Anaesthesia, Pain, Intensive Care and Emergency - Part 6 potx

Available devices There are presently four major methods with which it is possibletocalculate CO and other cardiovascular parameters from the analysis of arterial pressure waveform (Table 2): (1) the PiCCO monitor, (2) the LiDCO plus system, (3) the PRAM—Pres- sure Recording Analytical Method—system, and (4) the Vigileo monitor. Table 2. Main features of four different pulse contour methods PiCCO LiDCO PRAM Vigileo Artery used Femoral Radial Radial or femoral Radial Dedicated catheter Yes No No Yes External calibration Central line Central or peripheral line No No HR, SV, CO, SVR Yes Yes Yes Yes ITBV, EVLW, GEDV Yes No No No SVV% Yes Yes Yes Yes dp/dt; CCE; CFI Yes; no; yes No; no; no Yes; yes; no No; no; no ScvO2 No No No Yes HR heart rate, SV stroke volume, CO cardiac output, SVR systemic vascular resistance, ITBV intra-thoracic blood volume, EVLW extravascular lung water, GEDV global end-diastolic volume, SVV stroke volume variation, dp/dt pressure variations over time, CCE cardiac cycle efficiency, CFI cardiac function index, ScvO central oxygen venous saturation Fig. 3. Algorithms for calculating cardiac output from arterial waveforms. The figure shows the algorithm used by classical pulse contour method (PCM; left) and the new pressure recording analytical method (PRAM; right) for calculating stroke volume (SV). With PCM, the pulse pressure is converted to SV by calculating the area (A) under the pulsatile portion of the pressure wave [10–14]. With PRAM, the pulse pressure is converted to SV by calculating the whole area (P+C, pulsatile and continuous, respectively) under the systolic portion of the curve [14, 19–22]. Psys, Pdic, Pdia systolic, dicrotic, and diastolic pressures, Z aortic impedance, cal calibration by thermodilution (ThD), p/t description of the pressure wave profile expressed as variations in pressure (P) over time (t), K factor inversely related to the instantaneous acceleration of the vessel cross-sectional area (see text for details) 230 S. Scolletta, B. Biagioli, P. Giomarelli PiCCO Monitor The PiCCO monitors stroke volume and several volumes using transpulmonary thermodilution (e.g., intrathoracic blood volume [ITBV] and global end-diastolic volume [GEDV], both of which are indexes of preload and extravascular lung water [EVLW], an index of pulmonary oedema). The latest version uses an algorithm that includes analysis of arterial pressure during the diastolic phase to address issues around nonlinear compliance and flow–pressure relationships. According to PiC- CO’s algorithm the SV is calculated as: cal (Asys+C(p)×dP/dt)dt where cal = calibration factor by bolus thermodilution, Asys = area under the systolic portion of the curve, C(p) = compliance corrected for arterial pressure, P = pressure, and t = time. PiCC O needs regular recalibration in the event of major haemodynamic changes. PiCCO has been validated against the pulmonary artery catheter (PAC) in several conditions and has also proved to be a reliable tool in ICU and operating room [15, 16]. LiDCO plus system The LiDCO system measures CO using lithium transpulmonary thermodilution. This approach is not morphology based, i.e., is not a pulse contour method. Rather it is based on the assumption that the net power change in a heartbeat is the balance between the input of a mass (stroke volume) of blood minus the blood mass lost to the periphery during the beat. It is based on the principle of conservation of mass/powe r and on the assumption that following correction for compliance and calibration there is a linear relationship between net power and netflow.The algorithm overcomes the problem of reflected waves by taking account of the entire beat and uses an autocorrelation to determine what proportion of the change in power is determined by the stroke volume. LiDCO has been validated in several studies and proved to be a reliable monitoring system in different conditions [14, 17, 18]. PRAM—pressure recording analytical method The most innovative feature of this method is the lack of a requirement for calibration. The algorithm is based on the physical theory of perturbations, analys- ing the arterial wave using a collecting signal of 1,000 Hz. The most important points on the arterial wave for the calculation are the initial point of the pulse wave (diastolic pressure), the highest point (systolic pressure), and the point of closure of the aortic valve (dicrotic notch or incisura). PRAM uses these and other points of perturbance to take into account the interaction of left ventricle contraction, aortic impedance and compliance and peripheral resistance. With PRAM, the SV is calculated as: A/(P/t×K) where A=whole area under the systolic portion of the curve, P/t=description of the pressure wave profile expressed as the variations in pressure (P) over time (t); Arterial waveform analysis to determine cardiovascular parameters 231 K=factor inversely related to the instantaneous acceleration of the vessel cross sectional area (Fig. 3). PRAM has been validated in humans and animals, and in cardiac surgery [19–22]. VIGILEO Monitor The Vigileo system uses a dedicated transducer (FloTrac) incorporated in the monitor. As with PRAM, in this system calibration is not needed, and only an arterial line is required. The algorithm is based primarily on the standard deviation of the pulse pressure waveform: CO=f(compliance, resistance)×s p HR where f (compliance, resistance) is a scale factor proportional to vasculature compliance and peripheral resistance, s p is the standard deviation of arterial pressure, and HR is the heart rate. The standard deviation of the arterial pressure is computed beat-to-beat. Compliance and resistance are derived from the analysis of the shape of the arterial pressure wave. Additional parameters, such as the pressure-dependent Windkessel compliance, C w , based on Langwouters’ study [12], and patient body surface area, are also included to take other patient-specific characteristics into account. The Vigileo system seems to be easy to use and accurate, and it provides reliable cardiac output assessment [23]. Preload monitoring and estimation of fluid responsiveness Haemodynamic instability with low cardiac output in critically ill patients is often caused by hypovolaemia. However, determining the level of preload, and most importantly fluid responsiveness, i.e. predicting whether or not fluid loading will increase a patient’s CO, is still very difficult at the patient’s bedside. Several studies published within the last 15 years have clearly demonstrated that volumetric para- meters such as the GEDV and the ITBV (both by PiCCO monitor) make it possible both to assess cardiac preload and to monitor changes in preload under fluid therapy in critically ill patients much more reliably than the cardiac filling pres- sures, central venous pressure (CVP) or pulmonary artery occlusion pressure (PAOP)[24–27]. Thismeansthatthestatic parameters(CVPandPAOP)donotallow prediction, prior to fluid loading, of whether or not the intervention in question will increase the patient’s CO. Within the last few years, there has been renewed interest in the specific interactions of the lungs and the cardiovascular system caused by mechanical ventilation [28]. So-called dyn amic parameters, such as pulse pressure variation (PPV) and stroke volume variation (SVV), all based on ventilation-induced changes in the interactions of heart and lungs, have been evaluated by different groups with a view to improving the assessment of fluid responsiveness, and by this means to optimise fluid therapy in mechanically ventilated patients [29–31]. The rationale behind the parameters SVV and PPV is similar: the alternating intrathoracic pressure during each mechanical breath induces transient but distinct changes—predominantly in cardiac pr eload—which, according to the Frank- 232 S. Scolletta, B. Biagioli, P. Giomarelli Starling mechanism, lead to undulations in left ventricular stroke volume (Fig. 4). Thus, each mechanical breath serves as a small endogenous volume loading and unloading manoeuvre. The degree of undulation depends on where on the Starling curve the patient’s left ventricle is operating. The Starling (or ventricular function) curve describes the relation between preload and stroke volume [32]. A steep slope of the Starling curve is associated with a large SVV, whereas a shallow slope results in only a small SVV. Thus, high SVV indicates volume responsiveness, or in other words, shows that SV and CO can be improved by fluid loading. Conversely, a low SVV in a hypotensive patient will support the decision to use catecholamines. For example, a value under 