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The Nihon Kohden NKV-440 Ventilator System is intended to provide continuous ventilation for adult, pediatric and neonatal patients who require invasive or noninvasive respiratory support. The NKV-440 offers mandatory and spontaneous ventilation modes as well as respiratory monitoring. The NKV-440 is intended for use in hospitals and hospital-type facilities, as well as, for in-hospital transportation.

The NKV-440 is a servo-controlled ventilator that is designed to meet the gas delivery and performance requirements for neonate through adult patients. The NKV-440 design is comprised of two major components, a Breath Delivery Unit (BDU) and a Graphic User Interface (GUI). The GUI allows clinicians to set ventilator control parameters such as PEEP and inspiratory pressure, to set alarm limits such as high inspiratory pressure alarm, to view monitored numeric values, and to view waveforms. The BDU assembly contains a blower and the electronics required to perform breath delivery. Ambient air is taken into the blower and mixed with oxygen which is flow rate controlled by a proportional valve. The mixed gas is provided to the patient. The microprocessor controls the blower and the proportional valve to deliver the pressure and oxygen concentration which are set by the user. It also provides various alarms and other design features to maximize patient safety.

The provided document is an FDA 510(k) premarket notification for the Nihon Kohden NKV-440 Ventilator System. It details the device's indications for use, technological characteristics, and comparison to a predicate device (Nihon Kohden NKV-550 Ventilator System).

The document does not include information about AI/ML algorithm performance, acceptance criteria for such algorithms, or studies involving human readers or ground truth established by experts for image analysis. Therefore, I cannot address most of the specific points requested regarding acceptance criteria and the study proving the device meets them, as it relates to AI/ML device performance.

This 510(k) pertains to a physical medical device (a ventilator), and its substantial equivalence is demonstrated through engineering performance testing against established standards and comparison of technical characteristics with a legally marketed predicate device.

However, I can extract the general acceptance criteria for this type of device based on the information provided:

Summary of Acceptance Criteria and Device Performance (Based on the provided document for a Ventilator):

Since this is a ventilator and not an AI/ML diagnostic tool, the "acceptance criteria" discussed are related to performance against established engineering and safety standards, and functional equivalence to a predicate device, rather than diagnostic accuracy metrics.

Regarding the points specific to AI/ML device studies, the document states "Not Applicable" for clinical and animal performance data, and does not mention any AI/ML components inherent to the device or its assessment.

Therefore, the following points cannot be answered from the provided text:

2. Sample sizes used for the test set and the data provenance: Not applicable, as this is not an AI/ML clinical study. Performance is demonstrated through engineering tests and comparison to a predicate device.
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 applicable.
4. Adjudication method (e.g. 2+1, 3+1, none) for the test set: Not applicable.
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.
6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done: Not applicable.
7. The type of ground truth used (expert consensus, pathology, outcomes data, etc.): Not applicable.
8. The sample size for the training set: Not applicable.
9. How the ground truth for the training set was established: Not applicable.

In conclusion, the supplied document describes the regulatory clearance for a conventional medical ventilator by demonstrating substantial equivalence to a predicate device through non-clinical performance data and adherence to recognized standards. It does not involve AI/ML technology or human reader studies.

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The Nihon Kohden NKV-330 Ventilator is intended to provide ventilation and oxygen concentration for patients who are breathing spontaneously but need partial ventilation support due to respiratory failure or chronic respiratory insufficiency. It is intended for children weighing 12.5 kg or greater to adult patients. It offers noninvasive ventilation, invasive ventilation, and respiratory monitoring. The NKV-330 is intended for use in hospital-type facilities, and in-hospital transportation by qualified and trained users under the directions of a physician.

The NKV-330 is a servo-controlled ventilator that is designed to meet the gas delivery and performance requirements for pediatric through adult patients. The NKV-330 design is comprised of two major components, a Breath Delivery Unit (BDU) and a Graphic User Interface (GUI). The GUI allows clinicians to set ventilator control parameters such as PEEP and inspiratory pressure, to set alarm limits such as high inspiratory pressure alarm, to view monitored numeric values, and to view waveforms. The BDU assembly contains a blower and the electronics required to perform breath delivery. Ambient air is taken into the blower and mixed with oxygen which is flow rate controlled by a proportional valve. The mixed gas is provided to the patient. The microprocessor controls the blower and the proportional valve to deliver the pressure and oxygen concentration which are set by the user. It also provides various alarms and other design features to maximize patient safety.

