(131 days)
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.
| Acceptance Criterion (Test Category) | Reported Device Performance (Outcome) |
|---|---|
| System Mechanical Verification | Met requirements; functionally equivalent to predicate. |
| System Electrical Safety | Met requirements; functionally equivalent to predicate. |
| Electrical Reliability | Met requirements; functionally equivalent to predicate. |
| Software Verification | All new system and software requirements verified successfully. Function of device modifications confirmed. Equivalent to predicate with enhancements. |
| Control Accuracy and Precision | Met requirements; equivalent to predicate. |
| Electromagnetic Compatibility | Met requirements. |
| Radio Frequency | Met requirements. |
| Alarm Functionality | Verified new alarm conditions, prioritization, and user explanatory text. Met requirements and improved safety profiles. Equivalent to predicate with enhancements. |
| Artificial Patient Testing | Met requirements; equivalent to predicate's control capabilities. |
| Cybersecurity | Met relevant cybersecurity standards and requirements; secure data output confirmed. |
| Packaging Integrity | Met requirements. |
| Human Factors and Validation | Conducted to ensure user interface changes (e.g., new notification banner, alarm text) are suitable and safe. Met requirements. |
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.
§ 870.5900 Thermal regulating system.
(a)
Identification. A thermal regulating system is an external system consisting of a device that is placed in contact with the patient and a temperature controller for the device. The system is used to regulate patient temperature.(b)
Classification. Class II (performance standards).