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The bellavista 1000 ventilator is intended to provide positive pressure ventilator support to adults and pediatrics (IBW greater than 6 kg).

Environment of use: hospitals, sub-acute care facilities and intra-hospital transfer

It is intended for use by qualified, trained personnel under the direction of a physician.

The bellavista 1000 ventilator (hereafter referred to as "bellavista") is designed for continuous ventilation of adult and pediatric patients.

The bellavista ventilator is a positive pressure ventilator for intubated patients and patients with mask ventilation. Its pneumatic power is provided by an internal turbine. Supplemental oxygen is provided by an auxiliary oxygen source.

The following modes of ventilation are available

• Adults: CPAP, PCV, P-A/C, PC-SIMV, PSV, S, S/T, T, beLevel, APRV, VCV, ● V-A/C, VC-SIMV.
• Pediatrics the following modes of ventilation are available: CPAP, PCV, P-A/C, ● PC-SIMV, S, T, beLevel, APRV, VCV, V-A/C, VC-SIMV

The provided text is a 510(k) Premarket Notification from the FDA for a medical device called the "bellavista 1000" ventilator. It is a letter confirming the device's substantial equivalence to legally marketed predicate devices.

Crucially, this document does NOT describe the acceptance criteria and study that proves the device meets the acceptance criteria in the way you are asking.

The 510(k) process for substantial equivalence (SE) reviews a new device against a predicate device. It demonstrates that the new device is as safe and effective as a legally marketed device, not that it independently "meets acceptance criteria" through clinical trials for novel devices.

Therefore, many of the specific points you requested (e.g., sample size for test set, data provenance, number of experts for ground truth, adjudication method, MRMC study, standalone performance, type of ground truth, training set information) are not applicable to this type of regulatory submission because clinical performance studies, as you've outlined, are generally not required for a 510(k) unless significant differences or new questions of safety/effectiveness arise.

The document states:

• "No clinical testing was conducted or required in support of this premarket notification." (Page 17)
• The comparison is primarily against a predicate device (HAMILTON-C2, K121225) and some reference devices (HAMILTON-G5, COVIDIEN-PB 840, DRAEGER-Oxylog 3000 plus).

Instead of clinical study data, the document relies on:

• Performance Testing:
  • Tests according to IEC 60601-1:2005+A1:2012, IEC 60601-1-2:2007, ISO 80601-2-12:2011, IEC 60601-1-8:2006+A1:2012, ISO 80601-2-55:2011.
  • Reliability testing as described in ASTM F1100-90.
  • Validation testing with "wide range of System Acceptance Tests (SAT)".
  • Biocompatibility testing according to ISO 10993-1, with certain scientific methodologies within ISO 18562-3.
• Comparison of Technical Specifications: Detailed tables comparing settings, alarms, monitoring parameters, and accuracy controls with the predicate device.
• Usability: Summative usability tests performed with a user group of respiratory therapists.

Given this, I will answer the applicable parts of your request based on the provided document and clarify why other points are not present.

Acceptance Criteria and Device Performance (Based on Substantial Equivalence to Predicate)

The "acceptance criteria" in this context are primarily demonstrating equivalence to the predicate device (HAMILTON-C2, K121225) and compliance with relevant performance standards. The "reported device performance" is presented through detailed comparisons.

1. Table of Acceptance Criteria and Reported Device Performance

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

• Sample Size: Not applicable. This is a 510(k) premarket notification relying on technical specifications and performance testing against standards and a predicate device, not a clinical study with patient samples.
• Data Provenance: The document does not specify the country of origin for the internal testing data, but the submitter is IMTMEDICAL AG, Switzerland. The testing is non-clinical (laboratory/bench testing) rather than retrospective or prospective patient data.

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

• Not Applicable. Ground truth in the context of clinical expert consensus would be relevant for devices involving image interpretation or diagnosis. For a ventilator, "ground truth" for performance is established through internationally recognized performance standards (e.g., ISO, IEC, ASTM) and physical measurements using test lungs and calibrated sensors.
• The usability testing was conducted with a user group reported as "respiratory therapists," but no number or detailed qualifications are provided.

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

• Not Applicable. This is a method used in clinical studies, particularly for diagnostic devices where subjective interpretation (e.g., by radiologists) needs consensus. It does not apply to the technical performance testing of a ventilator.

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

• No. An MRMC study is a type of clinical study for diagnostic devices, especially those using AI, to assess the impact of AI on human reader performance. This document concerns a ventilator, which is a therapeutic device, and explicitly states "No clinical testing was conducted or required."

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

• Yes, in spirit, for certain aspects. The performance testing (e.g., accuracy of controls, alarm limits, monitoring parameters) represents the "standalone" or "algorithm only" performance of the ventilator's internal systems against engineering specifications and international standards. This is not "AI algorithm only" but "device functionality only." The document does not detail specific "algorithms" for AI, as this is a traditional ventilator.

