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The Byonyks X-1 APD Cycler is indicated for acute and chronic peritoneal dialysis.

The Byonyks X-1 APD Cycler System includes an Automated Peritoneal Dialysis Cycler and a disposable tubing set. The Byonyks X-1 APD Cycler is intended for acute and chronic peritoneal dialysis. Byonyks X-1 APD Cycler is an automated peritoneal dialysis system that uses a peristaltic pumping mechanism to infuse the dialysate (Dialyzing Solution) into the peritoneal cavity and drain it after the dialysate has dwelled within a patient's peritoneal cavity for a specified amount of time. Byonyks X-1 APD Cycler is a prescription-use-only device and the therapies administered using Byonyks X-1 APD Cycler are prescribed by a physician. The device operates according to a therapy prescription provided by the patient's physician. The device is designed to be used in dialysis clinics, outpatient care areas, and home treatment settings with dialyzing solutions approved for peritoneal dialysis. Dialysate is infused into the patient's peritoneal cavity from a dialysate bag through a surgically implanted catheter which provides a fluid connection to the device's disposable tubing set. The dialysate remains in the peritoneal cavity for the dwell time which is a programmed length of time prescribed by the patient's physician. After the dwell time has elapsed, the fluid is drained from the patient using the device's peristaltic pumping system to extract the fluid from the patient's peritoneal cavity. Peristaltic pumping mechanism of the Byonyks X-1 APD cycler assist the dialysate flow at pre- programmed flowrate up to the volume prescribed by the patient's physicians, device continuously monitors volume of dialysate exchanges along with the fluid pressure external to the cassette of disposable set, fluid pressure detects resistance in dialysate exchanges at which pumping regulates the overall flow.

The Byonyks X-1 APD Cycler System consists of the (i) main control unit (Cycler) and the (ii) disposable set.

The provided 510(k) clearance letter and summary for the Byonyks X-1 APD Cycler focuses on the substantial equivalence of the device to a predicate device, primarily through engineering and bench testing, and does not include an AI/ML component. Therefore, the information required to answer your prompt, such as acceptance criteria for AI/ML performance, study details for AI/ML models (sample size, data provenance, expert ground truth, adjudication, MRMC studies, standalone performance, training data details), is not present in the provided document.

The document details performance testing for the physical cycler device and its disposable set, as well as general medical device requirements like biocompatibility, electrical safety, EMC, and human factors. However, these are evaluations of the hardware and overall system functionality, not specific to an AI/ML algorithm's performance on diagnostic tasks.

Therefore, I cannot populate the table or answer the specific questions related to AI/ML acceptance criteria and performance study details based on the given text.

If this medical device were to incorporate AI/ML, the 510(k) summary would typically include a separate section outlining the AI/ML algorithm, its intended use, performance metrics, and the details of the validation study.

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Intelligent Dialysis Assistant (IDA) is intended for automatic single exchange of dialysate solution exchanges in the treatment of adult renal failure patients undergoing peritoneal dialysis.

All therapies using the Intelligent Dialysis Assistant (IDA) must be prescribed and performed under the responsibility of a physician who is familiar and well informed about peritoneal dialysis. The patient prescription may include single or multiple exchanges, depending on the patient's need.

The IDA Cartridge is a single-use, sterile cartridge exclusively for use with the IDA. It is intended to interface the IDA with the Twin Bag Set (patient dialysis prescription) and the patient's peritoneal catheter.

The Medical Supervision Portal is intended for use by healthcare professionals to remotely communicate new or modified treatment parameters with compatible dialysis instruments and transfer completed treatment database to aid in the review, analysis, and evaluation of patients' historical treatment results. This Medical Supervision Portal is not intended to be a substitute for good clinical management practices, nor does its operation creatment pathways.

The IDA Smartphone App is a software medical application intended for patients to review their treatment and review and approve their dialysis prescription provided by the healthcare professional through the Medical Supervision Portal. The user is not intended to take clinical action based on the application of a qualified healthcare professional.

Not Found

The provided FDA 510(k) clearance letter for the "Digital Dialysis Clinic - Intelligent Dialysis Assistant (IDA) & IDA Cartridge with Medical Supervision Portal and IDA Smartphone App" primarily focuses on the substantial equivalence determination for regulatory clearance. It does not contain specific details about the acceptance criteria or a detailed study proving the device meets those criteria, as typically found in clinical study reports or more comprehensive device descriptions.

