Determination of Clinically Acceptable Analytical Variation of Cardiac Troponin at Decision Thresholds.

BACKGROUND: Clinical decision-making for risk stratification for possible myocardial infarction (MI) uses high-sensitivity cardiac troponin (hs-cTn) thresholds that range from the limit of detection to several-fold higher than the upper reference limit (URL). To establish a minimum analytical variation standard, we can quantify the effect of variation on the population clinical measures of safety (sensitivity) and effectiveness [proportion below threshold, or positive predictive value (PPV)]. METHODS: From large datasets of patients investigated for possible MI with the Abbott hs-cTnI and Roche hs-cTnT assays, we synthesized datasets of 1 000 000 simulated patients. Troponin concentrations were randomly varied several times based on absolute deviations of 0.5 to 3 ng/L and relative changes of 2% to 20% around the low-risk threshold (5 ng/L) and URLs, respectively. RESULTS: For both assays at the low-risk thresholds, there were negligible differences in sensitivity (<0.3%) with increasing analytical variation. The proportion of patients characterized as low risk reduced by 30% to 29% (Roche) and 53% to 44% (Abbott). At the URL, increasing analytical variation also did not change sensitivity; the PPV fell by less than 3%. For risk stratification, increased delta thresholds (change between serial troponin concentrations) increased sensitivity at the cost of a decreased percentage of patients below the delta threshold, with the largest changes at the greatest analytical variation. CONCLUSIONS: At the low-risk threshold, analytical variation up to 3 ng/L minimally impacted the safety metric (sensitivity) but marginally reduced effectiveness. Similarly, at the URL even relative variation up to 25% minimally impacted safety metrics and effectiveness. Analytical variation for delta thresholds did not negatively impact sensitivity but decreased effectiveness.

Derivation and Validation of Thresholds Using Synthetic Data Methods for Single-Test Screening of Emergency Department Patients with Possible Acute Myocardial Infarction Using a Point-of-Care Troponin Assay.

BACKGROUND: Single-sample (screening) rule-out of acute myocardial infarction (AMI) with troponin requires derivation of a single-test screening threshold. In data sets with small event numbers, the lowest one or two concentrations of myocardial infarction (MI) patients dictate the threshold. This is not optimal. We aimed to demonstrate a process incorporating both real and synthetic data for deriving such thresholds using a novel pre-production high-precision point-of-care assay. METHODS: cTnI concentrations were measured from thawed plasma using the Troponin I Next (TnI-Nx) assay (i-STAT; Abbott) in adults on arrival to the emergency department with symptoms suggestive of AMI. The primary outcome was an AMI or cardiac death within 30 days. We used internal-external validation with synthetic data production based on clinical and demographic data, plus the measured TnI-Nx concentration, to derive and validate decision thresholds for TnI-Nx. The target low-risk threshold was a sensitivity of 99% and a high-risk threshold specificity of >95%. RESULTS: In total, 1356 patients were included, of whom 191 (14.1%) had the primary outcome. A total of 500 synthetic data sets were constructed. The mean low-risk threshold was determined to be 5 ng/L. This categorized 38% (95% CI, 6%-68%) to low-risk with a sensitivity of 99.0% (95% CI, 98.6%-99.5%) and a negative predictive value of 99.4% (95% CI, 97.6%-99.8%). A similarly derived high-risk threshold of 25 ng/L had a specificity of 95.0% (95% CI, 94.8%-95.1%) and a positive predictive value of 74.8% (95% CI, 71.5%-78.0%). CONCLUSIONS: With the TnI-Nx assay, we successfully demonstrated an approach using synthetic data generation to derive low-risk thresholds for safe and effective screening.

External validation of a rapid algorithm using high-sensitivity troponin assay results for evaluating patients with suspected acute myocardial infarction.

