Search Results

Cerebral Autoregulation Index (CAI) Algorithm is an informational index intended to represent a surrogate measurement of whether cerebral autoregulation is likely intact or is likely impaired as expressed by the level of coherence or lack thereof between Mean Arterial Pressure (MAP) and the Absolute Levels of Blood Oxygenation Saturation (StO2) in patient's cerebral tissue. MAP is acquired by the HemoSphere pressure cable and StO2 is acquired by the ForeSight oximeter cable. CAI is intended for use in patients over 18 years of age receiving advanced hemodynamic monitoring. CAI is not indicated to be used for treatment of any disease or condition and no therapeutic decisions should be made based solely on the Cerebral Autoregulation Index (CAI) Algorithm.

The Cerebral Adaptive Index (CAI) Algorithm is being renamed to Cerebral Autoregulation Index (CAI) Algorithm. The originally cleared Cerebral Adaptive Index is in effect an index of cerebral autoregulation, and the renaming results in a labeling change. The evidence to support the proposed labeling change for the Cerebral Autoregulation Index algorithm demonstrates the capability of CAI to represent a surrogate measurement of whether cerebral autoregulation is likely intact or is likely impaired, as expressed by the level of coherence or lack thereof between MAP (as a surrogate of cerebral perfusion pressure) and cerebral StO2 (as a surrogate of cerebral blood flow) of the patient.

The Cerebral Autoregulation Index (CAI) Algorithm is a derived parameter that quantifies the dynamic relationship between two existing hemodynamic parameters, Mean Arterial Pressure (MAP) and the Absolute Levels of Blood Oxygenation Saturation (StO2) in the cerebral tissue. CAI is intended to represent a surrogate measurement of whether cerebral autoregulation is likely intact or is likely impaired as expressed by the level of coherence between MAP and cerebral StO2. The output will be represented as an index value in a trend plot.

MAP is acquired from the HemoSphere Pressure Cable (initially cleared in K180881 on November 16, 2018). StO2 used for computing CAI is acquired from the ForeSight Oximeter Cable (cleared in K201446 on October 1, 2020).

CAI will be continuously displayed at 20-second rate. The parameter will not have any alarm ranges and will be represented as a number with a range between 0 to 100. A high CAI value (CAI ≥45) means that MAP and StO2 have a greater coherence and informs the clinician that alterations in MAP may result in concomitant changes in cerebral oxygen saturation because cerebral autoregulation is likely impaired. Whereas a low CAI value (CAI

Here’s a breakdown of the acceptance criteria and the study that proves the device meets them, based on the provided text:

Device Name: Cerebral Autoregulation Index (CAI) Algorithm

The document describes a 510(k) submission for a name change (and re-clarification of its meaning) of an existing device (Cerebral Adaptive Index (CAI) Algorithm) to Cerebral Autoregulation Index (CAI) Algorithm. The core algorithm and its function remain the same. The performance data presented appears to be the original validation data for the algorithm, supporting the claim that the renamed device retains its safety and effectiveness.

Acceptance Criteria and Reported Device Performance

Study Details

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

   • Test Set Sample Size: 50 subjects.
   • Data Provenance: Retrospectively obtained from 3 clinical sites:
     • Northwestern University, Chicago, USA
     • UC Davis, Sacramento, USA
     • Amsterdam UMC, Amsterdam, The Netherlands
   • Patient Characteristics: Adult surgical patients (cardiac and general surgery) over 18 years of age.

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

   • The document does not specify the number of experts used to establish the ground truth or their qualifications. The ground truth was established algorithmically based on physiological measurements.

3. Adjudication Method:

   • Not applicable/Not mentioned. The ground truth was established via a polynomial fit of CBFV-MAP data to determine LLA and ULA, and then a rule-based classification (Intact or Impaired) was applied. There's no indication of human adjudication of this ground truth.

4. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study:

   • No MRMC study was done, as this algorithm is not intended for human interpretation or direct assistance in a diagnostic image reading scenario. Its output is an index value representing a physiological state.

5. Standalone Performance:

   • Yes, a standalone performance evaluation was conducted. The study assessed the algorithm's ability to discriminate between "Intact" and "Impaired" cerebral autoregulation conditions based on its calculated CAI value, against a ground truth derived from physiological measurements (CBFV-MAP).

