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For the prevention and treatment of pressure ulcers. Patient lateral rotation of up to 30 degrees may also be used as a preventive tool against further complications associated with critically ill patients or immobility.

The PressureGuard Turn Select is an air flotation, alternating pressure support system. It consists of a foam shell manufactured with medical grade, polyurethane foam that meets the California Technical Bulletin 117. The perimeter bolsters are designed to safely prompt the patient toward the center of the surface, facilitating safe transfers and edge-of-bed sittings. The inflation system is cradled and securely positioned within the foam shell. Through computerized technology, the internal air pressures of the inflation system are controlled to achieve four operating modes. The CENTER Mode provides a level supine surface. The FIXED ROLL Mode provides automatic turning, turning the patient to the left followed by a 2 hour dwell time, then returning to center for a 2 hour dwell time, followed by a turn to the right followed by a 2 hour dwell time. The CUSTOM ROLL Mode provides for selection of roll patterns, roll angles and dwell times to meet individual patient needs. The CPR Mode provides a firm surface to aid in CPR Procedures (with a crash board). A Service Required Feature is provided to alert the health care provider in the event of system malfunction. CPR Alarm and Lock-Out features are also included.

The provided text describes a 510(k) submission for the "PressureGuard Turn Select" alternating pressure mattress, which is intended for the prevention and treatment of pressure ulcers and for patient lateral rotation. The submission focuses on demonstrating substantial equivalence to a predicate device (PressureGuard IV, 510K953503) rather than defining and proving specific acceptance criteria through a clinical study with performance metrics.

Therefore, many of the requested categories for a study that proves device meets acceptance criteria cannot be directly answered from the given document, as this submission is for a medical device cleared via substantial equivalence, not typically a clinical trial demonstrating performance against quantitative acceptance criteria for software or an AI algorithm.

However, I can extract information related to the closest aspects from the provided text.

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

   No quantifiable acceptance criteria or performance metrics (like sensitivity, specificity, accuracy) are provided in the document for the PressureGuard Turn Select. The demonstration is based on "substantial equivalence" to a predicate device. The performance is implied to be similar to the predicate device.

   Acceptance Criterion	Reported Device Performance
   Not specified	Not specified
   (Implied) Substantial Equivalence to predicate device for intended use and safety	The device is similar in function and intended use to the predicate.
   (Implied) Pressure-management	Verified through interface pressure testing (no results or criteria provided).
   (Implied) Conformance to UL 544 and CSA 122.25	System is designed to conform to these standards.

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 describe a "test set" in the context of clinical data or AI validation. The "interface pressure testing" mentioned is likely an engineering or bench test, not a clinical study on a patient sample. No sample size for such testing is provided, nor is the provenance of any data.

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)

   Not applicable. The submission does not describe a clinical study requiring expert-established ground truth.

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

   Not applicable. No clinical test set or 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

   Not applicable. This device is a mattress system, not an AI-assisted diagnostic tool.

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

   Not applicable. This submission is for a physical medical device, not an algorithm.

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

   Not applicable. The concept of "ground truth" for clinical outcomes or diagnostic accuracy is not relevant to this 510(k) submission, which focuses on similarity to a predicate device and engineering testing.

8. The sample size for the training set

   Not applicable. A "training set" is relevant for AI/ML algorithms. This is a physical medical device.

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

   Not applicable.

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For the prevention and treatment of pressure ulcers.

The PressureGuard Site Select is an air flotation, alternating pressure support system which provides for customized selection of surface firmness for a head, upper torso, lower torso, and heel zones.

The provided 510(k) summary for the PressureGuard Site Select primarily focuses on demonstrating substantial equivalence to a predicate device (PressureGuard IV) based on similar function and intended use. It describes the features and modes of operation of the device but does not include information about specific acceptance criteria or a study proving that the device meets such criteria.

Therefore, I cannot populate most of the requested fields based on the given document.

However, I can extract the following:

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

• Acceptance Criteria: Not explicitly stated in the document.
• Reported Device Performance: Not explicitly stated as per specific performance metrics. The document focuses on describing the device's features and comparability to a predicate.

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

• Sample Size: Not provided.
• Data Provenance: 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)

• Not applicable/Not provided, as there's no mention of a clinical or performance study with a test set requiring ground truth.

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

• Not applicable/Not provided.

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

• Not applicable. This is not an AI-powered device, and no MRMC study is mentioned.

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

• Not applicable. This is not an algorithm-only device.

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

• Not applicable/Not provided.

8. The sample size for the training set

• Not applicable/Not provided, as this is not an AI/machine learning device.

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

• Not applicable/Not provided.

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For the prevention and treatment of pressure ulcers.

The PressureGuard SelectCare is a powered air flotation mattress which provides pressure-reducing support within a range of adjustable firmness to meet individual comfort needs. The system also includes a CPR mode, providing a firm surface for performing CPR.

