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510(k) Data Aggregation
(106 days)
The Arthroscopes of appropriate size and length are indicated for use in diagnostic and operative arthroscopic procedures to provide illumination and visualization of the hip, shoulder, knee, elbow, wist, and ankle, and also to provide illumination and visualization during open and closed arthroscopic diagnostic procedures and removal of loose bodies and soft tissue within the joint.
Hip Diagnostic procedures may include: Staging of avascular necrosis Chondral injuries Joint sepsis Synovial chondomatosis Unresolved hip pain Labral tears
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The provided text is a US FDA 510(k) clearance letter for an Arthroscope (K091398). This document primarily describes the regulatory clearance of a medical device and its intended use, but it does not contain information about acceptance criteria, device performance studies, sample sizes, ground truth establishment, or multi-reader multi-case studies.
Therefore, I cannot fulfill your request for the specific details outlined, as this information is not present in the provided text. The document is about regulatory approval based on "substantial equivalence" to a predicate device, which often means demonstrating that the new device has the same intended use and technological characteristics as a legally marketed device, or that any differences do not raise new questions of safety or effectiveness. This type of submission generally does not require the comprehensive performance study data you're asking for.
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(221 days)
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(59 days)
Operative and Diagnostic Arthroscopy for visual imaging and light transmission to the operative area.
The Arthroscopes are limited in their use to: Wrist, Knee, Shoulder and Ankle Surgery.
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The provided document is a 510(k) premarket notification letter from the FDA for an "Arthroscope" manufactured by Medifix, Inc. This letter confirms that the device is substantially equivalent to a legally marketed predicate device.
Crucially, this document is a regulatory approval letter based on substantial equivalence, not a study report detailing acceptance criteria and performance data for the device itself. It confirms that the device is similar enough to previously approved devices that it doesn't require a new, extensive clinical trial.
Therefore, the document does not contain the information requested in your prompt regarding acceptance criteria, reported device performance, sample sizes, ground truth establishment, expert qualifications, adjudication methods, MRMC studies, or standalone performance for the Arthroscope.
The prompt's questions are designed for a document describing a clinical study or a performance validation report, which this 510(k) clearance letter is not.
To answer your questions, if this were indeed a study report, the typical information would be as follows:
- Table of Acceptance Criteria and Reported Device Performance: This would typically be a table showing specific metrics (e.g., sensitivity, specificity, accuracy, precision for diagnostic devices, or specific physical performance measures for instruments) and the required threshold for acceptance versus the actual measured performance of the device in a study.
- Sample Size Used for the Test Set and Data Provenance: This would detail how many cases or patients were included in the evaluation set, the demographics, and where the data originated (e.g., retrospective analysis of a hospital database from the USA, prospective collection from a multi-center trial in Europe).
- Number of Experts Used to Establish the Ground Truth and Qualifications: This would specify how many human experts (e.g., 3 board-certified radiologists, 5 orthopedic surgeons) independently reviewed the test cases and their experience level.
- Adjudication Method: How disagreements among experts were resolved (e.g., a "2+1" rule where if two experts agree, that's the truth, and a third expert adjudicates if there's a split; or a "3+1" rule with a super-expert, or a simple majority vote).
- Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study: This would describe if human readers evaluated cases both with and without the AI assistance, and the statistical measure of improvement (e.g., AUC increase, sensitivity improvement).
- Standalone Performance: This refers to the algorithm's performance without any human intervention.
- Type of Ground Truth Used: The definitive truth used to evaluate the device. For example:
- Expert Consensus: The agreed-upon diagnosis or finding by a panel of experts.
- Pathology: Histopathological reports from biopsies or surgical resections.
- Outcomes Data: Long-term follow-up of patients to confirm a disease or condition.
- Radiological Follow-up: Subsequent imaging studies confirming findings.
- Sample Size for the Training Set: The number of cases or data points used to develop and train the device's algorithms or models.
- How the Ground Truth for the Training Set was Established: Similar to point 7, but specifically for the data used during the development phase.
Since the provided document is a 510(k) letter, none of this specific study-related information is available within the text.
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(90 days)
The EBI Spinal Endoscopic System is intended as a diagnostic tool to visualize and illuminate the epidural space of the lumbar and sacral spine when assessing disease pathology using a percutaneous posterior approach.
The EBI Endoscopic Spinal System is an arthroscope consisting of several components and different accessories for viewing the lumbar and sacral spinal anatomy. This system includes a fiberscope, disposable catheter, and various accessories. The fiberscope is designed to connect to any compatible commercially available endoscopic video imaging system by using a camera coupler and light cord adaptors.
The provided text describes a 510(k) summary for the EBI Spinal Endoscopic System. It does not contain specific acceptance criteria, a detailed study proving device performance against such criteria, or the types of quantitative data requested in your prompt (e.g., sample sizes for test/training sets, number of experts for ground truth, adjudication methods, MRMC studies, standalone performance, or detailed ground truth types).
The document is a premarket notification for a medical device (arthroscope) stating its intended use and claiming substantial equivalence to predicate devices already on the market. It mentions "bench testing demonstrates that the device meets its functional requirements" but does not elaborate on what those functional requirements are or present the results of such testing.
Therefore, I cannot populate the table or answer most of your detailed questions based solely on the provided text.
However, I can provide what information is available about the "study" (bench testing) and general claims:
1. Table of Acceptance Criteria and Reported Device Performance
| Acceptance Criteria | Reported Device Performance |
|---|---|
| Functional Requirements (specifics not provided) | Bench testing demonstrates the device meets its functional requirements. |
2. Sample size used for the test set and the data provenance
- Sample Size (Test Set): Not specified.
- Data Provenance: Not specified (implied to be internal company bench testing).
3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts
- Not applicable/Not specified. This was bench testing, not a clinical study involving expert assessment of patient data.
4. Adjudication method for the test set
- Not applicable/Not specified.
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
- No, an MRMC study was not done. This device is an arthroscope, not an AI diagnostic tool for image interpretation.
6. If a standalone (i.e. algorithm only without human-in-the loop performance) was done
- Not applicable. This is a physical endoscopic system, not an algorithm.
7. The type of ground truth used
- For "functional requirements," ground truth would typically be engineering specifications, measurements, or established performance benchmarks for similar devices, which are not detailed here.
8. The sample size for the training set
- Not applicable. This is a physical device, not a machine learning model requiring a training set.
9. How the ground truth for the training set was established
- Not applicable.
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