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Alio is a wireless remote monitoring system intended for use by healthcare providers (HCP) to collect physiological data in clinical and non-clinical settings. The data includes measured hemoglobin (Hgb) and hematocrit (Hct), skin temperature, auscultation sound data, and heart rate. Data is transmitted wirelessly from the SmartPatch wearable sensor to a web-based portal for the HCP's review.

The data also include a qualitative indicator of abnormal levels of potassium derived from relative variability of photoplethysmography waveforms and medically accepted threshold values.

Alio is intended for use on general care patients who are 18 years of age or older. The SmartPatch sensor is indicated to provide measurement of heart rate, skin temperature, Hgb, Hct and a qualitative risk assessment of the patient having an abnormal potassium level. The SmartPatch sensor is indicated to record and transmit auscultation sound data. For qualitative assessment of abnormal potassium levels, and quantitative measurement of heart rate, skin temperature, Hgb and Hct, the SmartPatch should be placed on an arm based arteriovenous access on patients with end stage kidney disease (ESKD).

Alio is a secondary, adjunct patient monitor and is not intended to replace existing standard-of-care patient monitoring practices. Therapeutic management decisions, including management of dyskalemia, should be made based on a complete assessment of the patient's condition and should not be based solely on Alio.

Alio is a wireless remote monitoring system intended for use by healthcare providers (HCP) to collect physiological data in clinical and non-clinical settings. Alio is intended to be used on general care patients and patients with end stage kidney disease (ESKD), who are 18 years of age or older in clinical and non-clinical settings. Alio includes the following components:

Alio SmartPatch: The Alio SmartPatch is a flexible, silicone-encased patch designed to be worn between the cannulation sites of the arteriovenous (AV) fistula or graft for up to seven days. It houses numerous sensor technologies which collect data for the derivation of physiologic parameters including hemoglobin, hematocrit, an assessment of normal or abnormal (hyper or hypokalemic) levels of serum potassium (K+), skin temperature, auscultation sound data, and heart rate. The data from the sensors is transmitted from the SmartPatch to the Alio Hub via a bluetooth connection. The data is then transmitted to the Alio Cloud, via the Alio Hub, where it is analyzed and made available to a clinical care team via the Alio Portal.

Alio Hub: The Alio Hub is designed for use in clinical and non-clinical use settings. It automatically communicates with the activated Alio SmartPatch via Bluetooth and uploads physiological data to the Alio Cloud via cellular connection.

Alio Cloud: The Alio Cloud allows clinicians to access patient data collected via the Alio SmartPatch and wirelessly transferred from the Alio Hub to the secure server (the Alio Cloud).

Alio Portal: The Alio Portal stores data received from the Alio Cloud database that supports storage, analytics, system monitoring and visualization capabilities. This data is encrypted and HIPAA compliant. The Alio Portal also serves as the interface with the HCP who can then visualize and interact with data being generated by the system.

The provided text describes the Alio device, its intended use, and summaries of non-clinical and clinical testing performed for its 510(k) submission (K223073).

Unfortunately, the provided text does not contain the specific acceptance criteria or detailed study results (like sensitivity, specificity, accuracy metrics with confidence intervals for Hgb, Hct, or potassium levels) in a format suitable for a table of acceptance criteria vs. device performance. It broadly states that the device "meets its design requirements and intended use" and "can accurately assess abnormal potassium levels and measure hemoglobin (Hgb) and hematocrit (Hct)."

Therefore, I cannot directly provide a table of acceptance criteria and reported device performance as requested. I can, however, extract and summarize the other requested information based on the provided text.

Here's a summary of the available information regarding the Alio device's clinical study:

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

• Acceptance Criteria: Not explicitly stated in the provided text. The document indicates that the device "meets its design requirements and intended use" and "can accurately assess abnormal potassium levels and measure hemoglobin (Hgb) and hematocrit (Hct)." However, specific numerical thresholds for accuracy, sensitivity, or specificity as acceptance criteria are not detailed.
• Reported Device Performance:
  • The study "establish[ed] the accuracy of Alio in the assessment of abnormal potassium levels, and measurement of Hgb and Hct, compared to the standard of care blood results and heart rate."
  • "The results of the study demonstrate that Alio can accurately assess abnormal potassium levels and measure hemoglobin (Hgb) and hematocrit (Hct) when placed on an arteriovenous access site in patients with ESKD."
  • "The results further confirm that Alio can still accurately measure heart rate and record auscultation sound data at the new location."
  • No specific performance metrics (e.g., mean absolute error, correlation coefficients, sensitivity, specificity, AUC) or their numerical values are provided in this summary document.