The letter confirms the device's classification, intended use, and substantial equivalence to predicate devices, but lacks the in-depth technical and clinical performance data required to answer your specific questions about acceptance criteria, detailed study methodology, ground truth establishment, or human-AI interaction effects.

Therefore, I cannot provide the requested information from the given text. To answer your questions, you would typically need to consult a detailed clinical study report, a regulatory submission, or technical documentation for the device, which are not included in this FDA clearance letter.

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The Fresenius Liberty Select Cycler is indicated for acute and chronic peritoneal dialysis.

The Liberty Select Cycler is a software-controlled electro-mechanical medical device designed to deliver Automated Peritoneal Dialysis (APD) therapy for the treatment of end-stage renal disease (ESRD). The Cycler is designed as a table-top unit that can be used to perform peritoneal dialysis (PD) in hospitals, dialysis clinics, and at home. The software has been updated from version 2.9.2 to introduce the Remote Therapy Programming feature. This feature allows the Cycler to securely receive prescription settings remotely from a Fresenius server.

The provided text describes a 510(k) premarket notification for the Fresenius Liberty Select Cycler, focusing on a software modification (Remote Therapy Programming feature). The document emphasizes that there are no changes to the fundamental device characteristics or performance specifications compared to the predicate device.

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

1. Table of Acceptance Criteria and Reported Device Performance

The document explicitly states that the Liberty Select Cycler has the same essential performance characteristics as the predicate device (K181108). The acceptance criteria are presented as "Specifications" for key features:

Note: The document doesn't provide specific "reported device performance" values for these characteristics for the modified device. Instead, it states that the modified device has the "same essential performance characteristics" as the predicate and that "test results demonstrate that the differences between the proposed and the predicate devices do not raise any new concerns with regard to safety or effectiveness." This implies that the modified device performs within these established specifications.

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

The document does not explicitly state the sample size used for the test set or the data provenance (e.g., country of origin, retrospective/prospective). It mentions "Unit, software, regression (system verification), and validation testing" and "Human Factors Validation Testing" but does not detail the specifics of these test sets.

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

The document does not provide information on the number of experts used to establish ground truth or their qualifications. The testing mentioned (software verification, human factors) would typically involve engineering and possibly human factors specialists, but no details are given.

4. Adjudication Method for the Test Set

The document does not describe any specific adjudication method (e.g., 2+1, 3+1, none) for the test set.

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study Was Done, and Effect Size

No MRMC comparative effectiveness study is mentioned in the document. The submission focuses on substantial equivalence based on a software modification, not a comparison of human reader performance with and without AI assistance.

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

The device is a medical cycler, not an AI algorithm for diagnostic purposes. The "Remote Therapy Programming feature" is a software update that allows the device to receive prescription settings remotely. This is a functional update to the device's operational capabilities, not a standalone diagnostic algorithm. Therefore, "standalone" algorithm performance in the typical sense (e.g., for image analysis) is not applicable or discussed. The testing done covers software verification and validation, as well as human factors for the new feature.

7. Type of Ground Truth Used

For the specific performance characteristics listed (inflow, outflow, temperature, volume accuracy), the ground truth would be established by physical measurements and engineering standards against the device's design specifications. The document implies these were the basis for demonstrating equivalence to the predicate device.

For the software verification and validation testing, the "ground truth" would be the expected functional behavior and security requirements of the software, as defined in design documents and specifications, and adherence to relevant standards (e.g., ANSI/AAMI/IEC 62304 for medical device software lifecycle).

For the human factors validation testing, the "ground truth" would be safe and effective use of the device, particularly with the new remote programming feature, as measured against usability metrics and error rates.

8. Sample Size for the Training Set

The document does not mention a "training set" in the context of machine learning. The software modification described involves a new feature for remote programming, not a machine learning algorithm that requires training data.

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

As no training set for machine learning is mentioned, this information is not applicable.

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The Lilliput™ APD System is indicated for adult chronic peritoneal dialysis in home and clinical settings.

The Lilliput APD System is available in one (1) configuration that includes an electromechanical cycler (hereinafter referred to as "Cycler"), disposable set (hereinafter referred to as "Disposable Set''), USB key, and Kinexus Gateway. The Disposable Sets are available in three (3) configurations:

• . Lilliput Disposable Set, One Patient Connector (Low feature)
• Lilliput Disposable Set, One Patient Connector with Extended Drain and Patient Lines (Medium Feature)
• . Lilliput Disposable Set, Two Patient Connectors with Extended Drain and Patient Lines (High Feature)

The Cycler is a software-controlled electromechanical device. The Disposable Sets are single-use Class II devices designed to operate with the Cycler to perform Automated Peritoneal Dialysis (APD) therapy for the treatment of end-stage renal disease (ESRD). The Disposable Sets are provided sterile and non-pyrogenic and are sterilized using ethylene oxide (EO).

