Patterns and temporal trends of comorbidity among adult patients with incident cardiovascular disease in the UK between 2000 and 2014: A population-based cohort study

The burden of diabetes-associated multiple long-term conditions on years of life spent and lost

Diabetes mellitus is a central driver of multiple long-term conditions (MLTCs), but population-based studies have not clearly characterized the burden across the life course. We estimated the age of onset, years of life spent and loss associated with diabetes-related MLTCs among 46 million English adults. We found that morbidity patterns extend beyond classic diabetes complications and accelerate the onset of severe MLTCs by 20 years earlier in life in women and 15 years earlier in men. By the age of 50 years, one-third of those with diabetes have at least three conditions, spend >20 years with them and die 11 years earlier than the general population. Each additional condition at the age of 50 years is associated with four fewer years of life. Hypertension, depression, cancer and coronary heart disease contribute heavily to MLTCs in older age and create the greatest community-level burden on years spent (813 to 3,908 years per 1,000 individuals) and lost (900 to 1,417 years per 1,000 individuals). However, in younger adulthood, depression, severe mental illness, learning disabilities, alcohol dependence and asthma have larger roles, and when they occur, all except alcohol dependence were associated with long periods of life spent (11-14 years) and all except asthma associated with many years of life lost (11-15 years). These findings provide a baseline for population monitoring and underscore the need to prioritize effective prevention and management approaches.

Predicting the risk of diabetes complications using machine learning and social administrative data in a country with ethnic inequities in health: Aotearoa New Zealand

BACKGROUND

In the age of big data, linked social and administrative health data in combination with machine learning (ML) is being increasingly used to improve prediction in chronic disease, e.g., cardiovascular diseases (CVD). In this study we aimed to apply ML methods on extensive national-level health and social administrative datasets to assess the utility of these for predicting future diabetes complications, including by ethnicity.

METHODS

Five ML models were used to predict CVD events among all people with known diabetes in the population of New Zealand, utilizing nationwide individual-level administrative data.

RESULTS

The Xgboost ML model had the best predictive power for predicting CVD events three years into the future among the population with diabetes (N = 145,600). The optimization procedure also found limited improvement in prediction by ethnicity (using area under the receiver operating curve, [AUC]). The results indicated no trade-off between model predictive performance and equity gap of prediction by ethnicity (that is improving model prediction and reducing performance gaps by ethnicity can be achieved simultaneously). The list of variables of importance was different among different models/ethnic groups, for example: age, deprivation (neighborhood-level), having had a hospitalization event, and the number of years living with diabetes.

DISCUSSION AND CONCLUSIONS

We provide further evidence that ML with administrative health data can be used for meaningful future prediction of health outcomes. As such, it could be utilized to inform health planning and healthcare resource allocation for diabetes management and the prevention of CVD events. Our results may suggest limited scope for developing prediction models by ethnic group and that the major ways to reduce inequitable health outcomes is probably via improved delivery of prevention and management to those groups with diabetes at highest need.

Construction of a quality of life scale for older individuals with neuro-co-cardiological diseases

PURPOSE

This study aimed to develop a Quality of Life (QOL) assessment scale for older patients with Neuro-co-Cardiological Diseases (NCCD) and to evaluate the reliability and validity of the scale.

METHOD

The study participants were derived from the Elderly Individuals with NCCD Registered Cohort Study (EINCCDRCS), a multicenter registry of patients with NCCD. The preliminary testing of the questionnaire was conducted among 10 older individuals aged 65 years and older who had NCCD and were recruited from the registry. Other patients who met the inclusion criteria participated in the field testing. After verifying the unidimensionality, local independence, and monotonicity assumptions of the scale, we employed the Rasch model within Item Response Theory framework to assess the quality of the scale through methods including internal consistency, criterion validity, Wright map, and item functioning differential. Subsequently, we assessed the construct validity of the scale by combining exploratory factor analysis with confirmatory factor analysis.

RESULTS

Based on well-validated scales such as the short-form WHOQOL-OLD, HeartQOL, IQCODE, and SF-36, an original Neuro-co-Cardiological Diseases Quality of Life scale (NCCDQOL) was developed. 196 individuals from the EINCCDRCS were included in the study, with 10 participating in the preliminary testing and 186 in the field testing. Based on the results of the preliminary testing, the original questionnaire was refined through item deletion and adjustment, resulting in an 11-item NCCDQOL questionnaire. The Rasch analysis of the field testing data led to the removal of 21 misfitting individuals. The NCCDQOL demonstrated a four-category structure, achieved by combining two response categories. This structure aligned with the assumptions of unidimensionality, local independence, and monotonicity. The NCCDQOL also exhibited good validity and reliability.

CONCLUSION

The revised NCCDQOL questionnaire demonstrated good reliability and validity in the Rasch model, indicating promising potential for clinical application.

Targeted-BEHRT: Deep Learning for Observational Causal Inference on Longitudinal Electronic Health Records

Observational causal inference is useful for decision-making in medicine when randomized clinical trials (RCTs) are infeasible or nongeneralizable. However, traditional approaches do not always deliver unconfounded causal conclusions in practice. The rise of "doubly robust" nonparametric tools coupled with the growth of deep learning for capturing rich representations of multimodal data offers a unique opportunity to develop and test such models for causal inference on comprehensive electronic health records (EHRs). In this article, we investigate causal modeling of an RCT-established causal association: the effect of classes of antihypertensive on incident cancer risk. We develop a transformer-based model, targeted bidirectional EHR transformer (T-BEHRT) coupled with doubly robust estimation to estimate average risk ratio (RR). We compare our model to benchmark statistical and deep learning models for causal inference in multiple experiments on semi-synthetic derivations of our dataset with various types and intensities of confounding. In order to further test the reliability of our approach, we test our model on situations of limited data. We find that our model provides more accurate estimates of relative risk [least sum absolute error (SAE) from ground truth] compared with benchmark estimations. Finally, our model provides an estimate of class-wise antihypertensive effect on cancer risk that is consistent with results derived from RCTs.

Epidemiology of multimorbidity associated with atherosclerotic cardiovascular disease in the United States, 1999-2018

BACKGROUND

The multimorbidity of Atherosclerotic cardiovascular disease (ASCVD) and many other chronic conditions is becoming common. This study aimed to assess multimorbidity distribution in ASCVD among adults in the United States from 1999 to 2018.

METHODS

This cross-sectional survey from the National Health and Nutrition Examination Survey (NHANES) 1999-2018 using stratified multistage probability design. Among the 53,083 survey respondents during the study period, 5,729 US adults aged ≥ 20 years with ASCVD. Joinpoint regression was used to assess the statistical significance of prevalence trends in the prevalence of ASCVD stratified by multimorbidity. The Apriori association rule mining algorithm was used to identify common multimorbidity association patterns in ASCVD patients.

RESULTS

Overall, 5,729 of 53,083 individuals had ASCVD, and the prevalence showed a slow declining trend (biannual percentage change = -0.81%, p = 0.035, average 7.71%). The prevalence of ASCVD significantly decreased in populations without dyslipidemia, diabetes mellitus (DM), hypertension, asthma, chronic obstructive pulmonary disease (COPD), and arthritis (all groups, p < 0.05). Additionally, 65.6% of ASCVD patients had at least four of the 12 selected chronic conditions, with four and five being the most common numbers of conditions (17.9% and 17.7%, respectively). The five most common chronic conditions were (in order) dyslipidemia, hypertension, arthritis, chronic kidney disease, and DM. The coexistence of hypertension and dyslipidemia had the highest support in association rules (support = 0.63), while the coexistence of dyslipidemia, hypertension, metabolic syndrome, and DM had the highest lift (lift = 1.82).

CONCLUSIONS

During the 20-year survey period, there was a significant decrease in the overall prevalence of ASCVD. However, this reduction was primarily observed in individuals without dyslipidemia, DM, hypertension, asthma, COPD, and arthritis. Among populations with any of the evaluated chronic conditions, the prevalence of ASCVD remained unchanged. Most of ASCVD patients had four or more concurrent chronic conditions.

Quality of life in elderly patients with Neuro-co-Cardiological Diseases: Rasch analysis and confirmatory factor analysis of WHOQOL-BREF and SF-36 instruments

PURPOSE

The quality of life (QOL) in elderly patients with neuro-co-cardiological diseases multimorbidity (NCCD) exhibits distinct features, but there is a scarcity of research in this specialized area. This study seeks to comprehensively assess the QOL of elderly patients with NCCD, employing both the WHOQOL-BREF and SF-36 instruments, while concurrently evaluating the validity and reliability of these two measurement scales.

METHODS

The study participants were derived from the Elderly Individuals with Neuro-co-Cardiological Diseases Registered Cohort Study (EINCCDRCS). WHOQOL-BREF and SF-36 were used for QOL assessment. Rasch analysis, and Confirmatory Factor Analysis were conducted. Internal consistency, ceiling, and floor effects were also analyzed.

RESULTS

202 patients from the EINCCDRCS were included in the study. Both scales showed good reliability and validity. SF-36 demonstrated better distribution and targeting compared to WHOQOL-BREF. Some items exhibited potential bias in specific patient groups. However, the 'Role limitations due to emotional problems' component showed suboptimal performance in certain assessments, suggesting its consideration for removal in practical use. Differential item functioning was observed in patients with anxiety, depression, and cognitive impairment, highlighting the impact of these conditions on the QOL of elderly NCCD patients.

CONCLUSIONS

Both WHOQOL-BREF and SF-36 are effective instruments for assessing QOL in elderly NCCD patients, showing good reliability and validity for both scales. SF-36 generally outperforms WHOQOL-BREF overall. Patients diagnosed with anxiety and depression, as well as cognitive impairment, exhibited differences in QOL assessment. Further attention to these findings can improve QOL assessment and care for this population.

