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The PhySoft Anemia Management System® (PhySoftAMS®) is a software application used to obtain, track and trend patient data pertaining to the management of anemia, and to provide a schedule of erythropoiesis-stimulating agent (ESA) dosage recommendations to help achieve and maintain target hemoglobin levels in dialysis patients. PhySoftAMS® is intended to help physicians. nurses, clinicians, and anemia managers manage anemia in adult stage 5 chronic kidney disease (CKD) patients.

PhySoftAMS® is not a substitute for, but is rather intended to assist, clinical judgment. The erythropoiesis-stimulating agent (ESA) dosing regimen options calculated by this device are intended to be used by qualified and trained medical personnel to inform the optimization of the dosage of ESAs in accordance with their approved labeling in conjunction with clinical history, symptoms, and other diagnostic measurements, as well as the medical professional's clinical judgment. No medical decision should be based solely on the patient Hgb response to dosing regimen options calculated by this device.

PhySoftAMS® is a software application used to obtain, track and trend patient data pertaining to the management of anemia and to provide a schedule of erythropoiesis-stimulating agent (ESA) dosage recommendations to help achieve and maintain target hemoglobin levels in dialysis patients. PhySoftAMS® is intended to help physicians, nurses, clinicians and anemia managers manage anemia in adult stage 5 chronic kidney disease (CKD) patients.

PhySoftAMS® is intended for use by medical personnel such as clinicians, nurses, and physicians in dialysis clinics or other settings where anemia management for hemodialysis patients is conducted.

Healthcare professionals access PhySoftAMS® directly using a web application graphical user interface (GUI) or indirectly using the drug dosing-related screens of a third party's electronic health record (EHR) system via an application programming interface (API) provided by the PhySoftAMS® application server.

PhySoftAMS® evaluates whether adequate historical data is available to model patient ESA dose-Hgb response dynamics and project future ESA dose-Hgb response. If adequate data is available, PhySoftAMS® enables a physician to model a patient and select from one or more dosing schedule options most likely to result in achieving target Hgb levels or, at the physician's discretion. override the presented dosing schedule options.

The provided text describes a 510(k) premarket notification for a medical device called PhySoftAMS®, a software application for managing anemia in dialysis patients. However, the document does not contain the detailed information necessary to answer all the questions regarding acceptance criteria and the study proving the device meets those criteria.

Specifically, the document states:

• "Bench testing results demonstrate the modified device performance is computationally equivalent to the performance of the predicate device."
• "Software verification and validation of the device modifications that are the subject of this submission demonstrated that the enhancements for the subject (modified) device perform as intended and have no effect on the modeling process or other device functions of PhySoftAMS®."

This indicates that internal testing (bench testing, software V&V) was performed to show computational equivalence and proper function of the modifications, but it does not detail a clinical study or performance study with acceptance criteria, sample sizes, ground truth establishment, or multi-reader multi-case studies as requested.

Therefore, many of the requested details cannot be extracted from this document. I can only provide information directly inferable from the given text.

Here's an attempt to answer based only on the provided text, highlighting what is not available:

Acceptance Criteria and Study for PhySoftAMS®

The provided 510(k) summary (K232283) focuses on demonstrating substantial equivalence of a modified PhySoftAMS® to its predicate device (PhySoft AMS™, K130579), primarily regarding the new integration with EHR systems via an API. The performance data presented relates to computational equivalence and software functionality, rather than a clinical performance study with defined acceptance criteria for diagnostic or clinical accuracy.

1. Table of Acceptance Criteria and Reported Device Performance

Based on the provided text, formal acceptance criteria for a clinical performance study (e.g., sensitivity, specificity, accuracy targets) and corresponding reported performance metrics are not explicitly stated. The "Performance" section focuses on computational and functional equivalence to the predicate.

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

The document does not specify a sample size for a "test set" in the context of a clinical or retrospective/prospective performance study. The evaluations described (bench testing, software V&V) typically do not involve patient-level test sets in the same manner as a diagnostic study. The data provenance (country, retrospective/prospective) is also not mentioned.

