russell-icu.ppt

January 18, 2008

Computational Physiology for Critical Care Monitoring

Stuart Russell, UC BerkeleyStuart Russell, UC BerkeleyJoint work with Joint work with Geoff ManleyGeoff Manley, Mitch Cohen, Kristan Staudenmayer, Diane , Mitch Cohen, Kristan Staudenmayer, Diane Morabito (UCSF), Norm Aleks, Nimar Arora, Shaunak Chatterjee (UCB)Morabito (UCSF), Norm Aleks, Nimar Arora, Shaunak Chatterjee (UCB)

January 18, 2008

January 18, 2008

Critical care $300B/yr in US, high morbidity/mortality

Goal: improve outcomes, reduce length of stay, do science

Approach: Large-scale data repository for worldwide research use

Currently 60GB, 16 ICU beds monitored 24/7, soon multi-institutional First release any day now ….

Data mining for outcome prediction, early warning, etc. Real-time model-based estimation of patient state (And systems physiology model-building)

January 18, 2008

Critical care state estimation Given

~140 initial presentation fields ~40 real-time sensor streams ~1500 asynchronous measures (blood, drugs, etc.)

Compute posterior probability distribution for ~100 (patho)physiological state variables

Method Patient-adaptive dynamic Bayesian network (DBN): stochastic models of physiology and sensor dynamics (c.f. Guyton et al., 1972, 354-variable nonlinear ODE)

Flexible across time scales, models, sensors (images, text, etc.) Can incorporate genetic factors (observed or unobserved)

January 18, 2008

Human physiology v0.1

January 18, 2008

Medullary cardiovascular center

Cardiac parasympathetic output

Cardiac sympathetic output

Card. M2 Card. β1 Card. β2 Vasc. α1 Vasc. α2 Vasc. β2

Heart rate

Cardiac contrac-

tility

Venous tone

Arterio-lar tone

Cardiac preload

Capillary pressure

Cardiac stroke

volume

Cardiac output

Vascular resistance

Mean arterial blood

pressure

Barorecep-tor

discharge

Brain

Neurotransmitters

Heart

Blood flow

Vasculature

January 18, 2008





Heart rate

Cardiac contrac-

tility

Venous tone

Arterio-lar tone

Cardiac preload

Capillary pressure

Cardiac stroke

volume

Cardiac output

Vascular resistance

Mean arterial blood

pressure

Barorecep-tor

discharge





Heart rate

Cardiac contrac-

tility

Venous tone

Arterio-lar tone

Cardiac preload

Capillary pressure

Cardiac stroke

volume

Cardiac output

Vascular resistance

Mean arterial blood

pressure

Barorecep-tor

discharge

Brain

Neurotransmitters

Heart

Blood flow

Vasculature

January 18, 2008





Heart rate

Cardiac contrac-

tility

Venous tone

Blood [volume]

Arterio-lar tone

Cardiac preload

Capillary pressure

Cardiac stroke

volume

Cardiac output

Vascular resistance

Mean arterial blood

pressure

Barorecep-tor

discharge

Intracranial physiology

Tissues-NOS [perfusion]

GI/Liver [perfusion]

Blood [transu-dation]

Setpoint inputs from ANS, CNS,

intracranial, blood

Pulm. [intra-

thoracic press.]





Heart rate

Cardiac contrac-

tility

Venous tone

Blood [volume]

Arterio-lar tone

Cardiac preload

Capillary pressure

Cardiac stroke

volume

Cardiac output

Vascular resistance

Mean arterial blood

pressure

Barorecep-tor

discharge






intracranial, blood

Pulm. [intra-

thoracic press.]

January 18, 2008





Heart rate

Cardiac contrac-

tility

Venous tone

Blood [volume]

Arterio-lar tone

Cardiac preload

Capillary pressure

Cardiac stroke

volume

Cardiac output

Vascular resistance

Mean arterial blood

pressure

Barorecep-tor

discharge



MAP sensor model


Heart rate sensor model

Central venous

pressure sensor model



intracranial, blood

Pulm. [intra-

thoracic press.]





Heart rate

Cardiac contrac-

tility

Venous tone

Blood [volume]

Arterio-lar tone

Cardiac preload

Capillary pressure

Cardiac stroke

volume

Cardiac output

Vascular resistance

Mean arterial blood

pressure

Barorecep-tor

discharge



MAP sensor model



Central venous




intracranial, blood

Pulm. [intra-

thoracic press.]

January 18, 2008





Heart rate

Cardiac contrac-

tility

Venous tone

Blood [volume]

Arterio-lar tone

Cardiac preload

Capillary pressure

Cardiac stroke

volume

Cardiac output

Vascular resistance

Mean arterial blood

pressure

Barorecep-tor

discharge



MAP sensor model



Central venous


PK [conc. of phenyl-

ephrine]



intracranial, blood

Pulm. [intra-

thoracic press.]





Heart rate

Cardiac contrac-

tility

Venous tone

Blood [volume]

Arterio-lar tone

Cardiac preload

Capillary pressure

Cardiac stroke

volume

Cardiac output

Vascular resistance

Mean arterial blood

pressure

Barorecep-tor

discharge



MAP sensor model



Central venous


PK [conc. of phenyl-

ephrine]



intracranial, blood

Pulm. [intra-

thoracic press.]

January 18, 2008

Real data are messy

January 18, 2008

January 18, 2008

January 18, 2008

ALARM

January 18, 2008

January 18, 2008

Next Steps

Reduce ICU false alarms from >90% to <5%

Demonstrate clinically relevant inferences, e.g., Vascular stiffness Erroneous drug administration Pulmonary artery pressure (w/o catheter!)

Extend physiology model to all major systems

Multiscale: connect physiology to molecules

Health & Medicine

russell-icu.ppt