The provided document is a 510(k) summary for the Nihon Kohden NKV-330 Ventilator System. This type of submission focuses on demonstrating substantial equivalence to a legally marketed predicate device, rather than proving that a device meets specific acceptance criteria through a clinical study or detailed performance metrics.

Therefore, the document does not contain the specific acceptance criteria, reported device performance in those terms, details of a specific study proving it, sample sizes for test sets, data provenance, number of experts, adjudication methods, MRMC studies, standalone algorithm performance, or ground truth details as requested.

The document primarily states that the device's technical characteristics are "substantially equivalent" to a predicate device (Philips/Respironics V60 Ventilator) and lists various non-clinical performance data and standards compliance to support this claim. It explicitly states "Clinical performance data was not required to demonstrate substantial equivalence."

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The Nihon Kohden NKV-550 Series Ventilator System is intended to provide continuous ventilation for adult, pediatric and neonatal patients who require invasive or noninvasive respiratory support. The NKV-550 offers mandatory and spontaneous ventilation modes as well as respiratory monitoring. The NKV-550 is intended for use in hospitals and hospital-type facilities, as well as, for in-hospital transportation.

The Nihon Kohden NKV-550 Series Ventilator System consists of a graphic user interface (GUI) and a breath delivery unit (BDU). The GUI allows clinicians to set ventilator control parameters such as tidal volume and inspiratory pressure, to set alarm limits such as high inspiratory pressure alarm, to view monitored numeric values, to view waveform and loops, and to operate various features through the apps. The BDU contains a microprocessor that receives inputs from the electronic system and controls the pneumatic system for breath delivery to the patient. It also provides various alarms, a safety valve, and other design features to maximize patient safety.

This document, K192307, is a 510(k) premarket notification for a medical device (Nihon Kohden NKV-550 Series Ventilator System). It asserts substantial equivalence to a predicate device. As such, the FDA does not require a clinical study with human patients to demonstrate device performance against specific acceptance criteria for a new AI/ML algorithm. Instead, the focus is on demonstrating that the revised device meets the same performance and safety standards as the predicate device.

Therefore, the requested information about "acceptance criteria" and "study that proves the device meets the acceptance criteria" in the context of an AI/ML algorithm (including sample sizes, ground truth establishment, expert adjudication, MRMC studies, and standalone performance) is not applicable to this submission. This submission is for a ventilator, not an AI/ML diagnostic or therapeutic device.

The document discusses non-clinical performance data and states that clinical performance data was not required to demonstrate substantial equivalence.

Here's a breakdown of why the specific questions about an AI/ML study can't be answered from this document:

• 1. A table of acceptance criteria and the reported device performance: The document does not provide a table of performance acceptance criteria in the context of an AI/ML algorithm's output. It mentions "Met ISO 80601-2-12 requirements on essential performance of critical care ventilator," which refers to international safety and performance standards for ventilators, not an AI's diagnostic accuracy.
• 2. Sample sizes used for the test set and the data provenance: Not applicable. There is no AI/ML test set.
• 3. Number of experts used to establish the ground truth for the test set and the qualifications: Not applicable. There is no AI/ML ground truth establishment.
• 4. Adjudication method (e.g., 2+1, 3+1, none) for the test set: Not applicable.
• 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 is not an AI-assisted device.
• 6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done: Not applicable.
• 7. The type of ground truth used (expert consensus, pathology, outcomes data, etc.): Not applicable.
• 8. The sample size for the training set: Not applicable. There is no AI/ML training set.
• 9. How the ground truth for the training set was established: Not applicable.

What the document does provide regarding device performance:

The document states that the performance of the Nihon Kohden NKV-550 Series Ventilator System was demonstrated by various non-clinical tests performed in compliance with Design Controls:

• Software Verification
• Electrical Safety & EMC Testing
• Device Functionality Testing
• Performance of Therapy Types and Ventilation Modes
• Environmental Testing
• Cleaning & Disinfection
• Risk Management
• Accessory Compatibility
• Regression Testing

The key "performance" criterion mentioned is meeting ISO 80601-2-12 requirements on essential performance of critical care ventilators. This is a general safety and effectiveness standard for the device's physical and functional operation, not related to an AI's analytical accuracy.

