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The Redsense device is intended to monitor for potential blood loss from the hemodialysis access site in hemodialysis patients undergoing hemodialysis treatment. The device includes a blood sensor incorporated into a sensor patch. The sensor monitors potential blood leakage from the venous needle blood access via a light signal and will alarm if blood leakage is detected by the device's sensor.

Redsense Medical provides a system for monitoring the blood access during haemodialysis consisting of an alarm unit and a sensor connected to a specifically developed patch. The Redsense Patch uses integrated optic fibers to detect blood leakage from wounds. The optic fiber is connected to the sensor and alarm unit. If blood leakage occurs during haemodialysis, the patch surrounding the vein needle registers the event and changes a light signal to the alarm unit. This immediately activates a light and an alarm signal. Thus if a vein needle comes out of place extensive blood leakage is prevented.

Acceptance Criteria and Device Performance Study for Redsense Alarm System

The Redsense Alarm System (K130554) is a device intended to monitor for potential blood loss from the hemodialysis access site during hemodialysis treatment. The device includes a blood sensor incorporated into a sensor patch that detects blood leakage via a light signal and alarms if detected.

1. Acceptance Criteria and Reported Device Performance

The core functional acceptance criteria for the Redsense Alarm System are primarily based on sound output level and compliance with relevant electrical and EMC standards. The device's ability to detect blood is validated through non-clinical testing.

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

The provided document does not describe a specific test set with human subjects for the K130554 device's performance evaluation. The device's performance for blood detection was validated in "nonclinical test." The clinical evidence for the intended use and safety for the subject device (K130554) relies on previous clinical data from a predicate device (K071013).

Regarding the "user evaluation" mentioned:

• Sample Size: Not specified.
• Data Provenance: Not specified, but based on "user feedback," it is likely retrospective or observational use of the predicate device (K071013) that informed design changes for K130554, and potentially some limited prospective evaluation for the K130554 to confirm users "can handle the device and understand its use."

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

This information is not provided as the primary performance validation for blood detection was non-clinical. For the "user evaluation," no details are given about experts or their role in establishing ground truth.

4. Adjudication Method for the Test Set

This information is not provided as there is no detailed description of a clinical test set for K130554's performance.

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

There was no MRMC comparative effectiveness study described for the Redsense Alarm System (K130554) or its predicate devices. The device is an alarm system, not an interpretive diagnostic tool that involves human readers.

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

The device's core function is an automated alarm for blood leakage. The "ability to detect blood is validated in nonclinical test." This suggests a form of standalone performance evaluation for the sensor and alarm mechanism without direct human intervention as part of the detection process. However, the details of this non-clinical test are not provided.

7. Type of Ground Truth Used

• For blood detection (non-clinical test): The "ground truth" would have been established by controlled simulations of blood leakage under laboratory conditions, using known quantities and types of blood or blood-like substances to trigger the device's sensor.
• For the clinical evidence (derived from K071013): This would have involved actual patient outcomes and observations of blood loss instances in a clinical setting.

8. Sample Size for the Training Set

This information is not provided. The Redsense Alarm System appears to be based on a deterministic optical principle rather than a machine learning model that typically requires a "training set." The development of its algorithm would be based on engineering specifications and empirical testing.

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

As noted above, the concept of a "training set" in the context of machine learning does not readily apply to the described device. The "ground truth" for the device's development and validation would have been established through:

• Engineering specifications and physics: Understanding the optical properties of blood and how light interacts with it.
• Empirical testing and calibration: Testing the sensor's response to various concentrations and types of blood in a controlled environment to calibrate its sensitivity and alarm thresholds. This would involve creating controlled blood leakage scenarios and confirming the device's triggering mechanism.

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The Redsense device is intended to monitor for potential blood loss from the hemodialysis access site in hemodialysis patients undergoing continuous hemodialysis treatment up to 8 hours in the clinical settings. The device includes a blood sensor incorporated into an adhesive sensor patch. The sensor monitors potential blood leakage from the venous needle puncture site via an infrared light and will alarm if blood leakage is detected via absorption onto the device's sensor patch.

Redsense is a system for monitoring the vein needle during hemodialysis. Redsense consists of an alarm unit and optical sensor incorporated into an adhesive patch. The patch with the sensor is placed over the vein needle and detects any blood that drips onto the patch if the needle has been accidentally pulled out or if there is leakage during dialysis. If blood loss is detected, the device will alarm.

The provided text describes a 510(k) premarket notification for the Redsense Alarm Unit for Clinical Use, Model RA-1-RA001C. The submission's purpose is to expand the intended use of the device for up to 8 hours of clinical use, compared to the previously cleared 5 hours.

