scholarly journals CHARGE-AF in a national routine primary care electronic health records database in the Netherlands: validation for 5-year risk of atrial fibrillation and implications for patient selection in atrial fibrillation screening

Open Heart ◽  
2021 ◽  
Vol 8 (1) ◽  
pp. e001459
Author(s):  
Jelle C L Himmelreich ◽  
Wim A M Lucassen ◽  
Ralf E Harskamp ◽  
Claire Aussems ◽  
Henk C P M van Weert ◽  
...  
Keyword(s):  
Atrial Fibrillation ◽  
Primary Care ◽  
High Risk ◽  
The Netherlands ◽  
Patient Selection ◽  
Low Cost ◽  
Calibration Plot ◽  
Primary Care Data ◽  
C Statistic ◽  
Kaplan Meier

AimsTo validate a multivariable risk prediction model (Cohorts for Heart and Aging Research in Genomic Epidemiology model for atrial fibrillation (CHARGE-AF)) for 5-year risk of atrial fibrillation (AF) in routinely collected primary care data and to assess CHARGE-AF’s potential for automated, low-cost selection of patients at high risk for AF based on routine primary care data.MethodsWe included patients aged ≥40 years, free of AF and with complete CHARGE-AF variables at baseline, 1 January 2014, in a representative, nationwide routine primary care database in the Netherlands (Nivel-PCD). We validated CHARGE-AF for 5-year observed AF incidence using the C-statistic for discrimination, and calibration plot and stratified Kaplan-Meier plot for calibration. We compared CHARGE-AF with other predictors and assessed implications of using different CHARGE-AF cut-offs to select high-risk patients.ResultsAmong 111 475 patients free of AF and with complete CHARGE-AF variables at baseline (17.2% of all patients aged ≥40 years and free of AF), mean age was 65.5 years, and 53% were female. Complete CHARGE-AF cases were older and had higher AF incidence and cardiovascular comorbidity rate than incomplete cases. There were 5264 (4.7%) new AF cases during 5-year follow-up among complete cases. CHARGE-AF’s C-statistic for new AF was 0.74 (95% CI 0.73 to 0.74). The calibration plot showed slight risk underestimation in low-risk deciles and overestimation of absolute AF risk in those with highest predicted risk. The Kaplan-Meier plot with categories <2.5%, 2.5%–5% and >5% predicted 5-year risk was highly accurate. CHARGE-AF outperformed CHA2DS2-VASc (Cardiac failure or dysfunction, Hypertension, Age >=75 [Doubled], Diabetes, Stroke [Doubled]-Vascular disease, Age 65-74, and Sex category [Female]) and age alone as predictors for AF. Dichotomisation at cut-offs of 2.5%, 5% and 10% baseline CHARGE-AF risk all showed merits for patient selection in AF screening efforts.ConclusionIn patients with complete baseline CHARGE-AF data through routine Dutch primary care, CHARGE-AF accurately assessed AF risk among older primary care patients, outperformed both CHA2DS2-VASc and age alone as predictors for AF and showed potential for automated, low-cost patient selection in AF screening.

Arterial calcification in the prediction of atherosclerotic cardiovascular disease among women and men

2020 ◽  
Vol 41 (Supplement_2) ◽  
Author(s):  
J.E Van Der Toorn ◽  
D Bos ◽  
B Arshi ◽  
M.K Ikram ◽  
M.W Vernooij ◽  
...  
Keyword(s):  
Cardiovascular Disease ◽  
High Risk ◽  
The Netherlands ◽  
Arterial Calcification ◽  
Funding Source ◽  
Atherosclerotic Cardiovascular Disease ◽  
Intermediate Risk ◽  
C Statistic ◽  
Ascvd Risk ◽  
Risk Categories

