(113 days)
The intended use of NPOSES (Nocturnal Pulse Oximetry Study Expert System) software is to collect, analyze, report and archive oximetry trend data to provide information to a Medical Doctor specializing in sleep medicine, as a supplemental tool to assist in the timely diagnosis of pediatric obstructive sleep apnea (OSA).
NPOSES is intended for use by an MD/Respiratory Specialist through the following process steps (1) recording and transferring data from a pulse oximeter to a computer in order to maintain unique records per patient of pulse oximetry data, (2) analyzing. reviewing and validating patient data and summary statistics according to customized. user-selected parameters, and (3) generating and archiving reports.
NPOSES in itself is not a diagnosis tool. It is a decision management tool which allows medical personnel to upload and view data related to a sleep study and provide output reports as feedback which may be used by an MD to form a diagnosis.
The PHD Medical NPOSES (Nocturnal Pulse Oximetry Study Expert System) application scores data in the patient history, physician comments and test results to automatically produce an analysis report as input to the identification of pediatric obstructive sleep apnea which is presented to Respiratory Specialists and Medical Doctors. The suggested diagnosis is used to assist the Medical Director in the diagnosis of the severity of obstructive sleep apnea. The application enables the efficient processing of patient sleep evaluation studies while allowing the medical staff to concentrate on critical cases.
The provided text describes a 510(k) submission for the NPOSES device, a Nocturnal Pulse Oximetry Study Expert System. However, it does not include detailed information regarding specific acceptance criteria for performance, the study design, or the results of a study to prove the device meets acceptance criteria.
The "Performance Data" section merely states: "Testing was performed to confirm that NPOSES software is capable of meeting all of its intended functional requirements. NPOSES passed all tests." This is a very high-level statement and does not provide the granular details requested.
Therefore, many of the requested fields cannot be filled from the provided text.
Here's a breakdown of what can be inferred and what is missing:
1. A table of acceptance criteria and the reported device performance
| Acceptance Criteria | Reported Device Performance |
|---|---|
| Not specified | "NPOSES passed all tests." |
2. Sample size used for the test set and the data provenance (e.g. country of origin of the data, retrospective or prospective)
- Sample size for test set: Not specified.
- Data provenance: Not specified.
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)
- Not specified. The device is intended to "automatically produce an analysis report as input to the identification of pediatric obstructive sleep apnea which is presented to Respiratory Specialists and Medical Doctors." This suggests the output is reviewed by experts, but the process of establishing ground truth for a test set is not described.
4. Adjudication method (e.g. 2+1, 3+1, none) for the test set
- Not specified.
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 is mentioned. The device is a "management tool" and a "supplemental tool to assist in the timely diagnosis," not an AI diagnostic tool that human readers would directly interact with to improve performance. The description focuses on its function in processing and organizing data.
6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done
- The device is explicitly stated as "not a diagnosis tool. It is a management tool which allows medical personal to input and view data relating to a study and give feedback which may be used by an MD to form a diagnosis." This implies it's not a standalone diagnostic algorithm, but rather a tool to generate output for a medical doctor specializing in sleep medicine. The "Performance Data" section vaguely states "NPOSES software is capable of meeting all of its intended functional requirements" and "NPOSES passed all tests," which likely refers to its functional capabilities (data processing, reporting) rather than diagnostic accuracy as a standalone algorithm.
7. The type of ground truth used (expert consensus, pathology, outcomes data, etc)
- Not specified.
8. The sample size for the training set
- Not specified. The document does not describe a machine learning model that would typically have a "training set" in the modern sense. It refers to an "Expert System" but does not detail how this system was developed or "trained."
9. How the ground truth for the training set was established
- Not applicable/Not specified, as no training set or its ground truth establishment is described.
§ 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).