Accuracy of pre-hospital HEART score risk classification using point of care versus high sensitive troponin in suspected NSTE-ACS

External validation of the preHEART score and comparison with current clinical risk scores for prehospital risk assessment in patients with suspected NSTE-ACS

BACKGROUND

Emergency Medical Services (EMS) studies have shown that prehospital risk stratification and triage decisions in patients with suspected non-ST-elevation acute coronary syndrome (NSTE-ACS) can be improved using clinical risk scores with point-of-care (POC) troponin. In current EMS studies, three different clinical risk scores are used in patients suspected of NSTE-ACS: the prehospital History, ECG, Age, Risk and Troponin (preHEART) score, History, ECG, Age, Risk and Troponin (HEART) score and Troponin-only Manchester Acute Coronary Syndromes (T-MACS). The preHEART score lacks external validation and there exists no prospective comparative analysis of the different risk scores within the prehospital setting. The aim of this analysis is to externally validate the preHEART score and compare the diagnostic performance of the these three clinical risk scores and POC-troponin.

METHODS

Prespecified analysis from a prospective, multicentre, cohort study in patients with suspected NSTE-ACS who were transported to an ED between April 2021 and December 2022 in the Netherlands. Risk stratification is performed by EMS personnel using preHEART, HEART, T-MACS and POC-troponin. The primary end point was the hospital diagnosis of NSTE-ACS. The diagnostic performance was expressed as area under the receiver operating characteristic (AUROC), sensitivity, specificity, negative predictive value (NPV) and positive predictive value (PPV).

RESULTS

A total of 823 patients were included for external validation of the preHEART score, final hospital diagnosis of NSTE-ACS was made in 29% (n=235). The preHEART score classified 27% as low risk, with a sensitivity of 92.8% (95% CI 88.7 to 95.7) and NPV of 92.3% (95% CI 88.3 to 95.1). The preHEART classified 9% of the patients as high risk, with a specificity of 98.5% (95% CI 97.1 to 99.3) and PPV of 87.7% (95% CI 78.3 to 93.4). Data for comparing clinical risk scores and POC-troponin were available in 316 patients. No difference was found between the preHEART score and HEART score (AUROC 0.83 (95% CI 0.78 to 0.87) vs AUROC 0.80 (95% CI 0.74 to 0.85), p=0.19), and both were superior compared with T-MACS (AUROC 0.72 (95% CI 0.66 to 0.79), p≤0.001 and p=0.03, respectively) and POC-troponin measurement alone (AUROC 0.71 (95% CI 0.64 to 0.78), p<0.001 and p=0.01, respectively).

CONCLUSION

On external validation, the preHEART demonstrates good overall diagnostic performance as a prehospital risk stratification tool. Both the preHEART and HEART scores have better overall diagnostic performance compared with T-MACS and sole POC-troponin measurement. These data support the implementation of clinical risk scores in prehospital clinical pathways.

TRIAL REGISTRATION NUMBER

NCT05243485.

Artificial Intelligence in Point-of-Care Biosensing: Challenges and Opportunities

The integration of artificial intelligence (AI) into point-of-care (POC) biosensing has the potential to revolutionize diagnostic methodologies by offering rapid, accurate, and accessible health assessment directly at the patient level. This review paper explores the transformative impact of AI technologies on POC biosensing, emphasizing recent computational advancements, ongoing challenges, and future prospects in the field. We provide an overview of core biosensing technologies and their use at the POC, highlighting ongoing issues and challenges that may be solved with AI. We follow with an overview of AI methodologies that can be applied to biosensing, including machine learning algorithms, neural networks, and data processing frameworks that facilitate real-time analytical decision-making. We explore the applications of AI at each stage of the biosensor development process, highlighting the diverse opportunities beyond simple data analysis procedures. We include a thorough analysis of outstanding challenges in the field of AI-assisted biosensing, focusing on the technical and ethical challenges regarding the widespread adoption of these technologies, such as data security, algorithmic bias, and regulatory compliance. Through this review, we aim to emphasize the role of AI in advancing POC biosensing and inform researchers, clinicians, and policymakers about the potential of these technologies in reshaping global healthcare landscapes.

Management of patients suspected for non-ST elevation-acute coronary syndrome in the prehospital phase

The management of patients with suspected acute coronary syndrome, especially in prehospital settings, is challenging. This Special Report focuses on studies in emergency medical services concerning chest pain patients' triage and risk stratification. In addition, it emphasizes advancements in point-of-care cardiac troponin testing. These developments are compared with in-hospital guidelines, proposing an initial framework for a new acute care pathway. This pathway integrates a risk stratification tool with high-sensitivity cardiac troponin testing, aiming to deliver optimal care and collaboration within the acute care chain. It has the potential to contribute to a significant reduction in hospital referrals, reduce observation time and overcrowding at emergency departments and hospital admissions.

