NZ569268A - Blood gas prediction system and method - Google Patents

Abstract

A computer implemented model of the human cardiopulmonary system includes interfacing software arranged for inputs to the d model of performance parameters of equipment associated with cardio-pulmonary procedures. The model is adapted for prediction and monitoring in real-time of effects associated with the procedures. The model includes use of an unabbreviated alveolar air equation including terms for carbon dioxide and water vapour. The model includes a polynomial equation describing the relationship between right-to-left shunt across an artificial lung and gas flow through the lung. The model includes a polynomial equation describing the relationship between dead space of an artificial lung and the gas flow through the lung

Description

—■ t ' 19. Jun. 2008 1 4:50 WALLINGTON-DHMMFB Jo. 4925 P. 4 Please return form bv mail to: *10055949370* Intellectual Properly Office of New Zealand Development; PO Box 9241, Marion Square Wellington 6141 New Zealand JKaitflH etfcsrtjd iHldkuuid Property Giiw't cfNfv; /futawi (bkaftga 8 IP number/s: _____ Current Owner: Your reference: 082026 Patents Act 1953 -Office use only- INTELLECTUAL PROPIERTY OFFICE OF N.Z- 1 9 JUN 2008 RECEIVED Patent Form No. 5 - Complete Specification n no Date: (a;. Blopd_Gas Prediction System and Method I {or We), (b),P®xM AndrewPYBUS hereby declare the invention, for which I (or we) pray that a patent may be granted to me (or us), and the method by which it is to be performed, to be particularly described in and by the following statement (c) continue application on page 2 Signature Total Fee Paid NZ$ 250.00 Credit Card - Please complete credit card authorisation Date I ^ vi ww S*~- Direct Debit - Customer ID number required 02 92211040 (Australia) Customer ID No: Telephone _ Cheque - Made out to the Ministry of Emgj| mail@wallington-dummer.com Economic Development Your receipt will be automatically emailed to you. Please tick this box if you wish to receive a receipt by mall I I Continued over.

For assistance completing this form please call 0508 4IPONZ (0S08 447 669) 19. Jun, 2008 14:51 WALLINGTON-DUMMER No. 4925 P. 5 BLOOD GAS PREDICTION SYSTEM AND MODEL This invention relates to improvements in the 5 prediction and monitoring of characteristics of the blood gas composition of blood passing through heart lung machines (HLMs), produce training devices for simulators of one-lung anaesthesia and insertion of chest drains.

BACKGROUND The correct functioning of an ELM and its correct operation is clearly critical to the clinical outcome of procedures involving such equipment. Consequently the rneed for improvements in the design and construction of bypass 15 equipment as well as the monitoring and predictability of its performance has seen the development of software designed to model mathematically the various parameters involved.

In at least some instances such modelling is based on a 20 relationship, the assumption that carbon dioxide is not present in the alveolar gas. This assumption i3 deemed incorrect by at least some authorities.

In addition for the need for more accurate modelling, there has been a lack of interactive models which can predict and 25 display the performance of the bypass process in real time.

INTELLECTUAL PROPERTY OFFICE OF N.Z. 1 9 JUN 2008 RECEIVED 6 8 Received at IPONZ on 7 October 2009 Another disadvantage of most modelling currently known, is that its ability to predict the consequences of changing bypass equipment operating parameters, is not sufficiently accurate or reliable to allow its use for monitoring actual bypass equipment 5 or as a basis for clinical procedures.

It is an object of the present invention to address or at least ameliorate some of the above disadvantages.

Notes 1. The term "comprising" {and grammatical variations thereof) is used in this specification in the inclusive sense of "having" or "including", and not in the exclusive sense of "consisting only of". 2. The above discussion of the prior art in the Background of 15 the invention, is not an admission that any information discussed therein is citable prior art or part of the common general knowledge of persons skilled in the art in any country.

BRIEF DESCRIPTION OF INVENTION Accordingly, in a first broad form of the invention, there is provided a computer implemented model of the human cardiopulmonary system; said model including interfacing software 25 arranged for inputs to said model of performance parameters of Received at IPONZ on 7 October 2009 equipment associated with cardio-pulmonary procedures; said model adapted for prediction and monitoring in real-time of effects associated with said procedures.