6. Type of Ground Truth Used:

   • Physiological Ground Truth: The ground truth for cerebral autoregulation status (Intact vs. Impaired) was established using a polynomial fit of Cerebral Blood Flow Velocity (CBFV) and Mean Arterial Pressure (MAP) data. Specifically, LLA (Lower Limit of Autoregulation) and ULA (Upper Limit of Autoregulation) were determined from this data, and an autoregulation status was assigned based on MAP's relationship to these limits:
     • Impaired: MAP ≤ LLA or MAP ≥ ULA
     • Intact: LLA

Ask a specific question about this device

The Anumana Low Ejection Fraction AI-ECG Algorithm is software intended to aid in screening for Left Ventricular Ejection Fraction (LVEF) less than or equal to 40% in adults at risk for heart failure. This population includes, but is not limited to:
· patients with cardiomyopathies

• patients who are post-myocardial infarction
• · patients with aortic stenosis
• · patients with chronic atrial fibrillation
• · patients receiving pharmaceutical therapies that are cardiotoxic, and
  • postpartum women.

Anumana Low Ejection Fraction Al-ECG Algorthm is not intended to be a stand-alone diagnostic device for cardiac conditions, should not be used for monitoring of patients, and should not be used on ECGs with a paced rhythm.

A positive result may suggest the need for further clinical evaluation in order to establish a diagnosis of Left Ventricular Ejection Fraction (LVEF) less than or equal to 40%. Additionally, if the patient is at high risk for the cardiac condition, a negative result should not rule out further non-invasive evaluation.

The Anumana Low Ejection Fraction AI-ECG Algorithm should be applied jointly with clinician judgment.

The Low Ejection Fraction AI-ECG Algorithm interprets 12-lead ECG voltage times series data using an artificial intelligence-based algorithm. The device analyzes 10 seconds of a single 12lead ECG acquisition, and within seconds provides a prediction of likelihood of LVEF (ejection fraction less than or equal to 40%) to third party software. The results are displayed by the third-party software on a device such as a smartphone, tablet, or PC. The Low Ejection Fraction AI-ECG Algorithm was trained to predict Low LVEF using positive and control cohorts, and the prediction of Low LVEF in patients is generated using defined conditions and covariates. The Low Ejection Fraction AI-ECG Algorithm device is intended to address the unmet need for a point-of-care screen for LVEF less than or equal to 40% and is expected to be used by cardiologists, front-line clinicians at primary care, urgent care, and emergency care settings, where cardiac imaging may not be available or may be difficult or unreliable for clinicians to operate. Clinicians will use the Low Eiection Fraction AI-ECG Algorithm to aid in screening for LVEF less than or equal to 40% and making a decision for further cardiac evaluation.

Here's a breakdown of the acceptance criteria and the study proving the device meets those criteria, based on the provided FDA 510(k) clearance letter for the Low Ejection Fraction AI-ECG Algorithm:

Low Ejection Fraction AI-ECG Algorithm: Acceptance Criteria and Performance Study

1. Table of Acceptance Criteria and Reported Device Performance

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

• Sample Size for Test Set: The clinical validation study included 16,000 patient records initially, though 2,040 records were excluded due to quality checks, resulting in a final analysis sample of 13,960 patient-ECG pairs.
• Data Provenance: The data was retrospective, collected from 4 health systems across the United States.

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

The document does not specify the number of experts or their qualifications used to establish the ground truth for the clinical validation test set. The ground truth (LVEF 40%) was derived from transthoracic echocardiogram (TTE) measurements. While TTE interpretation requires expertise, the document doesn't detail the method of expert review or consensus for these TTE results themselves for the test set.

4. Adjudication Method for the Test Set

The document does not specify an adjudication method (e.g., 2+1, 3+1) for the ground truth for the test set. The ground truth was established by TTE measurements.

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

No, a Multi-Reader Multi-Case (MRMC) comparative effectiveness study was not done. The study evaluated the standalone performance of the AI algorithm against a ground truth without human readers in the loop.

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

Yes, a standalone performance study was done. The reported sensitivity and specificity values are for the algorithm's performance alone in detecting low LVEF.

7. The Type of Ground Truth Used

The type of ground truth used for both training and validation was objective clinical measurements from Transthoracic Echocardiogram (TTE), specifically the Left Ventricular Ejection Fraction (LVEF) measurement. An LVEF of $\le$ 40% was defined as the disease cohort, and > 40% as the control cohort.

8. The Sample Size for the Training Set

The training set for the algorithm development consisted of 93,722 patients with an ECG and TTE performed within a 2-week interval. These were split into:

• Training dataset: 50% of the 93,722 patients.
• Tuning dataset: 20% of the 93,722 patients.
• Set-aside testing dataset: 30% of the 93,722 patients (used for internal validation during development, distinct from the independent clinical validation study).

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

The ground truth for the training set was established using LVEF measurements obtained from transthoracic echocardiograms (TTE). Specifically, for each patient, the LVEF measurement from the earliest TTE within a 2-week interval of an ECG was paired with the closest ECG recording. LVEF $\le$ 40% defined the disease cohort, and LVEF > 40% defined the control cohort. This data was identified from a research-use authorized clinical database from Mayo Clinic.

