest age by people with CKD, cancer, and frailty. Conversely, women aged < 65 years who had diabetes or hypertension did not have higher mortality than 65-year-olds in the general population. Most people with medical conditions (except for Stage 4-5 CKD) aged < 45 years had lower predicted mortality than the general population at age 65 years.

CONCLUSION

The mortality risk in COVID-19 increases with age and comorbidity but the prognostic implications varied by sex and condition. These observations can support communication efforts and inform vaccine rollout in jurisdictions with limited vaccine supplies.

Development, promotion, and application of online OvAge calculator based on the WeChat applet: Clinical prediction model research

Ovarian age assessment is an important indicator to evaluate the ovarian reserve function and reproductive potential of women. At present, the application of ovarian age prediction model in China needs further improvement and optimization to make it more suitable for the actual situation of women in China. In this study, we collected subjects and their data in three ways: firstly, we collected clinical data from a number of women go to local hospital, including healthy women and women with DOR or PCOS; secondly, we obtained data by recruited healthy women through CRO companies for a fee; thirdly, we collected data from a number of healthy women using WeChat applet. Using the data collected by CRO company and WeChat applet, we applied the generalized linear model to optimize the ovarian age prediction model. The optimized formula is: OvAge = exp (3.5254-0.0001*PRL-0.0231*AMH), where P = 0.8195 for PRL and P = 0.0003 for AMH. Applying the formula to the hospital population data set for testing, it showed that the predicted ovarian age in the healthy women was comparable to their actual age, with a root mean squared error (RMSE) = 5.6324. The prediction accuracy was high. These data suggest that our modification of the ovarian age prediction model is feasible and that the formula is currently a more appropriate model for ovarian age assessment in healthy Chinese women. This study explored a new way to collect clinical data, namely, an online ovarian age calculator developed based on a WeChat applet, which can collect data from a large number of subjects in a short period of time and is more economical, efficient, and convenient. In addition, this study introduced real data to optimize the model, which could provide insights for model localization and improvement.

The Impact and Perception of England's Web-Based Heart Age Test of Cardiovascular Disease Risk: Mixed Methods Study

BACKGROUND

It is well documented that individuals struggle to understand cardiovascular disease (CVD) percentage risk scores, which led to the development of heart age as a means of communicating risk. Developed for clinical use, its application in raising public awareness of heart health as part of a self-directed digital test has not been considered previously.

OBJECTIVE

This study aimed to understand who accesses England's heart age test (HAT) and its effect on user perception, knowledge, and understanding of CVD risk; future behavior intentions; and potential engagement with primary care services.

METHODS

There were 3 sources of data: routinely gathered data on all individuals accessing the HAT (February 2015 to June 2020); web-based survey, distributed between January 2021 and March 2021; and interviews with a subsample of survey respondents (February 2021 to March 2021). Data were used to describe the test user population and explore knowledge and understanding of CVD risk, confidence in interpreting and controlling CVD risk, and effect on future behavior intentions and potential engagement with primary care. Interviews were analyzed using reflexive thematic analysis.

RESULTS

Between February 2015 and June 2020, the HAT was completed approximately 5 million times, with more completions by men (2,682,544/4,898,532, 54.76%), those aged between 50 to 59 years (1,334,195/4,898,532, 27.24%), those from White ethnic background (3,972,293/4,898,532, 81.09%), and those living in the least deprived 20% of areas (707,747/4,898,532, 14.45%). The study concluded with 819 survey responses and 33 semistructured interviews. Participants stated that they understood the meaning of high estimated heart age and self-reported at least some improvement in the understanding and confidence in understanding and controlling CVD risk. Negative emotional responses were provoked among users when estimated heart age did not equate to their previous risk perceptions. The limited information needed to complete it or the production of a result when physiological risk factor information was missing (ie, blood pressure and cholesterol level) led some users to question the credibility of the test. However, most participants who were interviewed mentioned that they would recommend or had already recommended the test to others, would use it again in the future, and would be more likely to take up the offer of a National Health Service Health Check and self-reported that they had made or intended to make changes to their health behavior or felt encouraged to continue to make changes to their health behavior.

CONCLUSIONS

England's web-based HAT has engaged large number of people in their heart health. Improvements to England's HAT, noted in this paper, may enhance user satisfaction and prevent confusion. Future studies to understand the long-term benefit of the test on behavioral outcomes are warranted.

Biological age calculators to motivate lifestyle change: Environmental scan of online tools and evaluation of behaviour change techniques

OBJECTIVE

"Biological age" calculators are widely used as a way of communicating health risk. This study evaluated the behaviour change techniques (BCTs) within such tools, underlying algorithm differences and suitability for people with varying health literacy.

METHODS

Two authors entered terms into Google (eg, biological/heart age) and recorded the first 50 results. A standard patient profile was entered into eligible biological age calculators. Evaluation was based on Michie et al's BCT taxonomy and a readability calculator.

RESULTS

From 4000 search results, 20 calculators were identified: 11 for cardiovascular age, 7 for general biological age and 2 for fitness age. The calculators gave variable results for the same 65-year-old profile: biological age ranged from younger to older (57-87 years), while heart age was always older (69-85+ years). Only 11/20 (55%) provided a reference explaining the underlying algorithm. The average reading level was Grade 10 (range 8.7-12.4; SD 1.44). The most common BCTs were salience of consequences, information about health consequences and credible source.

