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The DASH® SARS-CoV-2 & Flu A/B Test is a rapid reverse transcription polymerase chain reaction (RT-PCR) assay performed on the DASH Rapid PCR Instrument and is intended for the simultaneous in vitro qualitative detection and differentiation of SARS-CoV-2, influenza A and influenza B virus ribonucleic acid (RNA) in anterior nasal swab specimens from patients with signs and symptoms of respiratory tract infection. The test is intended to aid in the differential diagnosis of SARS-CoV-2, influenza B in humans in conjunction with other clinical, epidemiologic and laboratory findings.

Positive results of a specific target are indicative of that viral RNA and may not be the definite cause of disease. Positive results do not rule out co-infection with other pathogens. Negative results do not preclude SARS-COV-2, influenza A or influenza B infection and should not be used as the sole basis for patient management decisions.

The DASH® SARS-CoV-2 & Flu A/B Test is a rapid, polymerase chain reaction (PCR) assay performed on the DASH Rapid PCR Instrument (DASH Instrument) with the DASH External Controls. The external control materials and DASH Instrument are sold and distributed separately from the DASH SARS-CoV-2 & Flu A/B Test. The DASH SARS-CoV-2 & Flu A/B Test (for use with the DASH Rapid PCR System components) uses reverse transcription polymerase chain reaction (RT-PCR) for rapid qualitative detection and differentiation of SARS-CoV-2, Flu A and Flu B from nasal swabs.

The test combines the technologies of sequence specific capture sample preparation and RT-PCR amplification. The DASH SARS-CoV-2 & Flu A/B Test cartridge contains all reagents necessary to perform the test. An anterior nares nasal swab with a 30-mm breakpoint is used to collect a specimen. The nasal swab specimen is added directly to the DASH SARS-CoV-2 & Fly A/B Test cartridge sample chamber. The cartridge is capped and inserted into the DASH Rapid PCR Instrument to initiate the test, and all subsequent test steps are performed automatically by the DASH Instrument.

The provided text describes the performance of the DASH® SARS-CoV-2 & Flu A/B Test, a rapid RT-PCR assay. The information focuses on analytical and clinical performance studies to demonstrate its substantial equivalence to a predicate device for FDA clearance.

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

The acceptance criteria for a diagnostic test like this are typically related to:

• Analytical Sensitivity (Limit of Detection - LoD): The lowest concentration of the analyte that can be reliably detected.
• Precision/Reproducibility: The consistency of results when the test is run multiple times under varying conditions (different operators, days, sites, lots).
• Analytical Specificity (Cross-Reactivity & Microbial Interference): The ability of the test to exclusively detect the target analyte without reacting to other related or unrelated microorganisms and to perform accurately in the presence of other common substances.
• Clinical Performance (Agreement with a Comparator Method): How well the device's results align with a well-established (FDA cleared) method when tested on clinical samples. This is typically measured by Positive Percent Agreement (PPA) and Negative Percent Agreement (NPA).

Acceptance Criteria (Implied) and Reported Device Performance for DASH® SARS-CoV-2 & Flu A/B Test

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

• Analytical Test Sets:
  • LoD: 5 viral strains (SARS-CoV-2, Flu A x2, Flu B x2) evaluated, with "replicates" (number not explicitly stated per strain, but implies multiple).
  • Within-Laboratory Precision: 96 replicates per concentration (2X LoD, 5X LoD, and negative) for each of the triple positive samples (SARS-CoV-2, Flu A, Flu B). Total of 288 samples for positive and 96 for negative for each target (total 384 for each target or more generally 96 of each concentration for the multiplex test).
  • Reproducibility (Multi-Site): Over 810 samples tested (270 replicates per panel member across 3 sites, 5 days, 2 runs/day, 3 replicates/panel member). Panel members: true negative, low positive (2X LoD), moderate positive (5X LoD).
  • Analytical Specificity (Cross-Reactivity & Microbial Interference): 50 different viruses, bacteria, and fungi (for wet testing of cross-reactivity and interference). Each tested with three (3) replicates.
  • Inclusivity (Wet Testing): 7 strains of SARS-CoV-2, 21 strains of Flu A, and 10 strains of Flu B. Three (3) replicates evaluated per strain.
• Clinical Test Set:
  • Evaluated Subjects: 795 subjects evaluable for at least one analyte/target.
  • SARS-CoV-2: 795 evaluable subjects (168 positive by comparator, 627 negative).
  • Flu A & Flu B: 792 evaluable subjects (Flu A: 53 positive by comparator, 739 negative; Flu B: 37 positive by comparator, 755 negative).
• Data Provenance:
  • Clinical Study: Prospective collection of specimens within the United States (7 geographical locations). Specimens collected from January to March 2024.
  • Analytical Studies: Lab-based studies using contrived samples/strains. The text does not specify the country of origin for these analytical labs, but given the FDA submission, it's likely US or accredited international labs.

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

• For analytical studies (LoD, precision, specificity, inclusivity), the "ground truth" is established by the known concentration of the spiked viral strains or the defined presence/absence of organisms/substances. This does not involve human expert consensus.
• For the clinical study, the ground truth was established by comparison with an FDA cleared RT-PCR test.
  • SARS-CoV-2: Comparison with an FDA cleared RT-PCR test for SARS-CoV-2.
  • Flu A & Flu B: Comparison with a second FDA cleared test for Flu A and Flu B.
  • Discordant Results: Discordant results were investigated using a "third highly sensitive FDA cleared test."
• The text does not specify the number of experts or their qualifications for establishing the ground truth (i.e., for interpreting the results of the FDA-cleared comparator tests). This is typical for such submissions; the "expert" is implied to be the validated and regulated comparator device.

4. Adjudication Method (e.g. 2+1, 3+1, none) for the Test Set

• For the clinical study, an adjudication method was used for discordant results. The method was: "All discordant results between the DASH® SARS-CoV-2 & Flu A/B Test and the comparator were investigated using a third highly sensitive FDA cleared test." This acts as a reference standard to resolve discrepancies. It loosely resembles a "2+1" or "tie-breaker" approach where the third test breaks the tie between the investigational device and the initial comparator.

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 was not done. This type of study is relevant for imaging devices or AI algorithms where human readers interpret images. The DASH® SARS-CoV-2 & Flu A/B Test is a molecular diagnostic (RT-PCR) test; its output is qualitative (positive/negative) and determined by an automated instrument/software algorithm without human visual interpretation of the test result. Therefore, human reader improvement with AI assistance is not applicable to this device.

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

• Yes, a standalone performance was done for the device. The device is an automated RT-PCR system.
  • "The cartridge is capped and inserted into the DASH Rapid PCR Instrument to initiate the test, and all subsequent test steps are performed automatically by the DASH Instrument."
  • "A software algorithm determines whether any of the targets are positive."
  • The analytical and clinical performance data (LoD, precision, specificity, inclusivity, PPA/NPA) all represent the "algorithm only without human-in-the-loop performance" in terms of result generation. The human role is in specimen collection, loading the cartridge, and interpreting the final positive/negative result displayed by the instrument. The operators were "untrained" in the clinical study, further indicating the device's standalone nature in generating results.

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

• Analytical Studies: The ground truth was established using known quantities and defined characteristics of viral strains, bacteria, fungi, and chemical substances spiked into matrices (pooled nasal matrix, simulated clinical nasal matrix). This is a form of defined experimental truth.
• Clinical Study: The ground truth was established by comparison to results from one or more FDA cleared RT-PCR tests. This can be considered a reference standard ground truth based on established diagnostic methods. For discordant results, a "third highly sensitive FDA cleared test" served as the tie-breaker/confirmatory ground truth.

