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The Tablet Commander device is for use by patients to collect and transmit general health information, physiological measurements and other data between themselves and a caregiver.

The Tablet Commander makes no diagnosis. Clinical judgment and experience are required to check and interpret the information transmitted. The Tablet Commander is not intended as a substitute for medical care.

The Tablet Commander is a software application. Once installed on a commercially-available device, the Tablet Commander software uses standard communication protocols to exchange information with other medical devices (peripherals). Data collected from the medical devices is transmitted back to a database for review by a caregiver. The Tablet Commander software has a user interface which allows the patient and caregiver to communicate using methods which include questions and answers.

The provided text describes a 510(k) premarket notification for the "Tablet Commander" device, a software application for remote patient monitoring. The application focuses on functional and safety analysis rather than diagnostic accuracy. As such, acceptance criteria and performance metrics related to diagnostic accuracy (like sensitivity, specificity, or AUC) are not applicable or provided in this document.

Here's an analysis based on the information provided:

1. A table of acceptance criteria and the reported device performance

The document does not explicitly state quantitative acceptance criteria in terms of performance metrics like sensitivity, specificity, accuracy, or similar diagnostic measures. Instead, the acceptance is based on the device functioning according to its requirements and specifications, and demonstrating substantial equivalence to predicate devices in terms of intended use, technology, materials, and principles of operation, without introducing new hazards.

The key performance criterion is that the device "functioned according to its requirements and specifications." The validation activities supporting this are described as:

2. Sample size used for the test set and the data provenance (e.g. country of origin of the data, retrospective or prospective)

The document does not mention a specific "test set" in the context of clinical data or diagnostic performance. The validation appears to be primarily focused on software functionality and engineering verification and validation (V&V) activities. Therefore, details about the sample size for a test set, data provenance, or whether it was retrospective or prospective are not provided.

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts (e.g. radiologist with 10 years of experience)

Since there is no mention of a "test set" requiring ground truth establishment through expert review for diagnostic purposes, this information is not applicable and not provided in the document.

4. Adjudication method (e.g. 2+1, 3+1, none) for the test set

Similarly, as there is no diagnostic "test set" needing ground truth establishment, no adjudication method is described.

5. If a multi-reader, multi-case (MRMC) comparative effectiveness study was done, If so, what was the effect size of how much human readers improve with AI vs without AI assistance

No MRMC comparative effectiveness study was conducted or is mentioned, as the device is a remote patient monitoring system and not an AI-assisted diagnostic tool.

6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done

The Tablet Commander is described as a "software application" that collects and transmits data for review by a caregiver. It explicitly states, "The Tablet Commander makes no diagnosis," and "Clinical judgment and experience are required to check and interpret the information transmitted." This indicates that the device is not intended for standalone diagnostic performance; it functions as a data collection and transmission tool within a human-in-the-loop system. Therefore, a standalone algorithm-only performance study (in a diagnostic sense) was not done, and would not be relevant to its intended use.

7. The type of ground truth used (expert consensus, pathology, outcomes data, etc.)

For the software validation, the "ground truth" implicitly refers to the device's functional requirements and specifications. The V&V testing confirms that the software behaves as designed and meets these predefined requirements, rather than validating against clinical ground truth like pathology or expert consensus on a diagnosis.

8. The sample size for the training set

The document does not describe the use of machine learning or AI models that would require a "training set" for diagnostic algorithm development. The device is a software application for data management and communication.

9. How the ground truth for the training set was established

As there is no mention of a training set for machine learning, this information is not applicable and not provided.

Summary of the study and its purpose:

The study described is not a performance study in the typical sense of evaluating diagnostic accuracy using clinical data. Instead, it is a verification and validation (V&V) study of a software application for remote patient monitoring, conducted as part of a 510(k) premarket notification. The purpose was to demonstrate that the "Tablet Commander" software functions according to its requirements and specifications and that it is substantially equivalent to legally marketed predicate devices without raising new questions of safety or effectiveness.

