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CoNextions TR Tendon Repair System is indicated for the repair of severed Tendons in adults (22 years of age or older). The product is intended for the following indications:

• Digital Flexor Tendons
• Digital Extensor Tendons Proximal to the Metacarpophalangeal Joints (Zones 6-8)

The CoNextions TR Tendon Repair System consists of a single-use, sterile implant consisting of two identical stainless steel anchors implanted in either end of the injured tendon and connected by two loops of UHMWPE fiber. The implant is provided pre-loaded into an Implant Mechanism and with a Deployment Mechanism to facilitate placement.

The information regarding the acceptance criteria and study details for the CoNextions TR Tendon Repair System is extracted from the provided text.

1. Table of Acceptance Criteria and Reported Device Performance

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

• Test Set Sample Size:

  • Initially, 90 participants were screened and randomized: 40 to the CoNextions TR group and 50 to the Suture group.
  • After exclusions (8 participants under 22, 1 participant with unrelated injury), 81 participants remained.
  • For the 12-week follow-up: 72 participants (88.9% of 81).
  • For the 24-week follow-up: 70 participants (86.4% of 81).
  • Specific numbers for CoNextions TR group and Suture group are:
    • Rupture (12 weeks): 33 CoNextions TR, 45 Suture (for specific analysis 1/34 CoNextions TR, 5/47 Suture)
    • Surgical site infection: 34 CoNextions TR, 47 Suture
    • Strickland Score (12 weeks): 27 CoNextions TR, 41 Suture
    • Strickland Score (24 weeks): 30 CoNextions TR, 42 Suture
    • Secondary Effectiveness (24 weeks): N=32-33 for CoNextions TR, N=40-42 for Suture.

• Data Provenance: Prospective, multi-site clinical evaluation. The country of origin is not explicitly stated, but the FDA submission implies a US-based study or one adhering to US regulatory standards.

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

• Number of Experts: 5
• Qualifications of Experts: Fellowship-trained hand surgeons.

4. Adjudication Method for the Test Set

The document does not explicitly describe an adjudication method for establishing ground truth, such as a 2+1 or 3+1 consensus. The study was a clinical evaluation conducted by the involved surgeons and clinical staff, with outcomes assessed and recorded per protocol. Participants and therapists performing the majority of outcome assessments were blinded for the first 12 weeks.

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

This was not an MRMC study and does not involve AI assistance. The study compares a novel medical device (CoNextions TR Tendon Repair System) to a standard-of-care suture repair method for tendon lacerations.

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

This was not a standalone (algorithm only) study. It was a clinical study comparing a medical device with a human-in-the-loop (surgical implantation) to another surgical method.

7. The Type of Ground Truth Used

The ground truth was established through direct clinical outcomes and measurements from human patients, including:

• Physical examinations for re-rupture and surgical site infection.
• Objective measurements like goniometry for Strickland's Scores (mobility).
• Patient-reported outcomes (VAS Pain Scores, DASH Questionnaire Scores).
• Strength measurements (Grip Strength, Tip Pinch Strength).

8. The Sample Size for the Training Set

The document describes a clinical evaluation for the device and provides a summary of benchtop and animal testing. It does not mention a "training set" in the context of an algorithm or AI. The term "training set" is not applicable here as this is a device performance study, not an AI/ML study.

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

Not applicable, as there is no training set for an AI/ML algorithm mentioned in the document.

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The WEGO-STAINLESS STEEL is indicated for use in abdominal wound closure, hernia repair, sternal closure and orthopaedic procedures including cerclage and tendon repair.

The proposed device, WEGO-STAINLESS STEEL, is monofilament, non-absorbable surgical suture composed of stainless steel. WEGO-STAINLESS STEEL is undyed and uncoated. The proposed device is composed of suture and needle. The sutures are available in a range of gauge sizes and lengths attached to stainless steel needles of varying types and sizes. WEGO-STAINLESS STEEL complies with the requirements of the United States Pharmacopoeia for Non-Absorbable Surgical Sutures.

The provided document is a 510(k) summary for the "WEGO-STAINLESS STEEL" surgical suture, in which the manufacturer asserts substantial equivalence to a predicate device (Surgical Stainless Steel Suture K170767). The document describes non-clinical tests conducted to support this claim, but it does not describe an AI/ML powered device, nor does it detail acceptance criteria related to AI/ML performance, or comparative effectiveness studies of AI vs. human readers.

Therefore, the requested information regarding AI/ML acceptance criteria, study details, expert involvement, and MRMC studies cannot be extracted from this document, as it is outside the scope of a traditional medical device (surgical suture) 510(k) submission.