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

The document does not mention using experts to establish ground truth for a test set, as no such clinical or performance test set is described. The device provides "dosing recommendations," which would typically be compared against clinical outcomes or expert judgment in a performance study, but this is not detailed here.

4. Adjudication Method for the Test Set

Since no test set adjudicated by experts is described, the adjudication method is not applicable/not mentioned.

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

No MRMC study is described in the provided text. The device offers dosing recommendations and assists human users, but there is no information on a study comparing human readers with and without AI assistance, or an effect size.

6. If a Standalone (Algorithm Only Without Human-in-the-Loop Performance) Was Done

The text indicates the device "provides a schedule of erythropoiesis-stimulating agent (ESA) dosage recommendations to help achieve and maintain target hemoglobin levels" and is "intended to help physicians, nurses, clinicians, and anemia managers manage anemia." It explicitly states, "PhySoftAMS® is not a substitute for, but is rather intended to assist, clinical judgment." This implies a human-in-the-loop design. No standalone algorithmic performance study results are detailed in the document. The "computational equivalence" refers to the underlying modeling process itself.

7. The Type of Ground Truth Used

For the software verification and validation, the "ground truth" would be the expected behavior and output of the algorithms and software functions, based on predefined specifications and the known performance of the predicate device. For potential clinical application, the ultimate ground truth would relate to actual patient hemoglobin levels and clinical outcomes, but the studies described do not detail the collection or establishment of such ground truth.

8. The Sample Size for the Training Set

The document does not mention a training set size. This device appears to use PK/PD modeling of patient response rather than a deep learning model that typically requires a large training set of annotated data. The system tracks and trends past Hgb and ESA dosages for individual patient modeling, not a general training dataset for an AI model.

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

As no training set (in the context of machine learning) is explicitly mentioned, the method for establishing its ground truth is not detailed. The modeling is described as "PK/PD modeling of patient response to ESAs," which is typically based on physiological and pharmacological principles, not a data-driven training set with established ground truth labels in the same way an image classification AI might be trained.

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SAM is a web application used to obtain, track and trend patient data pertaining to the management of anemia, and to provide a schedule of erythropoiesis-stimulating agent (ESA) dosage recommendations to help achieve and maintain target hemoglobin (Hgb) levels in hemodialysis patients. The device is intended to help clinicians manage chronic anemia.

The device is not a substitute for, but rather intended to assist, clinical judgment. The ESA dosing regimen options calculated by this device are intended to inform the optimization of the dosage of ESAs in accordance with their approved labeling in conjunction with clinical history, symptoms, and other diagnostic measurements, as well as the clinicians' judgment. No medical decision should be based solely on the patient Hgb response to dosing regimen options calculated by this device.

SAM is a web application used to obtain, track and trend patient data pertaining to the management of anemia, and to provide a schedule of erythropoiesis-stimulating agent (ESA) dosage recommendations to help achieve and maintain target hemoglobin (Hgb) levels in hemodialysis patients. The device is intended to help clinicians manage chronic anemia.

Healthcare professionals access SAM using a web-enabled application (for example, a web browser or a web-enabled electronic health record system) communicating with the SAM web application server. Patient information is obtained by SAM from healthcare provider Electronic Medical Records. No components of SAM are required to be installed at end user or healthcare provider locations.

SAM estimates individual patient's Hgb response to ESAs. The results of this estimation are used to generate new patient-specific ESA dose recommendation to achieve target Hgb level specified by the physician. The ESA dose recommendation is reviewed by the physician, who after considering any additional relevant information about patient's condition, decides whether to follow or override the presented ESA dose recommendation.

