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The Arctic Sun® Temperature Management System is a thermal regulating system, indicated for monitoring and controlling patient temperature in adult and pediatric patients of all ages.

The Arctic Sun Temperature Management System is a non-invasive, thermal regulating system that monitors and controls patient temperature within a range of 32°C to 38.5°C (89.6°F to 101.3°F). The Arctic Sun Temperature Management System consists of the Arctic Sun 5000 Control Module and disposable non-sterile ArcticGel Pads. The control module recirculates temperature-controlled water to the ArcticGel Pads. A commercially-available medical temperature probe, such as naso-pharyngeal, bladder, rectal, or esophageal, connected to the control module senses the patient's core temperature. A control algorithm automatically adjusts the water temperature (automatic mode) or the clinician can adjust the water temperature (manual mode) to obtain the desired patient temperature. The ArcticGel Pads come in various sizes to cover a broad range of patients and fit both males and females. Each pad has an inlet and an outlet connection that attaches to a fluid delivery line that is connected to the Arctic Sun 5000 Control Module. Up to six pads can be connected at one time. The pads adhere to the patient by the use of a biocompatible hydrogel adhesive.

This document describes a 510(k) premarket notification for the Arctic Sun Temperature Management System. It's a submission for modifications to an existing device, rather than a completely new one. Therefore, the information provided focuses on demonstrating substantial equivalence to a predicate device, rather than a standalone study proving efficacy against specific acceptance criteria in the same way one might for a new AI diagnostic tool.

Here's an analysis of the provided text in relation to your questions:

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

The document does not explicitly state quantitative acceptance criteria in a typical "table" format with pass/fail metrics. This is common for 510(k) submissions of modified devices where the primary goal is demonstrating substantial equivalence to a predicate. The performance testing is geared towards verifying the functionality of the modifications and ensuring the device still performs as intended and complies with relevant standards.

The document states:

• "Hardware design verification and software validation of the Arctic Sun Temperature Management System was performed to verify all new system and software requirements, the result of which confirmed the function of the device modifications."
• "In addition to functional testing, the Arctic Sun Temperature Management System was retested, when applicable to confirm ongoing compliance with Electrical Safety and Electromagnetic Compatibility Standards."
• "The Arctic Sun Temperature Management System performs as intended, raises no new or different safety or effectiveness issues and is substantially equivalent to the predicate device."

Therefore, the implied acceptance criteria are:

• Successful verification of all new system and software requirements.
• Confirmation of the function of the device modifications.
• Ongoing compliance with Electrical Safety Standards.
• Ongoing compliance with Electromagnetic Compatibility Standards.
• No new or different safety or effectiveness issues compared to the predicate device.
• Substantial equivalence to the predicate device in indications for use, design, technological characteristics, materials, and system features and functions.

Reported Device Performance:
The document states that these criteria were met, but it does not provide specific numerical results or raw data from the tests. It concludes that the device "performs as intended" and is "substantially equivalent."

2. Sample sized 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 "sample size" in the context of a dataset for model evaluation, as this is not an AI diagnostic device. The testing described refers to "functional testing" and "retesting" for compliance. These tests would involve physical device testing, software testing, and hardware verification, not the processing of a dataset of patient information. Therefore, data provenance is not applicable in this context.

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 is not applicable. The device is a "Thermal Regulating System" for monitoring and controlling patient temperature. Its performance is evaluated through engineering verification and validation against design specifications and relevant standards, not by comparing its outputs to expert-established ground truth on a test set (like an imaging AI might).

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

This is not applicable for the reasons stated in point 3.

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 is not applicable. The Arctic Sun Temperature Management System is not an AI diagnostic tool used by human readers. It's a system to regulate patient temperature.

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

The device itself is a "Thermal Regulating System" with a control algorithm. The software validation confirmed the "function of the device modifications," which includes changes to the alert/alarm system, customizable protocols, data output for EMR, system default changes, and user preference changes to the user interface. While functional testing of the software components was performed, this isn't strictly a "standalone algorithm performance" study in the sense of evaluating an AI model's diagnostic accuracy. It's about verifying that the system operates correctly according to its specifications.

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

For this type of device, ground truth would be established by:

• Design Specifications: The intended behavior and performance limits defined during the device's design.
• Regulatory Standards: Compliance with electrical safety (e.g., IEC 60601-1) and electromagnetic compatibility (e.g., IEC 60601-1-2) standards.
• Predicate Device Performance: The established safety and effectiveness of the previously cleared Arctic Sun Temperature Management System (K142702 and K002577 for pads).
  The ground truth isn't in the form of clinical outcomes or expert consensus on patient data, but rather engineering and regulatory compliance.

8. The sample size for the training set

This is not applicable. The document describes a software and hardware modification verification and validation, not a machine learning model's training process.

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

This is not applicable for the reasons stated in point 8.

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The Arctic Sun® Temperature Management System is a thermal regulating system, indicated for monitoring and controlling patient temperature in adult and pediatric patients of all ages.

