ABSTRACT
Cardiac abnormalities were identified early in the epidemic of AIDS, predating the isolation and characterization of the etiologic agent, HIV. Several decades later, the causation and pathogenesis of cardiovascular disease (CVD) linked to HIV infection continue to be the focus of intense speculation. Before the widespread use of antiretroviral therapy, HIV-associated CVD was primarily characterized by HIV-associated cardiomyopathy linked to profound immunodeficiency. With increasing antiretroviral therapy use, viral load suppression, and establishment of immune competency, the effects of HIV on the cardiovascular system are more subtle. Yet, people living with HIV still face an increased incidence of cardiovascular pathology. Advances in cardiac imaging modalities and immunology have deepened our understanding of the pathogenesis of HIV-associated CVD. This review provides an overview of the pathogenesis of HIV-associated CVD integrating data from imaging and immunologic studies with particular relevance to the HIV population originating from high-endemic regions, such as sub-Saharan Africa. The review highlights key evidence gaps in the field and suggests future directions for research to better understand the complex HIV-CVD interactions.
Subject(s)
Cardiovascular Diseases , HIV Infections , Humans , HIV Infections/immunology , HIV Infections/epidemiology , HIV Infections/complications , Cardiovascular Diseases/immunology , Cardiovascular Diseases/etiology , Cardiovascular Diseases/diagnostic imaging , AnimalsABSTRACT
BACKGROUND AND AIMS: Patients with kidney failure have a higher risk of cardiovascular disease compared with the general population. Whilst temporal trends of myocardial infarction and stroke are declining in the general population, these have not been evaluated in patients with kidney failure. This study aimed to describe national trends in the incidence, treatment, and outcomes of myocardial infarction and stroke in patients with kidney failure (i.e. on dialysis or with a kidney transplant) over a 20-year period, stratified by age and sex. METHODS: In this retrospective national data linkage study, all patients with kidney failure in Scotland (UK) receiving kidney replacement therapy between January 1996 and December 2016 were linked to national hospitalization, prescribing, and death records. The primary outcomes were the incidence of myocardial infarction and stroke, and subsequent cardiovascular death. Generalized additive models were constructed to estimate age-standardized, sex-stratified incidence rates and trends in cardiovascular and all-cause death. RESULTS: Amongst 16 050 patients with kidney failure [52 (SD 15) years; 41.5% women], there were 1992 [66 (SD 12) years; 34.8% women] and 996 [65 (SD 13) years; 45.1% women] incident myocardial infarctions and strokes, respectively, between January 1996 and December 2016. During this period, the age-standardized incidence of myocardial infarction per 100 000 decreased in men {from 4376 [95% confidence interval (CI) 3998-4785] to 1835 (95% CI 1692-1988)} and women [from 3268 (95% CI 2982-3593) to 1369 (95% CI 1257-1491)]. Similarly, the age-standardized incidence of stroke per 100 000 also decreased in men [from 1978 (95% CI 1795-2175) to 799 (95% CI 729-875)] and women [from 2234 (95% CI 2031-2468) to 903 (95% CI 824-990)]. Compared with the general population, the incidence of myocardial infarction was four- to eight-fold higher in patients with kidney failure, whilst for stroke it was two- to four-fold higher. The use of evidence-based cardioprotective treatment increased over the study period, and the predicted probability of cardiovascular death within 1 year of myocardial infarction for a 66-year-old patient with kidney failure (mean age of the cohort) fell in men (76.6% to 38.6%) and women (76.8% to 38.8%), and also decreased in both sexes following stroke (men, from 63.5% to 41.4%; women, from 67.6% to 45.8%). CONCLUSIONS: The incidence of myocardial infarction and stroke has halved in patients with kidney failure over the past 20 years but remains significantly higher than in the general population. Despite improvements in treatment and outcomes, the prognosis of these patients following myocardial infarction and stroke remains poor.
Subject(s)
Myocardial Infarction , Renal Insufficiency , Stroke , Male , Humans , Female , Aged , Incidence , Retrospective Studies , Renal Dialysis/adverse effects , Myocardial Infarction/epidemiology , Myocardial Infarction/therapy , Myocardial Infarction/complications , Stroke/epidemiology , Stroke/therapy , Stroke/etiology , Risk FactorsABSTRACT
BACKGROUND: Cardiac troponin concentrations are lower in women than men. We examined whether age- and risk factor-related changes in cardiac troponin over the life course differ by sex and if the trajectory of cardiac troponin was informative in respect of cardiovascular outcomes in women and men in the general population. METHODS: In the Whitehall II cohort, high-sensitivity cardiac troponin I concentrations were measured on 3 occasions over a 15-year period. Using linear mixed-effects models, the sex-specific trajectories of cardiac troponin were evaluated, and the relationship with conventional cardiovascular risk factors determined. Using multistate joint models, the association between sex-specific trajectories of cardiac troponin and a composite outcome of nonfatal myocardial infarction, nonfatal stroke, or cardiovascular death was evaluated. RESULTS: In 2142 women and 5151 men (mean, 58±7 and 57±7 years of age, respectively), there were 177 (8.3%) and 520 (10.1%) outcome events, respectively, during a median follow-up of 20.9 (25th to 75th percentile, 15.8-21.3) years. Cardiac troponin concentrations were persistently lower in women than in men (median baseline concentration: 2.4 [25th to 75th percentile, 1.7-3.6] ng/L versus 3.7 [25th to 75th percentile, 2.6-5.8] ng/L, respectively, P<0.001), with women exhibiting a relatively larger increase with advancing age as compared with men (Pinteraction<0.001). Apart from age, a significant and divergent interaction with sex was found for the association between cardiac troponin and body mass index (BMI) (Pinteraction=0.008) and diabetes (Pinteraction=0.003). During follow-up, cardiac troponin concentrations were associated to the outcome in both women and men (adjusted hazard ratio per 2-fold difference [95% CI, 1.34 (1.17-1.52) and 1.30 (1.21-1.40), respectively], Pinteraction=0.752). The slope of cardiac troponin was significantly associated with the outcome in women, but not in men (adjusted hazard ratio [95% CI, 2.70 (1.01-7.33) and 1.31 (0.62-2.75), respectively], Pinteraction=0.250). CONCLUSIONS: Trajectories of cardiac troponin differ between women and men in the general population, with differing associations to conventional risk factors and cardiovascular outcomes. Our findings highlight the importance of a sex-specific approach when serial cardiac troponin testing is applied for cardiovascular risk prediction.
