Search Results

The CARESCAPE Respiratory Modules (E-SCO, E-SCOV, E-SCOVX, E-sCAIO, ESCAIOV, E-SCAIOVX) are indicated for use with a host device for monitoring respiratory parameters (CO2, O2, N2O, anesthetic agents, anesthetic agent identification and respiratory rate) and ventilatory parameters (airway pressure, flow and volume) of adult, pediatric and neonatal patients and gas exchange parameters (VCO2, VO2) of adult and pediatric patients.
When monitoring neonatal or other patients that have high respiration rate or low tidal volume these modules shall be used within the limits of respiration rates and tidal volumes to ensure specified measurement accuracy.
These modules are intended for use by qualified medical personnel only.

The CARESCAPE Respiratory Modules E-sCO, E-sCOV, EsCOVX, E-sCAiO, E-sCAiOV, E-sCAiOVX and accessories measure respiratory parameters (concentrations of Carbon Dioxide. Oxygen, Nitrous Oxide and anesthetic agents in the patient's breath, as well as the patient's respiration rate), ventilatory parameters (airway pressure, flow and breathing volumes) and gas exchange parameters (oxygen consumption and carbon dioxide production) of hospital patients.
Parameters measured by the CARESCAPE Respiratory Modules are CO2. N2O. O2. Anesthetic agents, Agent ID, Spirometry, oxygen consumption (VO2) and carbon dioxide production (VCO2) depending on the model used. The CARESCAPE Respiratory Modules is a family of single-width plug-in parameter modules for modular monitoring systems. The CARESCAPE Respiratory Modules are of the diverting type, which means that a small continuous flow of gas is sampled from the patient's breath to the module for measuring the gas concentrations. The CARESCAPE Respiratory Modules acquire the detected signals from the sensors of the modules, calculate the parameter values and communicate them to the host device. The CARESCAPE Respiratory Modules measure the patient's respiration rate and activate a status signal if no breaths are detected in 20 second time and the modules activate relevant status signals upon detecting failures or anomalies in the operation of the module hardware, software or gas sampling system.
The CARESCAPE Respiratory Modules do not trigger or issue any physiological or technical alarms by themselves. All management of alarms is entirely performed by the host devices based on parameter and status data received from the modules, as well as on the alarm condition data stored in the host device.

The provided document is a 510(k) premarket notification for the GE Healthcare CARESCAPE Respiratory Modules. This document describes the device, its intended use, and its substantial equivalence to a predicate device (K150245). It does not contain information about acceptance criteria and study data for the device's performance that would typically be found in a clinical study report.

Here's a breakdown of why the requested information cannot be fully provided from this document:

1. A table of acceptance criteria and the reported device performance: This document states that "The CARESCAPE Respiratory Modules and accessories is as safe and effective as the predicate device" and that "Performance testing (Verification)" was conducted. However, it does not explicitly list quantitative acceptance criteria or the specific performance results against those criteria (e.g., accuracy, precision, bias for gas measurements). It only indicates that "an evaluation was performed to account for gas return connection and gas return filter impact on the gas measurement accuracy, sample flow measurement accuracy as well as pump and filter lifetime."

2. Sample sized used for the test set and the data provenance (e.g. country of origin of the data, retrospective or prospective): The document states that no clinical studies were required, and non-clinical tests were performed. It does not provide details on sample sizes for these tests or data provenance.

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): This information is not present as the document focuses on device modifications and compliance with standards rather than clinical validation involving expert-established ground truth.

4. Adjudication method (e.g. 2+1, 3+1, none) for the test set: Not applicable, as expert adjudication for a test set is not described.

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: This is not applicable. The device is a respiratory gas module, not an AI-assisted diagnostic tool for "human readers."

6. If a standalone (i.e. algorithm only without human-in-the loop performance) was done: The document describes a medical device, not an AI algorithm in the context of standalone performance studies for AI. Its performance is inherent to its sensors and processing of physiological parameters.

7. The type of ground truth used (expert consensus, pathology, outcomes data, etc): For non-clinical tests, ground truth would typically refer to established reference measurements or calibrated standards. The document doesn't explicitly detail the "ground truth" methods used for the non-clinical evaluations but implies standard metrological practices for testing medical devices.

8. The sample size for the training set: Not applicable, as there's no mention of a machine learning or AI training set.

9. How the ground truth for the training set was established: Not applicable for the same reason as above.

Summary based on the provided document:

The document focuses on demonstrating substantial equivalence to a predicate device (K150245) for premarket notification, particularly highlighting that recent modifications do not introduce new technology or software. The changes mainly involve the addition of a "sample gas return feature."

Here's what can be extracted regarding the study that proves the device meets the acceptance criteria (though specific criteria and results are generalized):

Study Type: Non-clinical testing and evaluation were performed. No clinical studies were required.

Purpose of the Study: To ensure that the addition of the sample gas return feature and ongoing product maintenance activities do not affect product safety and performance, and that the device remains substantially equivalent to its predicate.

Specific Evaluations Mentioned:

• Evaluation of gas return connection and gas return filter impact on:
  • Gas measurement accuracy
  • Sample flow measurement accuracy
  • Pump and filter lifetime
• System level Volatile Organic Component (VOC) and particulate matter testing for new components and materials in the dry gas path.

Table of Acceptance Criteria and Reported Device Performance (Generalized based on the document):

Data Provenance and Sample Size:

• Sample Size (Test Set): Not specified in the document. The testing was non-clinical (laboratory/bench testing).
• Data Provenance: Implied to be from GE Healthcare's internal testing facilities (Finland, given the company's address).
• Retrospective/Prospective: Non-clinical verification and validation testing would typically be prospective (designed to verify specific requirements).

Ground Truth: For non-clinical tests, ground truth would be established through calibrated reference instruments and known gas concentrations. Specific details are not provided.

Training Set: Not applicable as this is not an AI/ML device in the context of self-learning algorithms.

In essence, this document serves as a regulatory submission arguing for equivalence based on adherence to standards and internal non-clinical evaluations, rather than a detailed report of a clinical performance study with specific acceptance criteria and outcome data as one might expect for a novel device or AI algorithm.

Ask a specific question about this device