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D-25 continuous non-invasive arterial oxygen saturation and pulse rate monitoring of patients > 30 kg.

N-25: continuous non-invasive arterial oxygen saturation and pulse rate monitoring of patients foot if 40 kg.

The ReNu Medical Reprocessed Nellcor™ D-25 Oximetry Sensor and Reprocessed Nellcor™ N-25 Oximetry Sensor are accessory devices to an oximeter monitoring system. The oxisensor is designed as a transducer for the transmission of electrical signals from the oximeter to the patient and the return of patient modified signals back to the oximeter for analysis and display of patient information. The sensor contains three optical components; two light emitting diodes (LEDs) serve as light sources and one photodiode acting as a light detector LED and sensor are contained in a laminated envelope provided with an adhesive bandage for attachment a patient. A sensor package is attached to a cable terminated in a multi-pin connector that plugs into the oximeter.

This looks like a 510(k) premarket notification for reprocessed oximetry sensors. Unfortunately, the provided text does not contain detailed information about acceptance criteria or a specific study proving the device meets those criteria, as one might find in a full clinical trial report.

The document states that the reprocessed sensors are "substantially equivalent" to predicate devices based on "bench testing, clinical performance data, and non-clinical performance data." However, it does not provide the specifics of these tests, including:

• Acceptance Criteria: What specific metrics (e.g., accuracy against a gold standard) were targeted, and what were the thresholds for success?
• Reported Device Performance: What were the numerical results of these tests for the reprocessed devices?
• Study Design Details: How many subjects/samples were used, where the data came from, details about ground truth, expert qualifications, etc.

Therefore, I cannot populate the table or answer most of the specific questions based only on the provided text.

Here's what I can extract and state regarding the questions, with the understanding that much information is missing:

1. Table of Acceptance Criteria and Reported Device Performance

2. Sample size used for the test set and the data provenance

• Sample Size (Test Set): Not specified.
• Data Provenance: The document mentions "clinical performance data" but does not specify the country of origin or whether it was retrospective or prospective.

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts

• Not specified. The document does not describe the establishment of a "ground truth" using experts for performance testing.

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

• Not specified. This level of detail about study design is not present.

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 an oximetry sensor, not an AI-assisted diagnostic tool that would typically involve human readers or MRMC studies for improved diagnostic performance.

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

• Not applicable in the context of an algorithm. However, the device itself (sensor) performs its measurement "stand-alone" in producing SpO2 and pulse rate data for the oximeter. The testing mentioned (bench, clinical, non-clinical) would assess its direct sensing performance.

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

• Not specified. For oximetry sensors, ground truth for SpO2 would typically involve co-oximetry of arterial blood samples. The document does not detail this.

8. The sample size for the training set

• Not applicable. This is not a machine learning or AI algorithm in the context of typical training sets. The "reprocessed" aspect implies a manufacturing process, and performance is evaluated against predicate device functionality.

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

• Not applicable (as above).

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