Ask a specific question about this device

The CorVista® System analyzes sensor-acquired physiological signals of patients presenting with cardiovascular symptoms (such as chest pain, dyspnea, fatigue) to indicate the likelihood of significant coronary artery disease. The analysis is presented for interpretation by healthcare providers in conjunction with their clinical judgment, the patient's signs, symptoms, and clinical history as an aid in diagnosis.

The CorVista® System is a non-invasive medical device system comprised of several hardware and software components that are designed to work together to allow a physician to evaluate the patient for the presence of cardiac disease, or cardiac disease indicators, using a static detection algorithm. The CorVista System has a modular design, where disease-specific "Add-On Modules" will integrate with a single platform, the CorVista Base System, to realize its intended use. The CorVista Base System is a combination of hardware, firmware, and software components with the functionality to acquire, transmit, store, and analyze data, and to generate a report for display in a secure web-based portal. The architecture of the CorVista Base system allows for integration with indication-specific "Add-Ons" which perform data analysis using a machine learned detection algorithm to indicate the likelihood of specific diseases at point of care. The CAD Add-On indicates the likelihood of significant Coronary Artery Disease (CAD). The analysis is presented for interpretation by healthcare providers in conjunction with their clinical judgment, the patient's signs, symptoms, and clinical history as an aid in diagnosis.

Here's a breakdown of the acceptance criteria and the study proving the CorVista® System meets them, based on the provided text:

1. Table of Acceptance Criteria and Reported Device Performance

The text does not explicitly state pre-defined acceptance criteria in a quantitative format (e.g., "Sensitivity >= X%"). Instead, it presents the device's performance results and implies that these results were deemed acceptable for substantial equivalence to the predicate device. The comparison to CCTA's "rule out performance" suggests a benchmark, but not a strict acceptance criterion.

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

• Test Set Sample Size: N = 1,816 subjects.
  • Population A (CAD+ for Sensitivity Testing): Number not specified, but this population was evaluated for sensitivity.
  • Population B (CAD- for Specificity Testing): Number not specified, but this population was evaluated for specificity.
• Data Provenance: Prospective, multicenter, non-randomized, repository study. The text does not explicitly state the country of origin, but given the FDA submission, it implicitly refers to data collected in the US.

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

The text states that the ground truth for CAD was established via "invasive catheterization (ICA)" or "core-lab adjudicated CTA."

• Number of Experts: Not explicitly stated for ICA or CTA adjudication.
• Qualifications of Experts: It implies that medical professionals performed the ICA, and a core-lab performed the CTA adjudication. The specific qualifications (e.g., number of years of experience for radiologists or cardiologists performing these procedures/adjudications) are not detailed.

4. Adjudication Method for the Test Set

The adjudication method for the ground truth was:

• For ICA: Clinical outcome from invasive coronary angiography. This is a direct, invasive diagnostic procedure.
• For CTA: "Core-lab adjudicated CTA." This implies a standardized process by a specialized lab, likely involving multiple readers or a defined quality control process, but the specific multi-reader method (e.g., 2+1, 3+1) is not provided.

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

• No, an MRMC comparative effectiveness study was not explicitly stated to have been done for human readers with and without AI assistance to assess improvement. The study described focuses on the standalone performance of the CorVista System compared to established diagnostic methods (ICA/CTA). The device is intended to be an "aid in diagnosis" used "in conjunction with their clinical judgment," but the study design presented does not evaluate the human-AI interaction in a comparative effectiveness study setting.

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

• Yes, a standalone performance study was done. The described clinical testing focuses on the algorithm's performance in indicating the likelihood of significant CAD by comparing its predictions to objective ground truth (ICA/CTA results). The reported sensitivity, specificity, and AUC-ROC are measures of the algorithm's standalone performance.

7. The Type of Ground Truth Used

• Objective Clinical Data / Outcomes Data: The ground truth for the test set was established by:
  • Invasive Coronary Angiography (ICA): This is considered a gold standard for diagnosing CAD.
  • Core-lab Adjudicated Coronary Computed Tomography Angiography (CTA): This is another strong diagnostic imaging modality, with the "core-lab adjudicated" aspect indicating a high level of rigor in interpretation.
    These methods directly determine the patient's actual CAD classification (CAD+ or CAD-).

8. The Sample Size for the Training Set

• The text states the ground truth for the "Model Training and Validation" was "Guideline-driven ground truth via invasive catheterization or core-lab adjudicated CTA." However, the specific sample size for the training set is not provided. The N=1,816 refers to the validation population (test set) used for performance testing.

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

• The ground truth for model training (and validation) was established using "Guideline-driven ground truth via invasive catheterization or core-lab adjudicated CTA." This implies that the same rigorous, objective diagnostic methods used for the test set's ground truth were also used to label the data utilized during the training and internal validation phases of the algorithm development.