Abstract Background The Coronary Artery Calcium (CAC) Score has emerged as a valuable tool in atherosclerotic cardiovascular disease (ASCVD) risk stratification. However, data on the relevance of arterial calcification in different vascular territories for ASCVD risk prediction is lacking. Purpose First, to assess the sex-specific distribution of arterial calcification in different vessel beds across ASCVD risk categories. Second, to determine the added value of arterial calcification in different vascular territories for ASCVD risk prediction. Methods From a large population-based study, 2,139 participants (mean age 69 years, 55% women) underwent non-contrast computed tomography to quantify CAC, aortic arch calcification (AAC), extracranial- (ECAC) and intracranial carotid artery calcification (ICAC), and vertebrobasilar artery calcification (VBAC). The outcome measure, incident ASCVD, composed of fatal and nonfatal myocardial infarction (MI), other coronary heart disease (CHD) mortality, and stroke. We fitted sex-specific prediction models according to the Pooled Cohort Equations (PCE), and categorized participants into low- (&lt;5%), borderline- (5% to 7.5%), intermediate- (7.5% to 20%), and high ASCVD risk (≥20%), based on the American College of Cardiology (ACC) and American Heart Association (AHA) guideline. Subsequently, we determined the distribution of calcifications in different vascular territories across the risk categories. Next, we extended the PCE prediction model with calcification volumes and calculated the c-statistic and the net reclassification improvement for events (NRIe) and non-events (NRIne). Results The median follow-up for ASCVD was 9.3 years. Among women, 38% was classified as low-risk, 19% as borderline risk, 31% as intermediate risk, and 12% as high risk. Among men, 2% was classified as low-risk, 10% as borderline risk, 60% as intermediate risk, and 28% as high risk. With increasing risk of ASCVD, a larger burden of calcification was observed. In women, simultaneously adding calcification volumes in all vessel beds led to the largest increase in c statistic (from 0.71 to 0.75) for the prediction of ASCVD and the most beneficial reclassification (NRIe: 11%, NRIne: 2%). Among men, the addition of CAC alone most substantially improved the prediction of ASCVD (c statistic improved from 0.65 to 0.68, NRIe and NRIne were 4% and 14%, respectively). Conclusions Our findings suggest a potential role for comprehensive assessment of calcification in different vessel beds for ASCVD risk stratification in particular among women. Funding Acknowledgement Type of funding source: Public Institution(s). Main funding source(s): The Rotterdam Study is supported by Erasmus MC and Erasmus University Rotterdam; the Netherlands Organization for Scientific Research; the Netherlands Organization for Health Research and Development (ZonMw); the Research Institute for Diseases in the Elderly; the Netherlands Genomics Initiative; the Ministry of Education, Culture, and Science; the Ministry of Health, Welfare, and Sports; European Commission; and the Municipality of Rotterdam. Dr. Kavousi is supported by the VENI grant (91616079) from ZonMw. Dr. Bos was supported by a fellowship of the BrightFocus Foundation (A2017424F). Oscar L. Rueda-Ochoa receives a scholarship from COLCIENCIAS-Colombia and support from Universidad Industrial de Santander,UIS-Colombia. None of the funders had any role in study design; study conduct; collection, management, analysis, and interpretation of the data; and preparation, review, or approval of the article.

scholarly journals SHARPEN score accurately predict in-hospital mortality in infective endocarditis: a real-world validation study

2020 ◽  
Vol 41 (Supplement_2) ◽  
Author(s):  
S.G Alves ◽  
F.B Filippini ◽  
G.P Dannenhauer ◽  
G Seroiska ◽  
L.F.S Birk ◽  
...  
Keyword(s):  
Multivariate Analysis ◽  
Cardiac Surgery ◽  
Infective Endocarditis ◽  
High Risk ◽  
Hospital Mortality ◽  
Rank Test ◽  
C Statistic ◽  
Kaplan Meier ◽  
Duke Criteria ◽  
High Negative Predictive Value

