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SJM trial stimulation systems are indicated for the treatment of chronic pain of the trunk and limbs, either as the sole mitigating agent, or as an adjunct to other modes of therapy used in a multidisciplinary approach.

The multilead trial cable is intended to be used as an accessory with compatible St. Jude Medical trial stimulator systems for trial stimulation either intraoperatively or postoperatively for a maximum of 30 days. The RJ45 adapter is intended to connect the multilead trial cable to compatible trial stimulators.

The Multi Lead Trial Cable (MLTC) consists of a case, a cable and a HDMI connector, and is used to electromechanically connect an implantable lead to an SJM trial stimulation system. The MLTC case has two cavities in which implantable lead(s) can be inserted and locked/unlocked in place via a slider mechanism. The extension cable provides extra length, so the cable can reach from the operative sterile field over the top of the anesthesia screen for the intraoperative trial procedure. The RJ45-HDMI adapter contains HDMI connectors at one end and RJ45 connectors at the other end. Since the MLTC uses a micro-HDMI connector and the SJM trial stimulation system uses a RJ45 connector, the adapter enables the Multi Lead Trial Cable to connect to the Trial Stimulator (MTS).

The provided text describes a 510(k) summary for the St. Jude Medical Multi Lead Trial Cable, a medical device used for spinal cord stimulation. This document focuses on demonstrating substantial equivalence to a predicate device rather than presenting a study proving a device meets specific acceptance criteria in the context of an AI/algorithm-driven medical device. Therefore, much of the requested information regarding acceptance criteria, study details, ground truth, and AI-specific metrics cannot be extracted directly from this document.

However, I can extract the general principle of the "study" that was conducted to demonstrate substantial equivalence, which is a form of acceptance criteria fulfillment for this type of device.

Here's a summary of what can be extracted and what cannot:

1. A table of acceptance criteria and the 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):

• Not applicable for this type of device submission. The "test set" here refers to the device itself being tested for physical and electrical properties, not a dataset for an algorithm. There is no mention of data provenance in the context of patient data or algorithm performance.

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

• Not applicable. "Ground truth" in this context would refer to expert assessment of patient conditions, which is not relevant for a hardware trial cable submission. The "ground truth" for this device is its adherence to engineering specifications and safety standards.

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

• Not applicable. Adjudication methods are typically for subjective assessments, often in clinical trials or expert reviews of images/diagnoses. This document describes engineering validation.

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, not applicable. This is not an AI-driven device.

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

• No, not applicable. This is a hardware accessory, not an algorithm.

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

• For this device, the "ground truth" for the performance testing is based on engineering specifications, industry standards, and regulatory requirements for electrical medical devices, as well as comparison to the predicate device's established performance. The document states that "performance testing demonstrated that these differences do not adversely affect the safety and effectiveness of the subject device" and "Completion of all verification and validation activities demonstrated that the subject devices meet their predetermined design and performance specifications."

8. The sample size for the training set:

• Not applicable. No training set as this is not an AI/ML device.

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

• Not applicable. No training set.

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