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Clinical Trials/NCT02399930
NCT02399930
Completed
Not Applicable

Automated Respiration Rate Evaluation to Improve Accuracy of the Early Warning Score Procedure Determined by the Electronic Cardiac Arrest Risk Triage Score (eCART) Algorithm

University of Chicago1 site in 1 country133 target enrollmentApril 2015
ConditionsHeart Arrest

Overview

Phase
Not Applicable
Intervention
Not specified
Conditions
Heart Arrest
Sponsor
University of Chicago
Enrollment
133
Locations
1
Primary Endpoint
Time of Detection
Status
Completed
Last Updated
9 years ago

Overview

Brief Summary

Currently, breathing rate and heart rate are checked by nursing staff manually every few hours and entered into a patient's medical record. The investigators are doing this study to see if a device that will automatically record breathing rate and heart rate every 15 minutes is as accurate as the manual measurement. The investigators will also see if these measurements, taken every 15 minutes, will help us predict adverse events more quickly and accurately than the measurements taken every few hours.

Detailed Description

Both cardiac arrest and sepsis are primarily identified by vital sign abnormalities. However, the practice of nurses and their designees routinely checking hospitalized patients' vital signs every four to eight hours throughout the day and night has remained essentially unchanged for over one hundred years. While respiratory rate has been shown to be the most predictive vital sign for adverse events on the wards, it is often inaccurately measured and poorly documented. For example, a disproportionate amount of respiratory rates are recorded as either 18 or 20 breaths/min, which is often higher than actual rates. We have previously statistically derived a physiology-based early warning score, called the electronic cardiac arrest risk triage score (eCART), using vital signs and lab values. The eCART was more accurate than scores commonly used in hospitals today. However, the vital sign values utilized for our score were manually collected by nursing staff every four hours. Recent technological advances have allowed for high-frequency measurement of pulse and respiratory rate using a cableless respiration monitor. These devices allow for more frequent and potentially more accurate measures of respiration, which may enhance the prediction ability for detecting adverse events on the wards. In addition, the increase in monitoring frequency may result in earlier detection of adverse events, which could translate into further improvements in patient outcomes. A subset of patients may be continuously measured using a telemetry system. The alarms and ECGs from these patients are monitored by staff in a centralized station in the hospital. When a clinical event requiring action is observed, a call is made to the unit alerting the clinical staff that action is necessary. We will collect the continuous measurements collected from this system and compare these continuous measurements to the high frequency and manual measurements.

Registry
clinicaltrials.gov
Start Date
April 2015
End Date
May 2016
Last Updated
9 years ago
Study Type
Observational
Sex
All

Investigators

Responsible Party
Sponsor

Eligibility Criteria

Inclusion Criteria

  • over 18 years
  • able to provide written consent

Exclusion Criteria

  • Not provided

Outcomes

Primary Outcomes

Time of Detection

Time Frame: 6 months

To determine whether high-frequency (Q15 min) monitoring of pulse and respiratory rates provides earlier detection of patient deterioration than standard validated (Q4hr) vitals or continuous respiratory monitoring (Qcont).

Physiological Validity

Time Frame: 6 months

To determine whether high-frequency (Q15min) monitoring provides respiratory rates with greater physiological validity than standard manual (Q4hr) vitals.

Accuracy

Time Frame: 6 months

To determine whether high-frequency (Q15min) monitoring provides data with greater accuracy for predicting risk of adverse events than intermittent (Q4hr) validated vitals.

Secondary Outcomes

  • Physiological Validity(6 months)
  • Detection Performance(6 months)

Study Sites (1)

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