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BACKGROUND: Current prediction models for mainland Europe do not include ethnicity, despite ethnic disparities in cardiovascular disease (CVD) risk. SCORE2 performance was evaluated across the largest ethnic groups in the Netherlands and ethnic backgrounds were added to the model. METHODS: 11,614 participants, aged between 40 and 70â¯years without CVD, from the population-based multi-ethnic HELIUS study were included. Fine and Gray models were used to calculate sub-distribution hazard ratios (SHR) for South-Asian Surinamese, African Surinamese, Ghanaian, Turkish and Moroccan origin groups, representing their CVD risk relative to the Dutch group, on top of individual SCORE2 risk predictions. Model performance was evaluated by discrimination, calibration and net reclassification index (NRI). RESULTS: Overall, 274 fatal and non-fatal CVD events, and 146 non-cardiovascular deaths were observed during a median of 7.8â¯years follow-up (IQR 6.8-8.8). SHRs for CVD events were 1.86 (95â¯% CI 1.31-2.65) for the South-Asian Surinamese, 1.09 (95â¯% CI 0.76-1.56) for the African-Surinamese, 1.48 (95â¯% CI 0.94-2.31) for the Ghanaian, 1.63 (95â¯% CI 1.09-2.44) for the Turkish, and 0.67 (95â¯% CI 0.39-1.18) for the Moroccan origin groups. Adding ethnicity to SCORE2 yielded comparable calibration and discrimination [0.764 (95â¯% CI 0.735-0.792) vs. 0.769 (95â¯% CI 0.740-0.797)]. The NRI for adding ethnicity to SCORE2 was 0.24 (95â¯% CI 0.18-0.31) for events andâ¯-â¯0.12 (95â¯% CI -0.13-0.12) for non-events. CONCLUSIONS: Adding ethnicity to the SCORE2 risk prediction model in a middle-aged, multi-ethnic Dutch population did not improve overall discrimination but improved risk classification, potentially helping to address CVD disparities through timely treatment.
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Atrial fibrillation (AF) is a common arrhythmia associated with an increased risk of stroke, which can be effectively reduced by prophylaxis initiation and integrated care to reduce cardiovascular risk and AF-related complications. Screening for AF has the potential to improve long-term clinical outcomes through timely AF detection in asymptomatic patients. With the central role of primary care in most European healthcare systems in terms of disease detection, treatment, as well as record keeping, primary care is ideally situated as a setting for AF screening efforts. In this review, we provide an overview of evidence relating to AF screening in primary care. We discuss current practices of AF detection and screening, evidence from AF screening trials conducted in primary care settings, stakeholder views on barriers and facilitators for AF screening in primary care, and important aspects that will likely shape routine primary care AF detection as well as AF screening efforts. Finally, we present a potential outline for a primary care-centred AF screening trial coupled to integrated AF care that could further improve the benefit of AF screening.
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BACKGROUND: The extent to which differences in results from Apixaban for Reduction in Stroke and Other Thromboembolic Events in Atrial Fibrillation (ARISTOTLE) and Rivaroxaban Once Daily Oral Direct Factor Xa Inhibition Compared with Vitamin K Antagonism for Prevention of Stroke and Embolism Trial (ROCKET) atrial fibrillation (AF)-the landmark trials for the approval of apixaban and rivaroxaban, respectively, for non-valvular AF-were influenced by differences in their protocols is debated. The potential influence of selection criteria on trial results was assessed by emulating these trials in data from the Global Anticoagulant Registry in the Field (GARFIELD)-AF registry. METHODS: Vitamin K antagonist (VKA) and non-vitamin K oral antagonist (NOAC) users from GARFIELD-AF were selected according to eligibility for the original ARISTOTLE or ROCKET AF trials. A propensity score overlap weighted Cox model was used to emulate trial randomisation between treatment groups. Adjusted HRs for stroke or systemic embolism (SE) within 2 years of enrolment were calculated for each NOAC versus VKA. RESULTS: Among patients on apixaban, rivaroxaban and VKA, 2570, 3560 and 8005 were eligible for ARISTOTLE, respectively, and 1612, 2005 and 4368, respectively, for ROCKET AF. When selecting for ARISTOTLE criteria, apixaban users had significantly lower stroke/SE risk versus VKA (HR 0.57; 95% CI 0.34 to 0.94) while no reduction was observed with rivaroxaban (HR 0.98; 95% CI 0.68 to 1.40). When selecting for ROCKET AF criteria, safety and efficacy versus VKA were similar across the NOACs. CONCLUSION: Apixaban and rivaroxaban showed similar results versus VKA in high-risk patients selected according to ROCKET AF criteria, whereas differences emerged when selecting for the more inclusive ARISTOTLE criteria. Our results highlight the importance of trial selection criteria in interpreting trial results and underline the problems faced in comparing treatments across rather than within clinical trials.