Preferably, said model includes use of an unabbreviated alveolar 5 air equation; said equation including terms for carbon dioxide and water vapour.

Preferably, said model includes a polynomial equation describing the relationship between right-to-left shunt across an artificial lung and gas flow through said lung.

Preferably, said model includes a polynomial equation describing the relationship between deadspace of an artificial lung and the gas flow through said lung.

Preferably, said prediction and monitoring is continually updated by said model within every 100ms of acquisition of said inputs.

Preferably, said model accepts inputs from an hydraulic device; said device simulating behaviour of a human circulatory system; said device when connected to a Heart Lung Machine (HLM) providing inputs to said model to generate a real-time display of virtual arterial and venous blood gases within a cardio-pulmonary 20 bypass circuit.

Received at IPONZ on 7 October 2009 Preferably, said model accepts inputs from an hydraulic device; said device simulating behaviour of a patient sustained by an Extra-corporeal Membrane Oxygenator (ECMO) system; said model generating a real-time display of virtual blood gases within said ECMO system and said patient.

Preferably, said model accepts inputs from an hydraulic device; said device simulating behaviour of a patient sustained by a Left Ventricular Assist Device (LVAD); said model generating a realtime display of virtual blood gases within said LVAD and said patient.

Preferably, said model accepts inputs from a pneumatic device; said device simulating behaviour of a patient undergoing ventilation using a double lumen tube; said model generating a real-time display of virtual arterial and venous blood gases during said ventilation.

Preferably, said model accepts inputs from a pneumatic device; said device simulating behaviour of a patient undergoing a procedure including insertion of a pleural catheter; said model generating a real-time display of virtual arterial and venous blood gases during said procedure.

Preferably, inputs to said model include inputs from an inline blood gas measuring electrode; said model calculating a Received at IPONZ on 7 October 2009 comparison between blood gas measurements derived from said electrode and predicted blood gas measurements generated by said model.

Preferably, said model further includes alarm systems; said alarm systems based on comparisons between input data received by said model and data generated by said model; alarm signals being generated by said alarm system when divergence between said input data and responses to said data predicted by said model indicate unacceptable physiological outcomes.

Preferably, comparison of blood gas measurements and said predicted blood gas measurements provide basis for an alarm system; said alarm system triggered when differences between said measured and predicted blood gas measurements exceed predetermined limits.

Preferably, said model is provided with a fast forward facility; said fast forward facility adapted for prediction of physiological outcomes based on current inputs received from cardio-pulmonary associated devices to said model during a clinical procedure.

Preferably, said model is adapted to predict physiological outcomes of selected clinical procedures based on current inputs received from cardio-pulmonary associated devices to said model.

Received at IPONZ on 7 October 2009 In another broad form of the invention, there is provided a system for the prediction and monitoring of the status of the blood gas composition in a cardio-pulmonary bypass equipment; said system comprising a blood gas electrode in communication with a blood stream and a software model; said software model adapted to integrate parameter inputs from said equipment, In a further broad form of the invention, there is provided a system for the comparison in real time between the status of the blood gas composition of blood passing through a heart lung machine, and a software model prediction of said blood gas composition; said software model calculating variables of said blood gas composition from parameters; said parameters including settings of said equipment and patient physiological parameters.

In yet a further broad form of the invention, there is provided a system for virtual arterial and venous blood gas analysis in cardiopulmonary bypass simulation equipment; said simulation equipment including an hydraulically realised analogue of the human cardiopulmonary system; said system including software integrating parameter inputs from variables applied to said bypass simulation equipment.

In yet another broad form of the invention there is provided a system for training operators of heart lung machines; said system including an hydraulically realised analogue of the human Received at IPONZ on 7 October 2009 cardiopulmonary system connected to said heart lung machines; said system including software for integrating parameter inputs from variables applied to said heart lung machines.

Preferably, said hydraulically realised analogue of the human 5 cardiopulmonary system includes ■ an oxygenator simulating the human lungs and a pump simulating the human heart.

Preferably, said parameter inputs include pump flow rate.

Preferably, said parameter inputs include sweep gas rate.

Preferably, said parameter inputs include fraction of inspired 10 oxygen (Fi02).

Preferably, said parameter inputs include temperature.

Preferably, said temperature includes measured arterial temperature.