CONCLUSIONS

Biological age tools have highly variable results, BCTs and readability.

PRACTICE IMPLICATIONS

Developers are advised to use validated models, explain the result at the average Grade 8 reading level, and incorporate a clear call to action using evidence-based behaviour change techniques.

Predicted heart age profile across 41 countries: A cross-sectional study of nationally representative surveys in six world regions

BACKGROUND

Predicted heart age (PHA) can simplify communicating the absolute cardiovascular disease (CVD) risk. Few studies have characterized PHA across multiple populations, and none has described whether people with excess PHA are eligible for preventive treatment for CVD.

METHODS

Pooled analysis of 41 World Health Organization (WHO) STEPS surveys conducted in 41 countries in six world regions between 2013 and 2019. PHA was calculated as per the non-laboratory Framingham risk score in adults without history of CVD. We described the differences between chronological age and PHA, the distribution of PHA, and the proportion of people with excess PHA that were eligible for antihypertensive and lipid-lowering treatment following the WHO guidelines. Logistic regression models were fitted to assess sociodemographic and health-related variables associated with PHA excess.

FINDINGS

94,655 individuals aged 30-74 years were included. 36% of those aged 30-34 years had a PHA of 30-34 years; 9% of those aged 60-64 years had a PHA of 60-64 years. Countries in Africa had the lowest prevalence of very high PHA (i.e., PHA exceeding chronological age in ≥5 years) and countries in Western Pacific had the highest. ≥50% of the population with PHA excess (i.e., PHA exceeding chronological age in ≥1 year) was not eligible for antihypertensive nor lipid-lowering treatment. Abdominal obesity, high total cholesterol, smoking and having diabetes were associated with higher odds of having PHA excess, whereas higher education and employment were inversely associated with excess PHA.

INTERPRETATION

PHA is generally higher than chronological age in LMICs and there are regional disparities. Most people with excess PHA would not be eligible to receive preventive medication.

FUNDING

RMC-L is supported by a Wellcome Trust International Training Fellowship (214185/Z/18/Z).

An Intuitive Risk Communication Tool to Enhance Patient-Provider Partnership in Diabetes Consultation

INTRODUCTION

This technology report introduces an innovative risk communication tool developed to support providers in communicating diabetes-related risks more intuitively to people with type 2 diabetes mellitus (T2DM).

METHODS

The development process involved three main steps: (1) selecting the content and format of the risk message; (2) developing a digital interface; and (3) assessing the usability and usefulness of the tool with clinicians through validated questionnaires.

RESULTS

The tool calculates personalized risk information based on a validated simulation model (United Kingdom Prospective Diabetes Study Outcomes Model 2) and delivers it using more intuitive risk formats, such as "effective heart age" to convey cardiovascular risks. Clinicians reported high scores for the usability and usefulness of the tool, making its adoption in routine care promising.

CONCLUSIONS

Despite increased use of risk calculators in clinical care, this is the first time that such a tool has been developed in the diabetes area. Further studies are needed to confirm the benefits of using this tool on behavioral and health outcomes in T2DM populations.

Vascular age based on coronary calcium burden and carotid intima media thickness (a comparative study)

BACKGROUND

Considering the importance of vascular age in the risk assessment of cardiovascular events and the presence of different methods for its estimation, this study aims to evaluate and compare vascular age according to coronary artery calcium scoring (CACS) and carotid ultrasonography.

METHODS

This study was conducted in Isfahan on patients who underwent CACS and carotid intima-media thickness (CIMT) assessments within 30 days. In patients who were candidates for CACS, calcium score was measured, then they were invited for carotid ultrasonography, and CIMT was measured. Vascular age was estimated based on these methods using available formulas.

RESULTS

In this study, 115 patients were enrolled. (Male 52.2%, female 47.8%). The mean chronological age was 59.08 ± 14.90 years old. The mean calcium score (CS) of patients was 48.23 ± 63.34. Mean CIMT was 0.73 ± 0.15 mm. The mean vascular age derived by CS and CIMT was 58.64 ± 12.63 and 53.99 ± 17.53 years, respectively. The vascular age obtained by CS was directly related to vascular age based on CIMT (P-value < 0.05).

CONCLUSION

Calcium score is as helpful as CIMT for vascular age estimation.

Step-by-step diagnosis and management of the nocebo/drucebo effect in statin-associated muscle symptoms patients: a position paper from the International Lipid Expert Panel (ILEP)

Statin intolerance is a clinical syndrome whereby adverse effects (AEs) associated with statin therapy [most commonly statin-associated muscle symptoms (SAMS)] result in the discontinuation of therapy and consequently increase the risk of adverse cardiovascular outcomes. However, complete statin intolerance occurs in only a small minority of treated patients (estimated prevalence of only 3-5%). Many perceived AEs are misattributed (e.g. physical musculoskeletal injury and inflammatory myopathies), and subjective symptoms occur as a result of the fact that patients expect them to do so when taking medicines (the nocebo/drucebo effect)-what might be truth even for over 50% of all patients with muscle weakness/pain. Clear guidance is necessary to enable the optimal management of plasma in real-world clinical practice in patients who experience subjective AEs. In this Position Paper of the International Lipid Expert Panel (ILEP), we present a step-by-step patient-centred approach to the identification and management of SAMS with a particular focus on strategies to prevent and manage the nocebo/drucebo effect and to improve long-term compliance with lipid-lowering therapy.

