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The JETi™ Hydrodynamic Thrombectomy System is intended to remove/aspirate fluid and break-up soft emboli and thrombus from the peripheral vasculature, including deep vein thrombosis (DVT), and to sub-selectively infuse/deliver diagnostics or therapeutics with or without vessel occlusion.

The JETi™ Hydrodynamic Thrombectomy System (JETi HTS) is a hydro-mechanical aspiration system intended for the removal of intravascular thrombus. The system is comprised of the JETi™ Catheter, JETi™ Pump Set, JETi™ Saline Drive Unit (SDU), JETi™ Accessory Cart, JETi™ Suction Tubing, and JETi™ Non-sterile Canister Set. The JETi Hydrodynamic Thrombectomy System is designed to continuously aspirate thrombotic material into the JETi Catheter, where a high-pressure stream of saline within the catheter tip macerates the thrombus as it is aspirated.

Here's an analysis of the provided text, focusing on acceptance criteria and the supporting study, structured as requested:

1. Table of Acceptance Criteria and Reported Device Performance

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The JETiTM Hydrodynamic Thrombectomy System is intended to remove/aspirate fluid and thrombus from the peripheral vasculature and to sub-selectively infuse/deliver diagnostics with or without vessel occlusion.

The JETiTM Hydrodynamic Thrombectomy System is a hydro-mechanical aspiration system intended for the removal of intravascular thrombus. The system is comprised of the JETiTM Catheter, JETiTM Pump Set, JETiTM Saline Drive Unit (SDU), JETiTM Accessory Cart, JETiTM Suction Tubing, and JETiTM Non-sterile Canister Set. The JETi Hydrodynamic Thrombectomy System is designed to continuously aspirate thrombotic material into the JETi Catheter, where a high-pressure stream of saline within the catheter tip macerates the thrombus as it is aspirated.

The JETi Catheter has two (2) lumens. The primary lumen (largest) is a conduit for thrombus aspiration. A secondary lumen, placed within the primary lumen, delivers saline through an orifice to break up and dilute the aspirated thrombus and facilitates rapid movement of the aspirate towards the vacuum. One (1) radiopaque (RO) marker band is located stiff proximal section which transitions to a more flexible distal section with a round, soft tip. A filter is incorporated into the catheter connector to ensure that no debris or foreign material is injected into the patient vasculature. The JETi Catheter is available in two sizes: 6 French size (6F) and 8 French size (8F). The JETi Pump Set is intended to deliver a high pressure sterile saline stream to the JETi Catheter. The pressure for the saline stream is created through the cassette's piston assembly, which snaps into the SDU.

The JETi Saline Drive Unit (SDU) is a non-sterile reusable, (multiple patient, multiple use) device that incorporates the saline pumping components and the vacuum pump within a single enclosure. The fork drive of the SDU is designed to run the JETi Pump Set piston assembly to deliver a stream of saline to the JETi Catheter when activated by the handheld switch if the vacuum is present. In conjunction with the JETi Pump Set, the SDU can sub selectively infuse / deliver diagnostics or therapeutic fluids when utilizing the optional HYPER PULSETM Fluid Delivery feature. The JETi Suction Tubing is a sterile single use device that incorporates the pressure monitoring sensor and valve into a single enclosure, that is in-line with the aspiration lumen, for the handheld switch. When the handheld switch is activated, within the aspiration lumen, the diluted thrombus and saline is then drawn back through the primary lumen of the JETi Catheter and deposited into the vacuum source (JETi Non-sterile Canister Set) via the JETi Suction Tubing. When the handheld switch is de-activated, a valve closes, stopping the flow of thrombus, and a relief valve inside the SDU briefly opens and closes to reduce foaming at the vacuum source (JETi Non-sterile Canister Set). The SDU contains a microprocessor-controller circuit board and firmware that monitors various functions of the motor and vacuum to ensure that the device is functioning as expected. A Liquid Crystal Display (LCD) screen on the front panel of the SDU indicates to the user the status of the system. Several safety features are incorporated into the firmware to ensure proper functionality. The SDU is supported by a mobile, height adjustable cart with an integrated IV pole. Energy is provided by a 24-volt external power supply, which is connected to the main supply. The external power supply is provided with the SDU and is part of the system

The provided text is a 510(k) summary for the JETi™ Hydrodynamic Thrombectomy System, which is a medical device for removing thrombus from peripheral vasculature. This document focuses on demonstrating substantial equivalence to a predicate device, rather than reporting on a study that proves the device meets specific acceptance criteria in terms of clinical performance or diagnostic accuracy. Therefore, information regarding acceptance criteria for clinical performance, sample sizes for test/training sets, expert qualifications, ground truth establishment, or multi-reader multi-case studies are not available in this document.

