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510(k) Data Aggregation
(168 days)
DEHAS Medical Systems GmbH
The demand valve is used for the application of 100 vol% oxygen during manual ventilation with the resuscitator bag, as well as during direct non-invasive inhalation with the resuscitator mask in spontaneously breathing patients.
The valve, non - rebreathing QualityFlow O2 demand valve is a medical device to deliver medical oxygen or a medical air - oxygen mixture to a patient on demand. Unlike continuous oxygen systems, the demand valve only supplies medical gas when the patient inhales, reducing oxygen consumption and ensuring the patient receives gas only when needed. The QualityFlow O2 Demand Valve from DEHAS consists of a membrane that is activated by negative pressure during inspiration and a valve mechanism that controls gas flow. During inspiration, the valve opens due to the movement of the membrane, while during expiration it is closed by a return spring. The function of the demand valve is based on providing gas only when a negative pressure is applied to the membrane, e.g. by the patient inhaling with a connected mask or suction of the resuscitator when connected (expansion after previous compression of the resuscitator). The valve therefore ensures that gas only flows when it is needed.
The provided document is a 510(k) Premarket Notification for a medical device called "QualityFlow O2 Demand Valve". This type of submission aims to demonstrate that a new device is substantially equivalent to a legally marketed predicate device, and thus does not require clinical studies in many cases.
Based on the provided text, the device in question (QualityFlow O2 Demand Valve) is a mechanical device, not an AI/software-driven one. Therefore, the questions related to AI/MRMC studies, training/test sets, ground truth establishment by experts, and adjudication methods are not applicable to this submission. The "acceptance criteria" discussed in this document refer to the device's ability to meet various engineering, safety, and performance standards, rather than diagnostic accuracy metrics common for AI/ML devices.
Here's an analysis based on the information relevant to this type of medical device submission:
1. Table of Acceptance Criteria (Relevant Standards) and Reported Device Performance:
The document summarizes non-clinical tests performed according to international standards to demonstrate substantial equivalence and that the device performs as intended.
| Acceptance Criteria (Standard Used) | Description of Test | Reported Device Performance |
|---|---|---|
| ISO 5356-1 Third edition 2004-05-15: Anaesthetic and respiratory equipment - Conical connectors: Part 1: Cones and sockets | Specifies the dimension and dimensional requirements for cones and bushings intended for the connection of anesthesia and ventilator equipment (e.g., in ventilation systems, anesthetic gas transport systems and vaporizers). | Result: pass |
| IEC 62366-1 Edition 1.1 2020-06 CONSOLIDATED VERSION: Medical devices - Part 1: Application of usability engineering to medical devices | Used to verify and validate the usability of the QualityFlow O2 demand valve. | Result: pass |
| ISO 14971 Third Edition 2019-12: Medical devices - Application of risk management to medical devices | Process for identification and assessment of hazards and associated risks, control of these risks, and monitoring effectiveness of risk control measures. | Result: pass |
| ISO 15001:2010: Anesthetic and respiratory equipment - Compatibility with oxygen | Used to ensure the oxygen compatibility of the used materials. | Result: pass |
| ISO 10993-1 Fifth edition 2018-08: Biological evaluation of medical devices - Part 1: Evaluation and testing within a risk management process | Used for biological evaluation of medical devices and testing within a risk management process. | Result: pass |
| ISO 18562-1 First edition 2017-03: Biocompatibility evaluation of breathing gas pathways in healthcare applications - Part 1: Evaluation and testing within a risk management process | Evaluated biocompatibility of breathing gas pathways, specifically for indirect patient contact via medical oxygen (gas pathway contact, limited exposure |
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(245 days)
DEHAS Medical Systems GmbH
The air-oxygen mixer Quality Mix is used to administer a continuous, precise mix of medical air and medical oxygen through its outlet ports - to infants, children and adults. The exact fractional inspiratory oxygen concentration (FiO2) corresponds to the selected FiO2 setting on the control knob (dial).
It is a restricted medical device intended for use by qualified, trained personnel under the direction of a physician in professional healthcare settings.