Prehospital stratification and prioritisation of non-ST-segment elevation acute coronary syndrome patients (NSTEACS): the MARIACHI scale

OBJECTIVE

The objective of this study was to develop and validate a risk scale (MARIACHI) for patients classified as non-ST-segment elevation acute coronary syndrome (NSTEACS) in a prehospital setting with the ability to identify patients at an increased risk of mortality at an early stage.

METHODS

A retrospective observational study conducted in Catalonia over two periods: 2015-2017 (development and internal validation cohort) and Aug 2018-Jan 2019 (external validation cohort). We included patients classified as prehospital NSTEACS, assisted by an advanced life support unit and requiring hospital admission. The primary outcome was in-hospital mortality. Cohorts were compared using logistic regression and a predictive model was created using bootstrapping techniques.

RESULTS

The development and internal validation cohort included 519 patients. The model is composed of five variables associated with hospital mortality: age, systolic blood pressure, heart rate > 95 bpm, Killip-Kimball III-IV and ST depression ≥ 0.5 mm. The model showed good overall performance (Brier = 0.043) and consistency in discrimination (AUC 0.88, 95% CI 0.83-0.92) and calibration (slope = 0.91; 95% CI 0.89-0.93). We included 1316 patients for the external validation sample. There was no difference in discrimination (AUC 0.83, 95% CI 0.78-0.87; DeLong Test p = 0.071), but there was in calibration (p < 0.001), so it was recalibrated. The finally model obtained was stratified and scored into three groups according to the predicted risk of patient in-hospital mortality: low risk: < 1% (-8 to 0 points), moderate risk: 1-5% (+ 1 to + 5 points) and high risk: > 5% (6-12 points).

CONCLUSION

The MARIACHI scale showed correct discrimination and calibration to predict high-risk NSTEACS. Identification of high-risk patients may help with treatment and low referral decisions at the prehospital level.

Consequences of different cut-off values for high-sensitivity cardiac troponin for risk stratification of patients suspected for NSTE-ACS with a modified HEART score

Aim: This study aims to enhance prehospital risk assessment for suspected non-ST-elevation acute coronary syndrome (NSTE-ACS) patients using the HEART-score. By incorporating novel point-of-care high-sensitivity cardiac troponin devices, a modified HEART-score was developed and compared with the conventional approach. Patients & methods: Troponin points within the modified HEART-score are based on values below the limit of quantitation (LoQ), between the LoQ and 99th percentile and above the 99th percentile of the used device. A total HEART-score of three or lower is considered low-risk for major adverse cardiac events. Results & conclusion: The number of low-risk patients decreased based on the modified HEART-score. The sensitivity and negative predictive value increased which suggests increasing safety in ruling out patients with suspected NSTE-ACS.

Performance of a prehospital HEART score in patients with possible myocardial infarction: a prospective evaluation

INTRODUCTION

The History, Electrocardiogram (ECG), Age, Risk Factors and Troponin (HEART) score is commonly used to risk stratify patients with possible myocardial infarction as low risk or high risk in the Emergency Department (ED). Whether the HEART score can be used by paramedics to guide care were high-sensitivity cardiac troponin testing available in a prehospital setting is uncertain.

METHODS

In a prespecified secondary analysis of a prospective cohort study where paramedics enrolled patients with suspected myocardial infarction, a paramedic Heart, ECG, Age, Risk Factors (HEAR) score was recorded contemporaneously, and a prehospital blood sample was obtained for subsequent cardiac troponin testing. HEART and modified HEART scores were derived using laboratory contemporary and high-sensitivity cardiac troponin I assays. HEART and modified HEART scores of ≤3 and ≥7 were applied to define low-risk and high-risk patients, and performance was evaluated for an outcome of major adverse cardiac events (MACEs) at 30 days.

RESULTS

Between November 2014 and April 2018, 1054 patients were recruited, of whom 960 (mean 64 (SD 15) years, 42% women) were eligible for analysis and 255 (26%) experienced a MACE at 30 days. A HEART score of ≤3 identified 279 (29%) as low risk with a negative predictive value of 93.5% (95% CI 90.0% to 95.9%) for the contemporary assay and 91.4% (95% CI 87.5% to 94.2%) for the high-sensitivity assay. A modified HEART score of ≤3 using the limit of detection of the high-sensitivity assay identified 194 (20%) patients as low risk with a negative predictive value of 95.9% (95% CI 92.1% to 97.9%). A HEART score of ≥7 using either assay gave a lower positive predictive value than using the upper reference limit of either cardiac troponin assay alone.