The document primarily details the device's technical specifications and compares them to predicate devices to establish substantial equivalence for regulatory clearance. It also mentions non-clinical testing for areas like packaging, human factors, and electromagnetic compatibility (EMC).

Here's a breakdown of the information that is available based on your request:

1. Table of Acceptance Criteria and Reported Device Performance:

The document does not provide a formal table of clinical acceptance criteria and device performance as would be seen in a study evaluating diagnostic accuracy or clinical outcomes. Instead, it focuses on non-clinical testing and substantial equivalence to a predicate device.

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

• Not Applicable / Not Provided for clinical performance. The document explicitly states "No clinical testing is provided in this pre-market notification."
• For non-clinical testing:
  • Packaging Validation: The sample size is not specified, but the data provenance would be internal Abbott testing.
  • Human Factors Evaluation: The sample size (number of users) is not specified, but the data provenance would be from the human factors study conducted by Abbott.
  • EMC Testing: The sample size is not specified (typically one or a few devices tested), and the data provenance would be from laboratory testing conforming to IEC standards.

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

• Not Applicable / Not Provided. This information is relevant for clinical studies involving expert interpretation for ground truth, which were not part of this submission.

4. Adjudication method for the test set:

• Not Applicable / Not Provided. This information is relevant for clinical studies that involve multiple readers and potentially discrepancies in their assessments for ground truth, which were not part of this submission.

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. The document explicitly states "No clinical testing is provided in this pre-market notification." This device is a physical thrombectomy system, not an AI-assisted diagnostic or treatment planning tool for which MRMC studies would typically be conducted.

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

• Not Applicable. This is a physical medical device, not an algorithm, so "standalone" performance in the context of an algorithm is not relevant.

7. The type of ground truth used:

• Not Applicable / Not Provided for clinical performance. For the non-clinical tests mentioned:
  • Packaging Validation: Ground truth is based on established ASTM standards and internal product specifications.
  • Human Factors Evaluation: Ground truth relates to adherence to human factors principles and user understanding, evaluated through methods like usability testing.
  • EMC Testing: Ground truth is defined by the limits and methodologies specified in the IEC 60601-1-2 standard.

8. The sample size for the training set:

• Not Applicable / Not Provided. This device is not an AI/ML algorithm that would typically use a "training set."

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

• Not Applicable / Not Provided. As this is not an AI/ML algorithm requiring a training set, the concept of establishing ground truth for a training set does not apply.

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The PAL® Infiltration System is indicated for the purpose of aesthetic body contouring.

The MicroAire® Power Assisted Liposuction (PAL®) Infiltration System is a medical device intended for aesthetic body contouring. The PAL Infiltration System is a stand-alone peristaltic Infiltration Pump, with the ability to control ON/OFF function to the PAL Handpiece (sold separately), the Infiltration Pump, or a Foot Switch (INF-FOOT-1) depending on the doctor's preference.

The PAL® Infiltration System is comprised of the following components that are subject to this 510K:

• INF-PUMP PAL Infiltration Pump
• Accessories
  • o PAL-INF-1600 Infiltration Tubing
  • o PAL-INF-XXXXX Single-Use Infiltration Cannulas
  • o PAL-INF-RXXXXX Multi-Use Infiltration Cannula
  • o INF-CBL-5020, Infiltration Pump to 5020 Console Connector Cable
  • o INF-FOOT-1, Infiltration Foot Switch

The provided document is a 510(k) Pre-Market Notification for a medical device (MicroAire PAL Infiltration System). This type of submission focuses on demonstrating "substantial equivalence" to a legally marketed predicate device, rather than proving novel safety and effectiveness through clinical trials or performance studies with acceptance criteria in the typical sense of AI/algorithm performance.

Therefore, the requested information regarding acceptance criteria, study design for proving device performance (especially related to AI/algorithms), sample sizes for test/training sets, expert ground truth establishment, MRMC studies, or standalone algorithm performance, is not applicable to this type of regulatory submission.

The document describes engineering and biocompatibility testing, primarily against established standards, to demonstrate that the new device performs similarly and is as safe as its predicate. It does not involve AI, image analysis, or diagnostic/prognostic output that would require the typical performance study elements you've listed.

