(130 days)
The TeslaGuard® Patient Monitor is capable of monitoring:
- SpO2 (Arterial Oxygen Saturation)
- ECG (3-Lead)
- IBP (Invasive Blood Pressure)
- NIBP (Non-invasive Blood Pressure)
- CO2 and Anesthetic Agents (with optional multi-gas module)
This device will produce visual and audible alarms if any of these parameters vary beyond preset limits and produce timed or alarm recordings.
With the optional multi-gas module installed, sampled breathing gases from adults and pediatrics can be displayed. The multi-gas module continuously measures the content of CO2, N2O, O2 and one of the anesthetic agents, Halothane, Isoflurane, Enflurane, Sevoflurane and Desflurane in any mixture, and communicates real time and derived gas information to the TeslaGuard Patient Monitor.
The device is intended to be used in the environment where patient care is provided by Healthcare Professionals, no physicians or technicians, trained on the use of the device, who will determine when to rely on the information provided by the device based upon their professional assessment of the patient's medical condition.
The device is intended for use in the Adult, Pediatric and Neonatal populations.
The TeslaGuard design allows monitoring of intensive care patients while in an MRI-scanner. During use, the unit must be positioned in a way that the maximum field strength is not higher than 20 mT, and the distance to the magnet core is at least 1.5m.
This 510(k) has been filed to establish substantial equivalence for an optional multi-gas module. With the multi-gas module installed, sampled breathing gases from adults and pediatrics can be displayed. The multi-gas module continuously measures the content of CO2, N2O, O2 and one of the anesthetic agents, Halothane, Isoflurane, Enflurane, Sevoflurane and Desflurane in any mixture, and communicates real time and derived gas information to the TeslaGuard Patient Monitor.
The provided 510(k) summary for the MIPM TeslaGuard® multi-gas module does not contain the detailed information necessary to fully address all aspects of your request regarding acceptance criteria and a definitive study demonstrating performance against those criteria. This type of submission typically focuses on demonstrating substantial equivalence to a predicate device rather than presenting a full clinical study with specific acceptance metrics.
However, based on the provided text, here's what can be extracted and inferred:
1. A table of acceptance criteria and the reported device performance
The document does not explicitly state quantitative acceptance criteria in a table format with corresponding device performance. It generally states that "Laboratory bench testing was conducted to validate performance specifications of the multi-gas module." and "Simulated use testing was conducted to establish safety and effectiveness of the TeslaGuard multi-gas module under maximum intended MRI conditions." without providing the actual specifications or results.
2. Sample size used for the test set and the data provenance (e.g. country of origin of the data, retrospective or prospective)
The document mentions "Laboratory bench testing" and "Simulated use testing." These typically involve controlled laboratory environments and simulated patient scenarios rather than a test set of patient data. Therefore, there's no mention of a sample size in terms of patient data or data provenance (country, retrospective/prospective).
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)
Since there is no mention of a test set based on patient data requiring ground truth establishment, this information is not applicable and not provided.
4. Adjudication method (e.g. 2+1, 3+1, none) for the test set
Similarly, no information is provided regarding adjudication methods, as there's no evident test set requiring expert consensus.
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
The device is a patient monitor with an optional multi-gas module, not an AI-assisted diagnostic imaging device for human readers. Therefore, an MRMC comparative effectiveness study involving human readers and AI assistance is not relevant to this device and was not performed.
6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done
The "Laboratory bench testing" and "Simulated use testing" would be considered standalone performance assessments of the device's functionality. The device is designed to continuously measure gases and communicate information to a monitor, which is inherently a standalone algorithm/device function. Specific performance metrics (e.g., accuracy, precision) would have been assessed during these tests, but are not detailed in the summary.
7. The type of ground truth used (expert consensus, pathology, outcomes data, etc)
For laboratory and simulated use testing of a multi-gas module, the ground truth would typically be established by:
- Reference gas mixtures: Using precisely calibrated gas mixtures with known concentrations of CO2, N2O, O2, and anesthetic agents as the "true" values.
- Reference instruments: Comparing the device's measurements against a highly accurate and calibrated reference instrument (e.g., a laboratory-grade gas analyzer) that serves as the gold standard.
The summary does not explicitly state which type of ground truth was used.
8. The sample size for the training set
The device is a hardware-based patient monitor with a sensing module, not a machine learning or AI-driven system that would typically require a "training set" in the conventional sense. The development and calibration of the module would involve engineering and physical sciences principles, and extensive testing with various gas concentrations and environmental conditions, rather than a data training set.
9. How the ground truth for the training set was established
As there is no "training set" as understood in AI, this question is not applicable. The calibration and design optimization of the device would rely on established scientific principles, precise laboratory measurements, and the use of reference standards.
Conclusion:
The 510(k) summary for the TeslaGuard® multi-gas module indicates that its performance was validated through "Laboratory bench testing" and "Simulated use testing" to establish its "safety and effectiveness." However, it does not provide specific acceptance criteria, quantitative performance results, or details about the methodology (e.g., sample sizes, ground truth establishment, expert involvement) in the way a clinical study for a diagnostic AI device would. This is typical for submissions of this nature, where the focus is on demonstrating equivalence to predicate devices and meeting general performance and safety requirements through engineering and controlled testing, rather than presenting a full-scale clinical trial report.
§ 870.2300 Cardiac monitor (including cardiotachometer and rate alarm).
(a)
Identification. A cardiac monitor (including cardiotachometer and rate alarm) is a device used to measure the heart rate from an analog signal produced by an electrocardiograph, vectorcardiograph, or blood pressure monitor. This device may sound an alarm when the heart rate falls outside preset upper and lower limits.(b)
Classification. Class II (performance standards).