Subject(s)
Atrial Fibrillation , Factor Xa Inhibitors , Patient Selection , Pyrazoles , Pyridones , Rivaroxaban , Stroke , Humans , Atrial Fibrillation/drug therapy , Atrial Fibrillation/complications , Factor Xa Inhibitors/therapeutic use , Factor Xa Inhibitors/administration & dosage , Stroke/prevention & control , Stroke/etiology , Pyrazoles/therapeutic use , Pyridones/therapeutic use , Pyridones/adverse effects , Pyridones/administration & dosage , Rivaroxaban/administration & dosage , Rivaroxaban/therapeutic use , Male , Female , Aged , Treatment Outcome , Registries , Administration, Oral , Risk Factors , Randomized Controlled Trials as Topic/methods , Risk Assessment/methods , Anticoagulants/therapeutic use , Vitamin K/antagonists & inhibitorsABSTRACT
OBJECTIVES: Proper coding of heart failure (HF) in electronic health records (EHRs) is an important prerequisite for adequate care and research towards this vulnerable patient population. We set out to evaluate the accuracy of registration of HF diagnoses in primary care EHRs. METHODS: In a routine primary care database covering the Amsterdam Metropolitan Area, we identified all episodes of care with International Classification of Primary Care (ICPC) codes K77 (decompensatio cordis) or K84.03 (cardiomyopathy) up to 31/12/2021. We also performed two text-based searches to identify HF episodes without an appropriate ICPC-code. An expert panel evaluated all ICPC and text matches for congruence between the assigned codes and notes. RESULTS: From a database of 968,433 records we identified 19,106 patients (2.0â¯%) with a total of 24,011 ICPC-coded HF episodes. Removal of 1,324 episodes found to concern other or uncertain diagnoses and inclusion of 4,582 validated HF episodes identified through text search led to exclusion of 909 (overregistration: 4.8â¯%) and inclusion of 2,266 additional patients (underregistration: 11.1â¯%). The inclusion of miscoded HF episodes advanced the first known date of HF diagnosis in 3.9â¯% of records, with a median shift of 3.45 years. Episode-level underregistration decreased significantly over time, from 23.8â¯% in 2006 to 10.0â¯% in 2021. CONCLUSIONS: While there is improvement over time, there are still substantial levels of over- and underregistration of HF, emphasizing the need for cautious interpretation of ICPC-coded data. The findings contribute to the understanding of HF registration issues in primary care and provide insights for improving registration practices.
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INTRODUCTION: Telephone triage is pivotal for evaluating the urgency of patient care, and in the Netherlands, the Netherlands Triage Standard (NTS) demonstrates moderate discrimination for chest pain. To address this, the Safety First Prediction Rule (SFPR) was developed to improve the safety of ruling out acute coronary syndrome (ACS) during telephone triage. METHODS: We conducted an external validation of the SFPR using data from the TRACE study, a retrospective cohort study in out-of-hours primary care. We evaluated the diagnostic accuracy assessment for ACS, major adverse cardiovascular events (MACE), and major events within 6 weeks. Moreover, we compared its performance with that of the NTS algorithm. RESULTS: Among 1404 included patients (57.3% female, 6.8% ACS, 8.6% MACE), the SFPR demonstrated good discrimination for ACS (C-statistic: 0.79; 95%-CI: 0.75-0.83) and MACE (C-statistic: 0.79; 95%-CI: 0.0.76-0.82). Calibration was satisfactory, with overestimation observed in high-risk patients for ACS. The SFPR (risk threshold 2.5%) trended toward higher sensitivity (95.8% vs. 86.3%) and negative predictive value (99.3% vs. 97.6%) with a lower negative likelihood ratio (0.10 vs. 0.34) than the NTS algorithm. CONCLUSION: The SFPR proved robust for risk stratification in patients with acute chest pain seeking out-of-hours primary care in the Netherlands. Further prospective validation and implementation are warranted to refine and establish the rule's clinical utility.