Here's a breakdown based on the document's content, explaining why your specific questions are not directly answerable in this context:

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

• Not Applicable in the AI/algorithmic sense. The "acceptance criteria" here are met through demonstrating compliance with recognized standards (e.g., ISO 10993 for biocompatibility, IEC 60601 for electrical safety) and internal specifications for functional parameters (e.g., flow rate). The document states: "Results confirm that the design inputs and performance specifications for the device are met. The PAL Infiltration System passed the testing in accordance with internal requirements, national standards, and international standards shown below, supporting its safety and effectiveness, and its substantial equivalence to the predicate device."
• Reported Performance (Functional, not diagnostic):
  • Infiltration Pump Flow Rate: "meets internal specifications" (No specific numerical target or range is given in the public summary, only that it passed).
  • Biocompatibility: Passed Cytotoxicity, Sensitization, Irritation, Pyrogenicity, Acute Systemic Toxicity per ISO 10993-5, -10, -11, and USP .
  • Electrical Safety: Passed per IEC 60601-1.
  • Electromagnetic Disturbance (EMD) testing: Passed per IEC 60601-1-2.
  • Transportation Testing: "Demonstrates package integrity maintained" per ASTM D4169.

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

• Not Applicable. This device is a mechanical pump and associated cannulas/tubing. Performance testing refers to engineering tests on a limited number of manufactured units or materials, not a "test set" of patient data for an algorithm. There is no patient data involved in these performance tests.

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

• Not Applicable. No "ground truth" in the clinical/interpretive sense is established as there's no AI or diagnostic component.

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

• Not Applicable. No clinical/interpretive test set or adjudication is relevant here.

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. This is not an AI device.

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

• Not Applicable. No ground truth for clinical outcomes in this context. Performance is measured against engineering specifications and international standards.

8. The sample size for the training set:

• Not Applicable. No training set, as there is no AI/machine learning component.

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

• Not Applicable. No training set or associated ground truth.

In summary: The provided document is a direct FDA 510(k) submission that demonstrates substantial equivalence for a physical medical device (an infiltration pump) through engineering and biocompatibility testing against established standards, not through AI/algorithm performance studies or clinical trials involving patient data analysis. Your questions are tailored for AI/ML device submissions, which is a different regulatory pathway and type of evidence.

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The A8, A9 Anesthesia System is a device used to administer to a patient, continuously or intermittently, a general inhalation anesthetic and to maintain a patient's ventilation.

The A8, A9 is intended for use by licensed clinicians in the administration of general anesthesia, for patients requiring anesthesia within a health care facility, and can be used in adult, pediatric and neonate populations.

High Flow Nasal Cannula (HFNC) is indicated for delivery of nasal high flow oxygen to spontaneously breathing adult patients. It can be used for pre-oxygenation and short-term supplemental oxygenation (up to 10 minutes) during intubation in operating rooms. It is not intended for apneic ventilation. HFNC is indicated for use in adults only.

The A8, A9 Anesthesia System is a continuous flow inhalation gas anesthesia system that delivers anesthetic vapor and provides for automatic and manual modes of ventilation. The A8, A9 Anesthesia System incorporates O2, CO2, N2O and Agent concentration monitoring (Desflurane, Isoflurane, Halothane, and Sevoflurane). The A8, A9 Anesthesia System is a modified version the previously cleared Mindray A7 Anesthesia System cleared in K171292.

The provided text describes the 510(k) premarket notification for the Mindray A8, A9 Anesthesia System, focusing on demonstrating substantial equivalence to predicate devices rather than proving the device meets specific acceptance criteria based on studies involving human readers or AI performance metrics.

Therefore, most of the information requested in your prompt (acceptance criteria table with performance, sample size for test set, data provenance, number of experts for ground truth, adjudication method, MRMC study, standalone performance, training set size, and ground truth establishment for training set) is not available in this document.

The document details engineering tests and conformance to standards, which are different from clinical performance studies for AI/radiology devices.

Here's a breakdown of what is available and what is not:

Information Found in the Document:

• Device Name: A8, A9 Anesthesia System
• Predicate Devices: K171292 (A7 Anesthesia System), K192972 (BeneVision N Series Patient Monitors). Reference devices also listed.
• Technological Differences from Predicate:
  • Change the Vaporizer Type and the addition of Electronic Vaporizers (A9)
  • Change certain parameters of the ventilator modes
  • Addition of the High Flow Nasal Cannula Oxygen (HFNC)
  • Change the Anesthetic Gas Module and Accessories
  • Addition of the Sealed Lead Acid Battery
• Performance Data (Type of Studies Conducted):
  • Functional and System Level Testing (bench testing) to validate performance and ensure specifications are met.
  • Biocompatibility Testing (conformance to ISO standards: 10993-1, -5, -10, -18, 18562-1, -2, -3)
  • Software Verification and Validation Testing (following FDA's "Guidance for the Content of Premarket Submissions for Software Contained in Medical Devices")
  • Electromagnetic Compatibility and Electrical Safety (conformance to IEC and ANSI/AAMI standards: ES60601-1, IEC 60601-1-6, -1-8, ISO 80601-2-13, -2-55, IEC 60601-1-2)
  • Bench Testing (conformance to ASTM and ISO standards: F1101-90, IEC 60601-1-6, -1-8, ISO 5360, 10079-3, 80601-2-13, -2-55)