The Arctic Sun Temperature Management System is a noninvasive, thermal regulating system that monitors and controls patient temperature within a range of 32°C to 38.5°C (89.6°F to 101.3°F). The Arctic Sun Temperature Management System consists of the Arctic Sun 5000 Control Module and disposable non-sterile ArcticGel Pads. The control module re-circulates temperature-controlled water to the ArcticGel Pads. A commercially-available medical temperature probe, such as naso-pharyngeal, bladder, rectal, or esophageal, connected to the control module senses the patient's core temperature. A control algorithm automatically adjusts the water temperature (automatic mode) or the clinician can adjust the water temperature (manual mode) to obtain the desired patient temperature.

The ArcticGel Pads come in various sizes to cover a broad range of patients and fit both males and females. Each pad has an inlet and an outlet connection that attaches to a fluid delivery line that is connected to the Arctic Sun 5000 Control Module. Up to six pads can be connected at one time. The pads adhere to the patient by the use of a biocompatible hydrogel adhesive

The Small Universal ArcticGel Pad and Neonatal ArcticGel Pad are modified versions of the current ArcticGel Pads and utilize an additional patient contacting fabric material.

The provided text describes a 510(k) premarket notification for the Arctic Sun Temperature Management System. It primarily focuses on demonstrating substantial equivalence to predicate devices rather than an efficacy study with specific acceptance criteria and detailed performance metrics. Therefore, many of the requested details about acceptance criteria, study design, and ground truth are not present in this document.

However, I can extract information related to the device description, biocompatibility, and performance testing, which are relevant to the device meeting certain criteria for substantial equivalence.

Here's a breakdown of the available information:

1. Table of Acceptance Criteria and Reported Device Performance

The document does not provide a table of quantitative acceptance criteria with corresponding performance metrics. Instead, it relies on comparative testing to demonstrate substantial equivalence to predicate devices. The "performance" mentioned is that the device performs as intended and its performance is substantially equivalent to predicate devices.

2. Sample Size for the Test Set and Data Provenance

The document does not explicitly state a sample size for a "test set" in the context of an efficacy study. The testing performed was "Biocompatibility and Performance Testing" for the Small Universal ArcticGel Pad and Neonatal ArcticGel Pad.

• Sample Size: Not specified. Biocompatibility testing typically involves in-vitro and in-vivo tests with specific sample numbers for each test, but these are not detailed here. Performance testing would involve a set of pads, but the quantity is not given.
• Data Provenance: Not specified, but likely from internal Medivance, Inc. studies as part of their 510(k) submission. There is no mention of country of origin of data, or if it was retrospective or prospective clinical data. It appears to be bench/laboratory testing.

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

Not applicable. The document describes biocompatibility and performance testing against industry standards (ISO 10993) and comparison to predicate devices, not an expert-driven ground truth for a clinical test set.

4. Adjudication Method for the Test Set

Not applicable, as no expert adjudication of a test set is described.

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study Was Done

No, an MRMC comparative effectiveness study is not mentioned. This is a thermal regulating system, not an imaging or diagnostic device where human reader performance with or without AI assistance would be relevant.

6. If a Standalone (i.e., algorithm only without human-in-the-loop performance) Was Done

The device is an automated system (Arctic Sun 5000 Control Module) that automatically adjusts water temperature based on a control algorithm and sensed patient core temperature. While the control algorithm operates "standalone" in automatic mode, the document does not describe "standalone performance" in the context of a diagnostic algorithm or AI system for interpretation that would typically require such studies. It details that the system's performance (including the algorithm's control) was "substantially equivalent" to predicate devices.

7. The Type of Ground Truth Used

• Biocompatibility: Ground truth was established by adherence to recognized international standards (ISO 10993-1, 10993-05, and 10993-10). These standards define the methods and acceptance criteria for cytotoxicity, irritation, and sensitization.
• Performance: Ground truth for comparative performance (cooling capacities and durations) was the performance of the predicate devices. The new pads were compared to these established devices.

8. The Sample Size for the Training Set

No training set is mentioned. This is not a machine learning device that would typically involve a "training set" for an AI algorithm.

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

Not applicable, as no training set is mentioned.

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The Arctic Sun Temperature Management System is a thermal regulating system, indicated for monitoring and controlling patient temperature.

The Arctic Sun Temperature Management System is a thermoregulatory device that monitors and controls patient temperature within a range of 32°C to 38.5 C (89.6°F to 101.3 F). The Arctic Sun System consists of the Arctic Sun Control Module and disposable ArcticGel Pads.

A patient temperature probe connected to the Control Module provides patient temperature feedback to an internal control algorithm which automatically increases or decreases the circulating water temperature to achieve a pre-set patient target temperature determined by the clinician.

The Arctic Sun pulls temperature-controlled water ranging between 4°C and 42°C (39.2°F and 107.6°F) through the ArcticGel Pads, resulting in heat exchange between the water and the patient.