However, I can provide the available information regarding the non-clinical tests performed to demonstrate substantial equivalence for the surgical suture:

Acceptance Criteria and Device Performance (for Non-Clinical Tests of Surgical Suture)

The acceptance criteria for the "WEGO-STAINLESS STEEL" surgical suture were based on compliance with established international and pharmacopeial standards. The reported device performance indicates that the proposed device met these standards.

The subsequent questions are related to AI/ML device studies and are not applicable to this document, as it concerns a conventional surgical suture.

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. This document describes non-clinical tests on a physical device, not an AI/ML model.
3. 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. Ground truth for AI/ML is not relevant here.
4. Adjudication method (e.g. 2+1, 3+1, none) for the test set: Not applicable.
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. No clinical study was included, and this is not an AI-assisted device.
6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done: Not applicable. This is not an algorithm.
7. The type of ground truth used (expert consensus, pathology, outcomes data, etc): Not applicable.
8. The sample size for the training set: Not applicable. This is not an AI/ML device.
9. How the ground truth for the training set was established: Not applicable. This is not an AI/ML device.

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MERISTEEL™ sutures are intended for use in abdominal wounds closure, hernia repair, sterna closure and orthopaedic procedure including cerclage & tendon repair.

MERISTEEL™ Stainless steel suture is a monofilament, non-absorbable sterile surgical suture composed of stainless steel. This suture is available undyed and uncoated. MERISTEEL™ suture is available in a range of gauge sizes and lengths, and attached to standard stainless steel needles of various types and sizes. Stainless steel suture complies with the requirements of the United States Pharmacopoeia for Non Absorbable Surgical suture and European Pharmacopoeia for Sterile Non-Absorbable surgical strands

This looks like a 510(k) summary for a medical device (MERISTEEL™ Stainless Steel Surgical Suture). However, the document does not contain acceptance criteria for an AI/ML-driven device or study details proving those criteria are met.

The provided document describes a traditional medical device (surgical sutures) and outlines tests conducted to demonstrate equivalence to a predicate device, such as:

• **Diameter USP **
• **Tensile strength USP **
• **Needle attachment USP **
• Suture Length
• Biocompatibility as per ISO 10993-1

These are performance standards for the physical properties and biological safety of the suture material, not criteria related to AI/ML performance.

Therefore, I cannot provide the requested information regarding acceptance criteria and study details for an AI/ML device based on the provided text. The document is about a conventional medical device submission.

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Stainless Steel Suture is indicated for use in abdominal wound closure, hernia repair, sternal closure and orthopaedic procedures including cerclage and tendon repair.

Stainless Steel Suture is a sterile monofilament or multifilament, non-absorbable sterile surgical suture composed of 316L stainless steel. The suture is also available coated with polyethylene. Stainless Steel Suture is available in a range of gauge sizes and lengths, non-needled or attached to needles of various types and sizes. Stainless Steel Suture complies with the requirements of the European Pharmacopoeia (Ph. Eur.) for Sterile Non-Absorbable Strands and the United States Pharmacopoeia (USP) for Non Absorbable Surgical Sutures. The European Pharmacopoeia recognizes units of measure Metric and Ph. Eur. sizes as equivalent which is reflected on the labeling.

Stainless Steel Suture elicits a minimal acute inflammatory reaction in tissue and is not absorbed. Implantation studies in animals show that no significant change in the retention of tensile strength of the suture occurs during the lifetime of the implantation.

The provided text describes a 510(k) premarket notification for a medical device called "Stainless Steel Suture" by Ethicon Incorporated. This is not a study proving device performance against acceptance criteria in the manner typically seen for new, innovative devices with novel performance characteristics or AI components. Instead, it's a submission to demonstrate substantial equivalence to a legally marketed predicate device.

Therefore, many of the requested categories (like sample sizes for test/training sets, number of experts, adjudication methods, MRMC studies, standalone performance of an algorithm, and ground truth types related to performance metrics) are not applicable in this context because the FDA cleared this device based on its substantial equivalence to an existing device, rather than novel performance data from a clinical or algorithm-based study.

The primary "acceptance criteria" here relate to demonstrating that the new device is as safe and effective as the predicate device, with a focus on updated labeling for MRI safety. The "study" isn't a complex clinical trial or AI algorithm validation, but rather a series of bench and design verification tests and a comparison to the predicate.