Abstract Background Infective Endocarditis (IE) has impressive 30-day mortality of up to 30%. Prompt recognition of high-risk patients is required in order to optimize management and outcomes. The SHARPEN score was recently developed to predict intrahospital mortality in patients admitted due to IE, regardless of the need to undergo cardiac surgery. We aimed to evaluate the accuracy of the SHARPEN score to predict in-hospital mortality in comparison to Charlson Comorbidity Index (CCI). Methods Retrospective cohort of all consecutive adult admissions between 2000 and 2016 with diagnosis of definitive IE according to the Modified Duke Criteria. The SHARPEN score was applied comprising: Systolic blood pressure at presentation, Heart failure, Age, Raised creatinine, Pneumonia, Elevated peak CRP and Non-intravenous drug abuser. The CCI was applied to assess comorbidities. Accuracy in predict mortality was estimated with C-statistic. DeLong test was used to compare the areas under the curve (AUC). Survival probabilities were estimated by Kaplan-Meier method and differences between survival curves analyzed using the log-rank test. Multivariate analysis using Poisson Regression with robust variation was performed to determine independent predictors of in-hospital mortality. Results 179 cases of IE were registered (70% male; 55±17 years-old) with an in-hospital mortality of 22%. Cardiac surgery was required in 68 (38%) of the patients. Calculated SHARPEM and CCI scores were 9 (7–11) and 3 (1–6) points respectively. SHARPEN was able to predict in-hospital mortality with an AUC of 0.76 (95% CI 0.7–0.8; p&lt;0.001) and cut-off &gt;10 points (Sen=69%; Sp=71%; PPV=40%; NPV=89%). Mortality was significant higher (40% vs 11%; p&lt;0.001) in patients with SHARPEN &gt;10 points (FIGURE). CCI had a similar AUC of 0.7 (95% CI 0.6 - 0.8; p&lt;0.001) with SHARPEN (p=0.32). However, in a multivariate analysis, SHARPEN score &gt;10 points a stronger predictor related with in-hospital mortality (OR 2.3; 95% CI 1.1 - 4.8; p=0.03) in comparison to CCI &gt;3 points (OR 1.4; 95% CI 0.7–2.8; p=0.3). Conclusion SHARPEN score demonstrated a good accuracy in predict in-hospital mortality independently of other variables, with a high negative predictive value. These findings suggest that SHARPEN score may be useful to stratify high-risk IE patients in a clinical setting. Funding Acknowledgement Type of funding source: None

Low varicella-related consultation rate in the Netherlands in primary care data

Vaccine ◽  
2014 ◽  
Vol 32 (28) ◽  
pp. 3517-3524 ◽  
Author(s):  
Alies van Lier ◽  
Jolanda van Erp ◽  
Gé A. Donker ◽  
Nicoline A.T. van der Maas ◽  
Miriam C.J.M. Sturkenboom ◽  
...  
Keyword(s):  
Primary Care ◽  
The Netherlands ◽  
Consultation Rate ◽  
Primary Care Data

Atrial fibrillation detection with a portable device during cardiovascular screening in primary care

Heart ◽  
2020 ◽  
Vol 106 (16) ◽  
pp. 1261-1266 ◽  
Author(s):  
Adriana C Diamantino ◽  
Bruno R Nascimento ◽  
Andrea Z Beaton ◽  
Maria Carmo P Nunes ◽  
Kaciane K B Oliveira ◽  
...  
Keyword(s):  
Atrial Fibrillation ◽  
Primary Care ◽  
Heart Disease ◽  
High Risk ◽  
High Sensitivity ◽  
Low Risk ◽  
Intermediate Risk ◽  
Complete Study ◽  
Risk Patients ◽  
Primary Care Patients