'What is the risk to me from COVID-19?': Public involvement in providing mortality risk information for people with 'high-risk' conditions for COVID-19 (OurRisk.CoV)

Patients and public have sought mortality risk information throughout the pandemic, but their needs may not be served by current risk prediction tools. Our mixed methods study involved: (1) systematic review of published risk tools for prognosis, (2) provision and patient testing of new mortality risk estimates for people with high-risk conditions and (3) iterative patient and public involvement and engagement with qualitative analysis. Only one of 53 (2%) previously published risk tools involved patients or the public, while 11/53 (21%) had publicly accessible portals, but all for use by clinicians and researchers.Among people with a wide range of underlying conditions, there has been sustained interest and engagement in accessible and tailored, pre- and postpandemic mortality information. Informed by patient feedback, we provide such information in 'five clicks' (https://covid19-phenomics.org/OurRiskCoV.html), as context for decision making and discussions with health professionals and family members. Further development requires curation and regular updating of NHS data and wider patient and public engagement.

Interventions Using Heart Age for Cardiovascular Disease Risk Communication: Systematic Review of Psychological, Behavioral, and Clinical Effects

BACKGROUND

Cardiovascular disease (CVD) risk communication is a challenge for clinical practice, where physicians find it difficult to explain the absolute risk of a CVD event to patients with varying health literacy. Converting the probability to heart age is increasingly used to promote lifestyle change, but a rapid review of biological age interventions found no clear evidence that they motivate behavior change.

OBJECTIVE

In this review, we aim to identify the content and effects of heart age interventions.

METHODS

We conducted a systematic review of studies presenting heart age interventions to adults for CVD risk communication in April 2020 (later updated in March 2021). The Johanna Briggs risk of bias assessment tool was applied to randomized studies. Behavior change techniques described in the intervention methods were coded.

RESULTS

From a total of 7926 results, 16 eligible studies were identified; these included 5 randomized web-based experiments, 5 randomized clinical trials, 2 mixed methods studies with quantitative outcomes, and 4 studies with qualitative analysis. Direct comparisons between heart age and absolute risk in the 5 web-based experiments, comprising 5514 consumers, found that heart age increased positive or negative emotional responses (4/5 studies), increased risk perception (4/5 studies; but not necessarily more accurate) and recall (4/4 studies), reduced credibility (2/3 studies), and generally had no effect on lifestyle intentions (4/5 studies). One study compared heart age and absolute risk to fitness age and found reduced lifestyle intentions for fitness age. Heart age combined with additional strategies (eg, in-person or phone counseling) in applied settings for 9582 patients improved risk control (eg, reduced cholesterol levels and absolute risk) compared with usual care in most trials (4/5 studies) up to 1 year. However, clinical outcomes were no different when directly compared with absolute risk (1/1 study). Mixed methods studies identified consultation time and content as important outcomes in actual consultations using heart age tools. There were differences between people receiving an older heart age result and those receiving a younger or equal to current heart age result. The heart age interventions included a wide range of behavior change techniques, and conclusions were sometimes biased in favor of heart age with insufficient supporting evidence. The risk of bias assessment indicated issues with all randomized clinical trials.

CONCLUSIONS

The findings of this review provide little evidence that heart age motivates lifestyle behavior change more than absolute risk, but either format can improve clinical outcomes when combined with other behavior change strategies. The label for the heart age concept can affect outcomes and should be pretested with the intended audience. Future research should consider consultation time and differentiate between results of older and younger heart age.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

NPRR2-10.1101/2020.05.03.20089938.

Interventions Using Heart Age for Cardiovascular Disease Risk Communication: Systematic Review of Psychological, Behavioral, and Clinical Effects

BACKGROUND

Cardiovascular disease (CVD) risk communication is a challenge for clinical practice, where physicians find it difficult to explain the absolute risk of a CVD event to patients with varying health literacy. Converting the probability to heart age is increasingly used to promote lifestyle change, but a rapid review of biological age interventions found no clear evidence that they motivate behavior change.

OBJECTIVE

In this review, we aim to identify the content and effects of heart age interventions.

METHODS

We conducted a systematic review of studies presenting heart age interventions to adults for CVD risk communication in April 2020 (later updated in March 2021). The Johanna Briggs risk of bias assessment tool was applied to randomized studies. Behavior change techniques described in the intervention methods were coded.

