Abstract
Introduction. This study tested the hypothesis that cardiac arrest patients use a “cardiac
pump” and a “thoracic pump” to generate blood flow during resuscitation. We aimed to
quantify the effect of both mechanisms on PetCO2 (end-tidal carbon dioxide tension) in
individual out-of-hospital cardiac arrest (OHCA) patients.
Material and methods. Twenty-seven patients were studied in this observational prospective
study. Compression depth, rate and PetCO2 were assessed using an accelerometer and a
mainstream PetCO2 monitor (Zoll E series defibrillator). An experimental apparatus was
connected to the endotracheal tube, measuring intratracheal pressures. In 20 s interval before
each ventilation, we measured compression depth (CD), ventilation pressure (Pvent), number
of compressions (#C), intrathoracic pressure difference (ΔCP) and total intrathoracic pressure
(PIP). Individual patient models were created using UNIANOVA. Patients were categorised
according to the variables best predicting PetCO2 changes. A “cardiac pump” was considered
to be present when CD and/or # predicted PetCO2 changes and a “thoracic pump” when ΔCP
predicted PetCO2.
Results. In 13/27 (48%) patients a “cardiac pump mechanism” was identified.. In 1/27 (4%) a
“thoracic pump mechanism” and 10/27 (37%) a combination of both mechanisms was found.
An increase of depth with one centimetre increased PetCO2 from 1 to 12 mm Hg in 18/27
(67%) patients. An increase in rate with 10/min raised PetCO2 from 3 to 12 mm Hg in 6/27
(22%) patients. An increase of 10 mm H2O in ΔCP would increase PetCO2 from 1 to 19 mm
Hg in 10/27 (37%) in patients. Ten patients (37%) showed a negative influence of either PIP or
Pvent on PetCO2.
Conclusion. We developed a method to quantify the relative effect of the “cardiac” and of the
“thoracic pump mechanism” in OHCA patients, showing that a “thoracic pump mechanism”
is currently not accessed in all patients. While excessive PIP negatively influenced PetCO2, a
higher ΔCP can increase PetCO2.
1
Abstract
Introductie. Deze studie test de hypothese dat patiënten met een hartstilstand gebruik maken
van een “cardiale pomp” en een “thoracale pomp” om bloed flow te genereren tijdens
reanimtie. Het doel van deze studie is om het effect van beide mechanismen te kwantificeren
op de end-tidal CO2 spanning (PetCO2) bij patiënten die lijden aan een uit-hospitaal
hartstilstand (OHCA).
Materialen en methoden. Zevenentwintig patiënten zijn bestudeerd in deze observationele
prosepctieve studie. Compressiediepte, -snelheid en PetCO2 werden bekomen door
respectievelijk een accelerometer en een mainstream PetCO2 monitor (Zoll E Series
defibrillator). Een experimenteel toestel werd verbonden aan de endotracheale tube en maakte
intratracheale drukmeting mogelijk. Over een tijdsinterval van 20 seconden voor elke
ventilatie, werden mediane compressiediepte (CD), mediane ventilatiedruk (Pvent),
intrathoracaal drukverschil (ΔCP) en gemiddelde intrathoracale druk (PIP) gemeten.
Individuele patiëntmodellen werden gemaakt met UNIANOVA. De patiënten werden
gecategoriseerd volgens de variabelen die het beste de veranderingen in PetCO2 voorspellen.
Een “cardiale pomp” werd weerhouden als CD en/of #C PetCO2 veranderingen voorspelde en
een “thoracale pomp” als ΔCP PetCO2 veranderingen voorspelde.
Resultaten.. In 13/27 (48%) patiënten werd een “cardiale pompmechanisme” weerhouden, in
één (4%) een “thoracaal pompmechanisme” en in 10/27 (37%) patiënten een combinatie van
beide mechanismen. Een toename van diepte met één centimeter deed PetCO2 toenemen van 1
tot 12 mm Hg in 18/27 (67%) patiënten. Een toename in frequentie van 10/min deed PetCO2
toenemen van 3 tot 12 mm Hg. Een toename van 10 mm H2O zou een toename in PetCO2 van
1 tot 19 mm Hg bewerkstelligen in 10/27 (37%) patiënten. Tien (37%) patiënten toonden een
negatieve invloed van ofwel PIP ofwel Pvent op PetCO2.