The provided text describes the acceptance criteria and performance data for the Lilliput™ APD System, but it does not detail a study proving the device meets acceptance criteria in the context of diagnostic performance involving human readers or ground truth established by experts/pathology. Instead, the document focuses on engineering and safety performance criteria typical for a medical device.

Therefore, many of the requested fields cannot be filled as the information is not present in the provided text, particularly for AI/diagnostic performance studies.

Here's a breakdown of the available information:

1. Table of Acceptance Criteria and Reported Device Performance

The provided document lists "Essential Performance Specifications/Characteristic" in Table 4 and also describes various performance tests. The reported device performance is generally stated as "verified," "determined," or "acceptable results obtained," without specific numerical outcomes in all cases.

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The CloudCath System is intended for patients undergoing acute and chronic peritoneal dialysis.

The CloudCath System enables drainage and measures turbidity, reported as a numeric score, in peritoneal dialysate effluent as a supplement to visual examination of cloudiness in dialysate drain lines. The system is indicated for use by patients undergoing continuous cycling peritoneal dialysis (CCPD) in a healthcare facility or at home. The optical sensor has associated hardware and software components to allow for data transmission to a healthcare professional.

This system is not intended to provide diagnostic information and is not intended to be a substitute for good clinical management practices, nor does its operation create decisions or treatment pathways.

The CloudCath Peritoneal Dialysis Drain Set Monitoring System (CloudCath System) is a tabletop passive drainage system used as an attachment during a peritoneal dialysis (PD) treatment and indicated for use by patients with acute and chronic end-stage renal disease undergoing PD. The CloudCath System connects directly to the end of the cycler tubing set drain line in order to enable draining and contains an optical sensor that measures turbidity, reported as a turbidity score, in peritoneal dialysate effluent as a supplement to visual examination of cloudiness in dialysate drain lines. The system is indicated for use with validated peritoneal dialysis cyclers in healthcare facilities or home use environments. The optical sensor has associated hardware and software components to allow for remote data transmission by healthcare providers.

The CloudCath System is comprised of three main components: Sensor, Drain Set and Patient Monitoring Software. The Drain Set and the Sensor are components used by the patient. The Patient Monitoring Software is a cloud-based system used by a healthcare professional to view the results from the patient's use of the CloudCath System.

The CloudCath Peritoneal Dialysis Drain Set Monitoring System (CloudCath System) measures turbidity, reported as a numeric score, in peritoneal dialysate effluent as a supplement to visual examination of cloudiness in dialysate drain lines for patients undergoing continuous cycling peritoneal dialysis (CCPD). While this document does not contain an "acceptance criteria" table in the traditional sense for specific performance metrics (e.g., sensitivity, specificity), it outlines the non-clinical performance testing conducted to demonstrate the device's safety and effectiveness and its substantial equivalence to a predicate device.

Here's an interpretation based on the provided text:

1. Table of Acceptance Criteria (Interpreted from "Results / Conclusions") and Reported Device Performance

The document states that all tests were successfully completed and did not raise any different questions of safety or effectiveness. This implies that the acceptance criteria for each test type were met. The "Results / Conclusions" column effectively serves as the reported device performance against implicitly set acceptance criteria for each non-clinical test.

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

The document mentions "clinical samples" for Method Comparison testing and Reference Intervals/Ranges testing. However, it does not specify the sample sizes for these tests or the data provenance (e.g., country of origin, retrospective/prospective nature). The focus is on non-clinical performance and comparability.

3. Number of Experts Used to Establish Ground Truth and Qualifications of Experts

This information is not provided in the document. The ground truth for the analytical and clinical sample testing would likely be based on established laboratory methods for turbidity measurement, rather than expert interpretation in the same way an imaging AI model would use expert readers.

4. Adjudication Method for the Test Set

This information is not provided. Given the nature of turbidity measurement, it's unlikely that an adjudication method for human interpretation would be primarily used for ground truth.

5. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study

A MRMC comparative effectiveness study was not conducted or described. The device measures turbidity as a supplement to visual examination, and the testing focuses on the instrumental performance and comparability of the turbidity measurements rather than a human-in-the-loop diagnostic improvement.

6. Standalone Performance Study (Algorithm Only Without Human-in-the-Loop)

The "Analytical Performance testing of turbidity measurements" and "Method Comparison testing using clinical samples" represent evaluations of the device's standalone performance in measuring turbidity. The "algorithm" here refers to the optical sensor's ability to accurately quantify turbidity. The results indicate that the device "Pass[ed]" these tests, implying its standalone performance met the internal criteria for limits of detection, bias, precision, and comparability to a comparative method.

7. Type of Ground Truth Used

The ground truth for the performance testing related to turbidity measurements would be based on:

• Reference laboratory methods: For "Method Comparison testing using clinical samples," the ground truth would be the results from a highly accurate and precise comparative method for measuring turbidity in dialysate effluent.
• Defined solutions/standards: For "Analytical Performance testing," the ground truth would be precise, known turbidity values in control solutions or standards used for calibration and validation.
• Engineering specifications/measurements: For mechanical, electrical, and dimensional testing, the ground truth would be the defined engineering specifications the device is designed to meet, validated by precise measurement tools.

8. Sample Size for the Training Set

This information is not applicable/not provided in the document for the turbidity measurement aspect. The CloudCath System is an optical sensor measuring a physical property (turbidity), not a machine learning model that requires a "training set" in the conventional sense of AI for image interpretation or diagnosis. Its "learning" is based on its optical and electronic design for accurate physical measurement.

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

As above, this is not applicable for this device in the context of an AI/ML training set. The device's operation is based on established optical measurement principles rather than a trained AI algorithm in the typical machine learning sense. The "ground truth" for its development would be based on physics, engineering, and chemistry principles for accurate turbidity sensing.

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Homechoice Claria APD System:

Baxter's Homechoice Claria APD system is intended for automatic control of dialysis solution exchanges in the treatment of pediatric and adult renal failure patients undergoing peritoneal dialysis in the HOME HEALTHCARE ENVIRONMENT including comparable use in professional healthcare facilities.

Sharesource Connectivity Platform for use with the Homechoice Claria APD System:

The Sharesource portal is intended for use by healthcare professionals to remotely communicate new or modified treatment parameters with compatible dialysis instruments and transfer completed treatment database to aid in the review, analysis, and evaluation of patients' historical treatment results. This system is not intended to be a substitute for good clinical management practices, nor does its operation create decisions or treatment pathways.

The Homechoice Claria APD System (Claria) is intended for automatic control of dialysis solution exchanges in the treatment of pediatric and adult renal failure patients undergoing peritoneal dialysis. The system automatically cycles peritoneal dialysis solution in the amounts and at the times prescribed by a clinician familiar with and well informed about peritoneal dialysis. The clinician may use the Sharesource Connectivity Platform for Use with the Homechoice Claria APD System (Sharesource) to remotely communicate with the Claria cycler. Sharesource allows the transfer of treatment data originating from the treatment device to the clinician for review of historical treatment results. It also allows the clinician to adjust the device settings of the Claria cycler remotely. Changes to the device program by the clinician require the patient to review and accept the changes prior to the implementation of those changes. If the patient does not accept the changes, the Claria cycler will not accept the modified program. Sharesource does not include any real-time monitoring or real-time programming capabilities.

Here's an analysis of the provided text regarding the acceptance criteria and study information for the Baxter Homechoice Claria APD System and Sharesource Connectivity Platform:

It's important to note that the provided text is a 510(k) summary and not a detailed clinical study report. Therefore, some information, especially detailed performance metrics, sample sizes for specific tests, and expert qualifications, is either summarized at a high level or not explicitly stated in the document.

Acceptance Criteria and Study for Baxter Homechoice Claria APD System & Sharesource Connectivity Platform

1. Table of Acceptance Criteria and Reported Device Performance

The 510(k) summary does not explicitly present a table of numerical acceptance criteria with corresponding performance metrics. Instead, it describes a high-level approach to demonstrating substantial equivalence. The "acceptance criteria" are implied to be achieving equivalence to the predicate devices through successful performance testing and risk mitigation.

