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Large data-set studies on CVD and multi-morbidity

PLOS Medicine has published a special issue on cardiovascular disease (CVD) and multi-morbidity, with three studies using data drawn respectively from the  UK Clinical Practice Research Datalink, the Myocardial Ischaemia National Audit Project (England and Wales), and the Swedish National study of Ageing and Care in Kungsholmen (SNAC-K).

PLOS Medicine has published a special issue on cardiovascular disease (CVD) and multi-morbidity advised by guest editors Dr Carolyn SP Lam, Duke-NUS Medical School, Singapore, Dr Kazem Rahimi, The George Institute for Global Health, University of Oxford, UK, and Dr Steven Steinhubl, Scripps Translational Science Institute, US.

CVD is the number one cause of death and disability globally, with an estimated 17.7 million deaths from CVD in 2015. The demographic shift towards older populations across the globe and the relatively slower decline in morbidity compared with mortality from CVD have resulted in increasing numbers of people with both CVD and other chronic and disabling conditions. Multi-morbidity, commonly defined as the presence of two or more chronic medical conditions in an individual, is linked to poorer outcomes, lower quality of life, and increased healthcare utilisation.

The Special Issue opens with three original research articles:

In the first article, using data from the UK Clinical Practice Research Datalink, a population-based dataset including routinely collected data from 674 UK general practices, Kazem Rahimi of the George Institute for Global Health, Oxford, UK, and colleagues describe the prevalence of 56 clinically important and common comorbidities in 229,205 patients with newly diagnosed non-fatal CVD between 2000 and 2014. Using age- and sex-standardized estimates, the researchers found that while the incidence of CVD decreased by 34% between 2000 to 2014, the prevalence of having 5 or more comorbidities increased from 6.3% (95% CI 5.6%±17.0%) in 2000 to 24.3% (22.1%±34.8%) in 2014. The most common comorbidities were hypertension (28.9%), depression (23.0%), arthritis, (20.9%), asthma (17.7%), and anxiety (15.0%). While the findings rely on recorded diagnoses which could underestimate the actual prevalences in the general population, they emphasize the need to broaden the current single-disease paradigm in CVD management to account for the increasing burden of comorbidities.

In the second article, a population-based study using data from the Myocardial Ischaemia National Audit Project (England and Wales), Marlous Hall of the University of Leeds, UK, and colleagues identify multi-morbidity patterns in patients admitted with acute myocardial infarction (heart attack) between 2003 and 2013. Of the 693,388 patients with AMI admitted over this period, 60% had at least one of the 7 conditions examined (diabetes, chronic obstructive pulmonary disease or asthma, heart failure, renal failure, stroke, peripheral vascular disease, or hypertension). The researchers identified 3 multi-morbidity phenotype clusters: (1) a high multi-morbidity class, with concomitant heart failure, peripheral vascular disease, and hypertension, (2) a medium multi-morbidity class, with peripheral vascular disease and hypertension, and (3) a low multi-morbidity class. They estimated that patients who had high and medium levels of multi-morbidity had average reduced life expectancies of 2.9 (95% CI 2.6±3.2) and 1.5 years (95% CI 1.3±1.7), respectively, compared with patients who had few comorbidities. While the authors did not examine all common comorbid conditions (e.g. dementia and cancer), the findings suggest that development of treatment guidelines for multi-morbidity patient groups, rather than those currently available for single-diseases, has the potential to substantially improve post-MI outcomes for patients with multi-morbid conditions.

In the third article, using data from the Swedish National study of Ageing and Care in Kungsholmen (SNAC-K), Davide Vetrano of the Karolinska Institutet, Stockholm, Sweden, and colleagues examined trajectories of functional decline, measured by walking speed and activities of daily living (ADL), in 2,385 older adults with and without cardiovascular disease (ischemic heart disease, heart failure, and atrial fibrillation) and neuro-psychiatric disease (e.g. mood disorders, dementia, and stroke). During the nine-year follow-up, individuals with multiple cardiovascular and neuro-psychiatric diseases had the steepest declines in walking speed (up to 0.7 m/s; p < 0.001) and ADL independence (up to three impairments in ADL) compared with those without these diseases. The researchers observed significant declines over time for both walking speed and ADL in older adults with one or more neuro-psychiatric diseases, but only for walking speed and those with cardiovascular multi-morbidity. While the authors were not able to account for the specific contribution of individual diseases, these findings suggest that neuro-psychiatric diseases may play a greater role in functional decline in older adults than cardiovascular disease.