Ask a specific question about this device

HemoSphere Advanced Monitor with HemoSphere Swan-Ganz Module:
The HemoSphere Advanced Monitor when used with the HemoSphere Swan-Ganz Module and Edwards Swan-Ganz Catheters is indicated for use in adult and pediatric critical care patients requiring monitoring of cardiac output [continuous (CO) and intermittent (iCO)] and derived hemodynamic parameters. Pulmonary artery blood temperature monitoring is used to compute continuous and intermittent CO with thermodilution technologies. It may also be used for monitoring hemodynamic parameters in conjunction with a perioperative goal directed therapy protocol in a hospital environment. Refer to the Edwards Swan-Ganz catheter indications for use statement for information on target patient population specific to the catheter being used. Refer to the Edwards Swan-Ganz catheter indications for use statement for information on target patient population specific to the catheter being used.
Refer to the Intended Use statement for a complete list of measured and derived parameters available for each patient population.

HemoSphere Advanced Monitor with HemoSphere Oximetry Cable:
The HemoSphere Advanced Monitor when used with the HemoSphere Oximetry catheters is indicated for use in adult and pediatric critical care patients requiring of venous oxygen saturation (SvO2 and ScvO2) and derived hemodynamic parameters in a hospital environment. Refer to the Edwards oximetry catheter indications for use statement for information on target patient population specific to the catheter being used.
Refer to the Intended Use statement for a complete list of measured and derived parameters available for each patient population.

HemoSphere Advanced Monitor with HemoSphere Pressure Cable:
The HemoSphere Advanced Monitor when used with the HemoSphere Pressure Cable is indicated for use in critical care patients in which the balance between cardiac function, fluid status, vascular resistance and pressure needs continuous assessment. It may be used for monitoring hemodynamic parameters in conjunction with a perioperative goal directed therapy protocol in a hospital environment. Refer to the Edwards FloTrac, Acumen IQ and TruWave DPT sensor indications for use statement for information on target patient population specific to the sensor being used. The Edwards Acumen Hypotension Index feature provides the clinician with physiological insight into a patient's likelihood of future hypotensive events (defined as mean arterial pressure 40 kg.
• When used with Medium Sensors, the ForeSight Oximeter Cable is indicated for use on pediatric subjects ≥3 kg.
• When used with Small Sensors, the ForeSight Oximeter Cable is indicated for cerebral use on pediatric subjects

The HemoSphere Advanced Monitoring platform was designed to simplify the customer experience by providing one platform with modular solutions for their hemodynamic monitoring needs. The user can choose from the available optional sub-system modules or use multiple sub-system modules at the same time. This modular approach provides the customer with the choice of purchasing and/or using specific monitoring applications based on their needs. Users are not required to have all of the modules installed at the same time for the platform to function.
HemoSphere Advanced Monitoring Platform, subject of this submission, consists of the HemoSphere Advanced Monitor that provides a means to interact with and visualize hemodynamic and volumetric data on the monitor screen and its five (5) optional external modules: the HemoSphere Swan-Ganz Module (K163381 cleared, April 14, 2017), the HemoSphere Oximetry Cable (K163381 cleared, April 14, 2017), HemoSphere Pressure Cable (K180881 Cleared, November 16, 2018), HemoSphere Technology Module (K213682 cleared, June 22, 2022), HemoSphere ForeSight Module (K213682, June 22, 2022), and the HemoSphere ClearSight Module (K203687 cleared, May 28, 2021). Additionally, the HemoSphere Advanced Monitoring Platform includes the Acumen Hypotension Prediction Index software feature (DEN160044 granted March 16, 2018) and the Acumen Assisted Fluid Management software feature (DEN190029 granted November 13, 2020). The HemoSphere Advanced Monitor also has wired and wireless capabilities, which was originally used only for connecting to a Hospital Information System (HIS) for data charting purposes. This capability is now used to allow it to stream continuously monitored data to the Viewfinder Remote, a mobile device-based application, for remote viewing the information (K211465, cleared July 8, 2021). The remotely transmitted data from the patient monitoring sessions include all hemodynamic parameter data and the associated physiological alarm notifications, historical trend data, and parameter waveform data.

