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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™ Stat Temperature Management System is a non-invasive, thermal regulating 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 system consists of a console, non-sterile single patient use ArcticGel™ Pads, and associated accessories.

The Arctic Sun™ Stat Temperature Management System circulates temperature-controlled water ranging between 4°C and 40°C (39.2°F and 104°F) through the ArcticGel™ Pads, resulting in heat exchange between the water and the patient. A commercially available Yellow Springs Instrument (YSI) 400 series compatible patient temperature probe connected to the console 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™ Stat console has the option to provide secure data output of device monitoring values; there is no patient-identifiable information. The data output functions, including USB, RS-232, and Wi-Fi, do not allow the user to write to the device and are intended for user convenience only.

The provided FDA 510(k) clearance letter for the Arctic Sun Stat Temperature Management System does not contain detailed information about specific acceptance criteria, study methodologies, sample sizes, or ground truth establishment for a clinical or performance study that would typically be associated with an AI/ML device clearance.

This document describes a regulatory submission for a device that has undergone software modifications and other minor changes, primarily relating to alarms, Wi-Fi support, and software anomaly corrections. The clearance is based on substantial equivalence to an existing predicate device (which is, in fact, the same device but an earlier version, K200225).

The submission emphasizes non-clinical testing and states that "No clinical testing was required to evaluate substantial equivalence." This is a key point: detailed human reader studies or extensive clinical data would generally NOT be required for a 510(k) based on substantial equivalence for this type of device (a thermal regulating system), especially when the changes are software-based and don't alter the fundamental mechanism of action or indications for use.

Therefore, many of the requested points in your prompt are not applicable (N/A) based on the information provided in this 510(k) summary. The acceptance criteria and "studies" are focused on engineering verification and validation rather than clinical performance with human-in-the-loop or standalone AI performance against a ground truth.

Here's how to address your prompt based on the provided text:

Description of Acceptance Criteria and Proving Device Meets Them

The "acceptance criteria" and "study" in this context refer to the non-clinical performance testing and verification/validation activities conducted to demonstrate that the modified Arctic Sun Stat Temperature Management System remains safe and effective, and is substantially equivalent to its predicate device. Since this is a hardware device with software modifications, the focus is on maintaining previously established performance, reliability, and safety characteristics.

The overarching acceptance criterion is demonstrating substantial equivalence to the predicate device (K200225) without raising new questions of safety or effectiveness. This is achieved through a suite of non-clinical tests.

Summary of Device Performance: The document states, "The results from this testing demonstrate that the technological characteristics and performance criteria of the subject device are substantially equivalent to the predicate device and performs in a manner equivalent to devices currently on the market for the same intended use."

1. Table of Acceptance Criteria and Reported Device Performance

Given that this is a 510(k) for software and minor hardware modifications to an existing device, the "acceptance criteria" are more akin to successful completion of verification and validation against specified design requirements and FDA-recognized standards, rather than clinical performance metrics in humans.

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

• Sample Size for Test Set: Not explicitly stated in terms of patient numbers. For non-clinical testing, "samples" would refer to the number of devices or components tested. The document lists "Artificial patient testing," which would imply a simulated environment, not human subjects. Therefore, the "sample size" for patient data is N/A (not applicable, as no clinical patient data was used for testing equivalence).
• Data Provenance: N/A (no clinical patient data used). The testing was conducted internally by Medivance, Inc.

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

• N/A: No ground truth in the context of expert consensus on medical images or diagnoses was established as this was not an AI diagnostic device or clinical study. The "ground truth" for non-clinical testing is adherence to engineering specifications, safety standards, and performance benchmarks established during the device's original development (and maintained through these modifications).

4. Adjudication Method for the Test Set

• N/A: No clinical adjudication process was performed for patient data, as no clinical patient data was used. Adjudication in this context would refer to internal quality assurance and design control processes.

5. If a Multi Reader Multi Case (MRMC) Comparative Effectiveness Study was done

• No, N/A: An MRMC comparative effectiveness study was not performed. This type of study is typical for AI-powered diagnostic imaging devices to assess the impact of AI on human reader performance. As a thermal regulating system, this is not relevant to its regulatory pathway or the type of changes involved.

