(19 days)
The CardioServer ECG Management System software is intended to be marketed to medical professionals and for point-of-care use. The software is designed to provide a database used through out the medical community to store, display, edit and print high resolution ECG data received from devices such as electrocardiographs.
The CardioServer ECG Management System software allows medical professionals responsible for the diagnosis and treatment of patients (adult and pediatric) with heart disease to: review and edit specific patient ECG data including intervals such as QT measurements and algorithm generated preliminary interpretative statements. ECG records are all associated by patient ID and other demographic data. Secure access to the database is provided.
CardioServer ECG Management System is a software only ECG management database that stores, displays, and prints high resolution ECG data transferred from a Datrix Cardio WiFi electrocardiograph device. All ECG records are associated by patient ID, and a final record including physician interpretation can be created.
The software system analyzes data using an ECG analysis algorithm developed under direction of Dr. Peter MacFarlane, University of Glasgow (note: the same algorithm is contained in the predicate device to which equivalency is being claimed). The ECG display is able to show 1, 3, or 12 leads at once, full disclosure, user-selected strips, and interpretations editable bv physician. Hardware requirements: are Windows 2000 or 2003 Server operating system; Pentium IV, 2GHz (minimum); 512 MB RAM (minimum); 10/100 Ethernet (minimum); RAID 5 storage; 1024x768 monitor; and standard back-up technology.
The provided text describes a 510(k) summary for the Datrix CardioServer ECG Management System. However, it does not contain specific acceptance criteria, a detailed study proving the device meets criteria, or the types of quantitative performance metrics typically associated with AI/ML device evaluations.
Instead, the submission focuses on:
- Establishing substantial equivalence to a predicate device (Quinton Pyramis ECG Management System K032038).
- Describing the software's functionality, intended use, and hardware requirements.
- Stating compliance with the FDA Guidance Document: "General Principles of Software Validation."
- Highlighting that the device utilizes the same ECG analysis algorithm (University of Glasgow ECG Algorithm) as the predicate device.
Given this, I cannot provide the requested information in the format specified because the document does not contain it. The provided text primarily addresses regulatory compliance through substantial equivalence, general software validation, and technological comparison to a predicate device. It lacks the details of a performance study with specific acceptance criteria and outcome metrics for algorithmic performance.
Here's what I can extract based on the provided text, and where information is missing:
1. Table of Acceptance Criteria and Reported Device Performance:
| Acceptance Criteria | Reported Device Performance |
|---|---|
| Not specified in the document. The document primarily focuses on software validation and equivalence to a predicate device, rather than explicit performance-based acceptance criteria for the algorithm's diagnostic accuracy. | The device meets the "FDA Guidance Document: General Principles of Software Validation; Final Guidance for Industry and FDA Staff with acceptable results..." |
| "...demonstrating substantial equivalence [to the predicate device]." | |
| The device utilizes the University of Glasgow ECG Algorithm, which is also present in the predicate device. |
2. Sample size used for the test set and the data provenance:
- Test Set Sample Size: Not specified.
- Data Provenance: Not specified. The document mentions the University of Glasgow ECG Algorithm, implying its origin, but does not detail a specific dataset used for this device's testing or validation of the algorithm's performance.
3. Number of experts used to establish the ground truth for the test set and their qualifications:
- Not specified. The document does not describe a performance study involving expert-established ground truth. Interpreted statements are "editable by physician," but this pertains to clinical use, not the validation process.
4. Adjudication method for the test set:
- Not specified.
5. If a multi-reader multi-case (MRMC) comparative effectiveness study was done, and its effect size:
- No, an MRMC study was not described. The document does not mention any studies involving human readers or comparative effectiveness with AI assistance.
6. If a standalone (algorithm only without human-in-the-loop performance) was done:
- A standalone performance study of the algorithm's diagnostic accuracy, as typically reported today, is not detailed. The document states: "The software system analyzes data using an ECG analysis algorithm developed under direction of Dr. Peter MacFarlane, University of Glasgow (note: the same algorithm is contained in the predicate device to which equivalency is being claimed)." This indicates the algorithm itself has a history, but a specific standalone validation study for this device is not provided in terms of performance metrics. The testing focused on software validation and functionality.
7. The type of ground truth used:
- Not specified. For the algorithm (University of Glasgow ECG Algorithm), it is generally understood that such algorithms are developed and validated against expert consensus or clinically confirmed diagnoses, but the details for this submission are absent.
8. The sample size for the training set:
- Not specified. This refers to the training of the University of Glasgow ECG Algorithm, which is an external component, and its training details are not provided in this 510(k) summary.
9. How the ground truth for the training set was established:
- Not specified. (Refer to point 8).
Summary of Missing Information:
The provided 510(k) summary is primarily concerned with establishing substantial equivalence to a predicate device and demonstrating software validation according to FDA guidance. It leverages the fact that it uses the same ECG analysis algorithm as the predicate device. It does not contain the detailed performance study data (acceptance criteria, test set characteristics, ground truth establishment, expert involvement, specific performance metrics for diagnostic accuracy) that would be expected for a more modern AI/ML device submission demonstrating algorithmic performance.
§ 870.1425 Programmable diagnostic computer.
(a)
Identification. A programmable diagnostic computer is a device that can be programmed to compute various physiologic or blood flow parameters based on the output from one or more electrodes, transducers, or measuring devices; this device includes any associated commercially supplied programs.(b)
Classification. Class II (performance standards).