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The DripAssist Plus is a device intended to be used with gravity infusions as a supplementary monitor the flow of fluid through a compatible drip chamber. The device is intended to be used with single-use intravascular administration sets uniquely identified as "compatible with DripAssist Plus." Sensors measure the flow rate and calculations are performed to convert the drip rate to mL/hr measurement and total volume. An alarm is available to alert the user if the drip rate deviates from the set infusion rate setting controlled through the IV administration set.

The DripAssist Plus device is intended to be used as a supplementary monitoring system for monitoring the flow rate of intravenous fluids. DripAssist Plus is a passive device. It does not control the flow rate of fluids passing through a drip chamber. The device operates by monitoring the drops through the drip chamber of a compatible single-use intravascular administration set that is inserted into a mechanical attachment mechanism on the DripAssist Plus. By tracking the intervals between drops, the device calculates the flow rate through the chamber and displays the flow rate on an LCD screen. The device operates by tracking drops using an infrared emitter and detector positioned on opposite sides of a well wherein the drip chamber is situated. There is an alarm functionality that can be activated once a desired flow rate, or "set point," is reached. The alarm, when activated, will sound when the flow rate deviates a fixed percentage from the "set point." The device can be used with compatible drip sets of 10, 15, 20, or 60 gtt/mL. The device is powered by one AA battery. The device can display the flow rate in drops per minute or mL per hour. The unit of measurement being displayed can be changed while the device operates. The device can also display the total volume that has dispensed through the drip chamber. The device is designed to be used with drip rates slow enough to be calculated by the human eye; a steady stream of fluid is outside the operating parameters.

The provided document describes the DripAssist Plus, a device intended to be a supplementary monitor for gravity infusions, and its substantial equivalence to the predicate device, DripAssist (K150687). The document primarily focuses on demonstrating that the DripAssist Plus meets its specifications and is substantially equivalent to the predicate device.

Here's an analysis of the acceptance criteria and the study performance based on the provided text:

1. Table of acceptance criteria and the reported device performance

The document does not explicitly provide a "table of acceptance criteria" with specific pass/fail thresholds for each test, nor does it present the "reported device performance" in a granular, quantitative manner for all parameters. Instead, it describes general performance characteristics and states that "Predefined acceptance criteria were met" and "results were acceptable for all testing."

However, we can infer some performance characteristics and the device's claimed adherence to them:

Inferred Acceptance Criteria and Reported Performance for DripAssist Plus (compared to DripAssist Predicate)

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The DripAssist is a device intended to be used as a supplementary monitor that measures the flow of fluid through the drip chamber of a standard IV administration set. Sensors measure the flow rate and calculations are performed to convert the drip rate to ml/hr measurement and total volume. An alarm is available to alert the drip rate deviates from the infusion rate setting controlled through the IV administration set.

The DripAssist device is intended to be used as a supplementary monitoring system for monitoring the flow rate of intravenous fluids. The DripAssist is a passive device. It does not control the flow rate of fluids passing through a drip chamber. The device operates by monitoring the drops through the drip chamber of a standard IV administration set. By tracking the intervals between drops, the device calculates the flow rate through the chamber and displays the flow rate on an LCD screen. The device operates by tracking drops using an infrared emitter and detector positioned on opposite sides of a well wherein the drip chamber is situated. There is an alarm functionality that can be activated once a desired flow rate, or "set point," is reached. The alarm, when activated, will sound when the flow rate deviates from a fixed percentage from the "set point."

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

Acceptance Criteria and Device Performance

Study Information

1. Sample Size used for the test set and the data provenance:

   • The provided text does not specify the exact sample size for each performance test (Drip Rate Accuracy, Alarm Accuracy, EMC, Design Verification and Validation).
   • The data provenance is not explicitly stated (e.g., country of origin, retrospective/prospective). These are non-clinical performance tests conducted on the device itself, rather than clinical studies on patients.

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

   • This information is not provided. Given these are performance tests of a physical device measuring flow rates, the "ground truth" would likely be established through highly calibrated measurement equipment or standard reference methods, rather than expert human interpretation.

3. Adjudication method for the test set:

   • This is not applicable as the studies described are performance tests of a physical device against predefined metrics, not human-interpreted data requiring adjudication.

