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The InDiscal™ Digital Manometer is indicated to be used for dispensing fluids into the intervertebral disc and monitoring the pressure of those fluids during discography procedures in symptomatic patients with suspected intervertebral disc pathology.

The InDiscal™ Digital Manometer is a sterile, single-use device that is used to dispense fluids into and monitor pressure in vertebral discs during spinal procedures such as discography. The device consists of a plastic syringe with a screw-type plunger and locking lever, a rotating palm grip that controls the plunger, a manometer with a digital LCD screen and a connecting tube.

Here's an analysis of the provided text, focusing on the acceptance criteria and study information for the InDiscal™ Digital Manometer:

Acceptance Criteria and Device Performance

The document describes the InDiscal™ Digital Manometer as a sterile, single-use device for dispensing fluids and monitoring pressure in vertebral discs during spinal procedures (discography). The submission is a 510(k) premarket notification, which aims to demonstrate substantial equivalence to legally marketed predicate devices.

The "acceptance criteria" in this context are not explicitly stated as numerical targets in a table, but rather implicitly defined by the successful completion of various verification and validation tests designed to demonstrate substantial equivalence to predicate devices and compliance with design inputs. The reported device performance is that it "passed all verification and validation tests."

Here's a summarized table based on the information provided:

Study Details

Here's a breakdown of the study-related information:

1. Sample sizes used for the test set and the data provenance:

   • Sample Size: Not specified. The document only lists types of tests conducted (e.g., Ingress Protection, Accuracy testing, Software validation).
   • Data Provenance: Not specified. Given the nature of the tests (mechanical, electrical, software), these would typically be conducted in a laboratory setting by the manufacturer (Baylis Medical Company Inc., based in Canada).

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

   • Not applicable/Not specified. The listed tests (mechanical, electrical, software accuracy) typically rely on engineering specifications or reference standards, not expert clinical interpretation, to establish "ground truth."

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

   • Not applicable/None. The tests described are objective engineering and performance evaluations against predefined specifications, not subjective clinical assessments requiring adjudication.

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

   • No. This type of study is specifically designed for evaluating diagnostic imaging systems or AI algorithms with human readers, which is not applicable to a digital manometer.

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

   • Yes, implicitly. The listed tests (Mechanical, Electrical, Software, Accuracy, General) are inherently standalone performance evaluations of the device itself, without human interpretation in the loop. The "Accuracy testing of the pressure gauge" and "Software validation" are examples of standalone performance assessments.

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

   • The ground truth for these tests would be objective engineering standards, calibrated reference instruments, and design specifications. For example, for "Accuracy testing," the ground truth would be the known pressure generated by a calibrated standard, and the device's reading would be compared against it. For "Electrical Testing," the ground truth would be established by relevant electrical safety standards (e.g., IEC standards).

7. The sample size for the training set:

   • Not applicable/Not specified. This device does not appear to involve machine learning or AI that would require a "training set" in the conventional sense. The "software validation" refers to verifying that the device's embedded software functions as designed.

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

   • Not applicable, as there is no apparent training set for an AI/ML algorithm. The ground truth for the software validation would be the software's design requirements and specifications.

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