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AIM: To evaluate the use of a single-lead electrocardiography (1L-ECG) device and digital cardiologist consultation platform in diagnosing arrhythmias among general practitioners (GPs). BACKGROUND: Handheld 1L-ECG offers a user-friendly alternative to conventional 12-lead ECG in primary care. While GPs can safely rule out arrhythmias on 1L-ECG recordings, expert consultation is required to confirm suspected arrhythmias. Little is known about GPs' experiences with both a 1L-ECG device and digital consultation platform for daily practice. METHODS: We used two distinct methods in this study. First, in an observational study, we collected and described all cases shared by GPs within a digital cardiologist consultation platform initiated by a local GP cooperative. This GP cooperative distributed KardiaMobile 1L-ECG devices among all affiliated GPs (n = 203) and invited them to this consultation platform. In the second part, we used an online questionnaire to evaluate the experiences of these GPs using the KardiaMobile and consultation platform. FINDINGS: In total, 98 (48%) GPs participated in this project, of whom 48 (49%) shared 156 cases. The expert panel was able to provide a definitive rhythm interpretation in 130 (83.3%) shared cases and answered in a median of 4 min (IQR: 2-18). GPs responding to the questionnaire (n = 43; 44%) thought the KardiaMobile was of added value for rhythm diagnostics in primary care (n = 42; 98%) and easy to use (n = 41; 95%). Most GPs (n = 36; 84%) valued the feedback from the cardiologists in the consultation platform. GPs experienced this project to have a positive impact on both the quality of care and diagnostic efficiency for patients with (suspected) cardiac arrhythmias. Although we lack a comprehensive picture of experienced impediments by GPs, solving technical issues was mentioned to be helpful for further implementation. More research is needed to explore reasons of GPs not motivated using these tools and to assess real-life clinical impact.
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Cardiologists , General Practitioners , Humans , Netherlands , Referral and Consultation , Electrocardiography/methodsABSTRACT
BACKGROUND: It is thought that ChatGPT, an advanced language model developed by OpenAI, may in the future serve as an AI-assisted decision support tool in medicine. OBJECTIVE: To evaluate the accuracy of ChatGPT's recommendations on medical questions related to common cardiac symptoms or conditions. METHODS: We tested ChatGPT's ability to address medical questions in two ways. First, we assessed its accuracy in correctly answering cardiovascular trivia questions (n = 50), based on quizzes for medical professionals. Second, we entered 20 clinical case vignettes on the ChatGPT platform and evaluated its accuracy compared to expert opinion and clinical course. Lastly, we compared the latest research version (v3.5; 27 September 2023) with a prior version (v3.5; 30 January 2023) to evaluate improvement over time. RESULTS: We found that ChatGPT latest version correctly answered 92% of the trivia questions, with slight variation in accuracy in the domains coronary artery disease (100%), pulmonary and venous thrombotic embolism (100%), atrial fibrillation (90%), heart failure (90%) and cardiovascular risk management (80%). In the 20 case vignettes, ChatGPT's response matched in 17 (85%) of the cases with the actual advice given. Straightforward patient-to-physician questions were all answered correctly (10/10). In more complex cases, where physicians (general practitioners) asked other physicians (cardiologists) for assistance or decision support, ChatGPT was correct in 70% of cases, and otherwise provided incomplete, inconclusive, or inappropriate recommendations when compared with expert consultation. ChatGPT showed significant improvement over time; as the January version correctly answered 74% (vs 92%) of trivia questions (p = 0.031), and correctly answered a mere 50% of complex cases. CONCLUSIONS: Our study suggests that ChatGPT has potential as an AI-assisted decision support tool in medicine, particularly for straightforward, low-complex medical questions, but further research is needed to fully evaluate its potential.