A life-course approach to tackling noncommunicable diseases in women

Women's health has been critically underserved by a failure to look beyond women's sexual and reproductive systems to adequately consider their broader health needs. In almost every country in the world, noncommunicable diseases are the leading causes of death for women. Among these, cardiovascular disease (including heart disease and stroke) and cancer are the major causes of mortality. Risks for these conditions exist at each stage of women's lives, but recognition of the unique needs of women for the prevention and management of noncommunicable diseases is relatively recent and still emerging. Once they are diagnosed, treatments for these diseases are often costly and noncurative. Therefore, we call for a strategic, innovative life-course approach to identifying disease triggers and instigating cost-effective measures to minimize exposure in a timely manner. Prohibitive barriers to implementing this holistic approach to women's health exist in both the social arena and the medical arena. Recognizing these impediments and implementing practical approaches to surmounting them is a rational approach to advancing health equity for women, with ultimate benefits for society as a whole.

Multimorbidity of cardiovascular disease subtypes in a prospective cohort of 1.2 million UK women

OBJECTIVE

Cardiovascular multimorbidity (CVM) is the co-occurrence of multiple cardiovascular disease subtypes (CVDs) in one person. Because common patterns and incidence of CVM are not well-described, particularly in women, we conducted a descriptive study of CVM in the Million Women Study, a large population-based cohort of women.

METHODS

UK women aged 50-64 years were followed up using hospital admissions and mortality records for an average of 19 years. CVM was defined as having ≥2 of 19 selected CVDs. The age-specific cumulative incidence of CVM between age 60 and 80 years was estimated. The numbers and proportions of individual, pairs and other combinations of CVDs that comprised incident CVM were calculated. For each individual CVD subtype, age-standardised proportions of the counts of other co-occurring CVDs were estimated.

RESULTS

The age-specific likelihood of having CVM nearly doubled every 5 years between age 60 and 80 years. Among 1.2 million women without CVD at study baseline, 16% (n=196 651) had incident CVM by the end of follow-up. Around half of all women with CVM had a diagnosis of ischaemic heart disease (n=102 536) or atrial fibrillation (n=96 022), almost a third had heart failure (n=72 186) and a fifth had stroke (n=40 442). The pair of CVDs with the highest age-adjusted incidence was ischaemic heart disease and atrial fibrillation (18.95 per 10 000 person-years). Over 60% of individuals with any given CVD subtype also had other CVDs, after age standardisation.

CONCLUSIONS

CVM is common. The majority of women with any specific CVD subtype eventually develop at least one other. Clinical and public health guidelines for CVD management should acknowledge this high likelihood of CVM.

Sodium-based paracetamol: impact on blood pressure, cardiovascular events, and all-cause mortality

BACKGROUND AND AIMS

Effervescent formulations of paracetamol containing sodium bicarbonate have been reported to associate with increased blood pressure and a higher risk of cardiovascular diseases and all-cause mortality. Given the major implications of these findings, the reported associations were re-examined.

METHODS

Using linked electronic health records data, a cohort of 475 442 UK individuals with at least one prescription of paracetamol, aged between 60 and 90 years, was identified. Outcomes in patients taking sodium-based paracetamol were compared with those taking non-sodium-based formulations of the same. Using a deep learning approach, associations with systolic blood pressure (SBP), major cardiovascular events (myocardial infarction, heart failure, and stroke), and all-cause mortality within 1 year after baseline were investigated.

RESULTS

A total of 460 980 and 14 462 patients were identified for the non-sodium-based and sodium-based paracetamol exposure groups, respectively (mean age: 74 years; 64% women). Analysis revealed no difference in SBP [mean difference -0.04 mmHg (95% confidence interval -0.51, 0.43)] and no association with major cardiovascular events [relative risk (RR) 1.03 (0.91, 1.16)]. Sodium-based paracetamol showed a positive association with all-cause mortality [RR 1.46 (1.40, 1.52)]. However, after further accounting of other sources of residual confounding, the observed association attenuated towards the null [RR 1.08 (1.01, 1.16)]. Exploratory analyses revealed dysphagia and related conditions as major sources of uncontrolled confounding by indication for this association.

CONCLUSIONS

This study does not support previous suggestions of increased SBP and an elevated risk of cardiovascular events from short-term use of sodium bicarbonate paracetamol in routine clinical practice.

Comorbidity clusters and in-hospital outcomes in patients admitted with acute myocardial infarction in the USA: A national population-based study

BACKGROUND

The prevalence of multimorbidity in patients with acute myocardial infarction (AMI) is increasing. It is unclear whether comorbidities cluster into distinct phenogroups and whether are associated with clinical trajectories.

METHODS

Survey-weighted analysis of the United States Nationwide Inpatient Sample (NIS) for patients admitted with a primary diagnosis of AMI in 2018. In-hospital outcomes included mortality, stroke, bleeding, and coronary revascularisation. Latent class analysis of 21 chronic conditions was used to identify comorbidity classes. Multivariable logistic and linear regressions were fitted for associations between comorbidity classes and outcomes.

RESULTS

Among 416,655 AMI admissions included in the analysis, mean (±SD) age was 67 (±13) years, 38% were females, and 76% White ethnicity. Overall, hypertension, coronary heart disease (CHD), dyslipidaemia, and diabetes were common comorbidities, but each of the identified five classes (C) included ≥1 predominant comorbidities defining distinct phenogroups: cancer/coagulopathy/liver disease class (C1); least burdened (C2); CHD/dyslipidaemia (largest/referent group, (C3)); pulmonary/valvular/peripheral vascular disease (C4); diabetes/kidney disease/heart failure class (C5). Odds ratio (95% confidence interval [CI]) for mortality ranged between 2.11 (1.89-2.37) in C2 to 5.57 (4.99-6.21) in C1. For major bleeding, OR for C1 was 4.48 (3.78; 5.31); for acute stroke, ORs ranged between 0.75 (0.60; 0.94) in C2 to 2.76 (2.27; 3.35) in C1; for coronary revascularization, ORs ranged between 0.34 (0.32; 0.36) in C1 to 1.41 (1.30; 1.53) in C4.

CONCLUSIONS

We identified distinct comorbidity phenogroups that predicted in-hospital outcomes in patients admitted with AMI. Some conditions overlapped across classes, driven by the high comorbidity burden. Our findings demonstrate the predictive value and potential clinical utility of identifying patients with AMI with specific comorbidity clustering.

Developing prediction models to estimate the risk of two survival outcomes both occurring: A comparison of techniques

INTRODUCTION

This study considers the prediction of the time until two survival outcomes have both occurred. We compared a variety of analytical methods motivated by a typical clinical problem of multimorbidity prognosis.

METHODS

We considered five methods: product (multiply marginal risks), dual-outcome (directly model the time until both events occur), multistate models (msm), and a range of copula and frailty models. We assessed calibration and discrimination under a variety of simulated data scenarios, varying outcome prevalence, and the amount of residual correlation. The simulation focused on model misspecification and statistical power. Using data from the Clinical Practice Research Datalink, we compared model performance when predicting the risk of cardiovascular disease and type 2 diabetes both occurring.

RESULTS

Discrimination was similar for all methods. The product method was poorly calibrated in the presence of residual correlation. The msm and dual-outcome models were the most robust to model misspecification but suffered a drop in performance at small sample sizes due to overfitting, which the copula and frailty model were less susceptible to. The copula and frailty model's performance were highly dependent on the underlying data structure. In the clinical example, the product method was poorly calibrated when adjusting for 8 major cardiovascular risk factors.

DISCUSSION

We recommend the dual-outcome method for predicting the risk of two survival outcomes both occurring. It was the most robust to model misspecification, although was also the most prone to overfitting. The clinical example motivates the use of the methods considered in this study.

Predicting Multimorbidity Using Saudi Health Indicators (Sharik) Nationwide Data: Statistical and Machine Learning Approach

The Saudi population is at high risk of multimorbidity. The risk of these morbidities can be reduced by identifying common modifiable behavioural risk factors. This study uses statistical and machine learning methods to predict factors for multimorbidity in the Saudi population. Data from 23,098 Saudi residents were extracted from the "Sharik" Health Indicators Surveillance System 2021. Participants were asked about their demographics and health indicators. Binary logistic models were used to determine predictors of multimorbidity. A backpropagation neural network model was further run using the predictors from the logistic regression model. Accuracy measures were checked using training, validation, and testing data. Females and smokers had the highest likelihood of experiencing multimorbidity. Age and fruit consumption also played a significant role in predicting multimorbidity. Regarding model accuracy, both logistic regression and backpropagation algorithms yielded comparable outcomes. The backpropagation method (accuracy 80.7%) was more accurate than the logistic regression model (77%). Machine learning algorithms can be used to predict multimorbidity among adults, particularly in the Middle East region. Different testing methods later validated the common predicting factors identified in this study. These factors are helpful and can be translated by policymakers to consider improvements in the public health domain.

Causal relationship between osteoarthritis with atrial fibrillation and coronary atherosclerosis: a bidirectional Mendelian randomization study of European ancestry

Background

Osteoarthritis (OA) is a degenerative disease with high prevalence. Some observational studies have shown that patients with osteoarthritis often have co-existing cardiovascular diseases (CVD) such as atrial fibrillation (AF) and coronary atherosclerosis (CA). However, there is still a lack of stronger evidence confirming the association between osteoarthritis and cardiovascular disease. In this study, we used a bidirectional two-sample Mendelian randomization study to investigate the relationship between OA with AF and CA.