Preferably, said temperature includes measured venous 15 temperature.

Preferably, said temperature includes measured nasopharyngeal temperature.

Preferably, said parameter inputs include haematocrit.

Preferably, said parameter inputs include metabolic rate (V02).

Received at IPONZ on 7 October 2009 Preferably, said integrating of parameter inputs occurs in real time.

Preferably, said integrating of parameters is refreshed at predetermined intervals.

Preferably, a said predetermined interval is equal to or less than 100ms.

In yet another broad form of the invention there is provided an expert surveillance system; said system constantly assessing adequacy of a current perfusion state with particular reference 10 to gas flow management, blood flow and pressure management, temperature and oxygenation; said system advising a perfusionist of any impending problem.

Preferably, said advice is delivered to a computer terminal or to a ^head up' display system.

Preferably, predictions derived from a blood gas modelling system, (or measurements made by an in-line blood gas electrode such as the Terumo CDI-500 blood gas electrode) can then be combined with real-time data derivpd from an HLM and ancillary equipment as input parameters of said expert surveillance system. 19. Jun. 2008 14:54 WALL INGTON-DOMMER No, 4925 P. 13 BRIEF DESCRIPTION OF DRAWINGS Embodiments of the present invention will now be described with reference to the accompanying drawings wherein: Figure 1 is a schematic diagram of an BLM to a patient and a computer implemented blood gas prediction system according to the invention/ Figure 2 is a schematic diagram of an HLM connected to an analogue of a human cardio-pulmonary system, 10 Figure 3 is a typical display monitoring parameters of an HLM, Figure 4 is a similar display generated by the blood gas prediction system of the present invention showing input sources, Figure 5 is a representation of the "Riley" lung model, Figure 6A is a parallel version of the model of the invention depicting a patient on cardio-pulmonary bypass in symbolic form, Figure 6B is a series version of the model of the invention depicting a patient on veno-venous Extracorporeal Membrane Oxygenation (ECMO), Figure 6C is a parallel version of the model depicting the three lobes of the right lung and two lobes of the left 25 lung, uii. 2008 14:54 WALLIM<sTON-DUMME'R Ho. 4925 P. 14 - ll - Figure 7 is a display generated by the prediction system and model of an actual and predicted equipment performance showing the effect of reducing FjOa on P&02, as well as the time delay between the response predicted by 5 the model and the actual equipment response, Figure 8 is a display of the actual and predicted responses of Figure 1 with the time delay removed to show the close correspondence between predicted and actual responses, Figure 9 is a displayed output from the prediction system and model of the invention indicating nadir SVO2 following restoration of circulation after arrests of 3 and 6 minutes respectively, Figure 10 is another example of an actual and model 15 predicted response of the effect of transient sweep gas failure on partial oxygen pressure (Pa02), Figure 11 is a further example o£ displayed output showing a comparison between model predicted transient sweep gas failure effect on Pa02 and persistent gas supply 20 failure, Figure 12 is a displayed output ■ .of actual and predicted responses on PaC>2 of a reduction in main arterial pump flow, Figure 13 shows the model predicted effects of the 25 reduction in main arterial pump flow on predicted PaQ2, 19..Jun. 2008 14:55 WA1LINQTON-OUMMER No. 4925 P. 15 ( e Figure 14 shows the start up screen of the software-based ECMO simulator as realised in the system of the invention.

DERAILED DESCRIPTION OF PREFERRED EMBODIMENTS Figure 1 shows a typical schematic arrangement of a patient connected to an heart lung machine (HLM) for a medical procedure. In essence, the HLM takes over the 10 functions of the heart and lungs of a patient during the procedure, principally providing for the circulation and continual oxygenation of the blood and removal of carfoondioxide, For the effective performance of such equipment close monitoring o£ the various operating 35 parameters which control these processes is essential.

Also essential is the thorough training of anaesthetists and perfusionists who operate such equipment. To that end, as shown schematically in Figure 2, simulators have been devised which provide an analogue of the heart 20 and lungs, and which may be connected to an HLM and to suitably programmed computer equipment.

