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The LNCS Sensors are indicated for the continuous nonitoring of functional oxygen saturation of arterial hemoglobin (SpO2) and pulse rate (measured by an SpO2 sensor) for use with adult, pediatric, infant, and neonatal patients during both no motion and motion conditions, and for patients who are well or poorly perfused in hospital-type facilities, mobile, and home environments.

The LNCS Oximetry Sensors are to be reprocessed. They are fully compatible disposable sensors for use with Masimo SET and Masimo SET compatible pulse oximeter monitors. The LNCS Oximety Sensors are also compatible with Nellcor compatible pulse oximeter monitors. There is no change in the sensor design or performance. The only change is that the sensors are to be reprocessed and subjected to ethylene oxide (EO) sterilization, and are to be supplied as sterile sensors by Masimo.

The provided document is a 510(k) summary for the Masimo LNCS Oximetry Sensors. It focuses on the substantial equivalence of reprocessed and sterilized sensors to previously cleared sensors. Therefore, the information typically found in acceptance criteria and detailed study reports for new device performance (like specific accuracy metrics, sample sizes for test/training sets, expert qualifications, etc.) is not present in this summary.

Here's a breakdown of what can be extracted based on the request, and what cannot:

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

• Acceptance Criteria: Not explicitly stated in terms of specific performance metrics (e.g., accuracy, precision errors for SpO2). The primary acceptance criterion here is "substantial equivalence" to previously cleared predicate devices. This means the reprocessed sensors must perform at least as well as the original, non-reprocessed sensors.
• Reported Device Performance: The document only states: "The results of the performance data demonstrate that the LNCS Oximetery Sensors, after reprocessed and sterilized are as safe and effective as the legally marketed predicate devices." No specific numerical performance values (e.g., SpO2 accuracy, pulse rate accuracy) are 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)

• Sample Size for Test Set: Not specified.
• Data Provenance: The testing was "in-house and laboratory validation testing." No information on country of origin or whether it was retrospective or prospective is provided.

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)

• Number of Experts: Not applicable/not specified. For oximetry sensors, ground truth typically comes from a reference device (e.g., CO-oximeter for SpO2) rather than expert consensus on images.
• Qualifications of Experts: Not applicable/not specified.

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

• Adjudication Method: Not applicable/not specified. Oximetry sensor performance is typically evaluated against reference instruments, not expert adjudication in the way image analysis algorithms are.

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

• MRMC Study: No. This device is an oximetry sensor, not an AI-powered diagnostic tool requiring human reader studies.

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

• Standalone Performance: Not applicable in the context of an "algorithm only" device, as this is a physical sensor. The "performance data" mentioned would be for the sensor itself.

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

• Type of Ground Truth: Not explicitly stated in this summary. For oximetry devices, ground truth for SpO2 accuracy is typically established using a reference CO-oximeter with arterial blood samples. The document refers to "in-house and laboratory validation testing," which would imply such rigorous reference methods.

8. The sample size for the training set

• Sample Size for Training Set: Not applicable. This device is a sensor, not an AI/ML algorithm that requires a training set.

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

• Ground Truth for Training Set: Not applicable.

Summary of available information as per request:

This 510(k) summary is for a device modification (reprocessing and sterilization) of an existing device type, not a new technology introduction. Therefore, the focus is on demonstrating that the reprocessing and sterilization do not negatively impact the established performance and safety of the device, rather than establishing original performance criteria from scratch. Detailed performance metrics and study designs, if required, would typically be found in the full 510(k) submission, not necessarily in the public summary.

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This sensor is indicated for use in continuous noninvasive arterial oxygen saturation and pulse rate monitoring.

The devices are reprocessed Low Noise Cabled Sensors (LNCS)® Series - Adult, Pediatric, and Infant SpO2 adhesive sensors. The sensors are disposable devices used for continuous noninvasive arterial oxygen saturation and pulse rate monitoring.

The provided document states that the Reprocessed Pulse Oximeter Sensors have identical indications for use, technological characteristics, design, materials, and intended use as the predicate devices. Therefore, the acceptance criteria are implicitly that the reprocessed devices perform as "originally intended" by the manufacturer of the predicate devices. The study conducted to prove this involved bench and laboratory testing.

Here's a breakdown of the requested information:

1. Table of Acceptance Criteria and Reported Device Performance

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

• Sample Size: Not explicitly stated. The document refers to "bench and laboratory testing" and "each individual Pulse Oximeter Sensor is tested," suggesting that a robust testing protocol was followed but does not provide specific numbers for the test set.
• Data Provenance: Not explicitly stated. The document does not mention the country of origin of data or whether it was retrospective or prospective. It describes general testing conducted by the applicant, Ascent Healthcare Solutions.

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

• Number of Experts: Not applicable. The "ground truth" here is the performance specifications of the original, new device. The testing conducted by Ascent Healthcare Solutions was to verify that the reprocessed devices meet these pre-defined specifications through direct measurement and physical/chemical analysis, not through expert interpretation of clinical data on the reprocessed devices themselves.
• Qualifications of Experts: Not applicable, for the reasons above.

4. Adjudication Method for the Test Set

• Adjudication Method: Not applicable. The testing described is objective, physical, and chemical in nature, designed to confirm that the reprocessed devices meet established performance parameters. There is no subjective interpretation requiring an adjudication process.

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

• MRMC Study: No, an MRMC comparative effectiveness study was not done. The device is a reprocessed medical device, and the evaluation focused on its functional equivalence to the original device through bench and laboratory testing.

6. If a Standalone (i.e., algorithm only without human-in-the-loop performance) Was Done

• Standalone Performance: Not applicable. This device is a physical medical sensor, not an algorithm. The performance evaluation is of the sensor itself.

7. The Type of Ground Truth Used

• Type of Ground Truth: The ground truth for the reprocessed sensors is the performance specifications and characteristics of the original, new predicate devices (Masimo LNCS and SPO2.COM Sensors). The objective was to demonstrate that the reprocessed devices continue to meet these original manufacturer specifications after reprocessing.

8. The Sample Size for the Training Set

• Sample Size for Training Set: Not applicable. This is not an AI/ML algorithm that requires a "training set." The device is a reprocessed physical medical device.

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

• Ground Truth for Training Set Establishment: Not applicable, as there is no training set for this type of device.

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