Methods

OA data from the UK Biobank and arcOGEN (Arthritis Research UK Osteoarthritis Genetics, a study that aimed to find genetic determinants of osteoarthritis and elucidate the genetic architecture of the disease) integration were selected for the study (n = 417,596), AF data were obtained from six studies (n = 1,030,836), and coronary atherosclerosis data were derived from the FinnGen (n = 218,792). MR analysis was performed primarily using the Inverse variance weighted (IVW) method, with MR Egger, weighted median, simple mode, weighted mode as supplements, sensitivity analysis was performed using Cochran Q statistic, and leave-one-out analysis.

Results

We found that OA and AF were positively associated [IVW: OR (95% CI): 1.11 (1.04, 1.19), P = 0.002], while OA and CA were negatively associated [IVW: OR (95% CI): 0.88 (0.79, 0.98), P = 0.02]. In the reverse MR analysis, no effect of AF on OA was found [IVW: OR (95% CI): 1.00 (0.97, 1.03), P = 0.84], meanwhile, CA and OA were found to be associated negatively [IVW: OR (95% CI): 0.95 (0.92, 0.99), P = 0.01]. No violations of MR assumptions were found in the sensitivity analysis.

Conclusion

This research confirms that OA is a risk factor for AF, and there is a mutual protective factor between OA and CA. However, further studies are still necessary to elucidate the underlying mechanisms.

Systolic blood pressure, chronic obstructive pulmonary disease and cardiovascular risk

OBJECTIVE

In individuals with complex underlying health problems, the association between systolic blood pressure (SBP) and cardiovascular disease is less well recognised. The association between SBP and risk of cardiovascular events in patients with chronic obstructive pulmonary disease (COPD) was investigated.

METHODS AND ANALYSIS

In this cohort study, 39 602 individuals with a diagnosis of COPD aged 55-90 years between 1990 and 2009 were identified from validated electronic health records (EHR) in the UK. The association between SBP and risk of cardiovascular end points (composite of ischaemic heart disease, heart failure, stroke and cardiovascular death) was analysed using a deep learning approach.

RESULTS

In the selected cohort (46.5% women, median age 69 years), 10 987 cardiovascular events were observed over a median follow-up period of 3.9 years. The association between SBP and risk of cardiovascular end points was found to be monotonic; the lowest SBP exposure group of <120 mm Hg presented nadir of risk. With respect to reference SBP (between 120 and 129 mm Hg), adjusted risk ratios for the primary outcome were 0.99 (95% CI 0.93 to 1.05) for SBP of <120 mm Hg, 1.02 (0.97 to 1.07) for SBP between 130 and 139 mm Hg, 1.07 (1.01 to 1.12) for SBP between 140 and 149 mm Hg, 1.11 (1.05 to 1.17) for SBP between 150 and 159 mm Hg and 1.16 (1.10 to 1.22) for SBP ≥160 mm Hg.

CONCLUSION

Using deep learning for modelling EHR, we identified a monotonic association between SBP and risk of cardiovascular events in patients with COPD.

Generalization of contextual fear is sex-specifically affected by high salt intake

A hallmark symptom of many anxiety disorders, and multiple neuropsychiatric disorders more broadly, is generalization of fearful responses to non-fearful stimuli. Anxiety disorders are often comorbid with cardiovascular diseases. One established, and modifiable, risk factor for cardiovascular diseases is salt intake. Yet, investigations into how excess salt consumption affects anxiety-relevant behaviors remains little explored. Moreover, no studies have yet assessed how high salt intake influences generalization of fear. Here, we used adult C57BL/6J mice of both sexes to evaluate the influence of two or six weeks of high salt consumption (4.0% NaCl), compared to controls (0.4% NaCl), on contextual fear acquisition, expression, and generalization. Further, we measured osmotic and physiological stress by quantifying serum osmolality and corticosterone levels, respectively. Consuming excess salt did not influence contextual fear acquisition nor discrimination between the context used for training and a novel, neutral context when training occurred 48 prior to testing. However, when a four week delay between training and testing was employed to induce natural fear generalization processes, we found that high salt intake selectively increases contextual fear generalization in females, but the same diet reduces contextual fear generalization in males. These sex-specific effects were independent of any changes in serum osmolality nor corticosterone levels, suggesting the behavioral shifts are a consequence of more subtle, neurophysiologic changes. This is the first evidence of salt consumption influencing contextual fear generalization, and adds information about sex-specific effects of salt that are largely missing from current literature.

Exploring the genetic correlation of cardiovascular diseases and mood disorders in the UK Biobank

AIMS

Cardiovascular diseases (CVDs) are the leading cause of deaths globally. Mortality and incidence of CVDs are significantly higher in people with mood disorders. About 81.1% of CVD patients were reported with comorbidities in 2019, where the second most common comorbidity was due to major depressive disorder (MDD). This study, therefore, aimed to evaluate the genetic correlation between CVDs and mood disorders by using data from the UK Biobank towards understanding the influence of genetic factors on the comorbidity due to CVDs and mood disorders.

METHODS

The UK Biobank database provides genetic and health information from half a million adults, aged 40-69 years, recruited between 2006 and 2010. A total of 117,925 participants and 6,128,294 variants were included for analysis after applying exclusion criteria and quality control steps. This study focused on two CVD phenotypes, two mood disorders and 12 cardiometabolic-related traits to conduct association studies.

RESULTS

The results indicated a significant positive genetic correlation between CVDs and overall mood disorders and MDD specifically, showing substantial genetic overlap. Genetic correlation between CVDs and bipolar disorder was not significant. Furthermore, significant genetic correlation between mood disorders and cardiometabolic traits was also reported.

CONCLUSIONS

The results of this study can be used to understand that CVDs and mood disorders share a great deal of genetic liability in individuals of European ancestry.

Systolic Blood Pressure and Cardiovascular Risk in Patients With Diabetes: A Prospective Cohort Study

BACKGROUND

Whether the association between systolic blood pressure (SBP) and risk of cardiovascular disease is monotonic or whether there is a nadir of optimal blood pressure remains controversial. We investigated the association between SBP and cardiovascular events in patients with diabetes across the full spectrum of SBP.

METHODS

A cohort of 49 000 individuals with diabetes aged 50 to 90 years between 1990 and 2005 was identified from linked electronic health records in the United Kingdom. Associations between SBP and cardiovascular outcomes (ischemic heart disease, heart failure, stroke, and cardiovascular death) were analyzed using a deep learning approach.

RESULTS

Over a median follow-up of 7.3 years, 16 378 cardiovascular events were observed. The relationship between SBP and cardiovascular events followed a monotonic pattern, with the group with the lowest baseline SBP of <120 mm Hg exhibiting the lowest risk of cardiovascular events. In comparison to the reference group with the lowest SBP (<120 mm Hg), the adjusted risk ratio for cardiovascular disease was 1.03 (95% CI, 0.97-1.10) for SBP between 120 and 129 mm Hg, 1.05 (0.99-1.11) for SBP between 130 and 139 mm Hg, 1.08 (1.01-1.15) for SBP between 140 and 149 mm Hg, 1.12 (1.03-1.20) for SBP between 150 and 159 mm Hg, and 1.19 (1.09-1.28) for SBP ≥160 mm Hg.

CONCLUSIONS

Using deep learning modeling, we found a monotonic relationship between SBP and risk of cardiovascular outcomes in patients with diabetes, without evidence of a J-shaped relationship.

Liposaccharide-induced sustained mild inflammation fragments social behavior and alters basolateral amygdala activity

RATIONALE

Conditions with sustained low-grade inflammation have high comorbidity with depression and anxiety and are associated with social withdrawal. The basolateral amygdala (BLA) is critical for affective and social behaviors and is sensitive to inflammatory challenges. Large systemic doses of lipopolysaccharide (LPS) initiate peripheral inflammation, increase BLA neuronal activity, and disrupt social and affective measures in rodents. However, LPS doses commonly used in behavioral studies are high enough to evoke sickness syndrome, which can confound interpretation of amygdala-associated behaviors.

OBJECTIVES AND METHODS

The objectives of this study were to find a LPS dose that triggers mild peripheral inflammation but not observable sickness syndrome in adult male rats, to test the effects of sustained mild inflammation on BLA and social behaviors. To accomplish this, we administered single doses of LPS (0-100 μg/kg, intraperitoneally) and measured open field behavior, or repeated LPS (5 μg/kg, 3 consecutive days), and measured BLA neuronal firing, social interaction, and elevated plus maze behavior.

RESULTS

Repeated low-dose LPS decreased BLA neuron firing rate but increased the total number of active BLA neurons. Repeated low-dose LPS also caused early disengagement during social bouts and less anogenital investigation and an overall pattern of heightened social caution associated with reduced gain of social familiarity over the course of a social session.

CONCLUSIONS

These results provide evidence for parallel shifts in social interaction and amygdala activity caused by prolonged mild inflammation. This effect of inflammation may contribute to social symptoms associated with comorbid depression and chronic inflammatory conditions.

Artificial intelligence to enhance clinical value across the spectrum of cardiovascular healthcare

Artificial intelligence (AI) is increasingly being utilized in healthcare. This article provides clinicians and researchers with a step-wise foundation for high-value AI that can be applied to a variety of different data modalities. The aim is to improve the transparency and application of AI methods, with the potential to benefit patients in routine cardiovascular care. Following a clear research hypothesis, an AI-based workflow begins with data selection and pre-processing prior to analysis, with the type of data (structured, semi-structured, or unstructured) determining what type of pre-processing steps and machine-learning algorithms are required. Algorithmic and data validation should be performed to ensure the robustness of the chosen methodology, followed by an objective evaluation of performance. Seven case studies are provided to highlight the wide variety of data modalities and clinical questions that can benefit from modern AI techniques, with a focus on applying them to cardiovascular disease management. Despite the growing use of AI, further education for healthcare workers, researchers, and the public are needed to aid understanding of how AI works and to close the existing gap in knowledge. In addition, issues regarding data access, sharing, and security must be addressed to ensure full engagement by patients and the public. The application of AI within healthcare provides an opportunity for clinicians to deliver a more personalized approach to medical care by accounting for confounders, interactions, and the rising prevalence of multi-morbidity.