Here's the information extracted and adapted to the prompt, with explanations for why certain fields are not applicable:

1. Table of Acceptance Criteria and Reported Device Performance

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

• Sample Size: Not explicitly stated as this was a substantial equivalence submission based on bench testing of the product, not a clinical study with patient data. The tests would have used appropriate numbers of suture samples per the relevant ASTM and USP standards.
• Data Provenance: The data provenance is from bench/design verification activities performed by Ethicon Inc., in compliance with design control requirements. The data is prospective in the sense that these tests were conducted specifically for this 510(k) submission on the device to verify compliance with standards and MRI safety guidelines. Country of origin not specified, but likely where Ethicon's primary R&D/manufacturing takes place (e.g., USA given the submitter's address).

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

• Not Applicable. For a device like a stainless steel suture cleared via substantial equivalence, ground truth as typically defined for AI or diagnostic studies (i.e., expert consensus on clinical findings, pathology confirmation) is not relevant. The "ground truth" for the bench tests would be the established scientific/engineering principles and the specifications within the referenced ASTM and USP standards. The "experts" involved are the testing personnel and engineers who conducted and validated the bench tests according to recognized industry standards.

4. Adjudication Method for the Test Set

• Not Applicable. Adjudication methods (like 2+1 or 3+1 consensus) are typically used in clinical studies or AI algorithm validation to resolve discrepancies among human readers or between AI and human reads. This submission is based on objective bench testing against pre-defined engineering and safety standards, not subjective interpretations requiring adjudication.

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-powered diagnostic or assistive tool. Therefore, no MRMC study involving human readers or AI assistance was conducted or is relevant for its clearance.

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

• Not Applicable. This device is a physical surgical implant, not an algorithm or software. No standalone algorithm performance testing was performed.

7. The Type of Ground Truth Used

• Engineering Standards and Specifications: The "ground truth" for this device's performance is compliance with established and recognized engineering and medical device standards, specifically:
  • United States Pharmacopoeia (USP) monographs for sutures ( Needle Attachment, Tensile Strength, Diameter).
  • ASTM Standards for MRI Safety (F2503, F2052, F2119, F2182, F2213).
  • AAMI/ANSI/ISO 10993-7 for EO residual testing.
  • ANSI/AAMI ST72:2011 and USP , for Bacterial Endotoxin Testing (BET).
  • European Pharmacopoeia (Ph. Eur.) for Sterile Non-Absorbable Strands.
  • The "ground truth" also stems from the long history of safe and effective use of the predicate device (Surgical Stainless Steel Suture, K946173) which the proposed device is substantially equivalent to.

8. The Sample Size for the Training Set

• Not Applicable. This is not an AI/machine learning device, so there is no training set.

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

• Not Applicable. As there is no training set for an AI algorithm, this question is not relevant.

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"DemeSTEEL" is a stainless steel suture composed of 316L stainless steel with or without needles attached, and is intended for use in abdominal wound closure, intestinal anastomosis, hernia repair, sternal closure and certain orthopedic procedures, including cerclage and tendon repair.

Demetech's DemeSTEEL is a Monofilament and/or Multifilament Non-absorbable surgical suture composed of 316L Stainless Steel and supplied with and without needles affixed to the sutures. Demetech's DemeSTEEL Surgical Suture meets the requirements established by the United States Pharmacopeia (U.S.P.) for nonabsorbable surgical sutures. DemeSTEEL Stainless Steel sutures are composed of 316L stainless steel conforming to the FDA recognized ASTM Standard F138 Grade 2 "Stainless steel bar and wire for surgical implants".

This document describes the Demetech Non-Absorbable Stainless Steel Surgical Suture (DemeSTEEL) and its equivalency to predicate devices, primarily through non-clinical testing.

Here's a breakdown of the requested information:

1. Table of Acceptance Criteria and Reported Device Performance:

The document leverages the United States Pharmacopeia (USP) standards as its primary acceptance criteria. The device is reported to meet or exceed these standards.

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

The document does not explicitly state the specific sample sizes for each non-clinical test. It generally states that "Non-clinical testing was conducted on the device to prove conformance to the requirements of USP standards." The data provenance is laboratory testing conducted by Demetech, likely in the US, given the company's address and the FDA submission. The data is prospective, generated specifically for this submission.

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

Not applicable. This is a medical device submission primarily based on objective physical and chemical testing against established standards (USP, ASTM). There were no experts involved in establishing a "ground truth" in the way it is typically understood for interpretative tasks (e.g., medical image analysis). The "ground truth" here is adherence to specified material and performance parameters.

4. Adjudication Method for the Test Set:

Not applicable. No adjudications were performed as this primarily involves objective measurements of physical and chemical properties against predefined standards.

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 is a submission for a surgical suture, not an AI-powered diagnostic or assistive device. Therefore, no MRMC study was conducted or is relevant.