Here's an analysis of the provided text regarding the Arctic Sun™ Temperature Management System, Model 5000, focusing on the requested information:

1. Table of Acceptance Criteria and Reported Device Performance

The provided text does not explicitly state specific pass/fail acceptance criteria in a quantitative format (e.g., "accuracy ±X°C"). However, it broadly describes the testing performed and the conclusion drawn.

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

The document does not provide specific sample sizes for the test set. It mentions "Full system software, performance, functional, and inspection verifications" and "Design verification of the system requirements and software validation of the control and monitor processors software requirements."

The data provenance is for a medical device submitted to the US FDA for 510(k) clearance, implying the testing was prospective as part of the device's development and regulatory submission. The country of origin for the data is not explicitly stated but is implicitly related to Medivance, Inc. in Louisville, Colorado, USA.

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

This information is not provided in the document. The testing described appears to be primarily engineering and software verification/validation, not a clinical study involving human expert judgment for "ground truth."

4. Adjudication Method for the Test Set

This information is not provided as the type of testing described (engineering/software verification) does not typically involve an adjudication method in the way a clinical study would.

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

No, an MRMC comparative effectiveness study was not done. The submission is for a thermal regulating system, and the testing described focuses on the functionality and safety of the device itself, particularly changes to the user interface and software, rather than evaluating human reader performance with or without AI assistance.

6. Standalone (Algorithm Only Without Human-in-the-Loop) Performance

Yes, effectively, a standalone performance evaluation was done. The "control algorithm" mentioned in the device description operates automatically based on patient temperature feedback. The "software validation of the control and monitor processors software requirements" would be an evaluation of this algorithm's performance in achieving and maintaining target temperatures without direct human intervention in the temperature regulation process itself.

7. Type of Ground Truth Used

For the performance aspects (monitoring and controlling temperature), the ground truth would be objective physical measurements (e.g., calibrated temperature sensors) rather than expert consensus, pathology, or outcomes data. For the software and user interface, the ground truth would be adherence to design specifications and functional requirements.

8. Sample Size for the Training Set

The concept of a "training set" is relevant for machine learning algorithms. While the device utilizes a "control algorithm," the documentation does not indicate that this algorithm was developed using machine learning with a distinct training set. It's more likely a rule-based or PID (Proportional-Integral-Derivative) control system that doesn't traditionally have a "training set" in the sense of supervised learning. Therefore, this information is not applicable/provided.

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

As explained above, a "training set" with established ground truth is not mentioned or implied for this device's control algorithm. The ground truth for developing and validating such a system typically comes from engineering principles, mathematical modeling, and previous predicate device data.

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The Arctic Sun™ Temperature Management System is a thermal regulating system, indicated for monitoring and controlling patient temperature.

The Arctic Sun Temperature Management System is a device used to monitor and control patient temperature. It consists of single-use heat transfer pads, which are adhered to areas of the patient's skin, and a control module that circulates temperature-controlled water. The control module is connected to the pads by flexible tubing. A commercially available temperature probe connected to the control module senses the patient's core temperature. The system can control the patient's core temperature by altering the temperature of the circulating water.

The provided text is a 510(k) summary for the Arctic Sun™ Temperature Management System, Model 2000. It details the device's purpose, comparison to predicate devices, and conclusions about safety and effectiveness. However, it does not include specific information about acceptance criteria or a detailed study proving the device meets those criteria in the way typically expected for an AI/ML medical device.

Here's an analysis based on the limited information provided and what is missing:

The document describes a thermal regulating system, not an AI/ML device. Therefore, the questions related to AI/ML specific studies (e.g., sample size for test set, data provenance, number of experts for ground truth, MRMC studies, standalone performance, training set details) are not applicable to this submission.

The "study" mentioned is primarily focused on electrical safety and functional performance testing in accordance with existing standards, rather than a clinical study evaluating diagnostic or prognostic accuracy with a defined ground truth.

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)

• Not applicable / Not explicitly stated. The testing described is for electrical safety and functional performance of the device unit, not clinical data involving patient test sets.

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. This device is a thermal regulating system, not an AI/ML diagnostic or prognostic tool that requires expert-established ground truth for a test set.

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

• Not applicable. See #3.

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. This is not an AI/ML device, so an MRMC study is not relevant.

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

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

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

• Not applicable. For this type of device, ground truth relates to the accuracy of temperature regulation and safety, established through engineering and performance testing against defined specifications, rather than clinical outcomes or diagnostic accuracy.

8. The sample size for the training set

• Not applicable. This is not an AI/ML device.

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

• Not applicable. This is not an AI/ML device.

Summary of what the document does indicate about the "study":

The "study" referred to in the document is primarily engineering and performance testing of the device's control unit.

• Testing Scope: Electrical safety testing (IEC601/EN60601 series) and functional safety and performance testing.
• Conclusion: Based on this testing and comparison to predicate devices, the Arctic Sun™ Temperature Management System, Model 2000, performs as intended and raises no new safety or effectiveness issues, supporting its substantial equivalence claim.

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