Here's an analysis of the acceptance criteria and study detailed in the provided text for the Smart Anemia Manager (SAM) device:

1. Table of Acceptance Criteria and Reported Device Performance

The document does not explicitly state formal "acceptance criteria" for the study in a pass/fail sense with numerical targets. Instead, it describes demonstrating "non-inferiority to AMP 1 and 2 in mean hemoglobin, percent in target range and hemoglobin standard deviation." The clinical trials then provide performance measures.

Here's a table summarizing the performance metrics and implicit targets/comparisons:

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

• Simulation Testing:

  • Test Set Sample Size: A pool of 2430 simulated patients were created. Each protocol (SAM, AMP1, AMP2) was run for 26,730 simulations (likely meaning 26,730 unique scenarios or patient instances within the pool).
  • Data Provenance: In silico simulation. The concepts for patient response to ESA were based on published pharmacodynamics (Uehlinger et al. Clin Pharmacol Ther 51:76-89, 1992). This is synthetic data, not real patient data.

• Clinical Studies:

  • Clinical Trial 1 (Randomized, Controlled, Double-Blind):
    • Test Set Sample Size: 62 subjects (52 completed the study).
    • Data Provenance: Prospective clinical trial.
  • Clinical Trial 2 (Case-Controlled & Cross-Sectional):
    • Test Set Sample Size: Not explicitly stated but compared to PhySoft AMS™ over a 45-month follow-up period.
    • Data Provenance: Retrospective, comparing long-term follow-up of SAM and PhySoft AMS™ performance.

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

• Simulation Testing: No human experts were used to establish ground truth. The ground truth was defined by the in silico model of patient response to ESA, based on published pharmacodynamics.
• Clinical Studies: The document does not specify how ground truth was established for the clinical trials beyond stating that Hgb levels were measured and safety events tracked. It implies that standard clinical measurements and outcomes served as the "ground truth." There is no mention of an expert panel to adjudicate individual cases or outcomes.

4. Adjudication Method (for the test set)

• Simulation Testing: Not applicable, as it's a simulated environment.
• Clinical Studies: Not explicitly stated. For Clinical Trial 1, safety events (CSE) were tracked, but the adjudication method for these events is not described (e.g., whether an independent clinical events committee adjudicated them). For Hgb levels, standard laboratory measurements would be considered the ground truth, not requiring expert adjudication.

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

• No, an MRMC study was not done. This device (Smart Anemia Manager, SAM) is an algorithm that provides dosage recommendations, not an imaging device or diagnostic tool that humans interpret. Therefore, the concept of "human readers improving with AI vs. without AI assistance" as typically studied in MRMC designs for diagnostic AI is not directly applicable here.
• The clinical trials assess the effectiveness of the recommendations provided by SAM compared to standard of care/predicate, rather than how humans perform with those recommendations versus without them. The device produces the recommendation; it doesn't assist human interpretation in the typical MRMC sense.

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

• Yes, the simulation testing represents a standalone evaluation of the algorithm's performance. In the simulation, SAM's dosing recommendations were directly applied to simulated patients, and the outcomes (Hgb levels, variability, ESA dose) were compared to other algorithmic protocols (AMP1, AMP2).
• The clinical trials, by definition, involve human clinicians using the SAM recommendations (or standard of care/predicate recommendations), but SAM itself is intended to generate recommendations. The study's focus is on the clinical outcomes resulting from following those recommendations.

7. The type of ground truth used

• Simulation Testing: Mathematically defined in silico model of patient pharmacodynamics (response to ESA and red blood cell life spans).
• Clinical Studies:
  • Clinical Trial 1: Measured hemoglobin concentrations, and a Composite Safety Event (CSE) based on medical outcomes (mortality, MI, CVA, CHF). This is outcomes data combined with standard clinical measurements.
  • Clinical Trial 2: Measured hemoglobin concentrations and the incidence of high hemoglobin concentrations (above 12.9 g/dL). This is standard clinical measurements.

8. The sample size for the training set

The document does not provide information regarding the sample size for the training set used to develop or train the SAM algorithm. It describes the technology as using an "individualized dose response model" but doesn't detail how this model was trained.