OBJECTIVE: We sought to validate the clinical performance of a rapid assessment pathway incorporating the Siemens Atellica IM high sensitivity cardiac troponin I (hs-cTnI) assay in patients presenting to the emergency department (ED) with suspected acute myocardial infarction (AMI). METHODS: This was a multicentre prospective observational study of adult ED patients presenting to five Australian hospitals between November 2020 and September 2021. Participants included those with symptoms of suspected AMI (without ST-segment elevation MI on presentation ECG). The Siemen's Atellica IM hs-cTnI laboratory-based assay was used to measure troponin concentrations at admission and after 2-3 hours and cardiologists adjudicated final diagnoses. The HighSTEACS diagnostic algorithm was evaluated, incorporating hs-cTnI concentrations at presentation and absolute changes within the first 2 to 3 hours. The primary outcome was index AMI, including type 1 or 2 non-ST segment elevation MI (NSTEMI) or ST-elevation MI (STEMI) following presentation. 30-day major adverse cardiac outcomes (including AMI, urgent revascularisation or cardiac death) were also reported. The trial was registered with the Australian and New Zealand Clinical Trials Registry. RESULTS: 1994 patients were included. The average age was 56.2 years (SD=15.6), and 44.9% were women. 118 (5.9%) patients had confirmed index AMI. The 2-hour algorithm defined 61.3% of patients as low risk. Sensitivity was 99.1% (94.0%-99.9%) and negative predictive value was 99.9% (99.3%-100%). 24.4% of patients were deemed intermediate risk. When applying the parameters for high risk, 252 (14.3%) were identified, with a specificity of 91.5% (88.7%-93.6%) and a PPV of 42.0% (35.6-48.7%). CONCLUSIONS: A 2-hour algorithm based on the HighSTEACS strategy using the Siemens Atellica IM hs-cTnI laboratory-based assay enables safe and efficient risk assessment of emergency patients with suspected AMI. TRIAL REGISTRATION NUMBER: ACTRN12621000053820.

Attitudes towards artificial intelligence in emergency medicine.

OBJECTIVE: To assess Australian and New Zealand emergency clinicians' attitudes towards the use of artificial intelligence (AI) in emergency medicine. METHODS: We undertook a qualitative interview-based study based on grounded theory. Participants were recruited through ED internal mailing lists, the Australasian College for Emergency Medicine Bulletin, and the research teams' personal networks. Interviews were transcribed, coded and themes presented. RESULTS: Twenty-five interviews were conducted between July 2021 and May 2022. Thematic saturation was achieved after 22 interviews. Most participants were from either Western Australia (52%) or Victoria (16%) and were consultants (96%). More participants reported feeling optimistic (10/25) than neutral (6/25), pessimistic (2/25) or mixed (7/25) towards the use of AI in the ED. A minority expressed scepticism regarding the feasibility or value of implementing AI into the ED. Multiple potential risks and ethical issues were discussed by participants including skill loss from overreliance on AI, algorithmic bias, patient privacy and concerns over liability. Participants also discussed perceived inadequacies in existing information technology systems. Participants felt that AI technologies would be used as decision support tools and not replace the roles of emergency clinicians. Participants were not concerned about the impact of AI on their job security. Most (17/25) participants thought that AI would impact emergency medicine within the next 10 years. CONCLUSIONS: Emergency clinicians interviewed were generally optimistic about the use of AI in emergency medicine, so long as it is used as a decision support tool and they maintain the ability to override its recommendations.

Implementation of an integrated emergency department acute atrial fibrillation pathway safely reduces cardioversions and hospitalisations: A comparative pre-post study.