Information NOT Found in the Document (and why):

This document is for an Anesthesia System, which is a hardware medical device with integrated software for control and monitoring. It is not an AI-driven image analysis or diagnostic device that would typically involve acceptance criteria related to human reader performance, expert ground truth, or MRMC studies. The "performance data" section focuses on testing the device's functional specifications, safety, and compliance with general medical device standards.

1. A table of acceptance criteria and the reported device performance: Not provided in the format of performance metrics against specific acceptance thresholds for diagnostic accuracy, sensitivity, specificity, etc. The document generally states that "the devices continue to meet specifications and the performance of the device is equivalent to the predicate" based on functional and system-level testing, and compliance with standards. Key technical characteristics are compared in a large table, but this is a comparison to the predicate, not a list of acceptance criteria with measured performance against them.
2. Sample sized used for the test set and the data provenance: Not applicable in the context of this type of device submission. The "test set" here refers to the actual physical devices undergoing bench and functional testing, not a dataset of patient images or clinical cases.
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 this context would be engineering specifications and validated measurement techniques, not expert clinical interpretation.
4. Adjudication method: Not applicable.
5. If a multi-reader multi-case (MRMC) comparative effectiveness study was done: No. This type of study is for evaluating diagnostic performance, typically for imaging devices or AI algorithms assisting human readers.
6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done: Not applicable. This device is an anesthesia system, not a standalone AI algorithm for diagnosis.
7. The type of ground truth used: For this device, ground truth is established by engineering design specifications, international and national consensus standards (e.g., ISO, IEC, ASTM), and validated measurement instruments.
8. The sample size for the training set: Not applicable for this type of device. There is no "training set" in the machine learning sense described. Software validation ensures the embedded software performs as designed and specified for controlling the anesthesia system.
9. How the ground truth for the training set was established: Not applicable.

In summary, the provided document describes a regulatory submission for an anesthesia system, which relies on demonstrating safety and efficacy through engineering testing and adherence to established performance standards for medical devices, rather than AI model validation studies common for diagnostic algorithms.

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The A7 Anesthesia System is a device used to administer to a patient, continuously or intermittently, a general inhalation anesthetic and to maintain a patient's ventilation.

The A7 is intended for use by licensed clinicians, for patients requiring anesthesia within a health care facility, and can be used in adult and pediatric (including neonate, infant, child and adolescent) populations.

The A7 Anesthesia System is a continuous flow inhalation gas anesthesia system that delivers anesthetic vapor and provides for automatic and manual modes of ventilation. The A7 incorporates 02, CO2, N2O and Agent concentration monitoring (Desflurane, Isoflurane, Enflurane, Sevoflurane and Halothane).

This document refers to the Mindray A7 Anesthesia System (K171292). It outlines its indications for use, device description, and a comparison to a predicate device (K151954), along with reference devices, to demonstrate substantial equivalence.

Here's an analysis of the acceptance criteria and study information based on the provided text:

Summary of Acceptance Criteria and Reported Device Performance

The acceptance criteria for the Mindray A7 Anesthesia System are implicitly derived from its comparison to a predicate device (also an A7 Anesthesia System, K151954) and several reference devices. The core principle is "substantial equivalence," meaning the new device performs at least as well as, or comparably to, the established devices.

The table below summarizes the key technical characteristics and their reported performance/specifications for both the subject device and its direct predicate. Since the document states "The functional and system level testing showed that the device continues to meet specifications and the performance of the device is equivalent to the predicate," the performance of the subject device is presented as matching the predicate.

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AnapnoGuard 100 Respiratory Guard System is intended for airway management by oral/nasal intubation while providing continuous endotracheal cuff pressure control using non-invasive measurement and monitoring of carbon dioxide concentration in the subglottic space and evacuation of secretions from above the endotracheal tube's cuff.