Subject(s)
Life Change Events , Myocardial Infarction , Humans , Male , Female , Biomarkers , Sex Characteristics , Troponin I , Troponin TABSTRACT
In the Emergency Department, patients with suspected myocardial infarction can be risk stratified using the HEART pathway, which has recently been amended for prehospital use and modified for the incorporation of a high-sensitivity cardiac troponin test. In a prospective analysis, the performance of both HEART pathways in the prehospital setting, with a high-sensitivity cardiac troponin test using 3 different thresholds, was evaluated for major adverse cardiac events at 30 days. We found that both low-risk HEART pathways, when using the most conservative cardiac troponin thresholds, approached but did not reach accepted rule-out performance in the Emergency Department.
Subject(s)
Emergency Medical Services , Myocardial Infarction , Humans , Myocardial Infarction/diagnosis , Myocardial Infarction/blood , Emergency Medical Services/methods , Prospective Studies , Risk Assessment/methods , Male , Female , Middle Aged , Aged , Biomarkers/blood , Emergency Service, Hospital , Allied Health Personnel , Troponin/blood , Emergency Medical Technicians , ParamedicsABSTRACT
BACKGROUND: Many studies have investigated whether single cardiac biomarkers improve cardiovascular risk prediction for primary prevention but whether a combined approach could further improve risk prediction is unclear. We aimed to test a sex-specific, combined cardiac biomarker approach for cardiovascular risk prediction. METHODS: In the Generation Scotland Scottish Family Health Study, N-terminal pro-B-type natriuretic peptide (NT-proBNP), growth differentiation factor-15 (GDF-15), cardiac troponin I (cTnI), cardiac troponin T (cTnT), and C-reactive protein (CRP) were measured in stored serum using automated immunoassays. Sex-specific Cox models that included SCORE2 risk factors evaluated addition of single and combined biomarkers for prediction of major adverse cardiovascular events (MACE). Combined biomarker models were compared to a baseline model that included SCORE2 risk factors. RESULTS: The study population comprised 18 383 individuals (58.9% women, median age of 48 years [25th-75th percentile, 35-58 years]). During the median follow up of 11.6 (25th-75th percentile, 10.8-13.0) years, MACE occurred in 942 (5.1%) individuals. The greatest increase in discrimination with addition of individual biomarkers to the base model was for women GDF-15 and for men NT-proBNP (change in c-index: + 0.010 for women and +0.005 for men). For women, combined biomarker models that included GDF-15 and NT-proBNP (+0.012) or GDF-15 and cTnI (+0.013), but not CRP or cTnT, further improved discrimination. For men, combined biomarker models that included NT-proBNP and GDF-15 (+0.007), NT-proBNP and cTnI (+0.006), or NT-proBNP and CRP (+0.008), but not cTnT, further improved discrimination. CONCLUSIONS: A combined biomarker approach, particularly the use of GDF-15, NT-proBNP and cTnI, further refined cardiovascular risk estimates.
Subject(s)
Cardiovascular Diseases , Growth Differentiation Factor 15 , Male , Humans , Female , Middle Aged , Family Health , Biomarkers , Natriuretic Peptide, Brain , C-Reactive Protein/metabolism , Peptide Fragments , Troponin T , PrognosisABSTRACT
Artificial intelligence (AI) will impact many aspects of clinical pharmacology, including drug discovery and development, clinical trials, personalized medicine, pharmacogenomics, pharmacovigilance and clinical toxicology. The rapid progress of AI in healthcare means clinical pharmacologists should have an understanding of AI and its implementation in clinical practice. As with any new therapy or health technology, it is imperative that AI tools are subject to robust and stringent evaluation to ensure that they enhance clinical practice in a safe and equitable manner. This review serves as an introduction to AI for the clinical pharmacologist, highlighting current applications, aspects of model development and issues surrounding evaluation and deployment. The aim of this article is to empower clinical pharmacologists to embrace and lead on the safe and effective use of AI within healthcare.