The model of the present invention comprises a library or suite of procedures and functions which replicate the behaviour of the respiratory gasses (oxygen Oj and carbon 25 dioxide CO2) as well as the metabolic acids under varying conditions of the systemic blood flow and lung ventilation. wi. 2008 14: 55 WALL INGTON-DUMMER No. 4925 P. 16 The model comprises a "single" ventricular cixcuit which allows for the inclusion, of any number of lungs (artificial and natural) either in parallel or series with each other (as shown in the representations of Figures 6A to 6C). Each 5 of the representative lungs can be set to behave either as ""open" or "closed" glottis systems during apnoea. The model and the formulae employed are loosely based on the worfc of C.J. Dickinson and described in his book A computer Model of Human Respiration1.

The processes of oxygenation and perfusion are controlled by a number of variables interacting through equations which model the dynamics of the heart and lung systems in the human body. A large selection of input variables is available in the model. These parameters 15 include,, but are not limited to, the volumes and temperatures of all compartments (including the blood and gas phases) and the partial pressures, concentrations and amounts of oxygen, carbon dioxide within each compartment.

The primary function of the algorithms within the 20 model is to replicate the behaviour of the respiratory gases in the patient as input parameters vary during a simulation session. If interfaced to a hardware simulation system (such as the Ulco Technologies "Orpheus" simulator)r most of the input data are acquired automatically from the 25 electronic control unit of the device. Similarly, if 1 Dickinson C J. (1977) "A Computer Model of Hinnan Respiration'1 MTP tress Ltd. ISBN 0 85200173 & n. 2003 14:55 WALLIN6T0N-DUMMER No, 4925 P. 17 interfaced with an HIM, the input data can be acquired automatically from the HLM itself or from its associated ancillary devices, as shown in Figure 4.

Critical to the performance of the HLM are some seven 5 parameters as shown in Figure 4. These are: • Fraction of inspired oxygen (P1O2) • The metabolic rate (VOa> • Temperature • Pump flow 10 • Gas flow • Oxygenator • Haematocrit In addition to its ability to be interfaced with a HLM or with a hardware analogue of a human respiratory system, 15 the library can be integrated with teaching and simulation packages which have been implemented entirely in software. Examples of such packages would include "ECMO", "left Ventricular Assist" and "One lung Anaesthesia" training packages.

Some aspects of the model include the use of the "Riley" technique2 represented diagrammatically in Figure 5/ for the .modelling of the behaviour of an artificial lung. It is noted that all previously published accounts of gas exchange in artificial lungs,, unlike the . model of the un. 2008 14:56 WALLINGTON-DUMMER No. 4925 P, 18 present invention, use an abbreviated form of the alveolar air equation which does not take into account the presence of carbon dioxide and water vapour.

Another differentiating feature of the modal of the 5 present invention is its ability to model the lungs as either Mopen" or "closed glottis systems. The "open" glottis calculations employed in the model permit the performance of an artificial lung to be accurately modelled in case of gas supply failure. The *closed" glottis variant 10 permits accurate simulation o£ lobar collapse when one-lung anaesthesia is modelled.

Another feature of the model is the ability to model the effect of multiple lung units, each functioning independently either in series or parallel with each other 15 or in any combination thereof as illustrated schematically in Figures 6A to 6C, All previously published accounts of gas exchange in artificial lungs use a constant value for oxygen solubility. This does not permit the quantification of 20 '"super saturation" of plasma under conditions of temperature change. By contrast the present model incorporates a temperature dependent value for the solubility of oxygen in plasma. 2 Riley, ILL. and Coumsnd, A (1949) "Ideal" Alveolar Air and the Analysis ofVewfilation-Perfuglon Relationships m Lungs Journal of Applied Physiology, 1, 825-847 un.. 2008 14:56 WALLINGTON-DUMMER No. 4925 P. 19 The model is capable of the acquisition of data in real-time from an HLM and ancillary equipment. This data may then be used to predict and display the constituency of the arterial and venous gases continuously within 100ms of 5 data acquisition. A "fast forward" feature in the model allows a user to examine the effects of therapeutic intervention or other possible events using an accelerated time base.

The model uses a number of polynomial equations to 10 describe various relationships. These include the relationship between right-to-left shunt across an artificial lung (Qs/Qt), the relationship between ttdead space" of the artificial lung (Vd/Vt) and the gas flow through the lung.