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

Not applicable. This is a physical medical device (suture), not an algorithm or software.

7. The Type of Ground Truth Used:

The "ground truth" used is defined by:

• Established Industry Standards: United States Pharmacopeia (USP) for non-absorbable surgical sutures, including specific sections for diameter, tensile strength, needle attachment, suture length, and sterility.
• Material Specifications: ASTM Standard F138 Grade 2 for 316L stainless steel.
• Biocompatibility Standards: Implicitly, common standards for biocompatibility testing for implantable devices, with the 316L material having an "established history of use."

8. The Sample Size for the Training Set:

Not applicable. There is no "training set" as this is not a machine learning or AI-based device.

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

Not applicable. As noted above, there is no "training set." The performance of the suture is assessed against predefined, universally accepted physical and chemical standards.

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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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ferroFibre 14 Stainless Steel Sutures are 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™ Stainless Steel Suture is available in United States Pharmacopocia (USP) sizes 5-0 to #5 in various lengths. The ferroFibre multifilament stainless stecl sutures are supplied storile, armed with cutting needles. The sutures are fabricated from 316 stainless steel that meets ASTM F138-03.

The provided text describes a 510(k) submission for the ferroFibre™ Stainless Steel Suture. This document focuses on the regulatory clearance for a medical device and does not contain information about an AI/ML powered device, nor does it detail a clinical study with acceptance criteria and reported device performance in the way requested.

The document outlines performance testing conducted to characterize biocompatibility, diameter, and tensile strength according to ISO 10993 standards and USP Monographs. However, it does not provide specific acceptance criteria or reported performance values for these tests. It also does not include details on sample sizes for testing, ground truth establishment, expert involvement, or any multi-reader multi-case (MRMC) studies, as these types of studies are not relevant for the regulatory approval of a non-AI/ML surgical suture device.

Therefore, I cannot populate the requested table or answer the specific questions related to AI/ML device performance and clinical study design for this submission. The content is about a traditional medical device (surgical sutures) and its regulatory clearance based on substantial equivalence to existing products.

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The Suturtek 360° Sternal Closure Device is intended for use during thoracic surgery to hold and close the sternum after a sternotomy. It is designed to aid in the prevention of suture needle stick injuries.

The SuturTek 360° Sternal Closure Device™ is a an instrument that is used to pass stainless steel needles through sternum for fixation with stainless steel sutures. It is used to hold and close the sternum after a sternotomy.

The device is sterilized before each use. The cartridge containing the needle (with suture attached) is loaded onto the distal end of the device. The needle is engaged by the device's internal drive mechanism and driven through the sternum to be sutured. The suture is thus passed completely through the tissue. Once the suture is in place, the device is withdrawn from the incision leaving the suture strand looped through the sternum. Additional interrupted stitches are placed in the same manner and then the ends of the suture are tied together in the usual fashion.

The provided document is a 510(k) Summary of Safety and Effectiveness for the SuturTek 360° Sternal Closure Device™. This submission process seeks to demonstrate "substantial equivalence" to a legally marketed predicate device, rather than proving the device meets specific performance criteria through a standalone study with ground truth establishment and expert adjudication.

Therefore, the document does not contain the information requested regarding acceptance criteria, reported device performance, sample sizes for test/training sets, data provenance, number/qualifications of experts, adjudication methods, MRMC studies, or specific ground truth methodologies in the context of device performance evaluation.

Instead, the submission relied on demonstrating equivalence to the predicate device, the SuturTek FASTCLOSE™ Sternum Closure Device™ (K032468).

The document states:

• "Documentation was provided which demonstrated that the SuturTek 360° Sternal Closure Device™ is substantially equivalent to the predicate device, the SuturTek FASTCLOSE™ Sternum Closure Device™ K032468"

This type of submission focuses on comparing the new device's design, materials, and intended use to a device already cleared by the FDA, rather than conducting a de novo study to establish performance metrics against a defined standard.

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The SuturTek Surgical Steel Suture is intended for use in sternal closure.

The SuturTek Surgical Steel Suture is a sterile, single-use, non absorbable, stainless steel monofilament suture. It is designed to remain inside the patient. It may or may not be attached to a stainless steel needle. The needle and any unused portions of suture are disposables.

The provided text describes a 510(k) summary for a surgical steel suture and does not contain detailed information about acceptance criteria, device performance, or a study proving its conformance beyond general bench testing. The document is primarily focused on demonstrating substantial equivalence to predicate devices for regulatory approval.

Therefore, many of the requested details cannot be extracted from the given input.