Subject(s)
Artificial Intelligence , Pharmacology, Clinical , Humans , Machine Learning , Biomedical Technology , Drug DiscoveryABSTRACT
BACKGROUND: Tuberculosis (TB) continues to be a major cause of death across sub-Saharan Africa (SSA). In parallel, non-communicable disease and especially cardiovascular disease (CVD) burden has increased substantially in the region. Cardiac manifestations of TB are well-recognised but the extent to which they co-exist with pulmonary TB (PTB) has not been systematically evaluated. The aim of this study is to improve understanding of the burden of cardiac pathology in PTB in those living with and without HIV in a high-burden setting. METHODS: This is a cross-sectional and natural history study to evaluate the burden and natural history of cardiac pathology in participants with PTB in Lusaka, Zambia, a high burden setting for TB and HIV. Participants with PTB, with and without HIV will be consecutively recruited alongside age- and sex-matched TB-uninfected comparators on a 2:1 basis. Participants will undergo baseline assessments to collect clinical, socio-demographic, functional, laboratory and TB disease impact data followed by point-of-care and standard echocardiography. Participants with PTB will undergo further repeat clinical and functional examination at two- and six months follow-up. Those with cardiac pathology at baseline will undergo repeat echocardiography at six months. DISCUSSION: The outcomes of the study are to a) determine the burden of cardiac pathology at TB diagnosis, b) describe its association with patient-defining risk factors and biochemical markers of cardiac injury and stretch and c) describe the natural history of cardiac pathology during the course of TB treatment.
Subject(s)
HIV Infections , Tuberculosis , Humans , Zambia/epidemiology , HIV Infections/diagnosis , HIV Infections/epidemiology , HIV Infections/complications , Prevalence , Cross-Sectional Studies , Tuberculosis/complications , Tuberculosis/epidemiologyABSTRACT
BACKGROUND: Heart failure (HF) with preserved or mildly reduced ejection fraction includes a heterogenous group of patients. Reclassification into distinct phenogroups to enable targeted interventions is a priority. This study aimed to identify distinct phenogroups, and compare phenogroup characteristics and outcomes, from electronic health record data. METHODS: 2,187 patients admitted to five UK hospitals with a diagnosis of HF and a left ventricular ejection fraction ≥ 40% were identified from the NIHR Health Informatics Collaborative database. Partition-based, model-based, and density-based machine learning clustering techniques were applied. Cox Proportional Hazards and Fine-Gray competing risks models were used to compare outcomes (all-cause mortality and hospitalisation for HF) across phenogroups. RESULTS: Three phenogroups were identified: (1) Younger, predominantly female patients with high prevalence of cardiometabolic and coronary disease; (2) More frail patients, with higher rates of lung disease and atrial fibrillation; (3) Patients characterised by systemic inflammation and high rates of diabetes and renal dysfunction. Survival profiles were distinct, with an increasing risk of all-cause mortality from phenogroups 1 to 3 (p < 0.001). Phenogroup membership significantly improved survival prediction compared to conventional factors. Phenogroups were not predictive of hospitalisation for HF. CONCLUSIONS: Applying unsupervised machine learning to routinely collected electronic health record data identified phenogroups with distinct clinical characteristics and unique survival profiles.
Subject(s)
Electronic Health Records , Heart Failure , Stroke Volume , Ventricular Function, Left , Humans , Heart Failure/physiopathology , Heart Failure/diagnosis , Heart Failure/mortality , Female , Male , Aged , Middle Aged , Risk Assessment , United Kingdom/epidemiology , Risk Factors , Prognosis , Aged, 80 and over , Databases, Factual , Unsupervised Machine Learning , Hospitalization , Time Factors , Comorbidity , Cause of Death , Phenotype , Data MiningABSTRACT
BACKGROUND: Socioeconomic deprivation is associated with higher cardiovascular morbidity and mortality. Whether deprivation status should be incorporated in more cardiovascular risk estimation scores remains unclear. This study evaluates how socioeconomic deprivation status affects the performance of 3 primary prevention cardiovascular risk scores. METHODS: The Generation Scotland Scottish Family Health Study was used to evaluate the performance of 3 cardiovascular risk scores with (ASSIGN [Assessing cardiovascular risk using SIGN (Scottish Intercollegiate Guidelines Network) guidelines to ASSIGN preventive treatment]) and without (SCORE2 [Systematic Coronary Risk Evaluation 2 algorithm], Pooled Cohort Equations) socioeconomic deprivation as a covariate in the risk prediction model. Deprivation was defined by Scottish Index of Multiple Deprivation score. The predicted 10-year risk was evaluated against the observed event rate for the cardiovascular outcome of each risk score. The comparison was made across 3 groups defined by the deprivation index score consisting of group 1 defined as most deprived, group 3 defined as least deprived, and group 2, which consisted of individuals in the middle deprivation categories. RESULTS: The study population consisted of 15 506 individuals (60.0% female, median age of 51). Across the population, 1808 (12%) individuals were assigned to group 1 (most deprived), 8119 (52%) to group 2, and 4708 (30%) to group 3 (least deprived), and 871 (6%) individuals had a missing deprivation score. Risk scores based on models that did not include deprivation status significantly under predicted risk in the most deprived (6.43% observed versus 4.63% predicted for SCORE2 [P=0.001] and 6.69% observed versus 4.66% predicted for Pooled Cohort Equations [P<0.001]). Both risk scores also significantly overpredicted the risk in the least deprived group (3.97% observed versus 4.72% predicted for SCORE2 [P=0.007] and 4.22% observed versus 4.85% predicted for Pooled Cohort Equations [P=0.028]). In contrast, no significant difference was demonstrated in the observed versus predicted risk when using the ASSIGN risk score, which included socioeconomic deprivation status in the risk model. CONCLUSIONS: Socioeconomic status is a largely unrecognized risk factor in primary prevention of cardiovascular disease. Risk scores that exclude socioeconomic deprivation as a covariate under- and overestimate the risk in the most and least deprived individuals, respectively. This study highlights the importance of incorporating socioeconomic deprivation status in risk estimation systems to ultimately reduce inequalities in health care provision for cardiovascular disease.
