Neutrophil Counts and Initial Presentation of 12 Cardiovascular Diseases

Shah, Anoop D; Denaxas, Spiros; Nicholas, Owen; Hingorani, Aroon D.; Hemingway, Harry

doi:10.1016/j.jacc.2016.12.022

Cited by 114 publications

(93 citation statements)

References 30 publications

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“…Inflammation could be triggered by comorbidities such as diabetes or obesity or via endothelial dysfunction and atherosclerosis from an underlying heart disease; however, it remains to be investigated how inflammation and HF interact exactly. Similar results have recently been reported for other CVDs . Additionally, we found an association of creatinine and an inverse association of haemoglobin with incident HF.…”

Section: Discussionsupporting

confidence: 91%

“…We confirmed several associations of risk factors with HF, such as diabetes, BMI, and smoking. Our study supports and contributes to previous studies in CALIBER, which have shown associations of these risk factors with a range of CVDs. We observed similar patterns of association between men and women as well as attenuation of the associations of risk factors with HF at older age.…”

Section: Discussionsupporting

confidence: 91%

“…Similar results have recently been reported for other CVDs. 24 Additionally, we found an association of creatinine and an inverse association of haemoglobin with incident HF. Low haemoglobin, or anaemia, and raised creatinine levels are frequently observed among HF .…”

Section: Risk Factors For Incident Heart Failurementioning

confidence: 55%

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Risk factors for incident heart failure in age‐ and sex‐specific strata: a population‐based cohort using linked electronic health records

Uijl

Koudstaal

Direk

et al. 2019

European J of Heart Fail

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Aims Several risk factors for incident heart failure (HF) have been previously identified, however large electronic health records (EHR) datasets may provide the opportunity to examine the consistency of risk factors across different subgroups from the general population. Methods and results We used linked EHR data from 2000 to 2010 as part of the UK‐based CALIBER resource to select a cohort of 871 687 individuals 55 years or older and free of HF at baseline. The primary endpoint was the first record of HF from primary or secondary care. Cox proportional hazards analysis was used to estimate hazard ratios for associations between risk factors and incident HF, separately for men and women and by age category: 55–64, 65–74, and > 75 years. During 5.8 years of median follow‐up, a total of 47 987 incident HF cases were recorded. Age, social deprivation, smoking, sedentary lifestyle, diabetes, atrial fibrillation, chronic obstructive pulmonary disease, body mass index, haemoglobin, total white blood cell count and creatinine were associated with HF. Smoking, atrial fibrillation and diabetes showed stronger associations with incident HF in women compared to men. Conclusion We confirmed associations of several risk factors with HF in this large population‐based cohort across age and sex subgroups. Mainly modifiable risk factors and comorbidities are strongly associated with incident HF, highlighting the importance of preventive strategies targeting such risk factors for HF.

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Section: Discussionsupporting

confidence: 91%

Section: Discussionsupporting

confidence: 91%

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Risk factors for incident heart failure in age‐ and sex‐specific strata: a population‐based cohort using linked electronic health records

Uijl

Koudstaal

Direk

et al. 2019

European J of Heart Fail

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“…This relationship continued to approach significance even when percent body fat was included in the model, indicating the relationship is not solely due to obesity. Increased white cell counts have been shown to predict arterial stiffness in adults in a variety of conditions and increased neutrophil counts predict future cardiovascular disease in adults . The increased neutrophil counts are thought to be evidence of increased endothelial inflammatory damage.…”

Section: Discussionmentioning

confidence: 99%

Increased body fat and reduced insulin sensitivity are associated with impaired endothelial function and subendocardial viability in healthy, non‐Hispanic white adolescents

et al. 2019

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Background Cardiovascular disease has its origins in adolescents. Endothelial dysfunction, arterial stiffness, and decreased endocardial oxygen supply: demand ratios are early functional markers of cardiovascular risk. The goal of this study was to determine the relationships of these markers to physical, inflammatory, and metabolic markers in healthy non‐Hispanic, white adolescents. Methods Thirty‐four of the 75 subjects were female. Mean age was 15.0 ± 1.7 years and mean body mass index (BMI) was 22.0 ± 5.8 kg/m2 (mean ± SD). Reactive hyperemia was measured using venous occlusion plethysmography. Arterial tonometry was used to measure the augmentation index (AIx75) and the Buckberg subendocardial viability ratio. Blood samples were taken to measure inflammatory and lipid markers and oral glucose tolerance test was used to assess insulin sensitivity. Results Reactive hyperemia decreased as body mass and fat mass increased. It also decreased with increasing neutrophil count. The Buckberg index was higher in males and was positively related to insulin sensitivity even when accounting for age, sex, and resting heart rate. AIx75 was not related to any of the other variables. Conclusions These results demonstrate that increased fat mass and decreased insulin sensitivity are related to poorer vascular function and cardiac risk in adolescents before the development of actual cardiovascular disease.

