Improving Safety and Efficacy of Endoscopic Procedures – A Deep Machine Learning based Depth of Sedation Monitor
- Conditions
- GI and bronchial endoscopy
- Registration Number
- DRKS00016605
- Lead Sponsor
- niversitätsklinikum Halle (Saale)
- Brief Summary
Not available
- Detailed Description
Not available
Recruitment & Eligibility
- Status
- Complete
- Sex
- All
- Target Recruitment
- 171
Inclusion Criteria
1) Adult males or females capable of giving consent.
2) Planned procedure is of elective nature and in endoscopy Department.
3) Anticipated Duration of procedure is > 20 minutes.
4) Sedation Regimen is NAPS.
Exclusion Criteria
1) Impaired Hearing.
2) Cognitive (GCS =14 Points) or acute psychiatric alteration.
3) Patients with structural brain disease, cerebral metastasis or known cerebral epilepsy. Also, mental alteration due to newly prescribed medication.
4) Sedation with substances different than outlined in protocol.
5) Allergy or intolerance to Propofol and it's components.
Study & Design
- Study Type
- observational
- Study Design
- Not specified
- Primary Outcome Measures
Name Time Method There is a shared primary endpoint:<br>A primary endpoint is the prognostic accuracy of the statistical model to separate consciousness from unconsciousness, whereby<br>- vital signs and processed EEG-parameters may be included in the model,<br>- the concrete set of input variables will be based on preliminary analysis of study data,<br>- the prognostic accuracy of the model is defined by its test characteristics (Sn, Sp, PPV, NPV) and its AUC of the Reciever-Operating-Curve,<br>- the model will be validated on a sufficiently large cohort.<br>A primary endpoint is the prognostic accuracy in differentiating different levels of sedation according to the MOAA/S-Scale, whereby the points mentioned above also apply.
- Secondary Outcome Measures
Name Time Method Secondary endpoints are the prognostic accuracies of single processed EEG-Parameters in regard to state of consciousness and clinical sedation depth as outlined in the primary endpoint. These include <br>• EEG-parameters of the frequency domain (e.g. TP, MF, SEF90, SEF95, PPF, WSMF and power in a-, ß-, d-, ?- and ?-frequency bands),<br>• EEG-parameters of the time-frequency domain (e.g. bispectrum, bicoherence, phase synchronization) and<br>• measures of complexity as well as non-linear parameters (e.g. ApEn, PeEn, Order Recurrence Rate and Order Phase Coupling).