The key study type conducted was risk-based verification and validation testing of the software, following FDA guidances ("Guidance for the Content of Premarket Submissions for software Contained in Medical Devices" and "General Principles of Software Validation") and using IEC 62304 as a model for software development. This type of study focuses on ensuring the software is correctly built (verification) and that it meets specified user needs (validation) within its intended technical scope, rather than clinical efficacy or diagnostic performance. No clinical tests were conducted because the device was considered to present no new hazards to safety or effectiveness compared to predicate devices.

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The Commander III is for use by patients to collect and transmit general health questions and patient vital sign data (such as weight, blood pressure, glucose, pulse oximetry, peak flow) between the patient, typically at home, and a health care professional at a remote site.

The Commander III is an FDA cleared device (K053303, K053304). It is similar to a simple personal computer with a modem that stores and transmits data to remote locations. The Commander III is cleared for use with a pulse oximeter, a weight scale, a glucose meter, a peak flow meter and a blood pressure cuff. This premarket submission seeks to add an additional pulse oximeter, the PO100, for use with the Commander III. The PO100 is a reusable pulse oximeter that connects to the Cardiocom Commander III via a cable in the same manner as the currently cleared pulse oximeter.

The provided text is a 510(k) summary for the Cardiocom Commander III, seeking to add an additional pulse oximeter (PO100) for use with the device. It focuses on demonstrating substantial equivalence to a predicate device rather than presenting a detailed study proving the device meets specific acceptance criteria with quantifiable performance metrics.

Therefore, much of the requested information cannot be extracted from this document, as it describes a regulatory submission focused on substantial equivalence rather than a detailed performance study with acceptance criteria.

However, based on the provided text, here's what can be gathered and what cannot:

1. A table of acceptance criteria and the reported device performance

This information is not provided in the document. The submission states: "To verify that device design met its functional and performance requirements, representative samples of the device underwent electrical, mechanical and clinical testing in accordance with applicable industry standards." However, it does not specify the numerical acceptance criteria or the quantitative results of these tests for the Commander III or the PO100.

2. Sample size used for the test set and the data provenance (e.g., country of origin of the data, retrospective or prospective)

This information is not provided in the document. The text mentions "representative samples of the device" were tested, but no details on the sample size or the nature of the data are given.

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts (e.g., radiologist with 10 years of experience)

This information is not provided in the document. The submission does not detail any expert-driven ground truth establishment.

4. Adjudication method (e.g., 2+1, 3+1, none) for the test set

This information is not provided in the document.

5. If a multi-reader multi-case (MRMC) comparative effectiveness study was done, If so, what was the effect size of how much human readers improve with AI vs without AI assistance

This information is not provided and is not applicable. The device described (Commander III with PO100) is a medical device for collecting and transmitting vital sign data, not an AI or imaging diagnostic tool that would typically involve human readers or MRMC studies.

6. If a standalone (i.e., algorithm only without human-in-the-loop performance) was done

This information is not explicitly detailed in the context of specific performance metrics. The submission focuses on the Commander III's ability to "store and transmit data to remote locations" and its use with various sensors, including the new PO100 pulse oximeter. The "functional and safety testing" mentioned implies testing the device's standalone performance in accordance with industry standards, but no specific results are given.

7. The type of ground truth used (expert consensus, pathology, outcomes data, etc.)

This information is not provided in the document. Given the nature of the device (a data collection and transmission system), ground truth would typically refer to the accuracy of the vital sign measurements provided by the connected sensors (like the pulse oximeter) compared to a gold standard, but this is not discussed in the summary.

8. The sample size for the training set

This information is not applicable/provided. The device is not an AI/machine learning algorithm requiring a "training set" in the conventional sense. Its functionality is to collect and transmit data from established medical sensors.

9. How the ground truth for the training set was established

This information is not applicable/provided for the same reasons as point 8.

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The Commander III device is for use by patients to collect and transmit general health questions and patient vital sign data (such as weight, blood pressure, glucose, pulse oximetry, peak flow) between the patient, typically at home, and a health care professional at a remote site.
Contraindications, Precautions and Warnings: The Commander III device makes no interpretation, evaluation, medical judgments or recommendations for treatment. Clinical judgment and experience are required to check and interpret the information transmitted. The Commander III is not intended as a substitute for medical care.