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

   • No, an MRMC comparative effectiveness study was not done. The DripAssist is an IV flow rate monitor, not an AI-powered diagnostic device. The studies were focused on the device's accuracy and performance.

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

   • Yes, the described studies (Drip Rate Accuracy Test, Alarm Accuracy Test, EMC, Design Verification and Validation) are standalone performance tests of the device itself (algorithm and hardware combined) without human-in-the-loop performance being evaluated as a primary outcome. The device's function is to monitor and alert, it does not involve human interpretation of complex data.

6. The type of ground truth used:

   • For the Drip Rate Accuracy Test, the ground truth would typically be established by a highly accurate, calibrated flow meter or precise measurement of dispensed volume over time.
   • For the Alarm Accuracy Test, the ground truth would be the actual flow rate deviation measured by calibrated equipment.
   • For EMC, the ground truth is adherence to the specified IEC standard.
   • For Design Verification and Validation, the ground truth would be the pre-defined design specifications and user requirements.

7. The sample size for the training set:

   • This information is not applicable. The DripAssist is not an AI/machine learning device that requires a "training set" in the conventional sense for developing a predictive algorithm. It operates based on pre-programmed logic for infrared detection, calculations, and alarm triggers.

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

   • This information is not applicable, as there is no "training set" for this type of device.

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The Fluid Level Monitor is a passive sensing device that alarms when the infusion fluid is low. The device provides both visual and audible alarms when preset condition is met.

The Fluid Level Monitor is intended for low-fluid-level alarm use in any healthcare setting where gravity flow infirsed. The use of the device improves efficiency within a busy medical setting by providing healthcare personnel of the low-fluid-level status.

LM771: 1-channel, DC battery power LM781: 1-channel, DC plug-in power LM785: 5-channel DC plug-in power

Fluid Level Monitor is a passive sensing device that alarms when the infusion fluid level is low. Fluid Level Monitor provides both visual and audible alarms when preset condition is met. Fluid Level Monitor operates on DC power source.

Fluid Level Monitor includes both main control unit and external sensor. There are status LEDs on the main control unit to display run, alarm and battery-low status. There is a buzzer on the main control unit to provide audible alarm.

The external sensor is connected to the main control unit via shielded signal cable. The sensor can be clipped on the tubing to monitor fluid level.

The provided text describes the Coleman Laboratories' Fluid Level Monitor and its 510(k) submission. However, it does not contain specific details about acceptance criteria and a study that proves the device meets those criteria in the format explicitly requested. The document does mention "Summary Performance Data" and states: "Based on the risk analysis, the verification and validation tests that were performed and the acceptance criteria applied for each are listed in Section 18. Performance testing was conducted to confirm compliance to design specifications; all functions were verified to operate as designed." Unfortunately, "Section 18" is not included in the provided text.

Therefore, I cannot populate most of the requested fields. I can, however, extract the limited performance information provided.

Here's a summary based on the available information:

1. Table of acceptance criteria and the reported device performance:

2. Sample size used for the test set and the data provenance:
Not specified in the provided text.

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts:
Not applicable, as the device is a passive sensor and the testing described is functional, not a diagnostic or AI-assisted interpretation requiring expert ground truth.

4. Adjudication method for the test set:
Not applicable.

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 MRMC comparative effectiveness study was not done. This device is a passive sensor for low-fluid alarms, not an AI-assisted diagnostic tool for human readers.

6. If a standalone (i.e., algorithm only without human-in-the-loop performance) was done:
Yes, the performance testing described appears to be a standalone functional validation of the device's alarm system, without human interaction as part of the primary performance measurement.

7. The type of ground truth used:
Functional verification against design specifications. For example, verifying the alarm triggers when the fluid level is low, and that power consumption is consistent across power sources and channels.

8. The sample size for the training set:
Not applicable as this is a hardware device with embedded logic, not a machine learning model that requires a training set in the conventional sense.

9. How the ground truth for the training set was established:
Not applicable.

Additional Note: The document emphasizes substantial equivalence to predicate devices (K030136 - Drip Alert, K903193 - Levelert) based on design principles, material, indications for use, and intended use. This suggests the performance expectations might be benchmarked against these existing devices.