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

• Sample Size for Test Set: 125 subjects.
• Data Provenance:
  • Country of Origin: Not explicitly stated, but the study was described as a "multicenter, prospective study." Given the FDA submission, it's highly likely to be U.S.-based, but this is an inference, not a direct statement.
  • Retrospective or Prospective: Prospective. The text states: "An IRB-approved clinical study has been conducted to validate the ability of Alio to quantify the new measurements and support the proposed expanded indications. Alio was studied in a multicenter, prospective study with 125 subjects."

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

• This information is not provided in the text. The ground truth was established by "standard of care blood results" for Hgb and Hct, and for abnormal potassium levels, but the expertise involved in interpreting these and deriving final ground truth labels is not specified.

4. Adjudication method for the test set

• This information is not provided in the text.

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 described. The study focused on the accuracy of the device in assessing physiological parameters compared to standard of care, not on human reader performance with or without AI assistance. The device is described as a "secondary, adjunct patient monitor," suggesting it aids, but does not necessarily directly compare, human diagnostic performance.

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

• Yes, the described study appears to be a standalone performance evaluation of the Alio device's algorithm. The "AI/ML algorithm used in the calculation of the new physiologic parameters" is specifically mentioned. The study assessed the device's ability to "accurately assess abnormal potassium levels, and measure hemoglobin (Hgb) and hematocrit (Hct)" against "standard of care blood results." This implies the algorithm's output was directly compared to ground truth, which is characteristic of a standalone study.

7. The type of ground truth used

• For Hemoglobin (Hgb) and Hematocrit (Hct): "standard of care blood results."
• For Abnormal Potassium Levels: "standard of care blood results." The study objective was to establish accuracy compared to "standard of care blood results."
• For Heart Rate: "standard of care blood results" (implied as part of the comparison, though usually heart rate ground truth comes from ECG or other direct measurements). The text states "compared to the standard of care blood results and heart rate," which might imply different methods for heart rate ground truth.
• The study stated it evaluated patients within "defined Hgb and Hct reference ranges (7-15 g/dL Hgb, 21-45% Hct)." This suggests quantitative comparison with clinical lab values.

8. The sample size for the training set

• The sample size for the training set is not provided. The text only mentions the clinical study for validation (test set) with 125 subjects. The AI/ML algorithm's training data is not described.

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

• This information is not provided, as the training set details are absent from this summary.

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The Alio Medical Remote Monitoring System is a wireless remote monitoring system intended for use by healthcare professionals to intermittently collect physiological data in home use settings. The data includes skin temperature, auscultation sound data and heart rate. Data is transmitted wirelessly from the SmartPatch wearable sensor to a web-based portal for the healthcare provider's (HCP) review.

The Alio Medical RMS is intended for use on general care patients who are 18 years of age or older. The SmartPatch sensor is indicated to measure skin temperature and pulse rate where clinically indicated. The SmartPatch sensor is indicated to record and transmit auscultation sound data where clinically indicated.

The device is not intended for use in critical care or other high-acuity environments. The Alio Medical RMS is a secondary, adjunct patient monitor and is not intended to replace existing standard-of-care patient monitoring practices.

Alio Medical Remote Monitoring System, or "Alio Medical RMS", utilizes a wearable device (SmartPatch) on the skin to gather physiological data and then transmits it to a device (Bedside Hub) located in the subject's home. The Bedside Hub then relays this raw data to the Alio Medical Cloud where it is processed and analyzed using Alio's proprietary algorithms. Data is accessible to Healthcare Professionals and the Alio clinical team via a web-based Clinician Portal. The SmartPatch and Bedside Hub are intended to be used on general care patients who are 18 years of age or older in a non-clinical environment. The web-based Clinical Portal is to be used by healthcare professionals in an office environment.