OBJECTIVE: Atrial fibrillation/flutter (AF/AFL) accounts for high rates of ED presentations and hospital admissions. There is increasing evidence to suggest that delaying cardioversion for acute uncomplicated AF is safe, and that many patients will spontaneously revert to sinus rhythm (SR). We conducted a before-and-after evaluation of AF/AFL management after a change in ED pathway using a conservative 'rate-and-wait' approach, incorporating next working day outpatient clinic follow-up and delayed cardioversion if required. METHODS: We performed a before-and-after retrospective cohort study examining outcomes for patients who presented to the ED in Christchurch, New Zealand, with acute uncomplicated AF/AFL in the 1-year period before and after the implementation of a new conservative management pathway. RESULTS: A total of 360 patients were included in the study (182 'Pre-pathway' vs 178 'Post-Pathway'). Compared to the pre-pathway cohort, those managed under the new pathway had an 81.2% reduction in ED cardioversions (n = 32 vs n = 6), and 50.7% reduction in all cardioversions (n = 65 vs n = 32). There was a 31.6% reduction in admissions from ED (n = 54 vs n = 79). ED length of stay (3.9 h vs 3.8 h, net difference -0.1 h, 95% confidence interval [CI] -0.6 to 0.3), 1-year ED AF representation (32.4% vs 26.4%, net difference -6.0% [95% CI -16.0% to 3.9%]), 1-year ED ischaemic stroke presentation (2.2% in both groups) and 7-day all-cause mortality rates (hazard ratio 1.05 [95% CI 0.6 to 1.9]) were all similar. CONCLUSIONS: Using a conservative 'rate-and-wait' strategy with early follow-up for patients presenting to ED with AF/AFL can safely reduce unnecessary cardioversions and avoidable hospitalisations.

Machine learning for diagnosis of myocardial infarction using cardiac troponin concentrations.

Although guidelines recommend fixed cardiac troponin thresholds for the diagnosis of myocardial infarction, troponin concentrations are influenced by age, sex, comorbidities and time from symptom onset. To improve diagnosis, we developed machine learning models that integrate cardiac troponin concentrations at presentation or on serial testing with clinical features and compute the Collaboration for the Diagnosis and Evaluation of Acute Coronary Syndrome (CoDE-ACS) score (0-100) that corresponds to an individual's probability of myocardial infarction. The models were trained on data from 10,038 patients (48% women), and their performance was externally validated using data from 10,286 patients (35% women) from seven cohorts. CoDE-ACS had excellent discrimination for myocardial infarction (area under curve, 0.953; 95% confidence interval, 0.947-0.958), performed well across subgroups and identified more patients at presentation as low probability of having myocardial infarction than fixed cardiac troponin thresholds (61 versus 27%) with a similar negative predictive value and fewer as high probability of having myocardial infarction (10 versus 16%) with a greater positive predictive value. Patients identified as having a low probability of myocardial infarction had a lower rate of cardiac death than those with intermediate or high probability 30 days (0.1 versus 0.5 and 1.8%) and 1 year (0.3 versus 2.8 and 4.2%; P < 0.001 for both) from patient presentation. CoDE-ACS used as a clinical decision support system has the potential to reduce hospital admissions and have major benefits for patients and health care providers.

Personalized diagnosis in suspected myocardial infarction.

BACKGROUND: In suspected myocardial infarction (MI), guidelines recommend using high-sensitivity cardiac troponin (hs-cTn)-based approaches. These require fixed assay-specific thresholds and timepoints, without directly integrating clinical information. Using machine-learning techniques including hs-cTn and clinical routine variables, we aimed to build a digital tool to directly estimate the individual probability of MI, allowing for numerous hs-cTn assays. METHODS: In 2,575 patients presenting to the emergency department with suspected MI, two ensembles of machine-learning models using single or serial concentrations of six different hs-cTn assays were derived to estimate the individual MI probability (ARTEMIS model). Discriminative performance of the models was assessed using area under the receiver operating characteristic curve (AUC) and logLoss. Model performance was validated in an external cohort with 1688 patients and tested for global generalizability in 13 international cohorts with 23,411 patients. RESULTS: Eleven routinely available variables including age, sex, cardiovascular risk factors, electrocardiography, and hs-cTn were included in the ARTEMIS models. In the validation and generalization cohorts, excellent discriminative performance was confirmed, superior to hs-cTn only. For the serial hs-cTn measurement model, AUC ranged from 0.92 to 0.98. Good calibration was observed. Using a single hs-cTn measurement, the ARTEMIS model allowed direct rule-out of MI with very high and similar safety but up to tripled efficiency compared to the guideline-recommended strategy. CONCLUSION: We developed and validated diagnostic models to accurately estimate the individual probability of MI, which allow for variable hs-cTn use and flexible timing of resampling. Their digital application may provide rapid, safe and efficient personalized patient care. TRIAL REGISTRATION NUMBERS: Data of following cohorts were used for this project: BACC ( www. CLINICALTRIALS: gov ; NCT02355457), stenoCardia ( www. CLINICALTRIALS: gov ; NCT03227159), ADAPT-BSN ( www.australianclinicaltrials.gov.au ; ACTRN12611001069943), IMPACT ( www.australianclinicaltrials.gov.au , ACTRN12611000206921), ADAPT-RCT ( www.anzctr.org.au ; ANZCTR12610000766011), EDACS-RCT ( www.anzctr.org.au ; ANZCTR12613000745741); DROP-ACS ( https://www.umin.ac.jp , UMIN000030668); High-STEACS ( www. CLINICALTRIALS: gov ; NCT01852123), LUND ( www. CLINICALTRIALS: gov ; NCT05484544), RAPID-CPU ( www. CLINICALTRIALS: gov ; NCT03111862), ROMI ( www. CLINICALTRIALS: gov ; NCT01994577), SAMIE ( https://anzctr.org.au ; ACTRN12621000053820), SEIGE and SAFETY ( www. CLINICALTRIALS: gov ; NCT04772157), STOP-CP ( www. CLINICALTRIALS: gov ; NCT02984436), UTROPIA ( www. CLINICALTRIALS: gov ; NCT02060760).