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The Low Fluid Alarm System is a stand alone accessory for monitoring of liquid levels (standard saline solutions or other solutions with an aqueous base) in a reservoir. It is generally useable with rigid polycarbonate, flexible polyvinyl chloride (PVC) or glass reservoirs. If the level falls below a predetermined threshold visual and acoustical alarms appear.

The Low Fluid Alarm System is designed for continuous arthroscopy operation in operating rooms and intensive care units. For the patient's safety the device is to be operated only by qualified medically-trained personnel and only with constant supervision.

Not Found

The provided document is a 510(k) clearance letter from the FDA for a device called "Low Fluid Alarm." This letter confirms substantial equivalence to a predicate device and allows the manufacturer, Em-tec GmbH, to market the device.

However, the document does not contain any information regarding acceptance criteria, device performance data, study designs, sample sizes, ground truth establishment, or expert qualifications.

The document primarily focuses on:

• The FDA's decision of substantial equivalence.
• Regulatory requirements and classifications.
• Indications for Use statement for the Low Fluid Alarm.

Therefore, I cannot provide the requested information based solely on the text provided. The information you're asking for would typically be found in the 510(k) submission itself (e.g., in a performance data section), which is not part of this clearance letter.

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The ISSYS Drug Flow Monitor is a passive monitoring device for gravity infusion. The unit uses a flow sensor to measure the amount of liquid through the infusion line and displays the flow rate and total volume administered to the patient. Flow rates and volumes are recorded, and if the flow rate or volume falls outside the preset range, both a visible and audible alarm is triggered. This monitor is indicated for use in where the flow rates are between 5 and 200 mL/hr. The accuracy of the monitor is +/- 20% at 5 mL/hr and +/- 5% at 200 mL/hr. For use with IV drug solutions administered by gravity. WARNING: DO NOT USE WITH BLOOD OR BLOOD PRODUCTS.

The ISSYS Drug Flow Monitor is a passive monitoring device for gravity infusion. The unit uses a flow sensor to measure the amount of liquid through the infusion line and displays the flow rate and total volume administered to the patient. Flow rates and volumes are recorded, and if the flow rate or volume falls outside the preset range, both a visible and audible alarm is triggered.

The provided text describes a 510(k) premarket notification for the ISSYS Drug Flow Monitor®. It includes information on the device's intended use and performance specifications, which can be interpreted as acceptance criteria. However, it does not detail a specific study proving the device meets these criteria in the comprehensive manner requested (e.g., sample size, expert ground truth, MRMC study, training set details).

Here's a breakdown of the information that can be extracted or inferred, and what is missing:

1. Table of Acceptance Criteria and Reported Device Performance

Based on the "Indications For Use" section, the following can be constructed:

Missing Information:
The document does not provide details of a specific study that proves these performance metrics. It merely states them as characteristics of the device and its intended use. There is no mention of study design, methodology, or results from an independent study to validate these claims.

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

Missing Information:
The document does not describe a test set, its sample size, or its data provenance (e.g., country of origin, retrospective/prospective). The provided text is a regulatory clearance letter, not a scientific study report.

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

Missing Information:
No information is provided regarding experts, ground truth establishment, or their qualifications. This is not a study involving human interpretation of medical images or data.

4. Adjudication Method

Missing Information:
No information is provided about an adjudication method. This is not relevant for a device that directly measures flow rates.

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

Missing Information:
An MRMC study is not relevant for this device. The ISSYS Drug Flow Monitor® is a "passive monitoring device" that "uses a flow sensor to measure the amount of liquid." It's an automated measurement device, not one that assists human readers in interpreting clinical data.

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

While the device operates "standalone" in the sense that it automatically measures and alarms, the document does not describe a study to test its standalone performance against a gold standard or reference. It only states the device's claimed accuracy specifications.

7. Type of Ground Truth Used

Missing Information:
No information is provided regarding the type of ground truth used for performance validation. For a device measuring flow, the ground truth would typically be highly accurate reference flow meters, but the document does not describe how these specific accuracy figures were derived or verified in a formal study for regulatory submission.

8. Sample Size for the Training Set

Missing Information:
There is no mention of a "training set." This type of device is likely based on physical principles of fluid dynamics and sensor calibration, not on machine learning or algorithms that require training data.