2. Sample Sizes and Data Provenance (Test Set)

• Sample Size Used for the Test Set: Not explicitly stated in the provided summary. The summary refers to "performance testing" but does not give specific numbers of cases, cycles, or patient data points used for these tests.
• Data Provenance (e.g., country of origin of the data, retrospective or prospective): Not explicitly stated. The document refers to "design validation" and "performance testing," which typically involve internal testing and potentially external validation, but specific details about the type or origin of data used for these tests are not provided.

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

This information is not provided in the summary. The nature of this device (a peritoneal dialysis system and connectivity platform) makes "ground truth" establishment less about expert interpretation of images or clinical findings, and more about functional verification and validation against requirements and predicate performance. Therefore, "experts" would likely be engineers, clinicians (involved in setting requirements), and quality assurance personnel, rather than ground truth adjudicators in the typical sense of diagnostic AI.

4. Adjudication Method for the Test Set:

This information is not provided and is generally not applicable in the context of device functional performance testing for a 510(k) submission. Adjudication methods like 2+1 or 3+1 are typically used in studies where clinical diagnosis or interpretation of data (e.g., images) requires independent expert review to establish a "ground truth" that a device's output is compared against. For a physical device and software platform, the assessment would be against pre-defined functional specifications, safety standards, and equivalence to a predicate.

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study was done, and the effect size of how much human readers improve with AI vs without AI assistance:

No. A Multi-Reader Multi-Case (MRMC) comparative effectiveness study is not applicable to this device. This type of study is relevant for diagnostic AI tools that assist human readers in tasks like image interpretation. The Baxter Homechoice Claria APD System and Sharesource Connectivity Platform are for managing peritoneal dialysis and remote monitoring/programming, not for diagnostic interpretation by human readers. The "AI" (Sharesource) here functions as a data transfer and remote programming tool, not as a diagnostic aid that enhances human interpretation.

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

Yes, in spirit, but not in the diagnostic AI sense. The performance testing described suggests that the system's functionalities (e.g., automatic solution exchanges, data transfer, remote programming capabilities) were validated as standalone functions according to their specifications. The safety and effectiveness claims are based on the device operating independently (the cycler itself) and the Sharesource platform facilitating data/program exchange, rather than its performance in conjunction with a human diagnostic interpreter. The Sharesource explicitly states it "is not intended to be a substitute for good clinical management practices, nor does its operation create decisions or treatment pathways," emphasizing that human clinical judgment remains central.

7. The Type of Ground Truth Used:

The "ground truth" for this type of device is established through:

• Engineering specifications and requirements: The device functions according to its design.
• Predicate device performance: The new device performs equivalently to the legally marketed predicate devices.
• Risk analysis and mitigation: All identified risks are addressed, and the device operates safely.
• Compliance with standards: Adherence to electrical safety, EMC, software, and human factors standards.
• Verification and Validation (V&V) testing: Demonstrating that the device meets its design inputs and user needs.

This is a functional and safety "ground truth" derived from design control processes, rather than a clinical ground truth like pathology or outcome data typically used for diagnostic or predictive AI.

8. The Sample Size for the Training Set:

This information is not provided and is not applicable in the typical sense. This device is a medical device system (hardware and software) and a connectivity platform, not a machine learning or AI model that undergoes a "training phase" with a specific dataset. The "software" mentioned would likely be traditional embedded software and web-based applications, developed through standard software engineering practices (coding, testing, debugging), rather than being "trained" on a dataset like a deep learning model.

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

This information is not provided and is not applicable for the reasons stated above (not an AI model with a training set). The "ground truth" for developing the software and hardware would be the design requirements, functional specifications, and relevant regulatory standards.

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The Fresenius Liberty Select Cycler is indicated for acute and chronic peritoneal dialysis.

The Liberty Select Cycler is an electro-mechanical medical device. Software controls the functions of the machine during peritoneal dialysis treatment, including fluid flow, heating, and alarms. Like the predicate device, the modified Liberty Select Cycler is a software-controlled electromechanical medical device designed as a table-top unit to deliver Automated Peritoneal Dialysis (APD) therapy for the treatment of end-stage renal disease (ESRD). The Liberty Select Cycler is used to perform continuous and intermittent peritoneal dialysis therapies. Treatment settings are programmed based on a physician's prescription.

Acceptance Criteria and Device Performance for Fresenius Liberty Select Cycler (K181108)

This submission (K181108) is for a modification to the Fresenius Liberty Select Cycler, specifically concerning software updates. The key point is that the essential performance characteristics, indications for use, materials, and other technological aspects remain the same as the predicate device (K171652). Therefore, the acceptance criteria and performance data presented here are based on the essential performance characteristics outlined for the device.

