(281 days)
The HumiGard™ Surgical Humidification System is intended to warm and humidify carbon dioxide gas from an insufflator prior to entry into the surgical cavity during laparoscopic surgery.
The HumiGard™ Surgical Humidification System is designed to warm and humidify carbon dioxide (CQ>) gas after it leaves a commercially available insufflator (used to requlate the supply of CO2 gas into the intended body cavity) and thereafter maintain the CO2 gas in a warmed and humidified condition to the point of delivery into the patient's peritoneum via heated tubing.
The HumiGard™ Surgical Humidification System is comprised of a reusable Humidifier (SH870 Humidifier), supply voltage cord (115V or 230V) and the single use, sterile Humidified Insufflation Kit (ST520).
The ST520 Insufflation Kit is ETO sterilized (SAL 10th) and provides all of the necessary components needed to deliver the heated, humidified CO2 gas during laparoscopic surgical procedures, including the insufflation tube, chamber, dry-line/filter assembly, funnel, and optional barb connector.
The SH870 Humidifier contains embedded software that controls the operation of the humidifier power and functions.
The HumiGard™ system conditions the CO2 gas by using a water-filled chamber that is seated on a heater plate on the humidifier. Once the heater plate warms to the target temperature, the heated water in the chamber produces vapour that humidifies the gas as it passes through the chamber. The surgical humidifier also provides power to the heating element (i.e., the heaterwire) within the heated insufflation tube to maintain the desired heat and humidity of the CO2 gas as it travels from the chamber to the patient interface (trocar/cannula).
The provided text describes a 510(k) premarket notification for the HumiGard™ Surgical Humidification System. It focuses on demonstrating substantial equivalence to a predicate device rather than a comprehensive study proving acceptance criteria for an AI/ML powered device.
Therefore, many of the requested details, such as those pertaining to AI/ML specific studies, human reader performance, training data, and expert consensus for ground truth, are not available in the provided document.
However, I can extract information related to the device's performance verification testing and the acceptance criteria implicitly demonstrated by that testing.
Here's a breakdown of what can be extracted and what cannot:
Information Available:
- Acceptance Criteria (Implicit through Performance Testing Categories): The document states that "Performance verification testing of the HumiGard™ system consisted of temperature output, humidity output, flow rate, leak rate, compliance, maximum delivered enthalpy, surface temperature of the tubing, condensation, and outlet connection strength. The verification testing demonstrated that the device performs as intended and met appropriate acceptance criteria." While the specific numerical acceptance criteria are not explicitly listed in a table, the types of performance metrics evaluated serve as the implicit acceptance criteria categories.
- Reported Device Performance (Comparative): The "Technical Specifications" table provides comparative performance data between the HumiGard™ system and the predicate device for some metrics.
- Sample Size for Test Set: Not explicitly stated as a "sample size" in the context of an AI/ML test set, but testing was performed on the device.
- Data Provenance (Implicit): The testing was conducted by the manufacturer, Fisher & Paykel Healthcare, which is based in New Zealand. The data is from non-clinical performance verification testing.
- Ground Truth Type: For the device's functional performance, the "ground truth" would be established by validated measurement instruments and standardized testing protocols, measuring direct physical outputs (temperature, humidity, flow, etc.).
Information NOT Available (Relevant to AI/ML context, not applicable to this device type):
- Explicit table of acceptance criteria with reported device performance (numerical values for all tests): The document lists categories of tests, but not specific pass/fail thresholds or the exact numerical results for all of them.
- Number of experts used to establish ground truth & qualifications: This is not an AI/ML diagnostic device, so expert consensus on medical images/data is not relevant for the ground truth of its physical performance.
- Adjudication method for the test set: Not applicable.
- Multi-reader multi-case (MRMC) comparative effectiveness study: Not conducted as this is a physical medical device, not a diagnostic AI tool.
- Effect size of human readers improving with AI vs. without AI assistance: Not applicable.
- Standalone (algorithm only) performance: Not applicable; this is a physical device.
- Sample size for training set & how ground truth was established for training set: Not applicable, as this is not an AI/ML device that requires training data in the typical sense.