Subject(s)
Cardiovascular Diseases , Cardiovascular Diseases/diagnosis , Cardiovascular Diseases/epidemiology , Cardiovascular Diseases/prevention & control , Cohort Studies , Female , Humans , Male , Primary Prevention , Risk Factors , Social Class , Socioeconomic FactorsABSTRACT
BACKGROUND: The 99th centile of cardiac troponin, derived from a healthy reference population, is recommended as the diagnostic threshold for myocardial infarction, but troponin concentrations are strongly influenced by age. Our aim was to assess the diagnostic performance of cardiac troponin in older patients presenting with suspected myocardial infarction. METHODS: In a secondary analysis of a multicenter trial of consecutive patients with suspected myocardial infarction, we assessed the diagnostic accuracy of high-sensitivity cardiac troponin I at presentation for the diagnosis of type 1, type 2, or type 4b myocardial infarction across 3 age groups (<50, 50-74, and ≥75 years) using guideline-recommended sex-specific and age-adjusted 99th centile thresholds. RESULTS: In 46 435 consecutive patients aged 18 to 108 years (mean, 61±17 years), 5216 (11%) had a diagnosis of myocardial infarction. In patients <50 (n=12 379), 50 to 74 (n=22 380), and ≥75 (n=11 676) years, the sensitivity of the guideline-recommended threshold was similar at 79.2% (95% CI, 75.5-82.9), 80.6% (95% CI, 79.2-82.1), and 81.6% (95% CI, 79.8-83.2), respectively. The specificity decreased with advancing age from 98.3% (95% CI, 98.1-98.5) to 95.5% (95% CI, 95.2-95.8), and 82.6% (95% CI, 81.9-83.4). The use of age-adjusted 99th centile thresholds improved the specificity (91.3% [90.8%-91.9%] versus 82.6% [95% CI, 81.9%-83.4%]) and positive predictive value (59.3% [57.0%-61.5%] versus 51.5% [49.9%-53.3%]) for myocardial infarction in patients ≥75 years but failed to prevent the decrease in either parameter with increasing age and resulted in a marked reduction in sensitivity compared with the use of the guideline-recommended threshold (55.9% [53.6%-57.9%] versus 81.6% [79.8%-83.3%]. CONCLUSIONS: Age alters the diagnostic performance of cardiac troponin, with reduced specificity and positive predictive value in older patients when applying the guideline-recommended or age-adjusted 99th centiles. Individualized diagnostic approaches rather than the adjustment of binary thresholds are needed in an aging population.
Subject(s)
Acute Coronary Syndrome , Myocardial Infarction , Acute Coronary Syndrome/diagnosis , Aged , Biomarkers , Female , Humans , Male , Myocardial Infarction/diagnosis , Risk Assessment , Troponin IABSTRACT
BACKGROUND: People with comorbidities are underrepresented in clinical trials. Empirical estimates of treatment effect modification by comorbidity are lacking, leading to uncertainty in treatment recommendations. We aimed to produce estimates of treatment effect modification by comorbidity using individual participant data (IPD). METHODS AND FINDINGS: We obtained IPD for 120 industry-sponsored phase 3/4 trials across 22 index conditions (n = 128,331). Trials had to be registered between 1990 and 2017 and have recruited ≥300 people. Included trials were multicentre and international. For each index condition, we analysed the outcome most frequently reported in the included trials. We performed a two-stage IPD meta-analysis to estimate modification of treatment effect by comorbidity. First, for each trial, we modelled the interaction between comorbidity and treatment arm adjusted for age and sex. Second, for each treatment within each index condition, we meta-analysed the comorbidity-treatment interaction terms from each trial. We estimated the effect of comorbidity measured in 3 ways: (i) the number of comorbidities (in addition to the index condition); (ii) presence or absence of the 6 commonest comorbid diseases for each index condition; and (iii) using continuous markers of underlying conditions (e.g., estimated glomerular filtration rate (eGFR)). Treatment effects were modelled on the usual scale for the type of outcome (absolute scale for numerical outcomes, relative scale for binary outcomes). Mean age in the trials ranged from 37.1 (allergic rhinitis trials) to 73.0 (dementia trials) and percentage of male participants range from 4.4% (osteoporosis trials) to 100% (benign prostatic hypertrophy trials). The percentage of participants with 3 or more comorbidities ranged from 2.3% (allergic rhinitis trials) to 57% (systemic lupus erythematosus trials). We found no evidence of modification of treatment efficacy by comorbidity, for any of the 3 measures of comorbidity. This was the case for 20 conditions for which the outcome variable was continuous (e.g., change in glycosylated haemoglobin in diabetes) and for 3 conditions in which the outcomes were discrete events (e.g., number of headaches in migraine). Although all were null, estimates of treatment effect modification were more precise in some cases (e.g., sodium-glucose co-transporter-2 (SGLT2) inhibitors for type 2 diabetes-interaction term for comorbidity count 0.004, 95% CI -0.01 to 0.02) while for others credible intervals were wide (e.g., corticosteroids for asthma-interaction term -0.22, 95% CI -1.07 to 0.54). The main limitation is that these trials were not designed or powered to assess variation in treatment effect by comorbidity, and relatively few trial participants had >3 comorbidities. CONCLUSIONS: Assessments of treatment effect modification rarely consider comorbidity. Our findings demonstrate that for trials included in this analysis, there was no empirical evidence of treatment effect modification by comorbidity. The standard assumption used in evidence syntheses is that efficacy is constant across subgroups, although this is often criticised. Our findings suggest that for modest levels of comorbidities, this assumption is reasonable. Thus, trial efficacy findings can be combined with data on natural history and competing risks to assess the likely overall benefit of treatments in the context of comorbidity.