IS In Use Functionally, the invention includes a software 20 interface between the model and a range of equipment associated with cardio-respiratory procedures, simulation and training.

Thus, as illustrated in Figure 2, the model which is resident on a computer system 10 can interact with an 25 hydraulic device 12 which simulates the behaviour of the human circulation. The device 12 can be physically un. 2008 14:57 'WALLINGTON-DUMMER Nu. 4925 P. 20 connected to a cardiopulmonary bypass circuit and an HLM 14. The model's input parameters can be acquired from the device and used to generate real-time displays of the ■"virtual" arterial and. venous blood gases within the 5 cardiopulmonary bypass circuit. Examples of a display is shown in Figure 3, Similarly, the software interface can allow the model to interact with a hydraulic device which simulates the behaviour of a human being sustained by an Extra-Corporeal 10 Membrane Oxygenator (ECMO) system. The model's input parameters can again be acquired front the device and used to generate a real-time display of the "virtual'" blood gases within the ECMO system and the patient.

The software can further allow the modal to interact 15 with an hydraulic device which simulates the behaviour of a human being sustained by a Left Ventricular Assist Device (LVAD) system. In this arrangement also the model's input parameters are derived from the device and used to generate a real-time display of the "virtual" blood gases within the 20 LVAD system and in the patient.

In another arrangement the software provides an interface allowing the model to interact with a pneuiaatic device which simulates the behaviour of a human undergoing ventilation using a double lumen tube. The model's input 25 parameters can be acquired from the device and again used un. 2008 1 4:5? WALL IN6TON-DUMMER No. 4925 P. 21 to generate real-time display of "virtual" arterial and venous blood gases during this form of ventilation.

In a further arrangement the software allows the interfacing of the model with a pneumatic device which 5 simulates the behaviour of a human in whom a pleural catheter ("Chest Drain") has been inserted. In this application also the model acquires its input parameters from the device and uses these to generate a real-time display of the "virtual" arterial and venous blood gases 10 during this form of therapy.

Other devices which may interact with the model via the software include various HLMs and ancillary perfusion devices such as theriftoirietero, haemoglobinnrnfiters, rotameters, and oxygen analysers which permits the real-15 time predictions of the arterial and venous blood gas conditions on the bases of the data provided by these devices.

Interaction between the model and an inline blood gas electrode (such as the Terumo CDI series) is also possible 20 via the software, permitting comparison of the predicted blood gas measurements with data acquired from the inline electrode system. Such a display is shown for example in Figures 7 and 3. These comparisons may then be used as the basis of an "intelligent" alarm system. For example, such 25 an alarm might be triggered if a predicted measurement of a parameter (such as P02 or temperature) did not approximate 19. Jun. 2008 1 4: 57 WALL INGTON-OUMMER No. 4925 P. 22 the actual measurement; that is Lhe difference between actual and predicted blood gas measurements exceeds predetermined limits.

Such an intelligent alarm system can greatly improve 5 the safety of the clinical management of patients in the operating theatre. The alarm system takes data from a wide variety of monitoring devices, inputs this data to the model and predicts the expected responses. Because the model incorporates a facility for ^fast forwarding" 10 predictions based upon current input as alluded to above, the user of the system can be warned if therapeutic manoeuvres are likely to produce unacceptable physiological responses in the patient or if the actual physiological responses do not correspond with the predicted response. IS The predictions derived from the blood gas modelling system, (or measurements made by an in-line blood gas electrode such as the Terumo CDI-5Q0 blood gas electrode) can then be combined with real-time data derived from the HLM and ancillary equipment as the input parameters of an 20 expert surveillance system.

The expert surveillance system constantly assesses the adequacy of the current perfusion state with particular reference to gas flow management, blood flow and pressure management, temperature and oxygenation and advises the 25 perfusionist of any impending problem. This advice can be 19. Jun. 2008 14:58 WALLINGTQN-DUMMER No. 4925 P. 23 delivered to a computer terminal or lhead up' display system.

Based on current inputs from a given monitoring system ul device an oporator of the model can call up a variety of 5 "what if" responses, allowing the clinician to select appropriate therapeutic interventions. Thus for example, the model of the present invention permits the -user to predict the likely effects of therapeutic interventions such as manipulation of the inspired oxygen concentration 10 or • sweep gas flow rate in a patient on a cardio-pulmonary bypass.