Conclusie. We hebben een methode ontwikkeld om het relatieve effect van een “cardiaal” en
“thoracaal pomp mechanisme” in OHCA patiënten te kwantificeren en hebben aangetoond dat
het “thoracaal pompmechanisme” niet gebruikt word in alle patiënten. Hoewel een
overdreven PIP de PetCO2 negatief beïnvloedde, deed een hogere ΔCP PetCO2 toenemen.
2
Background
During the course of history, attempts to restore vital functions are not uncommon. Depictions
of air insufflations were first described in Egyptian and biblical mythology. The research of
Kouwenhower, Jude and Knickerbocker during the late fifties demonstrated that closed chest
compressions raised arterial blood pressure, facilitated defibrillation and consequently rapid
resuscitation in a canine model (Kouwenhouwer et al., 1960). This research made the
combination of closed chest compressions and periodical air insufflation the cornerstone of
modern cardiopulmonary resuscitation (CPR) (Koster et al., 2010).
Approximately 80 to 90% of all cardiopulmonary arrests are cardiac in origin and are
associated with a higher chance of resuscitation and survival compared with their non-cardiac
counterparts (Pell et al., 2003). The most common cardiac aetiology of out-of-hospital
cardiopulmonary arrest (OHCA) is myocardial ischemia due to atherosclerotic multivessel
disease of the coronary arteries. If an initial electrocardiogram is obtained shortly after the
occurrence of OHCA, most patients will present with ventricular fibrillation (VF), reflecting
electrical instability inherent to the chronic cardiac ischemia (Kremers et al., 1989; Engdahl et
al., 2003). Non-cardiac causes of OHCA include trauma, postoperative complications, drug
abuse, pulmonary embolism, aortic dissection/aneurysm, obstructive pulmonary disease and
pneumonia. These conditions present mostly with asystole and pulseless electrical activity
(PEA). These cardiac rhythms are associated with a lower chance of successful resuscitation
and survival (Engdahl et al., 2003).
The major role of CPR is to provide sufficient blood flow to vital organs (like the
myocardium and central nervous tissue) in order to provide both successful defibrillation and
return of spontaneous circulation (ROSC) and maintaining the function of these vital organs.
Despite 30 years of research, the mechanisms by which blood flows through the body during
CPR is not fully understood. Two theories have been proposed to explain the mechanisms of
blood flow. The first is the direct cardiac compression model. External compressions squeeze
the heart between sternum and spine, causing elevated pressure in both ventricles, opening
both semilunar valves and pumping blood in the pulmonary artery and in the aorta
(Kouwenhouwer et al., 1960; June et al., 1961). Several observations indicate that this
mechanism may not always be operative. Coughing can prolong consciousness up to 40
seconds in patients with VF during cardiac catheterization. This demonstrates that blood flow
3
can be generated by changes in extra- to intrathoracic pressure gradient (Criley et al., 1976).
In addition, echocardiography has shown that late in the course of CPR the mitral and
tricuspid valves do not close (Werner et al., 1981) and that the dimensions of the left ventricle
do not change (Rich et al., 1981). These data led to the “thoracic pump mechanism” as a
model for blood flow during CPR. It theorizes that the heart serves as a passive conduit
between the pulmonary artery and aorta with selective flow to the aorta and the
brachiocephalic veins who are protected by the closing of intrathoracic inlet venous valves.
The negative pressure generated during decompression in experimental resuscitation settings
supports this assumption. The use of an intrathoracic pressure regulator to create a superior
intrathoracic pressure gradient improved the venous return, perfusion of and flow to vital
organs, cardiac output and cerebral flow in pigs (Yannopoulos et al., 2005; Yannopoulos et
al., 2006). Other studies demonstrated that excessive positive intrathoracic pressure caused by
overzealous ventilation (Aufderheide et al., 2004) or incomplete chest wall recoil
(Aufderheide et al., 2005) may have a detrimental effect on survival from cardiac arrest.
Positive end-expiratory pressure (PEEP) increased intrathoracic pressure, preventing venous
return and thus lowering cardiac output (Hodgkin et al., 1980). An observational study in a
porcine model however, demonstrated that PEEP created an increase in carotid blood flow
(Chandra et al., 1981). A canine model confirmed this increase in carotid blood flow to a
maximum threshold of 5 cm PEEP, suggesting a similar PEEP threshold may exist in humans
(Ido et al., 1982). These various results show that neither theory fully explains all
hemodynamic processes during CPR, suggesting that in reality a combination of both
mechanism may be present.