CONCLUSIONS

A HEART score derived by paramedics in the prehospital setting, even when modified to harness the precision of a high-sensitivity assay, does not allow safe rule-out of myocardial infarction or enhanced rule-in compared with cardiac troponin testing alone.

Ruling out acute coronary syndrome in primary care with a clinical decision rule and a capillary, high-sensitive troponin I point of care test: study protocol of a diagnostic RCT in the Netherlands (POB HELP)

INTRODUCTION

Chest pain is a common reason for consultation in primary care. To rule out acute coronary syndrome (ACS), general practitioners (GP) refer 40%-70% of patients with chest pain to the emergency department (ED). Only 10%-20% of those referred, are diagnosed with ACS. A clinical decision rule, including a high-sensitive cardiac troponin-I point-of-care test (hs-cTnI-POCT), may safely rule out ACS in primary care. Being able to safely rule out ACS at the GP level reduces referrals and thereby alleviates the burden on the ED. Moreover, prompt feedback to the patients may reduce anxiety and stress.

METHODS AND ANALYSIS

The POB HELP study is a clustered randomised controlled diagnostic trial investigating the (cost-)effectiveness and diagnostic accuracy of a primary care decision rule for acute chest pain, consisting of the Marburg Heart Score combined with a hs-cTnI-POCT (limit of detection 1.6 ng/L, 99th percentile 23 ng/L, cut-off value between negative and positive used in this study 3.8 ng/L). General practices are 2:1 randomised to the intervention group (clinical decision rule) or control group (regular care). In total 1500 patients with acute chest pain are planned to be included by GPs in three regions in The Netherlands. Primary endpoints are the number of hospital referrals and the diagnostic accuracy of the decision rule 24 hours, 6 weeks and 6 months after inclusion.

ETHICS AND DISSEMINATION

The medical ethics committee Leiden-Den Haag-Delft (the Netherlands) has approved this trial. Written informed consent will be obtained from all participating patients. The results of this trial will be disseminated in one main paper and additional papers on secondary endpoints and subgroup analyses.

TRIAL REGISTRATION NUMBERS

NL9525 and NCT05827237.

Early risk assessment in patients with suspected NSTE-ACS; a retrospective cohort study

INTRODUCTION

Chest pain is among the most common reasons for Emergency Department (ED) presentation, while most patients should be considered low risk for Acute Coronary Syndrome (ACS). Management of these patients places a significant burden on our health care system. Various risk scores have been developed to facilitate the triage of patients with chest pain. However, it remains unclear which score performs best in identifying low risk patients, in various settings. The aim of this study was to determine which risk score performs best in ruling out non-ST elevation ACS (NSTE-ACS).

METHODS

Data was collected from all patients >18 years presenting to the ED between 01 and 01-2019 and 01-07-2019, if they were suspected of NSTE-ACS. Primary endpoint was NSTE-ACS during presentation to the ED or hospitalization, according to the 2020 ESC guidelines. In a secondary analysis we determined the number low-risk patients, at set safety levels of 95% and 98%.

RESULTS

A total of 536 patients were included, 192 (35.9%) were admitted to the hospital and NSTE-ACS occurred in 134 of 536 patients (25.0%). When areas under the curve (AUC) were compared, pre-HEART (0.869; CI 0.835-0.903), T-MACS (0.862; CI 0.825-0.898) and HEART (0.850; CI 0.815-0.885) performed best. At a safety level of 98%, the HEART score was the best performing risk score and identified 28.9% of patients as low risk, and missed 0 cases of NSTE-ACS. Followed by the pre-HEART score, which identified 18.3% of all patients as low risk, and missed 0% of NSTE-ACS.

CONCLUSIONS

The newly developed pre-HEART score is both practical and has accurate diagnostic properties, closely followed by the HEART score, and T-MACS. New pre-hospital risk scores are promising and much needed. Future studies should focus on the usage of pre-hospital scores for triage of patients with chest pain, in order to reduce the burden on emergency health care.

Prehospital risk assessment in patients suspected of non-ST-segment elevation acute coronary syndrome: a systematic review and meta-analysis

OBJECTIVE

To review, inventory and compare available diagnostic tools and investigate which tool has the best performance for prehospital risk assessment in patients suspected of non-ST-segment elevation acute coronary syndrome (NSTE-ACS).