Hi-BEHRT: Hierarchical Transformer-Based Model for Accurate Prediction of Clinical Events Using Multimodal Longitudinal Electronic Health Records

Electronic health records (EHR) represent a holistic overview of patients' trajectories. Their increasing availability has fueled new hopes to leverage them and develop accurate risk prediction models for a wide range of diseases. Given the complex interrelationships of medical records and patient outcomes, deep learning models have shown clear merits in achieving this goal. However, a key limitation of current study remains their capacity in processing long sequences, and long sequence modelling and its application in the context of healthcare and EHR remains unexplored. Capturing the whole history of medical encounters is expected to lead to more accurate predictions, but the inclusion of records collected for decades and from multiple resources can inevitably exceed the receptive field of the most existing deep learning architectures. This can result in missing crucial, long-term dependencies. To address this gap, we present Hi-BEHRT, a hierarchical Transformer-based model that can significantly expand the receptive field of Transformers and extract associations from much longer sequences. Using a multimodal large-scale linked longitudinal EHR, the Hi-BEHRT exceeds the state-of-the-art deep learning models 1% to 5% for area under the receiver operating characteristic (AUROC) curve and 1% to 8% for area under the precision recall (AUPRC) curve on average, and 2% to 8% (AUROC) and 2% to 11% (AUPRC) for patients with long medical history for 5-year heart failure, diabetes, chronic kidney disease, and stroke risk prediction. Additionally, because pretraining for hierarchical Transformer is not well-established, we provide an effective end-to-end contrastive pre-training strategy for Hi-BEHRT using EHR, improving its transferability on predicting clinical events with relatively small training dataset.

Does educational attainment modify the causal relationship between adiposity and cardiovascular disease? A Mendelian randomization study

A greater risk of cardiovascular disease is associated with low educational attainment and high adiposity. Despite the correlation between low educational attainment and high adiposity, whether educational attainment modifies the risk of CVD caused by high adiposity remains poorly understood. We investigated the effect of adiposity (body mass index [BMI] and waist-to-hip ratio adjusted for BMI [WHRadjBMI]) on incident CVD among individuals with varying education levels, using associational and one-sample Mendelian randomization (MR) survival analyses. Data were collected from 2006 to 2021, and sample sizes were 254,281 (27,511 CVD cases) for BMI and 253,968 (27,458 CVD cases) for WHRadjBMI. In the associational model, a standard deviation (SD) higher BMI was associated with 19.81 (95% CI: 18.55-21.06) additional cases of incident CVD per 10,000 person-years for individuals with a secondary education, versus 32.96 (95% CI: 28.75-37.17) for those without. When university degree served as the education variable, education group differences attenuated, with 18.26 (95% CI: 16.37-20.15) cases from a one SD higher BMI for those with a university degree versus 23.18 [95% CI: 21.56-24.72] for those without. For the MR model, an SD higher BMI resulted in 11.75 (95% CI: -0.84-24.38) and 29.79 (95% CI: 17.20-42.44) additional cases of incident CVD per 10,000 person-years for individuals with versus without a university degree. WHRadjBMI exhibited no effect differences by education. While the associational model showed evidence of educational attainment modifying the relationship between adiposity and incident CVD, it does not modify the association between adiposity and incident CVD in the MR models. This suggests either less education does not cause greater risk of incident CVD from high adiposity, or MR models cannot detect the effect difference. The associational point estimates exist within the MR models' confidence intervals in all BMI analyses, so we cannot rule out the effect sizes in the associational models.

Phenotypic Disease Network-Based Multimorbidity Analysis in Idiopathic Cardiomyopathy Patients with Hospital Discharge Records

BACKGROUND

Idiopathic cardiomyopathy (ICM) is a rare disease affecting numerous physiological and biomolecular systems with multimorbidity. However, due to the small sample size of uncommon diseases, the whole spectrum of chronic disease co-occurrence, especially in developing nations, has not yet been investigated. To grasp the multimorbidity pattern, we aimed to present a multidimensional model for ICM and differences among age groups.

METHODS

Hospital discharge records were collected from a rare disease centre of ICM inpatients (n = 1036) over 10 years (2012 to 2021) for this retrospective analysis. One-to-one matched controls were also included. First, by looking at the first three digits of the ICD-10 code, we concentrated on chronic illnesses with a prevalence of more than 1%. The ICM and control inpatients had a total of 71 and 69 chronic illnesses, respectively. Second, to evaluate the multimorbidity pattern in both groups, we built age-specific cosine-index-based multimorbidity networks. Third, the associated rule mining (ARM) assessed the comorbidities with heart failure for ICM, specifically.

RESULTS

The comorbidity burden of ICM was 78% larger than that of the controls. All ages were affected by the burden, although those over 50 years old had more intense interactions. Moreover, in terms of disease connectivity, central, hub, and authority diseases were concentrated in the metabolic, musculoskeletal and connective tissue, genitourinary, eye and adnexa, respiratory, and digestive systems. According to the age-specific connection, the impaired coagulation function was required for raising attention (e.g., autoimmune-attacked digestive and musculoskeletal system disorders) in young adult groups (ICM patients aged 20-49 years). For the middle-aged (50-60 years) and older (≥70 years) groups, malignant neoplasm and circulatory issues were the main confrontable problems. Finally, according to the result of ARM, the comorbidities and comorbidity patterns of heart failure include diabetes mellitus and metabolic disorder, sleeping disorder, renal failure, liver, and circulatory diseases.

CONCLUSIONS

The main cause of the comorbid load is aging. The ICM comorbidities were concentrated in the circulatory, metabolic, musculoskeletal and connective tissue, genitourinary, eye and adnexa, respiratory, and digestive systems. The network-based approach optimizes the integrated care of patients with ICM and advances our understanding of multimorbidity associated with the disease.

Drug-Drug-Gene Interactions in Cardiovascular Medicine

Cardiovascular disease remains a leading cause of both morbidity and mortality worldwide. It is widely accepted that both concomitant medications (drug-drug interactions, DDIs) and genomic factors (drug-gene interactions, DGIs) can influence cardiovascular drug-related efficacy and safety outcomes. Although thousands of DDI and DGI (aka pharmacogenomic) studies have been published to date, the literature on drug-drug-gene interactions (DDGIs, cumulative effects of DDIs and DGIs) remains scarce. Moreover, multimorbidity is common in cardiovascular disease patients and is often associated with polypharmacy, which increases the likelihood of clinically relevant drug-related interactions. These, in turn, can lead to reduced drug efficacy, medication-related harm (adverse drug reactions, longer hospitalizations, mortality) and increased healthcare costs. To examine the extent to which DDGIs and other interactions influence efficacy and safety outcomes in the field of cardiovascular medicine, we review current evidence in the field. We describe the different categories of DDIs and DGIs before illustrating how these two interact to produce DDGIs and other complex interactions. We provide examples of studies that have reported the prevalence of clinically relevant interactions and the most implicated cardiovascular medicines before outlining the challenges associated with dealing with these interactions in clinical practice. Finally, we provide recommendations on how to manage the challenges including but not limited to expanding the scope of drug information compendia, interaction databases and clinical implementation guidelines (to include clinically relevant DDGIs and other complex interactions) and work towards their harmonization; better use of electronic decision support tools; using big data and novel computational techniques; using clinically relevant endpoints, preemptive genotyping; ensuring ethnic diversity; and upskilling of clinicians in pharmacogenomics and personalized medicine.

Evaluating the Feasibility and Efficacy of A Novel CBTi/SMT Treatment Protocol for Cardiac Rehab Patients: A Non-Randomized Pilot Trial

INTRODUCTION

Cardiac patients and those with chronic medical conditions often suffer from comorbidities such as insomnia and mood disorders. Previous treatment protocols have focused on resolving symptoms of anxiety and depression in this population using Stress Management Training (SMT). However, these treatments have neglected the importance of sleep problems in these patients. This pilot trial sought to address this by examining the feasibility of a novel CBTi/SMT treatment protocol.

METHODS

42 participants attending a Cardiac Rehab (CR) exercise program registered in this 7-week non-randomized pilot trial. The primary objective of the pilot trial was to determine the feasibility of the protocol for retention and adherence rates. Secondarily, the authors sought to examine the potential efficacy of the program in terms of treating insomnia, depression, anxiety, emotion dysregulation, and arousal.

RESULTS

29 participants attended at least 1 class, with 21 participants completing the program. The average attendance for the program completers was 6 out of 7 classes (SD = 0.8) with four days of practice each week (SD = 1.6) for 33 minutes daily (SD = 16.8). Moreover, the number of participants meeting clinical threshold for insomnia, anxiety, and/or depression was significantly reduced at post-treatment and follow-up. Similarly, raw scores on the relevant scales were significantly reduced at both timepoints.

CONCLUSION

This pilot trial provided preliminary evidence for the feasibility and efficacy of targeting sleep improvement with a combined CBTi/SMT protocol. This provides the groundwork for future RCTs to establish the effectiveness of targeting insomnia in a range of medical populations.

A nationwide study of multimedicine use in people treated with cardiovascular medicines in Australia

STUDY OBJECTIVE

Multimorbidity and multimedicine use are common in people with cardiovascular disease and can lead to harms, such as prescribing errors and drug interactions. We quantified multimedicine use in people treated with cardiovascular medicines in a national sample of Australians.