Capnography and end-tidal carbon dioxide tension (PetCO2), i.e. the measurement of CO2 at
the end of expiration, has found its way into pre-hospital medicine and the emergency
department. Though initially its main use was verification of correct placement of the
endotracheal tube (ETT) (Timmerman et al., 2007), it can be employed for hemodynamic
monitoring of intubated and non-intubated patients and monitoring of CPR efforts
(Ward and Yearly, 1998). While cardiac output (CO) in humans is not routinely measured
because insertion of a pulmonary artery catheter is not possible or indicated, several animal
studies indicated a relationship between CO and PetCO2 in situations of low flow such as
resuscitation and shock (Blumenthal and Voorhees, 1997; Jin et al., 2000). Several other
researchers showed a similar relationship between PetCO2 and coronary perfusion pressure
(CPP) (Sanders et al., 1985; Kern et al., 1989; Von Planta et al., 1989). This association of
4
PetCO2 and physiological parameters makes it a valuable parameter during CPR. Several
investigators reported that PetCO2 may offer prognostic information concerning the likelihood
of obtaining ROSC. These included averaging PetCO2 over 20 minutes of resuscitation, taking
initial and maximal PetCO2, PetCO2 changes after ROSC and PetCO2 during resuscitation of
various presenting rhythms such as asystole and PEA. Numerous studies illustrated that
ROSC is associated with a sudden increase in PetCO2, sometimes even before a pulse is felt
(Kalenda, 1987; Garnett et al., 1987; Sanders et al., 1989; Grmec et al., 2003). Several groups
have also demonstrated that an initial PetCO2 of 10 to 15 mmHg has a high predictive value
for non-ROSC (Grmec and Klemen, 2001: Gmrec et al., 2003; Grmec et al., 2007; Grmec et
al., 2011). Other research groups have associated a PetCO2 value of less than 10 mmHg after
20 minutes of resuscitation with a low chance of obtaining ROSC (Wayne et al., 1995;
Cantineau et al., 1996; Levine et al., 1997; Kolar et al., 2008). This prognostic value of
PetCO2 was also applicable in cardiac arrest due to asphyxia after 1 to 5 minutes of ventilation
during the CPR algorithm (Grmec et al., 2003; Grmec et al., 2011). During a respiratory
arrest, cardiac output and pulmonary blood flow continues for a period of time prior to cardiac
standstill. During this stage cellular metabolism continues so CO2 is still being delivered to
the lungs, thereby increasing the alveolar CO2 tension (Berg et al., 1996). Research has found
that several factors may alter the PetCO2 during CPR. A theoretical animal model showed an
augmentation of CO following an increase in compression rate from 60/’ to 120/’ (Maier et
al., 1984). This is confirmed by an increase in CPP, PetCO2, higher chance for successful
defibrillation and a higher chance for ROSC in animals (Feneley et al., 1988; Swenson et al.,
1988). Not all animal models, however, reached the same conclusion, as some showed no
difference in CPP and survival (Kern et al., 1986; Milander et al., 1995). Human studies have
not demonstrated a conclusive correlation between compression rate or depths and PetCO2
(Ornato et al., 1988; Kern et al., 1991). No randomized studies exist comparing different
compression rates in humans and their effect on PetCO2 and/or survival. A porcine model
demonstrated a linear relationship between depth and PetCO2 (Babbs et al., 1983). Increasing
compression depth in humans is associated with a higher chance of successful defibrillation,
ROSC and hospital discharge (Edelson et al., 2006; Kramer-Johansen et al., 2006; Babbs et
al., 2008; Edelson et al., 2008). However resuscitation in these studies was performed
according to the 2005 resuscitation guidelines (Handley et al., 2005), limiting the number of
patients with compression depths higher than 5,1 cm. There are no studies prospectively
linking different compression depths to PetCO2 in cardiac arrest patients.
5
Aim of the study
This study tested the hypothesis that cardiac arrest patients use a “cardiac pump mechanism”
and a “thoracic pump mechanism” to generate blood flow during resuscitation efforts. We
aimed to quantify the effect of both pump mechanisms on PetCO2 in individual OHCA
patients.
