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Computational Physiology for Critical Care Monitoring

Computational Physiology for Critical Care Monitoring. Stuart Russell, UC Berkeley Joint work with Geoff Manley , Mitch Cohen, Kristan Staudenmayer, Diane Morabito (UCSF), Norm Aleks, Nimar Arora, Shaunak Chatterjee (UCB). $300B/yr in US, high morbidity/mortality

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Computational Physiology for Critical Care Monitoring

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  1. Computational Physiology for Critical Care Monitoring Stuart Russell, UC Berkeley Joint work with Geoff Manley, Mitch Cohen, Kristan Staudenmayer, Diane Morabito (UCSF), Norm Aleks, Nimar Arora, Shaunak Chatterjee (UCB)

  2. $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) Critical care

  3. 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) Critical care state estimation

  4. Human physiology v0.1

  5. Brain Neurotransmitters Heart Vasculature Blood flow 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

  6. Brain Neurotransmitters Heart Vasculature Blood flow Medullary cardiovascular center Medullary cardiovascular center Cardiac parasympathetic output Cardiac sympathetic output Cardiac parasympathetic output Cardiac sympathetic output Card. M2 Card. β1 Card. β2 Vasc. α1 Vasc. α2 Vasc. β2 Card. M2 Card. β1 Card. β2 Vasc. α1 Vasc. α2 Vasc. β2 Heart rate Cardiac contrac-tility Venous tone Arterio-lar tone Heart rate Cardiac contrac-tility Venous tone Arterio-lar tone Cardiac preload Capillary pressure Cardiac preload Capillary pressure Cardiac stroke volume Cardiac stroke volume Cardiac output Vascular resistance Cardiac output Vascular resistance Mean arterial blood pressure Mean arterial blood pressure Barorecep-tor discharge Barorecep-tor discharge

  7. Setpoint inputs from ANS, CNS, intracranial, blood Setpoint inputs from ANS, CNS, intracranial, blood Medullary cardiovascular center Medullary cardiovascular center Cardiac parasympathetic output Cardiac sympathetic output Cardiac parasympathetic output Cardiac sympathetic output Card. M2 Card. β1 Card. β2 Vasc. α1 Vasc. α2 Vasc. β2 Card. M2 Card. β1 Card. β2 Vasc. α1 Vasc. α2 Vasc. β2 Heart rate Cardiac contrac-tility Venous tone Blood [volume] Pulm. [intra-thoracic press.] Arterio-lar tone Heart rate Cardiac contrac-tility Venous tone Blood [volume] Pulm. [intra-thoracic press.] Arterio-lar tone Cardiac preload Capillary pressure Cardiac preload Capillary pressure Cardiac stroke volume Cardiac stroke volume Blood [transu-dation] Blood [transu-dation] Cardiac output Vascular resistance Cardiac output Vascular resistance Mean arterial blood pressure Mean arterial blood pressure Intracranial physiology Tissues-NOS [perfusion] GI/Liver [perfusion] Barorecep-tor discharge Intracranial physiology Tissues-NOS [perfusion] GI/Liver [perfusion] Barorecep-tor discharge

  8. Setpoint inputs from ANS, CNS, intracranial, blood Setpoint inputs from ANS, CNS, intracranial, blood Medullary cardiovascular center Medullary cardiovascular center Cardiac parasympathetic output Cardiac sympathetic output Cardiac parasympathetic output Cardiac sympathetic output Card. M2 Card. β1 Card. β2 Vasc. α1 Vasc. α2 Vasc. β2 Card. M2 Card. β1 Card. β2 Vasc. α1 Vasc. α2 Vasc. β2 Heart rate Cardiac contrac-tility Venous tone Blood [volume] Pulm. [intra-thoracic press.] Arterio-lar tone Heart rate Cardiac contrac-tility Venous tone Blood [volume] Pulm. [intra-thoracic press.] Arterio-lar tone Cardiac preload Capillary pressure Cardiac preload Capillary pressure Heart rate sensor model Heart rate sensor model Cardiac stroke volume Cardiac stroke volume Central venous pressure sensor model Central venous pressure sensor model Blood [transu-dation] Blood [transu-dation] Cardiac output Vascular resistance Cardiac output Vascular resistance Mean arterial blood pressure Mean arterial blood pressure MAP sensor model MAP sensor model Intracranial physiology Tissues-NOS [perfusion] GI/Liver [perfusion] Barorecep-tor discharge Intracranial physiology Tissues-NOS [perfusion] GI/Liver [perfusion] Barorecep-tor discharge

  9. Setpoint inputs from ANS, CNS, intracranial, blood Setpoint inputs from ANS, CNS, intracranial, blood Medullary cardiovascular center Medullary cardiovascular center PK [conc. of phenyl-ephrine] PK [conc. of phenyl-ephrine] Cardiac parasympathetic output Cardiac sympathetic output Cardiac parasympathetic output Cardiac sympathetic output Card. M2 Card. β1 Card. β2 Vasc. α1 Vasc. α2 Vasc. β2 Card. M2 Card. β1 Card. β2 Vasc. α1 Vasc. α2 Vasc. β2 Heart rate Cardiac contrac-tility Venous tone Blood [volume] Pulm. [intra-thoracic press.] Arterio-lar tone Heart rate Cardiac contrac-tility Venous tone Blood [volume] Pulm. [intra-thoracic press.] Arterio-lar tone Cardiac preload Capillary pressure Cardiac preload Capillary pressure Heart rate sensor model Heart rate sensor model Cardiac stroke volume Cardiac stroke volume Central venous pressure sensor model Central venous pressure sensor model Blood [transu-dation] Blood [transu-dation] Cardiac output Vascular resistance Cardiac output Vascular resistance Mean arterial blood pressure Mean arterial blood pressure MAP sensor model MAP sensor model Intracranial physiology Tissues-NOS [perfusion] GI/Liver [perfusion] Barorecep-tor discharge Intracranial physiology Tissues-NOS [perfusion] GI/Liver [perfusion] Barorecep-tor discharge

  10. Real data are messy

  11. ALARM

  12. 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

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