RESULTS

From a total of 7926 results, 16 eligible studies were identified; these included 5 randomized web-based experiments, 5 randomized clinical trials, 2 mixed methods studies with quantitative outcomes, and 4 studies with qualitative analysis. Direct comparisons between heart age and absolute risk in the 5 web-based experiments, comprising 5514 consumers, found that heart age increased positive or negative emotional responses (4/5 studies), increased risk perception (4/5 studies; but not necessarily more accurate) and recall (4/4 studies), reduced credibility (2/3 studies), and generally had no effect on lifestyle intentions (4/5 studies). One study compared heart age and absolute risk to fitness age and found reduced lifestyle intentions for fitness age. Heart age combined with additional strategies (eg, in-person or phone counseling) in applied settings for 9582 patients improved risk control (eg, reduced cholesterol levels and absolute risk) compared with usual care in most trials (4/5 studies) up to 1 year. However, clinical outcomes were no different when directly compared with absolute risk (1/1 study). Mixed methods studies identified consultation time and content as important outcomes in actual consultations using heart age tools. There were differences between people receiving an older heart age result and those receiving a younger or equal to current heart age result. The heart age interventions included a wide range of behavior change techniques, and conclusions were sometimes biased in favor of heart age with insufficient supporting evidence. The risk of bias assessment indicated issues with all randomized clinical trials.

CONCLUSIONS

The findings of this review provide little evidence that heart age motivates lifestyle behavior change more than absolute risk, but either format can improve clinical outcomes when combined with other behavior change strategies. The label for the heart age concept can affect outcomes and should be pretested with the intended audience. Future research should consider consultation time and differentiate between results of older and younger heart age.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

NPRR2-10.1101/2020.05.03.20089938.

Cardiovascular disease risk communication in NHS Health Checks: a qualitative video-stimulated recall interview study with practitioners

BACKGROUND

NHS Health Check (NHSHC) is a national programme to identify and manage cardiovascular disease (CVD) risk. Practitioners delivering the programme should be competent in discussing CVD risk, but there is evidence of limited understanding of the recommended 10-year percentage CVD risk scores. Lifetime CVD risk calculators might improve understanding and communication of risk.

AIM

To explore practitioner understanding, perceptions, and experiences of CVD risk communication in NHSHCs when using two different CVD risk calculators.

DESIGN & SETTING

Qualitative video-stimulated recall (VSR) study with NHSHC practitioners in the West Midlands.

METHOD

VSR interviews were conducted with practitioners who delivered NHSHCs using either the QRISK2 10-year risk calculator (n = 7) or JBS3 lifetime CVD risk calculator (n = 8). Data were analysed using reflexive thematic analysis.

RESULTS

In total, nine healthcare assistants (HCAs) and six general practice nurses (GPNs) were interviewed. There was limited understanding and confidence of 10-year risk, which was used to guide clinical decisions through determining low-, medium-, or high-risk thresholds, rather than as a risk communication tool. Potential benefits of some JBS3 functions were evident, particularly heart age, risk manipulation, and visual presentation of risk.

CONCLUSION

There is a gap between the expectation and reality of practitioners' understanding, competencies, and training in CVD risk communication for NHSHCs. Practitioners would welcome heart age and risk manipulation functions of JBS3 to promote patient understanding of CVD risk, but there is a more fundamental need for practitioner training in CVD risk communication.

Cardiovascular disease risk communication in NHS Health Checks using QRISK®2 and JBS3 risk calculators: the RICO qualitative and quantitative study

BACKGROUND

The NHS Health Check is a national cardiovascular disease prevention programme. There is a lack of evidence on how health checks are conducted, how cardiovascular disease risk is communicated to foster risk-reducing intentions or behaviour, and the impact on communication of using different cardiovascular disease risk calculators.

OBJECTIVES

RIsk COmmunication in Health Check (RICO) study aimed to explore practitioner and patient understanding of cardiovascular disease risk, the associated advice or treatment offered by the practitioner, and the response of the patients in health checks supported by either the QRISK^®2 or the JBS3 lifetime risk calculator.

DESIGN

This was a qualitative study with quantitative process evaluation.

SETTING

Twelve general practices in the West Midlands of England, stratified on deprivation of the local area (bottom 50% vs. top 50%), and with matched pairs randomly allocated to use QRISK2 or JBS3 during health checks.

PARTICIPANTS

A total of 173 patients eligible for NHS Health Check and 15 practitioners.

INTERVENTIONS

The health check was delivered using either the QRISK2 10-year risk calculator (usual practice) or the JBS3 lifetime risk calculator, with heart age, event-free survival age and risk score manipulation (intervention).

RESULTS

Video-recorded health checks were analysed quantitatively (n = 173; JBS3, n = 100; QRISK2, n = 73) and qualitatively (n = 128; n = 64 per group), and video-stimulated recall interviews were undertaken with 40 patients and 15 practitioners, with 10 in-depth case studies. The duration of the health check varied (6.8-38 minutes), but most health checks were short (60% lasting < 20 minutes), with little cardiovascular disease risk discussion (average < 2 minutes). The use of JBS3 was associated with more cardiovascular disease risk discussion and fewer practitioner-dominated consultations than the use of QRISK2. Heart age and visual representations of risk, as used in JBS3, appeared to be better understood by patients than 10-year risk (QRISK2) and, as a result, the use of JBS3 was more likely to lead to discussion of risk factors and their management. Event-free survival age was not well understood by practitioners or patients. However, a lack of effective cardiovascular disease risk discussion in both groups increased the likelihood of a maladaptive coping response (i.e. no risk-reducing behaviour change). In both groups, practitioners often missed opportunities to check patient understanding and to tailor information on cardiovascular disease risk and its management during health checks, confirming apparent practitioner verbal dominance.

LIMITATIONS

The main limitations were under-recruitment in some general practices and the resulting imbalance between groups.

