(30 days)
The SealGuard Evac Endotracheal tube is indicated for airway management by oral/nasal intubation of the trachea, and for evacuation or drainage of the subglottic space.
The SealGuard Endotracheal tube is a device inserted into a patient's trachea via the nose or mouth to maintain an open airway.
The SealGuard™ and the SealGuard™ Oral Evac Tracheal Tubes are sterile, single-use devices supplied with a standard 15mm connector. On the Evac tubes, in addition to the main lumen, the tube has a separate Evac lumen which has a dorsal opening above the cuff. Access to the lumen is accomplished via a clear connecting tube with a capped Luer connector. The tube features a unique ultra thin high volume low pressure cuff and self sealing valve with attached pilot balloon. The unique cuff material of the SealGuard products ideally gives an improved sealing performance over historical PVC cuffed product. The tube incorporates a Magill curve, a hooded tip with Murphy Eye and a Tip-To-Tip™ radiopaque line to assist in radiographic visualization.
This document is a 510(k) summary for the SealGuard Endotracheal Tube and SealGuard Evac Endotracheal Tubes. It primarily focuses on demonstrating substantial equivalence to predicate devices and does not contain detailed information about a study proving the device meets specific acceptance criteria in the way one might expect for a novel AI/software medical device.
Therefore, many of the requested sections (sample size, experts, adjudication, MRMC, standalone performance, ground truth establishment, training set size) are not applicable or cannot be extracted from the provided text, as the submission is for a physical medical device (endotracheal tube) and its performance is typically evaluated through bench testing and clinical equivalence, not machine learning model evaluation.
Here's an analysis based on the provided text, addressing the applicable points and noting where information is not present:
Acceptance Criteria and Device Performance Study
The document does not explicitly present a table of "acceptance criteria" with quantitative metrics for performance and corresponding study results in the context of a software or AI device. Instead, the submission for this physical device focuses on demonstrating substantial equivalence to existing predicate devices (Hi-Lo Cuffed Tracheal Tube K871204 and Hi-Lo Evac Endotracheal Tubes K965132). This means the "acceptance criteria" are implicitly met by demonstrating that the new device is as safe and effective as the predicate device(s) for the stated indications for use.
The primary differences between the proposed and predicate devices are:
- Cuff material: PU (polyurethane) for SealGuard vs. PVC (polyvinylchloride) for predicate.
- Cuff shape: Tapered for SealGuard vs. barrel shape for predicate.
The study that "proves" the device meets the acceptance criteria (i.e., is substantially equivalent) would typically involve a combination of:
- Bench testing: To compare physical characteristics, sealing ability, and other performance metrics against the predicate devices.
- Biocompatibility testing: To ensure the new cuff material is safe.
- Design verification and validation: To confirm the device consistently performs as intended.
However, the provided text does not include the details of these studies or their specific results, nor does it list quantitative acceptance criteria. It only states that the device "maintain the same intended use as the predicate device" and "consist of the same fundamental technology." The FDA's letter confirms substantial equivalence based on the submitted information.
1. A table of acceptance criteria and the reported device performance
- Acceptance Criteria: Not explicitly stated in a quantitative table format within the provided text. The overall acceptance criterion is "substantial equivalence" to the predicate devices. This implies meeting the same safety and effectiveness standards, likely through performance testing related to sealing, material properties, and functionality consistent with an endotracheal tube.
- Reported Device Performance: Not detailed in a quantitative table within the provided text. The document describes the device's features (e.g., "unique ultra thin high volume low pressure cuff," "improved sealing performance over historical PVC cuffed product") but does not provide specific performance data or a direct comparison to predicate device data.
2. Sample sized used for the test set and the data provenance (e.g. country of origin of the data, retrospective or prospective)
This information is not applicable/not provided as the submission is not for an AI/software device that typically utilizes "test sets" of data for performance evaluation. The "study" mentioned is likely a set of engineering tests and possibly small-scale clinical equivalence evaluations (though not detailed here) for a physical medical device.
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)
This information is not applicable/not provided. Ground truth in the context of AI/software refers to the expert-labeled data used to evaluate algorithm performance. For a physical device, performance is typically assessed through direct measurement, mechanical testing, and observation, often against established standards or predicate device performance, rather than expert-labeled "ground truth."
4. Adjudication method (e.g. 2+1, 3+1, none) for the test set
This information is not applicable/not provided. Adjudication methods are relevant for resolving discrepancies in expert labeling for ground truth in AI studies.
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
This information is not applicable/not provided. An MRMC study is specific to evaluating diagnostic performance with and without AI assistance for tasks involving human interpretation of medical images or data. This is not relevant to an endotracheal tube.
6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done
This information is not applicable/not provided. "Standalone performance" refers to the performance of an algorithm without human intervention, which is not relevant for a physical medical device like an endotracheal tube.
7. The type of ground truth used (expert consensus, pathology, outcomes data, etc)
This information is not applicable/not provided. For a physical medical device, "ground truth" relates more to whether the device physically functions as intended and meets specifications (e.g., does the cuff inflate and seal effectively? Is the material biocompatible?). This is confirmed through engineering tests and material analysis rather than establishing "ground truth" from experts or pathology in the AI sense.
8. The sample size for the training set
This information is not applicable/not provided. A "training set" is used to develop and train machine learning models, which is irrelevant for this physical medical device submission.
9. How the ground truth for the training set was established
This information is not applicable/not provided for the same reasons as point 8.
§ 868.5730 Tracheal tube.
(a)
Identification. A tracheal tube is a device inserted into a patient's trachea via the nose or mouth and used to maintain an open airway.(b)
Classification. Class II (performance standards).