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AliveCor QT Service analyses 30 seconds of a previously acquired electrocardiogram (ECG) from AliveCor designed 6-Lead ambulatory ECG devices analyzed as normal sinus rhythm for QT interval measurements.

AliveCor OT Service is intended for use in a professional medical facility, such as a hospital, clinic, or doctor's office by a qualified health care professional, including trained ECG technician.

AliveCor QT Service is indicated for use on adult patients (older than 18 years). The device has not been tested for and is not intended for pediatric use. The service is not intended for use in life supporting, or sustaining systems, or continuous ECG monitors, or cardiac alarm devices, or OTC use only devices.

AliveCor QT Service is a cloud-based Software as a Medical Device (SaMD) that is used to measure the QT and heart-rate corrected QT ("QTc") interval measurements from electrocardiograms (ECG) recorded from adult patients (older than 18 years) using AliveCordesigned 6-Lead ambulatory ECG devices. AliveCor QT Service provides QT and QTc interval measurements only on ECGs analyzed as Normal Sinus Rhythm by KardiaAI (K201985).

AliveCor QT Service is a prescription (Rx) use only device intended for use by qualified healthcare professionals, including trained ECG technicians. Healthcare professionals can access AliveCor OT Service over the internet from patient management and ECG storage Medical Device Data Systems (MDDS), or from other prescription-use only medical data software devices. These devices provide a previously recorded ECG from an AliveCor-designed 6-Lead ambulatory ECG device, such as the KardiaMobile 6L (K210753), in a compatible format using the AliveCor QT Service's REST-based application program interface (API). REST or REpresentational State Transfer is a software methodology that defines rules for creating web services to access resources over Hypertext Transfer Protocol (HTTP). AliveCor QT Service responds to the analysis request with the following measurements:

• QT interval, measured from the first 30 seconds of the ECG
• Heart-rate corrected QT (QTc) interval based on the Bazett's formula and the Fridericia's ● formula

AliveCor QT Service utilizes various internal algorithms including deep neural networks (DNN) to analyze an ECG to compute the QT interval. AliveCor QT Service also includes algorithms to compute the RR-interval, which is used to provide both the Bazett's and Fridericia corrected OTc intervals. These algorithms were trained and validated on datasets with ECGs from patients representative of the device's intended use. The training included more than 750K ECGs from over 250K patients. The training dataset included more than 200K ECGs with approximately 49% data from females, approximately 70% from subjects who were reported as whites, 3% nonwhites, and 27% from those who did not report their race The validation was conducted on two datasets. The first dataset included more than 34K ECGs with approximately 51% data from females, approximately 80% from subjects who were reported as whites, 3.6% non-whites, and 1 7% from those who did not report their race. The second dataset included 226 ECGs with approximately 60% data from females, approximately 87% from subjects who were reported as whites, 3.2% non-whites, and 10% from those who did not report their race.

Here's a breakdown of the acceptance criteria and the study proving the device meets them, based on the provided FDA 510(k) summary for the AliveCor QT Service:

1. Table of Acceptance Criteria and Reported Device Performance

Note: The FDA 510(k) summary provides a high-level summary of the performance testing. While the acceptance criteria are stated, the precise numerical results for the mean and standard deviation of the interval differences are not explicitly detailed in this public document, beyond the assertion that the device "performs to its specifications" and achieves "substantially equivalent performance."

2. Sample Sizes Used for the Test Set and Data Provenance

• Test Set (Validation Datasets):
  • First Dataset: More than 34,000 ECGs
    • Provenance: Not explicitly stated (e.g., country of origin). Appears to be retrospective, as it's described as a "validation was conducted on two datasets."
    • Demographics: Approximately 51% females, ~80% whites, 3.6% non-whites, and 17% did not report their race.
  • Second Dataset: 226 ECGs
    • Provenance: Not explicitly stated (e.g., country of origin). Appears to be retrospective.
    • Demographics: Approximately 60% females, ~87% whites, 3.2% non-whites, and 10% did not report their race.
• Data Provenance: The document does not specify the country of origin for the validation datasets, only that they contain ECGs from "patients representative of the device's intended use." The testing was "nonclinical" and involved "standards-based and AliveCor proprietary ECG databases." It implies retrospective data collection.

3. Number of Experts Used to Establish Ground Truth for the Test Set and Their Qualifications

The document mentions "expert annotated reference interval from a supine, diagnostic bandwidth, 12-lead ECG" as the ground truth. However, it does not specify the following:

• The exact number of experts used.
• The specific qualifications of those experts (e.g., "radiologist with 10 years of experience" - for ECGs, this would typically involve cardiologists or electrophysiologists).
• The process for their annotation (e.g., independent reviews, consensus).

4. Adjudication Method for the Test Set

The document does not specify an explicit adjudication method (e.g., 2+1, 3+1, none) for the expert annotations used to establish ground truth for the test set. It simply states "expert annotated reference interval."

5. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study

• Was an MRMC study done? No. The document explicitly states: "No clinical testing was required to establish substantial equivalence." This indicates that the study focused on device performance against a predefined ground truth in a non-clinical setting, rather than a human-in-the-loop comparative effectiveness study for human readers.

6. Standalone (Algorithm Only) Performance

• Was a standalone performance study done? Yes. The entire nonclinical testing section describes the performance of the "AliveCor QT Service" (the algorithm) independently against expert-annotated ground truth. The acceptance criteria relate directly to the algorithm's output (mean and standard deviation of interval differences).

7. Type of Ground Truth Used

• Type of Ground Truth: The ground truth used was expert consensus / expert annotated reference interval. Specifically, it states "expert annotated reference interval from a supine, diagnostic bandwidth, 12-lead ECG."

8. Sample Size for the Training Set

• Training Set Sample Size: The training included more than 750,000 ECGs from over 250,000 patients.
  • Demographics: More than 200,000 ECGs within this set had demographic data: ~49% females, ~70% whites, 3% non-whites, and 27% did not report their race.

9. How the Ground Truth for the Training Set Was Established

The document states that the algorithms (including deep neural networks) were "trained and validated on datasets with ECGs from patients representative of the device's intended use." However, it does not explicitly detail how the ground truth for the training set was established. It is common practice for such large datasets to be assembled from institutional databases or clinical trials where ECGs might have pre-existing annotations or be reviewed by a panel of experts, but the specific methodology for establishing ground truth for the training set is not provided in this summary.

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