HemoSphere Advanced Monitoring platform as cleared in K213682 cleared June 22, 2022, is being modified as follows:

1. Acumen Assisted Fluid Management Automated Fluid Tracking Mode:
   The AFM software feature (AFM algorithm + AFM GUI), which informs clinicians of patient fluid responsiveness (K213682, cleared June 22, 2022), allows for manual fluid tracking, and resides on the HemoSphere Advanced Monitor.
   The AFM software feature is being modified to allow for an automated fluid tracking mode as the default mode. Users can switch to the optional manual fluid tracking mode through the advanced settings menu. This automated fluid tracking mode for the AFM software feature is achieved via two components namely, the Acumen AFM Cable and the Acumen IQ fluid meter (both devices subject of this 510(k)). No modifications have been made to the previously cleared AFM algorithm. AFM GUI screens have been updated to account for the automated fluid tracking mode via the Acumen AFM cable and Acumen IO fluid meter.
   The Acumen AFM Cable is a reusable cable that connects the Acumen IO fluid meter to the HemoSphere Advanced Monitoring Platform and converts the flow rate received from the Acumen IQ fluid meter to total volume for the HemoSphere monitor to be used by AFM software feature. No modifications have been made to the previously cleared AFM algorithm. AFM GUI screens have been updated to account for the automatic fluid tracking mode. The Acumen IQ fluid meter is a sterile, single use device that measures the flow of fluid delivered to a patient through the intravenous line to which it is connected.
   When used together, the Acumen IQ fluid meter with the Acumen AFM Cable connected to a HemoSphere monitor, the fluid volume can be automatically tracked and displayed on the monitor as part of the AFM software feature screens.

2. Automatic Zeroing of the Heart Reference Sensor (HRS)
   The ClearSight Module (CSM), initially cleared in K201446 on October 1, 2020, is a non-invasive monitoring platform that includes a Pressure Controller (PC2) that is worn on the wrist, a Heart Reference Sensor (HRS), and the ClearSight/Acumen IQ Finger Cuffs.
   The Pressure Controller (also referred to as 'Wrist unit' or PC2) is connected to the patient via a wrist band. The Pressure Controller connects to the ClearSight Module (CSM) on one end and with the Heart Reference Sensor (HRS) and the finger cuff on the other. The connection to the CSM provides power and serial communication. The Pressure Controller is designed to control the blood pressure measurement process and send the finger arterial pressure waveform to the CSM. The CSM software transforms the finger level blood pressure measurements into the conventional radial blood pressure.
   In the predicate HemoSphere (K213682, cleared on June 22, 2022), as part of the ClearSight workflow, the user was required to zero the HRS prior to monitoring by aligning both ends of the HRS, the heart end and the finger end, and pressing the "0" button on the HemoSphere Graphical User Interface (GUI). After zeroing the HRS, the user is required to place both ends of the HRS in the appropriate location and then they can begin monitoring.
   For the subject device, the Pressure Controller (PC2) firmware has been updated to include a mathematical model that automatically calculates the zero offset of the HRS based on the age of the specific HRS at the time of use. With the addition of the mathematical model, the user is no longer required to zero the HRS prior to start of monitoring since the system now has the zero-offset calculated. As such, the HemoSphere Advanced Monitor graphical user interface (GUI) was updated to remove the Zero HRS step as part of the Zero & Waveform screen and ClearSight setup.
   The ClearSight Module firmware was also updated as part of support for the Automatic Zeroing of HRS feature. The firmware update included additional logging to support HRS calibration, bug fixes and updates to communication to the pressure controller to support display of proper HRS calibration information.

3. Patient Query
   As cleared in K213682, when the user queried for patient information, all patient records that match the search criteria were sent to the HemoSphere platform (from the Viewfinder Hub) for the user to review. With this update, only 30 records are shared at a time between the Viewfinder Hub and HemoSphere monitor.

4. Miscellaneous Updates
   Miscellaneous updates include:

• Bug fixes -
• Cybersecurity updates -
• Operator's manual updates -
• Heart Reference Sensor Instructions for Use update -

Based on the provided text, the document is a 510(k) Premarket Notification from the FDA to Edwards Lifesciences, LLC, regarding the HemoSphere Advanced Monitor and related components. It does not contain the detailed acceptance criteria and study proving device performance in the way typically required for AI/ML-driven diagnostic devices. This document focuses on demonstrating substantial equivalence to a predicate device, rather than proving a new clinical claim with a standalone performance study.

Therefore, many of the requested details about acceptance criteria, human expert involvement, ground truth, and training set information are not available in this specific regulatory document, as they are not typically required for a 510(k) submission for device modifications like those described here. The "Acumen Assisted Fluid Management software feature" is mentioned, and an "AFM algorithm" is referenced, but detailed studies on its performance metrics are not included in this summary.

Here's a breakdown of what can be extracted and what information is missing:

Acceptance Criteria and Device Performance Study (Partial Information)

This 510(k) notification describes modifications to an existing device (HemoSphere Advanced Monitoring Platform) and new components (Acumen AFM Cable, Acumen IQ fluid meter). The primary goal is to demonstrate substantial equivalence to a previously cleared predicate device (K213682). As such, the performance data presented is focused on verifying that the modifications do not adversely affect safety and effectiveness, rather than establishing new clinical performance metrics or comparing AI performance against human readers.