Here's an analysis of the acceptance criteria and the study that proves the device meets them, based only on the provided text:

1. Table of Acceptance Criteria and Reported Device Performance:

The document does not explicitly state quantitative acceptance criteria (e.g., specific sensitivity, specificity, or false alarm rates) or numerical performance metrics for the device. Instead, the "Summary of Testing" broadly states that "Test results met the requirements of the standards used for testing."

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

The document does not specify the sample size used for the test set or the data provenance (e.g., country of origin, retrospective or prospective). It simply refers to "Verification testing."

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

The document does not provide any information regarding the number of experts, their qualifications, or how ground truth was established for the test set.

4. Adjudication Method for the Test Set:

No information is provided about any adjudication method (e.g., 2+1, 3+1, none) for the test set.

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

No, the document does not mention an MRMC comparative effectiveness study, nor does it discuss the effect size of human readers improving with AI vs. without AI assistance. The Redsense device is described as a standalone alarm system, not an AI-assisted diagnostic tool for humans.

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

Yes, the device described is a standalone alarm unit. The description of its function ("will alarm if blood leakage is detected via absorption onto the device's sensor patch") indicates it operates independently to detect blood loss and trigger an alarm without requiring human interpretation of its internal detection mechanism. The verification testing would have assessed this standalone performance.

7. The Type of Ground Truth Used:

The document does not explicitly state the type of ground truth used for the verification testing. Given the nature of the device (detecting blood leakage), it's highly probable that the ground truth would involve simulated or actual blood leakage events under controlled conditions, with the "true positive" of blood presence verified through direct observation or precise measurement. It is unlikely to be pathology, expert consensus in the diagnostic sense, or outcomes data for this type of device function.

8. The Sample Size for the Training Set:

The document does not refer to a "training set" or "training data." This is consistent with the device being a hardware-based sensor and alarm system, rather than a machine learning or AI algorithm that typically requires a training phase. The "verification testing" described is for demonstrating the device's functional performance against specifications.

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

As no training set is mentioned, there is no information on how its ground truth would have been established.

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The Redsense device is intended to monitor for potential blood loss from the hemodialysis access site in hemodialysis patients undergoing hemodialysis treatment up to 5 hours at home or in the clinical setting. The device includes a blood sensor incorporated into an adhesive dressing. The sensor monitors potential blood leakage from the needle puncture via an infrared light and will alarm if needle dislodgement or blood leakage is detected.

All use must be administrated under physician's prescription, and must be observed by a trained and qualified person considered to be competent in the use of this device by the prescribing physician.

Redsense Home Use is a system for monitoring the vein or arterial needle during hemodialysis. Redsense consists of an alarm unit and optical sensor incorporated into an adhesive patch. The patch with the sensor is placed around the vein needle and detects any blood that drips onto the patch if the needle has been accidentally pulled out or if there is leakage during dialysis. If blood loss is detected, the device will alarm.

Here's a breakdown of the acceptance criteria and study information for the Redsense - Home Use device, organized by your requested points:

1. Table of Acceptance Criteria and Reported Device Performance

The provided document describes the types of tests performed and their general success, rather than specific numerical acceptance criteria for performance metrics like sensitivity or specificity. The focus is on demonstrating that the device meets safety and functionality requirements for home use.

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

• Sample Size for User Evaluation (Test Set): 8 patients
• Data Provenance: Sweden (patients undergoing self-dialysis at a clinic or home dialysis in Sweden). The study was a prospective user evaluation of the device in its intended use environment.

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

The document does not explicitly state the number of experts or their specific qualifications for establishing ground truth in the user evaluation. The user evaluation focused on patient usability and false alarm rates, not on the diagnostic accuracy against an independent "gold standard" truth. It mentions that use "must be observed by a trained and qualified person considered to be competent in the use of this device by the prescribing physician," implying supervision, but not a panel of experts for ground truth assessment in the study itself.

4. Adjudication Method for the Test Set

The document does not describe a formal adjudication method (like 2+1 or 3+1). The user evaluation for false alarms and warnings likely relied on observations by the patients themselves and/or the "trained and qualified person" overseeing the treatment, rather than a blinded expert panel adjudication process for each event.

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 involving human readers and AI assistance was not performed. This device is a standalone blood loss detection system, not an AI-assisted diagnostic tool that aids human interpretation.

