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SMARTwatch for the Diagnosis of ST-segment Elevation Myocardial Infarction in Patients With Chest Pain (SMART-CART-AMI)

24. august 2026 opdateret af: Francisco Buendia Santiago, Hospital General Universitario Santa Lucia

Observational and Prospective Diagnostic Validation Study of the SMARTwatch for ST-segment Elevation Myocardial Infarction in Health Area of Cartagena

The main symptom that initiates the diagnostic and therapeutic process for patients with suspected acute coronary syndrome is chest pain. Based on a standard 12-lead electrocardiogram (ECG), patients can be diagnosed with ST-segment elevation myocardial infarction (STEMI), which requires immediate medical treatment. Recently, wearable devices like smartwatches with ECG capabilities have opened new pathways for cardiac triage, but their diagnostic precision and technical viability in a real, unselected Emergency Department setting need to be confirmed.

The primary objective of this prospective, observational study is to compare the diagnostic capacity of a 9-lead ECG obtained with a smartwatch against the standard 12-lead ECG for diagnosing STEMI in patients consulting for chest pain.

During the study, patients evaluated by the on-call cardiologist for ischemic chest pain will undergo their standard care. In addition to the standard 12-lead ECG, a 9-lead ECG will be sequentially recorded using a smartwatch. This is an observational study, meaning the smartwatch recording will not cause any delay in clinical action or negatively impact the patient's standard treatment.

Specifically, the study aims to:

  • Analyze the diagnostic agreement between expert cardiologists when blindly and independently classifying the smartwatch recordings versus the standard ECG recordings as "STEMI" or "non-STEMI".
  • Evaluate the technical feasibility of using the smartwatch in an Emergency Department setting by assessing the percentage of unreadable records due to artifacts.

Studieoversigt

Status

Rekruttering

Betingelser

Intervention / Behandling

Detaljeret beskrivelse

Background and Rationale:

The clinical spectrum of acute coronary syndrome (ACS) is broad, with chest pain being the primary symptom initiating the diagnostic and therapeutic cascade. In patients with ST-segment elevation myocardial infarction (STEMI), immediate reperfusion -primarily via percutaneous coronary intervention (PCI)-is crucial. While primary PCI has significantly reduced mortality, minimizing systemic delays remains vital.

Recently, wearable devices with electrocardiographic (ECG) capabilities have emerged as potential tools for ultra-early cardiac triage. Previous research, such as the SMARTAMI study, demonstrated that a sequential 9-lead smartwatch ECG has high sensitivity and specificity for detecting STEMI. However, these prior studies often compared confirmed myocardial infarction cases with healthy, asymptomatic cohorts in highly controlled environments. There is a critical need to validate the technical feasibility, signal quality, and diagnostic accuracy of this technology in a real-world Emergency Department (ED) setting with unselected patients, where factors like diaphoresis, acute pain, and time urgency complicate the recording process.

Study Design and Clinical Procedures:

This is a prospective, observational diagnostic validation and concordance study conducted in a real-world clinical setting. Patients evaluated by the on-call cardiologist for ischemic-profile chest pain will be consecutively enrolled. The study is purely observational; obtaining the smartwatch ECG will not delay standard clinical care, and standard medical management will remain unaltered.

Following standard protocols, an analog sequential 9-lead ECG (I, II, III, V1-V6) will be recorded using a smartwatch alongside the standard 12-lead ECG.

Blinding and Data Evaluation:

A rigorous double-blind, independent analysis will be performed. The on-call cardiologists responsible for acquiring the tracings in the ED will not participate in their interpretation. Both the standard 12-lead ECGs and the smartwatch ECGs will be completely anonymized using unique alphanumeric codes. Subsequently, independent expert cardiologists will blindly evaluate the tracings, classifying them as "STEMI" or "non-STEMI" without any knowledge of the patient's clinical data or the origin of each specific recording.

