Mapping of Cardiac Power in Healthy Humans and Testing of a New Blood Pressure Sensor
Condition: Healthy Volunteers
Study type: Observational

Summary: 
      Brief Summary:

      The study will record hemodynamic data from 20 healthy volunteers at rest and during moderate
      bicycle exercise in the recumbent and half sitting position for the following purposes:

      Sub-study 1 Testing the overall accuracy and the dependence on changes in posture and
      exercise of a new non-invasive blood pressure sensor against simultaneous invasive
      measurements.

      Sub-study 2 Exploration of the effect of exercise and position on cardiac energy delivery to
      the circulation. The interplay between heart and vasculature (Ventriculo-arterial coupling)
      will be characterized based on simultaneous blood pressure and ultrasound blood flow
      measurements.

      Sub-study 3 Evaluation and possible improvement of an individualized mechanistic model
      predicting the hemodynamic response to exercise based on hemodynamic profile at rest.

      Sub-study 4 Testing of a machine learning based system for evaluation of dynamic
      autoregulation of renal blood flow from simultaneous continuous blood pressure and ultrasound
      blood flow measurements.
    

Detailed description: 
      Sub-study 1 A new non-invasive blood pressure sensor designed to give continuous blood
      pressure signals from ambulatory persons has been developed at NTNU (Norwegian University of
      Technology and Science). In this sub study we will test the ability of this new device to
      correctly represent the invasive blood pressure measurements and if its accuracy is affected
      by changes in posture and activity.

      The new sensor is an armband carried around the distal forearm. We will evaluate the degree
      of correspondence with invasive blood pressure measurements from the probands' other arm. The
      study's primary goal is to compare paired, beat-to-beat numeric values for systolic,
      diastolic, and mean arterial pressures during each study period, As a secondary study goal
      the accordance of the arterial curve waveforms, in these periods will also be compared.
      Overall performance and data from each separate study period will be reported. The effect of
      changes in posture and activity on the convergence between invasive and non-invasive
      measurements will be assessed by comparison of four repeated recordings in recumbent and half
      sitting positions, namely: at rest and during bicycle exercise of 50, 100 and 150 Watts.

      Sub-study 2 Changes in posture and exercise level are both known to affect cardiac output and
      blood pressure, and thus the energy transfer from the heart to the circulation. The amount of
      energy can be assessed by multiplying invasive blood pressure recordings with synchronized
      transthoracic ultrasound measurement of blood flow through the aortic valve. The study's
      primary goal is to investigate the effect of exercise and position on cardiac energy delivery
      to the circulation in normal subjects. From the synchronized measurements of blood pressure
      and blood flow two separate parameters describing energy transfer are calculated, Total
      Cardiac Power, and Cardiac Power Output, both given in Watts. The former includes the energy
      associated with oscillations in flow and pressure, the latter does not. Oscillatory power is
      calculated as the difference: Total Cardiac Power - Cardiac Power Output.

      Energy transfer from the heart to the vasculature depends not only on the heart's
      contractility but also on systemic vascular resistance and aortic elastance. Cardio-vascular
      interaction will be investigated as a secondary study goal. Two methods will be used, both
      based on the combination of cardiac ultrasound and invasive arterial pressure. The first of
      these, Single beat Ventriculo-Arterial Coupling calculates Ae/Ees (Aortic elastance/Left
      ventricular elastance) that requires cardiac catheterization, from a combination of several
      less invasive variables. Despite complicated calculation this method has become increasingly
      popular in clinical research over the last years. Newly Oscillatory Power Fraction, i.e.
      Oscillatory Power/Total Cardiac Power was proposed as an alternative. This parameter is much
      easier calculated but little data confirm its reliability as a measure of cardio-vascular
      interaction.

      Repeated synchronized ultrasound and arterial pressure measurements during the same postures
      and bicycle workloads as described in Sub study 1 will be compared to assess the effects of
      exercise level and posture on energy transfer and, cardio-vascular interaction in healthy
      persons.

      Sub-study 3 A simple mechanistic model has been established predicting individual hemodynamic
      responses to exercise based on demographic data and the hemodynamic profile at rest.

      The main idea of this sub-study is to test this model by comparing the individually predicted
      hemodynamic values for each specific combination of posture and exercise applied in
      sub-studies 1 and 2 to the actual individual hemodynamic responses recorded in the study
      subjects. The overall result will be analyzed for determination of the model's predictive
      power.

      As a second goal, a detailed analysis will be performed for detection of possible
      improvements of the model.

      Sub-study 4 Impaired Dynamic Autoregulation of Renal Blood Flow may be an early warning
      signal in intensive care patients developing Acute Kidney Injury. However, assessment of the
      kidney's autoregulation mechanisms Myogenic Response (MR) and Tubulo-Glomerular Feedback
      (TGF) depends on simultaneous continuous recordings of blood pressure and flow signals from
      renal arteries for several minutes. This is challenging as the kidneys move with respiration,
      and we consequently developed a system for machine learning assisted ultrasound recording of
      flow velocities in renal arteries. A high-end ordinary ultrasound scanner will be used for a
      four minutes recording in recumbent and resting probands. Synchronized blood pressure curves
      are recorded from the indwelling arterial cannula.

      Assessment of MR and TGF function will be performed by off-line transfer function frequency
      analyses with blood pressure as input and flow velocities as output. Different machine
      learning methods and different approaches to the transfer function analysis will be tested to
      determine their ability to detect dynamic autoregulation of renal blood flow in normal
      subjects, and which method(s) perform(s) the best.
    

Intervention name(s): Bicycle exercise
Intervention type(s): Behavioral
Intervention description(s): Stepwise increased exercise for 5 minutes at 0, 50, 100 and 150 Watts. One series lying flat in prone position, after 15 minutes of rest, series repeated at 70 degrees head up tilt.
Observational model: Cohort
Time perspective: Prospective
Sampling method: Non-Probability Sample
Study population: 
        Community sample
      
Keywords: Blood pressure monitoring; Cardiac Power; Dynamic autoregulation of renal blood flow; Personalized hemodynamic modelling