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PURPOSE Chest pain frequently poses a diagnostic challenge for general practitioners (GPs). Utilizing risk stratification tools might help GPs to rule out acute coronary syndrome (ACS) and make appropriate referral decisions. We conducted a systematic review of studies evaluating risk stratification tools for chest pain in primary care settings, both with and without troponin assays. Our aims were to assess the performance of tools for ruling out ACS and to provide a comprehensive review of the current evidence. METHODS We searched PubMed and Embase for articles up to October 9, 2023 concerning adult patients with acute chest pain in primary care settings, for whom risk stratification tools (clinical decision rules [CDRs] and/or single biomarker tests) were used. To identify eligible studies, a combination of active learning and backward snowballing was applied. Screening, data extraction, and quality assessment (following the Quality Assessment of Diagnostic Accuracy Studies-2 tool) were performed independently by 2 researchers. RESULTS Of the 1,204 studies screened, 14 were included in the final review. Nine studies validated 7 different CDRs without troponin. Sensitivities ranged from 75.0% to 97.0%, and negative predictive values (NPV) ranged from 82.4% to 99.7%. None of the CDRs outperformed the unaided judgment of GP's. Five studies reported on strategies using troponin measurements. Studies using high-sensitivity troponin showed highest diagnostic accuracy with sensitivity 83.3% to 100% and NPV 98.8% to 100%. CONCLUSION Clinical decision rules without troponin and the use of conventional troponin showed insufficient sensitivity to rule out ACS in primary care and are not recommended as standalone tools. High-sensitivity troponin strategies are promising, but studies are limited. Further prospective validation in primary care is needed before implementation. Key words: acute coronary syndrome; chest pain; clinical decision rules; primary health care; troponin, https://doi.org/10.1370/afm.3141 INTRODUCTION Chest pain often poses a diagnostic challenge for general practitioners (GPs). While chest pain is the hallmark symptom of acute coronary syndrome (ACS), it is often caused by [...]

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. 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. From a database of 968,433 records we identified 19,106 patients (2.0 %) 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: 4.8 %) and inclusion of 2,266 additional patients (underregistration: 11.1 %). The inclusion of miscoded HF episodes advanced the first known date of HF diagnosis in 3.9 % of records, with a median shift of 3.45 years. Episode-level underregistration decreased significantly over time, from 23.8 % in 2006 to 10.0 % in 2021. 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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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. 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. 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 62.3 % were female. Predominant symptoms were chest pain and dyspnea (56.7 %). Additional diagnostic laboratory tests were commonly performed (CRP: 47.7 %, natriuretic peptides: 25.6 %, d-dimer: 21.5 %). Most common diagnoses were musculoskeletal symptoms (21.6 %) and coronary heart disease (7.1 %; 1.1 % ACS). Troponin testing showed sensitivity and specificity of 77.8 % (60.9–89.9) and 94.3 % (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). 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. [ABSTRACT FROM AUTHOR]

PURPOSE To validate a smartphone-operated, single-lead electrocardiography (1L-ECG) device (AliveCor KardiaMobile) with an integrated algorithm for atrial fibrillation (AF) against 12-lead ECG (12L-ECG) in a primary care population. METHODS We recruited consecutive patients who underwent 12L-ECG for any nonacute indication. Patients held a smartphone with connected 1L-ECG while local personnel simultaneously performed 12L-ECG. All 1L-ECG recordings were assessed by blinded cardiologists as well as by the smartphone-integrated algorithm. The study cardiologists also assessed all 12L-recordings in random order as the reference standard. We determined the diagnostic accuracy of the 1L-ECG in detecting AF or atrial flutter (AFL) as well as any rhythm abnormality and any conduction abnormality with the simultaneously performed 12L-ECG as the reference standard. RESULTS We included 214 patients from 10 Dutch general practices. Mean [+ or -] SD age was 64.1 [+ or -] 14.7 years, and 53.7% of the patients were male. The 12L-ECG diagnosed AF/AFL, any rhythm abnormality, and any conduction abnormality in 23, 44, and 28 patients, respectively. The 1L-ECG as assessed by cardiologists had a sensitivity and specificity for AF/AFL of 100% (95% CI, 85.2%-100%) and 100% (95% CI, 98.1 %-100%). The AF detection algorithm had a sensitivity and specificity of 87.0% (95% CI, 66.4%-97.2%) and 97.9% (95% CI, 94.7%-99.4%). The 1L-ECG as assessed by cardiologists had a sensitivity and specificity for any rhythm abnormality of 90.9% (95% CI, 78.3%-97.5%) and 93.5% (95% CI, 88.7%-96.7%) and for any conduction abnormality of 46.4% (95% CI, 27.5%66.1%) and 100% (95% CI, 98.0%-100%). CONCLUSIONS In a primary care population, a smartphone-operated, 1L-ECG device showed excellent diagnostic accuracy for AF/AFL and good diagnostic accuracy for other rhythm abnormalities. The 1L-ECG device was less sensitive for conduction abnormalities. Key words: single-lead; electrocardiography; medical device; atrial fibrillation; cardiac arrhythmia; cardiac conduction system disease; cardiac complexes, premature, INTRODUCTION Patients frequently visit their primary care physician with symptoms that may be due to cardiac arrhythmias. (1) Manifestations include palpitations, light-headedness, and (near) fainting and account for 0.8% to [...]

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. 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 (125 ng/L for NT-proBNP and 35 ng/L for BNP). We used inverse probability of treatment weighting to adjust for confounding. A total of 15,234 patients underwent NP testing, 6,870 with BNP (4.5 % had HF), and 8,364 with NT-proBNP (5.7 % had HF). NT-proBNP was more accurate than BNP, with an AUROC of 89.9 % (95 % CI: 88.4–91.2) vs. 85.9 % (95 % CI 83.5–88.2), with higher sensitivity (95.3 vs. 89.7 %) and specificity (59.1 vs. 58.0 %). Differentiating NP cut-off by clinical variables modestly improved diagnostic accuracy for BNP and NT-proBNP compared with a universal threshold. NT-proBNP outperforms BNP for detecting HF in primary care. Personalized instead of universal diagnostic thresholds led to modest improvement. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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 (n  = 25,524) and validation (n  = 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 C = 0.822 for age alone (95% CI, 0.801 to 0.842, P  < 0.001) and C = 0.824 for the hospital-based model (95% CI, 0.802 to 0.843, P  < 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. [ABSTRACT FROM AUTHOR]