Abstract 1
Background: Multimorbidity in people with cardiovascular disease (CVD) is common, but large-scale contemporary reports of patterns and trends in patients with incident CVD are limited. We investigated the burden of comorbidities in patients with incident CVD, how it changed between 2000 and 2014, and how it varied by age, sex, and socioeconomic status (SES).
Methods and findings: We used the UK Clinical Practice Research Datalink with linkage to Hospital Episode Statistics, a population-based dataset from 674 UK general practices covering approximately 7% of the current UK population. We estimated crude and age/sex-standardised (to the 2013 European Standard Population) prevalence and 95% confidence intervals for 56 major comorbidities in individuals with incident non-fatal CVD. We further assessed temporal trends and patterns by age, sex, and SES groups, between 2000 and 2014. Among a total of 4,198,039 people aged 16 to 113 years, 229,205 incident cases of non-fatal CVD, defined as first diagnosis of ischaemic heart disease, stroke, or transient ischaemic attack, were identified. Although the age/sex-standardised incidence of CVD decreased by 34% between 2000 to 2014, the proportion of CVD patients with higher numbers of comorbidities increased. The prevalence of having 5 or more comorbidities increased 4-fold, rising from 6.3% (95% CI 5.6%–17.0%) in 2000 to 24.3% (22.1%–34.8%) in 2014 in age/sex-standardised models. The most common comorbidities in age/sex-standardised models were hypertension (28.9% [95% CI 27.7%–31.4%]), depression (23.0% [21.3%–26.0%]), arthritis (20.9% [19.5%–23.5%]), asthma (17.7% [15.8%–20.8%]), and anxiety (15.0% [13.7%–17.6%]). Cardiometabolic conditions and arthritis were highly prevalent among patients aged over 40 years, and mental illnesses were highly prevalent in patients aged 30–59 years. The age-standardised prevalence of having 5 or more comorbidities was 19.1% (95% CI 17.2%–22.7%) in women and 12.5% (12.0%–13.9%) in men, and women had twice the age-standardised prevalence of depression (31.1% [28.3%–35.5%] versus 15.0% [14.3%–16.5%]) and anxiety (19.6% [17.6%–23.3%] versus 10.4% [9.8%–11.8%]). The prevalence of depression was 46% higher in the most deprived fifth of SES compared with the least deprived fifth (age/sex-standardised prevalence of 38.4% [31.2%–62.0%] versus 26.3% [23.1%–34.5%], respectively). This is a descriptive study of routine electronic health records in the UK, which might underestimate the true prevalence of diseases.
Conclusions: The burden of multimorbidity and comorbidity in patients with incident non-fatal CVD increased between 2000 and 2014. On average, older patients, women, and socioeconomically deprived groups had higher numbers of comorbidities, but the type of comorbidities varied by age and sex. Cardiometabolic conditions contributed substantially to the burden, but 4 out of the 10 top comorbidities were non-cardiometabolic. The current single-disease paradigm in CVD management needs to broaden and incorporate the large and increasing burden of comorbidities.

Jenny Tran, Robyn Norton, Nathalie Conrad, Fatemeh Rahimian, Dexter Canoy, Milad Nazarzadeh, Kazem Rahimi