Subject(s)
Asthma , Diabetes Mellitus, Type 2 , Rhinitis, Allergic , Humans , Male , Comorbidity , Randomized Controlled Trials as TopicABSTRACT
BACKGROUND: Health-related quality of life metrics evaluate treatments in ways that matter to patients, so are often included in randomised clinical trials (hereafter trials). Multimorbidity, where individuals have 2 or more conditions, is negatively associated with quality of life. However, whether multimorbidity predicts change over time or modifies treatment effects for quality of life is unknown. Therefore, clinicians and guideline developers are uncertain about the applicability of trial findings to people with multimorbidity. We examined whether comorbidity count (higher counts indicating greater multimorbidity) (i) is associated with quality of life at baseline; (ii) predicts change in quality of life over time; and/or (iii) modifies treatment effects on quality of life. METHODS AND FINDINGS: Included trials were registered on the United States trials registry for selected index medical conditions and drug classes, phase 2/3, 3 or 4, had ≥300 participants, a nonrestrictive upper age limit, and were available on 1 of 2 trial repositories on 21 November 2016 and 18 May 2018, respectively. Of 124 meeting these criteria, 56 trials (33,421 participants, 16 index conditions, and 23 drug classes) collected a generic quality of life outcome measure (35 EuroQol-5 dimension (EQ-5D), 31 36-item short form survey (SF-36) with 10 collecting both). Blinding and completeness of follow up were examined for each trial. Using trials where individual participant data (IPD) was available from 2 repositories, a comorbidity count was calculated from medical history and/or prescriptions data. Linear regressions were fitted for the association between comorbidity count and (i) quality of life at baseline; (ii) change in quality of life during trial follow up; and (iii) treatment effects on quality of life. These results were then combined in Bayesian linear models. Posterior samples were summarised via the mean, 2.5th and 97.5th percentiles as credible intervals (95% CI) and via the proportion with values less than 0 as the probability (PBayes) of a negative association. All results are in standardised units (obtained by dividing the EQ-5D/SF-36 estimates by published population standard deviations). Per additional comorbidity, adjusting for age and sex, across all index conditions and treatment comparisons, comorbidity count was associated with lower quality of life at baseline and with a decline in quality of life over time (EQ-5D -0.02 [95% CI -0.03 to -0.01], PBayes > 0.999). Associations were similar, but with wider 95% CIs crossing the null for SF-36-PCS and SF-36-MCS (-0.05 [-0.10 to 0.01], PBayes = 0.956 and -0.05 [-0.10 to 0.01], PBayes = 0.966, respectively). Importantly, there was no evidence of any interaction between comorbidity count and treatment efficacy for either EQ-5D or SF-36 (EQ-5D -0.0035 [95% CI -0.0153 to -0.0065], PBayes = 0.746; SF-36-MCS (-0.0111 [95% CI -0.0647 to 0.0416], PBayes = 0.70 and SF-36-PCS -0.0092 [95% CI -0.0758 to 0.0476], PBayes = 0.631. CONCLUSIONS: Treatment effects on quality of life did not differ by multimorbidity (measured via a comorbidity count) at baseline-for the medical conditions studied, types and severity of comorbidities and level of quality of life at baseline, suggesting that evidence from clinical trials is likely to be applicable to settings with (at least modestly) higher levels of comorbidity. TRIAL REGISTRATION: A prespecified protocol was registered on PROSPERO (CRD42018048202).
Subject(s)
Quality of Life , Humans , Bayes Theorem , Chronic Disease , Surveys and Questionnaires , ComorbidityABSTRACT
BACKGROUND: High-sensitivity cardiac troponin testing is a promising tool for cardiovascular risk prediction, but whether serial testing can dynamically predict risk is uncertain. We evaluated the trajectory of cardiac troponin I in the years prior to a cardiovascular event in the general population, and determine whether serial measurements could track risk within individuals. METHODS: In the Whitehall II cohort, high-sensitivity cardiac troponin I concentrations were measured on three occasions over a 15-year period. Time trajectories of troponin were constructed in those who died from cardiovascular disease compared to those who survived or died from other causes during follow up and these were externally validated in the HUNT Study. A joint model that adjusts for cardiovascular risk factors was used to estimate risk of cardiovascular death using serial troponin measurements. RESULTS: In 7,293 individuals (mean 58 ± 7 years, 29.4% women) cardiovascular and non-cardiovascular death occurred in 281 (3.9%) and 914 (12.5%) individuals (median follow-up 21.4 years), respectively. Troponin concentrations increased in those dying from cardiovascular disease with a steeper trajectory compared to those surviving or dying from other causes in Whitehall and HUNT (Pinteraction < 0.05 for both). The joint model demonstrated an independent association between temporal evolution of troponin and risk of cardiovascular death (HR per doubling, 1.45, 95% CI,1.33-1.75). CONCLUSIONS: Cardiac troponin I concentrations increased in those dying from cardiovascular disease compared to those surviving or dying from other causes over the preceding decades. Serial cardiac troponin testing in the general population has potential to track future cardiovascular risk.