1. Table of Acceptance Criteria and Reported Device Performance

The document does not explicitly present a table of predetermined acceptance criteria for AI performance in the way one would for a new AI diagnostic claim (e.g., sensitivity, specificity, AUC). Instead, it lists various verification and validation activities performed to ensure the modified device functions as intended and remains safe and effective.

Summary of Performance Data Presented:

2. Sample Size and Data Provenance for Test Set

• Sample Size: Not specified for any quantitative testing that would typically involve a "test set" in the context of AI model validation (e.g., number of patient cases, number of images). The performance data cited are primarily bench simulations and system-level verification, not a clinical study with a patient test set.
• Data Provenance: Not specified, as no new clinical data or specific patient test sets are described. The reference to "bench simulation" suggests data generated in a lab environment.

3. Number of Experts and Qualifications for Ground Truth

• Not Applicable/Not Provided: Since "No new clinical testing was performed" for this 510(k), there is no mention of expert involvement for establishing ground truth on a clinical test set. The original AFM algorithm clearance (DEN190029) might contain this information, but it's not in this document.

4. Adjudication Method for Test Set

• Not Applicable/Not Provided: No clinical test set described.

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

• No: The document explicitly states, "No new clinical testing was performed." Therefore, no MRMC study was conducted or reported in this submission.

6. Standalone (Algorithm Only) Performance Study

• Partial/Limited: While the document mentions "AFM outputs when the fluid meter mode was unlocked... were tested using a bench simulation," it does not provide quantitative results (e.g., accuracy, precision) for the algorithm's performance in a standalone setting. The focus is on the functionality and safety of the hardware additions (cable, meter) and the automation of fluid tracking for an existing algorithm. The "core predictive algorithm for the Assisted Fluid Management software feature" is stated to be from the predicate device (K213682), which itself refers back to DEN190029.

7. Type of Ground Truth Used

• Not explicitly stated for AI performance: For the "bench simulation" of AFM outputs, the "ground truth" would likely be the known, controlled fluid flow rates programmed into the simulation. No external clinical ground truth (e.g., pathology, long-term outcomes) is described in relation to the AI/AFM performance in this document.

8. Sample Size for Training Set

• Not Provided: The document focuses on demonstrating substantial equivalence of modifications. Information about the training set size for the AI algorithm (Acumen Assisted Fluid Management software feature) would have been part of its original clearance (DEN190029), not this subsequent 510(k) for modifications and new hardware. It mentions: "No modifications have been made to the previously cleared AFM algorithm."

9. How Ground Truth for Training Set Was Established

• Not Provided: Similar to point 8, this information would pertain to the original clearance of the AFM algorithm (DEN190029) and is not detailed in this document.

Ask a specific question about this device

HemoSphere Advanced Monitor with HemoSphere Swan-Ganz Module: The HemoSphere Advanced Monitor when used with the HemoSphere Swan-Ganz Module and Edwards Swan-Ganz Catheters is indicated for use in adult and pediatric critical care patients requiring monitoring of cardiac output [continuous (CO) and intermittent (iCO)] and derived hemodynamic parameters. It may also be used for monitoring hemodynamic parameters in conjunction with a perioperative goal directed therapy protocol in a hospital environment. Refer to the Edwards Swan-Ganz catheter indications for use statement for information on target patient population specific to the catheter being used. Refer to the Intended Use statement below for a complete list of measured and derived parameters available for each patient population.

HemoSphere Advanced Monitor with HemoSphere Oximetry Cable: The HemoSphere Advanced Monitor when used with the HemoSphere Oximetry Cable and Edwards oximetry catheters is indicated for use in adult and pediatric crtical care patients requiring of venous oxygen saturation (SvO2 and Scv02) and derived hemodynamic parameters in a hospital environment. Refer to the Edwards oximetry catheter indications for use statement for information on target patient population specific to the catheter being used. Refer to the Intended Use statement for a complete list of measured and derived parameters available for each patient population.

HemoSphere Advanced Monitor with HemoSphere Pressure Cable: The HemoSphere Advanced Monitor when used with the HemoSphere Pressure Cable is indicated for use in critical care patients in which the balance between cardiac function, fluid status, vascular resistance and pressure needs continuous assessment. It may be used for monitoring hemodynamic parameters in conjunction with a perioperative goal directed therapy protocol in a hospital environment. Refer to the Edwards FloTrac, Acumen IQ and TruWave DPT sensor indications for use statement for information on target patient population specific to the sensor being used. The Edwards Lifesciences Acumen Hypotension Index feature provides the clinician with physiological insight into a patient's likelihood of future hypotensive events (defined as mean arterial pressure