DESIGN

Cross-sectional study.

DATA SOURCE

Pharmaceutical dispensing claims for a 10% random sample of Australians.

PATIENTS

Australian adults dispensed any cardiovascular medicine between June and August 2019.

INTERVENTION

None.

MEASUREMENTS

We quantified the number and type of cardiovascular and non-cardiovascular medicines dispensed during the study period, and the number of unique prescribers, by age and sex.

MAIN RESULTS

We identified 493,081 people dispensed any cardiovascular medicine (median age = 67 years, 50.2% women). The population prevalence of cardiovascular medicine dispensing increased from 1.7% (n = 10,503) in people 18-34 years to 80.1% (n = 99,271) in people 75-84 years. Cardiovascular medicine dispensing varied by sex; women 18-34 years were more likely to be dispensed any cardiovascular medicine than men (male:female prevalence ratio [PR] = 0.84, 95% confidence interval [CI] = 0.81-0.87), whereas the prevalence of cardiovascular medicine dispensing was higher in men 35-44 years (PR = 1.27, 95% CI 1.24-1.30) and 45-54 years (PR = 1.24, 95% CI 1.22-1.26) and was similar between sexes in people ≥65 years. Overall, both women and men were dispensed a median of 2.0 (interquartile range [IQR] = 1.0-3.0) cardiovascular medicines. Two-thirds of people ≥65 years (73.5%; n = 208,524) were dispensed ≥2 cardiovascular medicines, with 16.6% (n = 6736) of people ≥85 years dispensed five or more. Women and men were dispensed a median of 2.0 (IQR = 1.0-5.0) and 2.0 (IQR = 0.0-4.0) non-cardiovascular medicines, respectively, to treat comorbid conditions, commonly gastroesophageal reflux disease medicines (32.2% of women and 26.6% of men), antibiotics (28.7% of women and 22.4% of men), and antidepressants (26.3% of women and 15.9% of men). One quarter of both sexes had multiple prescribers for their cardiovascular medicines alone, whereas 54.5% (n = 134,939) of women and 49.9% (n = 122,706) of men had multiple prescribers for all medicines.

CONCLUSION

Multimedicine use is common in people treated with cardiovascular medicines and presents a risk for inappropriate prescribing. Understanding the comorbid conditions commonly treated concurrently with cardiovascular disease can help improve co-prescribing guidelines and develop a person-centered approach to multimorbidity treatment.

Association of metabolic comorbidity with myocardial infarction in individuals with a family history of cardiovascular disease: a prospective cohort study

Background

The association between metabolic comorbidity and myocardial infarction (MI) among individuals with a family history of cardiovascular disease (CVD) is yet to be elucidated. We aimed to examine the combined effects of metabolic comorbidities, including diabetes mellitus, hypertension, and dyslipidemia, with a family history of CVD in first-degree on the risk of incident MI.

Methods

This cohort study consisted of 81,803 participants aged 40–89 years without a previous history of MI at baseline from the Korean Genome and Epidemiology Study. We performed Cox proportional hazard regression analysis to estimate the hazard ratios (HRs) and 95% confidence intervals (CIs) for MI and early-onset MI risk associated with metabolic comorbidity in individuals with a family history of CVD.

Results

During a median follow-up of 5 years, 1,075 and 479 cases of total and early-onset MI were reported, respectively. According to the disease score, among individuals who had a positive family history of CVD, the HRs for MI were 1.92 (95% CI: 1.47–2.51) in individuals with one disease, 2.75 (95% CI: 2.09–3.61) in those with two diseases, and 3.74 (95% CI: 2.45–5.71) in those with three diseases at baseline compared to individuals without a family history of CVD and metabolic diseases. Similarly, an increase of the disease score among individuals with a positive family history of CVD was associated with an increase in early-onset MI risk.

Conclusion

Metabolic comorbidity was significantly associated with an increased risk of MI among individuals with a family history of CVD.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12889-022-14330-2.

Patterns of multimorbidity in community health centres in Shanghai, China: a retrospective, cross-sectional study based on outpatient data from 2014 to 2018

OBJECTIVE

Caring for patients with multimorbidity is an important part of primary care. It has become increasingly relevant that understanding the spectrum of multimorbidity will help general practitioners (GPs) acquire working knowledge and improve management skills. However, there was little research on characteristics of multimorbidity in primary care in China. This study aimed to identify the spectrum of frequency, proportion and ranking of multimorbidity patterns in adult patients seen at community health centres (CHCs) in Shanghai, China.

DESIGN AND SETTING

This was an observational, retrospective, cross-sectional study analysis of outpatient data of 244 CHCs in Shanghai, China.

PARTICIPANTS

Adult patients with chronic disease who visited Shanghai CHCs during 2014-2018 were selected from Shanghai CHC electronic medical records database using the International Classification of Diseases 10th Revision codes matched to the Second Version of International Classification of Primary Care codes.

PRIMARY AND SECONDARY OUTCOME MEASURES

A number of adult patients with chronic disease were counted. Then frequency, proportion and rank of disease patterns of multimorbidity were analysed.

RESULTS

Analysis of 301 651 158 electronic health records of 5 909 280 adult patients (54.2% females) found the multimorbidity proportion to be 81.2%. The prevalence of multimorbidity increased with age, which climbed from 43.7% among those aged 19-34 to 94.9% among those more than 80 years of age. The proportion of multimorbidity was higher in females (83.2%) than males (79.7%). Vascular and metabolic diseases were the most frequent diseases for patients over 45 years old.

CONCLUSIONS

Multimorbidity has brought huge challenges to primary care practice in Shanghai. The Shanghai government should strengthen its support for the multitargeted prevention of chronic diseases and the improvement of GPs' management capabilities.

A Narrative Review of the Association Between Depression and Heart Disease Among Women: Prevalence, Mechanisms of Action, and Treatment

PURPOSE OF REVIEW

Sex and gender differences exist with regard to the association between depression and cardiovascular disease (CVD). This narrative review describes the prevalence, mechanisms of action, and management of depression and CVD among women, with a particular focus on coronary heart disease (CHD).

RECENT FINDINGS

Women versus men with incident and established CHD have a greater prevalence of depression. Comorbid depression and CHD in women may be associated with greater mortality, and treatment inertia. Proposed mechanisms unique to the association among women of depression and CHD include psychosocial, cardiometabolic, behavioral, inflammatory, hormonal, and autonomic factors. The literature supports a stronger association between CHD and the prevalence of depression in women compared to men. It remains unclear whether depression treatment influences cardiovascular outcomes, or if treatment effects differ by sex and/or gender. Further research is needed to establish underlying mechanisms as diagnostic and therapeutic targets.

Ejection Fraction Improvement Following Contemporary High-Risk Percutaneous Coronary Intervention: RESTORE EF Study Results

Background

Despite many reports of clinical outcomes in patients undergoing high-risk percutaneous coronary intervention (HRPCI) with hemodynamic support, little is known about whether this approach improves left ventricular ejection fraction (LVEF). The purpose of the present observational study was to examine, in an ideal patient population with Impella-supported HRPCI, whether there is an impact on left ventricular function at midterm follow-up.

Methods

RESTORE EF is a multicenter, retrospective analysis of a prospectively collected observational data set that aimed to assess 90-day LVEF in patients undergoing Impella-supported nonemergent HRPCI (NCT04648306), who survived with no intervening cardiac procedures prior to the primary endpoint follow-up window (90-day LVEF assessment). Secondary endpoints included change in New York Heart Association Functional Classification and Canadian Cardiovascular Society Angina Grade at the last follow-up.

Results

From August 2019 to May 2021, 406 patients were enrolled at 22 US sites. Age was 70.2 ​​± ​​11.4 ​​years; 26% were female. In paired assessment at 90-day follow-up, baseline LVEF improved from 35 ​​± ​​15% to 45 ​​± ​​14% (N = 251, P < .0001), with significantly greater improvement in patients with residual SYNTAX score I of 0. Percentage classified as New York Heart Association class III/IV decreased from 62% at baseline to 15% at last follow-up (P < .001), and percentage with Canadian Cardiovascular Society grade III/IV symptoms decreased from 72% to 2% (P < .0001).

Conclusions

In an ideal cohort of HRPCI patients, there is a signal that hemodynamically supported HRPCI affords significant improvement in 90-day LVEF, with complete revascularization associated with greater LVEF improvement. These hypothesis-generating findings merit further assessment in large, all-comer studies and randomized trials.

Multimorbidity as assessed by reporting of multiple causes of death: variations by period, sociodemographic characteristics and place of death among older decedents in England and Wales, 2001-2017

BACKGROUND

Multimorbidity is common at older ages and is associated with disability, frailty and poor quality of life. Research using clinical databases and surveys has shown associations between multimorbidity and indicators of social disadvantage. Use of multiple coded death registration data has been proposed as an additional source which may also provide insights into quality of death certification.

METHODS

We investigate trends in reporting multiple causes of death during 2001-2017 among decedents aged 65 years and over included in a census-based sample of 1% of the England and Wales population (Office for National Statistics Longitudinal Study). Using Poisson regression analysis, we analyse variations in number of mentions of causes of death recorded by time period, place of death, age, sex and marital status at death and indicators of health status and individual and area socioeconomic disadvantage reported at the census prior to death.

RESULTS

Number of mentions of causes recorded at death registration increased 2001-2017, increased with age, peaking among decedents aged 85-9 years, and was positively associated with indicators of prior disadvantage and poor health, although effects were small. Number of mentions was highest for hospital decedents and similar for those dying in care homes or their own homes.

CONCLUSION

Socioeconomic disadvantage, prior poor health, dying in hospital and older age-although not extreme old age-are associated with dying with more recorded conditions. Results may reflect both differences in multimorbidity at death and variations in quality of medical certification of death. Quality of death certification for decedents in care homes needs further investigation.