The cost savings of the rural accelerated chest pain pathway for low-risk chest pain in rural general practice: a cost minimisation analysis.

Introduction The rural accelerated chest pain pathway (RACPP) has been shown to safely reduce the number of transfers to hospital for patients who present with chest pain to rural general practice. Aim This study aimed to estimate the costs associated with assessing patients with low-risk chest pain using the RACPP in rural general practice compared with transporting such patients to a distant emergency department (ED). Methods This was a retrospective cost minimisation analysis. All patients with low-risk chest pain that were assessed in New Zealand (NZ) rural general practice using the RACPP between 1 June 2018 and 31 December 2019 were asked to participate. The costs incurred by patients were determined by an online survey. Patients were also asked to estimate the costs if they would have been transferred to ED. System costs were obtained from the relevant healthcare organisations. The main outcome measure was the total cost for patients who present with low-risk chest pain. Results In total, 15 patients (22.7% response rate) responded to the survey. Using the RACPP in general practice resulted in a median cost saving of NZ$1184 (95% CI: $1111 to $1468) compared with transferring the same patient to ED. Discussion Although limited by low enrolment, this study suggests that there are significant savings if the RACPP is used to assess patients with low-risk chest pain in rural NZ general practice.

Corrigendum to: The cost savings of the rural accelerated chest pain pathway for low-risk chest pain in rural general practice: a cost minimisation analysis.

Introduction The rural accelerated chest pain pathway (RACPP) has been shown to safely reduce the number of transfers to hospital for patients who present with chest pain to rural general practice. Aim This study aimed to estimate the costs associated with assessing patients with low-risk chest pain using the RACPP in rural general practice compared with transporting such patients to a distant emergency department (ED). Methods This was a retrospective cost minimisation analysis. All patients with low-risk chest pain that were assessed in New Zealand (NZ) rural general practice using the RACPP between 1 June 2018 and 31 December 2019 were asked to participate. The costs incurred by patients were determined by an online survey. Patients were also asked to estimate the costs if they would have been transferred to ED. System costs were obtained from the relevant healthcare organisations. The main outcome measure was the total cost for patients who present with low-risk chest pain. Results In total, 15 patients (22.7% response rate) responded to the survey. Using the RACPP in general practice resulted in a median cost saving of NZ$1184 (95% CI: $1111 to $1468) compared with transferring the same patient to ED. Discussion Although limited by low enrolment, this study suggests that there are significant savings if the RACPP is used to assess patients with low-risk chest pain in rural NZ general practice.

Diagnostic and prognostic performance of the ratio between high-sensitivity cardiac troponin I and troponin T in patients with chest pain.