1. Table of Acceptance Criteria and Reported Device Performance

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

The provided document does not specify a separate "test set" in the context of a clinical study with human subjects for this particular submission (K181108). This submission primarily focuses on software modifications to an already cleared device. The testing described is software verification and validation testing, which would typically involve testing on the device itself (hardware-in-the-loop) and simulated environments, rather than a human patient test set.

• Sample Size: Not applicable in the context of a human patient test set for this submission. The "sample size" would relate to the number of test cases or scenarios executed during software testing.
• Data Provenance: Not applicable in the context of clinical data provenance for this submission. The "data" comes from internal software testing and verification activities.

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

Not applicable. This submission focuses on software changes and mechanical/electrical device performance, not on diagnostic accuracy based on expert interpretation. The "ground truth" for software testing would be the expected behavior or outcome defined by design specifications and requirements.

4. Adjudication Method for the Test Set

Not applicable. Adjudication methods are typically used in studies involving human interpretation or clinical outcomes where discrepancies among readers or evaluators need to be resolved. This submission describes software and mechanical performance testing.

5. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study

No. An MRMC comparative effectiveness study was not done. This type of study is relevant for assessing the impact of AI on human reader performance in diagnostic tasks, which is not the purpose of this device or its modifications.

6. Standalone (Algorithm Only Without Human-in-the-Loop Performance) Study

Not explicitly a "standalone study" in the common sense of an AI algorithm making a diagnosis. However, the software verification and validation testing described can be considered a form of standalone performance evaluation for the software's intended functions within the device. The software controls functions like fluid flow, heating, and alarms independently, and its modifications were tested to ensure these functions operate correctly.

7. Type of Ground Truth Used

The ground truth for the performance characteristics listed in the table (Inflow, Outflow, Temperature, Volume Accuracy) would be established by engineering specifications, calibration standards, and validated measurement techniques. For the software verification, the ground truth would be the defined software requirements and expected outputs based on those requirements.

8. Sample Size for the Training Set

Not applicable. This device is an electro-mechanical medical device with software controls, not a machine learning or AI algorithm that requires a "training set" in the traditional sense. The software is programmed based on defined logic and parameters, rather than trained on data.

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

Not applicable. As there is no "training set" in the context of a machine learning algorithm, there is no ground truth established for it. The software's correct functioning is verified against its predefined specifications and requirements.

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The Liberty Cycler Sets are designed to operate with the Liberty Cycler to perform acute and chronic peritoneal dialysis.

The Cycler Sets are sterile, single-use devices designed to operate with the Liberty Cycler to perform acute and chronic peritoneal dialysis. Each Cycler Set contains a cassette portion and seven (7) fluid lines. The cassette is composed of a rigid molded plastic body covered with a flexible film (membrane). The cassette contains molded features, such as fluid channels, valve domes, and pumping chambers. There are 7 fluid lines connected to the cassette body:

• One (1) drain line (yellow clamp)
• One (1) patient connection line with two (2) stay •safe® patient connectors (blue clamp)
• Five (5) Dialysate Solution Lines (with Safe-Lock® connectors):
• One (1) heater bag (red clamp)
• One (1) last dialysate bag/'last fill option' (green clamp)
• Three (3) additional solution bags (white clamps)
  The flow of peritoneal dialysate solution to and from the patient's peritoneal cavity is directed by interaction between the Liberty Cycler and the cassette.

The Fresenius Liberty Cycler Set is an accessory for the Liberty Cycler, used for acute and chronic peritoneal dialysis. The 510(k) summary provides performance data and acceptance criteria for various aspects of the device.

Here's an overview of the acceptance criteria and supporting studies:

Key Takeaways:

• No AI Component: The provided document is for a medical device accessory (cycler set) that does not contain software or electrical components, and therefore no AI. Consequently, many of the typical AI-related study components (like expert ground truth, MRMC studies, training set details) are not applicable here.
• Focus on Physical and Biocompatibility Performance: The studies conducted focus on the physical performance of the cycler set (e.g., fill/drain accuracy, structural integrity, leak tests) and its biological safety (biocompatibility).
• Comparison to Predicate Device: The primary method for proving substantial equivalence to a legally marketed predicate device (K043363) relies on demonstrating similar technological characteristics and meeting established performance and safety standards.