Subject(s)
Proof of Concept Study , Humans , Decision Support Systems, Clinical , Decision Support Techniques , Artificial Intelligence , Cardiovascular Diseases/diagnosis , Cardiovascular Diseases/therapy , Heart Diseases/diagnosis , Heart Diseases/therapyABSTRACT
Background: Epidemiological studies suggest sex differences in the prevalence and characteristics of unrecognized and recognized myocardial infarction (uMI, rMI). Despite increasingly diverse populations, observations are limited in multiethnic contexts. Gaining better understanding may inform policy makers and healthcare professionals on populations at risk of uMI who could benefit from preventive measures. Methods: We used baseline data from the multiethnic population-based HELIUS cohort (2011-2015; Amsterdam, the Netherlands). Using logistic regressions, we studied sex differences in the prevalence and proportion of uMIs across ethnic groups. Next, we studied whether symptoms, clinical parameters, and sociocultural factors were associated with uMIs. Finally, we compared secondary preventive therapies in women and men with a uMI or rMI. We relied on pathological Q-waves on a resting electrocardiogram as the electrocardiographic signature for (past) MI. Results: Overall, and in Turkish and Moroccan subgroups, the prevalence of uMIs was higher in men than women. The proportion of uMIs was similar in women (21.0%) and men (18.4%), yet varied by ethnicity. In women and men, symptoms (chest pain, dyspnea) and clinical parameters (hypertension, hypercholesterolemia), and in women also lower educational level and diabetes were associated with lower odds of uMIs. Women (0.0%) and men (3.6%) with uMI were unlikely to receive secondary preventive therapies compared to those with rMI (28.1-40.9%). Conclusions: The prevalence of uMIs was higher in men than women, and sex differences in the proportion of uMIs varied somewhat across ethnic groups. People with uMIs did not receive adequate preventative medications, posing a risk for recurrent events.
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OBJECTIVES: Troponin testing is indicated in the diagnostic work-up of acute coronary syndrome (ACS) and incorporated in risk stratification pathways. This study aims to gain insights on the use, outcomes, and diagnostic accuracy of troponin testing in routine primary care; a setting that is understudied. METHODS: Routine data were used from the academic primary care network in the Amsterdam metropolitan area (968,433 patient records). The study population included adult patients who underwent high-sensitivity troponin I or T (hs-TnI/T) testing between 2011 and 2021. The primary outcome was the reported diagnosis and the secondary outcome was the diagnostic accuracy measured by death or ACS at 30 days. RESULTS: 3,184 patients underwent hs-troponin testing, either with hsTNT (n=2,333) or hsTNI (n=851). Median patients' age was 55 (44-65) years, and 62.3â¯% were female. Predominant symptoms were chest pain and dyspnea (56.7â¯%). Additional diagnostic laboratory tests were commonly performed (CRP: 47.7â¯%, natriuretic peptides: 25.6â¯%, d-dimer: 21.5â¯%). Most common diagnoses were musculoskeletal symptoms (21.6â¯%) and coronary heart disease (7.1â¯%; 1.1â¯% ACS). Troponin testing showed sensitivity and specificity of 77.8â¯% (60.9-89.9) and 94.3â¯% (93.5-95.1), respectively. Negative and positive predictive values were 99.7 (99.5-99.9) and 13.5 (11.1-16.4), and positive and negative likelihood ratios were 13.7 (10.9-17.1) and 0.24 (0.13-0.43). CONCLUSIONS: GPs occasionally use troponin testing in very low-risk patients, often as part of a multi-marker rule-out strategy. The diagnostic characteristics of troponin tests, while promising, warrant prospective validation and implementation to facilitate appropriate use.
