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The Navigator (stylet) is a stainless steel wire rod, inserted into the catheter to assist with insertion and placement of the catheter in the peritoneum.

Stainless steel wire rod intended to aid in the manipulation of or insertion of the catheter for placement in the peritoneum.

The provided document is a 510(k) summary for a medical device called "Navigator (stylet)". This document describes the device, its intended use, and biocompatibility testing. It is a premarket notification for a medical device and therefore does not contain information related to software algorithm performance, such as acceptance criteria for diagnostic accuracy, sample sizes for test sets in an AI context, or ground truth establishment by experts.

This document describes a physical medical device (a stainless steel wire rod or stylet), not a software algorithm or an AI-powered diagnostic tool. The "acceptance criteria" discussed are related to the physical properties and biological compatibility of the device, not its performance in a diagnostic or analytical capacity. Therefore, the questions related to AI/algorithm performance, ground truth, expert consensus, and comparative effectiveness studies are not applicable to the content provided.

Here's an attempt to answer the relevant questions based on the provided text, and to explicitly state when information is not applicable or available:

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

Note: The acceptance criteria for "Pass" in the cytotoxicity study and "Non-Hemolytic" in the hemolysis study are directly stated or directly implied by the result.

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: Not applicable. The document describes a physical device, not an algorithm tested with a data set of images or patient data. Biocompatibility studies are typically performed on samples of the device material, not a "test set" in the context of an algorithm.
• Data Provenance: Not applicable.

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 as typically defined for algorithms (e.g., disease presence/absence based on expert consensus) is not relevant for the assessment of a physical stylet's biocompatibility or dimensional equivalence. The "ground truth" for biocompatibility is established by standardized laboratory tests.

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

• Not applicable. Adjudication methods are typically used to resolve discrepancies in expert interpretation of diagnostic data for algorithm training/testing, which is not relevant here.

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 physical stylet, not an AI-powered diagnostic tool. MRMC studies evaluate the impact of AI on human reader performance, which is not relevant for this device.

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

• Not applicable. This is a physical device, not a standalone software algorithm.

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

• Not applicable in the context of an algorithm's diagnostic performance. For biocompatibility, the "ground truth" is provided by the results of standardized biological assays (cytotoxicity and hemolysis tests) and physical/material comparisons against predicate devices.

8. The sample size for the training set

• Not applicable. This device does not involve a training set for an algorithm.

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

• Not applicable. This device does not involve a training set or ground truth establishment in the context of an algorithm.

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Peritoneal Dialysis Coil Catheter with Spi-Argent™II, for the transport of dialysate solution to and from the peritoneal cavity for treatment of renal failure; suitable for CAPD (Continuous Ambulatory Peritoneal Dialysis)

Peritoneal Dialysis Coil Catheter with Spi-Argent™II, for the transport of dialysate solution to and from the peritoneal cavity for treatment of renal failure; suitable for CAPD (Continuous Ambulatory Peritoneal Dialysis). Peritoneal Dialysis Coil Catheter with Spi-Argent™ll is the same as the Peritoneal Dialysis Coil Catheter, K850247 except for the Spi-Argent™ II option offering. Spi-Argent™ II is the same surface treatment as the K942709, Mediastinal Drain with Spi-Argent™ II. The Spi-Argent™II surface treatment provides a lubricious surface to ease insertion and removal of the catheter.

The provided text is a 510(k) summary for the Sil-Med Corporation's Peritoneal Dialysis Coil Catheter with Spi-Argent™ II. This document describes the device, its intended use, and its predicate devices for the purpose of demonstrating substantial equivalence to the FDA.

Crucially, this document does NOT contain information about acceptance criteria or a study that proves the device meets specific performance criteria.

510(k) submissions typically focus on demonstrating substantial equivalence to a legally marketed predicate device rather than presenting detailed performance studies with acceptance criteria in the same way a PMA (Premarket Approval) submission would. While the sponsor would have conducted internal testing to ensure the device performs as intended, the provided summary does not include the specifics of such testing, acceptance criteria, or performance data.

Therefore, I cannot provide accurate answers to your questions based solely on the provided text. The requested information regarding acceptance criteria, study details, sample sizes, expert qualifications, adjudication methods, MRMC studies, standalone performance, ground truth types, and training set details are not present in this document.

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Catheter for drainage of blood and fluid from mediastinum after chest surgery and/or trauma; for use with suction apparatus

Silicone perforated tubing, flattened profile, blue radiopaque stripe; surface treated to reduce friction and Antimicrobial; perforations ("eyes") on both flattened surfaces of tubing; external end has cutaway adapter; imprinted with drain size

This document describes a 510(k) submission for an "Antimicrobial Mediastinal Silicone Drain." However, it is not a study involving AI or a medical imaging device.