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

Since the document does not specify a training set or its sample size, it also does not explain how the ground truth for any training set was established.

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PhySoft AMS™ is a web application used to obtain, track and trend patient data pertaining to the management of anemia, and to provide a schedule of erythropoiesis-stimulating agent (ESA) dosage recommendations to help achieve and maintain target hemoglobin levels in dialysis patients. PhySoft AMS™ is intended to help physicians, nurses, clinicians and anemia managers manage anemia in adult stage 5 chronic kidney disease (CKD) patients.

The PhySoft AMS™ is not a substitute for, but rather intended to assist, clinical judgment. The ESA dosing regimen options calculated by this device are intended to be used by qualified and trained medical personnel to inform the optimization of the dosage of ESAs in accordance with their approved labeling in conjunction with clinical history, symptoms, and other diagnostic measurements, as well as the medical professional's clinical judgment. No medical decision should be based solely on the patient Hgb response to dosing regimen options calculated by this device.

PhySoft AMS™ is a software application used to obtain, track and trend patient data pertaining to the management of anemia, and to provide a schedule of ESA dosage recommendations to help achieve and maintain target Hgb levels in dialysis patients. PhySoft AMS™ is intended to help physicians, nurses, clinicians and anemia managers manage anemia in adult stage 5 CKD patients.

PhySoft AMS™ is intended for use by medical personnel such as clinicians, nurses, and physicians in dialysis clinics or other settings where anemia management for hemodialysis patients is conducted.

Healthcare professionals access PhySoft AMS™ using a web browser communicating with the PhySoft AMS™ web application server. Patient information is obtained by PhySoft AMS™ from healthcare provider information systems. No components of PhySoft AMS™ are required to be installed at end user or healthcare provider locations.

PhySoft AMS™ assesses if there is adequate data to model an individual patient's Hgb response to ESAs. The results of this assessment are reviewed by the physician who, after considering any additional relevant information about the patient's condition, decides if they want to apply the PhySoft AMS™ ESA dose-Hgb response modeling capability to the particular patient's data. If adequate data are available, PhySoft AMS™ enables a physician to model a patient and select from dosing schedule options to achieve target Hgb levels or, at the physician's discretion, override the presented dosing schedule options.

The provided text states that a clinical evaluation was conducted for PhySoft AMS™ to demonstrate its safety and effectiveness. However, it does not provide specific details about the acceptance criteria or the results of the study in a format that allows for the extraction of a table of acceptance criteria and reported device performance, sample sizes for test sets, data provenance, number of experts, adjudication methods, MRMC study details, standalone performance, type of ground truth, training set sample size, or how ground truth for the training set was established.

The document only generally concludes that "The Performance data demonstrated the safety and effectiveness of PhySoft AMS™ in anemia management for hemodialysis patients." and that it is "substantially equivalent" to its predicate device. This implies that testing was done, but the detailed methodology and results are not included in this summary.

Therefore, I cannot provide the requested information from the given input.

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Vasc-Alert vascular data analysis software is intended for use by Healthcare professionals in a non-Vasc-Afert vascular data analysis software is nave access site stenosis in patients with grafts and critical care setting for assessment of mercasse money is to be used with data generated from hemodialysis machines.

Vasc-Alert is a software program for alerting dialysis center personnel of an increased risk of access site vace institutional hemodialysis patients. Vasc-Alert utilizes measurements routinely collected during a dialysis treatment by the hemodialysis machine, such as pressure and flow rate, and applies a previously published algorithm called the Vascular Access Pressure Ratio (VAPR) test to these measurements. The average VAPR test result for each treatment session is stored in a Vasc-Alert database. If a patient has a high reading in three consecutive dialysis sessions, a report is issued to the medical staff indicating that the patient should be examined more closely for the onset of stenosis. Hemodialysis center personnel can use the report as a tool to proactively monitor for incipient stenosis and prompt proactive intervention to avoid site closure.