IntroductionA novel handheld dual-electrode stick is a portable atrial fibrillation (AF) screening device (AFSD). We evaluated AFSD performance in primary care patients referred for echocardiogram (echo).MethodsThe AFSD has a light indication of irregular rhythm and single-lead ECG recording. Patients were instructed to hold the device for 1 min, and AF indication was recorded. A 12-lead ECG was performed for all AFSD-positive patients and 250 patients with negative AFSD screen. Echos were performed based on a clinical risk score: all high-risk patients and a sampling of low-risk patients underwent complete echo. Intermediate risk patients first had a screening echocardiogram, with a follow-up complete study if abnormality was suspected.ResultsIn 5 days, 1518 patients underwent clinical evaluation and cardiovascular risk stratification: mean age 58±16 years, 66% women. The AFSD was positive in 6.4%: 12.6% high risk, 6.1% intermediate risk and 2.2% low risk. Older age was a risk factor (9.3% vs 4.8% in those more than and less than 65 years, p=0.001). AFSD positive was independently associated with heart disease in echo (OR=3.9, 95% CI 2.1 to 7.2, p<0.001). Compared with 12-lead ECG, the AFSD had sensitivity of 90.2% (95% CI 77.0% to 97.3%) and specificity of 84.0% (95% CI 79.3% to 88.0%) for AF detection.ConclusionAFSD demonstrated high sensitivity for AF detection in primary care patients referred for echo. AF prevalence was substantial and independently associated with structural or functional heart disease, suggesting that AFSD screening could be a useful primary care tool to stratify risk and prioritise echo.

A national survey of the management of atrial fibrillation with antithrombotic drugs in Italian primary care

2010 ◽  
Vol 103 (05) ◽  
pp. 968-975 ◽  
Author(s):  
Alessandro Filippi ◽  
Marianna Alacqua ◽  
Warren Cowell ◽  
Annabelle Shakespeare ◽  
Lorenzo Mantovani ◽  
...  
Keyword(s):  
Atrial Fibrillation ◽  
Primary Care ◽  
Risk Stratification ◽  
Primary Care Physicians ◽  
Stroke Risk ◽  
Risk Profile ◽  
Antithrombotic Drugs ◽  
Factors Associated ◽  
Primary Care Data ◽  
Males And Females

SummaryThe aims of this study were to investigate trends in the incidence of diagnosed atrial fibrillation (AF), and to identify factors associated with the prescription of antithrombotics (ATs) and to identify the persistence of patients with oral anticoagulant (OAC) treatment in primary care. Data were obtained from 400 Italian primary care physicians providing information to the Health Search/Thales Database from 2001 to 2004. The age-standardised incidence of AF was: 3.9–3.0 cases, and 3.6–3.0 cases per 1,000 person-years in males and females, respectively. During the study period, 2,016 (37.2%) patients had no prescription, 1,663 (30.7%) were prescribed an antiplatelet (AP) agent, 1,440 (26.6%) were prescribed an OAC and 301 (5.5%) had both prescriptions. The date of diagnosis (p = 0.0001) affected the likelihood of receiving an OAC. AP, but not OAC, use significantly increased with a worsening stroke risk profile using the CHADS2 risk score. Older age increased the probability (p < 0.0001) of receiving an AP, but not an OAC. Approximately 42% and 24% of patients persisted with OAC treatment at one and two years, respectively, the remainder interrupted or discontinued their treatment. Underuse and discontinuation of OAC treatment is common in incident AF patients. Risk stratification only partially influences AT management.

scholarly journals A retrospective cohort study examining secondary prevention post stroke in primary care in an Asian setting

2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Vivek Bansal ◽  
Eng Sing Lee ◽  
Helen Smith
Keyword(s):  
Risk Factors ◽  
Atrial Fibrillation ◽  
Primary Care ◽  
Risk Factor ◽  
Cohort Study ◽  
High Risk ◽  
Secondary Prevention ◽  
Retrospective Cohort ◽  
Low Risk ◽  
Risk Factor Control