This document is a 510(k) summary for a medical device called "PressureGuard: SelectCare Mattress System". It describes the device, its intended use, and its substantial equivalence to a predicate device. However, it does not contain any information about acceptance criteria, device performance studies, sample sizes, expert ground truth, or MRMC studies that would be relevant to evaluating AI/ML-based medical devices.

Therefore, I cannot provide the requested information for the following reasons:

• No acceptance criteria or device performance data: The document does not specify any quantitative or qualitative acceptance criteria for the device's performance (e.g., pressure reduction percentages, incidence of pressure ulcers, etc.). Consequently, it does not report any device performance against such criteria.
• No study information: This is a pre-market notification (510(k)) summary, which focuses on demonstrating substantial equivalence to a legally marketed predicate device, not on presenting detailed clinical study results or performance metrics in the way an AI/ML device would.
• Irrelevance to AI/ML device evaluation: The device described is a physical mattress system, not an AI/ML-based diagnostic or prognostic tool. Therefore, concepts like "test set," "training set," "ground truth experts," "adjudication methods," or "MRMC studies" are not applicable in this context.

In summary, the provided text does not contain the type of information needed to answer your request, which is geared towards evaluating the performance of AI/ML medical devices.

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To lubricate a body orifice to facilitate entry of a diagnostic or therapeutic device.

Lubricating Jelly is a patient lubricant intended for medical purposes that is used to lubricate a body orifice to facilitate entry of a diagnostic or therapeutic device.

This document is a 510(k) summary for a medical device (Lubricating Jelly, Low Viscosity). It describes the device, its intended use, and claims substantial equivalence to a predicate device.

However, this document does not contain any information about acceptance criteria or a study proving device performance against such criteria in the context of diagnostic accuracy, clinical outcomes, or AI algorithm performance. It's a regulatory filing for a low-risk medical device, where the primary demonstration of safety and effectiveness often relies on showing substantial equivalence to an already marketed device, rather than extensive performance studies with acceptance criteria as one would find for diagnostic algorithms.

Therefore, I cannot extract the requested information (table of acceptance criteria, sample sizes, expert qualifications, etc.) because it is not present in the provided text. The document's purpose is to outline the device's characteristics and its equivalence to a predicate device, not to detail the results of a performance study with specific metrics and acceptance criteria.

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The Span-America Horizontal Low Air Loss Mattress System is a powered air flotation mattress with low air loss. The pressure-reducing surface is indicated for the prevention and treatment of pressure ulcers.

The Span-America Horizontal Low Air Loss Mattress System is a powered air flotation mattress which provides a continuous flow of air to the air sacks as a portion of the air is vented inside the mattress. The air flow is designed to provide and maintain an inflation level to achieve pressure reduction in the prevention and treatment of pressure ulcers.

This document is a 510(k) summary for a medical device submitted to the FDA in 1996. It describes a "Powered Low Air Loss Mattress System" intended for the prevention and treatment of pressure ulcers.

Critically, this document describes a physical medical device, not an Artificial Intelligence (AI) or software-as-a-medical-device (SaMD) product. Therefore, the requested information regarding AI model performance, training sets, ground truth establishment, expert adjudication, and MRMC studies is not applicable to this submission.

The 510(k) process for devices like this primarily focuses on demonstrating "substantial equivalence" to a predicate device already on the market. This often involves comparing technological characteristics, intended use, and performance claims to the predicate. Clinical studies, when present for these types of devices, typically focus on safety and effectiveness in a broader sense (e.g., patient outcomes related to pressure ulcer prevention/treatment), rather than the specific AI-related metrics you've requested.

Therefore, I cannot fulfill your request as written because the provided input does not describe an AI/SaMD product.

If you can provide a 510(k) summary, clinical study report, or other documentation for an AI-powered medical device, I would be happy to attempt to extract the requested information.

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For the prevention and treatment of pressure ulcers.

The PressureGuard Low Air Loss Mattress System is a powered air flotation mattress which provides a continuous flow of air to the air cylinders as a portion of the air is vented inside the mattress. The air flow is designed to provide and maintain an inflation level to achieve pressure reduction in the prevention and treatment of pressure ulcers.

This document is a 510(k) summary for a medical device (PressureGuard: Low Air Loss Mattress System) seeking clearance from the FDA in 1996. It describes the device, its intended use, and claims substantial equivalence to a predicate device.

However, the provided text does NOT contain any information regarding acceptance criteria, device performance studies, sample sizes, expert involvement, ground truth establishment, or any of the other specific details requested in your prompt (e.g., MRMC studies, standalone performance, training set details).

This document is a very high-level summary for regulatory submission, not a detailed scientific study report.

Therefore, I cannot fulfill your request with the given input. To provide the information you're looking for, I would need a different type of document, such as a clinical study report, a performance validation report, or a more detailed scientific publication associated with the device.

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Ask a specific question about this device

Ask a specific question about this device