AnapnoGuard 100 Respiratory Guard System is comprised of the following three main components: The AnapnoGuard endotracheal tube (ETT) with inflatable cuff (FDA cleared under K093126). The AnapnoGuard 100 Respiratory Guard System interconnection harness of tubes, connecting the ETT to the AnapnoGuard 100 control unit The AnapnoGuard 100 Respiratory Guard System control unit which consists of the following main modules: Host computer (PC) Microcontroller (MCU) Suction module (regulator and flow potency meter): including . a set of valves and pipes controlling the secretions suction/evacuation from above the ETT cuff. Rinsing module: Pumps saline to rinse the Suction and Vent/ ● CO2 lumens. CO2 analyzer module: including CO2 analyzer assembly, ● pump, valve and flow filter which sucks air from the subglottic space above the ETT cuff into the CO2 analyzer. . Cuff pressure module: includes two pressure gauges which monitor cuff pressure, a miniature air pump and two valves. Pneumatic module: valves, pipes and filters . Connectors panel for connecting the interconnection harness . (ETT), vacuum, trap bottle, rinsing fluid and filters. Operation buttons panel and navigation wheel . I/O communication panel . Display monitor . AnapnoGuard 100 Respiratory Guard System, including its three components monitors leak between the endotracheal tube's cuff and the trachea by measuring the Carbon Dioxide levels in the subglottic area above the cuff through a dedicated lumen in the endotracheal tube. Detection of a high level of Carbon Dioxide is an objective indicator for a leak (improper sealing of the trachea by the endotracheal tube cuff). The system continuously monitors and adjusts the cuff pressure to prevent a leak at minimum possible pressure (all within pressure limits preset by the user). Preventing a leak reduces the likelihood of aspiration of secretions from the upper airways into the lungs and increases the likelihood for no loss of ventilation and delivery of anesthetic and nebulized drugs into the lungs. Keeping the cuff pressure as low as possible reduces the mechanical pressure of the cuff on the tracheal tissue throughout the intubation period. The system also performs evacuation of secretions from above the endotracheal tube's cuff through a dedicated lumen at the dorsal side of the endotracheal tube.

Here's an analysis of the acceptance criteria and the study that proves the device meets them, based on the provided text:

Acceptance Criteria and Device Performance

The document describes several performance criteria derived from a comparison with predicate devices and specific performance bench tests. The clinical study primarily focuses on the effectiveness of the AnapnoGuard 100 Respiratory Guard System in optimizing cuff pressure and reducing CO2 leakage.

Table 1: Acceptance Criteria and Reported Device Performance

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The A7 Anesthesia System is a device used to administer to a patient, continuously or intermittently, a general inhalation anesthetic and to maintain a patient's ventilation.

The A7 is intended for use by licensed clinicians, for patients requiring anesthesia within a health care facility, and can be used in adult and pediatric populations.

The A7 Anesthesia System is a continuous flow inhalation gas anesthesia system that delivers anesthetic vapor and provides for automatic and manual modes of ventilation. The A7 incorporates O2, CO2, N2O and Agent concentration monitoring (Desflurane, Isoflurane, Enflurane, Sevoflurane and Halothane). The A7 consists of a main unit (includes an anesthetic ventilator and flow meter monitor assembly) and a detachable breathing system.

This document is a 510(k) premarket notification for the Mindray A7 Anesthesia System and primarily focuses on establishing substantial equivalence to a predicate device (K142552). It does not contain specific acceptance criteria for a study demonstrating performance, nor does it detail a standalone study or an MRMC comparative effectiveness study for a new AI feature.

The submission revolves around a modification to an existing A7 Anesthesia System (K142552) to include a "Fresh Gas Flow Optimizer feature." The key point is that "This feature does not change the fresh gas flow setting nor does it supply an alarm if the user does not follow the recommended fresh gas flow setting." This implies the feature is advisory and doesn't directly control the device's critical functions in a way that would necessitate extensive clinical performance studies for efficacy or safety.

Therefore, many of the requested details about acceptance criteria, study design, ground truth, and expert involvement are not present because the submission's purpose is to demonstrate equivalence of a modified, non-critical feature, rather than proving the performance of a new diagnostic or AI system.

However, based on the provided text, I can extract information related to general performance testing and the comparison between the subject device and its predicate.

Here's a breakdown of the available information:

1. Table of Acceptance Criteria and Reported Device Performance:

The document doesn't provide a typical "acceptance criteria" table with specific thresholds for a novel diagnostic or AI performance. Instead, it presents a technical comparison table between the subject A7 Anesthesia System and its predicate (K142552), demonstrating that their technical characteristics are largely identical or equivalent. The "performance data" section mentions compliance with various standards, which serve as the implicit acceptance criteria for the device's safety and fundamental operational performance.

2. Sample Size Used for the Test Set and Data Provenance:

• Sample Size: Not applicable. This document refers to the validation of a physical medical device and its embedded software, not a diagnostic algorithm or AI system. The testing is based on engineering verification and validation against specified standards and product specifications.
• Data Provenance: Not applicable. The "study" here is a technical validation against engineering specifications and industry standards, not a clinical data collection study for a diagnostic algorithm.