8. The Sample Size for the Training Set

• The document describes a 510(k) submission for a diagnostic test, not an AI/ML device where a distinct "training set" would be explicitly mentioned for model development. The text focuses on the validation of the device rather than its development. Therefore, a specific "training set sample size" for the algorithm itself is not provided in this document. The development of the assay (primers, probes, algorithm thresholds) would involve internal R&D, but the data presented here is for the regulatory submission's performance evaluation.

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

• As noted in point 8, a "training set" in the context of an AI/ML model for image or signal interpretation is not explicitly discussed. The "training" for this type of RT-PCR device involves the development and optimization of the assay's chemical reagents (primers, probes) and the instrument's detection algorithm. The ground truth for such development would involve:
  • Known concentrations of target nucleic acids: To establish reaction efficiency and sensitivity.
  • Characterized positive and negative clinical samples or controls: To optimize thresholds and ensure correct classification.
  • Various interfering substances/microorganisms: To ensure specificity.
• This ground truth is established through standard molecular biology and analytical chemistry practices, using highly characterized reagents and samples, and often iterative testing during the R&D phase prior to formal validation studies. The document does not detail this prior developmental process.

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The Omnipod Insulin Management System is intended for subcutaneous delivery of insulin at set and variable rates for the management of diabetes mellitus in persons requiring insulin and for the quantitative measurement of glucose in fresh whole capillary blood (in vitro) from the finger.

The glucose measurements should not be used for the diagnosis of or screening for diabetes. The PDM glucose meter is intended for single-patient use and should not be shared.

Abbott FreeStyle test strips are used with the built-in FreeStyle meter for the quantitative measurement of blood glucose in fresh whole capillary blood from the finger, upper arm, and palm. Abbott FreeStyle Control Solutions are used to verify that the meter and test strips are working together properly and that the test is performed correctly.

The Omnipod DASH Insulin Management System is intended for subcutaneous delivery of insulin at set and variable rates for the management of diabetes mellitus in persons requiring insulin.

Additionally, the Omnipod DASH System is interoperable with a compatible blood glucose meter to receive and display glucose measurements.

The subject devices provide for the management of insulin therapy and blood glucose monitoring by patients with diabetes mellitus. They are each comprised of two primary components: the disposable insulin infusion pump (Pod) and an associated wireless remote controller referred to as the Personal Diabetes Manager (PDM). The PDMs incorporate a suggested bolus calculator which aids the user in determining the insulin bolus dosage needed based on carbohydrates ingested, most recent blood glucose reading. programmable correction factor, insulin to carbohydrate ratio, target blood glucose value, and Insulin on Board (IoB).

The Pod is a body-wearable insulin pump that affixes to the user on the back of the arm, the lower back or abdomen, the thigh area, or any site that has a layer of fatty tissue available. It is held in place by an adhesive pad and provides up to three days of insulin before it is removed and replaced with a new Pod. The PDM is a handheld device that controls the Pod. The user interfaces with the device system through the PDM, where they control basal and bolus delivery and various insulin program settings and calculations. The PDM also has a food library to assist with carbohydrate calculations, and it maintains several variables in a history log for the viewer to track their diabetes therapy. The Omnipod Insulin Management System PDM has an integrated blood glucose meter and communicates with the Pod using wirelessly using secure, low power, bi-directional radio frequency (RF) communications at 433.92MHz. The Omnipod DASH Insulin Management System PDM does not have an integrated blood glucose meter, but is interoperable with a compatible blood glucose meter to receive and display glucose measurements. The Omnipod DASH PDM communicates to the Pod and a compatible blood glucose meter using Bluetooth Low Energy.

Both systems are for prescription use only.

The provided text describes modifications to the Omnipod Insulin Management System and Omnipod DASH Insulin Management System to include Lyumjev U100 insulin in their labeling as a compatible insulin. The submission emphasizes that the devices are substantially equivalent to their predicate devices cleared in K192659 because the only change is the addition of this new insulin and that performance testing demonstrates no adverse effect on safety when using Lyumjev U100.

Here's an analysis of the requested information based on the provided text:

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

The document does not explicitly state "acceptance criteria" in a tabulated format for the Lyumjev U100 insulin. Instead, it refers to broad performance categories and comparative characteristics with the predicate device. The core "acceptance criteria" can be inferred as demonstration that the device's performance (delivery accuracy, flow rates, etc.) is not negatively impacted and that the insulin's stability is maintained when used with Lyumjev U100.

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

The document does not provide specific sample sizes for the "in-use stability and leachables testing" conducted with Lyumjev U100 insulin. It also does not specify the country of origin of the data or whether the test was retrospective or prospective.

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 in the document. The testing described (drug stability/compatibility) is laboratory-based and does not involve human expert interpretation for ground truth establishment in the traditional sense of image analysis or diagnostic studies.

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

This information is not provided. Adjudication methods are typically relevant for studies involving human interpretation or subjective assessments, which do not appear to be the case here.

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

An MRMC comparative effectiveness study was not done. The device is an insulin management system, not an AI-assisted diagnostic tool that would involve human readers.

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

The testing described (drug stability and compatibility) is inherently "standalone" in that it assesses the physical and chemical interaction between the device components and the insulin, independent of human interaction within the testing framework. However, this is not an "algorithm-only" performance as would be seen in AI device submissions. The submission is for hardware/software system compatibility with a new drug.

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

The ground truth for the stability and compatibility testing would be established through laboratory analytical methods (e.g., chemical assays, spectroscopic analysis) to determine the integrity and concentration of the insulin, as well as the presence of leached substances, compared against established specifications for the insulin and device materials. This is not expertise-based ground truth like pathology or outcomes data.

8. The sample size for the training set

This information is not applicable and not provided. This submission is for compatibility with a new insulin, not an AI/ML algorithm that requires a training set.

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

Not applicable, as there is no training set for an AI/ML algorithm.

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The Omnipod DASH Insulin Management System is intended for subcutaneous delivery of insulin at set and variable rates for the management of diabetes mellitus in persons requiring insulin.

Additionally, the Omnipod DASH System is interoperable with a compatible blood glucose meter to receive and display glucose measurements.

The Omnipod Insulin Management System is intended for subcutaneous delivery of insulin at set and variable rates for the management of diabetes mellitus in persons requiring insulin and for the quantitative measurement of glucose in fresh whole capillary blood (in vitro) from the finger.

The glucose measurements should not be used for the diagnosis of or screening for diabetes. The PDM glucose meter is intended for single-patient use and should not be shared.

Abbott FreeStyle test strips are used with the built-in FreeStyle meter for the quantitative measurement of blood glucose in fresh whole capillary blood from the finger, upper arm and palm. Abbott Freestyle Control Solutions are used to verify that the meter and test strips are working together properly and that the test is performed correctly.

The subject devices provide for the management of insulin therapy by patients with diabetes mellitus. The devices are comprised of two primary components: the disposable insulin infusion pump (Pod) and an associated wireless remote controller referred to as the Personal Diabetes Manager (PDM). The PDMs incorporates a suggested bolus calculator which aids the user in determining the insulin bolus dosage needed based on carbohydrates ingested, most recent blood glucose reading, programmable correction factor, insulin to carbohydrate ratio, target blood glucose value, and Insulin on Board (IoB).

