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The AHI System is intended for use by healthcare professionals managing patients 18 years or older who are receiving continuous physiological monitoring with electrocardiography (ECG) in hospitals.

AHI provides a frequently updated binary output over time based on pattern analysis of a lead-II ECG waveform intended to describe a patient's hemodynamic status and indicate if a patient is showing signs of hemodynamic stability or instability. Signs of hemodynamic instability (HI) are defined as hypotension (systolic blood pressure

The AHI System is a multiparameter system designed to meet clinicians' need to identify patient hemodynamic status and predict patient hemodynamic instability episodes using two analytics:1. Analytic for Hemodynamic Instability (AHI): Utilizing data from a single existing lead of a non-invasive electrocardiograph (ECG), AH analyzes heart rate variability (HRV) and ECG morphology features to rapidly detect signs of hemodynamic stability and categorize each window of data as either "AHI Stable" or "AHI Unstable." Time trending of AHI outputs is also provided.

2. Analytic for Hemodynamic Instability Predictive Indicator (AH-P); Utilizing AH outputs from up to the most recent 30 minutes of EG data, AH-PI indicates the likelihood of a future episode of hemodynamic instability, defined as ten continuous minutes or more where signs of hemodynamic instability are present.

The provided text details the FDA clearance for the AHI System (v 2.2.0) and references a previous version (K212219) as the predicate device. However, the document primarily focuses on regulatory approval and equivalence, not on a detailed study proving the device meets specific acceptance criteria with performance metrics, sample sizes, expert qualifications, or ground truth establishment.

Therefore, many of the requested details about the study proving the device meets acceptance criteria are not present in the provided text. The text only vaguely refers to "Software: Software verification and validation testing were conducted and documentation was provided... Testing was conducted to ensure the AHI System works as designed." This is insufficient to populate the requested table and further study details.

Based on the provided text, here's what can be extracted and what is missing:

1. Table of Acceptance Criteria and Reported Device Performance

The provided text does not include a table of acceptance criteria or reported device performance metrics such as sensitivity, specificity, or AUC for the AHI System (v 2.2.0) or its predicate. It only states the device "works as designed" following software V&V.

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

The provided text does not specify the sample size used for any test set or the provenance (e.g., country of origin, retrospective/prospective) of the data.

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

The provided text does not mention the number or qualifications of experts used to establish ground truth for any test set.

4. Adjudication Method for the Test Set

The provided text does not describe any adjudication method (e.g., 2+1, 3+1, none) for a test set.

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

The provided text does not indicate that an MRMC comparative effectiveness study was done, nor does it provide any effect size for human reader improvement with or without AI assistance.

6. Standalone Performance Study

While the device's function (AHI and AHI-PI) is described as "pattern analysis of a lead-II ECG waveform" to indicate hemodynamic status and predict instability, the document does not provide the results of a standalone (algorithm only) performance study with specific metrics. It states "Testing was conducted to ensure the AHI System works as designed," which is a high-level statement without data.

7. Type of Ground Truth Used for the Test Set

The "Signs of hemodynamic instability (HI)" are defined within the Indications for Use as "hypotension (systolic blood pressure

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The AHI System is intended for use by healthcare professionals managing patients 18 years or older who are receiving continuous physiological monitoring with electrocardiography (ECG) in hospitals.

AHI provides a frequently updated binary output over time based on pattern analysis of a lead-II ECG waveform intended to describe a patient's hemodynamic status and indicate if a patient is showing signs of hemodynamic stability or instability. Signs of hemodynamic instability (HI) are defined as hypotension (systolic blood pressure

The AHI System is a multiparameter system designed to meet clinicians' need to identify patient hemodynamic status and predict patient hemodynamic instability episodes using two analytics:

1. Analytic for Hemodynamic Instability (AHI) (as granted in DEN200022): Utilizing data from a single existing lead of a non-invasive electrocardiograph (ECG), AHI analyzes heart rate variability (HRV) and ECG morphology features to rapidly detect signs of hemodynamic stability or instability and categorize each window of data as either "AHI Stable" or "AHI Unstable." Time trending of AHI outputs is also provided.

2. Analytic for Hemodynamic Instability Predictive Indicator (AHI-PI): Utilizing AHI outputs from up to the most recent 30 minutes of ECG data, AHI-PI indicates the likelihood of a future episode of hemodynamic instability, defined as ten continuous minutes or more where signs of hemodynamic instability are present.

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

1. Table of Acceptance Criteria and Reported Device Performance

• Low Risk (Green): 0.7% (CI: 0.4%, 1.3%)
• Moderate Risk (Yellow): 6.5% (CI: 3.7%, 10.3%)
• High Risk (Red): 35.9% (CI: 28.1%, 44.0%) |
  | Likelihood of HI compared to Low Risk | - Moderate Risk: 9x more likely to have an episode of HI in the next 1 hour than Low Risk.
• High Risk: 51x more likely to have an episode of HI in the next 1 hour than Low Risk. |
  | Prediction of patient deterioration (among those who had HI) | 89% of cases correctly predicted. |
  | Lead Time for Prediction | Median lead time of 48 minutes. |
  | Clinical Benefit | Demonstrate significant discrimination between risk of future hemodynamic instability events, providing adjunctive information to clinicians to facilitate fewer missed diagnoses of emerging HI/patient deterioration. |

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

• Sample Size: 65,969 "windows" (data points representing a period of time for which an AHI-PI indicator was generated). The exact number of patients is not explicitly stated, but the note mentions: "The unit of analysis here is at the windows level and not the patient level." The study used bootstrapping to account for multiple measurements per subject.
• Data Provenance: Prospectively collected from consecutive patients at Michigan Medicine. This indicates the data is from the United States and is prospective.
• Targeted Patient Population: Hospitalized patients 18 years or older who are receiving continuous physiological monitoring with electrocardiography (ECG) and are not contraindicated. Due to study design considerations, the primary study population was limited to patients who were invasively monitored with an arterial line.

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 the ground truth for the test set.

4. Adjudication Method for the Test Set

• The document does not mention an adjudication method for the test set.

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 MRMC comparative effectiveness study is mentioned for the AHI-PI system. The study focuses on the standalone performance of the AHI-PI algorithm. The device is intended for "adjunctive use" meaning it supports human healthcare professionals, but specific studies on human improvement with AI assistance are not described here.

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

• Yes, a standalone performance study was done for the AHI-PI. The reported data in the table directly reflects the algorithm's ability to predict hemodynamic instability without human intervention in the prediction process itself. The study compared AHI-PI outputs to a vital signs reference standard.

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

• Outcomes Data/Physiological Reference Standard: The ground truth for hemodynamic instability (HI) was defined using a "hemodynamic vital signs reference standard" based on continuous vital signs:
  • Hypotension (systolic blood pressure

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