The HemoSphere Advanced Monitoring platform was designed to simplify the customer experience by providing one platform with modular solutions for their hemodynamic monitoring needs. The user can choose from the available optional sub-system modules or use multiple sub-system modules at the same time. This modular approach provides the customer with the choice of purchasing and/or using specific monitoring applications based on their needs. Users are not required to have all of the modules installed at the same time for the platform to function. HemoSphere Advanced Monitoring Platform consists of the HemoSphere Advanced Monitor that provides a means to interact with and visualize hemodynamic and volumetric data on a screen and five (5) optional external modules: the HemoSphere Swan-Ganz Module (K163381 Cleared, April 14, 2017), the HemoSphere Oximetry Cable (K163381 Cleared, April 14, 2017), HemoSphere Pressure Cable (K180881 Cleared, November 16, 2018), HemoSphere Technology Module (K190205 August 29, 2019). HemoSphere ForeSight Module (K180003, May 10, 2018), and the HemoSphere ClearSight Module (K201446 Cleared October 1, 2020).

The provided FDA 510(k) summary (K221704) for the HemoSphere Advanced Monitoring Platform does not contain a table of acceptance criteria and reported device performance for the modifications made (specifically the Right Ventricular Pressure (RVP) algorithm). While it states that "All tests passed" and "demonstrated that the subject devices meet their predetermined design and performance specifications," specific numerical performance metrics and their corresponding acceptance criteria are not detailed in this document.

However, based on the information provided, here's a breakdown of the other requested information regarding the study supporting the device:

1. Table of Acceptance Criteria and Reported Device Performance

Not available in the provided document. The document states that "all performance verification and validation activities demonstrated that the subject devices meet their predetermined design and performance specifications" and "All tests passed," but it does not specify the quantitative acceptance criteria or the numerical results achieved by the device against those criteria.

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

The document states: "Clinical data (waveforms) were collected in support of the design and validation of the RVP algorithm."

• Sample Size for Test Set: Not specified. The document does not provide the number of patients or waveforms used for the clinical data collection for the RVP algorithm validation.
• Data Provenance: Not specified. The document does not mention the country of origin of the data or whether it was retrospective or prospective.

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

Not applicable/Not specified. The document mentions the collection of "clinical data (waveforms)" for the RVP algorithm validation, but it does not describe a process involving human experts to establish ground truth from this data. The RVP algorithm likely derives its parameters directly from physiological waveform data obtained from the Swan-Ganz Module and Pressure Cable, rather than relying on expert interpretation for ground truth.

4. Adjudication Method for the Test Set

Not applicable/Not specified. As there is no mention of human expert-established ground truth, an adjudication method is not described.

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

No. The document does not mention a Multi-Reader Multi-Case (MRMC) comparative effectiveness study, nor does it discuss human readers or AI assistance in a comparative context. The device focuses on monitoring physiological parameters rather than image interpretation or diagnostic tasks involving human readers.

6. Standalone (Algorithm Only) Performance Study

Yes, implicitly. The validation of the RVP algorithm described in the document is a standalone performance assessment. The statement "Clinical data (waveforms) were collected in support of the design and validation of the RVP algorithm" implies that the algorithm's performance was evaluated based on this collected data. The conclusion that the device "has successfully passed functional and performance testing, including software and algorithm verification and validation and bench studies" further supports that the algorithm's performance was assessed. However, specific standalone performance metrics are not provided.

7. Type of Ground Truth Used for the Test Set

The ground truth for the RVP algorithm's validation would be the physiological waveform data itself, specifically from the Swan-Ganz Module and Pressure Cable. The algorithm processes this raw physiological data to derive parameters like SYSRVP, DIARVP, MRVP, PRRVP, RV dp/dt, and RVEDP. The validation would involve comparing the algorithm's derived parameters against established methods or calculations from the same direct physiological measurements (e.g., from the Swan-Ganz catheter and pressure sensors).

8. Sample Size for the Training Set

Not specified. The document mentions "clinical data (waveforms) were collected in support of the design and validation of the RVP algorithm," but it does not differentiate between data used for design/training and data used specifically for validation (test set), nor does it specify the sample size for any such training.

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

Not specified/Not explicitly described. Given that the RVP algorithm processes physiological signals from existing, cleared hardware, the "ground truth" for any potential training would inherently be the raw physiological signals themselves, as measured by the Swan-Ganz Module and Pressure Cable. The algorithm's development would likely be based on established physiological principles and signal processing techniques to derive the mentioned RVP parameters. The document does not detail a specific "training set" or a separate process for establishing ground truth for training data beyond the intrinsic nature of the physiological measurements.

Ask a specific question about this device

HemoSphere Advanced Monitor with HemoSphere Swan-Ganz Module:

The HemoSphere Advanced Monitor when used with the HemoSphere Swan-Ganz Module and Edwards Swan-Ganz Catheters is indicated for use in adult and pediatric critical care patients requiring of cardiac output [continuous (CO) and intermittent (iCO)] and derived hemodynamic parameters. It may also be used for monitoring hemodynamic parameters in conjunction with a perioperative goal directed therapy protocol in a hospital environment. Refer to the Edwards Swan-Ganz catheter indications for use statement for information on target patient population specific to the catheter being used.

