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The HotDog Patient Warming System is intended to prevent or treat hypothermia and to provide warmth to patients. The HotDoq Patient Warming System should be used in circumstances in which patients may not maintain a state of normothermia. The patient warming system can be used with adult and pediatric patients.

The System is intended primarily for use in hospitals and surgical centers including without limitation operating, recovery and emergency rooms and on medical/surgical - floors.

The HotDog Patient Warming System consists of a temperature control unit that monitors and controls the temperature of a patient warming blanket or mattress. The blankets and mattresses are composed of a conductive polymer coated fabric heater encased in a polymer shell. The mattress also contains a pressure relieving foam pad.

The provided 510(k) summary for the HotDog Patient Warming System (K112488) does not describe a study involving an AI/Machine Learning device or an algorithm's performance against acceptance criteria in the way a typical diagnostic or image analysis AI study would.

Instead, this submission is for a medical device (a thermal regulating system) and its performance evaluation focuses on engineering benchmarks and safety standards. Therefore, many of the requested categories (like sample size for test/training sets, experts for ground truth, MRMC studies, standalone performance, etc.) are not applicable to this type of device and submission.

Here's an analysis based on the information provided, tailored to the context of this specific device:

1. Table of Acceptance Criteria and Reported Device Performance

2. Sample size used for the test set and the data provenance

• Sample Size: Not applicable in the context of clinical or image data. The "test set" here refers to the physical device units subjected to bench testing against engineering and safety standards. The document does not specify the number of units tested.
• Data Provenance: Not applicable in terms of country of origin for clinical data. The "data" comes from non-clinical bench testing conducted by the manufacturer, Augustine Biomedical & Design, LLC.

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

• Number of Experts/Qualifications: Not applicable. Ground truth for this type of device (thermal regulating system) is established by conformance to recognized engineering standards and performance specifications, not often by human experts interpreting clinical data in the same way as an AI diagnostic device. The "experts" involved would be engineers and quality assurance professionals ensuring compliance with the cited IEC standards.

4. Adjudication method for the test set

• Adjudication Method: Not applicable. Adjudication methods like 2+1 or 3+1 are used for reconciling discordant expert opinions on clinical cases. Here, the "truth" is determined by meeting objective engineering and safety standards, not by consensus on subjective interpretations.

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

• MRMC Study: No, an MRMC comparative effectiveness study was not done. This type of study is relevant for diagnostic AI devices, not for a patient warming system.

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

• Standalone Performance: Not applicable. This is not an algorithm-only device. The "device" is a physical patient warming system.

7. The type of ground truth used

• Type of Ground Truth: The "ground truth" for this submission is conformance to established international medical device safety and performance standards (IEC 60601 series) and demonstrated substantial equivalence to a previously cleared predicate device (K052392) through direct comparison of engineering characteristics and safety systems.

8. The sample size for the training set

• Sample Size for Training Set: Not applicable. There is no AI model or algorithm being "trained" for this device.

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

• Ground Truth for Training Set: Not applicable, as there is no training set for an AI model.

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The Hot Dog Patient Warming System is intended to prevent or treat hypothermia and to provide warmth to patients. The Hot Dog Patient Multifunction Controller should be used in circumstances in which patients may not maintain a state of normothermia. The System is intended primarily for use in hospitals and surgical centers including without limitation operating, recovery and emergency rooms and on medical/surgical floors.

The Hot Dog Multifunction Controller consists of a temperature control unit that monitors and controls the temperature of patient warming blankets and mattresses.

The provided text describes a medical device, the "Hot Dog Multifunction Controller," and its premarket 510(k) summary for FDA clearance. However, the document does not contain information about specific acceptance criteria, a study proving the device meets those criteria, or the details of such a study as requested in your prompt (e.g., sample sizes, ground truth establishment, expert qualifications, MRMC studies).

The non-clinical data section states:
"Bench testing was performed to demonstrate that the proposed controller is substantially equivalent to the predicate devices. Temperature characteristics and safety systems were compared and found to be comparable."

