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Datascope's 10 Fr. FlexiSheath™ Percutaneous Introducer is intended for the percutaneous introduction of Datascope's 9.5Fr. Intra-Aortic Balloon Catheters.

Datascope's 10 Fr. FlexiSheath™ Percutaneous Introducer is intended for the percutaneous introduction of Datascope's 9.5 Fr. Intra-Aortic Balloon Catheters.

The provided text describes a 510(k) premarket notification for Datascope's 10 Fr. FlexiSheath™ Percutaneous Introducer. In the context of 510(k) submissions, the concept of "acceptance criteria" and a "study that proves the device meets the acceptance criteria" in the traditional sense of a clinical trial with predefined performance metrics and statistical endpoints is generally not applicable for devices seeking substantial equivalence.

Instead, the submission aims to demonstrate that the new device is "substantially equivalent" to predicate devices already on the market. This is done by showing that the new device has similar technological characteristics and performance, and does not raise different questions of safety and effectiveness.

Here's an analysis of the provided text based on your request, interpreting "acceptance criteria" as the demonstration of substantial equivalence and "study" as the non-clinical testing performed:

1. Table of Acceptance Criteria (Substantial Equivalence Pillars) and Reported Device Performance

2. Sample size used for the test set and the data provenance (e.g. country of origin of the data, retrospective or prospective)

• Sample Size for Test Set: The document mentions "in-vitro tests" but does not specify the sample size used for these tests.
• Data Provenance: The document does not specify the country of origin of the data or whether the tests were retrospective or prospective. Given that this is an in-vitro study for a US submission, it's highly likely the tests were conducted in a US-based lab, but this is not explicitly stated. The tests are prospective in nature as they evaluate the device's characteristics.

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 or provided in the context of this 510(k) submission. For in-vitro tests demonstrating substantial equivalence, "ground truth" is typically established by engineering specifications, validated test methods, and comparison against the performance of predicate devices, not by expert consensus on clinical data. No human experts evaluating test results for "ground truth" are mentioned.

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

• This information is not applicable or provided. Adjudication methods are typically used in clinical studies involving interpretation of medical images or patient outcomes, not for in-vitro engineering tests.

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 type of study is relevant for AI-powered diagnostic devices, which is not the nature of Datascope's 10 Fr. FlexiSheath™ Percutaneous Introducer.
• The device is a medical introducer sheath, a physical medical device, not an AI or imaging diagnostic tool. Therefore, the concept of human readers improving with AI assistance is not applicable.

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

• No, a standalone (algorithm only) study was not done. As mentioned, this is a physical medical device, not an algorithm or software. Its performance is evaluated through physical and material properties, and functionality in a lab setting.

7. The type of ground truth used (expert consensus, pathology, outcomes data, etc.)

• For the non-clinical tests, the "ground truth" would be established by engineering specifications, validated test methods, and direct comparison of performance metrics (e.g., tensile strength, flexibility, lubricity, burst pressure, flow rates, etc.) against the established performance of the predicate devices. It is not based on expert consensus, pathology, or outcomes data.

8. The sample size for the training set

• This information is not applicable or provided. The concept of a "training set" and "validation set" is relevant for machine learning algorithms. This submission is for a physical medical device and relies on engineering and material characteristic tests rather than data-driven model training.

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

• This information is not applicable or provided as there is no "training set" in the context of this device and its substantial equivalence submission.

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The intra-aortic balloon is placed in the descending aorta just below the subclavian artery and is intended to improve cardiovascular functioning during the following situations:

Refractory ventricular failure Cardiogenic shock Unstable refractory angina Impending infarction Mechanical complications due to acute myocardial infarction Ischemic related intractable ventricular arrhythmias Cardiac support for high risk surgical patients and coronary angiography or angioplasty patients Septic shock Weaning from cardiopulmonary bypass Interoperative pulsatile flow generation Support for failed angioplasty and valvuloplasty

The intra-aortic balloon is placed in the descending aorta just below the subclavian artery and is intended to improve cardiovascular functioning during the following situations:

Refractory ventricular failure Cardiogenic shock Unstable refractory angina Impending infarction Mechanical complications due to acute myocardial infarction Ischemic related intractable ventricular arrhythmias Cardiac support for high risk surgical patients and coronary angiography or angioplasty patients Septic shock Weaning from cardiopulmonary bypass Interoperative pulsatile flow generation Support for failed angioplasty and valvuloplasty

The provided 510(k) summary for the Datascope Percor STAT-DL® 9.5Fr. & 10.5 Fr. Intra-Aortic Balloon (IAB) does not contain specific acceptance criteria or a detailed study proving the device meets said criteria in the way typically expected for an AI/ML device.

This document describes a medical device from 1997, which predates the widespread use of AI/ML in medical devices and the regulatory frameworks associated with them. The criteria for demonstrating safety and effectiveness at that time were different.

Here's an analysis based on the provided text, highlighting the absence of the requested AI/ML specific information:

1. A table of acceptance criteria and the reported device performance

The document does not provide a table of acceptance criteria nor specific performance metrics in the way a modern AI/ML device submission would. Instead, it relies on demonstrating substantial equivalence to predicate devices. The "reported device performance" is implicitly that it functions comparably to the predicates.

2. Sample size used for the test set and the data provenance (e.g. country of origin of the data, retrospective or prospective)

• Test Set Sample Size: Not applicable. There was no "test set" in the context of an AI/ML model for this submission. The "tests" mentioned are in-vitro physical/mechanical tests.
• Data Provenance: Not applicable for an AI/ML test set. The in-vitro tests would have been conducted in a lab setting.

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)

Not applicable. This device is not an AI/ML diagnostic or prognostic tool that relies on expert consensus for ground truth. Its safety and effectiveness are established through engineering design, material science, and mechanical testing, comparing it to existing, approved devices.

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

Not applicable. There was no expert adjudication process for this type of device submission.

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 designed to assist human readers.

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

Not applicable. This is a physical medical device (an intra-aortic balloon), not an algorithm.

7. The type of ground truth used (expert consensus, pathology, outcomes data, etc)

Not applicable. For this device, "ground truth" would relate to the physical and chemical properties of the device components and its functional operation when tested in vitro, compared against specifications or performance of predicate devices.

8. The sample size for the training set

Not applicable. There is no AI/ML model, and therefore no training set.

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

Not applicable. There is no AI/ML model, and therefore no training set or ground truth establishment for it.

Summary of the Study and Conclusion from the Document:

The "study" presented is a demonstration of substantial equivalence (through non-clinical tests) to legally marketed predicate devices.

• Non-Clinical Tests: In-vitro tests were conducted to demonstrate that the functionality and performance characteristics of the new device (Datascope Percor STAT-DL® 9.5Fr. & 10.5Fr. IAB) are comparable to the currently marketed predicate devices. The differences in material grade and chemical composition were analyzed and demonstrated not to affect safety or efficacy.
• Clinical Tests: The document explicitly states, "There has been no clinical evaluation of the new device in the U.S." This further emphasizes that the approval was based on non-clinical data and substantial equivalence.
• Conclusion: Based on the information from the in-vitro tests and comparison to predicate devices, Datascope's Percor STAT-DL® 9.5Fr. & 10.5Fr. IABs were considered substantially equivalent to Datascope's currently marketed IABs. This substantial equivalence is the "proof" that the device met the (implied) regulatory acceptance criteria for market clearance in 1997.

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