Multimorbidity Burden and Incident Heart Failure Among People With and Without HIV: The HIV-HEART Study

Objective

To examine the association between multimorbidity burden and incident heart failure (HF) among people with HIV (PWH) and people without HIV (PWoH).

Patients and Methods

The HIV-HEART study is a retrospective cohort study that included adult PWH and PWoH aged 21 years or older at Kaiser Permanente between 2000 and 2016. Multimorbidity burden was defined by the baseline prevalence of 22 chronic conditions and was categorized as 0-1, 2-3, and 4 or more comorbidities on the basis of distribution of the overall population. People with HIV and PWoH were followed for a first HF event, all-cause death, or up to the end of follow-up on December 31, 2016. Using Cox proportional hazard regression, hazard ratios and 95% CIs were calculated to examine the association between multimorbidity burden and incident HF among PWH and PWoH, separately.

Results

The prevalences of 0-1, 2-3, and 4 or more comorbidities were 83.3%, 13.0%, and 3.7% in PWH (n=38,868), and 82.2%, 14.3%, and 3.5% in PWoH (n=386,586), respectively. After multivariable adjustment, compared with people with 0-1 comorbidities, the hazard ratios of incident HF associated with 2-3 and 4 or more comorbidities were 1.33 (95% CI, 1.04-1.71) and 2.41 (95% CI, 1.78-3.25) in PWH and 2.10 (95% CI, 1.92-2.29) and 4.09 (95% CI, 3.64-4.61) in PWoH, respectively.

Conclusion

Multimorbidity was associated with a higher risk of incident HF among PWH and PWoH, with more prominent associations in PWoH and certain patient subgroups. The identification of specific multimorbidity patterns that contribute to higher HF risk in PWH may lead to future preventative strategies.

Temporal patterns of multi-morbidity in 570157 ischemic heart disease patients: a nationwide cohort study

Background

Patients diagnosed with ischemic heart disease (IHD) are becoming increasingly multi-morbid, and studies designed to analyze the full spectrum are few.

Methods

Disease trajectories, defined as time-ordered series of diagnoses, were used to study the temporality of multi-morbidity. The main data source was The Danish National Patient Register (NPR) comprising 7,179,538 individuals in the period 1994–2018. Patients with a diagnosis code for IHD were included. Relative risks were used to quantify the strength of the association between diagnostic co-occurrences comprised of two diagnoses that were overrepresented in the same patients. Multiple linear regression models were then fitted to test for temporal associations among the diagnostic co-occurrences, termed length two disease trajectories. Length two disease trajectories were then used as basis for constructing disease trajectories of three diagnoses.

Results

In a cohort of 570,157 IHD disease patients, we identified 1447 length two disease trajectories and 4729 significant length three disease trajectories. These included 459 distinct diagnoses. Disease trajectories were dominated by chronic diseases and not by common, acute diseases such as pneumonia. The temporal association of atrial fibrillation (AF) and IHD differed in different IHD subpopulations. We found an association between osteoarthritis (OA) and heart failure (HF) among patients diagnosed with OA, IHD, and then HF only.

Conclusions

The sequence of diagnoses is important in characterization of multi-morbidity in IHD patients as the disease trajectories. The study provides evidence that the timing of AF in IHD marks distinct IHD subpopulations; and secondly that the association between osteoarthritis and heart failure is dependent on IHD.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12933-022-01527-3.

Socioeconomic and health factors related to polypharmacy and medication management: analysis of a Household Health Survey in North West Coast England

OBJECTIVES

To examine the socioeconomic and demographic drivers associated with polypharmacy (5-9 medicines), extreme polypharmacy (9-20 medicines) and increased medication count.

DESIGN, SETTING AND PARTICIPANTS

A total of 5509 participants, from two waves of the English North West Coast, Household Health Survey were analysed OUTCOME MEASURES: Logistic regression modelling was used to find associations with polypharmacy and extreme polypharmacy. A negative binomial regression identified associations with increased medication count. Descriptive statistics explored associations with medication management.

RESULTS

Age and number of health conditions account for the greatest odds of polypharmacy. ORs (95% CI) were greatest for those aged 65+ (3.87, 2.45 to 6.13) and for those with ≥5 health conditions (10.87, 5.94 to 19.88). Smaller odds were seen, for example, in those prescribed cardiovascular medications (3.08, 2.36 to 4.03), or reporting >3 emergency attendances (1.97, 1.23 to 3.17). Extreme polypharmacy was associated with living in a deprived neighbourhood (1.54, 1.06 to 2.26). The greatest risk of increased medication count was associated with age, number of health conditions and use of primary care services. Relative risks (95% CI) were greatest for those aged 65+ (2.51, 2.23 to 2.82), those with ≥5 conditions (10.26, 8.86 to 11.88) or those reporting >18 primary care visits (2.53, 2.18 to 2.93). Smaller risks were seen in, for example, respondents with higher levels of income deprivation (1.35, 1.03 to 1.77). Polypharmic respondents were more likely to report medication management difficulties associated with taking more than one medicine at a time (p<0.001). Furthermore, individuals reporting a mental health condition, were significantly more likely to consistently report difficulties managing their medication (p<0.001).

CONCLUSION

Age and number of health conditions are most associated with polypharmacy. Thus, delaying or preventing the onset of long-term conditions may help to reduce polypharmacy. Interventions to reduce income inequalities and health inequalities generally could support a reduction in polypharmacy, however, more research is needed in this area. Furthermore, increased prevention and support, particularly with medication management, for those with mental health conditions may reduce adverse medication effects.

An Intelligent and Reliable Hyperparameter Optimization Machine Learning Model for Early Heart Disease Assessment Using Imperative Risk Attributes

Heart disease is a severe disorder, which inflicts an adverse burden on all societies and leads to prolonged suffering and disability. We developed a risk evaluation model based on visible low-cost significant noninvasive attributes using hyperparameter optimization of machine learning techniques. The multiple set of risk attributes is selected and ranked by the recursive feature elimination technique. The assigned rank and value to each attribute are validated and approved by the choice of medical domain experts. The enhancements of applying specific optimized techniques like decision tree, k-nearest neighbor, random forest, and support vector machine to the risk attributes are tested. Experimental results show that the optimized random forest risk model outperforms other models with the highest sensitivity, specificity, precision, accuracy, AUROC score, and minimum misclassification rate. We simulate the results with the prevailing research; they show that it can do better than the existing risk assessment models with exceptional predictive accuracy. The model is applicable in rural areas where people lack an adequate supply of primary healthcare services and encounter barriers to benefit from integrated elementary healthcare advances for initial prediction. Although this research develops a low-cost risk evaluation model, additional research is needed to understand newly identified discoveries about the disease.

Changes in the prevalence of comorbidity of mental and physical disorders in Singapore between 2010 and 2016

INTRODUCTION

Few studies have examined the changes in the prevalence of comorbidity of mental and physical disorders in recent years. The present study sought to examine whether the prevalence of comorbidity of mental and physical disorders in Singapore showed any changes between 2010 and 2016.

METHODS

We extracted data from two repeated nationally representative cross-sectional surveys conducted among resident adults aged ≥ 18 years in Singapore. Significant changes were tested using pooled multinomial logistic regression analyses.

RESULTS

The prevalence of comorbid mental and physical disorders increased significantly from 5.8% in 2010 to 6.7% in 2016. Among those with physical disorders, there were significant increases over time in the prevalence of comorbid generalised anxiety disorder (GAD) (0.1% vs. 0.4%) and obsessive-compulsive disorder (OCD) (1.4% vs. 3.9%) in diabetes mellitus, and alcohol dependence in cardiovascular disorders (0.1% vs. 1.3%). Among those with mental disorders, there were significant increases over time in the prevalence of comorbid diabetes mellitus in OCD (4.1% vs. 10.9%), cancer in major depressive disorder (0.4% vs. 2.4%), and cardiovascular disorders in GAD (0.4% vs. 6.7%) and alcohol dependence (0.9% vs. 11.8%). Significant changes in the overall prevalence of comorbid mental and physical disorders were also observed across age group, education and employment status.

CONCLUSION

The prevalence of comorbid mental and physical disorders increased significantly over time. This finding supports the need for more appropriate clinical management with better integration between mental health and general medical care professionals across all aspects of the healthcare system to treat this comorbidity in Singapore.

Theoretical explanations for socioeconomic inequalities in multimorbidity: a scoping review

OBJECTIVE

To document socioepidemiological theories used to explain the relationship between socioeconomic disadvantage and multimorbidity.

DESIGN

Scoping review.

METHODS

A search strategy was developed and then applied to multiple electronic databases including Medline, Embase, PsychInfo, Web of Science, Scielo, Applied Social Sciences, ERIC, Humanities Index and Sociological Abstracts. After the selection of studies, data were extracted using a data charting plan. The last search was performed on the 28 September 2021. Extracted data included: study design, country, population subgroups, measures of socioeconomic inequality, assessment of multimorbidity and conclusion on the association between socioeconomic variables and multimorbidity. Included studies were further assessed on their use of theory, type of theories used and context of application. Finally, we conducted a meta-narrative synthesis to summarise the results.

RESULTS

A total of 64 studies were included in the review. Of these, 33 papers included theories as explanations for the association between socioeconomic position and multimorbidity. Within this group, 16 explicitly stated those theories and five tested at least one theory. Behavioural theories (health behaviours) were the most frequently used, followed by materialist (access to health resources) and psychosocial (stress pathways) theories. Most studies used theories as post hoc explanations for their findings or for study rationale. Supportive evidence was found for the role of material, behavioural and life course theories in explaining the relationship between social inequalities and multimorbidity.

