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V-Loc™ 90 Absorbable Wound Closure Device is indicated for soft tissue approximation where use of an absorbable suture is appropriate.

The V-Loc™ 90 Absorbable Wound Closure Device is a suture prepared from a synthetic polyester (Glycomer™ 631) composed of glycolide, dioxanone and trimethylene carbonate. Each device has unidirectional barbs along the axis of the monofilament. The V-Loc™ 90 Absorbable Wound Closure Device will be offered both Undyed (clear) and Dyed with D&C Violet No. 2 at a level not exceeding 0.2% by weight of the suture in sizes U.S.P. (EP) 4-0 (Metric 2.0) 3-0 (Metric 3), 2-0 (Metric 3.5) and 0 (Metric 4). They will be supplied in pre-cut lengths affixed to various needle types.

Here's a breakdown of the acceptance criteria and study information for the V-Loc™ 90 Absorbable Wound Closure Device, based on the provided text:

Acceptance Criteria and Device Performance

The provided text details performance evaluations rather than explicitly stating pre-defined "acceptance criteria" with numerical targets. However, the "Results" section indicates the device passed these evaluations by performing comparably to predicate devices or meeting specific standards.

Table 1: Acceptance Criteria and Reported Device Performance

Study Details

2. Sample Size and Data Provenance

• Test Set Sample Size: Not explicitly stated as a number of devices or animals.
  • For in-vitro tests, the sample size is also not specified.
  • For the porcine model, it states "Chronic 21 day study." The number of animals used is not provided.
  • For the rat model, it states "degradation over 2 weeks." The number of animals used is not provided.
• Data Provenance: The studies were conducted by Surgical Devices, a global business unit of Tyco Healthcare Group LP (d/b/a Covidien) based in North Haven, CT, USA. The studies themselves are likely proprietary data generated specifically for this 510(k) submission. Therefore, it is prospective data for the purpose of demonstrating device performance. The country of origin of the data generation is implied to be within the US or a facility controlled by the US-based company.

3. Number of Experts and Qualifications for Ground Truth

• The document does not mention the use of external experts to establish ground truth for the test set. Performance data appears to be derived from direct physical testing (bench) and biological observation/measurement (animal models) rather than expert interpretation of images or other qualitative data requiring consensus.

4. Adjudication Method for the Test Set

• None explicitly stated. The evaluations are quantitative (e.g., tensile strength, pull force, degradation percentage) based on direct measurement, not on a subjective assessment that would typically require adjudication.

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

• No, an MRMC comparative effectiveness study was not done. This type of study is typically performed for diagnostic imaging devices where human interpretation is a key component. This device is a surgical suture, and its performance is evaluated through physical and biological property testing.

6. Standalone (Algorithm Only) Performance

• No, a standalone (algorithm only) performance study was not done. This device is a physical medical device (suture), not an AI algorithm.

7. Type of Ground Truth Used

• The ground truth used is primarily based on:
  • Direct Physical Measurements/Specifications: For in-vitro tests such as needle attachment (USP/EP specification), diameter (USP/EP), tensile strength, and barb holding strength.
  • Biomechanical Measurements: For in-vivo studies, such as pull force (to assess strength) in the porcine model and knot pull strength in the rat model. This involves objective quantitative data.
  • Comparison to Predicate Devices: Performance is often assessed relative to the behavior of established predicate devices (e.g., Quill™ SRS MONODERM, Biosyn™ suture).

8. Sample Size for the Training Set

• Not Applicable. The V-Loc™ 90 Absorbable Wound Closure Device is a physical medical device, not an AI/ML algorithm. Therefore, there is no "training set" in the context of machine learning. The device design and manufacturing process would be informed by general engineering principles and material science, not a data-driven training set.

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

• Not Applicable. As there is no training set for an AI/ML algorithm, there is no ground truth established for it. The device's characteristics are inherent to its design, materials, and manufacturing, which are validated through the performance tests described.

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The Auto Suture™ ENDO CLIP™ III 5mm Clip Applier is primarily indicated for patients undergoing laparoscopic surgical procedures involving dissection and occlusion of blood vessels, ducts and other tubular structures, and for radiographic marking.