6. If a Standalone (Algorithm Only Without Human-in-the-Loop Performance) was done

• Yes, in spirit (but not as a diagnostic AI model): The "Software verification," "Control accuracy and precision," and "Alarm functionality" tests represent the standalone performance of the device's algorithms and internal logic. These tests ensure the automated control and monitoring processes (the 'brains' of the device) function correctly as programmed, without direct human intervention during the measurement/control cycle itself. However, this is not an "AI diagnostic algorithm" in the typical sense of a standalone output for diagnosis.

7. The Type of Ground Truth Used

• Engineered Specifications and Standards: The "ground truth" for this device's performance validation is its design specifications, pre-established performance benchmarks, and compliance with applicable FDA-recognized consensus standards (e.g., for electrical safety, EMC, software validation, cybersecurity). For specific functionalities like temperature control, the "ground truth" is the accurate and precise maintenance of temperature within the specified range (32°C to 38.5°C), verified using calibrated equipment (e.g., in artificial patient testing).

8. The Sample Size for the Training Set

• N/A: As this device is not an AI/ML device that requires a "training set" in the common sense of machine learning, this concept does not apply. The control algorithm is likely rule-based or uses traditional control theory, not a learned model from data.

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

• N/A: See 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 Stat 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 system consists of the Arctic Sun Stat Control Module, associated accessories, and is used with the ArcticGel Pads. The Arctic Sun Stat Control Module and associated accessories are the subject of this submission. The Arctic Sun Stat Control Module circulates temperature-controlled water ranging between 4°C and 40°C (39.2°F and 104°F) through the ArcticGel Pads, resulting in heat exchange between the water and the patient. A commercially available YSI 400 series compatible patient temperature probe connected to the Arctic Sun Stat Control Module provides patient temperature feedback to an internal control algorithm, which automatically increases the circulating water temperature to achieve a pre-set patient target temperature determined by the clinician. The Arctic Sun Stat Control Module has the option to provide secure data output of device monitoring values; there is no patient-identifiable information. The data output functions, including USB, RS-232, and Wi-Fi, do not allow the user to write to the device and are intended for user convenience only.

This document is a 510(k) summary for the Arctic Sun Stat Temperature Management System. It states that "No clinical testing was required to evaluate the changes for substantial equivalence" and "No clinical data or testing was required to evaluate the proposed device modifications that are the subject of this submission."

Therefore, the provided text does not contain the information requested regarding acceptance criteria and the study that proves the device meets them, specifically:

1. A table of acceptance criteria and the reported device performance
2. Sample sized used for the test set and the data provenance
3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts
4. Adjudication method for the test set
5. If a multi-reader multi-case (MRMC) comparative effectiveness study was done, and its effect size
6. If a standalone performance study was done
7. The type of ground truth used
8. The sample size for the training set
9. How the ground truth for the training set was established

The document describes performance testing based on established methods, standards, and guidance documents to demonstrate substantial equivalence, but it explicitly states that no clinical data or testing was required. This implies that formal studies involving human subjects, expert adjudication, or complex ground truth establishment (as would be typical for AI/ML device evaluations) were not conducted for this 510(k) submission.

The "Summary of Performance Testing Used to Establish Substantial Equivalence" section mentions tests like "Artificial patient" and "Graphical user interface (GUI) testing," which are engineering or bench tests, not clinical studies involving patient data or human readers.

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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 Hybrid ArcticGel™ Pad is indicated as a standalone cooling device for the reduction of core temperature of adult patients where clinically indicated (e.g. heat stroke or hyperthermia). Additionally, the Hybrid ActicGel™ Pad is indicated as an adjunct to patient temperature control with the Arctic Sun® Temperature Management System. The Hybrid ArcticGel™ Pad is intended for use by health care professionals in all clinical environments, including, but not limited to in- hospital as well as EMS/transport settings.

