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The intended use of Redyrob is as a vacuum source / waste container utilized for post operative wound drainage. The indications for use for the device are to drain blood and secretions from wounds and body cavities for hematoma and surtma prophylaxes and for the removal of serosanguineous fluid and other harmful liquids.

REDYROB ® is a vacuum source/waste container utilized for postoperative wound drainage.

The provided text describes a 510(k) submission for the REDYROB® Closed Wound Drainage System. This type of regulatory submission focuses on demonstrating substantial equivalence to a legally marketed predicate device, rather than a clinical study establishing new performance metrics or acceptance criteria as one might find for a novel, high-risk device.

Therefore, many of the requested categories for acceptance criteria and study details cannot be directly extracted from this document, as they are not typically part of a 510(k) for a Class I device of this nature. The "acceptance criteria" here primarily refer to the product meeting its design specifications and demonstrating suitability through material testing and physical testing, rather than clinical performance metrics.

Here's a breakdown based on the information available:

1. Table of Acceptance Criteria and Reported Device Performance:

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

• Sample Size: Not specified for material or physical testing. The context implies routine quality control testing of manufactured units, which would involve a representative sample size based on manufacturing volumes and statistical sampling plans, but the specific numbers are not provided in this regulatory summary.
• Data Provenance: Not explicitly stated regarding country of origin for testing data. The testing is described as occurring internally by B. Braun Medical, Inc. (USA-based company). The testing is retrospective, as it's part of post-manufacturing quality control and validation.

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

• Not applicable in the context of this 510(k) summary. The "ground truth" for the device's technical performance is based on internal quality control standards and specifications, not expert clinical diagnosis or interpretation.

4. Adjudication Method for the Test Set:

• Not applicable. Adjudication methods (like 2+1, 3+1) are typically used in clinical studies where expert consensus is needed to establish ground truth for a diagnostic device. Here, the "truth" is whether a manufactured unit meets its engineering specifications.

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 not an AI-assisted diagnostic device, nor is it a device that involves human readers or interpretation of results in that sense. It is a physical medical device (a wound drainage system).

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

• Not applicable. The REDYROB® is a physical device, not an algorithm.

7. The Type of Ground Truth Used:

• For material safety, the ground truth is established by ISO Standard 10993 requirements for biocompatibility.
• For product performance, the ground truth is established by product design specifications, quality control test procedure documents, and established testing parameters. This is based on engineering and manufacturing standards.
• For substantial equivalence, the ground truth is the performance and safety profile of the legally marketed predicate device (Varidyne Model 250 Suction Drainage System).

8. The Sample Size for the Training Set:

• Not applicable. This document does not describe the development of a predictive model or algorithm that would require a training set. The device is a physically manufactured product.

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

• Not applicable for the same reason as above. There is no training set for this type of device.

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The Odontit Autogenous Bone Collection Device is indicated for use as an aspirator for the removal and collection of blood, autogenous bone chips, or other extraneous fluids from a surgical site. Using a vacuum source, the Odontit aspirator will remove materials (including blood, bone chips and other fluids) from the surgical site and pass them through a stainless steel screen which is designed to capture and collect autogenous bone. At the option of the surgeon, this bone may be removed from the aspirator, washed and cleansed as necessary, and returned to the same patient as an autogenous bone graft.

The capacity for bone collection in the screen is approximately 16 cc.

The Odontit Autogenous Bone Collection Device is a portable suction device intended for use as an aspirator for the removal and collection of blood, autogenous bone, or other extraneous fluids from a surgical site. The device consists of the following components: Body Assembly, Aspirator Tip, Screen Filter, Flex tubing, Rigid tubing and a Plunger.

The provided text describes a 510(k) Premarket Notification for the "Odontit Autogenous Bone Collection Device." This type of submission is for demonstrating substantial equivalence to a legally marketed predicate device, rather than proving safety and effectiveness through extensive clinical trials with specified acceptance criteria. Therefore, the information requested in your prompt related to clinical studies, acceptance criteria, sample sizes, expert ground truth, MRMC studies, and standalone performance is generally not applicable to a 510(k) submission of this nature.

Here's an explanation based on the document:

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

• Not Applicable. The 510(k) process for a device like this focuses on demonstrating "substantial equivalence" to a predicate device, not on meeting specific, pre-defined acceptance criteria from a performance study. Clinical performance metrics (like sensitivity, specificity, accuracy) or detailed engineering performance criteria (beyond basic functional specifications) are not presented in this document.

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

• Not Applicable. No test set or associated data provenance is discussed in this 510(k) summary. The submission is a regulatory filing, not a report of a clinical study.

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. No ground truth establishment by experts is described, as no specific test set or clinical study requiring such a method is mentioned.

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

• Not Applicable. No test set or corresponding adjudication method is discussed.

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. The device is a non-powered, single-patient, portable suction apparatus for collecting bone chips. It is not an AI-assisted diagnostic or interpretative device, so an MRMC study and AI-related effectiveness are entirely irrelevant to this submission.

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

• Not Applicable. This is a physical medical device, not an algorithm, so standalone performance in the context of an algorithm is not relevant.

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

• Not Applicable. As no clinical study results are presented, there is no discussion of ground truth.

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. As it's not an AI/ML algorithm, there's no training set or ground truth establishment for it.

Summary of the 510(k) Submission:

The provided document is a 510(k) Premarket Notification for the "Odontit Autogenous Bone Collection Device". The core of this submission is demonstrating substantial equivalence to a predicate device, the "KAM Super Sucker™" (K822065).