3. Number of Experts Used to Establish Ground Truth for the Test Set and Their Qualifications:

• Number of Experts: Not applicable. This relates to the device's engineering performance and compliance with standards, not expert-adjudicated ground truth from clinical images or data.
• Qualifications of Experts: Not applicable.

4. Adjudication Method for the Test Set:

• Adjudication Method: Not applicable. This concept applies to expert review of clinical cases rather than engineering testing. Performance data refers to objective measurements against specifications and standards.

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study was done:

• MRMC Study: No, an MRMC comparative effectiveness study was not done. The new feature ("Fresh Gas Flow Optimizer") is described as providing a "recommended value" to assist clinicians but "does not change the fresh gas flow setting nor does it supply an alarm if the user does not follow the recommended fresh gas flow setting." This indicates it's an informational, non-critical, non-diagnostic feature that wouldn't typically warrant an MRMC study for improved reader performance.

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

• Standalone Study: No, a standalone study for an AI algorithm's performance was not explicitly done or reported in this document in the typical sense. The "Fresh Gas Flow Optimizer" is an embedded software feature, and its performance would have been verified as part of the overall software validation (mentioned in section 4: "Software – The A7 Anesthesia System software has been fully verified and validated..."). However, there are no specific performance metrics like sensitivity/specificity for a standalone algorithm presented.

7. The Type of Ground Truth Used:

• Type of Ground Truth: For the device's overall performance, the "ground truth" consists of established engineering specifications, performance tolerances (e.g., accuracy for gas measurements), and compliance requirements of recognized medical device standards (e.g., ANSI/AAMI ES60601-1, IEC 60601-2-13, ISO 80601-2-55, IEC 62304).

8. The Sample Size for the Training Set:

• Sample Size for Training Set: Not applicable. The device's software is "verified and validated" but not described as a machine learning or AI model trained on a dataset. The "Fresh Gas Flow Optimizer" likely uses predefined algorithms and parameters based on physiology and anesthesia principles, rather than learning from a "training set."

9. How the Ground Truth for the Training Set was Established:

• Ground Truth for Training Set: Not applicable, as there is no mention of a machine learning "training set" or corresponding ground truth in the context of this 510(k) submission. For the device itself, as stated in point 7, the "ground truth" is defined by engineering specifications and industry standards.

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The A7 Anesthesia System is a device used to administer to a patient, continuously or intermittently, a general inhalation anesthetic and to maintain a patient's ventilation.

The A7 is intended for use by licensed clinicians, for patients requiring anesthesia within a health care facility, and can be used in adult and pediatric populations.

The A7 Anesthesia System is a continuous flow inhalation gas anesthesia system that delivers anesthetic vapor and provides for automatic and manual modes of ventilation. The A7 incorporates 02, CO2, N2O and Agent concentration monitoring (Desflurane, Isoflurane, Enflurane, Sevoflurane and Halothane). The A7 consists of a main unit (includes an anesthetic ventilator and flow meter monitor assembly) and a detachable breathing system.

The provided document is a 510(k) premarket notification for a medical device, the A7 Anesthesia System. It aims to demonstrate substantial equivalence to legally marketed predicate devices, rather than proving that the device meets specific acceptance criteria through a clinical study involving experts and ground truth as might be expected for an AI/ML device.

Therefore, much of the requested information (like sample size for test sets, number of experts for ground truth, adjudication methods, MRMC studies, standalone performance, training set size, and how training set ground truth was established) is not applicable or available in this type of document, as it describes a traditional medical device and its performance is validated through engineering and safety standards, not AI-centric clinical studies.

However, I can extract information related to "acceptance criteria" in the context of this device's regulatory pathway, and the "study" (testing) that proves it meets these criteria, which are primarily engineering standards and performance specifications.

Here's the breakdown of what can be extracted:

1. Table of Acceptance Criteria and Reported Device Performance

For an anesthesia system, "acceptance criteria" are typically defined by recognized consensus standards for safety and performance, and the "reported device performance" demonstrates adherence to these standards and documented specifications. The document provides a detailed comparison to a predicate device, which implicitly defines performance targets.

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

• Sample Size: Not applicable. For this type of device, "testing" refers to verification and validation against engineering specifications and standards, often conducted in a laboratory or simulated environment, not a clinical "test set" in the sense of patient data.
• Data Provenance: Not applicable. The testing described is functional and safety testing to standards, not based on 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 device performance is established by metrology, engineering specifications, and adherence to recognized standards, not by expert consensus on patient data.

