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510(k) Data Aggregation
(182 days)
The Vital Signs Monitor is designed for monitoring the vital physiological signs of the patient. It is used for non-invasive continuous monitoring of oxygen saturation (SpO2), pulse rate, CO2 and respiration rate.
The Vital Signs Monitor is adaptable to adult and pediatric usage in a hospital environment. It is intended to be used only under regular supervision of clinical personnel.
PC-900A vital signs monitor is a small Multi-parameter Patient Monitor, which can monitor the vital physiological parameters: Carbon Dioxide (CO2), Pulse Oxygen Saturation (SpO2), respiration and pulse rate. The accessories and the sensors will transfer the physical parameters into electrical signal, which will be collected and amplified by the circuit in the device. The specific sensors have been previously cleared by the FDA 510(k) process. (For specifics, please refer to the Description Section). After CPU analyzing and calculating, the parameters can display on the screen in a graphical way, record and/or print if necessary. The alarm will work if the parameters over the limits to take medical practitioner's attention.
Here's a breakdown of the acceptance criteria and study information based on the provided text for the Vital Signs Monitor, Model PC-900A:
1. Table of Acceptance Criteria and Reported Device Performance
The provided document is a 510(k) summary, which focuses on demonstrating substantial equivalence to predicate devices rather than providing specific acceptance criteria for a new clinical trial. However, it does list performance specifications and accuracy claims for the device. These can be interpreted as the functional acceptance criteria the manufacturer aims for, by comparing them to predicate devices.
| Parameter | Acceptance Criteria (Implied by equivalence and typical performance claims) | Reported Device Performance (PC-900A) |
|---|---|---|
| SpO₂ Measurement Range | Similar to predicate devices (e.g., 1%-100%) | 70%~99% |
| SpO₂ Accuracy | Similar to predicate devices (e.g., Adult/Pediatric: ±2% (70-100%), Neonate: ±3% (70-100%)) | Adult and Pediatric: $\pm$ 3% (during 70% |
| SpO₂ Alarms | High and lower alarms, adjustable limits | High and lower alarms. The limits are adjustable. |
| Pulse Rate Display Range | Similar to predicate devices (e.g., 20 bpm ~ 250 bpm) | 30 bpm~240 bpm |
| Pulse Rate Accuracy | Similar to predicate devices (e.g., ±3 bpm) | $\pm$ 2bpm or $\pm$ 2% (whichever is greater) |
| Pulse Rate Alarms | High and lower alarms, adjustable limits | High and lower alarms. The limits are adjustable. |
| CO₂ Module | Use of previously cleared modules (e.g., Respironics LoFlo™ EtCO2, CAPNOSTAT 5 EtCO2) | Respironics LoFlo™ EtCO2 (Side-stream) Module(K053174) and CAPNOSTAT 5 EtCO2 (Main-stream) Module(K042601) |
| CO₂ Measurement Method | Infrared absorption method | Infrared absorption method |
| CO₂ Measure Mode | Sidestream or Mainstream | Sidestream or Mainstream |
| CO₂ Response Time | Sidestream: <3s (includes transport and rise); Mainstream: <60ms (rise time) | Sidestream: <3seconds (includes transport time and rise time).Mainstream: <60ms (rise time) |
| CO₂ Accuracy (EtCO₂: 0-150mmHg) | 0-40 mmHg ±2mmHg, 41-70 mmHg ±5% of reading, 71-100 mmHg ±8% of reading, 101-150mmHg ±10% of reading (for Respironics LoFlo/CAPNOSTAT) | 0 |
| CO₂ Accuracy (EtCO₂: 0-99mmHg) | 0-38 mmHg: ± 2 mmHg; 39-99 mmHg: ± (5% of reading + 0.08% for every 1 mmHg above 38 mmHg) (Oridion Capnostream) OR 0-40mmHg ±2mmHg; 41-76mmHg ±8% of reading; 77-99mmHg ±10% of reading (Edan M3B) | 0 |
| Respiration Rate Measure Range | 2-150 rpm or 0-150 rpm | 2 |
| Respiration Rate Accuracy | Similar to predicate (e.g., 0-70 rpm: ±1 rpm; 71-120 rpm: ±2 rpm; 121-150 rpm: ±3 rpm for Capnostream) | ±2rpm (General Statement)0 |
| Flow Rate (Sidestream) | 50ml/min ±10 ml/min | 50ml/min ±10 ml/min (Sidestream)50 (42.5≤flow≤65) ml/min, flow measured by volume (From predicate description, likely applicable to the module) |
| Suffocation Alarm Delay | 10~60s | 10~60s |
| Alarms of EtCO₂, RR | High and lower alarms, adjustable limits | High and lower alarms. The limits are adjustable. |
2. Sample Size Used for the Test Set and Data Provenance
The 510(k) summary does not provide details on the sample size for a "test set" or data provenance (e.g., country of origin, retrospective/prospective clinical data).