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

Missing Information:
As there's no mention of a training set, there's no information on how its ground truth was established.

Summary of Document's Relevance to the Request:

The provided FDA letter serves as regulatory clearance based on the manufacturer's claims and submissions, not as a detailed scientific study report. It states the device's intended use and performance specifications (which can be interpreted as acceptance criteria), but it does not describe the specific studies that validated these claims according to the detailed scientific rigor outlined in your request. The format of the request (e.g., MRMC studies, expert ground truth) is more applicable to diagnostic imaging AI devices, whereas the ISSYS Drug Flow Monitor is a measurement and alarm device for gravity infusion systems.

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The Smith & Nephew LEVELERT II Fluid Level Sensor is intended to weigh a bag of irrigation fluid and signal operating room personnel when a pre-determined amount of fluid remains.

The Levelert II is a irrigation fluid bag level sensing device designed to provide the user with fluid level feedback at pre-determined values. The pre-determined values are selected by the user. The Levelert II is a stand-alone DC battery powered, nonrechargeable device that is used in arthroscopic procedures.

The provided text describes the Levelert II Fluid Level Sensor. However, it does not contain specific acceptance criteria or detailed study data as would be found in a comprehensive clinical or performance validation study report.

The text is a 510(k) summary for a medical device submission to the FDA, which focuses on demonstrating substantial equivalence to a predicate device. It briefly mentions "performance testing," "EMI/EMC testing," "UL Safety testing," and "software verification and validation," but does not provide the results of these tests, the acceptance criteria, or the methodology.

Therefore, I cannot populate all sections of your request based solely on the provided text.

Here's an attempt to answer based on the available information, with significant gaps noted:

1. Table of Acceptance Criteria and Reported Device Performance

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

• Sample Size: Not specified in the provided text. The text refers to "performance testing" but does not detail the number of units or test conditions.
• Data Provenance: Not specified. It can be inferred that testing was conducted by or on behalf of Smith & Nephew, Inc., Endoscopy Division, likely in the USA. The type of study (retrospective or prospective) is not applicable here as this is device performance testing rather than a clinical study with patient data.

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

• Not applicable/Not specified. For a device like a fluid level sensor, ground truth for performance testing would typically be established by calibrated measurement tools (e.g., precise scales for weight, or volumetric measurements) rather than human expert interpretation.

4. Adjudication Method for the Test Set

• Not applicable/Not specified. Adjudication methods (like 2+1, 3+1) are typically used for studies involving human interpretation or subjective assessment, which is not the primary focus of performance testing for this type of device.

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

• No, an MRMC comparative effectiveness study was not mentioned. This type of study is more relevant for diagnostic imaging or interpretation tasks where human readers are involved. The Levelert II is a sensor, not an interpretive aid.

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

• Yes, the performance testing described ("performance testing, EMI/EMC testing, UL Safety testing and the software verification and validation") appears to be standalone algorithm/device performance testing. The device is a "stand-alone DC battery powered" unit, indicating its primary function is independent. The stated "signal operating room personnel" suggests an output for human users, but the core performance evaluation would be of the device's ability to accurately weigh and signal.

7. The Type of Ground Truth Used

• Not explicitly stated, but for a fluid level sensor, the ground truth would most likely be objective, quantitative measurements obtained through calibrated instruments (e.g., highly accurate scales to measure fluid weight, or precise volumetric measurements). It would not be expert consensus, pathology, or outcomes data.

8. The Sample Size for the Training Set

• Not applicable/Not specified. This device is described as having a "load cell instead of a spring loaded circuit design" and incorporating a "microprocessor internally." While microprocessors contain software/firmware developed through engineering processes, the text does not indicate a machine learning model that would require a "training set" in the common sense (i.e., for AI/ML). The term "software verification and validation" is used, which refers to standard software development lifecycle testing.

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

• Not applicable, as a "training set" for AI/ML is not indicated for this device based on the provided description. Software verification and validation would establish ground truth through functional specifications and test cases derived from engineering requirements.

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The Drip Alert device is a passive device that measures time between intravenous drops and sounds an alarm when the time between drops falls outside an acceptable range due to air in the line, occlusion, low or empty fluid in the solution bag, high or low flow rate, and low battery.

