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Multifilament stainless steel sutures with crimps are intended for use in soft tissue to bone and bone to bone approximation and fixation during orthopedic procedures in the elbow, foot, ankle, knee, shoulder, and wrist for indications such as: Elbow - biceps tendon attachment; Foot and Ankle - achilles tendon attachment; Knee - patella tendon attachment to bone; Shoulder -biceps tendon tenodesis; Wrist - scapho-lunate approximation.

Multifilament stainless steel sutures with crimps are intended for use in soft tissue to bone and bone to bone approximation and fixation during orthopedic procedures in the elbow, foot, ankle, knee, shoulder, and wrist for indications such as: Elbow - biceps tendon attachment; Foot and Ankle - achilles tendon attachment; Knee - patella tendon attachment to bone; Shoulder -biceps tendon tenodesis; Wrist - scapho-lunate approximation.

Multifilament Stainless Steel Sutures with Crimps are available in a range of USP sizes (4-0 to #3) and lengths, attached to stainless steel needles of various types and sizes.

Multifilament SS Sutures are manufactured in IX19, 7X7 or 7X19 filament constructions. The sutures are identified by black and white tips which are used as a guide at the tip, and are removed prior to the end of the procedure. The sutures and tips were cleared for use under the PONTIS 510(k), K101126.

The washer is available in the following sizes:
000-0739_1-01 Washer, Plate - 0.012", .045"
000-0739_1-00 Washer, Plate - 0.012", .062"
000-0764 Washer, Plate, 2-Hole - 0.012"

The suture guide and the cannulated K-wire are available in one size.

The provided text describes the "Multifilament Stainless Steel Sutures with Crimps" device by PONTIS Orthopaedics and its 510(k) summary, but it does not contain specific acceptance criteria or a detailed study proving the device meets them in the format requested.

The document primarily focuses on demonstrating substantial equivalence to predicate devices based on design, materials, intended use, principles of operation, and technical characteristics. The nonclinical tests performed are mentioned, but quantitative acceptance criteria and detailed performance results are absent.

Therefore, I cannot directly extract the table of acceptance criteria and reported device performance, nor can I provide information about sample sizes for test sets, data provenance, number of experts, adjudication methods, MRMC studies, standalone performance, or training set details as these are not present in the provided text.

Based on the information given, here's what can be inferred about the "study" that supports the device, focusing on the mechanical testing mentioned:

1. Table of Acceptance Criteria and Reported Device Performance

• Acceptance Criteria: Not explicitly stated in quantitative terms. The document indicates that testing demonstrated "substantially equivalent" mechanical properties to predicate devices.
• Reported Device Performance: Not given in quantitative terms. The document states that testing demonstrated "substantially equivalent" mechanical properties for tendon to bone and bone to bone approximation compared to predicate devices.

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

• Sample Size: Not specified.
• Data Provenance: Not specified, but generally, bench testing for device submissions like this is performed in a laboratory setting, likely in the US where the submitter is located. It is prospective testing designed for the submission.

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

• Not applicable. This device is a mechanical suture system, and its performance is evaluated through bench testing (mechanical and biocompatibility), not by expert interpretation of images or other data requiring a "ground truth" established by human experts in the context of diagnostic AI. Biocompatibility was "conducted under the predicate submission K081060".

4. Adjudication method for the test set:

• Not applicable, as this refers to a process for resolving discrepancies in expert labeling or assessment, which is not relevant for the type of mechanical bench testing described for this device.

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 device is a surgical suture, not an AI-assisted diagnostic or therapeutic tool.

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

• Not applicable. This is a mechanical surgical device, not an algorithm.

7. The type of ground truth used:

• For mechanical tests: Engineering specifications and established test methods for evaluating suture strength, pull-out force, and cyclic loading for medical devices, with the "ground truth" being these measurable physical properties.
• For biocompatibility: Established ISO standards for biocompatibility testing.

8. The sample size for the training set:

• Not applicable. This is a physical medical device, not an AI model requiring a training set.

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

• Not applicable, as this is a physical medical device, not an AI model.