Subject(s)
Acute Coronary Syndrome , Primary Health Care , Troponin I , Humans , Female , Middle Aged , Male , Aged , Adult , Netherlands , Acute Coronary Syndrome/diagnosis , Acute Coronary Syndrome/blood , Troponin I/blood , Cohort Studies , Troponin T/blood , Chest Pain/diagnosis , Chest Pain/blood , Biomarkers/blood , Risk Assessment , Sensitivity and SpecificityABSTRACT
OBJECTIVES: Heart failure (HF) is a prevalent syndrome with considerable disease burden, healthcare utilization and costs. Timely diagnosis is essential to improve outcomes. This study aimed to compare the diagnostic performance of B-type natriuretic peptide (BNP) and N-terminal proBNP (NT-proBNP) in detecting HF in primary care. Our second aim was to explore if personalized thresholds (using age, sex, or other readily available parameters) would further improve diagnostic accuracy over universal thresholds. METHODS: A retrospective study was performed among patients without prior HF who underwent natriuretic peptide (NP) testing in the Amsterdam General Practice Network between January 2011 and December 2021. HF incidence was based on registration out to 90 days after NP testing. Diagnostic accuracy was evaluated with AUROC, sensitivity and specificity based on guideline-recommended thresholds (125â¯ng/L for NT-proBNP and 35â¯ng/L for BNP). We used inverse probability of treatment weighting to adjust for confounding. RESULTS: A total of 15,234 patients underwent NP testing, 6,870 with BNP (4.5â¯% had HF), and 8,364 with NT-proBNP (5.7â¯% had HF). NT-proBNP was more accurate than BNP, with an AUROC of 89.9â¯% (95â¯% CI: 88.4-91.2) vs. 85.9â¯% (95â¯% CI 83.5-88.2), with higher sensitivity (95.3 vs. 89.7â¯%) and specificity (59.1 vs. 58.0â¯%). Differentiating NP cut-off by clinical variables modestly improved diagnostic accuracy for BNP and NT-proBNP compared with a universal threshold. CONCLUSIONS: NT-proBNP outperforms BNP for detecting HF in primary care. Personalized instead of universal diagnostic thresholds led to modest improvement.
Subject(s)
Heart Failure , Natriuretic Peptide, Brain , Humans , Retrospective Studies , Natriuretic Peptides , Heart Failure/diagnosis , Sensitivity and Specificity , Primary Health CareABSTRACT
Out-of-hours primary care (OOH-PC) facilities act as a first point of contact in acute care in the Netherlands, including acute chest pain. The facilities perform initial triage to assess the patient's urgency using standardized triage protocols (Netherlands Triage Standard). The performance of the current protocol for chest pain assessment was recently evaluated and showed only moderate discriminatory properties. Although final triage decision-making is improved by the clinical experience of triage assistants and general practitioners, substantial over- and under-triage persists. Improving the care of patients with chest pain in OOH-PC should primarily be sought in improving the triage software, followed by the use of innovative diagnostic tools (such as troponine measurements).
Subject(s)
After-Hours Care , General Practitioners , Humans , After-Hours Care/methods , Chest Pain/diagnosis , Chest Pain/etiology , Triage/methods , Primary Health Care/methodsABSTRACT
BACKGROUND: Heart failure (HF) is a common cardiac syndrome with a high disease burden and poor prognosis in our aging populations. Understanding the characteristics of patients with newly diagnosed HF is essential for improving care and outcomes. The AMSTERDAM-HF study is aimed to examine the population characteristics of patients with incident HF. METHODS: We performed a retrospective dynamic cohort study in the Amsterdam general practice network consisting of 904,557 individuals. Incidence HF rates, geographical demographics, patient characteristics, risk factors, symptoms prior to HF diagnosis, and prognosis were reported. RESULTS: The study identified 10,067 new cases of HF over 6,816,099 person-years. The median age of patients was 77 years (25th-75th percentile: 66-85), and 48% were male. The incidence rate of HF was 213.44 per 100,000 patient-years, and was higher in male versus female patients (incidence rate ratio: 1.08, 95%-CI:1.04-1.13). Hypertension (men 46.3% and women 55.8%), coronary artery disease (men 36% and women 25%) and diabetes mellitus (men 30.5% and women 26.8%) were the most common risk factors. Dyspnoea and oedema were key reported symptoms prior to HF diagnosis. Survival rates at 10-year follow-up were poor, particularly in men (36.4%) compared to women (39.7%). Incidence rates, comorbidity burden and prognosis were worse in city districts with high ethnic diversity and low socio-economic position. CONCLUSION: Our study provides insights into incident HF in a contemporary Western European, multi-ethnic, urban population. It highlights notable sex, age, and geographical differences in incidence rates, risk factors, symptoms and prognosis.