This product is not intended for use as a life supporting device.
Warning: By using flows above 70 LPM, the risk of high flow such as ar trapping, barotrauma, and gastric insufflation (leading to possible aspiration) can occur.
The air-oxygen blender Quality Mix is a compact air/oxygen mixing device, which provides a precise mixing of medical grade air and oxygen gases. The blender is a pneumatic powered device with flowmeters which can be connected to outlet ports to regulate the gas flow.
The Quality Mix series medical air / oxygen blender includes following models: Quality Mix High Flow; Quality Mix High Flow XL and Quality Mix Low Flow; Quality Mix Low Flow XL.
The Quality Mix series air / oxygen blender is designed, tested and manufactured in accordance with the standard ISO 11195:2018 Gas mixers for medical use - Stand - alone qas mixers.
The Acceptance Criteria and the study proving the device meets them are detailed below, based on the provided text.
1. Table of Acceptance Criteria and Reported Device Performance
The device is the Quality Mix Blender, Oxymixer. The acceptance criteria are largely derived from compliance with the ISO 11195:2018 standard for gas mixers for medical use and are demonstrated through performance specified in comparison to the predicate device (Precision Blender K053232).
| Acceptance Criteria (from ISO 11195:2018 and performance specifications) | Reported Device Performance (Quality Mix Blender) | Result |
|---|---|---|
| Essential Performance Requirements (Clause 4 of ISO 11195:2018) | Fulfils Clause 4 essential performance requirements | Pass |
| Clause 9: Reverse gas flow | Performs as intended | Pass |
| Clause 11: Alarm systems | Performs as intended | Pass |
| Clause 12: Accuracy of indicated oxygen concentration | ± 3% | Pass |
| Clause 13: Gas supply failure | Performs as intended | Pass |
| Primary Outlet Flow Range | High Flow: 15 – 120 LPM (at 50 psi) | Pass |
| Low Flow: 3 – 30 LPM (at 50 psi) | Pass | |
| Auxiliary Outlet Flow Range (Bleed Closed) | High Flow: 15 – 120 LPM (at 50 psi) | Pass |
| Low Flow: 3 – 30 LPM (at 50 psi) | Pass | |
| Auxiliary Outlet Flow Range (Bleed Open) | High Flow: 0 – 105 LPM (at 50 psi, with ±3% accuracy for low flows) | Pass |
| Low Flow: 0 – 27 LPM (at 50 psi, with ±3% accuracy for low flows) | Pass | |
| Bleed Flow | High Flow: ≤ 13 LPM at 50 psi | Pass |
| Low Flow: ≤ 3 LPM at 50 psi | Pass | |
| Maximum Combined Flow (all outlets) | High Flow: ≥ 120 LPM | Pass |
| Low Flow: ≥ 30 LPM | Pass | |
| Bypass Flow (loss of air or oxygen supply) | High Flow: > 85 LPM | Pass |
| Low Flow: > 15 LPM | Pass | |
| Bypass Alarm Activation (pressure difference) | Activates when pressure difference ≥ 13.05 psi (0.9 bar) | Pass |
| Alarm Reset | Resets when pressure difference ≤ 4.35 psi (0.3 bar) | Pass |
| Alarm Sound Level | ≥ to 80 dB at 1 ft (0.3 m) | Pass |
| Oxygen Concentration Adjustment Range | 21 – 100 % | Pass |
| Gas Supply Pressure | 46.41 – 94.27 psi (3.2 – 6.5 bar) | Pass |
| Air and oxygen pressure differential | Should be within max 0.7 bar | Pass |
| Mixed Gas Stability | ± 1% Oxygen | Pass |
| Operating Temperature Range | 41°F to 122°F (5°C to 50°C) | Pass |
| Pressure Drop | High Flow: ≤ 0.21 bar at 30 LPM and 60% FiO2 (inlet 3.2-6.5 bar) | Pass |
| Low Flow: ≤ 0.14 bar at 10 LPM and 60% FiO2 (inlet 3.2-6.5 bar) | Pass | |
| Biocompatibility (ISO 18562-1, -2, -3) | Pass for particulate matter and VOC emissions | Pass |
| Risk Management (ISO 14971) | Applied for hazard identification, risk control, and monitoring | Pass |
| Usability (IEC 62366-1) | Verified and validated | Pass |
| Environmental Testing (Strength, Vibration, Shock) | Passed EN 1789, EN 60068-2-6, EN 60068-2-27, EN 60068-2-64 | Pass |
| Flow-metering devices (DIN EN ISO 15002) | Flowmeter accuracy, leak test, environmental, and mechanical condition met | Pass |
