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The SpassageQ is intended to be used with patient data from already cleared patient monitoring devices which measure respiratory rate, systolic blood pressure, and Glasgow Coma Scale (GCS) in patients being monitored in a healthcare facility. The device provides qSOFA score (also known as quickSOFA) which indicates patients with suspected infection who are at greater risk for a poor outcome. It uses three criteria, assigning one point for low blood pressure (SBP_100 mmHg), high respiratory rate (≥22 breaths per min), or altered mentation (Glasgow coma scale

The SpassageQ consists of:

• An automated algorithm to calculate data and generate qSOFA score and alarm when it is needed.
• · An HL7 message receiver to handle incoming connection attempts from HL7 gateway systems, parse HL7 messages, and check the validity of HL7 messages.
• · A qSOFA score module to calculate patients' qSOFA scores and offer their last 72 hours history data.
• · A web-based dashboard to render patients' qSOFA scores in a visually distinctive way depending on their value and enable intended users to be notified of patients with suspected infection.

The SpassageQ system works in the following sequence:

• · Receive patient data from the HL7 gateway system.
• · Extract 6 vital signs from the patient data and store them in the database.
• The Glasgow Coma Scale (GCS) of a patient is stored in the database when a user submits it.
• · SpassageQ calculates the qSOFA score automatically and stores the result in the database.
• · SpassageQ delivers 6 vital signs, qSOFA score, GCS to users.
• · When the patient's qSOFA score is 2 points or higher, the users are notified of the patient through a visual alarm, and the alarm shall be reviewed by the qualified practitioner.

This FDA 510(k) summary for the SpassageQ device does not explicitly describe acceptance criteria or a dedicated study for proving the device meets performance claims through clinical evaluation.

The document states that "Clinical testing was not needed in this 510(k) to support the substantial equivalence of the subject device to the predicate device." Therefore, information regarding acceptance criteria, reported performance, sample sizes, ground truth establishment, or multi-reader studies for device performance evaluation is absent from this submission.

The "Performance Data" section primarily focuses on non-clinical performance and adherence to various ISO and IEC standards related to risk management, software lifecycle, usability, and alarm systems. These are essential for software development and safety but do not assess the accuracy or effectiveness of the qSOFA score calculation itself directly against a clinical outcome.

Based on the provided text, here's what can be extracted and what cannot:

1. A table of acceptance criteria and the reported device performance

• Cannot be provided. The document does not define specific acceptance criteria for the qSOFA score calculation's accuracy or outcome prediction. It also does not report specific performance metrics for the device's ability to identify patients at greater risk for a poor outcome, as no clinical performance study was submitted.

2. Sample sized used for the test set and the data provenance (e.g. country of origin of the data, retrospective or prospective)

• Cannot be provided. No clinical test set description is available. The device receives patient data from "already cleared patient monitoring devices."

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)

• Cannot be provided. No clinical test set with expert-established ground truth was presented.

4. Adjudication method (e.g. 2+1, 3+1, none) for the test set

• Cannot be provided. No clinical test set with ground truth adjudication was presented.

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

• Cannot be provided. No MRMC study was conducted or reported.

6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done

• Partially answerable, but not with performance metrics. The SpassageQ is a standalone software device that calculates the qSOFA score automatically. However, there's no reported standalone performance study assessing its accuracy against a clinical ground truth. The device effectively performs its function (calculating qSOFA) as a standalone algorithm based on input vital signs.

7. The type of ground truth used (expert consensus, pathology, outcomes data, etc)

• Cannot be provided for device performance. No ground truth for evaluating the qSOFA score's predictive ability was used in a performance study for this 510(k). The qSOFA score itself is a standardized calculation based on specific vital sign thresholds, and the "ground truth" for its calculation is simply correct arithmetic. The clinical relevance of the qSOFA score is established in medical literature, not via a specific clinical study for this device's submission.

8. The sample size for the training set

• Cannot be provided. The SpassageQ calculates a rule-based score (qSOFA) and does not appear to use a machine learning model that requires a "training set" in the traditional sense. Its function is based on predefined criteria (SBP ≤ 100 mmHg, RR ≥ 22 bpm, GCS

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