The Pod is a body-wearable insulin pump that affixes to the user on the back of the arm, the lower back or abdomen, the thigh area, or any site that has a layer of fatty tissue available. It is held in place by an adhesive pad and provides up to three days of insulin before it is removed and replaced with a new Pod. The PDM is a handheld device that controls the Pod. The user interfaces with the device system through the PDM, where they control basal and bolus delivery and various insulin program settings and calculations. The PDM also has a food library to assist with carbohydrate calculations, and it maintains several variables in a history log for the viewer to track their diabetes therapy. The Omnipod Insulin Management System PDM has an integrated blood glucose meter and communicates with the Pod using wirelessly using secure, low power, bi-directional radio frequency (RF) communications at 433.92MHz. The Omnipod DASH Insulin Management System PDM does not have an integrated blood glucose meter, but is interoperable with a compatible blood glucose meter to receive and display glucose measurements. The Omnipod DASH PDM communicates to the Pod and a compatible blood glucose meter using Bluetooth Low Energy.

The systems are for prescription use only.

This document is a 510(k) premarket notification for the Omnipod Insulin Management System and Omnipod DASH Insulin Management System. It primarily discusses a labeling change to add Fiasp U100 insulin as compatible and asserts substantial equivalence to a previously cleared device (K182630). Therefore, the information typically found for acceptance criteria and a study proving device performance in a de novo or original 510(k) submission (which often includes specifics on a clinical trial or performance study with detailed metrics) is not present here.

Based on the provided document, I can extract the following relevant information regarding acceptance criteria and studies:

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

The document does not provide a table with specific quantitative acceptance criteria or detailed reported device performance metrics in the way a clinical study report would. Instead, it states that:

• Acceptance Criteria Mentioned: "Verification activities, as required by the risk analysis, demonstrated that the predetermined acceptance criteria were met and the devices are safe for use." However, the specific criteria themselves are not listed.
• Reported Device Performance:
  • "Drug Stability and Compatibility; In-use stability and leachables testing was conducted with Fiasp U100 insulin to verify and validate that the systems do not adversely affect the insulin."
  • "Fiasp stability testing in Omnipod Pods"
  • "Leachables study"

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

The document does not specify the sample sizes for the stability and leachables testing, nor does it provide information about the provenance of the data (e.g., country of origin, retrospective or prospective nature).

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 applicable to the type of testing described (drug stability and leachables) and is therefore not present in the document. These tests are laboratory-based and do not involve expert interpretation or ground truth establishment in the same way a diagnostic device might.

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

This information is not applicable to the type of testing described (drug stability and leachables) and is therefore not present 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

This information is not applicable. The device is an insulin management system, not an AI-assisted diagnostic tool requiring MRMC studies.

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

This information is not applicable in the context of the described modifications. The primary device function (insulin delivery) is not an algorithm-only standalone performance that would be assessed in this manner for the stated purpose of the submission. The "dose calculator" is mentioned within the context of the PDM, implying human interaction.

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

For the stability and leachables testing, the "ground truth" would be established by scientific analytical methods (e.g., chemical assays, chromatography) to measure insulin degradation, chemical composition of leachates, and ensure the drug substance remains within predefined acceptable ranges, as per established pharmaceutical and medical device testing standards. The document does not explicitly detail these laboratory "ground truth" methods but refers to "Fiasp stability testing in Omnipod Pods" and a "Leachables study."

8. The sample size for the training set

The document describes a 510(k) submission for a modification (labeling change for compatible insulins) to existing devices. There is no mention of a "training set" as would be used for machine learning or AI algorithm development because that is not the nature of this submission. The testing described (stability, leachables) does not involve training sets.

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

As there is no "training set" reported for this submission, this question is not applicable.

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The Omnipod DASH Insulin Management System (the Pump) with interoperable technology is intended for subcutaneous delivery of insulin at set and variable rates for the management of diabetes mellitus in persons requiring insulin.

The Pump is able to reliably and securely compatible, digitally connected devices, including automated insulin dosing software, to receive, execute and confirm commands from these devices.

The Pump is intended for single patient, home use and requires a prescription. The Pump is indicated for use with NovoLog, Humalog, Admelog, or Apidra U-100 insulin.

The Omnipod DASH™ Insulin Management System with interoperable technology provides for the management of insulin therapy by patients with diabetes mellitus. It is comprised of two primary components: the disposable insulin infusion pump (Pod), and an associated Bluetooth Low Energy (BLE) enabled remote controller. The Omnipod DASH System with interoperable technology is provided with the DASH Personal Diabetes Manager (PDM), but future alternate controllers may be established. The DASH PDM incorporates a suggested bolus calculator which aids the user in determining the insulin bolus dosage needed based on carbohydrates ingested, most recent blood glucose reading, programmable correction factor, insulin to carbohydrate ratio, target blood glucose value and Insulin on Board (IoB).

The Pod is a body-wearable insulin pump that affixes to the user on the back of the arm, the lower back or abdomen, the thigh area, or any site that has a layer of fatty tissue available. It is held in place by an adhesive pad and provides up to three days of insulin before it is removed and replaced with a new Pod. The DASH PDM is a handheld device that controls the Pod. The user interfaces with the device system through the DASH PDM using a touch screen, similar to a smartphone, where they control basal and bolus delivery and various insulin program settings and calculations. The DASH PDM also has a food library to assist with carbohydrate calculations, and it maintains several variables in a history log for the viewer to track their diabetes therapy. The device system is for prescription use only.

The remote control design of the Pod inherently enables connectivity to other interoperable controllers with new functionality. Capabilities can be built into compatible controllers to add functionality such as Automated Insulin Delivery (AID) systems. In this design, a controller may contain an algorithm and connect to an iCGM system. In such an integrated system, the AID controller would be responsible for coordinating the interoperable devices (Omnipod DASH and iCGM) in order to automate delivery. It would read the Pod for insulin delivery status, read the iCGM for the sensor value, compute an automated delivery amount and then command the Pod to deliver the required insulin amount. For this automated delivery to occur, the Controller is required to be in range of the Pod. The Pod is designed to the programmed basal rate in the case of extended loss of communication.

This document describes the Omnipod DASH™ Insulin Management System with interoperable technology. It is a 510(k) premarket notification for a Class II medical device, an alternate controller enabled infusion pump.

Key takeaway: This documentation confirms that the Omnipod DASH system is a medical device for insulin delivery, and the submission is for expanding its indications for use to include interoperable technology, allowing it to communicate with compatible digital devices. The FDA has determined it is substantially equivalent to existing devices.

Here's an analysis based on the provided text, focusing on the requested criteria for an AI/ML device, even though this document is for an infusion pump. It's important to note that the provided text is for an insulin pump, not an AI/ML diagnostic or assistive device. Therefore, many of the requested criteria (like ground truth, MRMC studies, expert adjudication) are not applicable in their typical sense for this type of medical device.

However, I will interpret the acceptance criteria in the context of a medical device submission, particularly for an infusion pump, and extract information where parallels can be drawn.

Acceptance Criteria for Omnipod DASH™ Insulin Management System with Interoperable Technology

The acceptance criteria for this device, as outlined in the "Special Control" section, predominantly focus on the safety and performance of the insulin pump itself, especially given its new interoperable functionality. The performance data presented demonstrates how the device meets these controls, often by stating that the subject device is identical to previous cleared versions (K182630 and K180045) and that previous testing is applicable, with some additional characterization.