CONCLUSION

Given the widely reported social inequalities in multimorbidity and its increasing public health burden, there is a critical gap in evidence on pathways from socioeconomic disadvantage to multimorbidity. Generating evidence of these pathways will guide the development of intervention and public policies to prevent multimorbidity among people living in social disadvantage. Material, behavioural and life course pathways can be targeted to reduce the negative effect of low socioeconomic position on multimorbidity.

Consultation rates in people with type 2 diabetes with and without vascular complications: a retrospective analysis of 141,328 adults in England

OBJECTIVE

To assess trends in primary and specialist care consultation rates and average length of consultation by cardiovascular disease (CVD), type 2 diabetes mellitus (T2DM), or cardiometabolic multimorbidity exposure status.

METHODS

Observational, retrospective cohort study used linked Clinical Practice Research Datalink primary care data from 01/01/2000 to 31/12/2018 to assess consultation rates in 141,328 adults with newly diagnosed T2DM, with or without CVD. Patients who entered the study with either a diagnosis of T2DM or CVD and later developed the second condition during the study are classified as the cardiometabolic multimorbidity group. Face to face primary and specialist care consultations, with either a nurse or general practitioner, were assessed over time in subjects with T2DM, CVD, or cardiometabolic multimorbidity. Changes in the average length of consultation in each group were investigated.

RESULTS

696,255 (mean 4.9 years [95% CI, 2.02-7.66]) person years of follow up time, there were 10,221,798 primary and specialist care consultations. The crude rate of primary and specialist care consultations in patients with cardiometabolic multimorbidity (N = 11,881) was 18.5 (95% CI, 18.47-18.55) per person years, 13.5 (13.50, 13.52) in patients with T2DM only (N = 83,094) and 13.2 (13.18, 13.21) in those with CVD (N = 57,974). Patients with cardiometabolic multimorbidity had 28% (IRR 1.28; 95% CI: 1.27, 1.31) more consultations than those with only T2DM. Patients with cardiometabolic multimorbidity had primary care consultation rates decrease by 50.1% compared to a 45.0% decrease in consultations for those with T2DM from 2000 to 2018. Specialist care consultation rates in both groups increased from 2003 to 2018 by 33.3% and 54.4% in patients with cardiometabolic multimorbidity and T2DM, respectively. For patients with T2DM the average consultation duration increased by 36.0%, in patients with CVD it increased by 74.3%, and in those with cardiometabolic multimorbidity it increased by 37.3%.

CONCLUSIONS

Annual primary care consultation rates for individuals with T2DM, CVD, or cardiometabolic multimorbidity have fallen since 2000, while specialist care consultations and average consultation length have both increased. Individuals with cardiometabolic multimorbidity have significantly more consultations than individuals with T2DM or CVD alone. Service redesign of health care delivery needs to be considered for people with cardiometabolic multimorbidity to reduce the burden and health care costs.

Phenotypic Disease Network Analysis to Identify Comorbidity Patterns in Hospitalized Patients with Ischemic Heart Disease Using Large-Scale Administrative Data

Ischemic heart disease (IHD) exhibits elevated comorbidity. However, few studies have systematically analyzed the comorbid status of IHD patients with respect to the entire spectrum of chronic diseases. This study applied network analysis to provide a complete picture of physical and mental comorbidities in hospitalized patients with IHD using large-scale administrative data. Hospital discharge records from a provincial healthcare database of IHD inpatients (n = 1,035,338) and one-to-one matched controls were included in this retrospective analysis. We constructed the phenotypic disease networks in IHD and control patients and further assessed differences in comorbidity patterns. The community detection method was applied to cluster diagnoses within the comorbidity network. Age- and sex-specific patterns of IHD comorbidities were also analyzed. IHD inpatients showed 50% larger comorbid burden when compared to controls. The IHD comorbidity network consisted of 1941 significant associations between 71 chronic conditions. Notably, the more densely connected comorbidities in IHD patients were not within the highly prevalent ones but the rarely prevalent ones. Two highly interlinked communities were detected in the IHD comorbidity network, where one included hypertension with heart and multi-organ failures, and another included cerebrovascular diseases, cerebrovascular risk factors and anxiety. Males exhibited higher comorbid burden than females, and thus more complex comorbidity relationships were found in males. Sex-specific disease pairs were detected, e.g., 106 and 30 disease pairs separately dominated in males and females. Aging accounts for the majority of comorbid burden, and the complexity of the comorbidity network increased with age. The network-based approach improves our understanding of IHD-related comorbidities and enhances the integrated management of patients with IHD.

Caregiving stress and burden associated with cardiometabolic risk in family caregivers of individuals with cancer

Chronic stress is a well-established risk factor for cardiometabolic disease. Caregiving for individuals with cancer is perceived as a chronic stressor yet research on the risk for cardiometabolic disease in this population, opposed to the elderly and those with Alzheimer's disease, is limited. Additionally, few studies have explored the early physiological changes that occur in family caregivers suggesting an elevated risk for illness. This cross-sectional study was designed to examine levels of cardiometabolic risk biomarkers and their correlates in caregivers of patients with colorectal cancer. Caregivers completed questionnaires that measure exposures to stress and vulnerability factors, psychological distress, and health habits as potential correlates. Traditional lipid and nontraditional lipoprotein particle biomarkers (e.g. concentration and size for all lipoprotein classes) were assayed from blood serum. Caregivers (N = 83, mean age = 49.8, 73% female) displayed levels of cardiometabolic biomarkers that suggest an elevated risk for cardiometabolic disease. Caregivers who were Hispanic, married, highly educated, employed, reported more hours spent caregiving daily, experienced higher caregiver burden associated with the lack of family support and impact on schedule, and psychological distress, demonstrated an elevated risk for cardiometabolic disease; primarily determined by nontraditional lipid biomarkers - large TRL-P, LDL-P, small HDL-P, large HDL-P, TRL-Z, LDL-Z and HDL-Z. These findings suggest that traditional lipid biomarkers may not be robust enough to detect early physiological changes associated with cardiometabolic disease risk in family caregivers. Moreover, findings reiterate the importance of assessing caregiver burden and providing evidence-based interventions to manage caregiving stress with the potential to improve caregivers' cardiometabolic health.

Temporal trends in anxiety and depression prevalence and their association with adverse outcomes in patients hospitalized for acute exacerbations of chronic obstructive pulmonary disease in Beijing, China, from 2004 to 2020

AIMS

To investigate the temporal trend in anxiety and/or depression prevalence in patients hospitalized for acute exacerbation of chronic obstructive pulmonary disease (AECOPD) in Beijing and their association with adverse outcomes.

MATERIALS AND METHODS

Hospital admission records from 2004 to 2020 with a primary discharge diagnosis of AECOPD were retrieved from Beijing Public Health Information Centre database. The anxiety and depression were identified from discharge diagnoses of each record. Joinpoint regression was used to analyze the temporal trend and calculate the annual percentage change (APC) for the prevalence of anxiety and/or depression. Generalized linear model was used to analyze the associations between anxiety and/or depression and patients' adverse outcomes.

RESULTS

A total of 382,125 records were included, most of which were male (66.0%) and aged ≥ 75 years (59.7%). Three segments in the temporal trend were observed, with a mild increase during 2004-2009 (APC: 5.9%, 95% CI: -14.9 to 31.7%), followed by a sharply increase during 2009-2012 (APC: 60.4%, 95% CI: 10.6 to 132.7%), then stabilized at about 3% during 2012-2020 (APC: 1.9%, 95% CI: -0.4 to 4.3%). On average, anxiety, and/or depression was more prevalent in females, the aged and those admitted in secondary hospitals (all P < 0.001). Patients with anxiety and/or depression had lower in-hospital mortality (IHM) (OR = 0.74, 95% CI: 0.63-0.88), but longer hospital stay (OR = 1.10, 95% CI: 1.07-1.13), more medical costs (OR = 1.12, 95% CI: 1.08-1.17) and higher risks of readmission for AECOPD at 30-, 90-, 180-day, and 1-year (ORs ranged from 1.22 to 1.51).

CONCLUSION

The prevalence of anxiety and/or depression in patients hospitalized for AECOPD in Beijing stabilized at approximately 3% after 2012. Anxiety and/or depression is associated with a heavier burden on patients, health care, and medical insurance systems. Appropriate diagnosis and effective treatment of anxiety and depression is crucial for patients with AECOPD.

Real-World Effectiveness of Beta-Blockers versus Other Antihypertensives in Reducing All-Cause Mortality and Cardiovascular Events

AIM

The aim of the study was to compare the effectiveness of beta-blockers with other antihypertensive classes in reducing all-cause mortality, cardiovascular-related mortality and the risk of cerebrocardiovascular events.

METHODS

This noninterventional study was conducted within the UK Clinical Practice Research Datalink. Hypertensive patients who initiated antihypertensive monotherapy were allocated to one of five cohorts: beta-blockers; angiotensin-converting enzyme inhibitors (ACEi); angiotensin II receptor blockers (ARB); calcium channel blockers (CCB); and diuretics. Differences in outcomes were assessed using Cox proportional hazard models with competing risks.

RESULTS

A total of 44,404 patients were prescribed beta-blockers (75% atenolol), 132,545 ACEi, 12,018 ARB, 91,731 CCB, and 106,547 diuretics. At baseline, patients in the beta-blocker cohort presented more frequently with angina, arrhythmia, and atrial fibrillation. The risk of all-cause mortality was lower for those treated with ACEi, ARB, and CCB, and no difference was observed compared with diuretics (adjusted hazard ratio versus beta-blockers (98.75% CI), for ACEi 0.71 (0.61, 0.83), ARB 0.67 (0.51, 0.88), CCB 0.76 (0.66, 0.88), diuretics 1.06 (0.93, 1.22)). No differences were seen in the risk of cardiovascular mortality for patients treated with beta-blockers, ARB, CCB, and diuretics, while a lower risk in patients treated with ACEi was observed (ACEi 0.63 (0.43, 0.91), ARB 0.64 (0.32, 1.28), CCB 0.71 (0.49, 1.03), diuretics 0.97 (0.69, 1.37)).