CONCLUSIONS

Communication of cardiovascular disease risk during health checks was brief, particularly when using QRISK2. Patient understanding of and responses to cardiovascular disease risk information were limited. Practitioners need to better engage patients in discussion of and action-planning for their cardiovascular disease risk to reduce misunderstandings. The use of heart age, visual representation of risk and risk score manipulation was generally seen to be a useful way of doing this. Future work could focus on more fundamental issues of practitioner training and time allocation within health check consultations.

TRIAL REGISTRATION

Current Controlled Trials ISRCTN10443908.

FUNDING

This project was funded by the National Institute for Health Research (NIHR) Health Technology Assessment programme and will be published in full in Health Technology Assessment; Vol. 25, No. 50. See the NIHR Journals Library website for further project information.

The effects of communicating cardiovascular disease risk as 'fitness age' on behavioral intentions and psychological outcomes

OBJECTIVES

There is increasing interest in 'biological age' formats to convey the risk of chronic disease. Fitness Age is a relatively new construct that may be useful for younger people who perceive cardiovascular disease (CVD) risk as less relevant. The current study tested whether Fitness Age increases behavioral intentions and psychosocial outcomes compared to formats commonly used for middle aged adults: Heart Age and percentage risk.

METHODS

180 young adults were randomized to 1 of 3 risk formats: Fitness Age, Heart Age, or lifetime percentage risk of CVD. To make the intervention more personally relevant, participants were assigned to receive a low or high risk result based on self-reported lifestyle factors. Validated measures were used for intentions, worry, perceived risk and credibility.

RESULTS

Percentage risk and Heart Age resulted in greater lifestyle change intentions and more accurate numeric risk perception than Fitness Age. High risk results were perceived as less credible but more worrying.

CONCLUSIONS

Fitness Age may be detrimental for risk perception and behavior change for young adults. Percentage risk and Heart Age formats were equally effective.

PRACTICE IMPLICATIONS

Labels for biological age formats matter when developing risk communication tools, and Fitness Age would not be a recommended format.

Current Best Practice for Presenting Probabilities in Patient Decision Aids: Fundamental Principles

BACKGROUND

Shared decision making requires evidence to be conveyed to the patient in a way they can easily understand and compare. Patient decision aids facilitate this process. This article reviews the current evidence for how to present numerical probabilities within patient decision aids.

METHODS

Following the 2013 review method, we assembled a group of 9 international experts on risk communication across Australia, Germany, the Netherlands, the United Kingdom, and the United States. We expanded the topics covered in the first review to reflect emerging areas of research. Groups of 2 to 3 authors reviewed the relevant literature based on their expertise and wrote each section before review by the full authorship team.

RESULTS

Of 10 topics identified, we present 5 fundamental issues in this article. Although some topics resulted in clear guidance (presenting the chance an event will occur, addressing numerical skills), other topics (context/evaluative labels, conveying uncertainty, risk over time) continue to have evolving knowledge bases. We recommend presenting numbers over a set time period with a clear denominator, using consistent formats between outcomes and interventions to enable unbiased comparisons, and interpreting the numbers for the reader to meet the needs of varying numeracy.

DISCUSSION

Understanding how different numerical formats can bias risk perception will help decision aid developers communicate risks in a balanced, comprehensible manner and avoid accidental "nudging" toward a particular option. Decisions between probability formats need to consider the available evidence and user skills. The review may be useful for other areas of science communication in which unbiased presentation of probabilities is important.

Evaluating the use of the heart age tool in community pharmacies: a 4-week cluster-randomized controlled trial

BACKGROUND

Joint British Societies have developed a tool that utilizes information on cardiovascular disease (CVD) risk factors to estimate an individual's 'heart age'. We studied if using heart age as an add-on to conventional risk communication could enhance the motivation for adapting to a healthier lifestyle resulting in improved whole-blood cholesterol and omega-3 status after 4 weeks.

METHODS

A total of 48 community pharmacies were cluster-randomized to use heart age+conventional risk communication (intervention) or only conventional risk communication (control) in 378 subjects after CVD risk-factor assessment. Dried blood spots were obtained with a 4-week interval to assay whole-blood cholesterol and omega-3 fatty acids. We also explored pharmacy-staff's (n=27) perceived utility of the heart age tool.

RESULTS

Subjects in the intervention pharmacies (n=137) had mean heart age 64 years and chorological age 60 years. In these, cholesterol decreased by median (interquartile range) -0.10 (-0.40, 0.35) mmol/l. Cholesterol decreased by -0.20 (-0.70, 0.30) mmol/l (P difference =0.24) in subjects in the control pharmacies (n=120) with mean chronological age 60 years. We observed increased concentrations of omega-3 fatty acids after 4 weeks, non-differentially between groups. Pharmacy-staff (n=27) agreed that heart age was a good way to communicate CVD risk, and most (n=25) agreed that it appeared to motivate individuals to reduce elevated CVD risk factors.

CONCLUSIONS

The heart age tool was considered a convenient and motivating communication tool by pharmacy-staff. Nevertheless, communicating CVD risk as heart age was not more effective than conventional risk communication alone in reducing whole-blood cholesterol levels and improving omega-3 status.