1. Table of Acceptance Criteria and Reported Device Performance

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

The document does not explicitly state the specific sample sizes for tests. It generally refers to previous clearances (K182630, K180045) for most testing, stating that the subject device is "identical" or that previous testing is "applicable," with "further characterization" or "delivery accuracy" specifically conducted for this submission.

• Sample Size: Not explicitly stated for specific tests in this summary. It mentions "statistically valid number of devices" as a requirement for delivery accuracy testing in the special control.
• Data Provenance: The data comes from the manufacturer's (Insulet Corporation) internal testing and previous FDA submissions (K182630, K180045). The country of origin for the data is not specified but is implied to be within Insulet's testing facilities (Acton, MA, USA is their address). The data would be prospective in nature, generated specifically for these regulatory submissions.

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

This information is not applicable in the context of this device. The Omnipod DASH Insulin Management System is an infusion pump, not a diagnostic device that relies on human expert interpretation of data (like medical images) to establish ground truth. The "ground truth" for this device relates to its physical and functional performance (e.g., accurate insulin delivery, proper communication), which is established through engineering and performance testing against predefined specifications.

4. Adjudication Method for the Test Set

This information is not applicable. Adjudication methods like 2+1 or 3+1 are used in studies where human readers are interpreting data or making diagnoses, and their initial assessments need to be reconciled to establish a consensus ground truth. For an infusion pump, performance is measured objectively via test equipment and quantitative outputs.

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

No, an MRMC study was not done or applicable. MRMC studies compare the performance of human readers, sometimes with and without AI assistance, especially in diagnostic imaging or similar fields. This device is an insulin pump, not a diagnostic tool where human interpretation is being augmented.

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

This concept is partially applicable but in a different context. The "algorithm" here is the pump's internal software controlling insulin delivery and communication. The "standalone" performance would be the pump's ability to deliver insulin accurately and communicate reliably based on pre-programmed settings or commands, independent of a human directly monitoring every millisecond. The performance tests (delivery accuracy, hazard detection, interoperability) are essentially evaluations of the pump's "standalone" (or automated) functional performance. The human (user) interacts with the PDM to initiate commands, but the core function (insulin delivery) is automated by the pump's internal algorithms.

7. The Type of Ground Truth Used

The "ground truth" for this device's performance is based on engineering specifications, established physical measurement methods, and regulatory standards for insulin pump function and safety.

Examples:

• For "infusion delivery accuracy," the ground truth is the precisely measured volume of fluid delivered compared to the commanded volume, determined using calibrated equipment.
• For "hazard detection," the ground truth is a simulated hazard (e.g., occlusion) and the objective measurement of the time taken for the pump to detect and alarm, compared against predefined safety limits.
• For "biocompatibility," the ground truth is the absence of adverse biological reactions, confirmed by standardized in-vitro and in-vivo tests according to ISO standards.

8. The Sample Size for the Training Set

This is not applicable in the AI/ML sense. This device is a traditional medical device (an infusion pump) with embedded software. It does not learn or get "trained" from data in the way a machine learning algorithm does. Its operation is based on deterministic algorithms and hardware.

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

This is not applicable as there is no "training set" for an AI/ML model for this device. The ground truth for its development and validation (e.g., engineering specifications, performance requirements) is established through established medical device development processes, risk analysis, and compliance with national and international standards (e.g., ISO, FDA guidance).

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Omnipod Insulin Management System

The Omnipod® Insulin Management System is intended for subcutaneous delivery of insulin at set and variable rates for the management of diabetes mellitus in persons requiring insulin and for the quantitative measurement of glucose in fresh whole capillary blood (in vitro) from the finger.

The glucose measurements should not be used for the diagnosis or screening for diabetes. The PDM glucose meter is intended for single patient use and should not be shared.

Abbott FreeStyle® test strips are used with the built-in FreeStyle meter for the quantitative measurement of blood glucose in fresh whole capillary blood from the finger, upper arm and palm. Abbott Freestyle Control Solutions are used to verify that the meter and test strips are working together properly and that the test is performed correctly.

Omnipod DASH Insulin Management System

The Omnipod DASH Insulin Management System is intended for subcutaneous delivery of insulin at set and variable rates for the management of diabetes mellitus in persons requiring insulin.

Additionally, the Omnipod DASH System is interoperable with a compatible blood glucose meter to receive and display glucose measurements.

The subject devices provide for the management of insulin therapy and blood glucose monitoring by patients with diabetes mellitus. They are each comprised of two primary components: the disposable insulin infusion pump (Pod) and an associated wireless remote controller referred to as the Personal Diabetes Manager (PDM). The PDMs incorporate a suggested bolus calculator which aids the user in determining the insulin bolus dosage needed based on carbohydrates ingested, most recent blood glucose reading, programmable correction factor, insulin to carbohydrate ratio, target blood glucose value, and Insulin on Board (IoB).

The Pod is a body-wearable insulin pump that affixes to the user on the back of the arm, the lower back or abdomen, the thigh area, or any site that has a layer of fatty tissue available. It is held in place by an adhesive pad and provides up to three days of insulin before it is removed and replaced with a new Pod. The PDM is a handheld device that controls the Pod. The user interfaces with the device system through the PDM, where they control basal and bolus delivery and various insulin program settings and calculations. The PDM also has a food library to assist with carbohydrate calculations, and it maintains several variables in a history log for the viewer to track their diabetes therapy. The Omnipod Insulin Management System PDM has an integrated blood glucose meter and communicates with the Pod using wirelessly using secure, low power, bi-directional radio frequency (RF) communications at 433.92MHz. The Omnipod DASH Insulin Management System PDM does not have an integrated blood glucose meter, but is interoperable with a compatible blood glucose meter to receive and display glucose measurements. The Omnipod DASH PDM communicates to the Pod and a compatible blood glucose meter using Bluetooth Low Energy.

Both systems are for prescription use only.

The provided document is a 510(k) summary for the Omnipod Insulin Management System and Omnipod DASH Insulin Management System. It describes modifications to an existing device rather than a new device and thus does not contain the specific information requested in the prompt regarding a study that proves the device meets specific acceptance criteria with detailed statistical analysis.

However, based on the Performance Data and Standards Compliance section, I can extract information about the types of testing performed and the general conclusions, even if the detailed acceptance criteria and study designs are not fully elaborated.

Here's an attempt to answer using the available information, noting where specific details are missing:

1. Table of Acceptance Criteria and Reported Device Performance

Missing Information: The document does not provide the specific numerical acceptance criteria (e.g., specific thresholds for leachables, precise depth specifications, or quantitative results from the stability/compatibility testing). It states that criteria were "met" or "verified" or "validated."

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

The document mentions "Real-world data analysis: An analysis of post-market data gathered from devices with the modified soft cannula was conducted..."

• Sample Size: Not specified.
• Data Provenance: Retrospective, post-market data. The country of origin is not specified.

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

Not applicable as this was not a diagnostic image-based AI study relying on expert ground truth. The "ground truth" for cannula performance or insulin stability would be derived from laboratory measurements and clinical outcomes, not expert consensus on interpretations.

4. Adjudication Method for the Test Set

Not applicable for this type of device modification study. Adjudication methods like 2+1 or 3+1 typically refer to reconciliation of discrepancies among multiple expert readers in diagnostic studies.

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 common for diagnostic imaging AI. The document focuses on performance testing of the device's physical and chemical properties and post-market safety.

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

The device is an insulin pump system with a bolus calculator, not a standalone AI algorithm for diagnosis. Therefore, this question isn't directly applicable in the typical sense of AI standalone performance. The "algorithm" for dose calculation is part of the system's intended function, and its overall safety and effectiveness were assessed as part of the system.