Based on the provided text, here is the information that can be extracted, framed within the context of the device's non-clinical performance verification:
Device: HumiGard™ Surgical Humidification System
1. Table of Acceptance Criteria (Implicit) and Reported Device Performance (Comparative where available):
| Acceptance Criteria (Performance Metric) | Device Performance (HumiGard™ Surgical Humidification System) | Reported Performance of Predicate Device (Lexion Medical Insuflow Device) | Comments/Acceptance Outcome |
|---|---|---|---|
| Temperature Output | Tested | Not explicitly stated | Met appropriate acceptance criteria |
| Humidity Output | At 32.1 °C | At 32.4 °C | "Difference is not clinically significant." Meets appropriate acceptance criteria. |
| Flow Rate (Achieved) | 15 L/min | 7-8 L/min | "Achieved flow rate does not introduce any different questions of safety or effectiveness as both devices are capable of operation within the flow parameters of commercially available insufflators." Met appropriate acceptance criteria. |
| Flow Rate (Maximum Input) | ≤ 45 L/min | 40 L/min | "Equivalent." Met appropriate acceptance criteria. |
| Leak Rate | Tested | Not explicitly stated | Met appropriate acceptance criteria |
| Compliance | Tested | Not explicitly stated | Met appropriate acceptance criteria |
| Maximum Delivered Enthalpy | Tested | Not explicitly stated | Met appropriate acceptance criteria |
| Surface Temperature of Tubing | Tested | Not explicitly stated | Met appropriate acceptance criteria |
| Condensation | Tested | Not explicitly stated | Met appropriate acceptance criteria |
| Outlet Connection Strength | Tested | Not explicitly stated | Met appropriate acceptance criteria |
| Biocompatibility | Results acceptable (Cytotoxicity, Irritation, Sensitization) | Not explicitly stated | Acceptable |
| Software Verification & Validation | Complete and acceptable (for "moderate" level of concern software) | N/A | Acceptable |
| Electrical Safety (IEC 60601-1) | Conforms | N/A | Conforms |
| EMC (IEC 60601-1-2) | Conforms | N/A | Conforms |
| Sterilization Packaging (ISO 11607) | Conforms | N/A | Conforms |
| ETO Sterilization (ISO 11135) | Conforms | N/A | Conforms |
2. Sample Size for Test Set and Data Provenance:
- Sample Size: Not explicitly quantified with a numerical sample size (e.g., "N units tested"). The document states that "Performance verification testing" was conducted, implying sufficient units were tested to demonstrate performance.
- Data Provenance: The testing was non-clinical performance verification testing conducted by the manufacturer, Fisher & Paykel Healthcare, based in New Zealand. It is retrospective in the sense that results are reported after the testing was completed.
3. Number of Experts used to establish the ground truth for the test set and qualifications of those experts:
- Not applicable in the context of this device. The "ground truth" for the device's physical performance (e.g., temperature, humidity) would be established by calibrated measurement equipment and standardized methods, not by expert human interpretation like in diagnostic AI/ML.
4. Adjudication method for the test set:
- Not applicable as the testing involves direct physical measurements against predefined specifications, not subjective human evaluation requiring adjudication.
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, an MRMC comparative effectiveness study was not done. This device is a physical medical device (surgical humidification system), not an AI/ML diagnostic tool that assists human readers.
6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done:
- Not applicable. This is a physical device, and its performance is evaluated as a complete system, not as a standalone algorithm.
7. The type of ground truth used:
- For the performance testing, the ground truth was based on objective, quantitative measurements obtained via calibrated testing equipment and adherence to established engineering and medical device standards (e.g., IEC 60601-1, ISO 10993).
8. The sample size for the training set:
- Not applicable. This device is not an AI/ML product developed through machine learning from a training dataset. It's a manufactured physical product.
9. How the ground truth for the training set was established:
- Not applicable, as there is no "training set" in the context of an AI/ML model for this device.
§ 884.1730 Laparoscopic insufflator.
(a)
Identification. A laparoscopic insufflator is a device used to facilitate the use of the laparoscope by filling the peritoneal cavity with gas to distend it.(b)
Classification. (1) Class II (performance standards).(2) Class I for tubing and tubing/filter kits which include accessory instruments that are not used to effect intra-abdominal insufflation (pneumoperitoneum). The devices subject to this paragraph (b)(2) are exempt from the premarket notification procedures in subpart E of part 807 of this chapter, subject to the limitations in § 884.9.