Commander III is similar to a simple personal computer with a modem that stores and transmits data. Commander III connects to a user's telephone line at home. It has a display that asks health related questions to which the user can respond 'Yes', 'No', or select from a list. It also has inputs for devices such as weight scales, blood pressure meters, glucometers, peak flow meters and pulse oximeters. These devices download data through a RS232 connection. The functionality of these devices has not been modified; they are used as supplied from the manufacturer.

Here's an analysis of the provided text regarding the Cardiocom Commander III, broken down by your requested categories.

Important Note: The provided document is a 510(k) summary for a medical device seeking clearance based on substantial equivalence. This type of submission relies on showing that a new device is as safe and effective as a legally marketed predicate device (K982481 A&D Medical UA-767PC Digital Blood Pressure Monitor in this case), rather than requiring extensive de novo clinical trials to prove efficacy from scratch. Therefore, many of the typical acceptance criteria and study details for AI/ML devices, such as multi-reader multi-case studies or detailed ground truth establishment, are not present in this type of submission. The focus is on demonstrating comparability to the predicate device, particularly in areas like accuracy and safety standards.

Acceptance Criteria and Device Performance

Study Proving Acceptance Criteria:

The document states, "The results of bench, laboratory, and clinical testing indicates that the new device is as safe and effective as the predicate device." And in the conclusion: "After analyzing bench, test laboratory, and clinical testing data, it is the conclusion of Cardiocom that the Cardiocom Commander III is as safe and effective as the predicate device, has essentially no significant technological differences, and has no new indications for use, thus rendering it substantially equivalent to the predicate device."

This indicates that studies were performed to demonstrate that the Commander III meets the same performance and safety standards as the predicate device, specifically ANSI/AAMI SP10: 1992+A1 for blood pressure accuracy.

Additional Information Not Extensively Detailed in the Provided Text:

1. Sample size used for the test set and the data provenance:

   • The document mentions "clinical testing data" but does not specify the sample size for a test set or the data provenance (e.g., country of origin, retrospective/prospective). As a 510(k) based on substantial equivalence, the clinical testing would likely be focused on demonstrating comparable performance to the predicate against established standards (like AAMI SP10), which often involves a specific number of subjects. However, these specifics are not in the provided summary.

2. Number of experts used to establish the ground truth for the test set and the qualifications of those experts:

   • Not applicable/Not specified in this type of submission. For blood pressure monitors, accuracy is typically assessed against a reference standard (e.g., a mercury sphygmomanometer used by trained clinicians) rather than "expert consensus" in the way it applies to diagnostic image interpretation. The AAMI SP10 standard outlines the methodology for such validation tests.

3. Adjudication method (e.g., 2+1, 3+1, none) for the test set:

   • Not applicable/Not specified. "Adjudication" typically refers to resolving discrepancies in expert interpretations, which isn't the primary method for validating blood pressure device accuracy.

4. If a multi reader multi case (MRMC) comparative effectiveness study was done, If so, what was the effect size of how much human readers improve with AI vs without AI assistance:

   • No. This device is a measurement system, not an AI diagnostic tool that assists human readers/interpreters. There is no mention of AI or human-in-the-loop performance measurement in the provided text.

5. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done:

   • Yes, in the sense that the device's ability to measure blood pressure, pulse, etc., is evaluated as a standalone function primarily against established standards (like AAMI SP10). The device itself is a standalone measurement system for collecting vital signs.

6. The type of ground truth used (expert consensus, pathology, outcomes data, etc):

   • For blood pressure accuracy, the ground truth would typically be established by a reference method, such as a mercury sphygmomanometer, performed by trained observers according to standard protocols (e.g., specified in AAMI SP10). The document refers to "clinical testing data" which would be based on this type of ground truth.

7. The sample size for the training set:

   • Not applicable/Not specified. This device is not described as using machine learning or AI that would require a distinct "training set." It is a hardware and software system for data collection and transmission.

8. How the ground truth for the training set was established:

   • Not applicable, as a training set, as typically understood for AI/ML, is not described for this device.

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The Commander III device is for use by patients to collect and transmit general health questions and patient vital sign data (such as weight, blood pressure, glucose, pulse oximetry, peak flow) between the patient, typically at home, and a health care professional at a remote site.

