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Development of Algorithms to Predict Hemodynamic Instability

This study has been completed.
Information provided by (Responsible Party):
Klinik für Kardiologie, Pneumologie und Angiologie, Heinrich-Heine University, Duesseldorf Identifier:
First received: December 16, 2010
Last updated: February 18, 2016
Last verified: February 2016

December 16, 2010
February 18, 2016
September 2010
April 2015   (Final data collection date for primary outcome measure)
Autonomic Dysfunction [ Time Frame: 24 hours ]
Dysfunction of the autonomic nervous system as assessed by autonomic reflex testing
Same as current
Complete list of historical versions of study NCT01262508 on Archive Site
Hemodynamic Deterioration [ Time Frame: 24 hours ]
Acute hemodynamic changes (Blood pressure changes > 10 mm Hg, heart rate changes > 5 bpm both within 30 seconds) of a patient as assessed by hemodynamic monitoring
Same as current
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Development of Algorithms to Predict Hemodynamic Instability
Development of Algorithms to Detect and Predict Hemodynamic Instability in Patients at Risk
Hemodynamic monitoring in hospitalized patients is crucial since in clinical practice unexpected deterioration of cardiovascular function remains a serious problem and an important cause of death. Novel perspectives in reflex testing of the autonomic nervous system might be useful to protect some patients from cardiovascular events by detecting cardiovascular deteriorations. In addition, standard pulse oximetry in low acuity settings is nowadays predominately used to monitor peripheral oxygen saturation. Of note, there is evidence that additional analyses of pulse wave characteristics might be a valuable source of information to generate additional insights into the cardiorespiratory status of the patient. Herein, we aim to develop novel algorithms in order to protect in-hospital patients from cardiovascular events in consequence of hemodynamic instability in the future.

70 datasets from hospitalized patients will be acquired in order to characterize the functional status of the autonomic nervous system as well as hemodynamics during baseline and during standard procedures including physical exercise testing and head-up tilt table testing.

Autonomic reflex testing:

  • Heart Rate Characteristics
  • Heart Rate Variability
  • Heart Rate Turbulence
  • Blood Pressure Variability
  • Baroreflex Sensitivity
  • Hyperoxic Chemoreflex Sensitivity

Hemodynamic Monitoring:

  • Heart Rate Trends
  • Blood Pressure Trends
  • Pulse Wave Characteristics
  • Cardiac Output
  • Peripheral Vascular Resistance
  • Context information
Observational Model: Case-Only
Time Perspective: Prospective
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Probability Sample
Patients being at risk of sudden cardiac death
Sudden Cardiac Death
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Risk Population
Patients being suspected to be at risk of hemodynamic instability due to medical history

*   Includes publications given by the data provider as well as publications identified by Identifier (NCT Number) in Medline.
April 2015
April 2015   (Final data collection date for primary outcome measure)

Inclusion Criteria:

  • hospitalization
  • Age > 17 years

Exclusion Criteria:

  • documented diseases of the central nervous system
  • impairment of mental health
  • age > 85 years
Sexes Eligible for Study: All
18 Years to 85 Years   (Adult, Senior)
Contact information is only displayed when the study is recruiting subjects
Autonomics - Prediction
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Klinik für Kardiologie, Pneumologie und Angiologie, Heinrich-Heine University, Duesseldorf
Klinik für Kardiologie, Pneumologie und Angiologie
Not Provided
Study Chair: Christian Meyer, MD University of Duesseldorf
Study Director: Malte Kelm, MD, PhD University of Duesseldorf
Heinrich-Heine University, Duesseldorf
February 2016

ICMJE     Data element required by the International Committee of Medical Journal Editors and the World Health Organization ICTRP