Personalized diagnosis in suspected myocardial infarction

Background: In suspected myocardial infarction (MI), guidelines recommend using high-sensitivity cardiac troponin (hscTn)- 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

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Exercise-associated hyponatraemia on the Kokoda Trail

Objective: The objective of the present study was to determine the prevalence of exercise-associated hyponatraemia in hikers/trekkers along the Kokoda Trail. Methods: This was a cross-sectional study of 191 trekkers on the Kokoda Trail, Papua New Guinea. Blood was taken and analysed immediately using point-of-care technology 2days walk from each end of the Trail. Results: The main outcome measure was hyponatraemia defined as serum sodium level less than 135mmol/L. Three participants (1.6%, 95% CI 0.5-4.5%) were found to have mild hyponatraemia. The hyponatraemic group had a median estimated fluid intake on the day of testing that was almost double that of the normal sodium group (6L vs 3.3L). Conclusion: Exercise-associated hyponatraemia occurs in trekkers on the Kokoda Trail. Strategies for prevention of exercise-associated hyponatraemia should be delivered to trekkers via the trekking companies, chiefly focussing on only drinking in response to thirst.</p

A risk assessment score and initial high-sensitivity troponin combine to identify low risk of acute myocardial infarction in the emergency department

Objectives: Early discharge of patients with presentations triggering assessment for possible acute coronary syndrome (ACS) is safe when clinical assessment indicates low risk, biomarkers are negative, and electrocardiograms (ECGs) are nonischemic. We hypothesized that the Emergency Department Assessment of Chest Pain Score (EDACS) combined with a single measurement of high-sensitivity cardiac troponin (hs-cTn) could allow early discharge of a clinically meaningful proportion of patients. Methods: We pooled data from four patient cohorts from New Zealand and Australia presenting to an emergency department with symptoms suggestive of ACS. The primary outcome was major adverse cardiac events (MACE) within 30 days of presentation. In patients with a nonischemic ECG we evaluated the sensitivity for MACE and percentage low risk of every combination of high-sensitivity cardiac troponin T (hs-cTnT) concentration and high-sensitivity cardiac troponin I (hs-cTnI) concentration with EDACS. We used a standard smoothing technique on the probability density function for hs-cTn and EDACS and applied bootstrapping to determine the optimal threshold combinations, namely, the combination that maximized the percentage low risk with ≥98.5% sensitivity for MACE. Results: From 2,536 patients, 2,258 presented without an ischemic ECG of whom 272 (12.1%) had a MACE within 30 days. The optimal threshold for hs-cTnI was 7 ng/L combined with an EDACS threshold of 16 (36.8% patients low risk). The optimal thresholds for hs-cTnT were 8 ng/L combined with an EDACS threshold of 15 (30.2% patients low risk). Conclusion: Single measurements of both hs-cTnI and hs-cTnT at presentation combined with EDACS to identify over 30% of patients as low risk and therefore eligible for safe early discharge after only one blood draw.</p

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.</p

Detectable high-sensitivity cardiac troponin within the population reference interval conveys high 5-year cardiovascular risk: an observational study

Increased cardiac troponin I or T detected by high-sensitivity assays (hs-cTnI or hs-cTnT) confers an increased risk of adverse prognosis. We determined whether patients presenting with putatively normal, detectable cTn concentrations [> limit of detection and < upper reference limit (URL)] have increased risk of major adverse cardiovascular events (MACE) or all-cause mortality.A prospective 5-year follow-up of patients recruited in the emergency department with possible acute coronary syndrome (ACS) and cTn concentrations measured with hs-cTnI (Abbott) and hs-cTnT (Roche) assays. Cox regression models were generated with adjustment for covariates in those without MACE on presentation. Hazard ratios (HRs) for hs-cTn were calculated relative to the HRs at the median concentration.Of 1113 patients, 836 were without presentation MACE. Of these, 138 incurred a MACE and 169 died during a median 5.8-year follow-up. HRs for MACE at the URLs were 2.3 (95% CI, 1.7-3.2) for hs-cTnI and 1.8 (95% CI, 1.3-2.4) for hs-cTnT. Corresponding HRs for mortality were 1.7 (95% CI, 1.2-2.2) for hs-cTnI and 2.3 (95 % CI, 1.7-3.1) for hs-cTnT. The HR for MACE increased with increasing hs-cTn concentration similarly for both assays, but the HR for mortality increased at approximately twice the rate for hs-cTnT than hs-cTnI. Patients with hs-cTnI ≥10 ng/L or hs-cTnT ≥16 ng/L had the same percentage of MACE at 5-year follow-up (33%) as patients with presentation MACE.Many patients with ACS ruled out and putatively normal but detectable hs-cTnI concentrations are at similar long-term risk as those with MACE. hs-cTnT concentrations are more strongly associated with 5-year mortality than hs-cTnI

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 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 low59 probability as having myocardial infarction than fixed cardiac troponin thresholds (61% versus 27%) with a similar negative predictive value, and fewer as high-probability for 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 one 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 healthcare providers