Commander III is similar to a simple personal computer with a modem that stores and transmits data. Commender III connects to a user's telephone line at home. It has a display that asks health related questions to which the user can respond 'Yes', 'No', or select from a list. It contains an integrated blood pressure meter. It also has inputs for devices such as weight scales, glucometers, peak flow meters and pulse oximeters. These devices download data through a RS232 connection. The functionality of these devices has not been modified; they are used as supplied from the manufacturer.

Here's the analysis of the provided text regarding the Cardiocom Commander III device, focusing on its acceptance criteria and the study used to prove it meets them:

Disclaimer: The provided document is a 510(k) summary, which is a premarket notification to the FDA to demonstrate that a device is substantially equivalent to a legally marketed predicate device. It is not generally a detailed clinical study report and thus may not contain all the specific metrics and methodologies typically found in such a report. Many of the requested details (like specific statistical measures for performance, sample sizes for training data, expert qualifications, etc.) are not explicitly stated in this type of regulatory submission and would be found in the actual studies conducted by the manufacturer, which are summarized or referenced here.

Acceptance Criteria and Reported Device Performance

The provided 510(k) summary for the Cardiocom Commander III does not define explicit, quantitative acceptance criteria for its performance. Instead, the core of this submission is a demonstration of substantial equivalence to a predicate device (Cardiocom LLC Commander II). This means the acceptance criterion is implicitly that the new device is "as safe and effective" as the predicate device.

The reported device performance, in this context, is that the new device maintains the same functionalities and performance characteristics as the predicate, especially regarding its core function of oscillometric automated blood pressure monitoring.

Study Details

The submission refers to "bench, laboratory, and clinical testing data" to support its claim of substantial equivalence. However, the details of these studies are very brief, which is typical for a 510(k) summary.

1. Sample size used for the test set and the data provenance:

   • Test Set Sample Size: Not explicitly stated. The document simply mentions "clinical testing data."
   • Data Provenance: Not specified (e.g., country of origin). The document does not indicate if the data was retrospective or prospective.

2. Number of experts used to establish the ground truth for the test set and the qualifications of those experts:

   • Number of Experts: Not mentioned.
   • Qualifications of Experts: Not mentioned.

3. Adjudication method (e.g., 2+1, 3+1, none) for the test set:

   • Not mentioned.

4. If a multi-reader, multi-case (MRMC) comparative effectiveness study was done, if so, what was the effect size of how much human readers improve with AI vs without AI assistance:

   • This is not applicable to this device. The Cardiocom Commander III is a non-invasive automated blood pressure monitor and a data collection/transmission system. It does not involve human "readers" interpreting medical images or data in a way that an AI would assist.

5. If a standalone (i.e., algorithm only without human-in-the-loop performance) was done:

   • Yes, for the blood pressure measurement component, the device would have undergone standalone performance testing against reference standards, as required for blood pressure devices. The submission states, "The Commander III has a built in NIBP meter," and this component's accuracy would have been validated. However, the specific results of this standalone performance (e.g., mean difference, standard deviation compared to a reference sphygmomanometer as per ISO standards) are not provided in this summary. The summary broadly states "bench, laboratory, and clinical testing data."

6. The type of ground truth used (expert consensus, pathology, outcomes data, etc.):

   • For the blood pressure meter component, the ground truth would typically be a simultaneous measurement by a trained observer using a calibrated mercury sphygmomanometer or an equivalent reference standard, adhering to recognized protocols for blood pressure device validation (e.g., ANSI/AAMI/ISO 81060-2). For the other vital sign inputs (glucometers, pulse oximeters, peak flow meters), the ground truth would be established by the respective reference devices' measurements, as the Commander III acts as a data collector and transmitter for these, not the primary measurement device (except for the built-in NIBP).

7. The sample size for the training set:

   • Not applicable/Not mentioned. This device does not appear to employ a machine learning or AI model that requires a "training set" in the conventional sense of AI algorithms that learn from data. It's a hardware device with embedded firmware for data collection and transmission.

8. How the ground truth for the training set was established:

   • Not applicable. As above, there's no indication of a machine learning "training set" being used for this device.

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