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The GIATM stapler with Tri-Staple™ technology has applications in abdominal and thoracic surgical procedures for resection, transection and creation of anastomosis.

The GIA™ stapler with Tri-Staple™ technology places two triple staggered rows of titanium staples and simultaneously cuts and divides tissue between these two triple rows. The GIA™ staplers and cartridges with Tri-Staple™ technology are currently available in 60mm and 80 mm length. The subject device provides the thin/medium staple size. Staplers for thin/medium tissue (tan) deploy three height-progressive rows of 2.4 mm, 2.7 mm and 3.0 mm titanium staples. Each GIA™ stapler with Tri-Staple™ technology may be reloaded with a GIAT™ Cartridge with Tri-Staple™ Technology up to 7 times for a total of 8 firings per instrument. The GIA™ Stapler with Tri-Staple™ Technology is a single-use device. It is packaged and sterilized via ETO (ethylene oxide) with a 5-year shelf life, and intended for multiple use during a single procedure.

This document is a 510(k) summary for a medical device called the "GIA™ Stapler with Tri-Staple™ Technology". It describes the device, its intended use, and the tests performed to demonstrate its substantial equivalence to a legally marketed predicate device.

Based on the provided text, there is no information about acceptance criteria or a study proving that an AI/Software device meets acceptance criteria. The document is for a surgical stapler, which is a physical medical device, not a software or AI product.

Therefore, I cannot provide the requested information, as the input document does not contain details about an AI medical device or its validation studies.

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The GIA™ stapler with Tri-Staple™ technology has applications in abdominal and thoracic surgical procedures for resection, transection and creation of anastomosis.

The GIA™ stapler with Tri-Staple™ technology places two triple staggered rows of titanium staples and simultaneously cuts and divides tissue between these two triple rows. The subject GIA™ stapler and cartridges with Tri-Staple™ technology are available in 60 mm and 80 mm staple line length and two staple sizes to accommodate tissue thicknesses: medium/thick and extra thick. Staplers for medium/thick tissue (purple cartridge) deploy three height-progressive rows of 3.0 mm, 3.5 mm and 4.0 mm titanium staples on either side of the tissue cut line. Staplers for extra thick tissue (black cartridge) deplov three height-progressive rows of 4.0 mm. 4.5 mm and 5.0 mm titanium staples on either side of the cut line. Each GIA™ staple™ technology may be reloaded with a GIA™ Cartridge with Tri-Staple™ Technology up to 7 times for a total of 8 firings per instrument.

The design modification is to add one contraindication per special control 21 CFR 878.4740(b)(2)(ix)(A), and revises IFUs and labels per new regulation requirements.

Based on the provided text, the device in question is a surgical stapler, not an AI/ML medical device. Therefore, the information requested regarding acceptance criteria, study design for AI/ML validation (e.g., sample sizes for training/test sets, expert ground truth, MRMC studies, standalone performance) is not applicable to this 510(k) submission.

The document describes the GIA™ Stapler with Tri-Staple™ Technology and a special 510(k) submission for adding a new contraindication to its labeling. The manufacturer argues for substantial equivalence to a predicate device (K202701, K192720) based on non-clinical performance data and the consistency of the added contraindication with surgical training and practice.

Here's what can be extracted from the text regarding the device and its assessment:

Device: GIA™ Stapler with Tri-Staple™ Technology
Type: Surgical Stapler (manual, linear stapler)
Function: Places two triple staggered rows of titanium staples and simultaneously cuts and divides tissue between these rows.
Applications: Abdominal and thoracic surgical procedures for resection, transection, and creation of anastomosis.

The "study that proves the device meets the acceptance criteria" in this context refers to the non-clinical performance data and the justification of substantial equivalence for the change introduced (the new contraindication).

Here's how the provided information relates to the request, acknowledging the non-AI/ML nature:

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

• Acceptance Criteria (Implicit for this submission): The primary acceptance criterion for this specific 510(k) submission is to demonstrate that the addition of a contraindication does not alter the fundamental operating principle, mechanism of action, intended use, or a new question of safety and effectiveness compared to the predicate device. The device's fundamental performance characteristics (e.g., staple formation, tissue cutting) are presumed to be established by the predicate device's clearance.
• Reported Device Performance (for this submission):
  • Technological and Performance Characteristics: The subject device is stated to "not change the fundamental operating principle and mechanism of action when compared to the predicate device."
  • Usability Assessment: "Usability assessment was performed for the proposed labeling changes to demonstrate substantial equivalence to the predicate device."
  • Contraindication: The added contraindication ("should not be used to staple tissues that are necrotic, friable, or have altered integrity, e.g., ischemic or edematous tissues") is stated to be "consistent with surgical training and practice."

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

• Not applicable in the context of AI/ML validation. For a mechanical device like a stapler, "test set" would typically refer to the samples of components or assembled devices used for various mechanical, material, or functional tests (e.g., staple strength, firing force, material biocompatibility). The document only generally states "Non-clinical performance data" and "Usability assessment was performed." Specific sample sizes or provenance for these engineering tests are not detailed in this 510(k) summary.