Abstract 2
Background: There is limited knowledge of the scale and impact of multimorbidity for patients who have had an acute myocardial infarction (AMI). Therefore, this study aimed to determine the extent to which multimorbidity is associated with long-term survival following AMI.
Methods and findings: This national observational study included 693,388 patients (median age 70.7 years, 452,896 [65.5%] male) from the Myocardial Ischaemia National Audit Project (England and Wales) who were admitted with AMI between 1 January 2003 and 30 June 2013. There were 412,809 (59.5%) patients with multimorbidity at the time of admission with AMI, i.e., having at least 1 of the following long-term health conditions: diabetes, chronic obstructive pulmonary disease or asthma, heart failure, renal failure, cerebrovascular disease, peripheral vascular disease, or hypertension. Those with heart failure, renal failure, or cerebrovascular disease had the worst outcomes (39.5 [95% CI 39.0–40.0], 38.2 [27.7–26.8], and 26.6 [25.2–26.4] deaths per 100 person-years, respectively). Latent class analysis revealed 3 multimorbidity phenotype clusters: (1) a high multimorbidity class, with concomitant heart failure, peripheral vascular disease, and hypertension, (2) a medium multimorbidity class, with peripheral vascular disease and hypertension, and (3) a low multimorbidity class. Patients in class 1 were less likely to receive pharmacological therapies compared with class 2 and 3 patients (including aspirin, 83.8% versus 87.3% and 87.2%, respectively; β-blockers, 74.0% versus 80.9% and 81.4%; and statins, 80.6% versus 85.9% and 85.2%). Flexible parametric survival modelling indicated that patients in class 1 and class 2 had a 2.4-fold (95% CI 2.3–2.5) and 1.5-fold (95% CI 1.4–1.5) increased risk of death and a loss in life expectancy of 2.89 and 1.52 years, respectively, compared with those in class 3 over the 8.4-year follow-up period. The study was limited to all-cause mortality due to the lack of available cause-specific mortality data. However, we isolated the disease-specific association with mortality by providing the loss in life expectancy following AMI according to multimorbidity phenotype cluster compared with the general age-, sex-, and year-matched population.
Conclusions: Multimorbidity among patients with AMI was common, and conferred an accumulative increased risk of death. Three multimorbidity phenotype clusters that were significantly associated with loss in life expectancy were identified and should be a concomitant treatment target to improve cardiovascular outcomes.

Marlous Hall, Tatendashe B Dondo, Andrew T Yan, Mamas A Mamas, Adam D Timmis, John E Deanfield, Tomas Jernberg, Harry Hemingway, Keith AA Fox, Chris P Gale

Abstract 3
Background: Functional decline is a strong health determinant in older adults, and chronic diseases play a major role in this age-related phenomenon. In this study, we explored possible clinical pathways underlying functional heterogeneity in older adults by quantifying the impact of cardiovascular (CV) and neuropsychiatric (NP) chronic diseases and their co-occurrence on trajectories of functional decline.
Methods and findings: We studied 2,385 people ≥60 years (range 60–101 years) participating in the Swedish National study of Aging and Care in Kungsholmen (SNAC-K). Participants underwent clinical examination at baseline (2001–2004) and every 3 or 6 years for up to 9 years. We grouped participants on the basis of 7 mutually exclusive clinical patterns of 0, 1, or more CV and NP diseases and their co-occurrence, from a group without any CV and NP disease to a group characterised by the presence of CV or NP multimorbidity, accompanied by at least 1 other CV or NP disorder. The group with no CV and/or NP diseases served as the reference group. Functional decline was estimated over 9 years of follow-up by measuring mobility (walking speed, m/s) and independence (ability to carry out six activities of daily living [ADL]). Mixed-effect linear regression models were used (1) to explore the individual-level prognostic predictivity of the different CV and NP clinical patterns at baseline and (2) to quantify the association between the clinical patterns and functional decline at the group level by entering the clinical patterns as time-varying measures. During the 9-year follow-up, participants with multiple CV and NP diseases had the steepest decline in walking speed (up to 0.7 m/s; p < 0.001) and ADL independence (up to three impairments in ADL, p < 0.001) (reference group: participants without any CV and NP disease). When the clinical patterns were analyzed as time varying, isolated CV multimorbidity impacted only walking speed (β −0.1; p < 0.001). Conversely, all the clinical patterns that included at least 1 NP disease were significantly associated with decline in both walking speed (β −0.21–−0.08; p < 0.001) and ADL independence (β −0.27–−0.06; p < 0.05). Groups with the most complex clinical patterns had 5%–20% lower functioning at follow-up than the reference group. Key limitations of the study include that we did not take into account the specific weight of single diseases and their severity and that the exclusion of participants with less than 2 assessments may have led to an underestimation of the tested associations.
Conclusions: In older adults, different patterns of CV and NP morbidity lead to different trajectories of functional decline over time, a finding that explains part of the heterogeneity observed in older adults’ functionality. NP diseases, alone or in association, are prevalent and major determinants of functional decline, whereas isolated CV multimorbidity is associated only with declines in mobility.

Davide L Vetrano, Debora Rizzuto, Amaia Calderón-Larrañaga, Graziano Onder, Anna-Karin Welmer, Roberto Bernabei, Alessandra Marengoni, Laura Fratiglioni

[link url=""]PLOS Collections Special Issue[/link]
[link url=""]PLOS Medicine abstract 1[/link]
[link url=""]PLOS Medicine abstract 2[/link]
[link url=""]PLOS Medicine abstract 3[/link]

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