Subject(s)
Cardiovascular Diseases , Humans , Female , Male , Longitudinal Studies , Cardiovascular Diseases/diagnosis , Troponin I , Biomarkers , Cohort Studies , Risk FactorsABSTRACT
INTRODUCTION: The History, Electrocardiogram (ECG), Age, Risk Factors and Troponin (HEART) score is commonly used to risk stratify patients with possible myocardial infarction as low risk or high risk in the Emergency Department (ED). Whether the HEART score can be used by paramedics to guide care were high-sensitivity cardiac troponin testing available in a prehospital setting is uncertain. METHODS: In a prespecified secondary analysis of a prospective cohort study where paramedics enrolled patients with suspected myocardial infarction, a paramedic Heart, ECG, Age, Risk Factors (HEAR) score was recorded contemporaneously, and a prehospital blood sample was obtained for subsequent cardiac troponin testing. HEART and modified HEART scores were derived using laboratory contemporary and high-sensitivity cardiac troponin I assays. HEART and modified HEART scores of ≤3 and ≥7 were applied to define low-risk and high-risk patients, and performance was evaluated for an outcome of major adverse cardiac events (MACEs) at 30 days. RESULTS: Between November 2014 and April 2018, 1054 patients were recruited, of whom 960 (mean 64 (SD 15) years, 42% women) were eligible for analysis and 255 (26%) experienced a MACE at 30 days. A HEART score of ≤3 identified 279 (29%) as low risk with a negative predictive value of 93.5% (95% CI 90.0% to 95.9%) for the contemporary assay and 91.4% (95% CI 87.5% to 94.2%) for the high-sensitivity assay. A modified HEART score of ≤3 using the limit of detection of the high-sensitivity assay identified 194 (20%) patients as low risk with a negative predictive value of 95.9% (95% CI 92.1% to 97.9%). A HEART score of ≥7 using either assay gave a lower positive predictive value than using the upper reference limit of either cardiac troponin assay alone. CONCLUSIONS: A HEART score derived by paramedics in the prehospital setting, even when modified to harness the precision of a high-sensitivity assay, does not allow safe rule-out of myocardial infarction or enhanced rule-in compared with cardiac troponin testing alone.
Subject(s)
Acute Coronary Syndrome , Myocardial Infarction , Humans , Female , Male , Prospective Studies , Acute Coronary Syndrome/diagnosis , Chest Pain/etiology , Risk Assessment , Troponin I , Emergency Service, Hospital , Electrocardiography , BiomarkersABSTRACT
BACKGROUND: High-sensitivity cardiac troponin assays enable myocardial infarction to be ruled out earlier, but the safety and efficacy of this approach is uncertain. We investigated whether an early rule-out pathway is safe and effective for patients with suspected acute coronary syndrome. METHODS: We performed a stepped-wedge cluster randomized controlled trial in the emergency departments of 7 acute care hospitals in Scotland. Consecutive patients presenting with suspected acute coronary syndrome between December 2014 and December 2016 were included. Sites were randomized to implement an early rule-out pathway where myocardial infarction was excluded if high-sensitivity cardiac troponin I concentrations were <5 ng/L at presentation. During a previous validation phase, myocardial infarction was ruled out when troponin concentrations were <99th percentile at 6 to 12 hours after symptom onset. The coprimary outcome was length of stay (efficacy) and myocardial infarction or cardiac death after discharge at 30 days (safety). Patients were followed for 1 year to evaluate safety and other secondary outcomes. RESULTS: We enrolled 31 492 patients (59±17 years of age [mean±SD]; 45% women) with troponin concentrations <99th percentile at presentation. Length of stay was reduced from 10.1±4.1 to 6.8±3.9 hours (adjusted geometric mean ratio, 0.78 [95% CI, 0.73-0.83]; P<0.001) after implementation and the proportion of patients discharged increased from 50% to 71% (adjusted odds ratio, 1.59 [95% CI, 1.45-1.75]). Noninferiority was not demonstrated for the 30-day safety outcome (upper limit of 1-sided 95% CI for adjusted risk difference, 0.70% [noninferiority margin 0.50%]; P=0.068), but the observed differences favored the early rule-out pathway (0.4% [57/14 700] versus 0.3% [56/16 792]). At 1 year, the safety outcome occurred in 2.7% (396/14 700) and 1.8% (307/16 792) of patients before and after implementation (adjusted odds ratio, 1.02 [95% CI, 0.74-1.40]; P=0.894), and there were no differences in hospital reattendance or all-cause mortality. CONCLUSIONS: Implementation of an early rule-out pathway for myocardial infarction reduced length of stay and hospital admission. Although noninferiority for the safety outcome was not demonstrated at 30 days, there was no increase in cardiac events at 1 year. Adoption of this pathway would have major benefits for patients and health care providers. Registration: URL: https://www.clinicaltrials.gov; Unique identifier: NCT03005158.