Another advantage of the invention, is that it permits a user to predict the likely effects of a wide variety of system mal-functions (such as failure of the oxygenator, IS gas supply or heater/cooler system) in a patient on cardiopulmonary bypass, Other examples include simulation of an Extra-Corporeal Membrane Oxygenator (ECMO) system which permits a user to simulate a patient in extreme respiratory failure,. and the simulation of a Left Ventricular Assist 20 Device (LVAD) system in which the user can simulate the effects of a LVDA in a patient in extreme cardiorespiratory failure. Yet another example is the simulation of a One-Lung Anaesthesia (OLA) system permitting a user to simulate OLA in a patient undergoing thoracic surgery, 25 The analysis and predictive outputs are available on a display of the computer system on which the model and vn, 2008 14:58 WALLINGTON-DUMMER \c.492: P. 24 8oftware ia implemented. A number of possible analytical and predictive displays are illustrated in Figures 3, 4 and 7 to 17.

The model of the present invention also clearly lends 5 itself to use as a teaching system for clinicians to gain an underatanding of the effects of a wide range of therapies involving the range of equipments discussed above.

Platform Embodiments of • the present invention can be implemented under Microsoft operating systems such as Windows XP and Vista. In a particular form the Microsoft Xbox can provide a very powerful graphics platform.

The above describes only some embodiments of the 15 present invention and modifications, obvious to those skilled in the art, can be made thereto without departing from the scope of the present invention.

Received at IPONZ on 16 November 2009 22

Claims (35)