"The controller is designed to meet the following performance standards:

• IEC 60601-1 Medical Electrical Equipment - Part 1: General Requirements For Basic Safety And Essential Performance, edition: 2
• IEC 60601-1-2, Medical Electrical Equipment - Part 1-2: General Requirements for Safety - Collateral standard: Electromagnetic Compatibility - Requirements and Tests, edition: 2.1
• IEC 60601-1-4:2000, Medical electrical equipment - Part 1: General requirements for safety - 4 - Collateral standard: Programmable electrical medical systems, edition 1.1."

The clinical data section simply states: "Not required."

Therefore, based solely on the provided text, I can only provide the following, which aligns with the information that is present:

1. Table of Acceptance Criteria and Reported Device Performance

2. Sample size used for the test set and the data provenance:
Not explicitly stated in the provided text. The document only mentions "bench testing."

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts:
Not applicable as no clinical or expert-reviewed ground truth study is described. The performance assessment relied on technical bench testing against predicate devices and adherence to international standards.

4. Adjudication method for the test set:
Not applicable.

5. If a multi-reader multi-case (MRMC) comparative effectiveness study was done:
No, an MRMC comparative effectiveness study was not done. The document states "Clinical Data: Not required," indicating that studies involving human readers or clinical outcomes were not part of this 510(k) submission for the device.

6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done:
The device is a "Multifunction Controller" for a "Thermal Regulating System," not an algorithm in the typical sense of AI/image analysis. Its performance was assessed via "bench testing" focusing on its technical functions (temperature control, safety systems) against established standards and predicate devices.

7. The type of ground truth used:
For the technical performance, the "ground truth" was established by adherence to international performance standards (IEC 60601-1 series) and comparison to the characteristics of legally marketed predicate devices.

8. The sample size for the training set:
Not applicable, as this is not an AI/ML device that requires a training set.

9. How the ground truth for the training set was established:
Not applicable.

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The Hot Dog Patient Warming Mattress System is intended to prevent or treat hypothermia and to provide warmth to patients. The Hot Dog Patient Warming Mattress should be used in circumstances in which patients may not maintain a state of normothermia. The mattress includes a pressure relieving pad.

The System is intended primarily for use in hospitals and surgical centers including without limitation operating, recovery and emergency rooms and on medical/surgical floors.

The Hot Dog Patient Warming Mattress System consists of a temperature control unit that monitors and controls the temperature of a patient warming mattress. The mattress is composed of a conductive polymer coated fabric heater encased in a polymer shell. The mattress also contains a pressure relieving foam pad.

It looks like the text provided is a 510(k) Premarket Notification summary for a medical device called the "Hot Dog Patient Warming Mattress System." This type of document is for regulatory clearance by the FDA, demonstrating substantial equivalence to existing devices, rather than a clinical study proving performance against acceptance criteria in the way a new drug or high-risk device might.

Here's an analysis based on the provided text, addressing the points you requested:

1. Table of Acceptance Criteria and Reported Device Performance

Based on the provided text, the "acceptance criteria" are not reported as specific numerical targets for performance metrics (e.g., "device must maintain temperature within +/- 0.5°C for 95% of use"). Instead, the acceptance criteria are framed in terms of meeting established medical device performance standards and being "comparable" or "substantially equivalent" to predicate devices.

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

The document does not describe a "test set" in the context of human subject data for performance evaluation. It mentions "Bench testing" which implies laboratory or engineering tests. There is no information provided about sample sizes for this testing or data provenance (e.g., country of origin, retrospective/prospective), as it was likely internal engineering testing.

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

This information is not applicable and not provided. The evaluation presented is based on engineering principles, compliance with technical standards, and comparison to predicate devices, not on expert consensus from clinical data.

4. Adjudication Method for the Test Set

This information is not applicable and not provided. There was no clinical test set requiring expert adjudication.