Subject(s)
Myocardial Infarction/pathology , Troponin I/blood , Adult , Aged , Biomarkers/blood , Electrocardiography , Female , Follow-Up Studies , Humans , Length of Stay , Male , Middle Aged , Myocardial Infarction/mortality , Odds Ratio , Patient Discharge , Randomized Controlled Trials as Topic , Risk Factors , Treatment OutcomeABSTRACT
BACKGROUND: There is limited evidence on the use of high-sensitivity C-reactive protein (hsCRP) as a biomarker for selecting patients for advanced cardiovascular (CV) therapies in the modern era. The prognostic value of mildly elevated hsCRP beyond troponin in a large real-world cohort of unselected patients presenting with suspected acute coronary syndrome (ACS) is unknown. We evaluated whether a mildly elevated hsCRP (up to 15 mg/L) was associated with mortality risk, beyond troponin level, in patients with suspected ACS. METHODS AND FINDINGS: We conducted a retrospective cohort study based on the National Institute for Health Research Health Informatics Collaborative data of 257,948 patients with suspected ACS who had a troponin measured at 5 cardiac centres in the United Kingdom between 2010 and 2017. Patients were divided into 4 hsCRP groups (<2, 2 to 4.9, 5 to 9.9, and 10 to 15 mg/L). The main outcome measure was mortality within 3 years of index presentation. The association between hsCRP levels and all-cause mortality was assessed using multivariable Cox regression analysis adjusted for age, sex, haemoglobin, white cell count (WCC), platelet count, creatinine, and troponin. Following the exclusion criteria, there were 102,337 patients included in the analysis (hsCRP <2 mg/L (n = 38,390), 2 to 4.9 mg/L (n = 27,397), 5 to 9.9 mg/L (n = 26,957), and 10 to 15 mg/L (n = 9,593)). On multivariable Cox regression analysis, there was a positive and graded relationship between hsCRP level and mortality at baseline, which remained at 3 years (hazard ratio (HR) (95% CI) of 1.32 (1.18 to 1.48) for those with hsCRP 2.0 to 4.9 mg/L and 1.40 (1.26 to 1.57) and 2.00 (1.75 to 2.28) for those with hsCRP 5 to 9.9 mg/L and 10 to 15 mg/L, respectively. This relationship was independent of troponin in all suspected ACS patients and was further verified in those who were confirmed to have an ACS diagnosis by clinical coding. The main limitation of our study is that we did not have data on underlying cause of death; however, the exclusion of those with abnormal WCC or hsCRP levels >15 mg/L makes it unlikely that sepsis was a major contributor. CONCLUSIONS: These multicentre, real-world data from a large cohort of patients with suspected ACS suggest that mildly elevated hsCRP (up to 15 mg/L) may be a clinically meaningful prognostic marker beyond troponin and point to its potential utility in selecting patients for novel treatments targeting inflammation. TRIAL REGISTRATION: ClinicalTrials.gov - NCT03507309.
Subject(s)
Acute Coronary Syndrome/blood , Acute Coronary Syndrome/mortality , C-Reactive Protein/metabolism , Acute Coronary Syndrome/diagnosis , Aged , Aged, 80 and over , Biomarkers/blood , Cohort Studies , Female , Follow-Up Studies , Humans , Longitudinal Studies , Male , Middle Aged , Mortality/trends , Predictive Value of Tests , Retrospective Studies , Risk Factors , United Kingdom/epidemiologyABSTRACT
The benefit and utility of high-sensitivity cardiac troponin (hs-cTn) in the diagnosis of myocardial infarction in patients with kidney impairment is unclear. Here, we describe implementation of hs-cTnI testing on the diagnosis, management, and outcomes of myocardial infarction in patients with and without kidney impairment. Consecutive patients with suspected acute coronary syndrome enrolled in a stepped-wedge, cluster-randomized controlled trial were included in this pre-specified secondary analysis. Kidney impairment was defined as an eGFR under 60mL/min/1.73m2. The index diagnosis and primary outcome of type 1 and type 4b myocardial infarction or cardiovascular death at one year were compared in patients with and without kidney impairment following implementation of hs-cTnI assay with 99th centile sex-specific diagnostic thresholds. Serum creatinine concentrations were available in 46,927 patients (mean age 61 years; 47% women), of whom 9,080 (19%) had kidney impairment. hs-cTnIs were over 99th centile in 46% and 16% of patients with and without kidney impairment. Implementation increased the diagnosis of type 1 infarction from 12.4% to 17.8%, and from 7.5% to 9.4% in patients with and without kidney impairment (both significant). Patients with kidney impairment and type 1 myocardial infarction were less likely to undergo coronary revascularization (26% versus 53%) or receive dual anti-platelets (40% versus 68%) than those without kidney impairment, and this did not change post-implementation. In patients with hs-cTnI above the 99th centile, the primary outcome occurred twice as often in those with kidney impairment compared to those without (24% versus 12%, hazard ratio 1.53, 95% confidence interval 1.31 to 1.78). Thus, hs-cTnI testing increased the identification of myocardial injury and infarction but failed to address disparities in management and outcomes between those with and without kidney impairment.
Subject(s)
Acute Coronary Syndrome , Myocardial Infarction , Renal Insufficiency , Troponin I , Biomarkers , Creatinine , Female , Humans , Kidney , Male , Middle Aged , Myocardial Infarction/blood , Myocardial Infarction/complications , Myocardial Infarction/diagnosis , Myocardial Infarction/therapy , Renal Insufficiency/blood , Renal Insufficiency/complications , Renal Insufficiency/diagnosis , Troponin I/blood , Troponin TABSTRACT
BACKGROUND: Data regarding high-sensitivity troponin concentrations in patients presenting to the emergency department with symptoms suggestive of myocardial infarction may be useful in determining the probability of myocardial infarction and subsequent 30-day outcomes. METHODS: In 15 international cohorts of patients presenting to the emergency department with symptoms suggestive of myocardial infarction, we determined the concentrations of high-sensitivity troponin I or high-sensitivity troponin T at presentation and after early or late serial sampling. The diagnostic and prognostic performance of multiple high-sensitivity troponin cutoff combinations was assessed with the use of a derivation-validation design. A risk-assessment tool that was based on these data was developed to estimate the risk of index myocardial infarction and of subsequent myocardial infarction or death at 30 days. RESULTS: Among 22,651 patients (9604 in the derivation data set and 13,047 in the validation data set), the prevalence of myocardial infarction was 15.3%. Lower high-sensitivity troponin concentrations at presentation and smaller absolute changes during serial sampling were associated with a lower likelihood of myocardial infarction and a lower short-term risk of cardiovascular events. For example, high-sensitivity troponin I concentrations of less than 6 ng per liter and an absolute change of less than 4 ng per liter after 45 to 120 minutes (early serial sampling) resulted in a negative predictive value of 99.5% for myocardial infarction, with an associated 30-day risk of subsequent myocardial infarction or death of 0.2%; a total of 56.5% of the patients would be classified as being at low risk. These findings were confirmed in an external validation data set. CONCLUSIONS: A risk-assessment tool, which we developed to integrate the high-sensitivity troponin I or troponin T concentration at emergency department presentation, its dynamic change during serial sampling, and the time between the obtaining of samples, was used to estimate the probability of myocardial infarction on emergency department presentation and 30-day outcomes. (Funded by the German Center for Cardiovascular Research [DZHK]; ClinicalTrials.gov numbers, NCT00470587, NCT02355457, NCT01852123, NCT01994577, and NCT03227159; and Australian New Zealand Clinical Trials Registry numbers, ACTRN12611001069943, ACTRN12610000766011, ACTRN12613000745741, and ACTRN12611000206921.).
