Diagnostic value of the cardiac electrical biomarker, a novel <scp>ECG</scp> marker indicating myocardial injury, in patients with symptoms suggestive of non‐<scp>ST</scp>‐elevation myocardial infarction

Strebel, Ivo; Twerenbold, Raphael; Boeddinghaus, Jasper; Abächerli, Roger; Giménez, María Rubini; Wildi, Karin; Grimm, Karin; Puelacher, Christian; Badertscher, Patrick; Sabti, Zaid; Breitenbücher, Dominik; Jann, Janina; Selman, Farah; Lavallaz, Jeanne du Fay de; Schaerli, Nicolas; Nestelberger, Thomas; Stelzig, Claudia; Freese, Michael; Schumacher, Lukas; Oßwald, Stefan; Reichlin, Tobias

doi:10.1111/anec.12538

Cited by 9 publications

(3 citation statements)

References 37 publications

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“…[6][7][8][9] Hence the diagnosis of NSTEMI with ECG alone is difficult and required cardiac enzymes assessment such as cardiac troponin (cTn) and other non-invasive cardiac imaging. 10 http://www. pakheartjournal.com Nonetheless, ECG has a significant logistic advantage over cTn as typically the turnaround time for cTn testing is more than an hour and ECG can be performed immediately in the emergency room at presentation or even before hospital arrival.…”

Section: Introductionmentioning

confidence: 99%

“…pakheartjournal.com Nonetheless, ECG has a significant logistic advantage over cTn as typically the turnaround time for cTn testing is more than an hour and ECG can be performed immediately in the emergency room at presentation or even before hospital arrival. 10,11 However, unlike cardiac enzyme assessment, progress in the interpretation of ECG during last few years is very low. 11 Therefore, it is equally important to evaluate the high risk ECG features and understand their clinical implications in order to optimize the management protocols for the NSTEMI patients.…”

Section: Introductionmentioning

confidence: 99%

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Electrocardiogram Changes in Patients with Positive Troponin I Presenting with Non-ST-Elevation Myocardial Infarction

Khowaja

Khan

et al. 2023

Pak Heart J

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Objectives: Unlike “ST-segment elevation myocardial infarction (STEMI)”, there is a wide spectrum of ECG changes for Non-STEMI (NSTEMI) patients with varying prognostic implications. Therefore, the purpose of this study was to determine the frequency of ECG changes in patients with positive high-sensitive troponins (hs-cTn) presenting with NSTEMI. Methodology: This Cross sectional study included 282 patients with positive hs-cTn diagnosed with NSTEMI. Standard 12-lead ECG was performed for all the patients. The clinical profile and ECG changes such as ST elevation in aVR, T wave inversion, and ST depression were noted. Results: Out of 282 patients, 68.1% (192) were male, mean age was 58.5 ± 10.6 years, 56.7% (160) were hypertensive, and 39.7% (112) were diabetic. The ECG was normal in 8.2% (23) while, 64.5% (182) had ST-depression, out of which 1.1% (2) had ST-depression of <1mm, 78% (142) had ST-depression of 1-2mm, and remaining 20.9% (38) had ST-depression of >2mm. T-wave inversions were observed in 45.7% (129). ST-elevation of ≥1 mm in lead aVR was noted in 19.1% (54) patients. Conclusion: A considerable number of NSTEMI patients with positive hs-cTn showed no specific ECG changes. ST-depression followed by T wave inversion and ST-elevation in aVR were the most commonly observed ECG findings in these patients. Considering the prognostic implications and association of these changes with the severity of diseases, prompt decision-making regarding invasive management strategy could be helpful in improving the outcomes of these patients.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Electrocardiogram Changes in Patients with Positive Troponin I Presenting with Non-ST-Elevation Myocardial Infarction

Khowaja

Khan

et al. 2023

Pak Heart J

View full text Add to dashboard Cite

show abstract

“…An overall picture of language models release and parameters size, with the publicly accessible GPT-4 [48] and recently reported PanGu-Σ [49] models highlighted. case of ECG, groundbreaking ECG technologies and devices, such as Universal ECG TM [40]- [44], can potentially benefit from obtaining a second-opinion of or an early analysis from an AI machine in particular in case of a junior medical doctor, under pressure emergency department practices, as part of a medical education program or in clinically challenging scenarios.…”

Section: Introductionmentioning

confidence: 99%

BioSignal Copilot: Leveraging the power of LLMs in drafting reports for biomedical signals

Liu

Kothur

et al. 2023

Preprint

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Recent advances in Large Language Models (LLMs) have shown great potential in various domains, particularly in processing text-based data. However, their applicability to biomedical time-series signals (e.g. electrograms) remains largely unexplored due to the lack of a signal-to-text (sequence) engine to harness the power of LLMs. The application of biosignals has been growing due to the improvements in the reliability, noise and performance of front-end sensing, and back-end signal processing, despite lowering the number of sensing components (e.g. electrodes) needed for effective and long-term use (e.g. in wearable or implantable devices). One of the most reliable techniques used in clinical settings is producing a technical/clinical report on the quality and features of collected data and using that alongside a set of auxiliary or complementary data (e.g. imaging, blood tests, medical records). This work addresses the missing puzzle in implementing conversational artificial intelligence (AI), a reliable, technical and clinically relevant signal-to-text (Sig2Txt) engine. While medical foundation models can be expected, reports of Sig2Txt engine in large scale can be utilised in years to come to develop foundational models for a unified purpose. In this work, we propose a system (SignalGPT or BioSignal Copilot) that reduces medical signals to a freestyle or formatted clinical, technical report close to a brief clinical report capturing key features and characterisation of input signal. In its ideal form, this system provides the tool necessary to produce the technical input sequence necessary for LLMs as a step toward using AI in the medical and clinical domains as an assistant to clinicians and patients. To the best of our knowledge, this is the first system for bioSig2Txt generation, and the idea can be used in other domains as well to produce technical reports to harness the power of LLMs. This method also improves the interpretability and tracking (history) of information into and out of the AI models. We did implement this aspect through a buffer in our system. As a preliminary step, we verify the feasibility of the BioSignal Copilot (SignalGPT) using a clinical ECG dataset to demonstrate the advantages of the proposed system. In this feasibility study, we used prompts and fine-tuning to prevent fluctuations in response. The combination of biosignal processing and natural language processing offers a promising solution that improves the interpretability of the results obtained from AI, which also leverages the rapid growth of LLMs.

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Changes in Cardiac Electrical Biomarker in Response to Coronary Arterial Occlusion: An Experimental Observation

Chattopadhyay,

Adjei,

Kardos

2024

J. of Cardiovasc. Trans. Res.

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Diagnostic value of the cardiac electrical biomarker, a novel ECG marker indicating myocardial injury, in patients with symptoms suggestive of non‐ST‐elevation myocardial infarction

Abstract: In conclusion, the CEB, an ECG marker of myocardial injury, significantly improves the accuracy and sensitivity of the ECG for the diagnosis of NSTEMI.

Cited by 9 publications

References 37 publications

Electrocardiogram Changes in Patients with Positive Troponin I Presenting with Non-ST-Elevation Myocardial Infarction

Electrocardiogram Changes in Patients with Positive Troponin I Presenting with Non-ST-Elevation Myocardial Infarction

BioSignal Copilot: Leveraging the power of LLMs in drafting reports for biomedical signals

Changes in Cardiac Electrical Biomarker in Response to Coronary Arterial Occlusion: An Experimental Observation

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