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The Nellcor OxiMax Pulse Oximetry Sensors, models MAX-A, MAX-AL, MAX-N, MAX-P, MAX-I and MAX-FAST are indicated for single patient use when continuous noninvasive arterial oxygen saturation and pulse rate monitoring are required for patients in the sizes indicated in the respective sensor directions for use.

Nellcor OxiMax Pulse Oximetry Sensors, models MAX-AL, MAX-AL, MAX-P, MAX-I and MAX-FAST are designed for continuous, non-invasive monitoring of functional oxygen saturation of arterial hemoglobin (SpO2) and pulse rate in conjunction with a Nellcor pulse oximeter. Nellcor OxiMax Pulse Oximetry Sensors, models MAX-A, MAX-AL, MAX-N, MAX-P, MAX-I and MAX-FAST are intended for prescription use with adult, pediatric and neonatal patients in hospitals, hospital-type facilities, intra-hospital transport, and home environments.

These OxiMax sensors each contain a memory chip carrying information about the sensor which the oximeter needs for correct operation including sensor model, Advanced Signal Evaluation, and data set revision. The memory chip is also cable of storing including in-sensor data when connected to an OxiMax-capable monitor, and lot code.

Here's a breakdown of the acceptance criteria and study information for the Nellcor OxiMax Pulse Oximetry Sensors, based on the provided text:

Nellcor OxiMax Pulse Oximetry Sensors: Acceptance Criteria and Study Information

1. Table of Acceptance Criteria and Reported Device Performance

Important Note: The provided text is a 510(k) summary, which often provides a high-level overview. Detailed performance data and specific acceptance criteria (e.g., ARMS values for SpO2 accuracy) are typically found in the full 510(k) submission, not always in the public summary. The summary confirms that studies were performed to support accuracy specifications, but doesn't report the specific numerical values of these specifications or the device's performance against them.

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

• Sample Size: Not explicitly stated in the provided text. The document mentions "Clinical tests were performed" and "Clinical studies were conducted" but does not specify the number of subjects or data points in the test set.
• Data Provenance: Not explicitly stated. The document confirms that clinical studies were conducted, implying human subject data collection, but does not specify the country of origin or whether it was retrospective or prospective. Given the context of a 510(k) submission for new sensors, it is highly probable these were prospective clinical studies conducted specifically for this submission.

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

• This information is not provided in the given text. For pulse oximetry, the "ground truth" for SpO2 accuracy is typically established by comparing the device's readings to arterial blood gas (ABG) measurements or co-oximetry, not usually by human expert consensus on the device's output itself. Therefore, the concept of "experts establishing ground truth for the test set" in the context of reader evaluation isn't directly applicable here. The experts involved would more likely be the clinicians performing the ABG measurements or managing the study, and their qualifications are not detailed.

4. Adjudication Method for the Test Set

• This information is not provided in the given text. Adjudication methods (like 2+1 or 3+1) are typically used when multiple human readers interpret data (e.g., medical images) to establish a consensus ground truth. For pulse oximetry, the direct comparison to ABG/co-oximetry as a reference standard eliminates the need for such adjudication of the device's output.

5. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study

• No, an MRMC comparative effectiveness study was not done as described in the provided text. MRMC studies are designed to assess the impact of an AI algorithm on human reader performance, usually in diagnostic tasks involving interpretation of visual data. Pulse oximetry is a direct measurement device; its performance is evaluated against a reference standard (like ABG), not by how it assists human readers in interpreting its output.

6. Standalone (Algorithm Only) Performance

• Yes, standalone performance was done. The entire premise of pulse oximetry testing for regulatory approval is to establish the accuracy of the device's (algorithm's) measurements of SpO2 and pulse rate against a
  reference standard (typically arterial blood gas/co-oximetry). The statement "Clinical tests were performed to support accuracy specifications for SpO2 performance" directly refers to evaluating the device's intrinsic measurement capabilities. The device processes electrical information "by use of an algorithm to provide real time values of SpO2, pulse rate and pulse amplitude," indicating a standalone algorithmic evaluation.

7. Type of Ground Truth Used

• The type of ground truth used is physiological reference data, specifically arterial blood oxygen saturation (SaO2) and heart rate measurements, likely obtained through arterial blood gas (ABG) analysis or co-oximetry. While not explicitly named, this is the universally accepted gold standard for determining the accuracy of pulse oximeters. The text states "Clinical tests were performed to support accuracy specifications for SpO2 performance," which implies comparison to a highly accurate and independent measure of arterial oxygen saturation.

8. Sample Size for the Training Set

• This information is not provided in the given text. For pulse oximetry devices, "training set" doesn't apply in the same way it would for a machine learning model that learns from large datasets. Instead, the device's algorithm is developed and refined based on engineering principles, physiological models, and data collected during R&D. If the "data set revision" mentioned in the memory chip refers to an internal algorithm update, the data used for its development (not necessarily a distinct "training set" in the ML sense) is not specified. The summary focuses on the clinical validation of the device's performance.

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

• This information is not applicable/provided in the traditional sense of a "training set" for a machine learning model. The pulse oximetry algorithm relies on empirical relationships between light absorption and blood oxygenation. The ground truth for developing and refining such an algorithm would have been established through extensive physiological studies, often involving human subjects under controlled desaturation protocols, where arterial blood samples (co-oximetry) provide the reference standard. However, the summary does not detail the specific methods or data used during the initial algorithm development or "training." It focuses on the validation of the final device.

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