The Arctic Sun Hybrid ArcticGel Pads are a modified version of the Arctic Sun ArcticGel Pads. The Hybrid ArcticGel Pad is designed to operate in two different modes, Ice Gel Mode in which is the pre-frozen pads are used as standalone devices to initiate patient cooling, and Water Flow Mode in which the pads are connected to the Arctic Sun Temperature Management System which is used to control the patient at a target temperature. These dual modes provide the opportunity for early initiation of cooling in the pre-hospital setting or the hospital emergency department followed by continued temperature management with the Arctic Sun once the ice gel is thawed. The Hybrid ArcticGel Pads are pre-frozen in a freezer operating between -3°C and -20°C (27°F and -4°F). The release liners are removed from the hydrogel adhesive, and the frozen Hybrid ArcticGel Pads are applied to the patient's skin. Between 4 and 8 pads are applied to the patient, depending on the patient's size and patient temperature reduction required. Heat from the patient is conducted through the hydrogel and pad layers into the ice gel compartment. The heat from the skin melts the ice gel. The duration of Ice Gel Mode is approximately 60 to 90 minutes from the time of application to complete melting of the Ice Gel. To convert to Water Flow Mode, pad lines are irreversibly snapped onto the inlet and outlet water ports of the Hybrid ArcticGel Pads. The pad line connectors are connected to the Arctic Sun fluid delivery line. Up to 6 Hybrid ArcticGel Pads may be connected to the Arctic Sun. Temperature controlled water from the Arctic Sun control module can then be circulated through the pad. The water passes through the water flow compartment, allowing heat to be transferred from the patient's skin across the hydrogel adhesive and into the circulating water.

The provided text describes a 510(k) summary for the Medivance Arctic Sun Hybrid ArcticGel Pad. It details the device, its intended use, and its substantial equivalence to predicate devices, supported by testing. However, it does not explicitly define acceptance criteria or detail a specific study proving the device meets those criteria in the typical sense of a clinical trial with statistical endpoints for performance.

Instead, the document focuses on comparative performance testing to demonstrate substantial equivalence to predicate devices and safety testing.

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 the format of a table with thresholds and measured performance. However, based on the Testing section, the implicit acceptance criteria are:

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

• Biocompatibility Testing: The sample size for biocompatibility testing is not specified, nor is the data provenance.
• Comparative Performance Testing: The sample size for comparative performance testing is not specified, nor is the data provenance.
• Safety Tests (Porcine Skin Model): The sample size for the porcine skin model is not specified (e.g., number of pigs or number of pads tested). The provenance is an animal model, not human data.

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

The document does not mention the use of experts to establish ground truth for any of the described tests. The tests appear to be primarily objective measurements (e.g., temperature, biocompatibility assays) rather than subjective expert evaluations.

4. Adjudication method for the test set

Not applicable, as no expert adjudication is mentioned.

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 a medical device, not an AI or imaging diagnostic tool that would typically involve human readers for interpretation.

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

Not applicable. This is a passive cooling device, not an algorithm.

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

• Biocompatibility: Ground truth would be based on established international standards (ISO 10993-05 and 10993-10) for cytotoxicity, irritation, and sensitization, likely using laboratory assays.
• Comparative Performance: Ground truth for "substantially equivalent cooling and temperature control performance" would be based on direct measurement of cooling rates and temperature stability as compared to the predicate devices. The specific metrics are not detailed but would be quantifiable.
• Safety (Porcine Skin Model): Ground truth for skin temperature would be direct temperature measurements, and "well-tolerated" would be based on observation for adverse reactions in the animal model.

8. The sample size for the training set

Not applicable. This is a medical device, not a machine learning model that requires a training set.

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

Not applicable.

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The NGT Temperature Sensor is indicated for continuous measurement of patient core (esophageal) temperature in patients using Bard® or Argyle® 16 Fr or 18 Fr nasogastric sump tubes or other 16 Fr or 18 FR nasogastric tubes with a vent lumen of sufficient diameter to allow easy movement of the sensor within the lumen.

The Medivance Nasogastric Tube (NGT) Temperature Sensor is a sterile, single use, disposable YSI400 series thermistor temperature probe that is designed for placement in the vent lumen of a 16 or 18 Fr Bard Nasogastric Sump or Argyle Salem Sump® nasogastric tube (or other 16 Fr or 18 FR nasogastric tubes with a vent lumen of sufficient diameter to allow easy movement of the sensor within the lumen) for measurement of esophageal temperature.

