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The Nellcor Puritan Bennett KnightStar 335 is indicated for use in treating spontaneously breathing adult patients with obstructive sleep apnea or respiratory insufficiency in a homecare, hospital or institutional environment. In addition, when used with a Control Module Type 1 and an airway pressure monitor, it is indicated for use in treating spontaneously breathing adult patients with respiratory failure in a hospital or institutional environment.

The KnightStar 335 is a microprocessor-controlled flow generator capable or monitoring and controlling pressure within the patient tubing circuit. Three modes of operation are available: CPAP (continuous positive airway pressure), I/E PAP (inspiratory and expiratory positive airway pressure), A/C (assist with control).

The provided text is a 510(k) summary for the Nellcor Puritan Bennett KnightStar 335 ventilator. It establishes substantial equivalence to a predicate device and describes the device's features and intended use. However, it does not contain specific acceptance criteria or a detailed study proving the device meets such criteria.

The document explicitly states:

• "No additional performance testing was done inasmuch as the KnightStar 335 has not been physically changed since the 510(k), K942210 was cleared."
• "All applicable tests outlined in the November 1993 'Reviewer Guidance for Premarket Notification Submissions' have been performed on the KnightStar 335, as described in the original 510(k) submission. K942210."
• "Clinical studies have been performed, as described in the article 'Evaluation of the Puritan Bennett 335 Portable Pressure Support Ventilator: Comparison with the Respironics BiPAP S/T', included as Attachment 5. Although not an extensive study, it does demonstrate that both devices can be used to treat patients with respiratory failure."

Therefore, I cannot populate the requested table and answer the questions based solely on the provided text, as the detailed information about acceptance criteria, specific performance metrics, sample sizes, ground truth establishment, expert qualifications, adjudication, or MRMC studies for this device is not present in this 510(k) summary. The summary refers to an original 510(k) submission (K942210) and an attachment (Attachment 5) for the details of testing and clinical studies, which are not included here.

Based on the provided text, here is what can be inferred or explicitly stated, with the understanding that key details are missing:

1. Table of Acceptance Criteria and Reported Device Performance:

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

• The document mentions a clinical study in "Attachment 5" but does not provide details on the sample size or data provenance (e.g., country of origin, retrospective/prospective). It only states: "Although not an extensive study..."

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

• This information is not provided in the document.

4. Adjudication method for the test set:

• This information is not provided in the document.

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:

• This device is a ventilator, not an AI or imaging device that would typically involve "human readers" or "AI assistance" in the way implied by this question. Therefore, an MRMC study demonstrating human reader improvement with AI is not applicable to this device type based on the provided information.

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

• Similar to point 5, this question pertains to AI/algorithm performance. The KnightStar 335 is a microprocessor-controlled ventilator, and the concept of "standalone algorithm performance without human-in-the-loop" as applied to diagnostic algorithms is not directly relevant to its described function. Performance testing would be against engineering specifications and clinical outcomes, not an AI algorithm's diagnostic accuracy.

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

• The document implies clinical studies demonstrating that "both devices can be used to treat patients with respiratory failure." This suggests clinical outcomes data might have been part of the implicit "ground truth" for demonstrating efficacy, but specific details are not given.

8. The sample size for the training set:

• This information is not provided in the document and is not applicable in the context of traditional medical device testing as opposed to AI/machine learning model development.

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

• This information is not provided in the document and is not applicable in the context of traditional medical device testing as opposed to AI/machine learning model development.

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