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Refractory left ventricular power failure. Cardiogenic shock unstable refractory angina. Mechanical complication due to acute myocardial infraction; i.e., ventricular sepial defect mitral regurgitation or papillary muscle rupture. Impending infraction, ischemia related intractable ventricular arrhythmias. Septic shock. Support for failed angioplasty and valvuloplasty. Cardiac support for high risk general surgical patients.

This device is identical in construction to the predicate sheathless 8 Fr-40cc NarrowFlex™ device IAB-04840S with the exception of the 30cc balloon and shorter overall length. The balloon volume and the overall length have been adapted from the 8 Fr-30cc Sheathless IAB-04230S predicate.

This 510(k) summary (K963865) describes a substantial equivalence claim for an intra-aortic balloon catheter, the Arrow 8Fr - 30cc Narrowflex™ Sheathless Intra-Aortic Balloon Catheter. The document focuses on comparing its characteristics to previously marketed predicate devices rather than providing a detailed study proving performance against specific acceptance criteria.

Therefore, many of the requested details, such as specific acceptance criteria with numeric thresholds, a specific study with a sample size, expert involvement for ground truth, or MRMC studies, are not present in the provided text. The submission relies on "nonclinical test results showing comparable performance" to established predicate devices.

Here's an attempt to answer based on the provided information, noting where information is not available:

1. Table of Acceptance Criteria and Reported Device Performance

Study Proving Device Meets Acceptance Criteria:

The document explicitly states: "The nonclinical test results included in the submission showing comparable performance to the predicate devices are as follows." This indicates that the "study" was a set of nonclinical tests designed to demonstrate equivalence to the predicate devices across the listed characteristics. The submission focuses on substantial equivalence to existing legally marketed devices (K961358 for both listed predicates) rather than establishing new, independent performance thresholds.

2. Sample Size and Data Provenance:

• Sample Size for Test Set: Not specified in the provided text. The document only mentions "nonclinical test results."
• Data Provenance: Not specified. Given it's a nonclinical bench test, typical provenance details like country of origin or retrospective/prospective don't directly apply in the same way they would for a clinical study. It's safe to assume these were internal laboratory tests conducted by Arrow International.

3. Number of Experts and Qualifications:

• Not applicable. This was a nonclinical engineering/performance test, not a study requiring expert readers for ground truth establishment.

4. Adjudication Method:

• Not applicable for a nonclinical test of this nature.

5. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study:

• No, an MRMC comparative effectiveness study was not mentioned or conducted. This type of study is typically for evaluating diagnostic imaging or similar devices where human interpretation is a key component.

6. Standalone Performance Study (Algorithm Only):

• Yes, in a sense, the "nonclinical test results" are a form of standalone performance evaluation for the device itself. However, it's not an "algorithm only" study as there's no algorithm involved. It's a physical device being tested without human-in-the-loop performance being a primary measure, but rather intrinsic device performance characteristics.

7. Type of Ground Truth Used:

• For the nonclinical tests, the "ground truth" would likely be engineering specifications, established physical limits, or direct comparative measurements against the predicate devices using calibrated instruments and standardized test methods. It's not expert consensus, pathology, or outcomes data.

8. Sample Size for the Training Set:

• Not applicable. This is a medical device, not an AI/machine learning algorithm, so there is no "training set."

9. How Ground Truth for the Training Set was Established:

• Not applicable, as there is no training set for an AI/machine learning algorithm.

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