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“…EHR phenotypes have been developed in CALIBER for acute Ml,(15) atrial fibrillation,(25) and stable coronary disease(26). Cohort studies of their associations with blood pressure,(27) diabetes,(28) smoking,(29) socioeconomic deprivation,(30) rheumatoid arthritis,(31) alcohol consumption(32) and neutrophil counts(33) have supported their validity.…”

Section: Introductionmentioning

confidence: 99%

Bleeding in cardiac patients prescribed antithrombotic drugs: Electronic health record phenotyping algorithms, incidence, trends and prognosis

Pasea

Chung

Pujades-Rodriguez

et al. 2019

Preprint

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BackgroundClinical guidelines and public health authorities lack recommendations on scalable approaches to defining and monitoring the occurrence and severity of bleeding in populations prescribed antithrombotic therapy. We aimed to develop electronic health record algorithms for different bleeding phenotypes, and to determine the incidence, time trends and prognosis of bleeding in patients with incident cardiac disorders indicated for antiplatelet and/or vitamin K antagonist (VKA) therapy.MethodsWe examined linked primary care, hospital admission and death registry electronic health records (CALIBER 1998-2010, England) of patients with newly diagnosed atrial fibrillation, acute myocardial infarction, unstable angina or stable angina to develop algorithms for bleeding events. Kaplan-Meier plots were used to estimate the incidence of bleeding events and we used Cox regression models to assess prognosis for all-cause mortality, atherothrombotic events and further bleeding following bleeding events.ResultsWe present electronic health record phenotyping algorithms for bleeding based on bleeding diagnosis in primary or hospital care, symptoms, transfusion, surgical procedures, and haemoglobin values. In validation of the phenotype we estimated a positive predictive value of 0.88 (95% Cl: 0.64, 0.99) for hospitalised bleeding. Amongst 128,815 patients, 27259 (21.2%) had at least one bleeding event, with 5 year risks of bleeding of 29.1%, 21.9%, 25.3% and 23.4% following diagnoses of atrial fibrillation, acute myocardial infarction, unstable angina and stable angina respectively. Rates of hospitalised bleeding per 1000 patients more than doubled from 1.02 (95% Cl: 0.83, 1.22) in January 1998 to 2.68 (95% Cl: 2.49, 2.88) in December 2009 coinciding with increased rates of antiplatelet and VKA prescribing. Patients with hospitalised bleeding and primary care bleeding, with or without markers of severity, were at increased risk of all-cause mortality and atherothrombotic events compared to those with no bleeding. For example the hazard ratio for all-cause mortality was 1.98 (95% Cl: 1.86, 2.11) for primary care bleeding with markers of severity, and 1.99 (95% Cl: 1.92, 2.05) for hospitalised bleeding without markers of severity, compared to patients with no bleeding.ConclusionsElectronic health record bleeding phenotyping algorithms offer a scalable approach to monitoring bleeding in the population. Incidence of bleeding has doubled in incidence since 1998, affects 1 in 4 cardiac patients, and is associated with poor prognosis. Efforts are required to tackle this iatrogenic epidemic.What is already known?Clinical guidelines and public health authorities lack recommendations on how to define or monitor the occurrence and severity of bleeding in populations.This is particularly important because clinical guidelines increasingly recommend the use of one, two or three antiplatelet and vitamin K antagonist drugs to lower the risk of subsequent atherothrombotic events in common heart diseases including atrial fibrillation, acute coronary syndromes and chronic stable angina.Clinical guidelines lack consistent recommendations of how to reduce the main side effect of bleeding.For acute myocardial infarction it has been shown that combining primary care electronic health records (which include information from hospital discharge summaries) and hospital admission data can generate valid EHR disease phenotypes and provide real-world estimates of disease occurrence.What is not known?It is not known how to define bleeding occurrence and severity in large scale, unselected populations by combining available information on bleeding diagnosis in primary or hospital care, symptoms, transfusion, surgical procedures, and haemoglobin values.The population-based incidence, time trends and long-term prognosis of bleeding have not been evaluated in people with common cardiac disorders.Comparisons of the population burden of bleeding across common cardiac disorders, such as atrial fibrillation, acute coronary syndromes and stable angina, are lacking.What this study adds?Phenotype: We developed standardised replicable EHR phenotyping algorithms defining bleeding and severity measures based on available clinical information across structured primary and hospital care EHR sources.Incidence: At 5 years of follow-up, one in five patients with cardiac disease had a bleeding event and 6.5% had fatal or severe bleeding.Trends: There was approximately a two-fold increase in incidence of primary care and hospitalised bleeding between 1998 and 2010. The rate of fatal bleeding remained stable.Prognosis: Patients with bleeding recorded in primary care or in hospital admissions are at increased bleeding between 1998 and 2010. The rate of fatal bleeding remained stable, risk of all-cause death and atherothrombotic events.

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Neutrophil Counts and Initial Presentation of 12 Cardiovascular Diseases

Cited by 114 publications

References 30 publications

Risk factors for incident heart failure in age‐ and sex‐specific strata: a population‐based cohort using linked electronic health records

Risk factors for incident heart failure in age‐ and sex‐specific strata: a population‐based cohort using linked electronic health records

Increased body fat and reduced insulin sensitivity are associated with impaired endothelial function and subendocardial viability in healthy, non‐Hispanic white adolescents

Bleeding in cardiac patients prescribed antithrombotic drugs: Electronic health record phenotyping algorithms, incidence, trends and prognosis

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