Quality of heart failure registration in primary care: observations from 1 million electronic health records in the Amsterdam Metropolitan Area.

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 (2.0 %) 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. 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.

Performance of ChatGPT as an AI-assisted decision support tool in medicine: a proof-of-concept study for interpreting symptoms and management of common cardiac conditions (AMSTELHEART-2).

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.

Troponin testing in routine primary care: observations from a dynamic cohort study in the Amsterdam metropolitan area.

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 62.3 % 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). 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.

Diagnostic properties of natriuretic peptides and opportunities for personalized thresholds for detecting heart failure in primary care.

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 (125 ng/L for NT-proBNP and 35 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 (4.5 % 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. CONCLUSIONS: NT-proBNP outperforms BNP for detecting HF in primary care. Personalized instead of universal diagnostic thresholds led to modest improvement.

Characteristics of heart failure in the Amsterdam metropolitan area (AMSTERDAM-HF): Data from a dynamic general practice cohort (2011-2021).

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.

Evaluation of telephone triage among chest pain patients in out-of-hours primary care in the Netherlands (TRACE).

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.

TARGET-HF: developing a model for detecting incident heart failure among symptomatic patients in general practice using routine health care data.

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.

Performance of popular pulse oximeters compared with simultaneous arterial oxygen saturation or clinical-grade pulse oximetry: a cross-sectional validation study in intensive care patients.

OBJECTIVES: To evaluate the performance of direct-to-consumer pulse oximeters under clinical conditions, with arterial blood gas measurement (SaO2) as reference standard. DESIGN: Cross-sectional, validation study. SETTING: Intensive care. PARTICIPANTS: Adult patients requiring SaO2-monitoring. INTERVENTIONS: The studied oximeters are top-selling in Europe/USA (AFAC FS10D, AGPTEK FS10C, ANAPULSE ANP 100, Cocobear, Contec CMS50D1, HYLOGY MD-H37, Mommed YM101, PRCMISEMED F4PRO, PULOX PO-200 and Zacurate Pro Series 500 DL). Directly after collection of a SaO2 blood sample, we obtained pulse oximeter readings (SpO2). SpO2-readings were performed in rotating order, blinded for SaO2 and completed <10 min after blood sample collection. OUTCOME MEASURES: Bias (SpO2-SaO2) mean, root mean square difference (ARMS), mean absolute error (MAE) and accuracy in identifying hypoxaemia (SaO2 ≤90%). As a clinical index test, we included a hospital-grade SpO2-monitor (Philips). RESULTS: In 35 consecutive patients, we obtained 2258 SpO2-readings and 234 SaO2-samples. Mean bias ranged from -0.6 to -4.8. None of the pulse oximeters met ARMS ≤3%, the requirement set by International Organisation for Standardisation (ISO)-standards and required for Food and Drug Administration (FDA) 501(k)-clearance. The MAE ranged from 2.3 to 5.1, and five out of ten pulse oximeters met the requirement of ≤3%. For hypoxaemia, negative predictive values were 98%-99%. Positive predictive values ranged from 11% to 30%. Highest accuracy (95% CI) was found for Contec CMS50D1; 91% (86-94) and Zacurate Pro Series 500 DL; 90% (85-94). The hospital-grade SpO2-monitor had an ARMS of 3.0% and MAE of 1.9, and an accuracy of 95% (91%-97%). CONCLUSION: Top-selling, direct-to-consumer pulse oximeters can accurately rule out hypoxaemia, but do not meet ISO-standards required for FDA-clearance.