4. Adjudication method for the test set

• Not applicable. There is no "adjudication method" in the sense of reconciling disagreements among experts for a clinical dataset. Device performance is objectively measured against predefined engineering and safety criteria.

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 anesthesia system, not an AI/ML-powered diagnostic or assistive tool for human readers. Therefore, an MRMC study is irrelevant.

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

• Not applicable. This device is a traditional medical apparatus, not an algorithm, and is designed for human operation within a clinical workflow.

7. The type of ground truth used

• Engineering specifications and recognized consensus standards. The device's "performance data" describes compliance with several IEC, ISO, ASTM, and CGA standards (e.g., IEC 60601 series for safety and essential performance, ISO 14971 for risk management, ISO 5356-1 for connectors, ISO 21647 for respiratory gas monitors, ASTM F1101-90 for ventilators, etc.). Biocompatibility testing (ISO 10993 series) also constitutes a "ground truth" for material safety.

8. The sample size for the training set

• Not applicable. This device is not an AI/ML system that requires a "training set" of data.

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

• Not applicable. As it's not an AI/ML system, there is no training set or ground truth established for one.

Summary of Acceptance Criteria and Proving Compliance for this Device:

The "acceptance criteria" for the A7 Anesthesia System are primarily defined by:

1. Safety and Performance Standards: The device must meet the requirements of a comprehensive list of international and national standards (e.g., IEC 60601 series, ISO 10993 series, ISO 14971, ASTM F1101, etc.).
2. Functional Specifications: The device must perform according to its design specifications (e.g., flow ranges, accuracy of gas monitoring, alarm functionalities, ventilation modes, etc.) as demonstrated through comparison with a legally marketed predicate device (the A5 Anesthesia System).
3. Biocompatibility: Materials in patient or gas path contact must comply with ISO 10993 requirements.
4. Software Validation: The software must be fully verified and validated in accordance with FDA guidance.

The "study that proves the device meets the acceptance criteria" consists of:

• Biocompatibility Testing: Conducted per ISO 10993-1, 5, 10, and 18 for cytotoxicity, irritation, sensitization, and volatile organic compound testing.
• Software Verification and Validation: Documentation provided to FDA in accordance with relevant guidance.
• Performance Testing: Demonstrated compliance with its product specifications and intended use by adhering to the listed standards (e.g., IEC 60601-1, IEC 60601-2-13, ISO 21647, etc.). This involves engineering tests, measurements, and simulations to confirm that the device's functional characteristics match its design and meet the safety and performance requirements set by the standards and predicate device's established performance.
• Substantial Equivalence Comparison: A detailed technical comparison to the predicate A5 Anesthesia Delivery System (K123211) showing that any differences do not raise new questions of safety or effectiveness. The comparison table explicitly lists how the A7's performance metrics align with or, in some cases (like individual gas flow accuracy), improve upon the predicate's. New features (Fresh Gas Control System, Negative Pressure Suction Device, Agent Consumption Calculation, Auxiliary Common Gas Outlet, Sample Gas Return, Quick Release APL Valve, Auxiliary Work Surface) were also subjected to performance testing to ensure safety and effectiveness.

In essence, for this type of traditional medical device, "acceptance criteria fulfillment" is a demonstration of engineering rigor, adherence to recognized safety and performance standards, and functional equivalence (or justifiable differences) to a predicate device, rather than a clinical trial with patient data interpreted by experts.

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The Naväge Nose Cleaner is intended to help relieve nasal and/or sinus congestion and stuffiness by washing and moisturizing the nasal cavity with a pressure-controlled stream of irrigant rinse.

The Naväge Nose Cleaner ("Naväge") is a powered nasal irrigator intended for OTC use to wash and moisturize the nasal cavity. There are many nasal irrigation devices in commercial distribution in the US, and Naväge is substantially identical to those devices in terms of intended use and indications for use. It is similar in terms of mechanical functionality with the single exception that in addition to using positive pressure, Naväge simultaneously uses negative pressure (suction). That is, the device uses a combination of positive pressure (gravity) to introduce irrigant rinse into the nasal cavity, and negative pressure (powered suction) to aspirate the rinse out of the nasal cavity. The simultaneous use of positive and negative pressure makes it possible for the device to be self-contained so that after washing through the nasal cavity, the irrigant rinse can flow into a removable collection tank attached to the device. This provides an improved nasal irrigation experience resulting from functional simplicity, superior ergonomics, and less mess than currently available devices.

The provided text describes the Naväge Nose Cleaner and its substantial equivalence to predicate devices, focusing on its functional characteristics rather than clinical performance or AI integration. Therefore, many of the requested categories related to acceptance criteria, study design for AI models, ground truth, and expert evaluation are not directly available in this document.