Refer to the Intended Use statement below for a complete list of measured and derived parameters available for each patient population.

HemoSphere Advanced Monitor with HemoSphere Oximetry Cable:

The HemoSphere Advanced Monitor when used with the HemoSphere Oximetry cable and Edwards is indicated for use in adult and pediatric crtical care patients requring of venous oxygen saturation (SvO2 and ScvO2) and derived hemodynamic parameters in a hospital environment. Refer to the Edwards oximetry catheter indications for use statement for information on target patient population specific to the catheter being used.

Refer to the Intended Use statement for a complete list of measured and derived parameters available for each patient population.

HemoSphere Advanced Monitor with HemoSphere Pressure Cable:

The HemoSphere Advanced Monitor when used with the HemoSphere Pressure Cable is indicated for use in critical care patients in which the balance between cardiac function, fluid status, vascular resistance and pressure needs continuous assessment. It may be used for monitoring hemodynamic parameters in conjunction with a perioperative goal directed therapy protocol in a hospital environment. Refer to the Edwards FloTrac, Acumen IQ and TruWave DPT sensor indications for use statement for information on target patient population specific to the sensor being used.

The Edwards Lifesciences Acumen Hypotension Prediction Index feature provides the clinician with physiological insight into a patient's likelihood of future hypotensive events (defined as mean arterial pressure

HemoSphere Advanced Monitoring Platform consists of the HemoSphere Advanced Monitor that provides a means to interact with and visualize hemodynamic and volumetric data on a screen and five (5) optional external modules: the HemoSphere Swan-Ganz Module (K163381 Cleared, April 14, 2017), the HemoSphere Oximetry Cable (K163381 Cleared, April 14, 2017), HemoSphere Pressure Cable (K180881 Cleared, November 16, 2018), HemoSphere Tissue Oximetry Module (K190205 August 29, 2019), and the HemoSphere ClearSight Module (K201446 Cleared October 1, 2020).

Acceptance Criteria and Device Performance for Edwards HemoSphere ClearSight Module

Based on the provided text, the Edwards HemoSphere ClearSight Module has undergone a modification to its existing APCO algorithm. The acceptance criteria and performance evaluation are related to ensuring this modification did not adversely affect the safety and effectiveness of the device, particularly concerning Cardiac Output accuracy.

1. Table of Acceptance Criteria and Reported Device Performance

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

• Sample Size: The text states that "retrospective analysis of clinical data from multiple independent datasets, comprised of data from patients over the age of 18 years" was used. However, a specific numerical sample size (e.g., number of patients or data points) is not provided in the document.
• Data Provenance: The data was "retrospective analysis of clinical data from multiple independent datasets." The country of origin of the data is not specified.

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

This information is not provided in the document. The text does not describe how the "ground truth" for the clinical data used in the retrospective analysis was established, nor does it mention the use of experts for this purpose.

4. Adjudication Method for the Test Set

This information is not provided in the document.

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study Was Done, If So, What Was the Effect Size of How Much Human Readers Improve with AI vs Without AI Assistance

A Multi-Reader Multi-Case (MRMC) comparative effectiveness study is not mentioned or described in the document. This study focuses on an algorithm modification for a medical device (HemoSphere ClearSight Module) measuring physiological parameters, not on human reader performance with or without AI assistance.

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

Yes, a standalone performance evaluation of the algorithm was done. The "Algorithm Verification (Clinical Performance Data)" section specifically states: "Algorithm performance was tested using clinical data." This indicates an evaluation of the algorithm's performance independent of real-time human interaction.

7. The Type of Ground Truth Used (Expert Consensus, Pathology, Outcomes Data, etc.)

The document refers to the evaluation of "Cardiac Output accuracy." For a device that measures physiological parameters like Cardiac Output, the "ground truth" would typically refer to a gold standard measurement technique for that parameter. However, the exact gold standard method used to establish the ground truth for Cardiac Output in the clinical data is not explicitly stated in the provided text. It implies the use of "clinical data" which would have reference measurements for comparison but does not detail the nature of these reference measurements.

8. The Sample Size for the Training Set

The document only mentions "retrospective analysis of clinical data" for testing the algorithm modification. It does not provide any information regarding a "training set" or its sample size. This suggests that the modification might have been made to an existing algorithm, and the focus of this submission is on verifying the impact of that modification using a test set, rather than developing a new algorithm from scratch requiring a separate training set.

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

Since no training set is mentioned, this information is not provided in the document.

Ask a specific question about this device