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510(k) Data Aggregation
(136 days)
DAVOL ABSORBABLE FASTENER SYSTEM, MODEL (S) 0113080,0113081, 0113082, 0113084, 0113086, 0113087
The Davol Absorbable Fastener System is indicated for the approximation of soft tissue and fixation of surgical mesh to tissues during open or laparoscopic surgical procedures, such as hernia repair.
The Davol Absorbable Fastener System is designed to deliver an absorbable fastener into I ho Da vir reberration ing general surgery procedures such as hernia repair. The fastener system consists of an ergonomic handle with trigger, shaft and penetrating tip. The shaft is available in either a 36 cm length for laparoscopic use or an 18 cm length for open surgical procedures. The device is preloaded with 5, 15, or 30 absorbable fasteners. Each absorbable fastener contains threads for mesh and tissue delivery.
The provided text describes a 510(k) summary for the Davol Absorbable Fastener System. This documentation is for a medical device that delivers absorbable fasteners during general surgery procedures like hernia repair. The request asks for details related to acceptance criteria and the study proving the device meets these criteria. However, a 510(k) summary for a medical device like this, particularly one from 2008, does not typically contain the detailed information requested regarding clinical trial design, acceptance criteria tables, sample sizes for test/training sets, expert qualifications, or multi-reader multi-case studies with AI assistance.
The provided text focuses on demonstrating substantial equivalence to a predicate device, which is the primary goal of a 510(k) submission. It briefly mentions performance data but does not specify "acceptance criteria" in the format of a table of metrics or provide detailed study designs that would typically be found in a clinical trial report or a more comprehensive performance study summary.
Therefore, many of the requested fields cannot be directly extracted from the provided document. I will fill in the information that can be inferred or directly stated, and indicate where the information is not available in the given text.
Here's an analysis based on the provided text:
1. A table of acceptance criteria and the reported device performance
| Acceptance Criteria (Inferred) | Reported Device Performance |
|---|---|
| Biocompatibility (non-toxic, non-sensitizing) | "The biocompatibility test results show that the material used in the design and manufacture of the components of the proposed device are non-toxic and non-sensitizing to biological tissues consistent with its intended use." |
| Mechanical strength of repair (over time, compared to predicate) | "The Davol Absorbable fasteners were tested in vitro in a hernia repair model and in vivo in an animal model to confirm the mechanical strength of the repair over time as compared to the predicate device." (Specific results not detailed) |
| Material degradation characteristics (over time) | "Additional in vitro laboratory tests were conducted to characterize material degradation over time." (Specific results not detailed) |
| Meeting established specifications for consistent performance | "All test results demonstrate that the material chosen, the manufacturing process, and the design utilized for the Davol Absorbable Fastener System met the established specifications necessary for consistent performance during its intended use." |
2. Sample size used for the test set and the data provenance (e.g. country of origin of the data, retrospective or prospective)
- Sample size for test set: Not specified in the document. The studies mentioned are "in vitro in a hernia repair model" and "in vivo in an animal model."
- Data provenance: Not specified. "In vivo in an animal model" suggests animal data, not human patient data from a specific country. The study design (retrospective/prospective) is not detailed.
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)
- Number of experts: Not applicable. This device is a surgical fastener system, not an AI diagnostic tool that would require expert-established ground truth for image interpretation or similar tasks. The "ground truth" for its performance would be objective measurements from mechanical tests and animal studies.
- Qualifications of experts: Not applicable.
4. Adjudication method (e.g. 2+1, 3+1, none) for the test set
- Adjudication method: Not applicable. This is not an AI diagnostic or interpretive device where adjudication of readings would be necessary. Performance is based on physical and biological 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
- MRMC comparative effectiveness study: No, this device is a physical surgical fastener, not an AI-assisted diagnostic or interpretive tool. Therefore, MRMC studies and "human readers improve with AI" metrics are not relevant.
6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done
- Standalone performance: Not applicable. This is a physical medical device (fastener system), not an algorithm or AI. Its performance is inherent to its design and material properties, tested in a lab or animal setting.
7. The type of ground truth used (expert consensus, pathology, outcomes data, etc)
- Type of ground truth: For biocompatibility, the ground truth is established through standard biological tests (e.g., cytotoxicity, sensitization assays). For mechanical strength, the ground truth would be objective measurements of force, displacement, or tear resistance; for degradation, it would be material property changes over time. These are all objective, laboratory-derived measurements rather than interpretive ground truths like expert consensus or pathology.
8. The sample size for the training set
- Sample size for training set: Not applicable. This is not an AI/machine learning device that requires a training set.
9. How the ground truth for the training set was established
- How ground truth for training set was established: Not applicable. This is not an AI/machine learning device.
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