The claim for substantial equivalence is based on:

• Product design
• Material of construction
• Function as an aspirator

The device's intended use is "as an aspirator for the removal and collection of blood, autogenous bone chips, or other extraneous fluids from a surgical site." It uses a vacuum source to pass materials through a stainless steel screen to capture autogenous bone, which can then be returned to the patient as an autogenous bone graft. The capacity for bone collection in the screen is approximately 16 cc.

The FDA reviewed the submission and determined that the device is substantially equivalent to legally marketed devices, allowing it to proceed to market. This type of submission does not typically involve the extensive clinical studies or performance data that would necessitate the reporting of acceptance criteria, sample sizes for test/training sets, or expert-established ground truths.

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The Cordis Suction Reservoir Kit is intended to be used with the Cordis Subdural Drainage Catheter for drainage of extraventricular fluid collections.

The kit consists of a Suction Reservoir and an extension tubing with an integrated male Luer connector. The Suction Reservoir has a 100 cc capacity with graduated markers every 25 cc allowing measurement of fluid collections. It also incorporates an anti-reflux valve to prevent backflow. The Suction Reservoir provides consistent negative pressure while returning to its original shape and volume.

This document is a Summary of Safety and Effectiveness for a medical device submitted to the FDA, specifically the Cordis Suction Reservoir Kit. It is a pre-market notification (510(k)) and does not contain the type of detailed performance criteria, study design, and results typically found in publications for AI/ML device approval.

Therefore, I cannot provide the information requested in your numbered list. This document focuses on demonstrating substantial equivalence to predicate devices rather than proving performance against specific quantitative acceptance criteria through rigorous clinical studies with AI components.

Here's why each point cannot be answered from the provided text:

1. A table of acceptance criteria and the reported device performance: This document does not describe quantitative performance metrics or acceptance criteria beyond functional statements like "provides consistent negative pressure." There are no reported device performance numbers.
2. Sample size used for the test set and the data provenance: There is no mention of a "test set," "sample size," or data origin for a performance study.
3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts: Not applicable. There is no mention of ground truth establishment by experts for a performance study.
4. Adjudication method (e.g. 2+1, 3+1, none) for the test set: Not applicable. No test set or adjudication is mentioned.
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 device is a physical suction reservoir, not an AI/ML-powered diagnostic or assistive technology. Therefore, an MRMC study related to AI assistance is not relevant.
6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done: Not applicable, as this is not an AI/ML algorithm.
7. The type of ground truth used (expert consensus, pathology, outcomes data, etc.): Not applicable. There is no mention of ground truth as it pertains to performance evaluation in the context of AI/ML or complex diagnostic devices.
8. The sample size for the training set: Not applicable, as this is not an AI/ML device that requires a training set.
9. How the ground truth for the training set was established: Not applicable, for the same reason as above.

In summary, the provided text describes a traditional medical device (a suction reservoir) and seeks 510(k) clearance based on substantial equivalence, not on the performance metrics and study types associated with AI/ML device evaluations.

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Post-operative passive drainage of serosanguineous fluids away from soft tissue operative site.

Passive Wound Drain. Flat Silicone Drain. Dimensionally equivalent to the Davol Gravity Drain, except Davol offers both 12" and 18"; Sil-Med Corporation offers 18" only. Both have inner diameter teeth to prevent the drain from collapsing. Both devices have a Radiopaque stripe. Sil-Med Penrose Drains are sold sterile only.

The provided text describes a 510(k) summary for the Sil-Med Corporation's Penrose Drain, comparing it to a predicate device, the Davol Gravity Drain. The information focuses on a comparison of device characteristics and biocompatibility testing, not on clinical performance or diagnostic accuracy. Therefore, the questions related to AI/algorithm performance, ground truth, expert opinions, and reader studies are not applicable to this submission.

Here's a breakdown of the available information:

1. Table of Acceptance Criteria and Reported Device Performance

Acceptance Criteria & Reported Performance for Sil-Med Penrose Drain

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 refers to various standard biocompatibility tests (e.g., Rabbit Pyrogen Test, Hemolysis-Rabbit Blood, Salmonella typhimurium REVERSE Mutation ASSAY, Kligman Maximization Study, USP CLASS VI, Elution Test, USP MUSCLE IMPLANTATION STUDY IN RABBITS WITH HISTOPATHOLOGY). The sample sizes are inherent to the standard protocols for these specific biological tests (e.g., number of rabbits for pyrogenicity or implantation, number of wells/bacteria for mutagenesis). The document does not explicitly state the specific number of samples or animals used beyond what is implied by the test names.

Data provenance (country of origin, retrospective/prospective) is not mentioned, as these are lab-based biological tests, not clinical studies involving patient data.

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. This submission concerns biocompatibility and dimensional equivalence, not diagnostic performance or expert review of medical images/data. The "ground truth" here is established by the validated methods of the specified biological and physical tests and their established pass/fail criteria.

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

Not applicable. Adjudication methods like 2+1 or 3+1 are typically used for resolving disagreements in expert readings of medical data. The tests described are objective biological and physical assessments.

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 not a submission for an AI/CAD device.

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

Not applicable. This is not a submission for an AI/CAD device.

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

The "ground truth" for the tests performed is based on:

• Established Biomedical Standards: For tests like USP CLASS VI, the ground truth is defined by the requirements outlined in the United States Pharmacopeia.
• Standardized Laboratory Protocols: For tests like pyrogenicity, hemolysis, mutagenesis, and sensitization, the ground truth is determined by the specific, validated methods and endpoints of these universally accepted in vitro and in vivo biological assays.
• Physical Measurement Comparisons: For dimensional equivalence, the ground truth is direct measurement and comparison to the predicate device's specifications.

8. The sample size for the training set

Not applicable. There is no AI/machine learning model being developed, so no training set is relevant.

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

Not applicable. As there is no AI/machine learning model, there is no training set and therefore no ground truth establishment for it.

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