Previous research of intrathoracic pressure showed that during a ventilation cycle, a
ventilation pressure (Pvent ) is built up, amplifying the compression waveforms (Aufderheide
et al., 2004). To describe the pressure difference between Pvent and the amplified compression
wave, we introduced a new parameter, the intrathoracic pressure difference (Delta
compression pressure (ΔCP)). A self-made apparatus connected to the ETT allowed us to
measure pressures in the trachea, which represent the overall intrathoracic pressures, and to
calculate pressure differences in the thoracic cavity. We hypothesized that by altering
compression and ventilation parameters, ΔCP will change accordingly. This change could
lead to a change in PetCO2.
Another possible way to influence PetCO2 is by enhancing the cardiac pump. Current CPR
guidelines recommend a compression depth of “at least 5 cm” (Koster et al., 2010). We
hypothesized that increasing compression depth beyond the current guidelines will lead to an
increase in cardiac output. The current CPR guidelines advise a minimal compression rate of
“at least 100 per minute” (Koster et al., 2010). We hypothesized that an increase in
compression rate will affect the PetCO2.
Moreover the intrathoracic pressure measuring device allowed the calculation of average
intrathoracic pressure (PIT). Elevated intrathoracic pressures may cause inhibition of venous
return and consequently a reduction in CO. Examining the PIT in patients undergoing CPR,
allowed us to correlate changes in PIT to CO, expressed by changes in the PetCO2. This study
also focused on describing the effect of PIT on PetCO2.
Finally both the “cardiac” and “thoracic pump model” were combined to quantify and predict
the PetCO2 changes present in single patients suffering from cardiac arrest. Optimizing both
“the thoracic pump”, by augmentation of ΔCP, and “the cardiac pump”, by altering
compression rate and depth, may lead to an increase in PetCO2 in certain patients suffering
6
from cardiac arrest. In this study we tried to ascertain the influence of both mechanisms on
PetCO2.
7
Materials and methods
1. Study design
A single centre observational study was conducted in patients suffering from OHCA between
October 2010 and April 2011. The study population was the municipality of Ghent including
its eastern suburbs, with a population of approximately 150 000 inhabitants. Initial basic life
support (BLS) for OHCA was provided by Emergency Medical Technicians with defibrillator
training (EMT-D). Advanced (cardiac) life support (ACLS) was provided by the Mobile
Intensive Care Unit (MICU) of Ghent University Hospital (GUH). This MICU was manned
by an EMT-D, a nurse specialized in emergency medicine and a physician, training for or
certified in the specialty of emergency medicine, anaesthesiology or internal medicine.
Physicians, paramedics and nurses staffing the MICU were informed about the study protocol.
Patients resuscitated before December 2010 received ALS according to the European
Resuscitation Council (ERC) 2005 guidelines (Nolan et al., 2005), afterwards the ERC 2010
guidelines were used (Deakin et al., 2010).
2. Patient selection
All patients suffering from OHCA resuscitated by the MICU of the GUH older than 18 years
between 22nd October and 15th April were eligible. Approval of this study was given by the
Ethics Committee of the Ghent University Hospital, under conditions for deferred informed
consent. In case of ROSC and transfer to a hospital, a family member was asked to give
informed consent. ROSC was defined as the return of a palpable pulse at any given time. The
decision to stop resuscitation efforts was solely the responsibility of the treating physician.
3. Materials
On arrival of the MICU patients were monitored and, when indicated, defibrillated with a
manual Zoll E Series defibrillator (Zoll Medical Company, Chelmsford, USA) (Figure 1 left). ECG data were obtained in all patients. CPR D-padz (Zoll Medical Company,
Chelmsford, USA) were applied on the patient’s chest according to the manufacturer’s
instructions. These pads included an accelerometer, which was placed between the rescuer’s
hand and the patient’s sternum (Figure 1 - right). This device measured compression depth
and rate. Using these data, the defibrillator provided the rescuers with real-time visual and
8
audible feedback of compression quality. All defibrillator data were stored on an external
memory card (Linear flash 32 Mb memory card, Zoll Medical Company, Chelmsford, USA).