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

• The "ground truth" for the device's technical performance is the relevant international performance standards (e.g., IEC, ISO, ASTM) and the measured performance of the legally marketed predicate device. These standards define acceptable ranges for parameters like accuracy, flow, pressure, etc.

8. The sample size for the training set

• Not Applicable. This is a traditional medical device (ventilator). The document does not describe the use of machine learning or AI models requiring a "training set" of data. Its design and validation rely on engineering principles, known predicate device performance, and adherence to established standards.

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

• Not Applicable. See point 8.

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The HAMILTON-C3 ventilator is intended to provide positive pressure ventilatory support to adults and optionally infants and neonates.

Intended areas of use:

· In the intensive care ward, intermediate care ward, emergency ward, long term acute care hospital or in the recovery room

· During transfer of ventilated patients within the hospital

The HAMILTON-C3 ventilator is a medical device intended for use by qualified, trained personnel under the direction of a physician and within the limits of its stated technical specifications.

The HAMILTON-C3 is designed for adult, paediatric, infant, and neonatal patients requiring invasive or noninvasive ventilation support. It covers a full range of clinical requirements, including invasive ventilation, automated ventilation with Adaptive Support Ventilation (ASV), and noninvasive ventilation.

The 510(k) submission intends to add the following new features to the previously cleared ventilator HAMILTON-C3:

• The following two new ventilation modes for adult / pediatric patient group: ● (S)CMV and SIMV
• SpO2 monitoring option

This section describes the acceptance criteria and the study proving the device meets those criteria, based on the provided text.

1. Table of acceptance criteria and reported device performance:

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

The provided text focuses on device performance testing against regulatory standards and software validation. It mentions "waveform performance testing" for the new ventilation modes. However, it does not specify the sample size for any test sets used in performance testing, nor does it detail the data provenance (e.g., country of origin, retrospective/prospective nature of data).

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):

This information is not provided in the document. The testing described is primarily technical compliance and performance against established engineering standards and validated software functionality, rather than a clinical study requiring expert ground truth for interpretation of outcomes.

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

This information is not provided. The text describes bench testing and software validation, not a study design involving adjudication of human interpretations.

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:

A multi-reader multi-case (MRMC) comparative effectiveness study was not mentioned in the provided text. The device is a ventilator, and the testing described is related to its technical performance and safety, not a diagnostic or interpretive AI system that human readers would use.

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

The document describes "Software Design and Validation" processes, "bench testing of the device," and "waveform performance testing" for the new ventilation modes. These types of tests are inherently "standalone" in that they evaluate the device's algorithmic and mechanical performance directly against engineering specifications and expected outputs, without direct human intervention as part of the core performance measurement, other than operating the test equipment. So, yes, standalone algorithm performance was assessed though not explicitly called out as such.

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

The "ground truth" for the device's technical performance and safety is derived from the international and national standards and guidelines listed (e.g., ANSI/AAMI ES60601-1, IEC 60601-1-2, ISO 80601-2-12). For the new ventilation modes, "waveform performance testing" was conducted, implying that the ground truth for correct operation were the expected waveform characteristics and parameters as defined by the ventilator's design specifications and the algorithms derived from the predicate HAMILTON-G5.

8. The sample size for the training set:

A "training set" is typically associated with machine learning or artificial intelligence models. As this document describes a medical device (ventilator) and its compliance with technical standards and software validation, there is no mention of a training set in the context of machine learning. The "training" for such a device would refer to its design, development, and engineering phases.

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

Since there is no mention of a training set in the context of machine learning, this question is not applicable. The "ground truth" for the device's design and functionality is established through engineering principles, medical device regulatory requirements, and the functionalities of predicate devices.

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The IntelliCuff device is intended to continuously measure and automatically maintain the userset cuff pressure of an endotracheal tube (ETT) or tracheostomy tube (TT) during mechanical ventilation.

The device can be used with any mechanical ventilator, as follows:

• . When used with a non-Hamilton Medical ventilator, IntelliCuff adjusts the cuff pressure to values set on the device.
• When used with a Hamilton Medical ventilator, IntelliCuff adjusts the cuff pressure to values set either on the device or on the ventilator, depending on configuration.

The device is to be used during ventilation of adults, pediatrics, and neonates, who are intubated with ETT or TT, in the following areas:

• In the intensive care ward or in the recovery room ●
• In the operation room during intubation narcosis
• For emergency medical care or primary care ●
• During transport within and outside of the hospital
• . During transfer by rescue vehicles, ship, jet, or helicopter

The IntelliCuff device continuously measures and automatically maintains cuff pressure during mechanical ventilation of adults, pediatrics, and neonates using a cuffed endotracheal tube or tracheostomy tube. It is an integrated and continuous cuff pressure control solution that secures airway management in intensive care units, operating rooms, and during interhospital transport.

When the IntelliCuff device is connected to a Hamilton Medical ventilator, cuff pressure settings can be manually adjusted by either selecting the appropriate values on the ventilator or the cuff pressure controller.

