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The DEFENDO™ Disposable Suction Valve is a disposable device that attaches to the suction cylinder of an endoscope. When the valve is depressed, the suction function on the endoscope is activated, allowing for the suctioning of fluid through the stem of the valve where it flows into the Suction Pump Canister.

AI/ML Overview

Here's a breakdown of the acceptance criteria and the study details for the DEFENDO™ Disposable Suction Valve, based on the provided document:

1. Table of Acceptance Criteria and Reported Device Performance

Acceptance Criteria	Reported Device Performance	Result
Connection to the endoscope: The valve must connect to the endoscope by aligning valve with port and pressing down. Must not be cumbersome to attach.	The force required to connect the BMI suction valve (100305) and the ease of installation was similar to the predicate (Olympus® MH-443). Alignment with the port notches was comparable. Test results showed "Smooth" for all 10 tests of the BMI 100305, matching the "Smooth" results of the predicate.	Pass
Priming time to Suction Canister: The device must be comparable to the predicate device in terms of being able to supply water within a reasonable time frame (priming time).	The average priming time for the BMI 100305 was 3.92 seconds (SD 0.163) over 10 tests, compared to the predicate's average of 4.16 seconds (SD 0.147) over 8 tests. The results indicate no significant difference between the two units.	Pass
Material Quantity Removed: The device must be comparable to the predicate device in terms of the amount of water removed in the defined time frame.	The average material removed for the BMI Suction Valve was 512.2 grams (SD 11.25) over 8 samples (10 tests each), compared to the predicate's average of 528.5 grams (SD 13.61) over 8 samples (10 tests each). The difference was < 4.5% for the worst case view (30 seconds of suction) and < 3.3% for a more typical 5-10 second suction. The BMI unit also showed improved repeatability (lower SD).	Pass
Spring Force & Displacement: The device must be comparable to the predicate device in terms of force required to activate the button.	The average force for the BMI 100305 was 2.862 lb (SD 0.178) for an average displacement of 0.1962 in (SD 0.003). The predicate averaged 2.0813 lb (SD 0.086) for an average displacement of 0.1876 in (SD 0.005). While there was a "slight difference," these differences were not perceivable in blind tests by the tester or other selected parties (3 additional people).	Pass
No sharp edges: The device must not be capable of snagging or piercing a nitrile glove if the wearer rubs his or her gloved fingers over any surface of the device.	Testing showed that the BMI Suction valve does not pinch, cut, or tear nitrile gloves. All 10 tests for the BMI 100305 resulted in "Pass," matching the "Pass" results of the predicate.	Pass

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

Connection to Endoscope: 10 tests for BMI 100305, 10 tests for Olympus MH-443 (predicate).
Priming Time: 10 tests for BMI 100305, 8 tests for Olympus MH-443 (predicate).
Material Quantity Removed: 8 devices of BMI-215 (DEFENDO™) and 8 devices of Olympus MH-443 (predicate), each subjected to 10 suction tests. This totals 80 tests for each device type.
Spring Force & Displacement: 10 tests for BMI 100305, 8 tests for Olympus MH-443 (predicate).
Sharp Edges: 10 tests for BMI 100305, 8 tests for Olympus MH-443 (predicate).

Data Provenance: The study appears to be a prospective bench testing study conducted by Byrne Medical, Inc. The document does not specify the country of origin for the data generation, though Byrne Medical Inc. is based in Conroe, TX, USA. The predicate device, Olympus® MH-443, is manufactured by Olympus® Optical Co. Ltd. Tokyo, Japan.

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

Number of Experts: For the "Spring Force & Displacement" test, it's mentioned that the differences were not perceivable in "blind tests by the tester or other selected parties (3 additional people)". This suggests 4 individuals participated in evaluating the tactile perception of force.
Qualifications of Experts: The qualifications of these individuals are not specified in the provided document. For the "Sharp Edges" test, a "tester's hand" is mentioned, implying at least one individual performed the test, again with no specific qualification mentioned.

4. Adjudication Method for the Test Set

The document does not explicitly describe a formal adjudication method (like 2+1 or 3+1 consensus). The evaluation criteria for most tests (e.g., connection, priming time, material quantity, sharp edges) relied on quantitative measurements or direct observation against the predicate device. For the "Spring Force & Displacement" test, a "blind test" by multiple individuals was mentioned, suggesting a qualitative comparison, but without a formal consensus or adjudication process detailed.

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study was done

No, an MRMC comparative effectiveness study was not done. This study is a bench testing evaluation of a physical medical device (a suction valve), not an AI-powered diagnostic or imaging tool. Therefore, the concept of "human readers improving with AI vs without AI assistance" is not applicable here.

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

This is not applicable as the device is a physical medical device (a disposable suction valve) and does not involve an algorithm or AI.

7. The Type of Ground Truth Used

The "ground truth" for these tests was established by:

Quantitative Benchmarking: Direct measurements and comparisons against a legally marketed predicate device (Olympus® MH-443 Suction Valve).
Physical Observation/Assessment: Direct observation of ease of connection, absence of sharp edges, and tactile perception (for spring force).
The "truth" was based on whether the performance characteristics of the new device were "comparable" or "substantially equivalent" to the predicate, as defined by the acceptance criteria.

8. The Sample Size for the Training Set

This is not applicable as the device is a physical medical device and does not involve machine learning algorithms that require a training set.

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

This is not applicable for the same reason as above (no training set for a physical device).

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