Figure 1: Left: The Zoll E Series defibrillator. Right: CPR D-Padz, consisting out of two defibrillator pads, an
accelerometer and the connector to the defibrillator
After endotracheal intubation (Hi-Contour Tracheal Tube, Mallinckrodt Medical, Athlone,
Ireland), patients were manually ventilated using an adult size, self-refilling ventilation bag
(Laerdal Silicone Resuscitation Adult, Laerdal Medical, Stavanger, Norway). After
confirmation of correct tube placement, mechanical or manual ventilation was performed at
the discretion of the physician. On March 4th, a change was made in hospital guidelines,
urging physicians to switch to mechanical ventilation as soon as possible. Patients were
mechanically ventilated using an Oxylog 3000 ventilator (Dräger Medical GmbH, Lübeck,
Germany). Based on the ERC 2010 guidelines (Koster et al., 2010), the ventilator was set as
follows: tidal volume of 6 to 7 ml per kilo, PEEP of 0 millimeters of water (mm H2O) (1 mm
H2O = 10 Pa), ventilatory rate of 10 per minute and inspiratory oxygen fraction of 100 %. An
oxygen saturation of 94 to 98 % was aimed at after obtaining ROSC. By making its value
independent of ventilatory parameters, the PetCO2 better reflected the efficiency of
resuscitation efforts.
A swivel and pediatric filter (Hygrobac, Mallinckrodt Medical, Athlone, Ireland) were
attached to the endotracheal tube. A portable infrared mainstream PetCO2 sensor (Capnostat 5,
Zoll Medical Company, Chelmsford, USA) was attached to this filter, i.e. between the
ventilation bag or the ventilation tubes of the Oxylog 3000 ventilator and the filter (Figure 2 left). This capnograph worked on the principle of non-dispersed infrared absorption with
dual-wavelength single-beam optics. It was calibrated and zeroed daily according to the
manufacturer’s instructions. After connection to the defibrillator, it allowed real-time
quantitative measurements of the PetCO2. PetCO2 was expressed in millimeters mercury (mm
Hg) (1 mm Hg = 133 Pa). Digital PetCO2 reading, ventilatory rate and capnograph waveforms
9
were visualized real-time on the defibrillator’s screen and stored on the external memory card
(Figure 2 - right). During the resuscitation this information was always available to the
treating resuscitation team.
Figure 2: Left: PetCO2 sensor Right: The screen of the Zoll E Series defibrillator showing the PetCO2,
capnograph waveform and respiratory rate
A self-developed pressure measurement system was used to ascertain intrathoracic pressures,
making use of a disposable extension piece connected to pressure sensors. This extension
piece consisted of a coupling piece which was directly attached to the endotracheal tube,
positioned before the filter, the PetCO2 sensor and the tubes of the mechanical ventilator.
Furthermore it consisted of two small tubes (length : 150 cm, diameter : 1,5 mm) (Extension
Line, Ciam Laboratories, Sallanches, France). One small tube was connected by a luer-lock
mechanism to the coupling piece on one end and an external device on the other end. The
second small tube was passed through the ETT on one end and connected to the same external
device on the other end. Consequently the first small tube was positioned at the proximal end
of the ETT, providing superficial pressure measurements, and the second small tube was
positioned at the distal end of the ETT, providing deep pressure measurements (Figure 3 left). For the purpose of this study, only the deep pressure measurements were used. The
external device contained two pressure sensors, two Wheatstone bridge amplifiers (Type
132B Sensor Amplifier, Datum Electronics, Isle of Wight, UK) and a pressure logger
(MSR145, MSR Electronics GmbH, Henggart, Switzerland) to digitize and record the
enhanced pressure data. A sturdy case enfolded the pressure sensors, amplifiers and the
logger. This device had an on/off switch, two luer-lock connection ports for the small tubes
and a USB2 port, to download the data on a personal computer (Figure 3 - right). During
resuscitation, pressure data were not visible to the treating physician. Disposables were not
reused. They were examined by an independent observer for potential clogging of the small
tubes with secretions or blood, prohibiting an adequate pressure measurement. Two pressure
10
loggers were present, one being used by the resuscitation team. The other was stored at the
emergency department, for use in case of technical malfunctioning. The logger was reset after
downloading the data.
Applying the disposable and PetCO2 sensor did not delay the resuscitation efforts and had no
adverse effect on the outcome of the patient. Resuscitated patients without either pressure
measurements or PetCO2 were excluded from the study. Other exclusion criteria are listed in
Table 1.