The Drip Alert device is intended to be used as a supplementary monitor with a standard IV administration set such that an alarm sounds when the drip rate in the drip chamber of the administration set falls outside a preselected range of acceptable drip rate deviation. The deviation in the drip rate may be due to air in the IV line, occlusion, excessive movement by the patient or displacement of the IV catheter.

The Drip Alert device is a passive device that measures time between intravenous drops and sounds an alarm when the time between drops falls outside an acceptable range due to air in the line, occlusion, low or empty fluid in the solution bag, high or low flow rate, and low battery. The Drip Alert device does not have a pump or clamping mechanism. It uses a processor to perform calculations and measurements and has a flow meter. It is powered by 2-AAA batteries with a typical 30 day life. It is a Class II Device.

This document, a 510(k) summary for the Drip Alert intravenous drip monitor, provides limited information about specific acceptance criteria and performance studies. The focus of this submission is to demonstrate substantial equivalence to predicate devices rather than necessarily reporting on extensive performance studies with defined acceptance criteria.

Based on the provided text, here's what can be extracted and what remains unknown:

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

The document does not explicitly state quantitative acceptance criteria or specific performance metrics as they would typically be presented from a defined study. Instead, it provides a comparative chart showing features and capabilities against predicate devices. The "performance" is implicitly defined by its functionality as described in the "Indication for Use" and the features listed in the "Substantial Equivalence Chart."

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

This information is not provided in the document. The 510(k) summary focuses on equivalence to predicate devices rather than detailed performance study results from a test set.

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

This information is not provided. As no specific performance study with a test set and ground truth is described, there's no mention of experts for establishing ground truth.

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

This information is not provided.

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 and is not applicable here. The Drip Alert is a device (monitoring system), not an AI-assisted diagnostic tool that would involve human readers interpreting cases.

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

The Drip Alert is a standalone device in the sense that it performs its monitoring function automatically and signals an alarm when a deviation occurs. It is not an "algorithm only" in the context of AI/ML, but rather an electronic device with a processor that performs calculations and measurements. The document does not describe what would typically be considered a 'standalone performance study' in the context of recent medical device submissions, which often entail detailed metrics like sensitivity, specificity, etc. However, its core function is designed to operate without constant human intervention for its primary task of monitoring.

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

This information is not provided.

8. The sample size for the training set

This information is not provided. The Drip Alert is described as having a processor to perform calculations; however, the document does not suggest it utilizes complex machine learning algorithms that would require a "training set" in the modern sense. It appears to be a rule-based or threshold-based system.

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

This information is not provided and is likely not applicable given the apparent nature of the device (not a machine learning model requiring a training set with ground truth).

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MT Alert Infusion Monitor is intended for use in any healthcare setting where gravityflow infusions are utilized.

The Stryker L3 Hydrolert is intended to monitor irrigant levels primarily during arthroscopic procedures and to alert operating room personnel of a low irrigant fluid level condition. It will offer both increased efficiency in arthroscopic procedures and universal compatibility with both arthroscopic pump and gravity fluid management systems. It is intended for use with saline solution or any other standard irrigant. It is not intended for use as an intravenous infusion monitor. The alarm is designed to be reusable.

The MT Alert Infusion Monitor is a passive weighing device that alarms when the infusion bag is near-empty. The alarm point can be set by the user. In addition, MT Alert may also assist in monitoring fluid bolus administration. MT Alert will alarm when a prescribed bolus of fluid has been taken from the infusion bag. MT Alert provides various audio and visual alarms. MT Alert operates from common alkaline batteries and mounts on common poles and rods.

The provided document describes a 510(k) summary for the MT Alert Infusion Monitor (later referenced as Stryker L3 Hydrolert, though the initial summary is for MT Alert). This device is a passive weighing device that alarms when an infusion bag is near-empty.

Here's an analysis of the acceptance criteria and the study that proves the device meets them:

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

The document does not explicitly state "acceptance criteria" but rather focuses on demonstrating "substantial equivalence" to a predicate device, the Smith & Nephew Dyonics LeveLert System. The performance is assessed by comparing the features and functions of the MT Alert with the predicate device.