Vasc-Alert comprises five main components or modules:

• A module for recording, transferring and parsing data collected by dialysis center machines. I
• A module for calculating the VAPR values from treatment data. .
• A module for identifying significant patterns in the calculated VAPR data that will prompt an 트 alert (i.e., 3 high readings in a row for a patient).
• A module for generating reports and sending these out to center personnel. l
• An internet-based data input module. 이

The provided text describes the Vasc-Alert device and its intended use but does not contain information about acceptance criteria or a study proving that the device meets such criteria.

Therefore, I cannot fulfill the request to describe the acceptance criteria and the study that proves the device meets them, as the necessary information is not present in the provided document.

The document mainly focuses on:

• A 510(k) summary for Vasc-Alert, outlining its proprietary name, common name, classification, and equivalent devices.
• A description of the Vasc-Alert software, including its components and how it functions (using VAPR test results to alert about potential stenosis).
• The FDA's letter of substantial equivalence, confirming the device's market clearance.
• The "Indications for Use Statement" for Vasc-Alert.

None of these sections detail acceptance criteria, study methodologies, sample sizes for testing or training, ground truth establishment, expert qualifications, or comparative effectiveness.

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The Transonic Syringe Warmer (Model SYR1000) is indicated for use with the Transonic HD01 (HD01PMS and HD02) systems to make Cardiac output measurements. The Transonic Syringe Warmer (Model SYR1000) is an accessory to our HD01-CO Hemodialysis Monitor for Cardiac Output (K980906) which are currently marketed as the HD01046 and HD02 systems. The HD01-CO Hemodialysis Monitor for Cardiac Output (HD01P05 and HD02 systems) requires the user to make a 30cc injection of approximately body temperature saline into the hemodialysis blood circuit for the CO measurement. The syringe warmer provides the user a convenient source of the 30cc injection of approximately body temperature saline for this injection.

In accordance with section 510(k) for the Federal Food, Drug, and Cosmetic Act, Transonic Systems Inc. intends to introduce into interstate commerce the Transonic Syringe Warmer as an accessory to our HD01-CO Hemodialysis Monitor for Cardiac Output (K980906). The HD01-CO Hemodialysis Monitor for Cardiac Output requires the user to make a 30cc injection of ~ body temperature saline into the hemodialysis blood circuit for the CO measurement. The syringe warmer will provide the user a convenient source of the 30cc injection of ~ body temperature saline for this injection.

The provided text describes a 510(k) premarket notification for the Transonic Syringe Warmer, an accessory device. The information primarily focuses on establishing substantial equivalence to a predicate device and does not contain detailed acceptance criteria, specific study designs, or performance metrics in a quantitative manner typical for AI/ML device submissions.

Based on the provided text, I can infer the general nature of the "acceptance criteria" and "study" as implied by the FDA's "Safety and Effectiveness" section, but there are no specific numerical thresholds or detailed study results. The submission relies on demonstrating the device is similar to a predicate device and meets general quality control requirements.

Here's an analysis based on the provided text, attempting to address your points as much as possible, while noting where information is absent for this type of submission:

Acceptance Criteria and Study for the Transonic Syringe Warmer

The Transonic Syringe Warmer is an accessory device intended to warm a 30cc syringe of saline to approximately body temperature for injection into a hemodialysis blood circuit. The acceptance criteria and supporting "study" described are focused on demonstrating the device's safety and effectiveness and its substantial equivalence to a predicate device, rather than a quantifiable performance study against specific metrics for AI/ML devices.

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

Based on the document, the acceptance criteria are implicitly tied to "release specifications" and "product design specifications." The "reported device performance" is essentially that the device functions as intended to warm saline.

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

The document does not specify a "test set" in the context of a typical AI/ML study with data points. Instead, it refers to "all finished products" being tested.