It is designed for immediate use; no calibration or maintenance is required. It operates in the recommended range of desired cuff pressures for various cuffed endotracheal tubes to provide suitable solutions for various clinical patient situations. For inflation, room air is used and no contact to the respiratory gas system of a patient occurs. A large-scale display and convenient and intuitive interaction buttons maximize safe use and visibility of all important data.

The associated accessories include:

• Cuff Pressure Tube with Filter
• Device Mount Solution ●
• USB Power Supply and Car Adapter

The provided text is a 510(k) Summary for the IntelliCuff device, which is an automatic cuff pressure controller for endotracheal and tracheostomy tubes. Unfortunately, the document does not contain a specific study demonstrating acceptance criteria for device performance as it does not report quantitative performance metrics against specific acceptance thresholds.

The document primarily focuses on demonstrating substantial equivalence to a predicate device through:

• Technological characteristics comparison: Showing that the IntelliCuff shares the same fundamental technological elements with predicate devices (e.g., inflation/deflation, user-controlled set pressure, software control, alarm system).
• Compliance with regulatory standards: Reporting that the device has undergone various electrical safety, electromagnetic compatibility (EMC), mechanical, and software verification and validation testing in accordance with relevant IEC and RTCA standards. These tests confirm the device's safety and functionality within its intended environment.
• Human Factors/Usability Study: Indicating conformance with FDA guidance for optimizing medical device design.

While these are crucial aspects of device clearance, they do not provide quantitative acceptance criteria for the device's primary function (continuously measuring and automatically maintaining cuff pressure) and the results of a study against those criteria. Such data would typically involve metrics like accuracy of pressure measurement, stability of pressure maintenance, response time to pressure deviations, etc., along with predefined acceptable ranges.

Therefore, I cannot fulfill all parts of your request with the information provided. The document states that "The test results show that the device has adequate performance for its intended use" and "the IntelliCuff device was found to have an adequate performance profile that is similar to the predicate devices" but does not quantify this performance or explicitly state acceptance criteria.

Here's a breakdown of what can be extracted from the provided text, and what cannot:

1. Table of Acceptance Criteria and Reported Device Performance:

• Cannot be created. The document mentions compliance with general safety and performance standards (e.g., IEC 60601-1, IEC 60601-1-2, RTCA/DO 160G) but does not provide specific, quantitative acceptance criteria for cuff pressure measurement or maintenance, nor does it report specific performance values against such criteria. It states that "The test results show that the device has adequate performance for its intended use" but without specific metrics.

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

• Not specified for performance testing. The document mentions "Electrical safety and EMC testing," "Mechanical testing," "Software Verification and Validation Testing," and a "Human Factors / Usability Study." While these involve testing, the sample size (e.g., number of devices tested, number of simulated or actual cases) for these tests is not given. The "data provenance" (country of origin, retrospective/prospective) is also not detailed for any specific performance study, as no such study with quantitative performance metrics is described.

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

• Not specified. This information would typically be relevant for studies involving human assessment or interpretation (e.g., image-based diagnostics, clinical outcomes). Since the IntelliCuff is a mechanical/electronic device for pressure control, the concept of "ground truth established by experts" in this context is not directly applicable to its core performance testing as described. For a human factors study, experts (usability engineers, clinicians) might be involved, but their number and qualifications are not listed.

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

• Not applicable/Not specified. Adjudication methods are typically used in studies involving subjective interpretation of data (e.g., by human readers). This type of method is not described for the performance testing of the IntelliCuff device.

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:

• No such study was performed/described. MRMC studies are used for evaluating diagnostic aids, often involving AI, where human readers interpret cases with and without the aid. The IntelliCuff device is an automated pressure controller, not a diagnostic aid for human interpretation, so an MRMC study is not relevant to its function and was not reported.

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

• Implied, but not explicitly detailed. The various compliance tests (electrical safety, EMC, mechanical, software V&V) are essentially standalone tests of the device's functionality and safety. The entire document describes the device (the algorithm and hardware) as a standalone system for continuous pressure maintenance. However, specific standalone performance metrics for things like pressure accuracy or response time are not given in the summary.

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

• Not explicitly stated for core performance, but implied by standards. For compliance with standards like IEC 60601-1 (safety) or RTCA/DO 160G (mechanical), the "ground truth" would be the specified limits and test methodologies defined by those standards. For software verification and validation, the "ground truth" would be the documented software requirements. For a human factors study, the "ground truth" relates to usability objectives and error rates, often compared against benchmarks or user feedback. However, for direct performance metrics like pressure accuracy, the "ground truth" would typically come from highly accurate reference measurement equipment. This is not detailed in the summary.

8. The sample size for the training set:

• Not applicable. The IntelliCuff device is described as a cuff pressure controller. The provided text does not indicate that it uses machine learning or AI models that require a "training set" in the conventional sense (e.g., for image recognition or predictive analytics). Its functionality appears to be based on control system algorithms rather than learned models.

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

• Not applicable. As no training set is mentioned or implied for a machine learning model, this question is not relevant based on the provided text.

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