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The CareGuide™ Oximeter is intended for use as an adjunct, non-invasive monitor of the hemoglobin oxygen saturation of microvascular blood in a region of skeletal muscle tissue beneath the sensor. The sensor may be positioned on pigmented skin. The CareGuide displays the most recent value of SmO2, as well as a graphical trend of previous SmO2 measurements. The CareGuide System should not be used as the sole basis for diagnosis or therapy. Note: The prospective clinical value of data from the CareGuide™ Oximeter has not been demonstrated in disease states.

The CareGuide sensor uses Near Infrared Spectroscopy (NIRS) to calculate muscle oxygen saturation (SmO2). The CareGuide Display is an all-in-one touch screen off-the-shelf computer. The display contains the user interface software, the algorithms that calculate SmQ2 from collected spectra, displays the current SmO2 result and trends previous results. The CareGuide reusable sensor contains the optical and electronic elements necessary to collect spectra from skin, fat and muscle. The sensor has a 3m long cord with a USB connection to the CareGuide display. The sensor contains 3 major components: (1) light sources to illuminate the skin; (2) a spectroscopic detector to analyze the reflected spectra back from the subject and (3) a microprocessor to control the optical components. The CareGuide Ray is a disposable sleeve which isolates the sensor optical elements from the patient's skin.

The provided text describes the CareGuide™ Oximeter, an oximeter that uses Near Infrared Spectroscopy (NIRS) to calculate muscle oxygen saturation (SmO2). The submission aims to demonstrate substantial equivalence to predicate devices. However, the document does not contain specific acceptance criteria for performance metrics (such as accuracy, sensitivity, or specificity) or a detailed study proving the device meets these criteria with quantitative results.

Therefore, I cannot fulfill all parts of your request as the information is not present in the provided text. I will provide what can be extracted.

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

The document does not explicitly state quantitative acceptance criteria or detailed reported device performance in a numerical format that would typically be found in a performance study. It broadly states: "The test results in this submission demonstrate that the CareGuide Oximeter meets the expected performance requirements for an Oximeter, and is therefore equivalent to the predicates relative to safety and mechanical properties."

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

• Test Set Sample Size: Not specified.
• Data Provenance:
  • An "isolated perfused animal limb GLP study" for accuracy against a laboratory co-oximeter. The location is not specified, but GLP (Good Laboratory Practice) implies a controlled environment.
  • A "clinical environment" study for the ability to measure tissue oxygen saturation in subjects with different skin color (pigmentation). The location and other details are not specified.

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)

Not specified. The ground truth for the animal study was a "laboratory co-oximeter." For the clinical environment study, how the ground truth for pigment measurement was established is not detailed.

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

Not specified. The document does not describe any adjudication process for establishing ground truth or evaluating device performance.

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 oximeter, not an AI-assisted diagnostic imaging device that involves human readers.

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

Yes, implicitly. The studies mentioned (animal, clinical environment) appear to evaluate the device's (including its algorithms) performance in measuring SmO2 directly, without a human-in-the-loop component for interpretation or assistance that would be typical in AI-assisted diagnosis.

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

• For accuracy: "laboratory co-oximeter" (considered a gold reference standard).
• For skin color study: Not explicitly stated, but implies a measure of tissue oxygen saturation from the device compared to a reference or evaluated for consistency across different skin pigmentations.

8. The sample size for the training set

Not applicable. The device described uses NIRS technology and algorithms; it is not presented as a machine learning system requiring a distinct "training set" in the common sense of AI models. The algorithms are likely based on biophysical models of light absorption and scattering.

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

Not applicable, as there is no mention of a training set for machine learning.

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