• Sample Size: "All finished products" are tested. This implies a 100% inspection or testing of manufactured units.
• Data Provenance: Not applicable in the context of clinical data. The tests are bench tests performed by the manufacturer, Transonic Systems Inc. (located in Ithaca, NY, USA).
• Retrospective/Prospective: Not applicable. These are manufacturing quality control tests, not clinical studies.

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 to the type of device and submission described. There is no mention of experts establishing ground truth for a test set, as this is a hardware device undergoing manufacturing quality control rather than a diagnostic AI/ML algorithm.

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

Not applicable. There is no "test set" requiring adjudication in the context of clinical or diagnostic performance. The testing described is internal quality control.

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, a multi-reader multi-case (MRMC) comparative effectiveness study was not done. This type of study is relevant for diagnostic imaging AI/ML devices, not for a syringe warmer. There is no AI component mentioned in this device.

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

No, a standalone algorithm-only performance study was not done. This device is a hardware accessory and does not contain an AI algorithm.

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

The "ground truth" for this device's performance is based on its adherence to manufacturing specifications and its ability to perform its stated function (warming saline to ~body temperature). This would be validated through engineering measurements and quality control checks, not expert consensus, pathology, or outcomes data in a clinical sense.

8. The sample size for the training set

Not applicable. This device does not use machine learning or have a "training set."

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

Not applicable. This device does not use machine learning or have a "training set."

Summary of the "Study" Described:

The "study" demonstrating the Transonic Syringe Warmer meets its acceptance criteria is best described as a comprehensive quality control and manufacturing testing process rather than a clinical trial or AI performance study.

• Process: "All finished products are tested and must meet all required release specifications before distribution."
• Testing Types: "physical testing, visual examination (in process and finished product)."
• Methodology: "The physical testing is defined by Quality Control Test Procedure documents. These tests are established testing procedures that ensure the products performance parameters conform to the product design specifications."
• Documentation: "The testing instruction records for each of the individually required procedures are approved, released, distributed and revised in accordance with document control cGMP's."

The submission primarily relies on demonstrating substantial equivalence to a predicate device (Vista Dental Anesthetic Syringe Warmer) and asserting that the modified intended use (warming saline for hemodialysis monitoring) "does not raise any new issues of safety or effectiveness." This approach underscores that the primary evidence for this particular 510(k) submission is related to manufacturing quality and equivalence, not advanced performance metrics or clinical study data.

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The Transonic Flow-QC Set is indicated for use as part of an extracorporeal blood circuit for hemodialysis when the Transonic HD01 System will be use to make access flow, recirculation, and/or cardiac output measurements during the patient's hemodialysis treatment.

In accordance with section 510(k) for the Federal Food, Drug, and Cosmetic Act, Transonic Systems Inc. intends to introduce into interstate commerce the Transonic Flow-QC® Sets which are Hemodialysis extension sets for connection into standard Hemodialysis circuits. These sets provide tubing segments of consistent material and wall thickness to which our HD01 Hemodialysis system can be calibrated. They also provide an injection port for making cardiac output measurements with the HD01 system.

The provided text is a 510(k) Summary for the Transonic Flow-QC® Sets, which focuses on demonstrating substantial equivalence to a predicate device rather than presenting a performance study with acceptance criteria in the typical sense of a medical device with an algorithm.

Therefore, the information requested regarding acceptance criteria, device performance, study characteristics (sample sizes, ground truth, experts, adjudication), and multi-reader multi-case (MRMC) or standalone studies is not explicitly available in the provided document. This document emphasizes material testing, compliance with standards, and comparison to a predicate device, which is a common approach for certain classes of medical devices.

Here's a breakdown based on the provided text, indicating where information is missing:

Acceptance Criteria and Device Performance

Study Details

Below is a response to each specific point, indicating that the information is not present in the provided 510(k) summary for the Transonic Flow-QC® Sets. This type of 510(k) submission, particularly for accessories, often relies on material compliance and comparison to a predicate rather than extensive clinical performance studies as would be seen for a diagnostic algorithm.