Subject(s)
Myocardial Infarction/blood , Myocardial Infarction/diagnosis , Risk Assessment/methods , Troponin/blood , Adult , Aged , Biomarkers/blood , Cohort Studies , Emergency Service, Hospital , Female , Humans , Male , Middle Aged , Prognosis , Sensitivity and Specificity , Troponin I/bloodABSTRACT
BACKGROUND: The applicability of randomised controlled trials of pharmacological agents to older people with frailty/multimorbidity is often uncertain, due to concerns that trials are not representative. However, assessing trial representativeness is challenging and complex. We explore an approach assessing trial representativeness by comparing rates of trial serious adverse events (SAE) to rates of hospitalisation/death in routine care. METHODS: This was an observational analysis of individual (125 trials, n=122,069) and aggregate-level drug trial data (483 trials, n=636,267) for 21 index conditions compared to population-based routine healthcare data (routine care). Trials were identified from ClinicalTrials.gov . Routine care comparison from linked primary care and hospital data from Wales, UK (n=2.3M). Our outcome of interest was SAEs (routinely reported in trials). In routine care, SAEs were based on hospitalisations and deaths (which are SAEs by definition). We compared trial SAEs in trials to expected SAEs based on age/sex standardised routine care populations with the same index condition. Using IPD, we assessed the relationship between multimorbidity count and SAEs in both trials and routine care and assessed the impact on the observed/expected SAE ratio additionally accounting for multimorbidity. RESULTS: For 12/21 index conditions, the pooled observed/expected SAE ratio was <1, indicating fewer SAEs in trial participants than in routine care. A further 6/21 had point estimates <1 but the 95% CI included the null. The median pooled estimate of observed/expected SAE ratio was 0.60 (95% CI 0.55-0.64; COPD) and the interquartile range was 0.44 (0.34-0.55; Parkinson's disease) to 0.87 (0.58-1.29; inflammatory bowel disease). Higher multimorbidity count was associated with SAEs across all index conditions in both routine care and trials. For most trials, the observed/expected SAE ratio moved closer to 1 after additionally accounting for multimorbidity count, but it nonetheless remained below 1 for most. CONCLUSIONS: Trial participants experience fewer SAEs than expected based on age/sex/condition hospitalisation and death rates in routine care, confirming the predicted lack of representativeness. This difference is only partially explained by differences in multimorbidity. Assessing observed/expected SAE may help assess the applicability of trial findings to older populations in whom multimorbidity and frailty are common.
Subject(s)
Frailty , Humans , Aged , Chronic Disease , Delivery of Health Care , WalesABSTRACT
BACKGROUND: Empirical evidence suggests a strong link between exposure to air pollution and heart failure incidence, hospitalizations, and mortality, but the biological basis of this remains unclear. We sought to determine the relationship between differential air pollution levels and changes in cardiac structure and function in patients with dilated cardiomyopathy. METHODS AND RESULTS: We undertook a prospective longitudinal observational cohort study of patients in England with dilated cardiomyopathy (enrollment 2009-2015, nâ¯=â¯716, 66% male, 85% Caucasian) and conducted cross sectional analysis at the time of study enrollment. Annual average air pollution exposure estimates for nitrogen dioxide (NO2) and particulate matter with diameter of 2.5 µm or less (PM2.5) at enrolment were assigned to each residential postcode (on average 12 households). The relationship between air pollution and cardiac morphology was assessed using linear regression modelling. Greater ambient exposure to NO2 was associated with higher indexed left ventricular (LV) mass (4.3 g/m2 increase per interquartile range increase in NO2, 95% confidence interval 1.9-7.0 g/m2) and lower LV ejection fraction (-1.5% decrease per interquartile range increase in NO2, 95% confidence interval -2.7% to -0.2%), independent of age, sex, socioeconomic status, and clinical covariates. The associations were robust to adjustment for smoking status and geographical clustering by postcode area. The effect of air pollution on LV mass was greatest in women. These effects were specific to NO2 exposure. CONCLUSIONS: Exposure to air pollution is associated with raised LV mass and lower LV ejection fraction, with the strongest effect in women. Although epidemiological associations between air pollution and heart failure have been established and supported by preclinical studies, our findings provide novel empirical evidence of cardiac remodeling and exposure to air pollution with important clinical and public health implications.