Subject(s)
General Practice , Heart Failure , Humans , Male , Female , Aged , Cohort Studies , Retrospective Studies , Risk Factors , Heart Failure/diagnosis , Heart Failure/epidemiology , Heart Failure/etiology , IncidenceABSTRACT
Background: The use of 12-lead electrocardiogram (ECG) is common in routine primary care, however it can be difficult for less experienced ECG readers to adequately interpret the ECG. Objective: To validate a smartphone application (PMcardio) as a stand-alone interpretation tool for 12-lead ECG in primary care. Methods: We recruited consecutive patients who underwent 12-lead ECG as part of routinely indicated primary care in the Netherlands. All ECGs were assessed by the PMcardio app, which analyzes a photographed image of 12-lead ECG for automated interpretation, installed on an Android platform (Samsung Galaxy M31) and an iOS platform (iPhone SE2020). We validated the PMcardio app for detecting any major ECG abnormality (MEA, primary outcome), defined as atrial fibrillation/flutter (AF), markers of (past) myocardial ischemia, or clinically relevant impulse and/or conduction abnormalities; or AF (key secondary outcome) with a blinded expert panel as reference standard. Results: We included 290 patients from 11 Dutch general practices with median age 67 (interquartile range 55-74) years; 48% were female. On reference ECG, 71 patients (25%) had MEA and 35 (12%) had AF. Sensitivity and specificity of PMcardio for MEA were 86% (95% CI: 76%-93%) and 92% (95% CI: 87%-95%), respectively. For AF, sensitivity and specificity were 97% (95% CI: 85%-100%) and 99% (95% CI: 97%-100%), respectively. Performance was comparable between Android and iOS platform (kappa = 0.95, 95% CI: 0.91-0.99 and kappa = 1.00, 95% CI: 1.00-1.00 for MEA and AF, respectively). Conclusion: A smartphone app developed to interpret 12-lead ECGs was found to have good diagnostic accuracy in a primary care setting for major ECG abnormalities, and near-perfect properties for diagnosing AF.
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The coronavirus disease 2019 (COVID-19) pandemic, including the restrictive measures taken to reduce the spread of the virus, negatively affected people's health behavior. We explored whether the pandemic also had an effect on metabolic risk factors for cardiovascular disease (CVD) in women and men. We conducted a natural experiment, using data from 6962 participants without CVD at baseline (2011-2015) of six ethnic groups of the HELIUS study in Amsterdam, the Netherlands. We studied whether participants whose follow-up measurements were taken within the 11 months before the pandemic (control group) differed from those whose measurements were taken taken within 6 months after the first lockdown (exposed group). Using sex-stratified linear regressions with inverse probability weighting, we compared changes in baseline- and follow-up data between the control and exposed group in six metabolic risk factors: systolic and diastolic blood pressure (SBP, DBP), total cholesterol (TC), fasting plasma glucose (FPG), hemoglobin A1c (HbA1c), and estimated glomerular filtration rate (eGFR). Next, we explored the mediating effect of changes in body-mass index (BMI), alcohol, smoking, depressive symptoms and negative life events at follow-up. We observed less favorable changes in SBP (+1.12mmHg for women, +1.38mmHg for men), DBP (+0.85mmHg, +0.80mmHg) and FPG (only in women, +0.12 mmol/L) over time in the exposed group relative to the control group. Conversely, changes in HbA1c (-0.65 mmol/mol, -0.84 mmol/mol) and eGFR (+1.06 mL/min, +1.04 mL/min) were more favorable in the exposed compared to the control group, respectively. Changes in SBP, DBP, and FPG were partially mediated by changes in behavioral factors, in particular BMI and alcohol consumption. Concluding, the COVID-19 pandemic, in particular behavioral changes associated with restrictive lockdown measures, may have negatively affected several CVD risk factors, in both women and men.