7. The Type of Ground Truth Used

• For Drug Stability and Compatibility: Laboratory analytical results for insulin integrity (e.g., potency, purity, presence of leachables).
• For Soft Cannula Studies: Engineering measurements and specifications for insertion depth and insulin infusion depth.
• For Safety and Effectiveness (Real-world data): Clinical outcomes, adverse event reports, and other post-market surveillance data.
• For Sterilization: Microbiological test results (bioburden) and compliance with sterilization standards.
• For Risk Management: Verification activities demonstrating that risks identified were mitigated to an acceptable level as defined by ISO 14971.

8. The Sample Size for the Training Set

Not applicable. This document describes a modification to an existing device, and the "real-world data analysis" was for post-market validation, not for training a machine learning model in the context of an AI device. The bolus calculator is rule-based and user-programmed, not an AI model requiring a training set in the typical sense.

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

Not applicable, as there's no mention of a traditional "training set" for an AI model.

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The Omnipod DASH™ Insulin Management System is intended for subcutaneous delivery of insulin at set and variable rates for the management of diabetes mellitus in persons requiring insulin.

Additionally. the Omnipod DASH System is interoperable with a compatible blood glucose meter to receive and display glucose measurements.

The Omnipod DASH™ Insulin Management System provides for the management of insulin therapy by patients with diabetes mellitus. It is comprised of two primary components: the disposable insulin infusion pump (Pod), and an associated Bluetooth Low Energy (BLE) enabled remote controller referred to as the Personal Diabetes Manager (PDM). The PDM can communicate with interoperable, compatible BLE enabled blood glucose meters. The PDM incorporates a suggested bolus calculator which aids the user in determining the insulin bolus dosage needed based on carbohydrates ingested, most recent blood glucose reading, programmable correction factor, insulin to carbohydrate ratio, target blood glucose value and Insulin on Board (IoB).

The Pod is a body-wearable insulin pump that affixes to the user on the back of the arm, the lower back or abdomen, the thigh area, or any site that has a layer of fatty tissue available. It is held in place by an adhesive pad and provides up to three days of insulin before it is removed and replaced with a new Pod. The PDM is a handheld device that controls the Pod. The user interfaces with the device system through the PDM using a touch screen, similar to a smartphone, where they control basal and bolus delivery and various insulin program settings and calculations. The PDM also has a food library to assist with carbohydrate calculations, and it maintains several variables in a history log for the viewer to track their diabetes therapy. The device system is for prescription use only.

The provided text describes the Omnipod DASH™ Insulin Management System and its 510(k) submission (K180045) to the FDA. The submission asserts substantial equivalence to a predicate device (K162296 Omnipod® Insulin Management System).

However, the document does not contain a typical acceptance criteria table with reported device performance in a numerical or statistical format that is commonly used for AI/ML-based diagnostic devices. Instead, it focuses on demonstrating safety and effectiveness through compliance with various standards and guidance documents. The "acceptance criteria" are implied by the successful completion of various tests and adherence to regulatory standards.

Here's a breakdown of the requested information based on the provided text, recognizing that it pertains to an insulin pump and not a diagnostic AI/ML device:

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

The document does not explicitly provide a table of acceptance criteria with corresponding performance metrics like sensitivity, specificity, accuracy, or other statistical measures, as would be common for AI/ML diagnostic tools. Instead, the "acceptance criteria" are implied by successful completion of various engineering, safety, and regulatory compliance tests. The "reported device performance" is that the device met these criteria.

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

The document lists various types of tests (bench testing, software V&V, human factors, biocompatibility, safety, EMC) but does not specify the sample sizes for these tests. For instance, for mechanical integrity or software testing, there's no mention of the number of devices or iterations tested. Similarly, no information is provided regarding data provenance (e.g., country of origin, retrospective/prospective). This type of detail is typically contained within the full test reports referenced by the 510(k) summary, but not elaborated here.

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 in a way that is relevant to AI/ML ground truthing. The "ground truth" for an insulin pump's performance is typically established through engineering specifications, regulatory standards, and clinical outcomes, rather than expert consensus on diagnostic interpretations. The document states that the safety assurance case and human factors validation involved identifying and mitigating risks (suggesting expert input in risk analysis), but it doesn't specify the number or qualifications of experts in the context of "ground truth" as it would for image-based diagnostic AI.

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

This detail is not mentioned. Adjudication methods like "2+1" or "3+1" are usually associated with establishing ground truth in clinical studies, particularly for diagnostic imaging. For an insulin pump, validation often relies on meeting predetermined engineering and safety specifications through direct measurement and testing, rather than a consensus-based adjudication process for interpretations.

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 study was performed or is referenced. This type of study is specifically designed for evaluating the impact of AI on human readers in diagnostic tasks, which is not applicable to the Omnipod DASH™ Insulin Management System as it is an insulin delivery device, not a diagnostic AI.

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

The device is an insulin pump, and its "algorithm" (the insulin dose calculator) is inherently designed for human-in-the-loop operation, where the user makes decisions based on the device's calculations and their own blood glucose readings. Therefore, a standalone "algorithm-only" performance study in the context of removing human interaction is not relevant or described. The document does mention "PDM software algorithm error results in errant insulin infusion program on the Pod," indicating that the software's performance is tested, but not as a replacement for human decision-making.

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

For this medical device, the "ground truth" is largely defined by:

• Engineering Specifications: The device must deliver insulin accurately, reliably, and safely according to its design parameters.
• Regulatory Standards: Compliance with international standards (e.g., ISO 14971 for risk management, ISO 10993 for biocompatibility, IEC 60601 series for electrical safety and performance, IEC 62304 for software).
• Safety Assurance Cases: Demonstrating that identified hazards are adequately mitigated and the system is acceptably safe for its intended use.
• Intended Use Validation: Human factors studies confirm that the device can be used safely by the target population.
• Clinical Efficacy (implied by predicate): The device's primary function (insulin delivery for diabetes management) is well-established therapy. The device demonstrates substantial equivalence to a predicate device, implying similar clinical effectiveness.

It is not based on expert consensus, pathology, or outcomes data in the typical sense of a diagnostic AI.

8. The sample size for the training set

Not applicable. The Omnipod DASH™ Insulin Management System is not an AI/ML device that undergoes "training" based on a dataset. It is a programmed medical device that operates based on predefined algorithms and user input.

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

Not applicable, as there is no "training set" for this type of medical device.

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The DASH 6® NRFit Lock syringe and DASH® NRFit Slip Syringe are intended to be used with ISO 80369-6 NRFit neuraxial compliant devices for administration of neuraxial medication.

The DASH 6® NRFit Plastic LOR Device is intended to be used with ISO 80369-6 NRFit neuraxial compliant epidural needle for locating the epidural space.

Accessories:

DASH 6® Introducer Needle is intended to be used with ISO 80369-6 NRFit neuraxial compliant spinal needle for guiding the placement of the spinal needle into the arachnoid/epidural space.

DASH 6@ NRFit Syringe Cap is intended to be used with ISO 80369-6 NRFit neuraxial syringes for sealing the tip of the syringe.

DASH 6® NRFit Drawing Up Filter Straw are intended to be used with ISO 80369-6 NRFit neuraxial syringe for the drawing up of neuraxial medication and anesthetic.

DASH 6@ NRFit Blunt Drawing Up Needle (with and without filter) is intended to be used with ISO 80369-6 NRFit neuraxial syringe for the drawing up of neuraxial medication and anesthetic.