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

   • Information Not Provided. The document describes manufacturing quality control and material testing, not a clinical performance study with a "test set" in the context of an algorithm.

2. Number of experts used to establish the ground truth for the test set and the qualifications of those experts (e.g. radiologist with 10 years of experience):

   • Information Not Provided. No "ground truth" establishment by experts is mentioned, as this is not a diagnostic device or an algorithm requiring such validation.

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

   • Information Not Provided. No adjudication method is mentioned, as there is no "test set" in the context of a diagnostic performance study.

4. 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:

   • Information Not Provided. No MRMC study was performed or is relevant, as this device is a hemodialysis accessory, not an AI-assisted diagnostic tool.

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

   • Information Not Provided. This device does not involve an algorithm, hence no standalone performance study was conducted or is applicable.

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

   • Information Not Provided. "Ground truth" in the context of diagnostic accuracy is not addressed. The "truth" for this device relates to manufacturing specifications and material compliance.

7. The sample size for the training set:

   • Information Not Provided. There is no "training set" as this device does not involve machine learning or an algorithm.

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

   • Information Not Provided. Not applicable, as there is no training set.

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The M2376A Device Link System is indicated for use in data collection and clinical information management either connected directly or through networks with independent bedside devices.

The M2376A is not intended for monitoring purpose, nor is the M2376A intended to control any of the clinical devices (independent bedside devices / information systems) it is connected to.

The Hewlett Packard M2376A Device Link System receives digital data produced by external devices through device specific cables, converts that data into the HL7 format and transmits that information to any networked Clinical Information System.

The provided text describes a 510(k) summary for the Hewlett Packard M2376A Device Link System. However, it does not contain any information regarding acceptance criteria, device performance, study details, sample sizes, ground truth establishment, expert qualifications, or adjudication methods.

The document is a regulatory submission for a device that facilitates electronic data collection and clinical information management by converting data from external devices into the HL7 format. The FDA's response letter confirms substantial equivalence to legally marketed predicate devices.

Therefore, I cannot fulfill your request for the specified information based on the provided input. The input focuses on the device's intended use and regulatory approval, not on performance studies or acceptance criteria.

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The CRIT-LINE MONITOR III, (CLM III) is a non-invasive hematocrit, oxygen saturation and percent change in blood volume monitor used in the treatment of hemodialysis patients. In addition, the CLM III estimates access recirculation and access blood flow in hemodialysis patients.

The CLM III consists of a state-of-the-art microprocessor which has all of the chip select logic, serial communication, timing and watchdog circuits incorporated within it. The CLM III is used in conjunction with the In-Line Diagnostics Blood Chamber. The blood chamber is connected to and becomes part of the dialysis tubing circuit. The sensor from the CLM III is connected to the blood chamber which reads critical blood parameters as blood passes through the blood chamber.

Here's an analysis of the provided text regarding the CRIT-LINE MONITOR III, structured to answer your questions:

Acceptance Criteria and Device Performance Study for CRIT-LINE MONITOR III

1. Table of Acceptance Criteria and Reported Device Performance

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

• Sample Size: 29 data points
• Data Provenance: Retrospective (though collected specifically for this validation, it's not a prospective interventional trial based on the description).
  • 16 data points from Victoria Hospital in London Ontario, Canada (April 8th and April 9th, 1999)
  • 13 data points from Central Valley Dialysis in Salt Lake City, Utah (June 22nd and June 24th, 1999)

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

The document does not mention the use of experts to establish ground truth. The "ground truth" (or reference method) was established by calculating Access Blood Flow (ABF) values externally using CRIT-LINE MONITOR III hematocrit measurements fed into a formula via a calculator or spreadsheet program (which was the previously approved method, K982412).

4. Adjudication Method for the Test Set

No adjudication method is described. The comparison was statistical between two calculated values (one internally by the device, one externally using device-generated hematocrit data and a formula).

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 device is a monitor measuring physiological parameters; it's not an AI system for image interpretation or diagnosis that would typically involve human readers.

