(448 days)
The OptiScanner® 5000 Glucose Monitoring System is an automated, bedside glucose monitoring device indicated for detecting trends and tracking patterns in persons (age 18 and older) in the surgical intensive care unit. The system collects a venous whole blood sample via connection to a central venous catheter, centrifuges the sample, and measures the plasma glucose concentration. It is not intended for the screening or diagnosis of diabetes mellitus but is indicated for use in determining dysglycemia. The OptiScanner® 5000 Glucose Monitoring System is for in vitro diagnostic use.
The OptiScanner® 5000 Glucose Monitoring System ("OptiScanner") is an in-line, automated, bedside, frequent, automated glucose monitoring system that quantitatively measures the concentration of glucose in the blood of patients in a Surgical Intensive Care Unit (SICU). In contrast to Point of Care (POC) glucose measuring devices that measure glucose using enzymatic techniques, the OptiScanner uses a direct, reagent-free, spectrophotometer method to quantify glucose. The system is comprised of the following three (3) primary components:
- OptiScanner Instrument
- OptiScanner Transport Cart
- OptiScanner Disposable Cartridge
The Instrument is the primary hardware component that houses all electrical, mechanical, analytical, and power subsystems. This includes the integrated pump, spectrometer, and the user interface. For mobility and easy access, the Instrument is mounted onto the chassis of a transport Cart. The Cart, in addition to holding the Instrument, holds batteries, IV pole(s) and a bar code scanner. The Cartridge is a disposable, single patient use, sterile component containing the fluid pathway through which the blood is sampled, stored, processed, and analyzed. The Cartridge is the only component of the OptiScanner system that comes in contact with patient blood. Integrated into the cartridge are tubing sets that are used to connect to the patient and to a saline bag. The Cartridge also includes a syringe that is pre-filled with heparin by the user for processing the blood samples. The Cartridge is inserted into the Instruments interface port that provides connections integrating the fluidic components of the Cartridge with the electromechanical sub-systems of the Instrument.
The document K162042 for the OptiScanner 5000 Glucose Monitoring System provides information on its acceptance criteria and the study conducted to prove it meets these criteria.
Here's a breakdown of the requested information:
1. Table of Acceptance Criteria and Reported Device Performance
The acceptance criteria for system accuracy is implicitly defined by the clinical study's primary endpoint, which the device met.
| Acceptance Criteria (Primary Endpoint) | Reported Device Performance |
|---|---|
| Overall MARD | 7.28% |
| Upper one-sided 97.5% confidence MARD | 7.50% |
| Overall population CV | 10.31% |
| Upper one-sided 97.5% confidence CV | Met (implied) |
2. Sample Size Used for the Test Set and Data Provenance
- Sample Size (Test Set): 160 Surgical Intensive Care Unit (SICU) subjects.
- Data Provenance: The study was a prospective, multi-center, non-randomized, observational study. While the specific countries are not explicitly stated, the context of an FDA submission typically implies data from within the United States or from sites compliant with FDA regulations. The data is prospective.
3. Number of Experts Used to Establish the Ground Truth for the Test Set and Their Qualifications
- This information is not explicitly stated in the provided text. The ground truth was established by a "standard blood glucose reference control device, (Yellow Springs Instruments 2300, [YSI])". This suggests that the YSI 2300 itself, a laboratory-grade analyzer, provided the reference values, rather than human experts interpreting results to establish ground truth.
4. Adjudication Method for the Test Set
- This information is not explicitly stated. The ground truth was established by comparison to the YSI 2300. In a study comparing an automated device to a reference method like the YSI, adjudication by human experts is typically not the primary method for establishing ground truth for individual glucose readings. The "matched samples" nature implies direct comparison between the OptiScanner and YSI readings.
5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study Was Done
- No, an MRMC comparative effectiveness study was not done. This study involved a device measuring glucose values against a reference device, not human readers interpreting results with or without AI assistance. Therefore, there is no effect size of how much human readers improve with AI vs. without AI assistance.
6. If a Standalone (i.e., algorithm only without human-in-the-loop performance) Was Done
- Yes, a standalone performance study was done. The OptiScanner 5000 Glucose Monitoring System is an automated device, and the clinical study (MANAGE IDE) evaluated its performance against a reference standard (YSI) without direct human intervention in the glucose measurement process or interpretation of the raw data by human readers for the purpose of the study's endpoints. The "reported blood glucose levels" from the OptiScanner are a direct output of its algorithm.
7. The Type of Ground Truth Used
- Reference Standard Device: The ground truth was established using a "standard blood glucose reference control device, (Yellow Springs Instruments 2300, [YSI])". The YSI is a laboratory instrument considered a "gold standard" for glucose measurement.
8. The Sample Size for the Training Set
- The document does not explicitly state the sample size used for the training set for the Partial Least Squares (PLS) regression algorithm. It describes the algorithm's use in calculating blood glucose levels but does not detail its development or training data.
9. How the Ground Truth for the Training Set Was Established
- The document does not explicitly state how the ground truth for the training set was established. It mentions that the system detects glucose by analyzing mid-infrared (MIR) light absorption spectra and calculates levels using a set of PLS regression algorithms. This implies that the algorithm would have been trained on reference glucose values (likely from a method similar to YSI or other lab analyzers) corresponding to MIR spectra. However, the specifics of this training process and ground truth establishment are not provided in the summary.
§ 880.5725 Infusion pump.
(a)
Identification. An infusion pump is a device used in a health care facility to pump fluids into a patient in a controlled manner. The device may use a piston pump, a roller pump, or a peristaltic pump and may be powered electrically or mechanically. The device may also operate using a constant force to propel the fluid through a narrow tube which determines the flow rate. The device may include means to detect a fault condition, such as air in, or blockage of, the infusion line and to activate an alarm.(b)
Classification. Class II (performance standards).