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

The document does not provide any information about a "test set" in the traditional sense of a clinical or performance study with a specific sample size. The validation procedures mentioned are described as indicating the new device is "as safe and effective as the predicate devices," but no details on these procedures or the data provenance are given.

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 document. The substantial equivalence argument relies on feature comparison, not independent expert assessment of device performance against a ground truth.

4. Adjudication method for the test set.

This information is not provided. As there is no described "test set" or independent expert review, there is no mention of an adjudication method.

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.

This information is not applicable and not provided. The device is a monitor for gravity-flow infusions, not an AI-powered diagnostic tool. Therefore, an MRMC study or AI assistance is not relevant to its functionality.

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

This information is not provided. Given the nature of the device as a physical monitor, the concept of "algorithm only" performance without human interaction doesn't directly apply in the way it would for, say, an image analysis algorithm. The function of the device is to alarm, and that alarm is inherently for human notification. No standalone performance data is presented beyond the comparison table.

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

The document does not describe the use of a ground truth in the context of a performance study. The ground truth for this submission appears to be the established functionality and performance of the legally marketed predicate device.

8. The sample size for the training set.

This information is not provided. Given that this is a physical monitoring device and not an AI/machine learning product, the concept of a "training set" is not applicable in the usual sense.

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

This information is not provided and not applicable for the reasons stated above.

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MT Alert Infusion Monitor is intended for use in any healthcare setting where gravity-flow infusions are utilized.

The MT Alert Infusion Monitor is a passive weighing device that alarms when the infusion bag is near-empty. The alarm point can be set by the user. In addition, MT Alert may also assist in monitoring fluid bolus administration. MT Alert will alarm when a prescribed bolus of fluid has been taken from the infusion bag. MT Alert provides various audio and visual alarms. MT Alert operates from common alkaline batteries and mounts on common poles and rods.

Here's the breakdown of the acceptance criteria and the study information for the MT Alert Infusion Monitor based on the provided document:

Acceptance Criteria and Device Performance

The provided document does not explicitly state quantitative acceptance criteria with specific performance metrics (e.g., accuracy percentages, alarm thresholds). Instead, the "Safety and Effectiveness in Comparison to Predicate Devices" section states: "The validation procedures performed on the system indicate that the new device is as safe and effective as the predicate devices."

The Substantial Equivalence Chart serves as an implicit set of functional acceptance criteria, demonstrating that the MT Alert Infusion Monitor meets or exceeds the capabilities of the predicate device (Smith & Nephew Dyonics LeveLert System).

Study Details

The provided 510(k) summary is very limited in its description of the underlying studies that demonstrate safety and effectiveness. It primarily relies on demonstrating substantial equivalence to a predicate device. Therefore, many of the requested details cannot be extracted directly from this document.

1. Sample size used for the test set and the data provenance:

   • Sample Size: Not specified in the provided document.
   • Data Provenance: Not specified. It's likely that internal bench testing or validation was performed.

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

   • Not specified. The document does not describe the establishment of a ground truth in a clinical or expert review setting for the validation.

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

   • Not specified.

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

   • Not applicable. This device is an infusion monitor, not an AI-assisted diagnostic tool for "human readers." The document states it "can improve existing practice by notifying healthcare personnel of gravity infusion end-points." However, no formal MRMC study or effect size is mentioned for human improvement with the device vs. without.

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

   • The device functions as a "standalone" monitor in that it operates independently to detect fluid levels and alarm. However, the term "standalone" in the context of performance studies usually refers to the performance of an algorithm without human intervention in a diagnostic sense. The device's primary function is to alert human personnel; it doesn't make diagnostic decisions. The document implies performance of the device itself was validated to ensure it functions as intended (e.g., alarming at the correct weight), but specific "standalone performance" metrics are not detailed.

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

   • For the functional aspects (e.g., alarming at a specific weight), the ground truth would likely be based on measured weight or volume (physical truth) rather than expert consensus or pathology. The document doesn't detail the specific methods for establishing ground truth during its internal validation.

7. The sample size for the training set:

   • Not applicable. This is a physical device with embedded logic, not a machine learning model that undergoes a "training" phase with a dataset.

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

   • Not applicable, as it's not a machine learning model.

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