DASH 6® NRFit Bacterial Disc Filter is intended to be used with ISO 80369-6 NRFit neuraxial compliant devices to ensure aseptic administration of neuraxial medication and anesthetic.

DASH 6® NRFit Epidural Flat Filter is intended to be used with ISO 80369-6 NRFit neuraxial compliant devices to ensure aseptic administration of neuraxial medication and anesthetic.

DASH 6® NRFit Tuohy-Borst Adapter is intended to be used with a epidural catheter to provide an ISO 80369-6 NRFit compliant connection.

DASH 6® NRFit Syringe to Syringe Adapter is intended to be used with ISO 80369-6 NRFit neuraxial syringe to allow for mixing/transfering medication between two syringes.

DASH 6® NRFit Needle Hub Cap is intended for sealing the hub of an NRFit compliant needle.

DASH 6@ NRFit Epidural Catheter Feeder is intended to be used with ISO 80369-6 NRFit neuraxial compliant devices to assist the insertion of an epidural needle into the epidural space.

The DASH 6® NRFit Syringes (Lock and Slip Syringes) are Single Use, in-hospital devices. They are provided in sizes ranging from 1 mL to 60 mL. The devices incorporate a male NRFit connector for connection to a female NRFit port. The syringes are designed according to ISO 7886-1 & ISO 80369-6 standard. The syringes are used for neuraxial purposes (ISO 80369-6 NRFit connection) and functions exactly the same as any hypodermic syringes that are on the market (ISO 7886-1).

The syringes will be supplied as individually packed (sterile) and the bulk packed (Nonsterile). The Sterile packed items will be supplied directly to the user and the bulk packed will be supplied to Anesthetic Conduction Kit manufacturers to be packaged into kit.

The syringe packaging will indicate the volume/size, the connector type (Lock or Slip variants) that the syringe contains and the sterility/sterilization method the syringe have been processed.

The DASH 6 ° Plastic LOR devices are Single Use, in-hospital devices. It is provided with a 10 mL size/volume and incorporates a male ISO 80369-6 NRFit slip connector to connect to a female ISO 80369-6 NRFit Port.

The Plastic LOR devices are designed according to ISO 80369-6 standard. The syringes are used for neuraxial purposes (ISO 80369-6 NRFit connection) and functions exactly the same as the LOR devices on the market.

The device will be supplied as individually packed (sterile) and the bulk packed (Nonsterile). The Sterile packed items will be supplied directly to the user and the bulk packed will be supplied to Anesthetic Conduction Kit manufacturers to be packaged into kit.

The devices packaging will indicate the volume/size, the connector type (Slip) that the device contains and the sterility/sterilization method the device have been processed.

Accessories:
DASH 6® NRFit Syringe Caps: Single Use, in-hospital devices with a female ISO 80369-6 NRFit connector.
DASH 6® NRFit Drawing up Filter Straw: Single Use, in-hospital devices with a female ISO 80369-6 NRFit connector and filter.
DASH 6 ° NRFit Blunt Drawing up Needle (with and without filter): Single Use, in-hospital devices with a female ISO 80369-6 NRFit connector and blunt needle (with or without filter).
DASH 6® NRFit Bacterial Disc Filter: Single Use, in-hospital devices with male & female ISO 80369-6 NRFit connectors and a 0.22µm filter.
DASH 6® NRFit Epidural Flat Filter: Single Use, in-hospital devices with male & female ISO 80369-6 NRFit connectors and a 0.22um filter.
DASH 6 ° NRFit Tuohy Borst Adapter: Single Use, in-hospital devices with a female ISO 80369-6 NRFit connector and open catheter port.
DASH 6® NRFit Needle Hub Caps: Single Use, in-hospital devices with a Male ISO 80369-6 NRFit connector.
DASH 6® Epidural Catheter Feeder: Single Use, in-hospital devices with a compatible male ISO 80369-6 NRFit connector.

The provided text is a 510(k) Premarket Notification for the DASH 6® NRFit System, which includes syringes and various accessories. This document primarily focuses on demonstrating substantial equivalence to predicate devices through design verification and compliance with specific ISO standards. It does not describe an AI medical device or a study involving human readers or AI assistance. Therefore, I cannot provide information on acceptance criteria and a study that proves the device meets those criteria in the context of AI performance, MRMC studies, standalone algorithm performance, number of experts, or ground truth for AI model development.

However, I can extract the acceptance criteria and the type of study conducted to demonstrate the device's technical specifications and substantial equivalence, as presented in the document:

1. Table of Acceptance Criteria and Reported Device Performance

The acceptance criteria for the DASH 6® NRFit System are primarily defined by compliance with several ISO standards. The studies conducted were design verification tests demonstrating compliance with these standards.

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

The document describes bench testing for physical characteristics, dimensional verification, and biocompatibility, not a clinical study with a "test set" in the context of AI or diagnostic performance. Therefore, typical sample size or data provenance details for medical image analysis are not applicable. The testing was conducted to verify compliance with engineering standards (ISO standards). The document does not specify the exact number of units tested for each specific test, but mentions "All necessary bench testing was conducted."

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 is not applicable as the device is a physical medical device (syringes, needles, etc.) and its performance is evaluated against engineering and biological standards, not diagnostic interpretations from experts. Ground truth is established by objective measurements against specified engineering and material science criteria.

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

Not applicable. This device is not an AI diagnostic tool and does not involve human adjudication of results in the traditional sense of a clinical study or image interpretation.

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. The DASH 6® NRFit System is a medical device (syringes, needles, etc.) and not an AI-powered diagnostic or assistive tool.

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

Not applicable. This device is not an algorithm or AI system. Its performance is evaluated intrinsically based on its physical properties and adherence to manufacturing and safety standards.

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

The "ground truth" for this device's evaluation is primarily the specifications and requirements defined by international standards (e.g., ISO 80369-6, ISO 7886-1, ISO 10993 series) and the manufacturer's own design specifications. It is based on objective, quantifiable physical and chemical measurements (e.g., fluid leakage, dimensions, material compatibility).

8. The sample size for the training set

Not applicable. There is no "training set" as this is a physical medical device, not a machine learning model.

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

Not applicable.

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The DASH 3TM ENFit Syringe is a sugle use syninge indicated for use as a dispenser, a measuring device, and a fluid transfer device. It is used to deliver fluids or nututional formula into the gastrointestinal system of a patient who is physically unable to eat and swallow. The enteral synnges are intended to be used in clinical or home care settings by users ranging from laypersons (under the supervision of a clinician) to clinicians, in all age groups.

The DASH 3TM Eccentric ENFit Syringe is a single use syringe indicated for use as a dispenser, a measuring device, and a fluid transfer device. It is used to deliver fluids or nutritional formula into the gastrointestinal system of a patient who is physically unable to eat and swallow. The enteral syninges are intended to be used in clinical or home care settings by users ranging from laypersons (under the supervision of a clinician) to clinicians, in all age groups.

The DASH 3TM Low Volume Tip ENFit Syringe is a sungle use syringe indicated for use as a dispenser, a measuning device, and a fluid transfer device. It is used to deliver fluids or nutritional formula into the gastrointestinal system of a patient who is physically unable to eat and swallow. The enteral syninges are intended to be used in clinical or home care settings by users ranging from laypersons (under the supervision of a clinicians, in all age groups.