CONCLUSIONS

These data add to the limited pool of evidence from real-world studies exploring the effectiveness of beta-blockers versus other antihypertensive classes. Discrepancies to previously published studies might be partly explained by differences in the selected populations and in the follow-up time.

Association between multimorbidity and mortality in a cohort of patients admitted to hospital with COVID-19 in Scotland

OBJECTIVES

We investigated the association between multimorbidity among patients hospitalised with COVID-19 and their subsequent risk of mortality. We also explored the interaction between the presence of multimorbidity and the requirement for an individual to shield due to the presence of specific conditions and its association with mortality.

DESIGN

We created a cohort of patients hospitalised in Scotland due to COVID-19 during the first wave (between 28 February 2020 and 22 September 2020) of the pandemic. We identified the level of multimorbidity for the patient on admission and used logistic regression to analyse the association between multimorbidity and risk of mortality among patients hospitalised with COVID-19.

SETTING

Scotland, UK.

PARTICIPANTS

Patients hospitalised due to COVID-19.

MAIN OUTCOME MEASURES

Mortality as recorded on National Records of Scotland death certificate and being coded for COVID-19 on the death certificate or death within 28 days of a positive COVID-19 test.

RESULTS

Almost 58% of patients admitted to the hospital due to COVID-19 had multimorbidity. Adjusting for confounding factors of age, sex, social class and presence in the shielding group, multimorbidity was significantly associated with mortality (adjusted odds ratio 1.48, 95%CI 1.26-1.75). The presence of multimorbidity and presence in the shielding patients list were independently associated with mortality but there was no multiplicative effect of having both (adjusted odds ratio 0.91, 95%CI 0.64-1.29).

CONCLUSIONS

Multimorbidity is an independent risk factor of mortality among individuals who were hospitalised due to COVID-19. Individuals with multimorbidity could be prioritised when making preventive policies, for example, by expanding shielding advice to this group and prioritising them for vaccination.

Evaluation of the impact of high-tone therapy on cognitive disorders and quality of life in the complex treatment of patients with comorbid pathology

Introduction. Comorbidity is an independent risk factor for mortality and significantly influences the prognosis and quality of life. Purpose: to evaluate the impact of high-tone HiTOP 4 touch therapy on cognitive disorders and quality of life in the complex treatment of patients with comorbid pathology. Methods: complex treatment of 2 groups of patients with inclusion in the basic treatment regimen of high-tone therapy was carried out - a total of 80 patients (men - 34, women - 46) aged 41 to 79 years old, group I - patients with hypertension and chronic cerebral ischemia (CСI) - 38 patients and group II - patients with hypertension, CСI and concomitant diabetes mellitus (DM) type 2 - 42 patients. The average age in group I was 61.5, in group II - 65.5. Group I received lisinopril and amlodipine in one tablet, group II received metformin in addition to the above therapy. Both groups received a course of 10 sessions of high-tone therapy using the device HiTOP 4 touch (Germany) according to the general method: 2 electrodes on the feet, 2 on the forearms and one on the neck-collar area. All the patients were assessed for their cognitive condition, degree of anxiety and depression, and estimated for quality of life before and after a course of high-tone therapy. In order to do this, we used valid assessment tests, such as the Montreal Cognitive Assessment Scale (MoCA), the Hospital Anxiety and Depression Scale (HADS), and the SF-36 Quality of Life Questionnaire. Results: the course of high-tone therapy for patients with hypertension and CCI led to improved quality of life, on all indicators of the SF-36 scale, except for pain intensity, increased cognitive functions by 3.52 points on the MoCA scale, reduced anxiety by 2.06 points and depression by 1.92 points on the HADS scale. The course of high-tone therapy for patients with CCI, hypertension and type 2 DM resulted in a significant improvement of 5 out of 8 quality of life indicators on the SF-36 scale, cognitive functions by 2.27 points on the MoCA scale and reduced anxiety by 4.3 points, and depression by 0.53 points on the HADS scale. Conclusion: the inclusion of high-tone therapy in the complex treatment of patients with comorbid pathology improves cognitive functions, reduces anxiety and depression, improves quality of life. Keywords: comorbid pathology, high-tone therapy, cognitive functions, anxiety, depression, quality of life,

Depressive symptoms during early adulthood and the development of physical multimorbidity in the UK: an observational cohort study

BACKGROUND

An understanding of whether early-life depression is associated with physical multimorbidity could be instrumental for the development of preventive measures and the integrated management of depression. We therefore aimed to map out the cumulative incidence of physical multimorbidity over adulthood, and to determine the association between the presence of depressive symptoms during early adulthood and the development of physical multimorbidity in middle age.

METHODS

In this observational cohort study, we used pooled data from the 1958 National Child Development Study (NCDS) and the 1970 British Cohort Study (BCS). Cohort waves were pooled in each decade of adult life available (when cohort members were aged 26 years in the BCS and 23 years in the NCDS [baseline]; 34 years in the BCS and 33 years in the NCDS [age 34 BCS/33 NCDS]; 42 years in the BCS and NCDS [age 42 BCS/NCDS]; and 46 years in the BCS and 50 years in the NCDS [age 46 BCS/50 NCDS]). We included participants who had completed the nine-item Malaise Inventory at baseline, and did not have a history of physical multimorbidity, any physical multimorbidity at baseline, or the presence of depressive symptoms before the development of physical multimorbidity. The presence of depressive symptoms was determined using the nine-item Malaise Inventory (cutoff score ≥4). Physical multimorbidity was defined as having at least two measures of any of the following ten self-reported groups of long-term conditions: asthma or bronchitis; backache; bladder or kidney conditions; cancer; cardiovascular conditions; convulsions or epilepsy; diabetes; hearing conditions; migraine; and stomach, bowel, or gall conditions. Cumulative incidence (with 95% CI) of physical multimorbidity was calculated for each decade considered after baseline, with physical multimorbidity being assessed as both a dichotomous and categorical variable. The association between depressive symptoms and the development of physical multimorbidity was assessed using adjusted relative risk ratios (with 95% CIs).

FINDINGS

Analyses included 15 845 participants, of whom 4001 (25·25%; 95% CI 24·57-25·93) had depressive symptoms at baseline and 11 844 (74·75%; 74·07-75·42) did not. The cumulative incidence of physical multimorbidity (dichotomous) ranged over the study period from 2263 (18·44%; 95% CI 17·75-18·14) of 12 273 participants at age 34 BCS/33 NCDS, to 4496 (42·90%; 41·95-43·85) of 10 481 participants at age 46 BCS/50 NCDS, and was consistently higher in participants with depressive symptoms at baseline. The adjusted relative risk of physical multimorbidity was higher in participants with depressive symptoms than in those without and remained stable over the study period (adjusted relative rate ratio 1·67, 95% CI 1·50-1·87, at age 34 BCS/33 NCDS; 1·63, 1·48-1·79, at age 42 BCS/NCDS; and 1·58, 1·43-1·73, at age 46 BCS/50 NCDS).

INTERPRETATION

The presence of depressive symptoms during early adulthood is associated with an increased risk of the development of physical multimorbidity in middle age. Although further research about the drivers of this relationship is needed, these results could help to enhance the integrated management of individuals with depressive symptoms and the development of preventive strategies to reduce the effect and burden of physical multimorbidity.

FUNDING

UK Medical Research Council and Guy's Charity.

Association between cardiometabolic disease multimorbidity and all-cause mortality in 2 million women and men registered in UK general practices

BACKGROUND

Myocardial infarction (MI), stroke and diabetes share underlying risk factors and commonalities in clinical management. We examined if their combined impact on mortality is proportional, amplified or less than the expected risk separately of each disease and whether the excess risk is explained by their associated comorbidities.

METHODS

Using large-scale electronic health records, we identified 2,007,731 eligible patients (51% women) and registered with general practices in the UK and extracted clinical information including diagnosis of myocardial infarction (MI), stroke, diabetes and 53 other long-term conditions before 2005 (study baseline). We used Cox regression to determine the risk of all-cause mortality with age as the underlying time variable and tested for excess risk due to interaction between cardiometabolic conditions.

RESULTS

At baseline, the mean age was 51 years, and 7% (N = 145,910) have had a cardiometabolic condition. After a 7-year mean follow-up, 146,994 died. The sex-adjusted hazard ratios (HR) (95% confidence interval [CI]) of all-cause mortality by baseline disease status, compared to those without cardiometabolic disease, were MI = 1.51 (1.49-1.52), diabetes = 1.52 (1.51-1.53), stroke = 1.84 (1.82-1.86), MI and diabetes = 2.14 (2.11-2.17), MI and stroke = 2.35 (2.30-2.39), diabetes and stroke = 2.53 (2.50-2.57) and all three = 3.22 (3.15-3.30). Adjusting for other concurrent comorbidities attenuated these estimates, including the risk associated with having all three conditions (HR = 1.81 [95% CI 1.74-1.89]). Excess risks due to interaction between cardiometabolic conditions, particularly when all three conditions were present, were not significantly greater than expected from the individual disease effects.

CONCLUSION

Myocardial infarction, stroke and diabetes were associated with excess mortality, without evidence of any amplification of risk in people with all three diseases. The presence of other comorbidities substantially contributed to the excess mortality risks associated with cardiometabolic disease multimorbidity.