Search Results

The Swabbable Cap provides temporary aseptic closure of the male luer connector of the IV tubing while disconnected from the patient, replacing the need for disposable caps to maintain aseptic procedure. The device is designed to be permanently attached to an IV administration set and used over the life of the administration set.

Provides temporary aseptic closure of the male luer connector of the IV tubing while disconnected from the patient, replacing the need for disposable caps to maintain aseptic procedure.

This looks like a 510(k) premarket notification for a medical device called the "PadLock™ Swabbable Cap." This document does not describe a study involving AI or machine learning. It describes a traditional medical device and its predicate device. Therefore, many of the requested fields related to AI study design and performance evaluation are not applicable.

Here's an analysis based on the provided text, focusing on what can be extracted:

1. Table of Acceptance Criteria and Reported Device Performance

The provided text does not contain explicit acceptance criteria or a detailed report of device performance from a study. It describes the device, its intended use, classification, and predicate device. The 510(k) process primarily demonstrates substantial equivalence to a predicate device, which often involves comparison of technological characteristics and performance specifications rather than a new study with explicit acceptance criteria provided in this summary.

2. Sample size used for the test set and the data provenance

Not applicable, as no clinical study or test set for an algorithm is described in this document. This is a traditional medical device submission.

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts
Not applicable.

4. Adjudication method (e.g. 2+1, 3+1, none) for the test set
Not applicable.

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/ML device.

6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done
Not applicable. This is not an AI/ML device.

7. The type of ground truth used (expert consensus, pathology, outcomes data, etc.)
Not applicable.

8. The sample size for the training set
Not applicable.

9. How the ground truth for the training set was established
Not applicable.

Ask a specific question about this device