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In any area such as neonatal and pediatric intensive care, anesthesia, adult critical care or any other area where the pump use can be monitored or supervised by a trained healthcare professional where the precise administration of fluids including drugs, antibiotics, lipids, blood, blood products, enteral solutions, or other therapeutic solutions is required.

Delivery routes include: Intravenous, arterial, epidural, spinal, enteral, and subcutaneous.

Delivery modes include: Continuous, volume/time, mass, body weight, and bolus.

The ABC Syringe Infusion Pump Model 4100 is software driven and microprocessor controlled electromechanical system, powered by 120VAC converted to DC (or an internal DC battery pack if AC power is not supplied), which is designed to allow the operator to program the infusion of fluid through a syringe and an administration set. The pump delivers fluid by controlling the displacement of the syringe plunger in accordance with the program entered by the operator.

Here's an analysis of the acceptance criteria and the study proving the device meets those criteria, based on the provided text:

Acceptance Criteria and Reported Device Performance

The acceptance criteria for the ABC Syringe Infusion Pump Model 4100 are primarily demonstrated by its compliance with international standards and its performance in specific tests, showing substantial equivalence to predicate devices. The document does not provide specific numerical acceptance thresholds or detailed performance metrics for each test, but rather asserts that the device "met or exceeded" the performance of the predicates.

• IEC 60601-1 (General requirements for safety)
• IEC 60601-1-2 (EMC requirements and tests)
• IEC 60601-2-24 (Particular requirements for the safety of infusion pumps and controllers) |

Study Details

Based on the provided text, the study conducted for the ABC Syringe Infusion Pump Model 4100 was primarily focused on demonstrating substantial equivalence to predicate devices through various performance tests and compliance with international standards. This is a common approach for 510(k) submissions, rather than a clinical trial in the traditional sense for AI/software devices.

Here's a breakdown of the requested information based on the available text:

1. 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 specify a "test set" in the context of patient data or clinical cases. The testing described appears to be bench testing or laboratory-based performance testing using "identified syringes."
   • No information is provided on the number of syringes used, their provenance, or whether the data was retrospective or prospective.

2. 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 or provided. The "ground truth" for this type of device (an infusion pump) would be the physical measurements of flow rate, accuracy, and occlusion pressure, as defined by engineering specifications and standards, not expert clinical interpretation.

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

   • This information is not applicable or provided. Adjudication methods are typically used in studies involving human interpretation (e.g., image reading) to resolve discrepancies. For a mechanical/electrical device, performance is measured against objective standards.

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 MRMC comparative effectiveness study was done. This type of study is relevant for AI-powered diagnostic or interpretive tools, not for an electromechanical infusion pump.

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

   • The device itself is a "standalone" electromechanical system. The performance testing (flow delivery, occlusion, software validation) was inherently standalone algorithm/device performance, as it wasn't evaluating human-in-the-loop clinical use but rather the device's adherence to its operational specifications.

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

   • The "ground truth" for the performance tests would be engineering specifications, physical measurements, and compliance with the specified international standards (IEC 60601-1, IEC 60601-1-2, IEC 60601-2-24). For example, flow accuracy would be compared to a defined range of acceptable deviation from the programmed rate.

7. The sample size for the training set:

   • This is not applicable as the device is not an AI/Machine Learning model that undergoes a "training phase" with a data set. The software likely went through development, verification, and validation, but not in the sense of an ML model training set.

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

   • Not applicable for the same reason as above.

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