Here's a breakdown of what can be inferred or directly stated from the provided text, and what is missing:

1. A table of acceptance criteria and the reported device performance

• Acceptance Criteria: Not explicitly stated. The document mentions "Bench testing was performed to demonstrate that the SuturTek Surgical Steel Suture would perform as intended." without listing specific performance metrics or thresholds.
• Reported Device Performance: Not explicitly stated. The document indicates that bench testing was performed and implies successful performance ("would perform as intended"), but no quantitative results are provided.

2. Sample sized used for the test set and the data provenance

• Sample Size for Test Set: Not mentioned.
• Data Provenance (e.g., country of origin of the data, retrospective or prospective): Not mentioned. It's bench testing, so "country of origin" of data wouldn't typically apply in the same way as clinical data.

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

• This information is not applicable as the testing described is bench testing, not a clinical study involving expert interpretation or ground truth establishment in a diagnostic sense.

4. Adjudication method for the test set

• Not applicable as the testing described is bench testing.

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, a MRMC comparative effectiveness study was not done. The device is a surgical suture, not an AI or imaging diagnostic device.

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

• Not applicable. The device is a surgical suture, not an algorithm.

7. The type of ground truth used

• Not applicable in the conventional sense. For bench testing of a physical device, the "ground truth" would be the engineering specifications and performance standards against which the device is tested. These specifics are not detailed in the provided text.

8. The sample size for the training set

• Not applicable, as this is a physical medical device, not an AI/ML algorithm requiring a training set.

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

• Not applicable, as this is a physical medical device.

Summary of available information:

• Study Type: Bench testing.
• Purpose of Study: To demonstrate that the SuturTek Surgical Steel Suture would perform as intended.
• Conclusion of Study (implied): The bench testing was successful, as the FDA granted 510(k) clearance based on substantial equivalence.
• Device Intended Use: For use in sternal closure during thoracic surgery.
• Comparison Basis: Substantial equivalence to predicate devices (Aesculap: Steelex Sternum Set; K023411 and CP Medical: Surgical Steel Monofilament Stainless Steel; K030351). The operating principle, materials, intended use, and design of construction are stated to be the same as predicate devices.

Missing Information (critical for your request): Detailed acceptance criteria, specific performance results, sample sizes, and expert involvement (as the study was bench testing).

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Synthes (USA) Titanium Wire is indicated for use in soft tissue approximation and/or ligation, for canthoplasty, canthopexy and/or canthal tendon repair.

The Synthes Titanium Wire with Barb is a nonabsorbable, monofilament, sterile surgical wire with an attached barb. The 28 gauge titanium wire with barb is available in a length of 538mm and has a permanently attached stainless steel needle.

This document, K042606, is a 510(k) summary for a medical device called "Synthes (USA) Titanium Wire." This type of document is typically for regulatory clearance, not for publishing detailed study results to demonstrate device performance against acceptance criteria in the way you've described for AI/ML device studies.

Therefore, the requested information regarding acceptance criteria, study details, sample sizes, ground truth establishment, expert qualifications, adjudication methods, and comparative effectiveness studies cannot be extracted from the provided text.

Here's why and what can be inferred:

• Device Type: This is a physical medical device (titanium wire for surgical use), not a software or AI/ML device.
• Regulatory Pathway: A 510(k) submission generally demonstrates substantial equivalence to a legally marketed predicate device, rather than proving performance against predefined acceptance criteria through extensive clinical studies in the same manner as an AI/ML device. For physical devices like this, the "study" often involves bench testing (material properties, tensile strength, fatigue) and biocompatibility, rather than clinical efficacy studies with human readers and ground truth.
• Missing Information: The document focuses on regulatory classification, intended use, and substantial equivalence to a predicate device. It does not contain any sections detailing:
  • Acceptance criteria for performance metrics (e.g., accuracy, sensitivity, specificity).
  • Results of a performance study demonstrating these metrics.
  • Sample sizes for test sets or training sets in the context of algorithm performance.
  • Details about expert readers, ground truth adjudication, or an MRMC study.

Therefore, I cannot populate the table or answer the specific questions about device performance studies as they pertain to AI/ML devices based on this document.

The document states:

• "Comparative information presented supports substantial equivalence." This is the core "proof" in a 510(k) submission, meaning the device is as safe and effective as a legally marketed predicate device.
• The "study" would have involved demonstrating that the Synthes (USA) Titanium Wire (the new device) has equivalent material properties, mechanical performance, and intended use as the Predicate Device: Synthes Titanium Wire.

If this were an AI/ML device submission, the requested information would be crucial. However, for this type of physical device, the "study" is of a different nature and is not detailed in terms of performance metrics like accuracy or sensitivity in this summary.

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