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

• Not applicable (no AI/ML ground truth). The "ground truth" concept in AI/ML refers to expert-annotated data. For this device, the "truth" is based on engineering specifications, material properties, and surgical principles. The document mentions the contraindication is "consistent with surgical training and practice," implying a consensus amongst medical professionals or established surgical guidelines, rather than a specific expert panel establishing "ground truth" for a dataset.

4. Adjudication method for the test set:

• Not applicable (no AI/ML ground truth).

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 mechanical surgical device, 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:

• Not applicable in the AI/ML sense. For this device, the "truth" for its performance is derived from:
  • Engineering specifications and testing: Ensuring the stapler performs its mechanical function (stapling, cutting) within predefined tolerances.
  • Surgical principles and clinical consensus: The added contraindication is deemed valid because it aligns with established surgical understanding of tissue viability.
• The document explicitly states: "Clinical performance data - No clinical study is deemed necessary since the substantial equivalence has been sufficiently demonstrated by non-clinical studies."

8. The sample size for the training set:

• Not applicable (no AI/ML training data).

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

• Not applicable (no AI/ML training data).

In summary, this 510(k) pertains to a hardware medical device (a surgical stapler) and its labeling changes, not an AI/ML-driven software product. Therefore, most of the detailed questions regarding AI/ML validation studies are not relevant to this specific FDA submission. The "evidence" provided for this submission focuses on demonstrating that the change (adding a contraindication) does not alter the device's fundamental equivalence to its predicate, primarily through non-clinical testing and alignment with accepted medical practice.

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The GLA™ stapler with Tri-Staple™ technology has applications in abdominal and thoracic surgical procedures for resection, transection and creation of anastomosis.

The GIA™ stapler with Tri-Staple™ technology places two triple staggered rows of titanium staples and simultaneously cuts and divides tissue between these two triple rows. The subject GIA™ stapler and cartridges with Tri-Staple™ technology are available in 60 mm staple line length and two staple sizes to accommodate tissue thicknesses: medium/thick and extra thick. Staplers for medium/thick tissue (purple cartridge) deploy three height-progressive rows of 3.0 mm. 3.5 mm and 4.0 mm titanium staples on either side of the tissue cut line. Staplers for extra thick tissue (black cartridge) deploy three height-progressive rows of 4.0 mm, 4.5 mm and 5.0 mm titanium staples on either side of the cut line. Each GIA™ stapler with Tri-Staple™ Technology may be reloaded with a GIA™ Cartridge with Tri-Staple™ Technology up to 7 times for a total of 8 firings per instrument.

The GIA™ Stapler with Tri-Staple™ Technology is manufactured with essentially the same patient contact materials that are utilized within the predicate device (K192720).

The GIA™ stapler with Tri-Staple™ technology has the same principle operation as the predicate device. The GIA™ Stapler with Tri-Staple™ Technology is a manual single-use device. It is provided sterile (ethylene oxide) with a 5-year shelf life, and intended for multiple use during a single procedure, which is the same as the predicate device (K192720).

The document describes a 510(k) premarket notification for the GIA™ Stapler with Tri-Staple™ Technology. A 510(k) submission aims to demonstrate that the new device is substantially equivalent to a legally marketed predicate device, rather than proving that it meets specific, novel acceptance criteria based on extensive clinical studies typical for novel devices.

Therefore, the "acceptance criteria" here refers to demonstrating that the subject device is substantially equivalent to the predicate device in terms of technological characteristics and performance, without raising new questions of safety or effectiveness. The study performed is a series of non-clinical performance tests.

Here's the breakdown of the information requested, based on the provided text:

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

Since this is a 510(k) submission focused on substantial equivalence, the "acceptance criteria" are implicitly that the subject device performs comparably to the predicate or reference device in specified non-clinical tests. The document doesn't provide explicit pass/fail criteria with numerical thresholds, but rather outlines the types of tests performed to demonstrate comparable performance.

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

The document does not specify the exact sample sizes for each of the non-clinical tests (bench, ex-vivo, in-vivo, biocompatibility). It only states that these tests "have been performed." The data provenance is not explicitly mentioned, but the submitter (Covidien) has corporate presence in both China (Leo Chen) and the USA (Katherine Y. Choi, U.S. Agent), suggesting the tests could have been conducted in various locations. Given the nature of these tests, they are inherently prospective experiments designed to evaluate device performance under controlled conditions.

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)

This type of information is not applicable to this submission. "Ground truth" established by experts is typically relevant for diagnostic AI/imaging devices where human interpretation is the benchmark. For a surgical stapler, the "ground truth" is defined by objective physical and biological performance metrics (e.g., burst pressure, staple formation, hemostasis) measured in laboratory or animal settings, not by expert consensus on interpretations.

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

This is not applicable as there is no expert adjudication of results in the context of mechanical device performance testing. The results are based on objective measurements and established test procedures.