1. Table of Acceptance Criteria and Reported Device Performance

Note: The document generally states that testing "was conducted or leveraged to support the determination of substantial equivalence" and "implies meeting criteria" without providing specific numerical acceptance limits or raw performance results. This is common in 510(k) summaries where detailed results are part of the full submission but not always publicly accessible.

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

• The document does not specify the exact sample sizes for each test in the test set.
• The data provenance is not explicitly stated in terms of country of origin or retrospective/prospective nature. However, these are performance tests and biocompatibility tests conducted on the physical device and its materials, typically under controlled laboratory conditions rather than with patient data.

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

• Not applicable. This device is a cycler set (physical accessory), not an AI/software device that generates outputs requiring expert interpretation for ground truth. Ground truth for these tests would be established by objective measurements against engineering specifications and international standards (e.g., ISO, ASTM).

4. Adjudication method for the test set

• Not applicable for the same reasons as point 3.

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 does not have an AI component and therefore no MRMC study was performed in this context.

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

• Not applicable. The device does not contain a standalone algorithm.

7. The type of ground truth used

• The ground truth for the performance and structural integrity tests are quantitative engineering specifications and established material testing standards.
• For biocompatibility, the ground truth is based on established international standards (e.g., ISO 10993-1) for evaluating biological responses to medical device materials.

8. The sample size for the training set

• Not applicable. This device is a physical accessory and does not involve machine learning or a training set.

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

• Not applicable for the same reasons as point 8.

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The Fresenius Liberty Select Cycler is indicated for acute and chronic peritoneal dialysis.

The Liberty Select Cycler is an electro-mechanical medical device. Software controls the functions of the machine during peritoneal dialysis treatment, including fluid flow, heating, and alarms. The Liberty Select Cycler is designed as a table-top unit and is prescribed for use in both professional and home treatment settings. The Liberty Select Cycler is a software-controlled electro-mechanical medical device designed to deliver Automated Peritoneal Dialysis (APD) therapy for the treatment of end-stage renal disease (ESRD). The Liberty Select Cycler is used to perform continuous and intermittent peritoneal dialysis therapies. Treatment settings are programmed based on a physician's prescription. The Liberty Select Cycler accommodates three (3) accessory devices: Cassette and tubing set, IQdrive, Optional wireless modem.

This document describes the Fresenius Liberty Select Cycler, a peritoneal dialysis system. Since the device is a peritoneal dialysis cycler and not an AI/ML powered device, the provided information does not contain details about acceptance criteria, test sets, ground truth, or training sets in the context of AI/ML performance evaluation. These types of details are typically pertinent to the validation of AI/ML algorithms, which is not the subject of this 510(k) summary.

However, the document does list essential performance characteristics and outlines the performance data used to demonstrate substantial equivalence to predicate devices. Here's a breakdown of the relevant information provided:

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

The document states "The Liberty Select Cycler has the same essential performance characteristics as the predicate device (K123630) as listed in Table 1." It then provides the following table:

Note: These specifications serve as the "acceptance criteria" for the device's essential performance characteristics. The document implies that the reported device performance (i.e., the performance of the Liberty Select Cycler) meets these specifications, as it concludes the device is substantially equivalent to the predicate. The document does not provide separate "reported device performance" values if they are identical to the specifications.

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

• This information is not explicitly provided in the context of AI/ML algorithm evaluation, as the device is not an AI/ML product.
• For the described performance parameters (inflow, outflow, temperature, volume accuracy), testing would typically involve a certain number of device units and repeated measurements. However, the specific sample size (e.g., number of cycles tested, number of devices) is not detailed in this summary.
• The data provenance (e.g., country of origin, retrospective/prospective) is also not applicable or specified for this type of medical device validation.

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

• This information is not applicable, as this device is not an AI/ML system requiring expert-established ground truth for algorithm performance.
• The "ground truth" for the performance characteristics would be established by validated measurement techniques and sensors inherent to the engineering and medical device testing processes.

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

• This information is not applicable for the type of device and validation described. Adjudication methods are typically used in clinical studies or AI/ML evaluations where there is subjective interpretation involved.

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 comparative effectiveness study was not done. This type of study is relevant for diagnostic or AI-assisted interpretation devices, which the Fresenius Liberty Select Cycler is not.

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

• This is not applicable as the device is not an AI/ML algorithm. The "standalone" performance here refers to the device's functional performance in an automated manner, which is what the essential performance characteristics refer to.