The DASH 3M ENFit Syringe Cap allows the advance preparation and secure storage and transport of medication fluids or mutritional formula. The synnge cap will fit any size of the Single Use Synnges (DASH 3TM)

The DASH 3™ ENFit Syringe device family is a Single Use, in-hospital and home care (DASH 3TM ENFit Syringe, DASH 3TM Eccentric ENFit Syringe, DASH 3TM ENFit Low Dose Tip Syringe) device.

It is provided in sizes from 1 mL to 100 mL. The device incorporates a female ENFit connector for connection to an enteral access device with a male ENFit port specified in ISO 80369-3. The Low Dose Tip contains the low dose design feature specified in (Draft) ISO 20695.

The DASH 3TM ENFit accessories are designed to be compatible with ENFit connector devices. The DASH 3TM ENFit Syringe Caps fit any size of the Single Use ENFit Syringes (DASH 3™), which allows the advance preparation and secure storage and transport of medication/fluids or nutritional formula.

The provided text describes a medical device, the DASH 3™ ENFit Syringe family and its accessories, and outlines the testing conducted to demonstrate its substantial equivalence to predicate devices, rather than a study proving the device meets specific acceptance criteria in the context of diagnostic performance. Therefore, I cannot extract information related to sample sizes for test sets, data provenance, number of experts for ground truth, adjudication methods, MRMC studies, standalone performance, or training set details as these are not relevant to this type of device submission.

However, I can provide the acceptance criteria and confirmed performance based on the engineering and functional testing described in the document.

Acceptance Criteria and Reported Device Performance

The device performance is demonstrated through various tests designed to confirm compliance with ISO standards and other design specifications. The document states that the DASH 3™ Syringe device family and its accessories "met all acceptance criteria, as described in Section 17." The table below summarizes the listed tests, which serve as the acceptance criteria, and the reported outcome.

Details of the Study:

The studies conducted are primarily engineering and functional bench tests, and risk assessments.

• Sample sized used for the test set and the data provenance: The document does not specify exact sample sizes for each test. The data provenance is implied to be from internal testing conducted by the manufacturer, Intervene Group Limited, likely in the UK, given the address. The studies are prospective in the sense that they were conducted for the purpose of this 510(k) submission.
• Number of experts used to establish the ground truth for the test set and the qualifications of those experts: Not applicable. Ground truth for these types of engineering tests is typically defined by adherence to published international standards (e.g., ISO) and the device's design specifications, not by expert consensus on observational data.
• Adjudication method (e.g. 2+1, 3+1, none) for the test set: Not applicable. Performance is measured against predefined objective standards and specifications.
• 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 is not an AI/diagnostic device.
• If a standalone (i.e. algorithm only without human-in-the-loop performance) was done: Not applicable. This is not an AI/diagnostic device.
• The type of ground truth used (expert consensus, pathology, outcomes data, etc): The "ground truth" for these tests is the adherence to the requirements outlined in the cited ISO standards (ISO 80369-3, ISO 80369-20, ISO 7886-1, Draft ISO 20695) and the internal design specifications of the device.
• The sample size for the training set: Not applicable. This is not a machine learning device; therefore, there is no "training set."
• How the ground truth for the training set was established: Not applicable.

In conclusion, the study supporting the device's substantial equivalence consists of a series of bench tests and assessments confirming that the DASH 3™ ENFit Syringe family and its accessories meet established engineering and performance standards, thereby demonstrating that they perform as intended and do not raise new questions of safety or effectiveness compared to predicate devices.

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Under the supervision of a healthcare professional, Dash-Topic Plus Cream is indicated to manage and relieve the burning, itching and pain experienced with various types of dermatoses, including atopic dermatitis, allergic contact dermatitis and radiation dermatitis. Dash-Topic Plus Cream also helps to relieve dry, waxy skin by maintaining a moist wound & skin environment, which is beneficial to the healing process.

Dash-Topic Plus Cream is a non-sterile, off-white, low odor, fragrance free, topical product. Dash-Topic Plus Cream forms a physical barrier that helps to maintain a moist wound and skin environment. Dash-Topic Plus Cream is a prescription device.

The provided document is a 510(k) summary for the medical device "Dash-Topic Plus Cream." It is a regulatory submission for premarket notification, aiming to demonstrate substantial equivalence to a legally marketed predicate device. This type of document focuses on comparing the new device to an existing one, rather than presenting a study of its independent effectiveness against clinical outcomes or a rigorous clinical trial. Therefore, the document does not contain the information required to answer your specific questions about acceptance criteria, detailed study designs, sample sizes, expert ground truth, or comparative effectiveness with human readers.

The document discusses "Performance Data" but this refers to non-clinical testing (biocompatibility, stability, etc.) to ensure safety and functionality, not clinical performance in terms of diagnostic accuracy or impact on human readers.

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

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

• Missing from document: The document does not provide a table of acceptance criteria in terms of clinical efficacy or diagnostic performance. The "performance data" section (Section VIII) lists non-clinical tests (biocompatibility, stability) and states the results (e.g., "non-cytotoxic, a negligible irritant and non-sensitizing"), but it doesn't define acceptance criteria for these tests within the narrative. Their acceptance is implied by the "Conclusion" that the device is substantially equivalent.

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

• Missing from document: There is no clinical test set described in the sense of a patient cohort or diagnostic images. The "tests" mentioned are laboratory-based assays (e.g., Agar Diffusion Cytotoxicity). Sample sizes for these types of tests typically refer to the number of samples or replicates tested in the lab, not patient populations. No data provenance in terms of country of origin or retrospective/prospective nature is applicable as no clinical study is described.

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)

• Missing from document: Not applicable. No clinical ground truth or expert review is mentioned because no clinical study or diagnostic AI algorithm testing is described.

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

• Missing from document: Not applicable. No clinical adjudication method is mentioned as there is no clinical test set to adjudicate.

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

• Missing from document: Not applicable. This document pertains to a topical cream, not an AI-powered diagnostic device, and therefore no MRMC study was performed or described.

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

• Missing from document: Not applicable. This device is a topical cream, not an algorithm.

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

• Missing from document: Not applicable for clinical ground truth. For the non-clinical tests, the "ground truth" would be the established scientific standards and methods for assessing cytotoxicity, irritation, sensitization, and stability (e.g., ISO standards, USP monographs).

8. The sample size for the training set

• Missing from document: Not applicable. This document is for a medical device (topical cream), not an AI algorithm that requires a training set.

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

• Missing from document: Not applicable. As above, there is no AI algorithm or training set.

Summary of what the document does provide regarding "performance":

The "Performance Data" (Section VIII) describes non-clinical testing to confirm the safety and effective performance in terms of the cream's physical and biological interaction with the body (biocompatibility) and its stability.

• Tests Conducted:

  • Agar Diffusion Cytotoxicity (ISO 10993-5: 2009)
  • Direct Primary Skin Irritation (ISO 10993-10:2010)
  • Kligman Maximization Sensitization (ISO 10993-10:2010)
  • Bench performance testing for release and shelf life stability (monitored parameters: Appearance, pH, preservative content, viscosity and package integrity)
  • Preservative Effectiveness Testing as per USP (Antimicrobial Effectiveness Testing)
  • USP (Microbial Enumeration Tests and Tests for Specified Microorganisms)
  • In-use stability testing for opened 450g container (monitored parameters: Appearance, pH, preservative content, viscosity, package integrity, USP and USP )

• Reported Results (Performance):

  • Dash-Topic Plus Cream is non-cytotoxic.
  • Dash-Topic Plus Cream is a negligible irritant.
  • Dash-Topic Plus Cream is non-sensitizing.
  • The bench performance data confirmed the physical characteristics, stability, and shelf-life.

