(92 days)
The BCI 1621 Oximetry Data Management Program analyzes data recorded using the BCI 3403 pulse oximeter and provides a printed oximetry data analysis report and graphical SpO2 trend. This information can aid in the analysis of pulse oximetry data from sleep screening, oxygen therapy validation, and/or related studies. Data from the BCI 3403 pulse oximeter are downloaded for analysis using a unique cable.
The BCI® 1621 Oximetry Data Management Program is a software program used as a pulse oximetry accessory.
The provided document is a 510(k) summary for the BCI® 1621 Oximetry Data Management Program. It focuses on demonstrating substantial equivalence to predicate devices rather than providing detailed acceptance criteria and a standalone clinical study for performance.
Here's a breakdown of the information requested, based only on the provided text:
1. Table of Acceptance Criteria and Reported Device Performance
The document does not explicitly state quantitative acceptance criteria for device performance. Instead, it relies on demonstrating that the new device performs "within its specifications" and "as well as the legally marketed predicate device(s)."
| Acceptance Criteria (Explicit) | Reported Device Performance |
|---|---|
| Not explicitly stated in quantitative terms. The implicit criterion is to perform "as well as" predicate devices and "within its specifications." | "The results demonstrated that the BCI® 1621 Oximetry Data Management Program performed within its specifications." |
| "Based on these results, it is our determination that the device is safe, effective, and performs as well as the legally marketed predicate device(s)." |
2. Sample Size Used for the Test Set and Data Provenance
- Sample Size: Not specified. The document mentions "clinical testing of the desaturation identification algorithm and overall software validation using simulators." It does not provide the number of patients, cases, or simulator runs.
- Data Provenance: Not specified regarding country of origin. The testing is described generally as "clinical testing" and "overall software validation using simulators." It does not clarify if the data was retrospective or prospective.
3. Number of Experts Used to Establish the Ground Truth for the Test Set and Qualifications of Those Experts
- This information is not provided in the document. The document describes "clinical testing of the desaturation identification algorithm" but does not detail how ground truth for this testing was established or who established it.
4. Adjudication Method for the Test Set
- This information is not provided in the document.
5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study Was Done, and the Effect Size of How Much Human Readers Improve with AI vs. Without AI Assistance
- No, an MRMC comparative effectiveness study was not done as described. This device is a "Pulse Oximeter Display Software" designed to provide analysis reports and graphical trends for healthcare professionals. It is not an AI-assisted diagnostic tool for human readers in the sense of improving their interpretation accuracy. Its function is to process and present oximetry data, which would then be interpreted by a healthcare professional. Therefore, the concept of improving human reader performance with AI assistance in this context is not applicable based on the device's stated function.
6. If a Standalone (i.e., algorithm only without human-in-the-loop performance) Was Done
- Yes, a standalone evaluation of the algorithm's performance was implied. The document states: "Testing of device performance included clinical testing of the desaturation identification algorithm and overall software validation using simulators." This indicates that the algorithm's ability to identify desaturations and the overall software's functionality were tested independently of human interpretation of the raw data. The phrase "performed within its specifications" suggests a standalone evaluation against predefined criteria for the software's output.
7. The Type of Ground Truth Used
- The document states "clinical testing of the desaturation identification algorithm." While not explicitly detailed, the "ground truth" for identifying desaturations in this context would typically be established by established physiological definitions of desaturation events based on SpO2 measurements, potentially validated by expert review of raw oximetry waveforms or comparison to a gold standard measurement, though this is not specified. The "overall software validation using simulators" would use known, controlled inputs to verify the software's processing and output.
8. The Sample Size for the Training Set
- This information is not provided in the document. The document primarily discusses testing and validation, not the development or training of the "desaturation identification algorithm." Given the age of the document (2002) and the nature of the device (software for displaying and analyzing oximetry data), it is unlikely to involve machine learning in the contemporary sense requiring a "training set" in the way an AI diagnostic algorithm would. The "algorithm" likely refers to a predefined set of rules or calculations for identifying desaturation events.
9. How the Ground Truth for the Training Set Was Established
- This information is not provided as a "training set" in the context of machine learning is not discussed. If the "algorithm" refers to rule-based logic, its "training" would be inherent in its design based on established medical definitions and physiological principles for desaturation.
§ 870.2700 Oximeter.
(a)
Identification. An oximeter is a device used to transmit radiation at a known wavelength(s) through blood and to measure the blood oxygen saturation based on the amount of reflected or scattered radiation. It may be used alone or in conjunction with a fiberoptic oximeter catheter.(b)
Classification. Class II (performance standards).