A qualitative exploration of two risk calculators using video-recorded NHS health check consultations

BACKGROUND

The aim of the study was to explore practitioner-patient interactions and patient responses when using QRISK®2 or JBS3 cardiovascular disease (CVD) risk calculators. Data were from video-recorded NHS Health Check (NHSHC) consultations captured as part of the UK RIsk COmmunication (RICO) study; a qualitative study of video-recorded NHSHC consultations from 12 general practices in the West Midlands, UK. Participants were those eligible for NHSHC based on national criteria (40-74 years old, no existing diagnoses for cardiovascular-related conditions, not on statins), and practitioners, who delivered the NHSHC.

METHOD

NHSHCs were video-recorded. One hundred twenty-eight consultations were transcribed and analysed using deductive thematic analysis and coded using a template based around Protection Motivation Theory.

RESULTS

Key themes used to frame the analysis were Cognitive Appraisal (Threat Appraisal, and Coping Appraisal), and Coping Modes (Adaptive, and Maladaptive). Analysis showed little evidence of CVD risk communication, particularly in consultations using QRISK®2. Practitioners often missed opportunities to check patient understanding and encourage risk- reducing behaviour, regardless of the risk calculator used resulting in practitioner verbal dominance. JBS3 appeared to better promote opportunities to initiate risk-factor discussion, and Heart Age and visual representation of risk were more easily understood and impactful than 10-year percentage risk. However, a lack of effective CVD risk discussion in both risk calculator groups increased the likelihood of a maladaptive coping response.

CONCLUSIONS

The analysis demonstrates the importance of effective, shared practitioner-patient discussion to enable adaptive coping responses to CVD risk information, and highlights a need for effective and evidence-based practitioner training.

TRIAL REGISTRATION

ISRCTN ISRCTN10443908 . Registered 7th February 2017.

Explainability for artificial intelligence in healthcare: a multidisciplinary perspective

BACKGROUND

Explainability is one of the most heavily debated topics when it comes to the application of artificial intelligence (AI) in healthcare. Even though AI-driven systems have been shown to outperform humans in certain analytical tasks, the lack of explainability continues to spark criticism. Yet, explainability is not a purely technological issue, instead it invokes a host of medical, legal, ethical, and societal questions that require thorough exploration. This paper provides a comprehensive assessment of the role of explainability in medical AI and makes an ethical evaluation of what explainability means for the adoption of AI-driven tools into clinical practice.

METHODS

Taking AI-based clinical decision support systems as a case in point, we adopted a multidisciplinary approach to analyze the relevance of explainability for medical AI from the technological, legal, medical, and patient perspectives. Drawing on the findings of this conceptual analysis, we then conducted an ethical assessment using the "Principles of Biomedical Ethics" by Beauchamp and Childress (autonomy, beneficence, nonmaleficence, and justice) as an analytical framework to determine the need for explainability in medical AI.

RESULTS

Each of the domains highlights a different set of core considerations and values that are relevant for understanding the role of explainability in clinical practice. From the technological point of view, explainability has to be considered both in terms how it can be achieved and what is beneficial from a development perspective. When looking at the legal perspective we identified informed consent, certification and approval as medical devices, and liability as core touchpoints for explainability. Both the medical and patient perspectives emphasize the importance of considering the interplay between human actors and medical AI. We conclude that omitting explainability in clinical decision support systems poses a threat to core ethical values in medicine and may have detrimental consequences for individual and public health.

CONCLUSIONS

To ensure that medical AI lives up to its promises, there is a need to sensitize developers, healthcare professionals, and legislators to the challenges and limitations of opaque algorithms in medical AI and to foster multidisciplinary collaboration moving forward.

Quantitative examination of video-recorded NHS Health Checks: comparison of the use of QRISK2 versus JBS3 cardiovascular risk calculators

OBJECTIVES

Quantitatively examine the content of National Health Service Health Check (NHSHC), patient-practitioner communication balance and differences when using QRISK2 versus JBS3 cardiovascular disease (CVD) risk calculators.

DESIGN

RIsk COmmunication in NHSHC was a qualitative study with quantitative process evaluation, comparing NHSHC using QRISK2 or JBS3. We present data from the quantitative process evaluation.

SETTING AND PARTICIPANTS

Twelve general practices in the West Midlands (England) conducted NHSHC using JBS3 or QRISK2 (6/group). Patients were eligible for NHSHC based on national criteria (aged 40-74, no existing cardiovascular-related diagnoses, not taking statins). Recruitment was stratified by patients' age, gender and ethnicity.

METHODS

Video recordings of NHSHC were coded, second-by-second, to quantify who was speaking and what was being discussed. Outcomes included consultation duration, practitioner verbal dominance (ratio of practitioner:patient speaking time (pr:pt ratio)) and proportion of time discussing CVD risk, risk factors and risk management.

RESULTS

173 video-recorded NHSHC were analysed (73 QRISK, 100 JBS3). The sample was 51% women, 83% white British, with approximately equal proportions across age groups. NHSHC duration varied greatly (6.8-38.0 min). Most (60%) lasted less than 20 min. On average, CVD risk was discussed for less than 2 min (9.06%±4.30% of consultation time). There were indications that, compared with NHSHC using JBS3, those with QRISK2 involved less CVD risk discussion (JBS3 M=10.24%, CI: 8.01-12.48 vs QRISK2 M=7.44%, CI: 5.29-9.58) and were more verbally dominated by practitioners (pr:pt ratio JBS3 M=3.21%, CI: 2.44-3.97 vs QRISK2=2.35%, CI: 1.89-2.81). The largest proportion of NHSHC time was spent discussing causal risk factors (M=37.54%, CI: 32.92-42.17).