METHODS

Systematic review and meta-analysis. Medline and Embase were searched up till 1 April 2021. Prospective studies with patients, suspected of NSTE-ACS, presenting in the primary care setting or by emergency medical services (EMS) were included. The most important exclusion criteria were studies including only patients with ST-elevation myocardial infarction and studies before 1995, the pretroponin era. The primary end point was the final hospital discharge diagnosis of NSTE-ACS or major adverse cardiac events (MACE) within 6 weeks. Risk of bias was evaluated by the Quality Assessment of Diagnostic Accuracy Studies Criteria.

MAIN OUTCOME AND MEASURES

Sensitivity, specificity and likelihood ratio of findings for risk stratification in patients suspected of NSTE-ACS.

RESULTS

In total, 15 prospective studies were included; these studies reflected in total 26 083 patients. No specific variables related to symptoms, physical examination or risk factors were useful in risk stratification for NSTE-ACS diagnosis. The most useful electrocardiographic finding was ST-segment depression (LR+3.85 (95% CI 2.58 to 5.76)). Point-of-care troponin was found to be a strong predictor for NSTE-ACS in primary care (LR+14.16 (95% CI 4.28 to 46.90) and EMS setting (LR+6.16 (95% CI 5.02 to 7.57)). Combined risk scores were the best for risk assessment in an NSTE-ACS. From the combined risk scores that can be used immediately in a prehospital setting, the PreHEART score, a validated combined risk score for prehospital use, derived from the HEART score (History, ECG, Age, Risk factors, Troponin), was most useful for risk stratification in patients with NSTE-ACS (LR+8.19 (95% CI 5.47 to 12.26)) and for identifying patients without ACS (LR-0.05 (95% CI 0.02 to 0.15)).

DISCUSSION

Important study limitations were verification bias and heterogeneity between studies. In the prehospital setting, several diagnostic tools have been reported which could improve risk stratification, triage and early treatment in patients suspected for NSTE-ACS. On-site assessment of troponin and combined risk scores derived from the HEART score are strong predictors. These results support further studies to investigate the impact of these new tools on logistics and clinical outcome.

FUNDING

This study is funded by ZonMw, the Dutch Organisation for Health Research and Development.

TRIAL REGISTRATION NUMBER

This meta-analysis was published for registration in PROSPERO prior to starting (CRD York, CRD42021254122).

Referral decisions based on a pre-hospital HEART score in suspected non-ST-elevation acute coronary syndrome: final results of the FamouS Triage study

AIMS

Although pre-hospital risk stratification of patients with suspected non-ST-elevation acute coronary syndrome (NSTE-ACS) by ambulance paramedics is feasible, it has not been investigated in daily practice whether referral decisions based on this risk stratification is safe and does not increase major adverse cardiac events (MACE). In Phase III of the FamouS Triage study, it was investigated whether referral decisions by ambulance paramedics based on a pre-hospital HEART score, is non-inferior to routine management.

METHODS AND RESULTS

FamouS Triage Phase III is a non-inferiority study, comparing the occurrence of MACE before (Phase II) and after (Phase III) implementation of referral decisions based on a pre-hospital HEART score. In Phase II, all patients were risk-stratified and referred to the hospital; in Phase III, low-risk patients (HEART score ≤ 3) were not referred. Primary endpoint was MACE (acute coronary syndrome, revascularization, or death) within 45 days. A total of 1236 patients were included. Mean age was 63 years, 43% were female, 700 patients were included in the second phase and 536 in the third phase in which 149 low-risk patients (28%) were not transferred to the hospital. Occurrence of 45 days MACE was 16.6% in Phase II and 15.7% in Phase III (P = 0.67). Percentage MACE in low-risk patients was 2.9% in Phase II and 1.3% in Phase III. After adjustments for differences in baseline variables, the hazard ratio of 45 days MACE in Phase III was 0.88 (95% confidence interval 0.63-1.25) as compared to Phase II.

CONCLUSION

Pre-hospital risk stratification of patients with suspected NSTE-ACS, avoiding hospitalization of a substantial number of low-risk patients, seems feasible and non-inferior to transferring all patients to the hospital.

URGENT 1.5: diagnostic accuracy of the modified HEART score, with fingerstick point-of-care troponin testing, in ruling out acute coronary syndrome

Background

The HEART score is a validated risk stratification tool for chest pain patients presenting to the emergency department and was recently investigated for implementation in a pre-hospital setting. Fingerstick (capillary blood) point-of-care (POC) troponin testing enables quick measurements outside the hospital and seems easier to implement than the current venous blood sampling techniques. This study investigates the diagnostic accuracy of the modified HEART score, integrating fingerstick POC troponin testing, in ruling out acute coronary syndrome (ACS).