Abstract Background Stroke is one of the top contributors to burden of disability-adjusted life-years worldwide. Family physicians have key role in optimising secondary prevention following stroke by managing clinical risk factors and promoting overall control in accordance with clinical practice guidelines. Methods Our objectives were: (i) to examine level of overall risk factor control together with control of singular risk factors one-year after an index-stroke event in individuals attending primary care facility and (ii) to describe factors associated with satisfactory risk factors control in individuals following stroke. Study Design: Retrospective cohort study. We conducted a study looking retrospectively at records from our electronic chronic disease database. Our study included individuals following stroke who visited primary care setting in Singapore between January 2012 to December 2016. Results There were 24,240 individuals in our study. Overall control was better in individuals without diabetes following stroke (49.2%) as compared to those with diabetes (28.1%). Among individuals without diabetes following stroke, factors significantly associated with overall control were sex (male) [OR (reference: female): 1.23, 95% CI: 1.10, 1.39], ethnicity (Malay) [OR (reference: Chinese): 0.72, 95% CI: 0.58, 0.90], BMI (high risk) [OR (reference: low risk): 0.72, 95% CI: 0.62, 0.84) and atrial fibrillation [OR: 1.47, 95% CI: 1.21, 1.78]. Among individuals with diabetes following stroke, factors significantly associated with overall control were sex (male) [OR (reference: female): 1.28, 95% CI: 1.12, 1.46], ethnicity (Malay) [OR (reference: Chinese): 0.81, 95% CI: 0.65, 0.99], ethnicity (Indian) [OR (reference: Chinese): 0.70, 95% CI: 0.55, 0.88], BMI (high risk) [OR (reference: low risk): 0.71, 95% CI: 0.59, 0.84), BMI (moderate risk) [OR (reference: low risk): 0.84, 95% CI: 0.72, 0.98), atrial fibrillation [OR: 1.24; 95% CI: 1.02, 1.51], chronic kidney disease [OR: 0.63, 95% CI: 0.54, 0.72] and smoking status [OR: 0.68, 95% CI: 0.54, 0.88]. Conclusion We reported sub-optimal level of overall control. Among individuals following stroke, those with diabetes had higher proportion of sub-optimal control as compared to those without diabetes. Irrespective of diabetic status, being female, having high BMI, and of Malay ethnicity as compared to Chinese ethnicity were associated with poorer overall risk factor control.

scholarly journals Selection of eligible participants for screening for lung cancer using primary care data

Thorax ◽  
2021 ◽  
pp. thoraxjnl-2021-217142
Author(s):  
Emma L O'Dowd ◽  
Kevin ten Haaf ◽  
Jaspreet Kaur ◽  
Stephen W Duffy ◽  
William Hamilton ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Primary Care ◽  
Risk Prediction ◽  
Prediction Models ◽  
Risk Prediction Models ◽  
Lung Cancers ◽  
Primary Care Data ◽  
C Statistic ◽  
The Cost ◽  
Predicted Risk

Lung cancer screening is effective if offered to people at increased risk of the disease. Currently, direct contact with potential participants is required for evaluating risk. A way to reduce the number of ineligible people contacted might be to apply risk-prediction models directly to digital primary care data, but model performance in this setting is unknown.MethodThe Clinical Practice Research Datalink, a computerised, longitudinal primary care database, was used to evaluate the Liverpool Lung Project V.2 (LLPv2) and Prostate Lung Colorectal and Ovarian (modified 2012) (PLCOm2012) models. Lung cancer occurrence over 5–6 years was measured in ever-smokers aged 50–80 years and compared with 5-year (LLPv2) and 6-year (PLCOm2012) predicted risk.ResultsOver 5 and 6 years, 7123 and 7876 lung cancers occurred, respectively, from a cohort of 842 109 ever-smokers. After recalibration, LLPV2 produced a c-statistic of 0.700 (0.694–0.710), but mean predicted risk was over-estimated (predicted: 4.61%, actual: 0.9%). PLCOm2012 showed similar performance (c-statistic: 0.679 (0.673–0.685), predicted risk: 3.76%. Applying risk-thresholds of 1% (LLPv2) and 0.15% (PLCOm2012), would avoid contacting 42.7% and 27.4% of ever-smokers who did not develop lung cancer for screening eligibility assessment, at the cost of missing 15.6% and 11.4% of lung cancers.ConclusionRisk-prediction models showed only moderate discrimination when applied to routinely collected primary care data, which may be explained by quality and completeness of data. However, they may substantially reduce the number of people for initial evaluation of screening eligibility, at the cost of missing some lung cancers. Further work is needed to establish whether newer models have improved performance in primary care data.

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