Summary of the Nonclinical Tests Performed (from text):

The nonclinical tests performed to demonstrate substantial equivalence included:

• Knot failure force compared to crimp failure force
• Pull-out strength
• Attachment strength
• Static testing
• Ultimate load following cyclic loading
• Biocompatibility testing (conducted under the predicate submission K081060 as materials are the same).

The conclusion was that these bench tests demonstrated that the mechanical properties are "substantially equivalent" for tendon to bone and bone to bone approximation to the predicate devices.

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ferroFIBRE™ Stainless Steel Suture with Crimp is intended for use in soft tissue approximation and for use in abdominal wound closure. hernia repair, sternal closure and certain orthopaedic procedures including cerclage and tendon repair

The ferroFibre™ with Crimp is a nonabsorbable sterile surgical suture with a crimp composed of stainless steel. The ferroFibre™ with Crimp is available in USP sizes 4-0 to size 3, attached to stainless steel needles of various types and sizes. The ferroFibre™ suture was previously cleared in the K081060. A stainless steel crimp is being added to provide an alternate to knot tying. The use of the crimp for size 3-0 and 4-0 was cleared under submission K101126.

The provided FDA 510(k) summary for the PONTIS ferroFIBRE™ Stainless Steel Suture with Crimp describes a medical device, not a software algorithm or AI model. Therefore, many of the requested categories related to AI performance, ground truth, and expert evaluation are not applicable.

However, I can extract information related to the device's non-clinical testing, which serves a similar purpose of demonstrating safety and effectiveness compared to acceptance criteria for a physical device.

Here's a breakdown of the requested information based on the provided document:

Acceptance Criteria and Study for PONTIS ferroFIBRE™ Stainless Steel Suture with Crimp

This submission is for a medical device (stainless steel suture with a crimp), not an AI algorithm. Therefore, "acceptance criteria" and "device performance" are typically assessed through physical and mechanical testing rather than AI-specific metrics like AUC, sensitivity, or specificity. The "study" refers to non-clinical tests.

1. Table of Acceptance Criteria and Reported Device Performance

2. Sample Size Used for the Test Set and Data Provenance

• Sample Size for Test Set: Not explicitly stated. The document mentions "verification and validation testing" including "knot failure force, crimp failure force and cyclic loading." However, the number of samples used for these tests is not provided.
• Data Provenance: N/A for clinical data, as this is a non-clinical device submission. The tests are laboratory-based mechanical and biological evaluations.

3. Number of Experts Used to Establish Ground Truth for the Test Set and Qualifications of those Experts

• N/A. This information is for AI algorithms. For a physical device, testing is conducted according to established engineering and material science standards. The "ground truth" for device performance is typically defined by the test protocols themselves, often referencing ISO or ASTM standards, and evaluated by qualified engineers or lab personnel.

4. Adjudication Method for the Test Set

• N/A. This information is for AI algorithms, often referring to expert review of ambiguous cases. Device testing involves objective measurement and analysis against predefined specifications.

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study Was Done, and Effect Size of Human Readers Improvement with AI vs. Without AI Assistance

• N/A. This is a physical medical device, not an AI system. MRMC studies are not applicable.

6. If a Standalone (i.e., algorithm only without human-in-the-loop performance) Was Done

• N/A. This is a physical medical device. "Standalone performance" in this context refers to the device's mechanical and material properties as assessed in laboratory tests, which were performed.

7. The Type of Ground Truth Used

• Defined by Test Protocols and Predicate Device Performance: The "ground truth" for this device is effectively established by accepted mechanical engineering principles, material science standards, and the performance characteristics of the predicate devices. The tests (knot failure force, crimp failure force, cyclic loading) measure objective physical properties against expected or established benchmarks derived from the predicate devices, which are already considered safe and effective. Biocompatibility "ground truth" is based on established biological safety standards.

8. The Sample Size for the Training Set

• N/A. This information is for AI algorithms. There is no "training set" for this physical device in the AI sense. Device design and development might involve iterative testing of prototypes, but this is distinct from AI training.

9. How the Ground Truth for the Training Set Was Established

• N/A. As there is no AI "training set," this question is not applicable. The design and validation of physical devices rely on engineering specifications, material properties, and performance data from similar, previously cleared devices.

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