Clinical Trials Logo

Clinical Trial Summary

Respiratory rate is an important predictor for many clinical outcomes in Emergency Medicine. Nevertheless it's measurement is often omitted as it is time-consuming and cumbersome. It is the only vital sign that is not routinely assessed by a device. In a pilot study was showed that a camera based monitoring system measures reliably respiratory rates in healthy volunteers.

The goal of this study is to test the accuracy of the same system in real patients in the triage setting of an Emergency Department (ED).


Clinical Trial Description

For triage of emergency patients at the Emergency Department of the University Hospital Basel the emergency severity index (ESI) is used. At decision point "D" in the ESI-algorithm vital signs such as respiratory rate, heart rate and oxygen saturation are needed.

According to the guidelines the respiratory rate is visually counted for one minute (WHOrecommendation) by a triage nurse.

Simultaneously in addition to the visual counting, it is planned to measure the same vital sign as part of our study also through a camera-based prototype application (CBPA) and capnography as a gold standard.

Hence the triage process is not prolongated through our study, only completed and a guideline compliant procedure is ensured which is only performed in a relatively low percentage in the ED of the University Hospital Basel. Clinical decisions are exclusively based on the actual clinical standard of visual counting and are not influenced by the measurements of our study.

For the capnography, which were considered as the most accurate method, the patient wears a nasal sample line (Philips® Heartstart MRx mit Philips® Smart CapnoLineā„¢PlusO2Long Oral/Nasal Sample Line).

The CBPA system consists of a notebook (HP Zbook 15 G3, S/N: CND705IXT6), USB-camera with lens (Tamron CCTV lens, CE 4402789484; UI3060 camera, 20170329-E347840), USB-harddrive (Western digital R/N D8B, S/N: WXA1E661J0XJ) to save the signals and an implement camera-based algorithm for extraction of breathing signals. The camera is pointing towards the torso of the patient to display it on the screen in a real-time application. The software is able to detect the respiratory-specific chest movements and generates a respiratory wave on the computer. From the configuration and frequency of these respiratory waves the software calculates the respiratory rate. No videos are recorded.

The data is acquired in a standardised protocol and stored coded in an Access®-database. To prevent potential bias the vital signs will be written down in the following order: 1. RR by visual counting 2. RR by CBPA 3. RR by capnography. The measurements take place in rooms of the ED which are designated to triage emergency patients.

As possible confounders sex, age and BMI are registered. ;


Study Design


Related Conditions & MeSH terms


NCT number NCT03393585
Study type Observational
Source University Hospital, Basel, Switzerland
Contact
Status Completed
Phase
Start date December 23, 2017
Completion date April 6, 2018

See also
  Status Clinical Trial Phase
Completed NCT05552989 - Towards Better Preparedness for Future Catastrophes - Local Lessons-learned From COVID-19
Not yet recruiting NCT04915690 - Investigation on the Practice Status of Emergency Stuff
Not yet recruiting NCT03424096 - Primary Palliative Care Education, Training, and Technical Support for Emergency Medicine N/A
Completed NCT02534324 - The Effect of Pre-discharge Blood Pressure of Patients With Asymptomatic Severe Hypertension in Emergency Department N/A
Completed NCT00991471 - The Effect of an Physician-Nurse Supplementary Triage Assistance Team on Emergency Department Patient Wait Times N/A
Recruiting NCT03257319 - Inhaled vs IV Opioid Dosing for the Initial Treatment of Severe Acute Pain in the Emergency Department Phase 3
Recruiting NCT05005117 - Laparoscopic Approach for Emergency Colon Resection N/A
Recruiting NCT03917368 - Ultrasound Evaluation of the Jugular Venous Pulse (US-JVP) N/A
Completed NCT04601922 - Qualitative Study of Long Term Cardiovascular Risk Prediction in the Emergency Department
Recruiting NCT05497830 - Machine Learning for Risk Stratification in the Emergency Department (MARS-ED) N/A
Active, not recruiting NCT06220916 - The Greek Acute Dance Injuries Registry
Recruiting NCT06072534 - Evaluation of Effectiveness of Two Different Doses of Mivacurium in Rapid Sequence Intubation N/A
Recruiting NCT05496114 - Medical Checklists in the Emergency Department N/A
Recruiting NCT05543772 - Evaluation of Blood Sampling From a Pre-existed Peripheral Intravenous Catheter Line Phase 4
Not yet recruiting NCT05528211 - Safety and Efficacy of Emergent TAVI in Patients With Severe AS
Completed NCT05818215 - Impact of the Qatar 2022 FIFA World Cup on PED Use and Misuse Patterns
Recruiting NCT04615065 - Acutelines: a Large Data-/Biobank of Acute and Emergency Medicine
Active, not recruiting NCT04648449 - Artificial Intelligence (AI) Support in Medical Emergency Calls
Active, not recruiting NCT05221697 - Effect of an ML Electronic Alert Management System to Reduce the Use of ED Visits and Hospitalizations N/A
Not yet recruiting NCT04431986 - ER2 Frailty Levels and Incident Adverse Health Events in Older Community Dwellers