In summary, this 510(k) submission is for a conventional medical device (a ventilator) with minor modifications, and as such, the detailed clinical study and AI/ML-specific acceptance criteria information requested is not part of this type of regulatory submission.

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The Nihon Kohden NKV-550 Series Ventilator System is intended to provide continuous ventilation for adult, pediatric and neonatal patients who require invasive or noninvasive respiratory support. The NKV-550 offers mandatory and spontaneous ventilation modes as well as respiratory monitoring. The NKV-550 is intended for use in hospitals and hospital-type facilities, as well as, for in-hospital transportation.

The Nihon Kohden NKV-550 Series Ventilator System consists of a graphic user interface (GUI) and a breath delivery unit (BDU). The GUI allows clinicians to set ventilator control parameters such as tidal volume and inspiratory pressure, to set alarm limits such as high inspiratory pressure alarm, to view monitored numeric values, to view waveform and loops, and to operate various features through the apps.

The BDU contains a microprocessor that receives inputs from the electronic system and controls the pneumatic system for breath delivery to the patient. It also provides various alarms, a safety valve, and other design features.

The Nihon Kohden NKV-550 Series Ventilator System's acceptance criteria and the study proving it meets these criteria are described below.

1. Table of Acceptance Criteria and Reported Device Performance

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

The document does not explicitly state a "test set" in the context of clinical data for performance evaluation. Instead, the performance was demonstrated through non-clinical testing against various standards and comparisons to a predicate device. Therefore, a specific sample size for a test set of patient data is not applicable here as clinical performance data was not required for substantial equivalence.

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

Not applicable, as clinical performance data was not required, and thus, no ground truth established by experts on patient data was utilized for the device's clearance. The "ground truth" for the non-clinical testing was established by the requirements and thresholds set by the relevant international standards (e.g., ISO 80601-2-12, ANSI AAMI ES60601-1, etc.).

4. Adjudication method for the test set:

Not applicable, as clinical performance data and expert-established ground truth were not used for the device's clearance.

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 a ventilator system, not an AI-assisted diagnostic or interpretation tool that would involve human readers or MRMC studies.

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

The device's performance was evaluated in a standalone manner by testing against established international standards. The listed "Summary of Non-Clinical Performance Data" includes:

• Software Verification
• Electrical Safety & EMC Testing
• Agency Testing to Applicable Standards
• Device Functionality Testing
• Performance of Therapy Types and Ventilation Modes
• Product Endurance
• Power Performance
• Environmental
• Cleaning & Disinfection
• Gas Path Biocompatibility
• Human Factors/Usability Testing
• Risk Management
• Waveform Comparison with Predicate
• Accessory Compatibility

These tests assess the device's intrinsic functions and compliance with safety and performance requirements, which can be considered standalone performance.

7. The type of ground truth used:

For the non-clinical performance evaluation, the "ground truth" was derived from:

• International Standards: e.g., ISO 80601-2-12 (essential performance of critical care ventilators), ANSI AAMI ES60601-1 (general requirements for basic safety and essential performance), IEC 60601-1-2 (electromagnetic compatibility), IEC 60601-1-6 (usability), IEC 60601-1-8 (alarm systems), IEC 62133 (batteries), ISO 80601-2-55 (respiratory gas monitor), ISO 10993-1 (biological evaluation), ISO 18562-1 to 3 (biocompatibility of breathing gas pathways).
• Predicate Device Characteristics: The Nihon Kohden NKV-550 Series Ventilator System was compared to the predicate device (Draeger Evita Infinity V500) based on its documented technical characteristics and performance, aiming for substantial equivalence.

8. The sample size for the training set:

Not applicable, as this device does not appear to involve machine learning or AI models that would require a training set of data. Its performance is based on engineering design and meeting pre-defined physical and functional specifications.

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

Not applicable, as there is no mention of a training set or machine learning components in the provided documentation.

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