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FilBloc Permanent sutures are intended for general soft tissue approximation, excluding closure of the epidermis, where use of a non-absorbable suture is appropriate.

The Assut FilBloc Permanent Suture range of devices comprises a variety of gauge sizes and lengths, supplied with or without stainless steel needles, which are also available in a variety of different sizes and shapes. The sutures may have a 'block' at one end, which allows surgeons to close wounds quickly and securely without tying knots or changing suturing techniques. The block is made from the same material as the suture, and is used to anchor the suture.

Assut FilBloc Permanent Sutures contact the patient and remain attached to the patient at the point suturing and may remain in place for significant periods.

The sutures with needles do not need to be used with any other devices, but the needleless sutures need to be used together with legally available separate needles.

This document describes a 510(k) premarket notification for a medical device (Assut FilBloc Permanent Sutures) and focuses on demonstrating substantial equivalence to a predicate device rather than setting and proving new acceptance criteria for a novel AI/software-based medical device.

Therefore, many of the requested sections (e.g., sample sizes for training/test sets, expert adjudication, MRMC studies, effect sizes, standalone performance, ground truth establishment) are not applicable to this type of regulatory submission and the information provided. This document is for a physical medical product, not an AI/software device.

However, I can extract information related to performance testing that serves a similar purpose to "acceptance criteria" for a physical device, and indicate which of your requested points are not applicable.

Acceptance Criteria for Assut FilBloc Permanent Sutures and Supporting Study

Note: This document pertains to a physical medical device (surgical sutures) and its 510(k) submission, which focuses on demonstrating substantial equivalence to a legally marketed predicate device. The concepts of "AI/software acceptance criteria," "training/test sets," "expert ground truth for AI," "MRMC studies," and "effect sizes" for human readers are not applicable to this type of device and submission. The performance data provided are for the physical properties and biocompatibility of the sutures.

1. Table of Acceptance Criteria and Reported Device Performance

• Suture Diameter ()
• Suture Attachment ()
• Tensile Strength ()
• Sterility
• Shelf Life
• Packaging Integrity
• Compliance with applicable USP monographs | Performed and established compliance with USP 29.
  Available sterile (ethylene oxide, with SAL 10⁻⁶).
  Tests undertaken to establish shelf life and packaging integrity.
  Yes (stated in comparison table). |
  | Biocompatibility (based on ISO 10993-1, 5, 6, 10, 11, 3):
• Cytotoxicity
• Sensitization
• Irritation or Intracutaneous Reactivity
• Acute Systemic Toxicity
• Subchronic Toxicity
• Genotoxicity
• Implantation
• Material Mediated Pyrogenicity
• Bacterial endotoxin testing (LAL test) | All listed tests were carried out to establish biocompatibility, indicating successful completion and acceptance.
  Bacterial endotoxin testing (LAL test) is carried out on every batch. |

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

The document does not specify the exact sample sizes for each physical or biocompatibility test. It broadly states that "Physical testing was performed" and "Tests were also undertaken" and "the following tests were carried out to establish the biocompatibility." For physical medical devices like sutures, these tests are typically conducted on representative batches per established test standards (e.g., USP monographs).

• Data Provenance: The tests were performed by Assut Europe S.p.A. (manufacturer in Italy). The data is generated prospectively as part of the device's development and manufacturing compliance.

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

Not Applicable. For a physical device like a suture, "ground truth" is established by laboratory measurements according to validated standards (e.g., USP monographs, ISO standards) rather than expert human interpretation of data.

4. Adjudication Method for the Test Set

Not Applicable. Adjudication methods like 2+1 or 3+1 are typically used for assessing performance in subjective tasks or when reaching consensus on ground truth from human experts, particularly in image interpretation or clinical diagnosis. This is not relevant for the objective physical and biocompatibility testing of a suture.

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 physical medical device, not an AI or imaging diagnostic device. MRMC studies are used to evaluate diagnostic performance of imaging modalities or AI systems.

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

Not Applicable. This is a physical medical device. The concept of "standalone algorithm performance" is not relevant here.

7. The Type of Ground Truth Used

The ground truth for the performance of the sutures is based on objective, standardized laboratory measurements and biological assay results as defined by:

• United States Pharmacopeia (USP) monographs, e.g., USP 29 for suture diameter (), suture attachment (), and tensile strength ().
• International Organization for Standardization (ISO) standards for biocompatibility (e.g., ISO 10993 series).

8. The Sample Size for the Training Set

Not Applicable. This is not an AI/machine learning device. There is no concept of a "training set" for the type of data presented (physical properties and biocompatibility).