BACKGROUND: Elevations of high-sensitivity cardiac troponin (hs-cTn) concentrations not related to type 1 myocardial infarction are common in chest pain patients presenting to emergency departments. The discrimination of these patients from those with type 1 myocardial infarction (MI) is challenging and resource-consuming. We aimed to investigate whether the hs-cTn I/T ratio might provide diagnostic and prognostic increment in this context. METHODS: We calculated the hs-cTn I/T ratio in 888 chest pain patients having hs-cTnI (Abbott Laboratories) or hs-cTnT (Roche Diagnostics) concentrations above the respective 99th percentile at 2 hours from presentation. All patients were followed for one year regarding mortality. RESULTS: The median hs-cTn I/T ratio was 3.45 (25th, 75th percentiles 1.80-6.59) in type 1 MI patients (n = 408 ☯46.0%]), 1.18 (0.81-1.90) in type 2 MI patients (n = 56 ☯6.3%]) and 0.67 (0.39-1.12) in patients without MI. The hs-cTn I/T ratio provided good discrimination of type 1 MI from no type 1 MI (area under the receiver-operator characteristic curve 0.89 ☯95% confidence interval 0.86-0.91]), of type 1 MI from type 2 MI (area under the curve 0.81 ☯95% confidence interval 0.74-0.87]), and was associated with type 1 MI in adjusted analyses. The hs-cTn I/T ratio provided no consistent prognostic value. CONCLUSIONS: The hs-cTn I/T ratio appears to be useful for early diagnosis of type 1 MI and its discrimination from type 2 MI in chest pain patients presenting with elevated hs-cTn. Differences in hs-cTn I/T ratio values may reflect variations in hs-cTn release mechanisms in response to different types of myocardial injury.

Chest pain workup in the presence of atrial fibrillation: impacts on troponin testing, myocardial infarction diagnoses, and long-term prognosis.

AIMS: Patients presenting to the emergency department (ED) with chest pain require evaluation for acute coronary syndrome (ACS). Atrial fibrillation (AF) can lead to troponin (cTn) elevation in the absence of ACS. There is limited evidence informing the impact of AF on the diagnostic performance of cTn testing for the diagnosis of Type 1 myocardial infarction (T1MI), or the association between AF and long-term outcomes in this context. METHODS AND RESULTS: This study used the IMPACT and ADAPT study databases to compile a combined cohort of 3496 adults presenting to ED with chest pain between 2007 and 2014, with early cTn testing during ED workup. The mean age was 56.6 years, and 40.2% were female. Outcomes included adjudicated diagnoses for the index admission and mortality to 1-year after presentation. The specificity of initial cTn testing for T1MI diagnosis was lower for patients in AF compared with those not in AF (79.2% vs. 95.4%, P < 0.001), largely due to a relative increase in Type 2 myocardial infarction diagnoses. Sensitivity for T1MI did not differ between patients with or without AF (88.5% vs. 91.5%, P = 0.485). AF was associated with increased 1-year mortality (10.4% vs. 2.3%, P < 0.001), although this was not significant on multivariable analysis. CONCLUSION: The specificity of serial cTn testing for the diagnosis of T1MI in patients presenting to ED with chest pain is reduced in the presence of AF. Further studies are needed to establish whether optimised cTn thresholds for patients with AF can improve workup and outcomes.

Finding acute coronary syndrome with serial troponin testing for rapid assessment of cardiac ischemic symptoms (FAST-TRAC): a study protocol.

OBJECTIVE: To determine the utility of a highly sensitive troponin assay when utilized in the emergency department. METHODS: The FAST-TRAC study prospectively enrolled >1,500 emergency department patients with suspected acute coronary syndrome within 6 hours of symptom onset and 2 hours of emergency department presentation. It has several unique features that are not found in the majority of studies evaluating troponin. These include a very early presenting population in whom prospective data collection of risk score parameters and the physician's clinical impression of the probability of acute coronary syndrome before any troponin data were available. Furthermore, two gold standard diagnostic definitions were determined by a pair of cardiologists reviewing two separate data sets; one that included all local troponin testing results and a second that excluded troponin testing so that diagnosis was based solely on clinical grounds. By this method, a statistically valid head-to-head comparison of contemporary and high sensitivity troponin testing is obtainable. Finally, because of a significant delay in sample processing, a unique ability to define the molecular stability of various troponin assays is possible. TRIAL REGISTRATION: ClinicalTrials.gov Identifier NCT00880802.