Search Results

The neonatal/adult Oxisensor, model N-25, is Indicated for single patient use when continuous noninvasive arterial oxygen saturation and pulse rate monitoring are required for patients weighing less than 3 kg or more than 40 kg.

The reprocessed ClearMedical/Nellcor N-25 Oxisensor is intended as a single patient use O₂ transducer/accessory sensor to a Nellcor Oximeter system. The role of the sensor the acquisition of patient data which is used by the oximeter in the determination of functional oxygen saturation and pulse rate of neonatal and adult patients. The N-25 oxisensor is used in conjunction with the Nellcor oximeter in a hospital environment where non-invasive monitoring of pulse oxygen hemoglobin saturation (SpO2) and pulse rate (PR) are required for patients with potentially abnormal pulmonary/circulatory function.

The ClearMedical/Nellcor Oxisensor is an accessory device to an oximeter monitoring system. The oximeter system is designed for the determination of functional oxygen saturation and pulse rate. 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) that serve as light sources and one photodiode that acts as a light detector. Both the LEDs and photodiode are contained within a laminated envelope with an adhesive bandage for attachment to a patient. Attached to the laminated envelope is a sensor cable, which terminates in a connector element that connects to the oximeter.

The provided document is a 510(k) summary for the ClearMedical/Nellcor Oxisensor II, Neonatal/Adult O2 Transducer, Model N-25, which is a reprocessed single-use device. This document primarily focuses on establishing "substantial equivalence" to a predicate device rather than presenting a performance study with explicit acceptance criteria for a new device's performance. Therefore, much of the requested information regarding acceptance criteria, study design, and specific performance metrics for the device itself is not explicitly detailed in this type of submission.

However, I can extract information related to the basis for establishing substantial equivalence, which serves as the "study" proving the device meets its regulatory acceptance criteria (i.e., substantial equivalence to a legally marketed predicate device).

Here's an analysis based on the provided text, addressing the points where information is available or inferable:

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

Since this is a 510(k) submission for a reprocessed device, the "acceptance criteria" are primarily framed around demonstrating substantial equivalence to the predicate device. The performance data presented is comparative, showing that the reprocessed device performs equivalently to the original. Explicit numerical acceptance criteria for clinical performance are not provided in this summary.

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

The summary states that "specific bench and non-invasive clinical testing" was performed. However, it does not specify:

• The exact sample size for the test set (number of patients or reprocessed devices tested).
• The country of origin of the data.
• Whether the study was retrospective or prospective.

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)

This information is not provided in the summary. For an oximeter, "ground truth" for oxygen saturation is typically established by arterial blood gas analysis (Co-Oximetry), not by expert consensus. The summary mentions "comparative non-invasive Co-Oximetry and Oximetry data," suggesting a comparison against a more accurate measurement method (Co-Oximetry), which would serve as the ground truth. However, details on how this was conducted or expert involvement in establishing ground truth are not present.

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

This information is not provided in the summary. Given the nature of oximetry, it's unlikely a multi-reader adjudication method would be directly relevant to the core SpO2 measurement, which tends to be an objective numerical value.

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

An MRMC study is not applicable here. This device is an oximeter transducer, an accessory device, not an AI-powered diagnostic tool requiring human interpretation. The "study" focuses on the equivalence of the reprocessed hardware's performance.

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

The device itself is a transducer, a hardware component that, in conjunction with an oximeter system, acquires data. It's not an algorithm that operates "standalone" in the way AI algorithms are evaluated. The "performance" refers to the sensor's ability to accurately transmit patient-modified signals to the oximeter, and thus its accuracy in contributing to SpO2 and pulse rate determination. The evaluation would have been of the device in its intended use, effectively "standalone" from human interpretation of raw signals, but in conjunction with the oximeter system.

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

The summary mentions "comparative non-invasive Co-Oximetry and Oximetry data." This strongly suggests that Co-Oximetry (a more accurate, usually invasive, measurement of arterial oxygen saturation) was used as the ground truth for evaluating the accuracy of the reprocessed oxisensor in contributing to SpO2 determination.

8. The sample size for the training set

This information is not relevant or provided as there is no "training set" in the context of this traditional medical device (a reprocessed oximeter transducer). The device is not an AI algorithm that learns from data.

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

Not applicable, as there is no training set for this type of device.

Ask a specific question about this device