Therefore, I cannot provide the information requested in your prompt as it pertains to AI/ML device studies. The prompt asks for details like:

• Acceptance criteria and reported device performance in the context of AI/ML metrics.
• Sample size and provenance for test sets for AI/ML models.
• Number of experts and their qualifications for establishing AI/ML ground truth.
• Adjudication methods for AI/ML ground truth.
• Multi-reader multi-case comparative effectiveness studies for AI/ML assistance.
• Standalone performance of an algorithm.
• Type of ground truth used for AI/ML training/testing.
• Sample size and ground truth establishment for AI/ML training sets.

The provided text describes a catheter with an antimicrobial coating. The "study" mentioned is a microbiological challenge test to prove the effectiveness of the antimicrobial surface against specific organisms.

Here's what I can extract from the provided text, re-framed to directly answer the specific questions where applicable, and noting where the information is not present or irrelevant to AI/ML:

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

Acceptance Criteria & Reported Performance (for Antimicrobial Efficacy):

(Note: The document doesn't explicitly state quantitative acceptance criteria like "X% reduction in bacterial count." It only states the device "proved effective" against the listed organisms through a challenge.)

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 Antimicrobial Challenge Test): Not specified in the document. This would typically refer to the number of device samples tested in the lab.
• Data Provenance: Not specified, but generally, these are laboratory-based studies, not 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)

• Number of Experts & Qualifications: Not applicable. Ground truth for an antimicrobial challenge test is established in a microbiology laboratory by testing the device against bacterial cultures, not by human experts interpreting medical images.

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

• Adjudication Method: Not applicable. This concept pertains to resolving discrepancies in expert interpretations of medical images, which is not relevant here.

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 Study: No. This is not an AI-assisted device.

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

• Standalone Performance: No. This is not an AI algorithm.

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

• Type of Ground Truth: The "ground truth" (or outcome measure) for this device is the inhibition or killing of specific microorganisms when they are exposed to the device's surface in a controlled laboratory setting (microbiological culture results).

8. The sample size for the training set

• Sample Size for Training Set: Not applicable. There is no AI model or training set involved.

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

• Ground Truth for Training Set Establishment: Not applicable. There is no AI model or training set involved.

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For post-operative drainage of serosanguineous fluids and blood away from operative site; for use with suction reservoir as a closed wound drain system

Two joined silicone tubing sections; flat drain section is partially perforated for fluid collection, is ribbed to prevent collapse as suction is applied, and has blue radiopaque stripe; round tubing is connected to suction reservoir inlet; offered with an introduction Trocar attached as an option; silver ion surface treated to ease insertion and removal.

This 510(k) summary describes a medical device, not an AI/ML algorithm. Therefore, many of the requested categories in your prompt are not applicable. I will address the relevant sections based on the provided text and indicate "N/A" for those that do not apply to a device submission of this nature.

Here's the analysis of the provided information:

Acceptance Criteria and Device Performance

The 510(k) summary does not explicitly list "acceptance criteria" in the format typically used for AI/ML performance metrics (e.g., sensitivity, specificity, AUC). Instead, for device submissions, the acceptance criteria are generally met by demonstrating substantial equivalence to a predicate device through shared technological characteristics, intended use, and performance claims.

The device performance is primarily established by referencing the performance of the predicate devices. The summary states:

"Sil-Med Corporation's Flat Suction Drain/Kit with Spi-Argent™ II, (with and without Trocar) is the same drain as the Sil-Slip Flat Suction Drain/Kit (with and without Trocar), K926408. The surface treatment is the same as the surface treatment on Sil-Med Corporation's Mediastinal Silicone Drain, K942709. No further claims will be made for the Flat Suction Drain/Kit with Spi-Argent™ II than made on K942709."

This indicates that the new device is considered to perform equivalently to the predicate devices.

Study-Specific Information (Not applicable for this type of submission)

The provided document is a 510(k) summary, which focuses on demonstrating substantial equivalence to a predicate device, not on presenting novel study results for AI/ML performance. Therefore, the following sections are not applicable and the information is not present in the provided text.

2. Sample size used for the test set and the data provenance: N/A (No test set for AI/ML performance is described).
3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts: N/A (No expert ground truth for AI/ML performance is described).
4. Adjudication method (e.g. 2+1, 3+1, none) for the test set: N/A (No test set for AI/ML performance is described).
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: N/A (This is a physical medical device, not an AI/ML system).
6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done: N/A (This is a physical medical device, not an AI/ML system).
7. The type of ground truth used (expert concensus, pathology, outcomes data, etc): N/A (No ground truth, in the context of AI/ML, is mentioned).
8. The sample size for the training set: N/A (This is a physical medical device, not an AI/ML system).
9. How the ground truth for the training set was established: N/A (This is a physical medical device, not an AI/ML system).

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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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