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Introduction: Current European Stroke Organisation (ESO) guidelines recommend >48 h of continuous electrocardiographic monitoring for atrial fibrillation (AF) in all patients with ischemic stroke or transient ischemic attack (TIA) with undetermined origin. We assessed the yield of the guideline-recommended monitoring for AF, as well as of extending monitoring up to 14 days. Patients and methods: We included consecutive patients with stroke/TIA without AF in an academic hospital in The Netherlands. We reported AF incidence and number needed to screen (NNS) in the overall sample after 48 h and 14 days of Holter monitoring. Results: Among 379 patients with median age 63 years (IQR 55-73), 58% male, Holter monitoring detected 10 cases of incident AF during a median of 13 (IQR 12-14) days of monitoring. Seven AF cases were detected within the first 48 hours (incidence 1.85%, 95% CI 0.74-3.81; NNS 54), and three additional AF cases were recorded among the 362 patients with >48 h of monitoring and without AF ⩽ 48 h (incidence 0.83%, 95% CI: 0.17-2.42; NNS 121). All AF cases were detected within the first 7 days of monitoring. Our sample was subject to sampling bias favoring inclusion of participants with low AF risk. Discussion: Strengths of this work were the broad inclusion criteria as recommended by ESO guidelines, and high Holter adherence among participants. The analysis was limited by inclusion of lower-risk cases and a relatively small sample size. Conclusion: In low-risk patients with recent stroke or TIA, ESO guideline-recommended screening for AF resulted in a low AF yield, with limited additional value of monitoring up to 14 days. Our results underline the need for a personalized approach in determining a patient's optimum duration for post-stroke non-invasive ambulatory monitoring.
Subject(s)
Atrial Fibrillation , Ischemic Attack, Transient , Ischemic Stroke , Stroke , Humans , Male , Middle Aged , Female , Atrial Fibrillation/diagnosis , Ischemic Attack, Transient/diagnosis , Electrocardiography, Ambulatory/adverse effects , Ischemic Stroke/complications , Stroke/diagnosisABSTRACT
Cardiovascular disease (CVD) prevention strategies include identifying and managing high risk individuals. Identification primarily occurs through screening or case finding. Guidelines indicate that psychosocial factors increase CVD risk, but their use for screening is not yet recommended. We studied whether psychosocial factors may serve as additional eligibility criteria in a multi-ethnic population without prior CVD. We performed a cross-sectional analysis using baseline data of 10,226 participants of Dutch, South-Asian Surinamese, African Surinamese, Ghanaian, Turkish and Moroccan origin aged 40-70 years, living in Amsterdam, the Netherlands. Using logistic regressions and Akaike Information Criteria, we analyzed whether psychosocial factors (educational level, employment status, occupational level, financial stress, primary earner status, mental health, stress, depression, and social isolation) improved prediction of high CVD risk (SCORE-estimated fatal and non-fatal CVD risk ≥5%) beyond eligibility criteria from history taking (smoking, obesity, family history of CVD). Next, we compared the additional predictive value of psychosocial eligibility criteria in women and men across ethnic groups, using the area under the curve (AUC). Of our sample, 32.7% had a high CVD risk. Only socioeconomic eligibility criteria (employment status and educational level) improved high CVD risk prediction (p < .001 for likelihood-ratio tests). These increased AUCs in women (from 0.563 to 0.682) and men (from 0.610 to 0.664), particularly in Dutch, South-Asian Surinamese, African Surinamese and Moroccan women, and Dutch and Moroccan men. Concluding, socioeconomic eligibility criteria may be considered as additional eligibility criteria for CVD risk screening, as they improve detection of women and men at high CVD risk.
Subject(s)
Cardiovascular Diseases , Ethnicity , Male , Humans , Female , Ghana , Cross-Sectional Studies , Risk Factors , Heart Disease Risk Factors , Netherlands/epidemiologyABSTRACT
OBJECTIVES: While ethnic minorities in Europe are disproportionally affected by cardiovascular disease (CVD), little is known about how general practitioners (GPs) perceive differences in risk or care needs across ethnic minority groups. Therefore, we explored GPs' views on whether ethnicity influences cardiovascular risk, whether a culturally sensitive approach is warranted, on potential barriers in the provision of such care, and to find potential opportunities to improve cardiovascular prevention for these groups. METHODS: We conducted a qualitative study by interviewing GPs practising in The Netherlands. The interviews were semistructured, audio-recorded, and analysed by 2 researchers using thematic analysis. RESULTS: We interviewed 24 Dutch GPs (50% male). GPs' views on the impact of ethnicity on CVD risk varied widely, yet it was generally recognized as a relevant factor in cardiovascular prevention for most minority groups, prompting earlier case-finding of high-risk patients. While GPs were aware of sociocultural differences, they emphasized an individualized approach. Perceived limitations were language barriers and unfamiliarity with sociocultural customs, leading to a need for continuing medical education on culturally sensitive care and reimbursement of telephone interpreting services. CONCLUSION: Dutch GPs have differing views on the role of ethnicity in evaluating and treating cardiovascular risk. Despite these differences, they emphasized the importance of a personalized and culturally sensitive approach during patient consultations and expressed a need for continuing medical education. Additional research on how ethnicity influences CVD risk may strengthen cardiovascular prevention in increasingly diverse primary care populations.