| Oxygen Compatibility (ISO 15001) | Ensured oxygen compatibility of used materials | Pass |
2. Sample Size Used for the Test Set and Data Provenance
The provided text describes non-clinical performance and safety testing. There is no mention of a "test set" in the context of patient data or clinical samples for the device itself. The testing was performed on the device units in a laboratory setting. No specific sample size (i.e., number of devices tested) is explicitly stated for each test, but it is implied that testing was conducted on representative units of the Quality Mix Blender series. The provenance of this data is from the manufacturer's internal testing as well as cooperation with an authorized, certified competence center for medical oxygen blenders for usability testing (likely in Germany, as the manufacturer is based in Germany). This is a retrospective analysis of device performance against established standards.
3. Number of Experts Used to Establish the Ground Truth for the Test Set and Their Qualifications
This information is not applicable as the study described is non-clinical performance testing of a medical device against engineering standards, not a diagnostic or AI-assisted clinical study requiring expert ground truth in the traditional sense. The "ground truth" for these tests are the objective measurements and specifications outlined in the referenced international standards (e.g., ISO 11195:2018, IEC 62366-1, ISO 14971).
4. Adjudication Method for the Test Set
Not applicable. This was non-clinical device performance and safety testing against established engineering and performance standards, not a clinical study involving human interpretation or adjudication.
5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study Was Done, and the Effect Size of How Much Human Readers Improve with AI vs. Without AI Assistance
No, an MRMC comparative effectiveness study was not done. This submission is for a breathing gas mixer, which is a hardware device (Quality Mix Blender), not an AI-powered diagnostic or assistive tool. Therefore, the concept of human readers improving with AI assistance is not relevant to this submission.
6. If a Standalone (Algorithm Only Without Human-in-the-Loop Performance) Was Done
Not applicable. As stated above, this is a hardware device, not an algorithm or AI-powered system.
7. The Type of Ground Truth Used
The ground truth used for these evaluations is based on International Standards and established engineering specifications. These include:
- ISO 11195:2018 (Gas mixers for medical use - Stand-alone gas mixers)
- ISO 14971:2007 (Medical devices - Application of risk management to medical devices)
- IEC 62366-1:2015 (Medical devices - Application of usability engineering to medical devices)
- EN 1789:2007+A2:2014 (Medical vehicles and their equipment - Road ambulances)
- EN 60068-2-6:2008 (Environmental testing - Part 2-6: Tests - Test Fc: Vibration (sinusoidal))
- EN 60068-2-27:2009 (Environmental testing - Part 2-27: Tests - Test Ea and guidance: Shock)
- EN 60068-2-64:2008 (Environmental testing – Part 2-64: Tests – Test Fh: Vibration, broadband random and guidance)
- DIN EN ISO 15002:2020-05 (Flow-metering devices for connection to terminal units of medical gas pipeline systems)
- ISO 15001:2010 (Anesthetic and respiratory equipment - Compatibility with oxygen)
- ISO 18562-1, -2, -3 (Biocompatibility evaluation of breathing gas pathways in healthcare applications)
These standards define the performance metrics, test methods, and acceptable ranges for the device's functionality, safety, and compatibility.
8. The Sample Size for the Training Set
Not applicable. There is no "training set" as this is a hardware medical device, not a machine learning or AI algorithm.
9. How the Ground Truth for the Training Set Was Established
Not applicable, as there is no training set for this device.
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