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The Neonatal ConchaSmart Breathing Circuits are intended for neonatal and infant patients in professional healthcare environments as a conduit for respiratory gas between a patient and a ventilator or Infant Flow Generator (for single limb configuration) and include heated wire(s) for use with the Hudson RCI Neptune Heated Humidifier. The heated wires are intended to aid in maintaining the set patient temperature and minimize condensation in the ventilator tubing.

The Neonatal ConchaSmart Breathing Circuits are intended for neonatal and infant patients in professional healthcare environments as a conduit for respiratory gas between a patient and a ventilator or Infant Flow Generator (for single limb configuration) and includes heated wire(s) for use with the Hudson RCI Neptune Heated Humidifier. The heated wires are intended to aid in maintaining the set patient temperature and minimize condensation in the ventilator tubing.

These devices are made of corrugated tubing (10mm in diameter), which houses the heated wires and are kitted with various adaptors and connectors to aid the respiratory care clinician in system configuration. In general these heated wire circuits are connected to both a ventilator and a Hudson RCI Neptune Heated Humidifier. The single limb configuration is compatible with the CareFusion Infant Flow system.

All Neonatal ConchaSmart Breathing Circuits have a useful life of 21 days. Neonatal ConchaSmart Breathing Circuits are sold non-sterile.

The provided text describes a 510(k) premarket notification for a medical device, the "Neonatal ConchaSmart Breathing Circuits." The submission aims to demonstrate substantial equivalence to legally marketed predicate devices. The document details the device's indications for use, technological characteristics, and performance data from non-clinical testing.

However, the information provided focuses on the physical and functional performance of the breathing circuits themselves, rather than an AI/ML-driven device's performance measured against acceptance criteria in a clinical or image-based diagnostic setting. Specifically, it does not contain the following information typically found in an AI/ML device submission for establishing acceptance criteria and proving performance:

• A table of acceptance criteria for AI/ML performance metrics (e.g., sensitivity, specificity, AUC) and reported device performance against these.
• Sample sizes for test sets in an AI/ML context (e.g., number of images, patient cases).
• Data provenance (country of origin, retrospective/prospective) for an AI/ML test set.
• Number of experts and their qualifications for establishing ground truth for an AI/ML test set.
• Adjudication methods for AI/ML ground truth.
• Multi-reader multi-case (MRMC) comparative effectiveness study details (effect size of human reader improvement with AI assistance).
• Standalone performance (algorithm only without human-in-the-loop) for an AI/ML device.
• Type of ground truth used (e.g., expert consensus, pathology, outcomes data) for an AI/ML device.
• Sample size for AI/ML training set.
• How ground truth for the AI/ML training set was established.

The document discusses engineering acceptance criteria related to standards for breathing circuits (e.g., resistance to flow, compliance, leakage, useful life, electrical safety, biocompatibility) and confirms that the device passed these tests. It indicates the device functions as intended with a specific humidifier.

Therefore, I cannot extract the requested information as the document describes a traditional medical device (breathing circuits) and not an AI/ML medical device where such acceptance criteria and study designs (related to AI model performance, human-in-the-loop studies, ground truth establishment for AI) would be relevant.

The acceptance criteria and study described in the document are limited to the physical and functional aspects of a non-AI/ML medical device.

The closest information provided related to "acceptance criteria" and "study proving it meets criteria" is:

Acceptance Criteria (Extrapolated from "Test Objective" and ISO Standards):

Study Proving Device Meets Acceptance Criteria:

The study involved a series of non-clinical, laboratory-based tests.

1. Sample Size Used for Test Set and Data Provenance: The document does not specify a "sample size" in terms of number of patient cases or images, as it is not an AI/ML study. It refers to testing "the proposed devices," implying physical units of the Neonatal ConchaSmart Breathing Circuits. The tests were performed in a lab setting, not using human data/patients, so "provenance" in the sense of country of origin or retrospective/prospective is not applicable.
2. Number of Experts and Qualifications for Ground Truth: Not applicable for this type of device where laboratory measurements against international standards establish "truth."
3. Adjudication Method: Not applicable. Lab testing against defined physical and electrical parameters.
4. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study: Not applicable. This is for AI/ML devices involving human readers.
5. Standalone Performance: Not applicable in the context of an AI/ML algorithm. The device performance itself is evaluated (e.g., its resistance to flow, electrical safety, etc.).
6. Type of Ground Truth Used: The "ground truth" here is adherence to specified parameters and performance limits defined by international standards (e.g., ISO 5367, IEC 60601-1, ISO 8185, ISO 5356-1, ISO 10993) and the manufacturer's design verification testing for compatibility and durability.
7. Sample Size for Training Set & How Ground Truth for Training Set was Established: Not applicable, as this is not an AI/ML device relying on a "training set" of data.

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