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BACKGROUND: Telephone triage is fully integrated in Dutch out-of-hours primary care (OOH-PC). Patients presenting with chest pain are initially assessed according to a standardized protocol ("Netherlands Triage Standard" [NTS]). Nevertheless, little is known about its (diagnostic) performance, nor on the impact of subsequent clinical judgements made by triage assistants and general practitioners (GPs). OBJECTIVE: To evaluate the performance of the current NTS chest pain protocol. METHODS: Observational, retrospective cohort study of adult patients with chest pain who contacted a regional OOH-PC facility in the Netherlands, in 2017. The clinical outcome measure involved the occurrence of a "major event," which is a composite of all-cause mortality and urgent cardiovascular and noncardiovascular conditions, occurring ≤6 weeks of initial contact. We assessed the performance using diagnostic and discriminatory properties. RESULTS: In total, 1,803 patients were included, median age was 54.0 and 57.5% were female. Major events occurred in 16.2% of patients with complete follow-up, including 99 (6.7%) cases of acute coronary syndrome and 22 (1.5%) fatal events. NTS urgency assessment showed moderate discriminatory abilities for predicting major events (c-statistic 0.66). Overall, NTS performance showed a sensitivity and specificity of 83.0% and 42.4% with a 17.0% underestimated major event rate. Triage assistants' revisions hardly improved urgency allocation. Further consideration of the clinical course following OOH-PC contact did generate a more pronounced improvement with a sensitivity of 89.4% and specificity of 61.9%. CONCLUSION: Performance of telephone triage of chest pain appears moderate at best, with acceptable safety yet limited efficiency, even after including further work-up by GPs.
Subject(s)
After-Hours Care , Triage , Adult , Humans , Female , Middle Aged , Male , Triage/methods , Netherlands , Retrospective Studies , Chest Pain/diagnosis , Chest Pain/etiology , Telephone , Primary Health Care/methodsABSTRACT
BACKGROUND: Timely diagnosis of heart failure (HF) is essential to optimize treatment opportunities that improve symptoms, quality of life, and survival. While most patients consult their general practitioner (GP) prior to HF, the early stages of HF may be difficult to identify. An integrated clinical support tool may aid in identifying patients at high risk of HF. We therefore constructed a prediction model using routine health care data. METHODS: Our study involved a dynamic cohort of patients (≥35 years) who consulted their GP with either dyspnoea and/or peripheral oedema within the Amsterdam metropolitan area from 2011 to 2020. The outcome of interest was incident HF, verified by an expert panel. We developed a regularized, cause-specific multivariable proportional hazards model (TARGET-HF). The model was evaluated with bootstrapping on an isolated validation set and compared to an existing model developed with hospital insurance data as well as patient age as a sole predictor. RESULTS: Data from 31,905 patients were included (40% male, median age 60 years) of whom 1,301 (4.1%) were diagnosed with HF over 124,676 person-years of follow-up. Data were allocated to a development (nâ =â 25,524) and validation (nâ =â 6,381) set. TARGET-HF attained a C-statistic of 0.853 (95% CI, 0.834 to 0.872) on the validation set, which proved to provide a better discrimination than Câ =â 0.822 for age alone (95% CI, 0.801 to 0.842, Pâ <â 0.001) and Câ =â 0.824 for the hospital-based model (95% CI, 0.802 to 0.843, Pâ <â 0.001). CONCLUSION: The TARGET-HF model illustrates that routine consultation codes can be used to build a performant model to identify patients at risk for HF at the time of GP consultation.