Here's an analysis of the provided text regarding the acceptance criteria and study for the Medivance Nasogastric Tube Temperature Sensor:

Acceptance Criteria and Device Performance

The provided text only explicitly states one accuracy specification. The other "acceptance criteria" are implied through compliance with standards.

Study Details

Based on the provided text, the study focused on technical and performance testing against recognized standards rather than a clinical trial with human subjects.

1. Sample size used for the test set and the data provenance: Not specified. The document states "Testing demonstrated that the Medivance NGT Temperature Sensor performance meets the applicable requirements...", implying lab-based performance testing rather than human patient data.
2. Number of experts used to establish the ground truth for the test set and the qualifications of those experts: Not applicable. The ground truth for performance standards is defined by the standards themselves, not by expert consensus on specific cases.
3. Adjudication method for the test set: Not applicable. The testing seems to be objective measurement against predefined technical specifications within the standards.
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: Not applicable. This device is a sensor, not an AI-assisted diagnostic tool for human readers.
5. If a standalone (i.e., algorithm only without human-in-the-loop performance) was done: Yes, the testing described appears to be standalone performance testing of the device itself against technical specifications and safety standards.
6. The type of ground truth used: Technical specifications and safety requirements outlined in the international standards BS EN 12470-4 and ISO 80601-2-56, and biocompatibility standards in ISO 10993-1.
7. The sample size for the training set: Not applicable. This technical testing does not involve a "training set" in the context of machine learning or AI.
8. How the ground truth for the training set was established: Not applicable.

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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 Blast® Intravenous Fluid Chiller is intended to cool sterile solutions during intravenous administration where clinically indicated for reduction of patient temperature.

The Arctic Blast Intravenous Fluid Chiller is composed of two main components: a heat exchanger assembly and an adsorption cooling module. The sterile fluid path is incorporated in the heat exchange assembly, which consists of the heat exchanger, a spike with vented drip chamber at the heat exchanger inlet, and a spike receptacle at the heat exchanger outlet. Prior to activation, the heat exchanger assembly inlet (spike) is connected to a liter bag of sterile fluid, and the outlet (spike port) is connected to a standard commercially-available intravenous infusion set. The heat exchanger assembly is constructed of materials and components which are commonly used in the manufacture of commercially-available intravenous infusion sets. The cooling module provides the cooling capability of the device via an adsorption process. The cooling module does not require an external power source. The cooling process is activated by pressing a button on the module. The cooling module is fully sealed and does not come into direct contact with the sterile fluid path.

The provided text does not contain specific acceptance criteria or a study detailing the device's performance against such criteria. The document is a 510(k) summary for the Arctic Blast Intravenous Fluid Chiller, focusing on its substantial equivalence to predicate devices rather than a detailed performance study.

Therefore, I cannot provide a table of acceptance criteria and reported device performance from the given information.

However, based on the provided text, I can state what is available regarding the device's characteristics and the regulatory review process:

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

• Information not available in the provided text. The document asserts substantial equivalence based on intended use, design, technological characteristics, materials, and system features/functions to predicate devices. It does not provide specific performance metrics or acceptance criteria for the Arctic Blast itself.

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

• Information not available in the provided text. The document does not describe any specific test set or clinical study for performance evaluation.

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):

• Information not available in the provided text.

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

• Information not available in the provided text.

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 thermal regulating system, not an AI-assisted diagnostic tool involving human readers.

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

• Not applicable. This device is a thermal regulating system, not an algorithm.

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

• Information not available in the provided text. As no specific performance study is detailed, the type of ground truth for any such study is also not mentioned. The substantial equivalence relies on comparison to predicate devices, which would have established their own safety and effectiveness.

8. The sample size for the training set:

• Not applicable. This device is not an AI/ML algorithm that requires a training set.

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

• Not applicable. This device is not an AI/ML algorithm that requires a training set and associated ground truth.

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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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