Statistical Approach and Sample Size:

Based on prior literature in controlled settings reporting a 93% sensitivity, this real-world study conservatively estimates an 85% expected sensitivity due to ED-specific variables (e.g., signal noise, diaphoresis). To achieve a 10% margin of error with a 95% confidence level, a sample size of 49 confirmed STEMI positive cases is required. Consecutive recruitment will continue uninterrupted until this target is reached. Patients enrolled during this period who are ultimately diagnosed as "non-STEMI" will be retained in the database to calculate the specificity of the device.

Undersøgelsestype

Observationel

Tilmelding (Anslået)

100

Kontakter og lokationer

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Studiesteder

    • Murcia
      • Cartagena, Murcia, Spanien, 30202
        • Rekruttering
        • Hospital General Universitario Santa Lucía
        • Kontakt:
        • Kontakt:
        • Ledende efterforsker:
          • Francisco Buendia Santiago, MD

Deltagelseskriterier

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Berettigelseskriterier

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  • Voksen
  • Ældre voksen

Tager imod sunde frivillige

Ingen

Prøveudtagningsmetode

Ikke-sandsynlighedsprøve

Studiebefolkning

The study population consists of unselected patients presenting to the Emergency Department at Hospital Universitario Santa Lucía (Cartagena) who are evaluated by the on-call cardiologist for ischemic-profile chest pain. This represents a real-world clinical cohort in an acute setting. Patients with extreme hemodynamic instability (where an additional recording would delay critical emergency treatment) and those with baseline electrocardiogram alterations (such as prior left bundle branch block or pacemaker-mediated pacing) that preclude proper ST-segment interpretation are excluded from this population.

Beskrivelse

Inclusion Criteria:

  • Patients evaluated by the on-call cardiologist for chest pain with an ischemic profile.

Exclusion Criteria:

  • Patients with extreme hemodynamic instability where the additional recording would cause an ethically unacceptable delay in their treatment.
  • Patients with a prior diagnosis of left bundle branch block or pacemaker-mediated pacing.
  • Patients who decline participation in the registry.

Studieplan

Dette afsnit indeholder detaljer om studieplanen, herunder hvordan undersøgelsen er designet, og hvad undersøgelsen måler.

Hvordan er undersøgelsen tilrettelagt?

Design detaljer

Kohorter og interventioner

Gruppe / kohorte
Intervention / Behandling
Generel kohorte
Recording a 9-lead ECG with a smartwatch

Hvad måler undersøgelsen?

Primære resultatmål

Resultatmål
Foranstaltningsbeskrivelse
Tidsramme
Smartwatch ECG records' ability to diagnose STEMI
Tidsramme: From enrollment to the blinded analysis at the end of the recruitment
Analyze the diagnostic agreement between expert cardiologists when blindly and independently classifying the smartwatch recordings versus the standard ECG recordings as "STEMI" or "non-STEMI".
From enrollment to the blinded analysis at the end of the recruitment

Samarbejdspartnere og efterforskere

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Sponsor

Publikationer og nyttige links

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Datoer for undersøgelser

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Studer store datoer

Studiestart (Faktiske)

14. august 2026

Primær færdiggørelse (Anslået)

1. februar 2027

Studieafslutning (Anslået)

1. februar 2027

Datoer for studieregistrering

Først indsendt

19. august 2026

Først indsendt, der opfyldte QC-kriterier

19. august 2026

Først opslået (Faktiske)

24. august 2026

Opdateringer af undersøgelsesjournaler

Sidste opdatering sendt (Faktiske)

26. august 2026

Sidste opdatering indsendt, der opfyldte kvalitetskontrolkriterier

24. august 2026

Sidst verificeret

1. august 2026

Mere information

Begreber relateret til denne undersøgelse

Andre undersøgelses-id-numre

  • I-AREA2_26-68_SMART-CART-AMI

Plan for individuelle deltagerdata (IPD)

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