The acceptance criteria for these tests are implicitly that the device passes specific thresholds or shows no adverse effects according to the referenced ISO and USP standards. However, the exact numerical acceptance criteria are not explicitly stated in this summary.

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The Decisio Health Patient Dashboard is a decision support device indicated for aggregating, displaying, and managing physiologic and other patient information. This information is generated by third party medical devices and patient information systems. The device performs automated calculations on patient data collected by third party devices based on approved clinical protocols at patient care facilities.

The Decisio Health Patient Dashboard is intended for use by clinicians in healthcare facilities.

The Decisio Health Patient Dashboard ("Patient Dashboard") is a data aggregation and visualization software device. The Patient Dashboard is designed to display patient information, facility specific care protocols, and visual cues to care providers on a single display device. The Patient Dashboard is configured to receive patient data through the facility's Electronic Medical Record system and display information to the user on a patient monitor, computer, or a mobile device. Data received through the EMR includes input from various sources within the hospital, including manually entered data into the EMR (e.g., laboratory data), vital signs monitors, ventilators, IV pumps, and Foley catheter devices. The data the Patient Dashboard receives are then stored, filtered, and displayed through the Patient Dashboard web browser application. The Patient Dashboard is customized to individual facility's care as it is programmed with the facility's treatment protocols, which dictate the information that is displayed relative to those protocols. The device performs automated calculations on patient data collected by third party devices based on approved clinical protocols at patient care facilities.

This document (K142106) describes the Decisio Health Patient Dashboard, a decision support device designed to aggregate, display, and manage patient information from third-party medical devices and information systems.

Here's an analysis of the provided information regarding acceptance criteria and the supporting study:

1. Table of Acceptance Criteria and Reported Device Performance

The document does not explicitly present a table of specific acceptance criteria (e.g., specific accuracy thresholds for calculations, or display fidelity metrics) with corresponding numerical device performance results as one might expect for a diagnostic or classification device.

However, based on the Testing in Support of Substantial Equivalence Determination section, the general acceptance criteria can be inferred as:

• Receiving data from the EMR.
• Processing patient data according to a facility protocol.
• Displaying the data as expected.
• Performing automated calculations on patient data based on approved clinical protocols. | "Unit, integration, and system level testing demonstrated that the Patient Dashboard meets its specifications, including receiving data from the EMR, processing patient data according to a facility protocol, and displaying the data as expected." "Performance testing verified that the device performs as intended." (No specific numerical metrics are provided for these performance aspects in the summary.) |
  | Usability/ Human Factors | The device design meets its intended use, and the user can interpret the displayed information as intended. | "Additionally, a human factors and usability study has been performed with the Patient Dashboard... The results of the study confirmed that the Patient Dashboard design meets its intended use and the user can interpret the displayed information as intended." (No specific quantitative usability metrics or error rates are provided, only a general confirmation of meeting the goal.) |
  | Safety & Effectiveness | Differences in technological characteristics between the Patient Dashboard and predicate devices do not raise new issues of safety or effectiveness. | "The differences in technological characteristics between the Patient Dashboard and the predicate devices do not raise new issues of safety or effectiveness." and "The differences in technological characteristics have been analyzed and addressed through software performance testing, and human factors and usability testing." (This is a qualitative statement of equivalence, not a direct performance metric.) |

Note: This submission is for a Class II regulatory clearance (510(k)), which focuses on demonstrating substantial equivalence to a legally marketed predicate device rather than independently proving safety and effectiveness through extensive clinical trials like a PMA. Therefore, the level of detail on specific performance metrics might be less extensive than for some other device types.

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

• Test Set Sample Size:
  • Functional Testing (Software Performance Testing): The document states "Unit, integration, and system level testing." It does not specify a numerical sample size for data points or test cases used in this testing.
  • Human Factors and Usability Study: 45 clinicians were involved.
• Data Provenance: The document does not specify the country of origin for the data used in functional testing. For the human factors study, it implies the clinicians are from "healthcare facilities" where the device is intended for use, but no specific geographic location is mentioned. The study is prospective in nature, as it was conducted specifically for the device submission.

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

• Functional Testing: The document does not mention external experts establishing ground truth for functional software testing. This type of testing typically relies on predefined specifications and expected outputs generated by developers or quality assurance engineers.
• Human Factors and Usability Study: The "clinicians" (45 of them) served as the "experts" or primary evaluators in this study by providing feedback on the device's design and interpretability. Their specific qualifications (e.g., tenure, specialty) are not detailed beyond "clinicians." The "ground truth" for usability is their ability to correctly interpret displayed information and interact with the device as intended.

4. Adjudication Method for the Test Set

• Functional Testing: Not applicable in the context of expert adjudication. Software testing typically involves verifying outputs against expected results defined by specifications.
• Human Factors and Usability Study: The document does not describe an explicit adjudication method (like 2+1 or 3+1 consensus). The "results of the study confirmed" suggests a summary of observations and feedback from the 45 clinicians led to the conclusion about the design's suitability and interpretability. It's likely a qualitative assessment or a design qualification activity rather than a ground truth establishment by external adjudicators for patient data.

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

• No, a MRMC comparative effectiveness study was not explicitly done or reported. The human factors study involved multiple clinicians but was focused on usability and interpretability of the device's output, not on comparing their performance with and without the AI assistance in a diagnostic or clinical decision-making context with specific clinical outcomes. The device is a "decision support device" that aggregates and displays information; it's not described as an AI that provides specific diagnostic interpretations that would typically warrant a full MRMC study.
• Effect Size of Human Readers Improvement with AI vs. Without AI Assistance: Not applicable, as an MRMC study comparing human performance with and without the device's assistance was not conducted or reported.

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

• Yes, a form of standalone performance was assessed through "Unit, integration, and system level testing." This software performance testing directly addressed how the algorithm (the "Patient Dashboard" software) "receives data from the EMR, processes patient data according to a facility protocol, and displays the data as expected" and "performs automated calculations." This specifically describes the algorithm's functional performance in isolation of direct human interpretative decision-making during the test itself (though it's designed for human use). The output of these tests would be objective verification against specifications.

7. Type of Ground Truth Used

• Functional Testing (Software Performance): The ground truth for this testing would be the predefined specifications for data reception, processing rules (facility protocols), calculation outputs, and display requirements. This implies the ground truth is established by internal engineering and quality assurance standards.
• Human Factors and Usability Study: The "ground truth" (or success criteria) for this study was the intended use and user interpretability, as confirmed by the clinicians. This is a form of expert consensus/feedback on usability and functional clarity, rather than a clinical ground truth like pathology or direct outcomes data.

8. Sample Size for the Training Set

• The document does not mention a training set sample size. This device is described as a "data aggregation and visualization software device" that "performs automated calculations on patient data collected by third party devices based on approved clinical protocols." This suggests it's primarily a rule-based system or a display system for pre-existing calculations/protocols, rather than a machine learning model that requires a "training set" in the conventional sense. If there are any "automated calculations," they are based on "approved clinical protocols," implying rules configured by clinical experts rather than learned from a dataset.

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

• As a training set is not explicitly mentioned or implied for a machine learning model, this question is not applicable. The device's "automated calculations" are stated to be based on "approved clinical protocols at patient care facilities," meaning these protocols themselves serve as the 'ground truth' or rules governing the calculations, established by clinical expertise at the local facility level, not derived from a training dataset.

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