(287 days)
Precision Flow™ is intended for use to add warm moisture to breathing gases from an external source for administration to a neonate/infant, pediatric and adult patients in the hospital, sub-acute institutions, and home settings. It adds heat and moisture to a blended medical air/oxygen mixture and assures the integrity of the precise air/oxygen mixture via an integral oxygen analyzer. The flow rates may be from 1 to 40 liters per minute via nasal cannula.
The Precision Flow™ consists of two parts: The main unit which contains all the electrical and electronic components including the electronic blender and flow controllers. All the sensors are located in the main unit. The main unit has no water pathways and the gas pathway contains only dry gas at room temperature, and consequently does not need internal cleaning or disinfection. The disposable components comprising the disposable water module, vapor transfer cartridge and heated delivery tube. Conditions in the circulating water and gas streams are sensed remotely via the interface between the main unit and the disposable module.
This 510(k) summary describes a medical device, the Vapotherm Precision Flow™, which is a respiratory gas humidifier. It is not an AI/ML powered device, therefore, many of the requested categories related to AI performance, ground truth, and expert evaluation are not applicable.
Here's an analysis of the provided text based on your request, highlighting the non-applicability of AI/ML specific criteria:
Acceptance Criteria and Device Performance (Non-AI/ML Device)
The Vapotherm Precision Flow™ is cleared based on demonstrating substantial equivalence to predicate devices, primarily through non-clinical performance data (testing) and a comparison of its technological characteristics to existing devices. The "acceptance criteria" here are implicitly that the device performs its intended functions (humidifying and blending medical gases) safely and effectively, and that these performance characteristics are comparable to legally marketed predicate devices without raising new safety or effectiveness concerns.
Since this is not an AI/ML device, performance metrics like sensitivity, specificity, accuracy, or AUC are not applicable or reported in this 510(k) summary. Instead, the performance is demonstrated through various engineering, safety, and biocompatibility tests.
| Acceptance Criteria (Implied) | Reported Device Performance |
|---|---|
| Biocompatibility: No adverse biological reactions. | Biocompatibility Tests (LLNA, Intracutaneous Reactivity, MEM Elution): Performed, implying acceptable results (otherwise it wouldn't be marketed). |
| Emissions: No harmful volatile organic compounds or particulates. | Volatile Organic Compounds (VOC), Particulate Matter tests: Performed to recognized standards, implying acceptable results. |
| Electrical Safety: Meets international safety standards. | EMC Test, Emissions Test, Safety Inspection Test, IEC 60601-1, IEC 60601-1-4, IEC 60601-1-8: Performed, ensuring compliance with general requirements for safety, programmable electrical medical systems, and alarm systems. |
| Microbiological Safety: No detectable bacteria after extended use. | Bio Burden, 30 Day Comparative Use Testing: "No detectible bacteria in any water condensation samples from the Precision Flow® devices either initially (3 days) or after 30 days of operation." |
| Software Functionality: Verified and validated. | Ximedica TRP 1097, TRP 1071 (Black Box), Unit Test Case Listing - 3VAP1004/TRP 1092 (White Box): Software verified and validated in accordance with applicable FDA guidance. |
| Thermal Stability: Maintains temperature regulation. | Thermal Stability: Performed, indicating proper temperature control. |
| Blender Accuracy: Maintains precise air/oxygen mixture. | Blender Comparison Performance: Performed, indicating comparable performance to predicate blenders, assuring integrity of the precise air/oxygen mixture via an integral oxygen analyzer. |
| Substantial Equivalence: Comparable to predicate devices. | The device has the same intended uses and similar indications, technological characteristics, and principles of operation as its predicate devices. Performance data demonstrate it is as safe and effective as the predicate devices, with minor differences raising no new issues. |
Non-Applicable (N/A) for AI/ML Specific Questions:
Given that K072845 describes a humidifier, not an AI/ML-powered device, the following categories are not applicable. The submission process for such a device focuses on engineering specifications, safety testing, and performance validation against established standards and predicate devices, rather than statistical performance against a ground truth dataset.
2. Sample size used for the test set and the data provenance: N/A (Not an AI/ML device, no "test set" in the context of an algorithm's classification/prediction performance). Testing involved physical hardware, software, and biological compatibility, not a data-driven test set.
3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts: N/A (Not an AI/ML device, no ground truth established by experts for algorithmic performance).
4. Adjudication method (e.g., 2+1, 3+1, none) for the test set: N/A (Not an AI/ML device, no adjudication of algorithm outputs).
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: N/A (Not an AI/ML device. No human-in-the-loop AI assistance involved).
6. If a standalone (i.e., algorithm only without human-in-the-loop performance) was done: N/A (Not an AI/ML device, no standalone algorithm performance to evaluate).
7. The type of ground truth used (expert consensus, pathology, outcomes data, etc.): N/A (Not an AI/ML device). The "ground truth" for this device relates to physical measurements meeting specifications (e.g., oxygen percentage, temperature, bacterial counts being zero).
8. The sample size for the training set: N/A (Not an AI/ML device, no "training set"). Software verification and validation are described, but this refers to traditional software engineering processes, not machine learning model training.
9. How the ground truth for the training set was established: N/A (Not an AI/ML device, no "training set" or ground truth in the ML context).
§ 868.5450 Respiratory gas humidifier.
(a)
Identification. A respiratory gas humidifier is a device that is intended to add moisture to, and sometimes to warm, the breathing gases for administration to a patient. Cascade, gas, heated, and prefilled humidifiers are included in this generic type of device.(b)
Classification. Class II (performance standards).