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

A Multi-Reader Multi-Case (MRMC) comparative effectiveness study is not applicable. This type of study is used for evaluating diagnostic devices, particularly those involving human interpretation of medical images (e.g., AI in radiology). The GIA™ Stapler is a surgical instrument, not a diagnostic AI device. The submission explicitly states: "No clinical study is deemed necessary since the substantial equivalence has been sufficiently demonstrated by non-clinical studies."

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

This is not applicable. The device is a manual surgical stapler; it is not an algorithm or an AI product, and therefore does not have a "standalone" algorithmic performance. Its performance is intrinsically tied to its mechanical function and human use in a surgical setting.

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

As explained in point 3, the concept of "ground truth" in the diagnostic context is not directly applicable. For this device, the "ground truth" for performance evaluation is based on objective measurements from in-vitro (bench), ex-vivo, and in-vivo (animal) studies, such as:

• Physical measurements of staple formation.
• Measured firing force.
• Burst pressure of stapled tissues.
• Assessment of pneumostasis.
• Evaluation of hemostasis.
• Standardized biocompatibility test results.

8. The sample size for the training set

This is not applicable. The GIA™ Stapler is a mechanical surgical device, not an AI/machine learning model that requires a training set.

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

This is not applicable for the same reason as point 8.

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The GIA™ stapler with Tri-Staple™ technology has applications in abdominal and thoracic surgical procedures for resection, transection and creation of anastomosis.

The subject GIA™ stapler with Tri-Staple™ technology places two triple staggered rows of titanium staples and simultaneously cuts and divides tissue between these two triple rows. The GIA™ stapler and cartridges with Tri-Staple™ technology are available in 80 mm staple line length and two staple sizes to accommodate various tissue thicknesses: medium/thick and extra thick. Staplers with medium/thick staple size (purple cartridge) deploy three height-progressive rows of 3.0 mm, 3.5 mm and 4.0 mm titanium staples on either side of the tissue cut line. Staplers with extra thick staple size (black cartridge) deploy three height progressive rows of 4.0 mm, 4.5 mm and 5.0 mm titanium staples on either side of the cut line. Each GIA™ stapler with Tri-Staple™ technology may be reloaded with GIA™ Cartridge with Tri-Staple™ Technology up to 7 times for a total of 8 firings per instrument.

The subject device GIA™ Stapler with Tri-Staple™ Technology is manufactured with the same patient contact materials that are utilized within the predicate device (K111825).

The subject device GIA™ stapler™ technology has the same principle operation as the predicate device. The GIA™ Stapler with Tri-Staple™ Technology is a manual single-use device. It is provided sterile (ethylene oxide) with 5-year shelf life, and intended for multiple use during a single procedure, which is the same as the predicate device (K111825).

The provided document is a 510(k) summary for the GIA™ Stapler with Tri-Staple™ Technology, a surgical stapler. It describes the device, its intended use, and its substantial equivalence to a predicate device.

However, the request asks for information regarding acceptance criteria and a "study that proves the device meets the acceptance criteria" in the context of an AI/algorithm-driven device. This document does not describe an AI/algorithm-driven device. It describes a mechanical surgical stapler. Therefore, many of the requested categories (e.g., sample size for test set, number of experts for ground truth, MRMC study, standalone performance, training set size, ground truth for training set) are entirely not applicable to a mechanical device submission like this one.

The document discusses performance tests for the surgical stapler, which are traditional engineering and biological tests, not AI model evaluations.

Given the nature of the provided document, I cannot fulfill the request as it pertains to an AI/algorithm-driven device.

What I can extract from the provided document, interpreting "acceptance criteria" as performance tests for a mechanical surgical stapler, is:

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

The document lists "Tests performed to evaluate and compare technological and performance characteristics," which essentially serve as acceptance criteria for this mechanical device. No specific quantitative "reported device performance" values are given in this summary; rather, it states that these tests were performed to "demonstrate substantial equivalence."

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

• Sample Size: Not specified in the provided 510(k) summary for any of the performance tests.
• Data Provenance: Not specified (e.g., country of origin). The tests are described as "non-clinical performance data." Some are in-vitro, ex-vivo, and in-vivo. These would typically be lab or animal studies for a mechanical device. The document explicitly states "No clinical study is deemed necessary."

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

• Not Applicable. This is a mechanical device, not one requiring expert human interpretation of images or signals for ground truth. The "ground truth" for these tests would be the physical properties and performance measurements of the stapler itself.

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

• Not Applicable. This concept is relevant for reconciling discrepancies in human expert labeling/interpretation, not for mechanical device 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:

• Not Applicable. This is explicitly an evaluation of an AI-driven device, which this is not. The document states "No clinical study is deemed necessary since the substantial equivalence has been sufficiently demonstrated by non-clinical studies."

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

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

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

• For mechanical devices, "ground truth" is established through direct measurement against predefined specifications, material properties, and functional performance benchmarks (e.g., burst pressure measurements, visual inspection, firing force data, staple formation analysis). It is not based on expert consensus of medical images or pathology.

8. The sample size for the training set:

• Not Applicable. This device is not an AI/ML algorithm that requires a training set.

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

• Not Applicable. This device is not an AI/ML algorithm.

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