10% for SVV implies that the patient probably does not need volume expansion, and a value over 15% implies that the patient probably does need volume expansion [33]. Arterial pulse contour analysis now seems to be a useful method for measuring, again continuously and in an automated fashion, those variations of SV that have a causative role in PPV [29–31, 33]. Finally, the early inspiration augmentation of the left ventricle (LV) stroke output is reflected as an increase in the systolic blood pressure termed delta up (dUp), while the later decrease in LV stroke output is reflected in a decrease in the systolic blood pressure termed delta down (dDown) [33]. The dUp is measured as the difference between the maximal value of the systolic blood pressure and the systolic blood pressure during a long end-expiratory pause or a short (5 s) episode of apnoea, while the dDown is measured as the difference between the reference end-expiratory systolic blood pressure and the minimal systolic blood pressure Fig. 4. Respiratory changes in arterial pressure in a mechanically ventilated patient. Pulse pressure (systolic minus diastolic pressure) is seen to be maximal (PPmax) at the end of the inspiratory period and minimal (PPmin) during the expiratory period. The respiratory changes in pulse pressure (PPV) can be calculated as the difference between PPmax and PPmin, divided by the mean of the two values. The delta Up (dUp) is the increase in systolic blood pressure, while the delta Down (dDown) reflects a decrease in systolic blood pressure. The systolic pressure variation (SPV) is the sum of dUp and dDown [25–33]. The line of reference is obtained during a long end-expiratory pause or a short (5 s) episode of apnoea (see text for details) Arterial waveform analysis to determine cardiovascular parameters 233 value. The sum of the dUp and the dDown, which is the difference between the maximal and the minimal systolic blood pressure values during one mechanical breath, is termed the ‘systolic pressure variation’ (SPV) (Fig. 4). It is important to note that dUp and dDown are two different haemodynamic events: dDown is due to the decrease in venous return during the mechanical breath, and its magnitude reflects fluid responsiveness [33]; dUp reflects the early inspiratory augmentation of the LV stroke output and was originally described as ‘reversal pulsus paradoxus’ [34]. Since the dUp can be influenced by some partial transmission of the airway pressure to the LV and aorta during the mechanical breath, it may not necessarily be representative of augmented LV stroke volume [33]. Furthermore, variations in stroke volume or pulse pressure may not be as readily attributed to hypovolaemia in the spontaneously breathing patient or in the presence of an irregular cardiac rhythm. As a result, these parameters may not be reliable in a large proportion of critical care patients [35]. Cardiac contractility assessment Most PCMs provide an indirect measure of LV contractility. They calculate the so-called dP/dt (mmHg/s), a variable based on LV intracavitary pressure, which is generated by an active myocardial stress. Thus, a high dP/dt ratio indicates im- proved LV contractility, whilst conversely a low dP/dt ratio indicates reduced cardiac contractility. PiCCO also provides the cardiac function index (CFI = CO/GEDV), which represents cardiac performance independently of the preload. PRAM also provides a new parameter, the CCE (cardiac cycle efficiency), which represents the performance of the LV and the ventricular-arterial coupling. The CCE ranges from –1 to +1, with –1 being the worst and +1 the best possible cardiac cycle performance. Recently, in 70 patients who had undergone coronary operations, the CCE meas- ured by PRAM was compared with the LV ejection fraction (EF%) by echocardio- graphy [36]. Overall, the correlation coefficient between LVEF% and CCE values was 0.82 (r 2 =0.91, p<0.001), and the correlation coefficients ranged from 0.80 to 0.84 at different points in the study (p<0.001) [36]. Conclusions Functional haemodynamic monitoring, which allows more detailed insight into cardiovascular physiology and disease than is otherwise possible, might help to improve the detection and the understanding of pathologic cardiocirculatory situa- tions. Theoretically, functional haemodynamic monitoring has the potential to improve the therapeutic management of critically ill patients, and thereby their outcome. Arterial pulse contour analysis is a method that can contribute to this developmentby (1) transferringinformationon CO andhenceonbloodflowon-line, and (2) enabling the direct interactions between the lungs and the cardiovascular system to be tracked continuously during mechanical ventilation [2, 14, 17, 24, 33]. 