However, I can extract information related to the device's performance specifications and the studies conducted to demonstrate substantial equivalence for certain aspects.

Acceptance Criteria and Reported Device Performance

The document does not explicitly state "acceptance criteria" in the typical sense of a pre-defined threshold for clinical efficacy but rather performance specifications for mechanical operation and demonstrations of equivalence for usability and safety.

Study Details

The document refers to studies conducted to demonstrate substantial equivalence, but it does not detail the methodology for all of them.

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

   • Flow Rate and Pressure Performance Data: No specific sample size or data provenance (country of origin, retrospective/prospective) is provided for the "Performance testing data for flow rate of irrigant and pressure." This likely refers to engineering bench testing rather than human subject data.
   • Comprehension Study: No specific sample size or data provenance is provided for the "comprehension study of the subject device's Instructions for Use."

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts: Not applicable. The performance testing appears to be objective mechanical measurements, not dependent on expert ground truth in a clinical sense. The comprehension study likely involved consumer participants rather than experts establishing a "ground truth."

4. Adjudication method (e.g. 2+1, 3+1, none) for the test set: Not applicable based on the information provided.

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 physical medical device (nasal irrigator), not an AI diagnostic or assistive technology.

6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done: Not applicable. This device is not an algorithm or AI system.

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

   • For flow rate and pressure: The "ground truth" would be the objective measurements obtained from laboratory equipment.
   • For biocompatibility: Compliance with ISO 10993 parts 5 and 10 constitutes the basis for determining biocompatibility.
   • For electrical safety: Compliance with IEC-60601-1 constitutes the basis for determining electrical safety.
   • For consumer comprehension: The "ground truth" would likely be the scores or performance on consumer comprehension tasks.

8. The sample size for the training set: Not applicable. The device is not an AI model requiring a training set.

9. How the ground truth for the training set was established: Not applicable.

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The Epix® Suction Irrigation System is intended as a general purpose suction and/or irrigation device for use in laparoscopic and open general surgery, laparoscopic and open gynecological surgery, and laparoscopic and open urologic surgery. This device delivers sterile irrigant solution and serves as a conduit for suction.

The Epix Irrigation Pump (model C7000) is reusable and operates outside of the sterile field. The Epix Suction Irrigation Tubing Set (model C7100) is a sterile, single use device, used in conjunction with the Epix Irrigation Pump and the house vacuum to deliver sterile irrigation fluids and to evacuate blood, tissue debris, and smoke from the surgical site.

Here's a breakdown of the acceptance criteria and study information for the Epix® Suction Irrigation System, based on the provided 510(k) summary:

This device is a suction irrigator, not an AI/ML powered device. As such, many of the typical categories for AI/ML device studies (such as MRMC studies, training set details, or ground truth establishment for a diagnostic algorithm) are not applicable. The study predominantly focuses on benchtop performance testing to demonstrate substantial equivalence to a predicate device.

1. Table of Acceptance Criteria and Reported Device Performance

The 510(k) summary doesn't explicitly state quantitative acceptance criteria with numerical targets for each test. Instead, the "acceptance criteria" are implied to be that the subject device performs comparably to the predicate device in the specified functional tests, demonstrating substantial equivalence. The reported device performance is that these tests confirmed substantial equivalence.

2. Sample Size Used for the Test Set and Data Provenance

The summary describes "bench top tests" where "the devices were tested side-by-side." It does not specify a numerical sample size (e.g., number of devices tested, number of trials). The data provenance is a laboratory setting from Applied Medical Resources Corporation. This is a prospective test, as the protocol was created specifically to confirm substantial equivalence.

3. Number of Experts Used to Establish the Ground Truth for the Test Set and Qualifications of Those Experts

Not applicable. This is a functional performance test for a physical device, not an AI/ML diagnostic device requiring expert ground truth for classification or interpretation.

4. Adjudication Method for the Test Set

Not applicable. This is a functional performance test for a physical 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

Not applicable. This is not an AI/ML device, and no MRMC study was conducted.

6. If a Standalone (i.e. algorithm only without human-in-the loop performance) Was Done

Not applicable. This is not an AI/ML device. The "standalone" test refers to the device's functional performance in a laboratory setting, as described in the benchtop tests.

7. The Type of Ground Truth Used

The "ground truth" for this type of device is the expected physical and functional performance according to engineering and safety standards (e.g., IEC 60601-1, ISO 10993, ISO 10079-3) and by comparison to the established performance of the predicate device.

8. The Sample Size for the Training Set

Not applicable. This is not an AI/ML device that requires a training set.

9. How the Ground Truth for the Training Set Was Established

Not applicable. This is not an AI/ML device.

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