CONCLUSIONS

There was wide variation in NHSHC duration. Many were short and practitioner-dominated, with little time discussing CVD risk. JBS3 appears to extend CVD risk discussion and patient contribution. Qualitative examination of how it is used is necessary to fully understand the potential benefits of these differences.

TRIAL REGISTRATION NUMBER

ISRCTN10443908.

Experiences of a National Web-Based Heart Age Calculator for Cardiovascular Disease Prevention: User Characteristics, Heart Age Results, and Behavior Change Survey

Background

Heart age calculators are used worldwide to engage the public in cardiovascular disease (CVD) prevention. Experimental studies with small samples have found mixed effects of these tools, and previous reports of population samples that used web-based heart age tools have not evaluated psychological and behavioral outcomes.

Objective

This study aims to report on national users of the Australian heart age calculator and the follow-up of a sample of users.

Methods

The heart age calculator was launched in 2019 by the National Heart Foundation of Australia. Heart age results were calculated for all users and recorded for those who signed up for a heart age report and an email follow-up over 10 weeks, after which a survey was conducted. CVD risk factors, heart age results, and psychological and behavioral questions were analyzed using descriptive statistics and chi-square tests. Open responses were thematically coded.

Results

There were 361,044 anonymous users over 5 months, of which 30,279 signed up to receive a heart age report and 1303 completed the survey. There were more women (19,840/30,279, 65.52%), with an average age of 55.67 (SD 11.43) years, and most users knew blood pressure levels (20,279/30,279, 66.97%) but not cholesterol levels (12,267/30,279, 40.51%). The average heart age result was 4.61 (SD 4.71) years older than the current age, including (23,840/30,279, 78.73%) with an older heart age. For the survey, most users recalled their heart age category (892/1303, 68.46%), and many reported lifestyle improvements (diet 821/1303, 63.01% and physical activity 809/1303, 62.09%). People with an older heart age result were more likely to report a doctor visit (538/1055, 51.00%). Participants indicated strong emotional responses to heart age, both positive and negative.

Conclusions

Most Australian users received an older heart age as per international and UK heart age tools. Heart age reports with follow-up over 10 weeks prompted strong emotional responses, high recall rates, and self-reported lifestyle changes and clinical checks for more than half of the survey respondents. These findings are based on a more engaged user sample than previous research, who were more likely to know blood pressure and cholesterol values. Further research is needed to determine which aspects are most effective in initiating and maintaining lifestyle changes. The results confirm high public interest in heart age tools, but additional support is needed to help users understand the results and take appropriate action.

Disparities in the Prevalence of Excess Heart Age Among Women with a Recent Live Birth

Background: Understanding and addressing cardiovascular disease (CVD) risk has implications for maternal and child health outcomes. Heart age, the modeled age of an individual's cardiovascular system based on risk level, and excess heart age, the difference between a person's heart age and chronological age, are alternative simplified ways to communicate CVD risk. Among women with a recent live birth, we predicted heart age, calculated prevalence of excess heart age (≥5 years), and examined factors associated with excess heart age. Materials and Methods: Data were analyzed in 2017 from 2009 to 2014 Pregnancy Risk Assessment Monitoring System (PRAMS). To calculate heart age we used maternal age, prepregnancy body mass index, systolic blood pressure, smoking status, and diabetic status. Weighted prevalence and prevalence ratios compared the likelihood of excess heart age across racial/ethnic groups by selected factors. Results: Prevalence of excess heart age was higher in non-Hispanic black women (11.8%) than non-Hispanic white women (7.3%, prevalence ratio [PR], 95% confidence interval [CI]: 1.62, 1.49-1.76) and Hispanic women (4.9%, PR, 95% CI: 2.39, 2.10-2.72). Prevalence of excess heart age was highest among women who were without health insurance, obese or overweight, engaged in physical activity less than thrice per week, or were smokers in the prepregnancy period. Among women with less than high school education, non-Hispanic black women had a higher prevalence of excess heart age than Hispanic women (PR, 95% CI: 4.01, 3.15-5.10). Conclusions: Excess heart age may be an important tool for decreasing disparities and encouraging CVD risk reduction among certain groups of women.

Novel Risk Modeling Approach of Atrial Fibrillation With Restricted Mean Survival Times: Application in the Framingham Heart Study Community-Based Cohort

BACKGROUND

Risk prediction models for atrial fibrillation (AF) do not give information about when AF might develop. Restricted mean survival time (RMST) quantifies risk into the time domain. Our objective was to use RMST to re-express individualized AF risk predictions.