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

No MRMC study was performed or described. This type of study is typically used for diagnostic imaging devices where human readers interpret medical images. The "Hot Dog Patient Warming Mattress System" is a therapeutic device, not an imaging device.

6. Standalone Performance

The "Bench testing" performed demonstrates standalone performance of the device against technical standards and in comparison to predicate devices. The summary states: "Bench testing was performed to demonstrate that the proposed warming mattress system is substantially equivalent to the predicate devices. Temperature characteristics, pressure relief characteristics and safety systems were compared and found to be comparable." However, specific numerical metrics of standalone performance are not detailed in this summary.

7. Type of Ground Truth Used

The "ground truth" for this substantial equivalence submission is based on:

• Compliance with recognized industry standards: IEC 60601-1, IEC 60601-1-2, IEC 60601-1-4, IEC 60601-2-35.
• Engineering specifications and design comparisons to legally marketed predicate devices.
• Bench test results (presumably against internal specifications and predicate device performance).

There is no mention of pathology, outcomes data, or expert consensus from clinical evaluation as ground truth.

8. Sample Size for the Training Set

This information is not applicable and not provided. The device described (a patient warming mattress) is not an AI/ML device that requires a training set for an algorithm.

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

This information is not applicable and not provided, as there is no training set for an AI/ML algorithm.

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The Hot Dog Patient Warming System is intended to prevent or treat hypothermia and to provide warmth to patients. The Hot Dog Patient Warming System should be used in circumstances in which patients could become cold.

The system in intended primarily for use in hospitals and surgical centers including without limitation operating, recovery and emergency rooms, burn units and on medical/surgical floors.

The Hot Dog Patient Warming System is designed to compensate for body heat loss before, during and after surgery and in other situations in which a patient could become cold.

The device consists of four primary components, the outer Warming Blanket (disposable), the Warming Pad, Connecting, Cable and the Temperature Controller.

The outer Warming Blanket is placed atop the patient, and the Warming Pad is placed over the outer Warming Blanket.

The microprocessor based Temperature Controller uses 110-240 VAC line voltage and is connected to the Warming Pad via a cable. The Controller output to the Warming Pad is 48 VDC or less.

The provided text is related to a Premarket (510k) Summary for a medical device called the "Hot Dog Patient Warming System." This type of document is for regulatory clearance and focuses on demonstrating substantial equivalence to a predicate device, rather than detailed performance studies like those typically conducted for AI or imaging devices.

Therefore, many of the requested categories (e.g., sample size for test/training sets, expert qualifications, adjudication methods, MRMC studies, standalone performance for algorithms) do not apply to this document and the type of device described. The study described here is a functional and safety testing of a physical patient warming system, not an analysis of data by an algorithm.

However, I will extract the relevant information where possible, based on the provided text.

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

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

This document describes a physical device's functional and safety testing, not a dataset analysis. Therefore, the concept of a "test set" in the context of data provenance and sample size of data points is not directly applicable. The testing was conducted on the device itself and its components. The document does not specify the number of units tested, the country of origin of the testing, or whether the testing was retrospective or prospective (though functional and safety testing is inherently prospective for the device being evaluated).

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 ground truth for device performance (temperature, safety shutdown) is based on physical measurements and engineering specifications, not expert interpretation of data.

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

Not applicable. This concept applies to human interpretation of data, not physical device testing.

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 or imaging device, and no human reader study was conducted.

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

Not applicable. This is not an algorithmic device. The device's standalone performance was evaluated through functional and safety testing, as described in the table above.

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

The ground truth for the device's performance was established through physical measurements and engineering standards/specifications for temperature and safety features. For example, "simulated skin temperatures that would cause thermal injury" serves as a benchmark, and the target "39 - 42 °C range" for contact temperature is a performance benchmark.

8. The sample size for the training set

Not applicable. This is a physical device, not an AI model, so there is no training set.

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

Not applicable. There is no training set for this device.

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