Search Results

Sapphire Primary Sets are indicated for the delivery of fluids from a container to a patient's vascular system.
Sapphire Blood Sets are indicated for the delivery of fluids including but not limited to blood and blood products to a patient's vascular system.
Sapphire Epidural Sets are indicated for the delivery of fluids from a container to a patient's epidural space.

Sapphire Sets are intended for use with the Sapphire Infusion System. Sapphire sets are comprised of various components including the following: male luer adapter with cap, female luer with cap, piercing pin connector, sapphire cassette, tubing, flow control device, filter, in-line adapter, injection site assembly, check valve, pressure activated valve and blood chamber. Sapphire sets are configured to ensure the intended use of the device is met. The sets are disposable devices for single patient use.

The provided text describes the 510(k) summary for "Sapphire Sets," which are administration sets intended for use with the Sapphire Infusion System. This document focuses on demonstrating substantial equivalence to predicate devices for regulatory approval, rather than detailing the performance of an AI/ML-driven medical device. Therefore, a direct answer to the request regarding acceptance criteria and study proving performance for an AI/ML device, as outlined in the prompt, cannot be fully provided from this document.

The document discusses non-clinical tests for the infusion set components, assuring their material and functional integrity, and their compatibility with the Sapphire Infusion System. It does not refer to AI/ML device performance or associated studies like MRMC or standalone algorithm performance.

However, I can extract information related to the closest aspects from the document:

1. Table of acceptance criteria and reported device performance:

The document doesn't provide a typical "acceptance criteria vs. reported performance" table like one would expect for an AI/ML algorithm with metrics like sensitivity, specificity, or AUC. Instead, it lists the types of non-clinical tests performed to demonstrate that the new Sapphire Sets perform as intended and meet applicable standards, confirming they are "acceptable."

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

This document does not specify a "test set" in the context of an AI/ML algorithm validating against a dataset. The testing described is for physical properties and functionality of medical device components. The document implies laboratory testing of device samples. Data provenance (country of origin, retrospective/prospective) is not relevant to this type of device submission.

3. Number of experts used to establish the ground truth for the test set and qualifications of those experts:

Not applicable. Ground truth for an AI/ML algorithm involving expert review is not relevant to the physical and functional testing of an infusion set.

4. Adjudication method (e.g. 2+1, 3+1, none) for the test set:

Not applicable. This is not an image-based or diagnostic AI/ML device where adjudication methods for ground truth would be used.

5. If a multi-reader multi-case (MRMC) comparative effectiveness study was done:

No. This type of study is for evaluating human performance (e.g., radiologists) with and without AI assistance, which is not applicable to an infusion set.

6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done:

No. This document is not about an AI/ML algorithm.

7. The type of ground truth used:

The 'ground truth' for the Sapphire Sets relates to established engineering standards (e.g., ISO standards for material properties, leakage, tensile strength, flow rate accuracy) and biological safety tests. It's based on objective, quantitative measurements and adherence to recognized industry standards, rather than expert consensus on diagnostic interpretations or clinical outcomes in the way an AI/ML model's performance would be assessed.

8. The sample size for the training set:

Not applicable. This document is not about an AI/ML algorithm.

9. How the ground truth for the training set was established:

Not applicable. This document is not about an AI/ML algorithm.

In summary: The provided document is a 510(k) premarket notification for a medical device (infusion sets) demonstrating substantial equivalence to predicate devices, primarily through engineering and material testing, and compliance with established standards. It does not describe the evaluation of an AI/ML medical device as outlined in the prompt's detailed questions.

Ask a specific question about this device

Hospira Sapphire Sets are indicated for the delivery of fluids from a container to a patient's vascular system.

Hospira Sapphire Sets are intended for use with the Sapphire Infusion System. Hospira Sapphire sets are comprised of various components including the following: male luer adapter with cap, female luer with cap, piercing pin connector, sapphire cassette, tubing, flow control device, in-line adapter, injection site assembly, check valve, and burette chamber. Hospira Sapphire sets are configured to ensure the intended use of the device is met. The sets are disposable devices for single patient use.

The document describes a 510(k) premarket notification for Hospira Sapphire Sets, an accessory for infusion pumps. The submission aims to demonstrate substantial equivalence to a predicate device.

Here's an analysis of the acceptance criteria and study information, based only on the provided text. Many of the requested details about acceptance criteria and study specifics are not explicitly stated in this type of regulatory document, which focuses on demonstrating equivalence rather than a full clinical trial.

1. Table of acceptance criteria and the reported device performance:

The document outlines a series of tests performed to establish substantial equivalence, primarily focusing on materials, design, and performance characteristics compared to the predicate device. Specific numerical acceptance criteria are generally not provided in this summary. Instead, it states that "All testing is acceptable."

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

• Sample Size: The document does not specify the sample sizes used for any of the tests (biocompatibility, particulate contamination, leakage, tensile strength, or flow rate accuracy).
• Data Provenance: The tests were conducted to demonstrate substantial equivalence of the "Hospira Sapphire Sets," which are described as a "combination of Hospira IV set components with the Sapphire Cassette." The testing was performed for the new device as part of the 510(k) submission. It relates to the safety and performance of the device itself and its interaction with the Sapphire Infusion System. This would be considered prospective testing conducted by the manufacturer for regulatory submission. Country of origin of the data is not specified, but the applicant is Hospira, Inc. in Lake Forest, Illinois, USA.

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts:

This is not applicable to this type of device submission. The "ground truth" for infusion pump accessories, in this context, is established through adherence to recognized international standards (e.g., ISO) and engineering performance specifications. There is no concept of expert "ground truth" establishment in the way it might apply to diagnostic AI or imaging devices.

4. Adjudication method for the test set:

This is not applicable. Adjudication methods like 2+1 or 3+1 are used in clinical studies, particularly for diagnostic devices where subjective interpretation (e.g., by radiologists) needs independent review to establish a consensus ground truth. For an infusion set, performance is measured against objective physical and chemical standards.

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 is not applicable. MRMC studies are relevant for diagnostic devices, especially those incorporating AI, where human "readers" (e.g., clinicians interpreting images) are part of the diagnostic process and their performance might be augmented by AI. The Hospira Sapphire Sets are infusion pump accessories, not diagnostic imaging devices or AI-powered tools for interpretation.

6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done:

This is not applicable. The device is an infusion set, not an algorithm or an AI-powered system. The tests described are for the physical and functional performance of the medical device itself.

7. The type of ground truth used:

The "ground truth" for the performance claims of the Hospira Sapphire Sets is based on adherence to recognized international standards (e.g., ISO 10993, ISO 8536-4, ISO 1135-4) and the engineering specifications and performance characteristics demonstrated to be "acceptable" through the conducted tests. It's essentially "compliance with established safety and performance benchmarks."

8. The sample size for the training set:

This is not applicable. The device is a physical medical device (infusion set), not a machine learning model that requires a training set.

9. How the ground truth for the training set was established:

This is not applicable for the same reason as point 8.

Ask a specific question about this device