METHODS AND RESULTS

We included AF-free participants from the Framingham Heart Study community-based cohorts. We predicted new-onset AF over 10-year follow-up according to baseline covariates: age, height, weight, systolic blood pressure, diastolic blood pressure, current smoking, antihypertensive treatment, diabetes mellitus, prevalent heart failure, and prevalent myocardial infarction. First, we fitted a Cox regression model and estimated the 10-year predicted risk of AF. Second, we fitted an RMST model and estimated the predicted mean time free of AF and alive over a time horizon of 10 years. We included 7586 AF-free participants contributing to 11 088 examinations (mean age 61±11 years, 44% were men). During 10-year follow-up, 822 participants developed AF. The Cox and RMST models were in agreement regarding the direction, strength, and statistical significance of associations for all covariates. Low (<5%), intermediate (5%-15%), and high (>15%) 10-year predicted risk of AF corresponded to predicted mean time alive and free of AF of 9.9, 9.6, and 8.8 years, respectively. A 60-year-old woman with a body mass index of 25 kg/m2, no use of hypertension treatment and no history of heart failure had a predicted mean time alive and free of AF of 9.9 years, whereas a 70-year-old man with a body mass index of 30 kg/m2, use of hypertension treatment, and with prevalent heart failure had a predicted mean time alive and free of AF of 7.9 years.

CONCLUSIONS

The RMST can be used to develop risk prediction models to express results in a time scale. RMST may offer a complementary risk communication tool for AF in clinical practice.

Improving cardiovascular disease risk communication in the UK national health service health check programme

OBJECTIVE

To develop and test training to improve practitioners' confidence and perceived understanding when communicating cardiovascular disease (CVD) risk using novel tools and metrics.

METHODS

A CVD risk communication training workshop was developed through interviews with patients and practitioners delivering Health Checks, a literature review, NICE guidance and the UK Health Check competency framework. It was pilot-tested with practitioners delivering Health Checks in the UK. Perceived practitioner understanding and confidence were measured before and up to 10 weeks after the workshop, and changes were compared with those in a control group (who received no intervention). Perceived impact was also explored through semi-structured interviews.

RESULTS

Sixty-two practitioners (34 intervention, 28 control) took part. Perceived practitioner understanding (p = .030) and perceived patient understanding (p = .007) improved significantly for those delivering Health Checks in the training group compared with controls. Practitioner confidence also improved significantly more in practitioners who attended the training (p = .001). Findings were supported by interviews with a sub-sample of practitioners (n = 13).

CONCLUSION

The training workshop improved practitioners' confidence and perceived understanding of CVD risk in Health Checks.

PRACTICE IMPLICATIONS

The training is an important step to improving practitioner understanding of CVD risk in Health Checks and should be implemented on a wider scale.

The prediction of therapy-benefit for individual cardiovascular disease prevention: rationale, implications, and implementation

PURPOSE OF REVIEW

We aim to outline the importance and the clinical implications of using predicted individual therapy-benefit in making patient-centered treatment decisions in cardiovascular disease (CVD) prevention. Therapy-benefit concepts will be illustrated with examples of patients undergoing lipid management.

RECENT FINDINGS

In both primary and secondary CVD prevention, the degree of variation in individual therapy-benefit is large. An individual's therapy-benefit can be estimated by combining prediction algorithms and clinical trial data. Measures of therapy-benefit can be easily integrated into clinical practice via a variety of online calculators. Lifetime estimates (e.g., gain in healthy life expectancy) look at therapy-benefit over the course of an individual's life, and are less influenced by age than short-term estimates (e.g., 10-year absolute risk reduction). Lifetime estimates can thus identify people who could substantially benefit from early initiation of CVD prevention. Compared with current guidelines, treatment based on predicted therapy-benefit would increase eligibility for therapy among young people with a moderate risk-factor burden and individuals with a high residual risk.

SUMMARY

The estimation of individual therapy-benefit is an important part of individualized medicine. Implementation tools allow for clinicians to readily estimate both short-term and lifetime therapy-benefit.

Investigating the Agreement Between Cardiovascular Disease Risk Calculators Among People Diagnosed With Schizophrenia

Background: People diagnosed with schizophrenia have a much reduced life expectancy compared to the general population, and a more than doubled risk of dying from cardiovascular disease (CVD). Existing CVD risk calculators can be used to detect people with an elevated predicted risk of CVD to inform interventions to reduce risk. Aims: This study aimed to compare four different risk calculators for 10-year predicted CVD risk in a sample of people with schizophrenia. Methods: Thirty participants with a diagnosis of schizophrenia spectrum disorders living within Greater Manchester, United Kingdom took part. Ten-year predicted cardiovascular risk scores were calculated using four different models: QRISK3, Framingham, PRIMROSE BMI, and PRIMROSE lipid. Risk estimates and classified risk categories were compared. Results: QRISK3 identified 11 (39%) as having >10% risk of a CV event within 10 years, 4 (14%) of whom exceeded 20%. The Framingham model identified 4 (14%) as exceeding 10%, none of whom exceeded 20%. PRIMROSE risk calculators identified no participants as having >10% risk of a CV event within 10 years. Pairwise concordance correlation coefficients between types of model ranged 0.22-0.77. Mean (± SD) age was 40 (± 10) years but QRISK3's mean "Heart age" was 58 (± 14) years. Conclusion: Risk calculators generate differing predicted CVD risk scores for patients with schizophrenia. Using one risk calculator might yield different recommended monitoring and treatment plans compared to another. Clinicians should therefore take into account other patient-related factors, such as patients' preferences and other underlying physical conditions when making treatment decisions.