The Auto Suture™ ENDO CLIP™ III 5mm Clip Applier contains 16 titanium clips. The applier is designed for introduction and use through an appropriately sized trocar sleeve, or larger with the use of a converter. The ENDO CLIP™ III 5mm Clip Applier consists of a trigger handle, shaft rotation knob, clip counter window and a 33 cm shaft with jaws at its distal end. Squeezing the handle places a titanium clip in the jaws and closes the jaws to close the clip on the vessel or structure.

The provided text is a 510(k) summary for the "Auto Suture™ ENDO CLIP™ III 5mm Clip Applier," a surgical device. It does not describe a study involving an algorithm or AI. Therefore, I cannot extract information related to acceptance criteria and device performance in the context of an AI/algorithm-based device.

The document discusses:

• The device's intended use (occlusion of blood vessels, ducts, and other tubular structures during laparoscopic surgery).
• Its technological characteristics (identical to predicate devices).
• Materials used (biocompatible).
• Performance data states that "In-vitro and in-vivo tests were performed to verify that the ENDO CLIP™ III 5mm Clip Applier was substantially equivalent to the predicate devices in occluding vessels and other tubular structures and to validate that the ENDO CLIP™ III 5mm Clip Applier performed as intended."

However, this paragraph does not provide any specific acceptance criteria (numerical thresholds) or reported device performance metrics (e.g., success rates, occlusion strength, or specific measurements) that could be tabulated. It only broadly states that tests were performed to demonstrate substantial equivalence and intended performance.

Therefore, I cannot fulfill the request for a table of acceptance criteria and reported device performance, nor can I answer the questions about sample sizes, ground truth establishment, expert involvement, or MRMC studies, as these relate to the evaluation of an AI/algorithm, which is not the subject of this document.

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V-Loc™ 180 absorbable wound closure devices are indicated for soft tissue approximation where use of an absorbable suture is appropriate.

The V-Loc™ 180 absorbable wound closure device (Size 4-0) is prepared from a copolymer of glycolic acid and trimethylene carbonate. The absorbable wound closure device is available clear or green. The device is sterile, inert, noncollagenous and nonantigenic.

The provided text is a 510(k) summary for the V-Loc™ 180 Absorbable Wound Closure Device. This type of submission is for medical devices and typically does not involve studies with human readers, AI assistance, or complex ground truth establishment as seen in diagnostic imaging AI/ML device submissions. Instead, it focuses on demonstrating substantial equivalence to a predicate device through performance testing (in vitro and in vivo), material characterization, and compliance with standards.

Therefore, many of the requested fields (2, 3, 4, 5, 6, 7, 8, 9) are not applicable to the information provided in this 510(k) summary.

Here's an analysis based on the provided document:

Acceptance Criteria and Reported Device Performance

The document states that "Performance testing (in vitro and in vivo) was conducted to verify that the V-Loc™ 180 Absorbable Wound Closure Device (Size 4-0) is safe and effective and performs as intended." However, it does not explicitly list specific numerical acceptance criteria or the detailed reported device performance in a table format. For 510(k) submissions, the “acceptance criteria” are generally met by demonstrating that the new device is substantially equivalent to a legally marketed predicate device, and the performance testing supports this claim of equivalence.

Table 1: Acceptance Criteria and Reported Device Performance (Inferred)

Study Details

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

   • The document mentions "Performance testing (in vitro and in vivo)" but does not specify sample sizes for these tests, nor does it provide details on data provenance (country, retrospective/prospective). For this type of device, "in vivo" testing typically refers to animal studies rather than human clinical trials for a 510(k).

2. 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 is a medical device (suture) submission, not an AI/ML diagnostic device requiring expert interpretation for ground truth.

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

   • Not applicable.

4. 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 an absorbable suture, not an AI-assisted diagnostic tool.

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

   • Not applicable. This is not an AI/ML algorithm.

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

   • For a suture device, "ground truth" would be established through physical and mechanical characterization (e.g., tensile strength, degradation rates) and biological response studies (e.g., biocompatibility) rather than expert consensus on images or pathology. The document indicates that materials were evaluated per ISO 10993-1, which provides standards for biological evaluation.

7. The sample size for the training set:

   • Not applicable. This is not an AI/ML algorithm requiring a training set.

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

   • Not applicable.

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