234 S. Scolletta, B. Biagioli, P. Giomarelli Clinician s today are equipped with several new PCMs that provide for minimally invasive haemodynamic assessment. These monitoring systems are not mutually exclusive; each has different advantages and limitations, and each has something to offer a given patient population, health car e institution budget and clinical use r. References 1. Nichols WW, O’Rourke MF (2005) McDonald’s blood flow in arteries: theoretical, experimental and clinical principles. Hodder–Arnold, London 2. Bennet D (2005) Arterial pressure: a personal view. In: Pinsky MR, Payen D (eds) Functional hemodynamicmonitoring. Springer, Berlin HeidelbergNewYork, pp 89–97 3. Snellen HA (1980) EJ Marey and cardiology. Kookyer, Rotterdam 4. Mahomed FA (1872) The physiological and clinical use of the sphygmograph. Med Times Gaz 1:62–64 5. Broadbent WH (1890) The pulse. Cassell, London 6. Kelly R, Hayward C, Avolio A et al (1989) Non-invasive determination of age-related changes in human arterial pulse. Circulation 80:1652–1659 7. Kemmotsu O, Ueda M, Otsuka H et al (1991) Arterial tonometry for non-invasive, continuous blood pressure monitoring during anesthesia. Anesthesiology 75:333–340 8. Glasser SP,ArnettDK,McVeighGEet al(1997)Vascular complianceand cardiovascular disease: a risk factor or a marker? Am J Hypertens 10:1175–1189 9. Karamanoglu M, O’Rourke MF, Avolio AP et al (1993) An analysis of the relationship between central aortic and peripheral upper limb pressure wave in man. Eur Heart J 14:160–167 10. Wesseling KH, De Wit B, Weber JAP et al (1983) A simple device for the continuous measurement of cardiac output. Its model basis and experimental verification. Adv Cardiol Phys 5 (Suppl II):16–52 11. Wesseling KH, Jansen JRC, Settels JJ et al (1993) Computation of aortic flow from pressure in humans using a nonlinear, three-element model. J Appl Physiol 74:2566–2573 12. Langewouters GJ, Wesseling KH, Goedhard WJA (1984) The static elastic properties of 45 human thoracicand20abdominal aortas invitroandtheparameters of a newmodel. J Biomech 17:425–435 13. Jansen JRC, Wesseling KH, Settels JJ et al (1990) Continuous cardiac output monitoring by pulse contour during cardiac surgery. Eur Heart J 11 (Suppl I):26–32 14. Cecconi M, Wilson J, Rhodes A (2006) Pulse pressure analysis. In: Vincent JL (ed) Yearbook of intensive care and emergency medicine. Springer, Berlin Heidelberg New York, pp 176–184 15. Della Rocca G, Costa MG, Pompei L et al (2002) Continuous and intermittent cardiac output measurement: pulmonary artery catheter versus aortic transpulmonary techni- que. Br J Anaesth 88:350–356 16. Rodig G, Prasser C, Keyl C et al (1999) Continuous cardiac output measurement: pulse contour analysis versus thermodilution technique in cardiac surgical patients. Br J Anaesth 82:525–530 17. Rhodes A, Sunderland R (2005) Arterial pulse power analysis: the LiDCOTM-plus system. In: Pinsky MR, Payen D (eds) Functional hemodynamic monitoring. Springer, Berlin Heidelberg New York, pp 183–192 Arterial waveform analysis to determine cardiovascular parameters 235 18. Linton RAF, Band DM, Haire KM (1993) A new method of measuring cardiac output in man using lithium dilution. Br J Anesth 71:262–266 19. Romano SM, Pistolesi M (2002) Assessment of cardiac output from systemic arterial pressure in humans. Crit Care Med 30:1834–1841 20. Giomarelli P, Biagioli B, Scolletta S (2004) Cardiac output monitoring by pressure recording analytical method in cardiac surgery. Eur J Cardiothorac Surg 26:515–520 21. Scolletta S, Romano SM, Biagioli B et al (2005) Pressure recording analytical method (PRAM) for measurement of cardiac output during various haemodynamic states. Br J Anaesth 95:159–165 22. Romano SM, Scolletta S, Olivotto I et al (2006) Systemic arterial waveform analysis and assessment of blood flow during extracorporeal circulation. Perfusion 21:109–116 23. Manecke GR (2005) Edwards FloTrac sensor and Vigileo monitor: easy, accurate, reliable cardiac output assessmentusing the arterialpulse wave. ExpertRevMedDevice 2:523–527 24. Reuter DA, Goetz AE (2005) Arterial pulse contour analysis: applicability to clinical routine. In: Pinsky MR, Payen D (eds) Functional hemodynamic monitoring. Springer, Berlin Heidelberg New York, pp 175–182 25. Sakka SG, Ruhl CC, Pfeiffer UJ et al (2000) Assessment of cardiac preload and extrava- scular lung water by single transpulmonary thermodilution. Intensive Care Med 26:180–187 26. Michard F, Teboul JL (2000)Using heart-lunginteraction to assess fluidresponsiveness during mechanical ventilation. Crit Care 4:282–289 27. Wiesenack C, Prasser C, Rodig G et al (2003) Stroke volume variation as an indicator of fluid responsiveness using arterial pulse contour analysis in mechanically ventilated patients. Anesth Analg 96:1254–1257 28. Jardin F, Farcot JC, Gueret P (1983) Cyclic changes in arterial pulse during respiratory support. Circulation 83:266–227 29. Perel A, Pizov R, Cotev S (1987) Systolic blood pressure variation is a sensitive indicator of hypovolemia in ventilated dogs subjected to graded hemorrhage. Anesthesiology 67:498–502 30. Reuter DA, Kirchner A, Felbinger TW (2003) Usefulness of left ventricular stroke volume variations to assess fluid responsiveness in patients with reduced left ventricu- lar function. Crit Care Med 31:1399–1404 31. Tavernier B, Makhotine O, Lebuffe G (1998) Systolic pressure variation as a guide to fluid therapy in patients with sepsis-induced hypotension. Anesthesiology 89:1313–1321 32. Sonnenblick EH, Strohbeck JE (1977) Current concepts in cardiology. Derived indices of ventricular and myocardial function. N Engl J Med 296:978–982 33. Perel A, Preisman S, Berkenstadt H (2005) Arterial pressure variation during positive- pressure ventilation. In: Pinsky MR, Payen D (eds) Functional hemodynamic monito- ring. Springer, Berlin Heidelberg New York, pp 313–329 34. Massumi RA, Mason DT, Zakauddin V et al (1973) Reversed pulsus paradoxus. N Engl J Med 289:1272–1275 35. Pinsky MR (2003)Probing thelimits ofarterialpulse contouranalysis topredict preload responsiveness. Anesth Analg 96:1245–1247 36. Scolletta S, Romano SM, Maglioni E et al (2005) Left ventricular performance by PRAM during cardiac surgery. Intensive Care Med 31 (Suppl 1):S157 236 S. Scolletta, B. Biagioli, P. Giomarelli The Utstein style for the reporting of data from cardiac arrest J.P. NOLAN, C.L. GWINNUTT Healthcare professionals who practise resuscitation come from many disciplines, organisations and backgrounds. In addition, the emergency medical service (EMS) systems in which they work differ in different parts of the world. Survival rates following out-of-hospital cardiac arrest (OHCA) vary substantially between health care systems. A review of EMS with a defibrillation capability that included 33,124 patients reported a median rate of 6.4% for survival to hospital discharge, with a range of 0–20.7% [1]. Summary data from 37 communities in Europe indicate that survival to hospital discharge after EMS-treated OHCA is 10.7% [2]. After in-hos- pital cardiac arrest (IHCA), the reported survival to 24 h rates range from 13% to 59% and survival to discharge rates from 0% to 42%, although major studies report a survival to discharge of approximately 20% [3–7]. The main reasons for this variation are the many confounders that influence outcome following cardiac arrest (Table 1) and the lack of uniformity in cardiac arrest reporting. This lack of uniformity in reporting pertains to both the process and the results of resuscitation attempts; for example, the definition of survival is reported variously as return of spontaneous circulation (ROSC) and as survival at 5 min, 1 h, 24 h, and discharge from hospital. Table 1. Confounders that influence cardiac arrest. (Reproduced from Advanced Life Sup- port, 5th edn, Resuscitation Council (UK), London, 2006) · Differences in the type of emergency medical service system (EMS; e.g. availability of defibrillators, differences in response intervals) · Differences in the incidence of bystander cardiopulmonary resuscitation (CPR) · Different patient populations (e.g., a study may be confined to in-hospital cardiac arrests (IHCA) or may include pre-hospital arrests) · Prevalence of co-morbidities · Frequency of implementing do-not-attempt-resuscitation (DNAR) policies · The primary arrest rhythm · The definition of cardiac arrest used e.g. whether primary respiratory arrests are included) · Availability of cardiac arrest and medical emergency teams Chapter 22 Why standardise data collection? The lack of uniformity in cardiac arrest reporting makes it difficult to evaluate the impact of individual factors, such as new drugs or techniques on survival. Thus, if it is intended that it should be possible togeneralisefromthefindingsfromresearch studies undertaken in one EMS system it is vitally important that the terminology and definitions used in the reporting of resuscitation events are standardised. New interventions have been introduced that have improved survival rates only slightly; this is because cardiac arrest is common and kills thousands of people every year. Individual hospitals or healthcare systems are unlikely to have sufficient patients to allow them to identify these subtle effects or eliminate confounding factors. Adopting uniform definitions and collecting standardised data on the process and outcome of cardiopulmonary resuscitation in many patients and systems may make it possible to identify relatively small changes in outcome. Changes in the resuscitation process can then be introduced and evaluated using a reliable measure of outcome. This methodology enables drugs and techniques developed in experimental studies to be evaluated reliably in the clinical setting. Origins of the Utstein style In June 1990, representatives from the AHA, European Resuscitation Council (ERC), Heart and Stroke Foundation of Canada (HSFC) and the Australian Resu- scitation Council (ARC) attended a meeting, hosted by the Laerdal Foundation, at Utstein Abbey on the island of Mosteroy, Norway [8]. The purpose of this meeting was to discuss problems in resuscitation nomenclature and the lack of standardised terminology in reports relating to adult out-of-hospital cardiac arrest. This was the first major collaborative venture involving resuscitation councils from around the world. A follow-up meeting was held in December 1990 in Surrey, England, where the decision was made to adopt the term ‘Utstein style’ for the uniform reporting of data from out-of-hospital cardiac arrests [9]. Out-of-hospital cardiac arrest The first of the ‘Utstein’ papers was entitled ‘Recommended guidelines for uniform reporting o f data from o ut- of-ho spital cardiac a r rest ( OHCR): the Utstein Style’ and wasp ubl ishedsimultaneous lyi nCirculation,ResuscitationandAnnalsofEmergency Medicine [10–12]. The Utstein meetings each took the form of a series of panel discussions to obtain consensus on definitions and terminology. The audience of experts rotated around series of panels on specific topics. Each panel session was chaired by two individuals; these co-chairmen remained in place and presented the topic to three separate audiences. The first discussion reviewed the evidence and produced a proposal. During the discussion with the second audience, reactions and comments on the draft proposal were sought, leaving the final audience to critique 238 J.P. Nolan, C.L. Gwinnutt and refine the finaltopic statement. The same formathasbeenusedinmostsubsequent Utsteinmeetingsandwasthestyleusedduringrecentresuscitationconsensusconfe- rences [13, 14]. The 1991 Utstein paper introduced a glossary of terms used in the collection o f cardiac arrest data and proposed a standard d efinition for each of these terms, e.g., bystander CPR was d efined as an attempt to perform basic cardiopulmo- nary resuscitation (CPR) by someone who is not part of an organised emergency response system. Time points and event-to-event intervals were defined precisely, and a template for reporting cardiac arrest data was proposed (Fig. 1). Recommendations for the description o f EM S systems were made. Fig. 1. The original Utstein reporting template for out-of-hospital cardiac arrest [12]. The Utstein style for the reporting of data from cardiac arrest 239 [...]