The document states: "The PC 900A has undergone Third Party safety testing in accordance with IEC standards and completed performance testing in accordance with IEC standards." This typically refers to bench testing and electrical safety, not clinical performance studies with a specific test set of patients whose data is then explicitly analyzed for the stated performance metrics. The performance metrics are likely derived from the specifications of the integrated modules (e.g., SpO2 module, CO2 module) and validated through benchtop testing or limited in-vivo testing to meet the module's specified accuracy.
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 summary. As the submission focuses on substantial equivalence based on technical specifications and predicate device comparison, a formal process of establishing ground truth by a panel of clinical experts for a dedicated test set is not described. The accuracy claims for SpO2 and CO2 modules are derived from their own clearances and internal validation data, which typically involve comparisons to reference methods rather than expert consensus on subjective data.
4. Adjudication Method for the Test Set
This information is not provided. Given the lack of a detailed clinical test set and expert review, an adjudication method would not be applicable in the context described.
5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study was Done
No, a Multi-Reader Multi-Case (MRMC) comparative effectiveness study was not done or described in this 510(k) summary. This type of study is more common for diagnostic imaging AI systems where human interpretation is a key component. The Vital Signs Monitor is a device that provides numerical physiological parameters, not an interpretation of complex data by a human reader.
6. If a Standalone Study (Algorithm Only Without Human-in-the-Loop Performance) Was Done
The performance data presented are standalone performance specifications of the device and its integrated modules. For example, the SpO2 accuracy and CO2 accuracy are direct measurements of the device's ability to provide accurate physiological readings, independent of a human operator's interpretation, other than their ability to correctly apply the sensors. No "algorithm only" study is explicitly mentioned as a separate entity, but the performance claims are inherently about the device's measurement capabilities.
7. The Type of Ground Truth Used
For the SpO2 and CO2 accuracy claims, the ground truth would typically be established by a reference method (e.g., co-oximetry for SpO2, calibrated gas analyzers for CO2) during controlled laboratory or clinical studies for the respective sensors/modules. The 510(k) refers to the use of "Creative SpO2 module with the same principle as PC-60(K063641) Creative SpO2 sensor only" and "Respironics LoFlo™ EtCO2 (Side-stream) Module(K053174) and CAPNOSTAT 5 EtCO2 (Main-stream) Module(K042601)." The accuracy statements for these components are derived from their own prior regulatory clearances and the studies that supported them, which would have used appropriate gold standard reference methods. The document itself does not detail these ground truth methodologies for this specific submission, but rather references the cleared modules.
8. The Sample Size for the Training Set
This information is not applicable and not provided. The Vital Signs Monitor is a hardware device integrating sensors and processing units, not an AI software system that undergoes "training" in the machine learning sense. The underlying algorithms for parameter measurements (like SpO2 and CO2) are based on established physiological principles and signal processing, not a data-driven training set.
9. How the Ground Truth for the Training Set Was Established
This question is not applicable due to the nature of the device (hardware monitor, not a machine learning model).
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