(235 days)
The Allon 2000 System is intended to maintain pre-set body temperature as determined by the physician. It can also be utilized to maintain normal body temperature during surgical procedures.
The Allon 2000 System is indicated primarily for use in hospital invasive and coronary care units, in operating, recovery and emergency rooms, in burn units, and on medical/surgical floors. This system can be used with adult and pediatric patients.
The Allon 2000 Hyper-Hypothermia system is used to either lower or raise a patient's temperature and/or maintain a desired patient temperature using a garment, which is wrapped around the body during and after surgery to achieve maximum coverage. This, for example, minimizes the tendency of the body to cool down as a result of anesthesia and exposure. The garment can be configured to cover any surface area of the patient's body and yet not to interfere with areas that must be exposed during surgery. As a flow of cooled or heated water is forced through the garment by the pump of the Allon 2000 System, the heat is exchanged with the body. The water temperature is controlled and maintained at any temperature between 59 and 104.3ºF (15 - 40.2ºC) using a feedback loop based on surface and core thermostat sensor readings.
Here's the information regarding the acceptance criteria and study for the Allon 2000 System, based on the provided 510(k) summary:
This document is a 510(k) summary for a medical device (Allon 2000 System) seeking clearance from the FDA. It does not describe the AI/ML device approval process, but rather a traditional medical device approval. Therefore, many of the requested fields pertaining to AI/ML device evaluation (like MRMC studies, ground truth for training/test sets, number of experts for ground truth, sample sizes for training/test sets in the context of AI) are not applicable or not provided in this type of submission.
The "acceptance criteria" for this device are broadly defined by its ability to meet established safety and performance standards, and its substantial equivalence to a predicate device.
1. A table of acceptance criteria and the reported device performance
| Acceptance Criteria Category | Specific Criteria | Reported Device Performance |
|---|---|---|
| Safety | Electrical Safety | Meets IEC 60601 and IEC 60602 standards (proven through in-vitro tests) |
| Electromagnetic Safety | Meets IEC 60601 and IEC 60602 standards (proven through in-vitro tests) | |
| Biocompatibility | Biocompatibility studies assure biological safety of the garment | |
| Effectiveness/Performance | Software Verification | Software and software applications have been verified |
| Software Validation | Software and software applications have been validated | |
| Maintain Pre-set Body Temperature | Established through in-vitro, animal, and clinical studies | |
| Maintain Normal Body Temperature during Surgery | Established through in-vitro, animal, and clinical studies | |
| Regulatory Compliance | Substantial Equivalence | Found substantially equivalent to the Blanketrol II System (Cincinnati Sub-Zero Products, Inc.) (A114385) based on safety and performance testing |
| Voluntary Standards Compliance | Complies with IEC 60601-1-1, IEC 60601-1-2, IEC 60601-2-35 - Part 2, IEC 68-2-13, MIL-STD-810E, IEC 68-2-6 |
2. Sample sized used for the test set and the data provenance (e.g. country of origin of the data, retrospective or prospective)
- Sample Size: Not specified in the provided text. The document generically states "clinical studies."
- Data Provenance: Not specified in the provided text. The submitting company is from Israel (M.T.R.E. Advanced Technologies Ltd., Caesarea Industrial Park, Israel). Clinical studies could have been conducted there or elsewhere. The study type (retrospective or prospective) is not specified.
3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts (e.g. radiologist with 10 years of experience)
- Not Applicable / Not Provided: This device is a thermal regulation system, not an AI/ML diagnostic or prognostic device that relies on expert interpretation for ground truth in its performance assessment. Its performance is measured directly by its ability to control temperature. The "experts" involved would likely be clinicians or engineers overseeing the animal and clinical studies, but their role is not to establish a "ground truth" in the AI sense.
4. Adjudication method (e.g. 2+1, 3+1, none) for the test set
- Not Applicable / Not Provided: Adjudication methods like 2+1 or 3+1 are typically used in studies where there is subjective human interpretation that needs to be reconciled to establish a consensus ground truth, common in AI/ML performance evaluation. This is not relevant for a device like Allon 2000, whose performance is based on objective physiological measurements (temperature control).
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-assisted device. Therefore, no MRMC study or assessment of human reader improvement with AI assistance would have been performed.
6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done
- Not Applicable: This is a physical thermal regulation device, not an algorithm. Its performance is inherent in its operation, not in an independent algorithm.
7. The type of ground truth used (expert concensus, pathology, outcomes data, etc)
- Physiological Measurements/Observed Outcomes: For a thermal regulation system, the "ground truth" for its performance would be the actual body temperature measurements of the subjects (in-vitro, animal, and clinical) and whether the device successfully maintained the pre-set or desired temperature. Outcomes data would relate to the success of temperature regulation and patient safety.
8. The sample size for the training set
- Not Applicable / Not Provided: This is not an AI/ML device that requires a "training set" in the computational sense. If "training set" refers to data used during early development or optimization, those details are not provided. The document mentions "in vitro, animal and clinical studies" to establish effectiveness.
9. How the ground truth for the training set was established
- Not Applicable / Not Provided: As this is not an AI/ML device, the concept of establishing ground truth for a "training set" is not relevant here. The device's efficacy is established through direct experimental evidence in controlled study environments.
§ 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).