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

• For the device's essential performance characteristics (Inflow, Outflow, Temperature, Volume Accuracy), the "ground truth" is based on engineering measurements and calibration standards. For example, volume accuracy would be measured against known, accurately measured volumes; temperature against calibrated thermometers; and flow rates against calibrated flow meters.

8. The sample size for the training set:

• This information is not applicable, as the device is not an AI/ML system that undergoes a "training set" phase.

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

• This information is not applicable, as the device is not an AI/ML system with a "training set."

Summary of Study/Testing Methods (as provided in the document):

The performance testing requirements were determined through:

• Application of a risk management process.
• Applicable FDA guidance documents.
• Performance standards (21 CFR 876.5630).

Testing included:

• Software Verification and Validation Testing: Unit, integration, and system-level software verification to demonstrate effectiveness of software modifications and confirm machine operation.
• Mechanical and Acoustic Testing: Verified that noise level does not exceed 40 dBA during treatment.
• Human Factors Testing: Performed on modifications impacting Human Factors, including:
  • Selectable drain exit criteria (70% or 85%).
  • Selectable additional drain option with alert.
  • STAT drain at the end of treatment.
  • Implement Soft Alarms.
  • The remaining essential and critical user tasks were determined to be equivalent to the predicate devices.

The conclusion states that the four new features tested are safe and effective for the intended users, uses, and use environments, and that the device is substantially equivalent to its predicate.

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Amia Automated PD System:
The Amia Automated PD System is intended for automatic control of dialysate solution exchanges in the treatment of adult renal failure patients undergoing peritoneal dialysis.

All therapies using the Amia Automated PD System must be prescribed and performed under the responsibility of a physician who is familiar and well informed about peritoneal dialysis.

Sharesource:
The Sharesource portal is intended for use by healthcare professionals to remotely communicate new or modified treatment parameters with compatible dialysis instruments and transfer completed treatment data to a central database to aid in the review, analysis, and evaluation of patients' historical treatment results. This system is not intended to be a substitute for good clinical management practices, nor does its operation create decisions or treatment pathways.

The Amia Automated PD System with Sharesource (hereafter "Amia/Sharesource System") device is intended for automatic control of dialysate solution exchanges in the treatment of adult renal failure patients undergoing peritoneal dialysis therapy. The system automatically cycles peritoneal dialysis fluid in the amounts and at the times prescribed by a clinician familiar and well informed about peritoneal dialysis. The clinician may use the optional Sharesource software accessory to remotely communicate with the Amia Automated PD System. Sharesource will allow the transfer of treatment data originating from the treatment device to the clinician for review of patient historical treatment results. It will also allow the clinician to adjust the device settings of the Amia Automated PD System remotely. Changes to device program by the physician require the patient to review and accept the changes prior to the change of the device program on the cycler. If the patient does not accept the changes, the device will not accept the modified program. The Amia Automated PD System with Sharesource does not include any real-time remote monitoring or real-time remote programming capabilities.

The provided document is a 510(k) summary for the Amia Automated PD System with Sharesource. It focuses on demonstrating substantial equivalence to predicate devices rather than proving the device meets specific acceptance criteria through a standalone study with detailed performance metrics.

Therefore, the document does NOT contain the following information:

• A table of acceptance criteria and reported device performance.
• Sample size used for a test set or its data provenance.
• Number of experts used to establish ground truth or their qualifications.
• Adjudication method for a test set.
• Information about a multi-reader multi-case (MRMC) comparative effectiveness study, including an effect size for human readers with and without AI assistance.
• A standalone performance study of the algorithm without human-in-the-loop.
• The type of ground truth used (e.g., pathology, outcomes data).
• Sample size for a training set.
• How ground truth for a training set was established.

However, the document does state the following about performance testing:

• Performance Data: "The device was tested to verify conformance with the design specifications and applicable industry standards and to verify compatibility and functionality with Sharesource. Complete system verification testing was performed to ensure that the device functions as intended and met all requirements."
• Human Factors Evaluation: "In addition, Human Factors evaluations for the Amia Automated PD System and the Sharesource software were conducted in simulated environments to ensure user needs and intended uses were met."

In summary, the document states generally that testing was performed to verify conformance to specifications and ensure the device functions as intended, and that a Human Factors evaluation was conducted. However, it does not provide specific acceptance criteria, detailed performance metrics, sample sizes, ground truth establishment, or details of a comparative effectiveness study that one might find for an AI/ML-driven diagnostic device.

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