(209 days)
The ArchiMed line of electrocardiograph products is used to record standard electrocardiographs at patient resting or exercising. Resting ECGs are automatically measured and interpreted by the optionally available interpretive software.
The ArchiMed product line represents two (4210, 4220) versions of a portable, multi channel electrocardiograph machine. These units are intended for acquisition, digitization, display and recording of conventional diagnostic 12 simultaneous lead ECG waveforms. The 4220 model can be equipped with a resting interpretation program covering adult populations. This analysis program is offered to the physician on an advisory basis only and physician is asked to over-read and validate (or change) the ECG interpretation. Moreover, the 4220 may be equipped with a software package to be used for exercise stress testing, has wider connectivity characteristics and can print to a laser printer.
Here's an analysis based on the provided document, addressing your request. It's important to note that the provided text is a 510(k) summary for an electrocardiograph device (ArchiMed), and not a detailed study report with performance metrics in the way you might expect for a modern AI/device submission. The document focuses on substantial equivalence to a predicate device rather than presenting a novel AI's performance.
Therefore, many of your requested points, especially those related to AI-specific performance, sample sizes for training/test sets, ground truth establishment, and MRMC studies, are not present in this type of regulatory submission from 1998 for an "Electrocardiograph data analysis firmware." The "interpretive software" mentioned is likely a rule-based algorithm rather than a machine learning model as understood today.
Acceptance Criteria and Study for ArchiMed Electrocardiograph (K973922)
The provided document, a 510(k) Safety and Effectiveness Summary for the ArchiMed electrocardiograph, primarily establishes substantial equivalence to a predicate device (Esaote P210, K902368) rather than demonstrating performance against specific, pre-defined quantitative acceptance criteria for a novel AI algorithm. The device's "effectiveness" is implicitly demonstrated through its similarity to a legally marketed predicate.
1. Table of Acceptance Criteria and Reported Device Performance
As this is a 510(k) submission focused on substantial equivalence, there are no explicit quantitative acceptance criteria or detailed performance metrics presented in the document in the format typically seen for novel AI device studies. The "performance" is primarily shown through a comparison chart demonstrating that its general characteristics, such as dimensions, weight, power supply, display, ECG storage, sampling frequency, and filter specifications, are "SAME" or comparable to the predicate device.
| Criterion Category | Acceptance Criteria (Implied by Substantial Equivalence) | Reported Device Performance (ArchiMed 4210/4220) |
|---|---|---|
| Physical/Technical Characteristics | Substantially equivalent to predicate device (Esaote P210, K902368) | - Dimensions: 328x254x75 mm (vs. 310x350x75 mm for predicate) |
- Weight: 3.3 kg (vs. 3.8kg for 4210, 4.8kg for 4220 of predicate)
- Display: LCD, backlit, 480x640 pixels (SAME)
- ECG storage: RAM Cards (vs. Floppy Disks for predicate; 4220 has HardDisk & Network)
- Sampling frequency: 1000 Hz (SAME)
- Common mode rejection: > 100 dB (SAME)
- Frequency response: 0.05 to > 150 Hz (SAME)
- Leads: 10 buffered with RL drive (SAME)
- Number of signals recorded: 8 simultaneously, 4 mathematically derived (vs. 12 channels for predicate)
- Recorder: Thermal print head (SAME)
- Paper speed & size: SAME for speed, A4/Letter size with half length (vs. A4/Letter for predicate) |
| Clinical Intended Use | Same intended use as predicate device. | Records standard electrocardiographs at patient resting or exercising. Optional interpretive software for resting ECGs provides advisory interpretation which physician must over-read and validate. |
| Safety | Complies with general controls, good manufacturing practices, and similar safety profile to predicate. | Not explicitly detailed as performance metrics but implicitly deemed safe through substantial equivalence to a legally marketed device and compliance with regulations. |
2. Sample Size Used for the Test Set and Data Provenance
The document does not describe a "test set" in the context of evaluating a machine learning algorithm. The submission is based on engineering specifications and the functional comparison to a predicate device. Therefore, no information on sample size or data provenance (country, retrospective/prospective) for an algorithmic test set is provided.
3. Number of Experts Used to Establish Ground Truth for the Test Set and Qualifications
This information is not provided. As the "interpretive software" is likely rule-based and offers "advisory" interpretations to be "over-read and validate (or change)" by a physician, the concept of establishing ground truth by multiple experts for an algorithmic test set is not detailed in this 1998 regulatory summary. The "ground truth" for the overall device's function would be its accurate acquisition and display of ECG waveforms, which is implicitly benchmarked against the predicate device.
4. Adjudication Method for the Test Set
No adjudication method for an algorithmic test set is described, as such a test set is not presented in the document.
5. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study
No MRMC study is mentioned or appears to have been conducted for this submission. The "interpretive program" is explicitly advisory, requiring physician over-read, indicating it is not intended to replace human interpretation but to assist it. Therefore, an effect size of human readers improving with AI vs. without AI assistance is not provided.
6. Standalone (Algorithm Only) Performance Study
While the device includes "Electrocardiograph data analysis firmware" and an "interpretation program," the document does not present a standalone performance study of this algorithm. Its function is described as providing an "advisory" interpretation that requires physician validation, implying it's not a standalone diagnostic tool. The submission focuses on the device as a whole and its equivalence to a predicate, not isolated algorithm performance.
7. Type of Ground Truth Used
For the interpretive software, the ground truth for its internal logic would likely have been established based on medical guidelines and expert consensus for ECG interpretation at the time of its development. However, the document itself does not specify how the ground truth was established for the "interpretive program." Given the context, it would not involve pathology or outcomes data directly for the algorithm's performance described here.
8. Sample Size for the Training Set
No information on a training set or its sample size is provided, as the software described is likely a rule-based expert system rather than a machine learning model requiring a discrete training phase with data in the modern sense.
9. How the Ground Truth for the Training Set Was Established
Since no training set is described, there is no information on how its ground truth was established. For a rule-based system, the "ground truth" for its logic would be derived from clinical knowledge and established ECG interpretation criteria.
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