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

Yes, in a way. The study's purpose was to validate the internal calculation of ABF by the CRIT-LINE MONITOR III. This internal calculation is essentially the "algorithm only" performance, compared against the established external calculation method which uses data generated by the same device (CLM III hematocrit measurements) but processes it outside the device. The study is evaluating the device's self-contained ABF calculation capability.

7. The Type of Ground Truth Used (expert consensus, pathology, outcomes data, etc.)

The "ground truth" was the previously approved method of ABF measurement, which involved:

• Measuring hematocrit values using the CLM III.
• Calculating ABF values externally via a calculator or spreadsheet program using these measured hematocrit values.
• This method itself had a 510(k) clearance (K982412).

Essentially, the ground truth was a reference calculation method using device-generated data.

8. The Sample Size for the Training Set

The document does not mention a separate training set. The CRIT-LINE MONITOR III is a physical device with a software modification for internal calculation. The description implies the software was developed based on existing understanding of the ABF formula and then validated with the 29 data points as the "test set" against the established external calculation method. It's unlikely that machine learning or a training set in the modern sense was used for this type of device in 1999.

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

As no explicit training set is mentioned, this question is not applicable. The device's internal ABF calculation functionality was evaluated against a pre-existing, legally marketed method of calculating ABF.

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The HP M2376A Device Link System is indicated for use in data collection and clinical information management, either connected directly or through networks, with the independent bedside devices that are listed below;

• 1. IMED 1310 (PC-1) channel IV Pump
• 2. In-line Diagnostic HR Crit-Line Monitor
• 3. Newport Wave Ventilator

The Hewlett Packard M2376A DeviceLink System receives digital data frontuced by external devices through device specific cables, converts that data into the HL7 format and transmits that information to any networked Clinical Information System.

When connected to a bedside device, the HP M2376A DeviceLink System is intended for electronic data collection and clinical Information management. DeviceLink is neither patient connected, nor does it remotely control the attached source device.

The provided document is a 510(k) summary for the Hewlett Packard M2376A DeviceLink System. It primarily focuses on demonstrating substantial equivalence to a predicate device and obtaining marketing clearance from the FDA. It does not describe or contain a study proving the device meets acceptance criteria in the way typically expected for a medical device performance study (e.g., clinical trial data, analytical performance data with specific metrics like sensitivity, specificity, accuracy).

Therefore, based on the provided text, a table of acceptance criteria and reported device performance, information about sample sizes, ground truth, expert involvement, MRMC studies, or standalone performance studies cannot be extracted.

The document states:

• Device Function: The Hewlett Packard M2376A DeviceLink System receives digital data from external devices, converts that data into the HL7 format, and transmits that information to any networked Clinical Information System.
• Intended Use: When connected to a bedside device, the HP M2376A DeviceLink System is intended for electronic data collection and clinical information management. DeviceLink is neither patient connected, nor does it remotely control the attached source device.
• Predicate Device: The HP M1032A VueLink Interface Plug-in Module (K923682).
• Technological Characteristics: "The technological characteristics are the same or similar to those found with the predicate device, with the exception that neither waveforms, alarms, nor image data are transmitted in the DeviceLink System."

Conclusion based on the provided text:

This submission is a regulatory clearance document rather than a scientific study report. It focuses on the device's intended use, its functional similarity to a previously cleared device, and its regulatory classification. It does not provide the kind of detailed performance data and study design (acceptance criteria, sample size, ground truth, expert review, standalone performance, etc.) that would typically be associated with proving a device meets specific performance criteria through a dedicated study.

Therefore, the requested information cannot be filled out from the provided text.

If this were a different type of medical device (e.g., an AI-powered diagnostic tool), the 510(k) summary would typically include a section detailing analytical and/or clinical performance studies with the requested metrics. However, for a data communication system like the DeviceLink, the primary focus for regulatory clearance is often on functional equivalence and safety (e.g., no adverse control of connected devices, proper data transmission format).

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