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

Yes, the primary evaluation of the Redsense device, particularly the alarm capabilities (audible, visual, and detection of blood leakage), represents a standalone performance assessment. The user evaluation then confirmed that this standalone device functioned appropriately in the home-use context with actual patients, but the core detection and alarming are performed by the algorithm/sensor itself without human intervention in the detection process.

7. The Type of Ground Truth Used

• For the audible and visual alarm tests, the "ground truth" was defined by the requirements outlined in "Class II Special Controls Guidance Document: Apnea Monitors" and ISO 9703-1:1992.
• For the user evaluation, the "ground truth" related to device functionality (e.g., whether it could be used by patients, if instructions were sufficient, whether false alarms increased, or if adverse effects occurred) was established through direct observation during home or clinic dialysis and patient feedback. The "blood loss detection" aspect's ground truth would have been real or simulated blood leakage events (though specifics aren't detailed in the provided excerpt for the home use study; it only states detection if "blood loss is detected").

8. The Sample Size for the Training Set

The document does not provide information about a "training set" for an algorithm. This device is an alarm system based on sensor detection (infrared light detecting blood), rather than a machine learning model that requires a discrete training phase.

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

As there is no explicit mention of a training set or a machine learning algorithm, information on how ground truth was established for a training set is not applicable or provided in the given text. The device's operation is based on a direct physical principle (infrared light detection of blood).

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The Redsense device is intended to monitor for potential blood loss from the hemodialysis access site in hemodialysis patients undergoing continuous hemodialysis treatment up to 5 hours in the clinical setting. The device includes a blood sensor incorporated into an adhesive sensor patch. The sensor monitors potential blood leakage from the venous needle puncture site via an infrared light and will alarm if blood leakage is detected via absorption onto the device's sensor patch.

Redsense is a system for monitoring the vein or arterial needle during hemodialysis. Redsense consists of an alarm unit and infrared sensor incorporated into an adhesive patch. The patch with the sensor is placed around the vein or arterial needle and detects any blood that drips onto the patch if the needle has been accidentally pulled out or if there is leakage during dialysis. If blood loss is detected, the device will alarm.

Here's a summary of the acceptance criteria and study information for the Redsense device, based on the provided text:

1. Table of Acceptance Criteria and Reported Device Performance

The provided document does not explicitly state quantitative acceptance criteria for the Redsense device's performance. Instead, it indicates that "Verification testing has been performed to verify that the Redsense device fulfills the Requirement Specifications" and "Results showed the device functioned successfully in the clinical environment."

Based on the device's functional description, the primary performance metric would be its ability to detect blood leakage and alarm. The closest stated performance characteristic is:

2. Sample Size for the Test Set and Data Provenance

• Sample Size for the Test Set: Not explicitly stated. The document mentions "clinical testing was conducted" but does not specify the number of patients or cases.
• Data Provenance: Prospective (clinical testing).
• Country of Origin: Sweden (Departments of Nephrology/Medicine at Eksjö, Halmstad, Hässleholm, Skövde, and Varberg Hospitals).

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

This information is not provided in the document. The study involved clinical testing in hospitals, implying medical professionals were involved in observing and confirming events, but the specific number or qualifications of experts establishing ground truth are not detailed.

4. Adjudication Method for the Test Set

This information is not provided in the document.

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

• Was an MRMC study done? No. The document describes a study to verify the Redsense device's functionality, not a comparative effectiveness study involving human readers with and without AI assistance.
• Effect Size of human readers improvement with AI vs without AI assistance: Not applicable, as no MRMC comparative effectiveness study was performed.

6. Standalone (Algorithm Only) Performance Study

Yes, a standalone study (clinical testing) was performed. The provided text describes the Redsense device, which includes a sensor and an alarm unit, as a standalone system designed to detect blood leakage. The clinical testing was conducted to verify that "the Redsense device fulfills the Requirement Specifications" and "functioned successfully in the clinical environment." This implies the device's performance was evaluated independently.

7. Type of Ground Truth Used

The ground truth for the clinical testing would have been clinical observation of actual blood leakage and confirmation by medical staff during hemodialysis treatments. This is inferred from the description of the device's purpose and the clinical study setting.

8. Sample Size for the Training Set

This information is not provided in the document. The Redsense device is described as a sensor-based system, and there is no mention of an "AI" or "algorithm" that would typically require a training set in the context of machine learning. The "Verification testing" and "Clinical testing" refer to the testing of the final, built device.

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

This information is not provided and is likely not applicable, as the device is not described as utilizing a machine learning algorithm that requires a training set with established ground truth. It appears to be a direct physical sensor detecting infrared light absorption by blood.

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