I claim is
1. A computer implemented model of the human cardiopulmonary system; said model including interfacing software arranged for inputs to said model of performance parameters of equipment associated with cardio-pulmonary procedures; said model adapted for prediction and monitoring in real-time of effects associated with said procedures.
2. The model of claim 1 wherein said model includes use of an unabbreviated alveolar air equation; said equation including terms for carbon dioxide and water vapour.
3. The model of claim 1 or 2 wherein said model includes a polynomial equation describing the relationship between right-to-left shunt across an artificial lung and gas flow through said lung.
4. The model of any one of claims 1 to 3 wherein said model includes a polynomial equation describing the relationship between deadspace of an artificial lung and the gas flow through said lung.
5. The model of any one of claims 1 to 4 wherein said prediction and monitoring is continually updated by Received at IPONZ on 16 November 2009 23 said model within every 100ms of acquisition of said inputs.
6. The model of any one of claims 1 to 5 wherein said model accepts inputs from an hydraulic device; said device simulating behaviour of a human circulatory system; said device when connected to a Heart Lung Machine (HLM) providing inputs to said model to generate a real-time display of virtual arterial and venous blood gases within a cardio-pulmonary bypass circuit.
7. The model of any one of claims 1 to 5 wherein said model accepts inputs from an hydraulic device; said device simulating behaviour of a patient sustained by an Extra-corporeal Membrane Oxygenator (ECMO) system; said model generating a real-time display of virtual blood gases within said ECMO system and said patient.
8. The model of any one of claims 1 to 5 wherein said model accepts inputs from an hydraulic device; said device simulating behaviour of a patient sustained by a Left Ventricular Assist Device (LVAD); said model generating a real-time display of virtual blood gases within said LVAD and said patient.
9. The model of any one of claims 1 to 5 wherein said model accepts inputs from a pneumatic device; said Received at IPONZ on 16 November 2009 24 device simulating behaviour of a patient undergoing ventilation using a double lumen tube; said model generating a real-time display of virtual arterial and venous blood gases during said ventilation. 5 10. The model of any one of claims 1 to 5 wherein said model accepts inputs from a pneumatic device; said device simulating behaviour of a patient undergoing a procedure including insertion of a pleural catheter; said model generating a real-time display of virtual
10. 10 arterial and venous blood gases during said procedure.
11. 11. The model of any preceding claim wherein inputs to said model include inputs from an inline blood gas measuring electrode; said model calculating a comparison between blood gas measurements derived from 15 said electrode and predicted blood gas measurements generated by said model.
12. 12. The model of any one of claims 1 to 11 wherein said model further includes alarm systems; said alarm systems based on comparisons between input data 20 received by said model and data generated by said model; alarm signals being generated by said alarm system when divergence between said input data and responses to said data predicted by said model indicate unacceptable physiological outcomes. Received at IPONZ on 16 November 2009 25
13. 13. The model of claim 12 wherein comparison of blood gas measurements and said predicted blood gas measurements provide basis for an alarm system; said alarm system triggered when differences between said measured and 5 predicted blood gas measurements exceed predetermined limits.
14. 14. The model of any one of claims 1 to 13 wherein said model is provided with a fast forward facility; said fast forward facility adapted for prediction of 10 physiological outcomes based on current inputs received from cardio-pulmonary associated devices to said model during a clinical procedure.
15. 15. The model of any one of claims 1 to 14 wherein said model is adapted to predict physiological outcomes of 15 selected clinical procedures based on current inputs received from cardio-pulmonary associated devices to said model.
16. 16. The raodel of claim 1 wherein said model receives inputs from a system for monitoring of the status of a 20 blood gas composition in a cardio-pulmonary bypass equipment; said system comprising a blood gas electrode in communication with a blood stream in said pulmonary bypass equipment and a software model; said Received at IPONZ on 16 November 2009 26 software model adapted to integrate parameter inputs from said equipment.
17. 17. The model of claim 1 wherein said model receives inputs from a system for comparison in real time 5 between the status of the blood gas composition of blood passing through a heart lung machine, and a software model prediction of said blood gas composition; said software model calculating variables of said blood gas composition from parameters; said 10 parameters including settings of said equipment and patient physiological parameters,
18. 18. The model of claim 1 wherein said model includes inputs from a system for virtual arterial and venous blood gas analysis in cardiopulmonary bypass 15 simulation equipment; said simulation equipment including an hydraulically realised analogue of the human cardiopulmonary system; said system including software integrating parameter inputs from variables applied to said bypass simulation equipment. 20 19. The model of claim 1 wherein said model provides a system for training of operators of heart lung machines; said system including an hydraulically realised analogue of the human cardiopulmonary system connected to said heart lung machines; said system
19. Received at IPONZ on 16 November 2009 27 including software for integrating parameter inputs from variables applied to said heart lung machines.
20. 20. The model of claim 19 wherein said hydraulically realised analogue of the human, cardiopulmonary system 5 includes an oxygenator simulating the human lungs and a pump simulating the human heart.
21. 21. The model of claim 19 wherein said parameter inputs include pump flow rate.
22. 22. The model of claim 19 wherein said parameter inputs 10 include sweep gas rate.
23. 23. The model of claim 19 wherein said parameter inputs include fraction of inspired oxygen (Fi02).
24. 24. The model of claim 19 wherein said parameter inputs include temperature. 15
25. 25. The model of claim 24 wherein said temperature includes measured arterial temperature.
26. 26. The model of claim 24 wherein said temperature includes measured venous temperature.
27. 27. The model of claim 24 wherein said temperature 20 includes measured nasopharyngeal temperature.
28. 28. The model of claim 19 wherein said parameter inputs include haematocrit. Received at IPONZ on 16 November 2009 28
29. 29. The model of claim 19 wherein said parameter inputs include metabolic rate (V02).
30. 30. The model of any one of claims 19 to 29 wherein said integrating of parameter inputs occurs in real time. 5
31. 31. The model of any one of claims 19 to 30 wherein said integrating of parameters is refreshed at predetermined intervals.
32. 32. The model of claim 31 wherein a said predetermined interval is equal to or less than 100ms. 10
33. 33. The model of claim 1 wherein said model provides an expert surveillance system; said system constantly assessing adequacy of a current perfusion state with particular reference to gas flow management, blood flow and pressure management, temperature and 15 oxygenation; said system advising a perfusionist of any impending problem.
34. 34. The model of claim 33 wherein said expert surveillance system advice is delivered to a computer terminal or to a ^head up' display system. 20
35. 35. The model of claim 33 or 34 wherein predictions derived from a blood gas modelling system, (or measurements made by an in-line blood gas electrode such as the Terumo CDI-500 blood gas electrode) can Received at IPONZ on 16 November 2009 29 then be combined with real-time data derived from an HLM and ancillary equipment as input parameters of said expert surveillance system.