Methods

The data of 96 patients with chest pain, included in a study investigating a novel POC troponin device under development at the cardiac emergency department, were analysed retrospectively. Based on the patients’ admission data and capillary POC high-sensitivity troponin I (hs-cTnI) results, the modified HEART score was determined. The outcome measure, for evaluating the diagnostic accuracy of the modified HEART score, was the occurrence of ACS.

Results

Of the total study population, 33 patients (34%) were diagnosed with ACS. Seventeen patients (18%) were classified as low risk (0–3 points) and one patient (6%) in this group was diagnosed with ACS. The sensitivity and negative predictive value of the modified HEART score was 97.0 and 97.6%, respectively.

Conclusion

The modified HEART score, integrating capillary POC hs-cTnI results, is a promising tool for ruling out ACS in patients with chest pain presenting to the cardiac emergency department. These results encourage prospective investigation into the integration of fingerstick POC troponin testing in the modified HEART score in a pre-hospital setting.

Supplementary Information

The online version of this article (10.1007/s12471-021-01646-8) contains supplementary material, which is available to authorized users.

Prehospital troponin as a predictor of early clinical deterioration

BACKGROUND AND OBJECTIVES

Elevated troponin T (cTnT) values are associated with comorbidities and early mortality, in both cardiovascular and noncardiovascular diseases. The objective of this study is to evaluate the prognostic accuracy of the sole utilization of prehospital point-of-care cardiac troponin T to identify the risk of early in-hospital deterioration, including mortality within 28 days.

METHODS

We conducted a prospective, multicentric, controlled, ambulance-based, observational study in adults with acute diseases transferred with high priority by ambulance to emergency departments, between 1 January and 30 September 2020. Patients with hospital diagnosis of acute coronary syndrome were excluded. The discriminative power of the predictive cTnT was assessed through a discrimination model trained using a derivation cohort and evaluated by the area under the curve of the receiver operating characteristic on a validation cohort.

RESULTS

A total of 848 patients were included in our study. The median age was 68 years (25th-75th percentiles: 50-81 years), and 385 (45.4%) were women. The mortality rate within 28 days was 12.4% (156 cases). The predictive ability of cTnT to predict mortality presented an area under the curve of 0.903 (95% CI: 0.85-0.954; P < .001). Risk stratification was performed, resulting in three categories with the following optimal cTnT cut-off points: high risk greater than or equal to 100, intermediate risk 40-100 and low risk less than 40 ng/L. In the high-risk group, the mortality rate was 61.7%, and on the contrary, the low-risk group presented a mortality of 2.3%.

CONCLUSIONS

The implementation of a routine determination of cTnT on the ambulance in patients transferred with high priority to the emergency department can help to stratify the risk of these patients and to detect unknown early clinical deterioration.

Development of a prehospital prediction model for risk stratification of patients with chest pain

INTRODUCTION

Chest pain is one of the most common reasons for contacting the emergency medical services (EMS). About 15% of these chest pain patients have a high-risk condition, while many of them have a low-risk condition with no need for acute hospital care. It is challenging to at an early stage distinguish whether patients have a low- or high-risk condition. The objective of this study has been to develop prediction models for optimising the identification of patients with low- respectively high-risk conditions in acute chest pain early in the EMS work flow.

METHODS

This prospective observational cohort study included 2578 EMS missions concerning patients who contacted the EMS in a Swedish region due to chest pain in 2018. All the patients were assessed as having a low-, intermediate- or high-risk condition, i.e. occurrence of a time-sensitive diagnosis at discharge from hospital. Multivariate regression analyses using data on symptoms and symptom onset, clinical findings including ECG, previous medical history and Troponin T were carried out to develop models for identification of patients with low- respectively high-risk conditions. Developed models where then tested hold-out data set for internal validation and assessing their accuracy.

RESULTS

Prediction models for risk-stratification based on variables mutual for both low- and high-risk prediction were developed. The variables included were: age, sex, previous medical history of kidney disease, atrial fibrillation or heart failure, Troponin T, ST-depression on ECG, paleness, pain debut during activity, constant pain, pain in right arm and pressuring pain quality. The high-risk model had an area under the receiving operating characteristic curve of 0.85 and the corresponding figure for the low-risk model was 0.78.

CONCLUSIONS

Models based on readily available information in the EMS setting can identify high- and low-risk conditions with acceptable accuracy. A clinical decision support tool based on developed models may provide valuable clinical guidance and facilitate referral to less resource-intensive venues.