The Alio Medical Remote Monitoring System includes the following components:

• SmartPatch
• Bedside Hub
• Alio Medical Cloud (backend only - not user facing)
• Clinician Portal

SmartPatch: A flexible, silicone-encased patch that can be worn where clinically indicated for up to seven days at a time. It houses numerous sensor technologies, which include a microphone, accelerometer, temperature sensors, and a PPG sensors collect physiological data including skin temperature, auscultation sound data, and heart rate. Data is transmitted to the Cloud, via the Hub, where it is analyzed and sent to a Healthcare Professional via the Web Portal.

Bedside Hub: The Bedside Hub has the form and finish of an at-home device. It automatically communicates with the activated SmartPatch and uploads physiological data to the Alio Medical Cloud.

Alio Medical Cloud: The Cloud features a database that supports storage, analytics, system monitoring and visualization capabilities. The Alio Medical Cloud is encrypted and HIPAA compliant. All patient data is fully traceable to device and patient ID via the database.

Clinician Portal: The Clinician Portal is the interface tool between a user (healthcare professional users only) and the system that enables the user to visualize and interact with data being generated by the system.

The provided text is a 510(k) summary for the Alio Medical Remote Monitoring System. It details the device's indications for use, components, and a comparison to predicate and reference devices, as well as listing compliance with various safety and performance standards. However, it does not contain the specific acceptance criteria or the study data that proves the device meets those criteria.

The section titled "9. Performance Data" states that "Nonclinical verification and validation test results established that the device meets its design requirements and intended use, that it is as safe, as effective, and performs as well as the predicate devices, and that no new issues of safety and effectiveness were raised." It also mentions "extensive safety and performance testing as shown in the test results provided in this submission."

Despite these statements, the actual acceptance criteria, reported device performance (e.g., accuracy metrics for heart rate or temperature), sample sizes, ground truth establishment, or details of a multi-reader multi-case study are not included in this summary. The summary focuses on regulatory compliance and substantial equivalence argument rather than detailed performance study results against specific criteria.

Therefore, I cannot populate the requested table and answer many of the questions based solely on the provided text. To fulfill the request, one would need access to the full submission documents, specifically the detailed performance study reports.

Based on the provided text, the following information is available (and what is not):

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

• Not provided in the text. The text only generally states that "the device meets its design requirements and intended use." Specific numerical acceptance criteria for measured parameters (skin temperature, auscultation sound, heart rate) and corresponding achieved performance values are absent.

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

• Not provided in the text. The text mentions "extensive safety and performance testing" but does not specify the sample sizes of patients or data points for any performance tests. Data provenance is also not mentioned.

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

• Not provided in the text. No information about expert involvement in establishing ground truth is present.

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

• Not provided in the text. No details on adjudication methods for test sets are mentioned.

5. If a multi reader multi case (MRMC) comparative effectiveness study was done, If so, what was the effect size of how much human readers improve with AI vs without AI assistance:

• Not applicable/Not mentioned. The device described is a "remote monitoring system" that collects physiological data for review by HCPs. It is not an AI-powered diagnostic imaging device typically subject to MRMC studies comparing human reader performance with and without AI assistance. The text does not describe any AI component that directly assists in human interpretation or diagnosis.

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

• Partially inferred/Limited information: The system uses "Alio's proprietary algorithms" to process and analyze raw data in the Alio Medical Cloud. While a standalone algorithm performance evaluation would logically be done internally to ensure accuracy of processed data (heart rate, temperature, sound data), the detailed results of such a standalone performance or how its accuracy was quantitatively measured against a gold standard are not provided in this summary. The stated function is to transmit data for HCP review, implying the algorithm's role is data processing rather than a standalone diagnostic output.

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

• Not provided in the text. The method for establishing ground truth for any measurements (e.g., a clinically validated temperature probe for skin temperature, or a gold standard ECG for heart rate) is not detailed.

8. The sample size for the training set:

• Not applicable/Not provided. While the system uses "proprietary algorithms," the document does not explicitly state that these algorithms are machine learning models requiring "training sets" in the typical sense. Even if they are, the training set size is not mentioned.

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

• Not applicable/Not provided. As with the training set itself, the method for establishing ground truth for any potential training data is not mentioned.

In summary, the provided 510(k) summary serves as a high-level overview for regulatory purposes, demonstrating substantial equivalence. It does not delve into the detailed technical performance study results, acceptance criteria, or statistical validations typically found in comprehensive study reports.

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