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

Not Applicable. As there is no training set mentioned, this question is not relevant. The ground truth for the device's performance relies on adherence to established, internationally recognized medical device standards and regulations.

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Filbloc sutures are indicated for use in general soft tissue approximation where use of an absorbable suture is appropriate.

Filbloc (polydioxanone) monofilament synthetic absorbable sutures are prepared from the polyester, poly(p-dioxanone). The empirical molecular formula of the polymer is: -(0-CH2-CH2-O-CH2-CO-CH2-CO)n- Filbloc sutures are undyed or dyed with D&C Violet No. 2 (21CFR§ 74.3602). The device is designed with unidirectional or bidirectional barbs, or with unidirectional barbs and final block in PDO. The barbs and the block design allow for tissue approximation, without need to tie surgical knot. The device is available in various lengths and diameter sizes 2 through 4/0 with various needles attached at one end or to both ends.

The provided text describes the 510(k) premarket notification for the "Filbloc" absorbable polydioxanone surgical suture. It focuses on demonstrating substantial equivalence to a predicate device, rather than defining specific acceptance criteria for a novel AI/software device and proving its performance through a study of that nature.

Therefore, the information required to answer the prompt is not present in the provided text. The document outlines a regulatory submission for a physical medical device (surgical sutures), detailing its material, design, intended use, and comparison to existing predicate devices. It describes physical and biocompatibility testing, but not a study designed to meet specific acceptance criteria for a device's "performance" in the way an AI/software device would be evaluated (e.g., sensitivity, specificity, AUC).

Here's why the required information is missing:

• Acceptance Criteria & Reported Device Performance (Table): The document doesn't define quantitative performance metrics such as sensitivity, specificity, accuracy, or any thresholds related to diagnostic or analytical performance. It discusses tensile strength and absorption time in comparison to a predicate, but these are material properties, not software performance.
• Sample Size (Test Set) & Data Provenance: Not applicable in the context of an absorbable suture device. The "testing" refers to physical and biocompatibility tests on the suture material itself, not a dataset of medical images or patient records.
• Number of Experts & Qualifications: Not applicable. There's no interpretive task that would require expert adjudication of a test set.
• Adjudication Method: Not applicable.
• MRMC Comparative Effectiveness Study: Not applicable. This type of study is for evaluating human performance with and without AI assistance, which is irrelevant for a surgical suture.
• Standalone Performance: While the "device" (suture) is a standalone physical product, the concept of "standalone performance" in the context of AI refers to the algorithm's performance without human intervention, which isn't relevant here.
• Type of Ground Truth: Not applicable in the AI/software sense. The "ground truth" for a suture would be its physical properties and biological absorption characteristics, confirmed through laboratory and animal testing.
• Sample Size (Training Set) & How Ground Truth for Training Set was Established: Not applicable, as this is not an AI/machine learning device.

In summary, the provided document is a 510(k) submission for a physical medical device (surgical sutures), outlining its characteristics and demonstrating substantial equivalence to a predicate device through physical and biocompatibility testing. It does not contain the type of information typically found in a study proving the acceptance criteria for an AI/software-based medical device.

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Assufil It is advised when an absorbable suture is needed for use in General Soft Tissue Approximation and Ligation

absorbable surgical suture

This document is a 510(k) premarket notification for a medical device, specifically an absorbable surgical suture called Assufil™. It does not present a study with acceptance criteria and device performance data in the way typically seen for AI/ML-based diagnostic devices.

Instead, this is a regulatory submission for a traditional medical device (suture) seeking substantial equivalence to a predicate device. The information provided is for regulatory clearance, not a performance study evaluating metrics like sensitivity, specificity, or accuracy against a ground truth for a diagnostic algorithm.

Therefore, I cannot extract the requested information regarding acceptance criteria, study details, sample sizes, expert qualifications, or ground truth methods from the provided text, as this type of information is not contained within this particular 510(k) submission for a surgical suture.

The content focuses on:

• Device Identification: Assufil™ absorbable surgical suture.
• Intended Use: General Soft Tissue Approximation and Ligation.
• Regulatory Classification: Class II, Absorbable poly(glycolide/L-lactide) surgical suture.
• Substantial Equivalence: The FDA's determination that the device is substantially equivalent to a legally marketed predicate device.

To answer your questions, I would need a 510(k) summary or a scientific publication detailing a performance study for a diagnostic or AI-driven device, which would include specific metrics, study design, and ground truth methodology.

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