... Emerg Med 34(1):517–525 2 Atwood C, Eisenberg MS, Herlitz J, Rea TD (2005) Incidence of EMS-treated out-of-hospital cardiac arrest in Europe Resuscitation 67 :75–80 3 Sandroni C, Nolan J, Cavallaro F, Antonelli M (20 06) In-hospital cardiac arrest: incidence, prognosis and possible measures to improve survival Intensive Care Med (in press) 4 Peberdy MA, Kaye W, Ornato JP et al (2003) Cardiopulmonary resuscitation... of medical and scientific knowledge, they also require close teamwork and collaboration between multi-professional and multi-specialty partners The demanding and rigorous nature of the work environments is similar, and the personality of the practitioners concordant In order to be successful in initiating new educational paradigms, the organisation must align the incentives of the team and its individual... surgery [65 ] and for gastrointestinal bleeding [66 ] and intracerebral haemorrhages in adults [67 ], etc A recent study by some of the investigators engaged in the first multicentre study, however [68 ], has led these workers to stress the futility of administering recombinant factor VIIa to patients with a very low RTS and of giving it too late, after the onset of profound acidosis and coagulopathy, and to... collaboratively to maximise patient care, be respectful of one another, and participate in the process of self-regulation, including remediation and discipline of members who have failed to meet professional standards … Physicians have both individual and collective obligations to participate in these processes The obligations include engaging in internal assessment and external scrutiny of all aspects... anaesthesiology and critical care medicine the distinctions become even more blurred; the disciplines require a detailed understanding of the human–machine interface from the perspectives of both practitioner and patient The routine requirement for utilisation of machinery in patient care is ubiquitous in anaesthesia and critical care, and this makes the specialist training curriculum more challenging and less... trauma—the Utstein style A report of a working party of the International Trauma Anaesthesia and Critical Care Society (ITACCS) Resuscitation 42:81–100 Langhelle A, Nolan J, Herlitz J et al (2005) Recommended guidelines for reviewing, reporting, and conducting research on post-resuscitation care: The Utstein style Resuscitation 66 :271–283 Nolan JP, Morley PT, Vanden Hoek TL, Hickey RW (2003) Therapeutic... design, rationale and preliminary results Resuscitation 65 : 265 –277 Sandroni C, Cavallaro F, Ferro G et al (2003) A survey of the in-hospital response to cardiac arrest on general wards in the hospitals of Rome Resuscitation 56: 41–47 Patrick A, Rankin N (1998) The in-hospital Utstein style: use in reporting outcome from cardiac arrest in Middlemore Hospital 1995–19 96 Resuscitation 36: 91–94 Skrifvars... rhythm and clinical outcome from in-hospital cardiac arrest among children and adults JAMA 295:50–57 8 Nolan J, Soar J (2005) Images in resuscitation: Utstein Abbey Resuscitation 64 :5 6 9 Chamberlain D (2005) The International Liaison Committee on Resuscitation (ILCOR)—past and present Compiled by the Founding Members of the International Liaison Committee on Resuscitation Resuscitation 67 :157– 161 10... enables resident physicians to learn the art and science of medicine and to apply that learning in a monitored and mentored setting within an institution committed to: competency based education and practice; support for professional and personal development of learners, faculty and staff; educational and clinical excellence through continuous quality improvement and innovation … Every patient deserves... Resuscitation 67 : 167 –170 15 Cummins RO, Chamberlain D, Hazinski MF et al (1997) Recommended guidelines for reviewing, reporting, and conducting research on in-hospital resuscitation: the in-hospital “Utstein style” American Heart Association Circulation 95:2213–2239 16 Cummins RO, Chamberlain D, Hazinski MF et al (1997) Recommended guidelines for reviewing, reporting, and conducting research on in-hospital . EMS-treated out-of-ho- spital cardiac arrest in Europe. Resuscitation 67 :75–80 3. Sandroni C, Nolan J, Cavallaro F, Antonelli M (20 06) In-hos pital cardiac arrest: incidence, prognosis and possible. guidelines for reviewing, reporting, and conducting research on post-resuscitation care: The Utstein style. Resu- scitation 66 :271–283 26. Nolan JP, Morley PT, Vanden Hoek TL, Hickey RW (2003) Therapeutic. Assessment of cardiac preload and extrava- scular lung water by single transpulmonary thermodilution. Intensive Care Med 26: 180–187 26. Michard F, Teboul JL (2000)Using heart-lunginteraction to assess