Figure 3: Left: The self-developed system to measure intratracheal pressures. It consists of a small tube
positioned in the endotracheal tube, another small tube connected to the connecting piece, swivel and filter. This
figure also shows the position of the PetCO2 sensor. Right: The external device, containing the pressure sensors,
amplifier and pressure logger, enfolded by a sturdy case.
4. Data processing
After each resuscitation, the data on the memory card of the defibrillator was downloaded and
reviewed in RescueNet Code Review (Zoll Medical Company, Chelmsford, USA) (Figure 4 left). Patients without PetCO2 were excluded from the study (Table 1). The initial rhythm and
post-resuscitation rhythm in case of ROSC were assessed. The defibrillator data were sampled
at 250 Hz (250 samples per second) and converted to an exportable text format (.txt).
The data on the pressure logger was transferred to a portable computer by USB connection
and reviewed in MSR Viewer 5.12 (MSR Electronics GmbH, Henggart, Switzerland) (figure
4 - right). Patients without deep pressure measurement or damped pressure waveforms during
resuscitation due to clogging of the small tubes were excluded. Additionally, patients who did
not have a minimum of one minute of resuscitation with both pressure data and PetCO2
available were excluded from the study (Table 1). The pressure data were sampled at 50 Hz
(50 samples per second) and converted to comma separated value format (.csv).
11
Figure 4: Left: A screenshot from the RescueNet Code review software showing a resuscitation trace with the
capnograph waveform, PetCO2, the respiratory rate, compression depth and rate. Right: A screenshot showing
the MSR Viewer software visualizing the pressure waveforms. The green waveforms correspond with the
superficial pressure measurements and the black waveforms with the deep pressure measurements.
Both text formats were imported in a Microsoft Excel (Microsoft Corporation, Redmond,
USA) spreadsheet using a self-developed macro, written in Microsoft Visual Basic for
Applications. To find an exact time match of pressure data and compression data, a “three
point approach” was used. These points were “transition points”, signalling the transition
from a period of chest compressions to a period of rest or vice versa. The pressure waveforms
between two of these transit points formed a “pressure profile”. A similar “compression
profile” could be found in the Zoll data. The time difference between these two profiles was
noted and an adjustment was made, matching both profiles. This process was repeated for two
other transition points. The course of the resuscitation was then reviewed per thirty seconds
perfectly matching the compression data and the corresponding pressure waveforms.
Each patient had a separate spreadsheet and was analysed individually. Utilizing the
technology of Visual Basic for Applications, several parameters were calculated per patient.
For each compression, the following parameters were obtained: compression depth (CD),
isolated distal and proximal peak pressure and the isolated ventilation pressure. Furthermore a
subtraction was made between the distal peak pressure (Ppeak) and ventilation pressure (Pvent).
We called this value the “delta compression pressure” or DeltaCP (ΔCP). We also calculated
the area under the curve (AUC) of the compressions in the pressure waveforms (AUCc) and
the AUC of the total pressure waveform. This variable corresponded with the average
intrathoracic pressure (PIP). For each variable, a mean, median and summation for a time
interval of 5, 10, 15 and 20 seconds were derived for every PetCO2. Additionally the number
of compressions given during these time intervals was calculated.
12
35
60
30
50
25
40
20
30
15
20
10
10
5
0
10:24:08
0
10:24:13
10:24:18
Figure 5: Imported pressure and compression data in MS Excel document. The capnograph waveform are blue
with the PetCO2 of a ventilation marked with a thick dark blue line. Compression depths are marked with small
black lines. The deep pressure waveform is coloured red with the grey areas defined as the area under the curve
of the compression peaks. The yellow arrow illustrates intrathoracic pressure difference or ΔCP.
Table 1: Exclusion criteria

Patients manually ventilated

Patients who did not have any PetCO2, due to sensor malfunctioning or nonapplication of the PetCO2 sensor

Patients who did not have any pressure measurement (either deep pressure
measurements of no pressure measurements at all) due to non-application of the
disposable, sensor malfunctioning, clogging of the small tubes or not activating the
logger

Patients with less than one minute of both PetCO2 and pressure measurements
available before obtaining ROSC
Figure 6: Imported pressure data in MS Excel document, illustrating total intrathoracic pressure (PIP).
13
5. Statistical analysis
Statistical analysis was performed using PASW Statistics 18.0 (IBM, New York, USA). The
null hypothesis was considered to be rejected at a two-tailed alpha rate of 0.05 or less.
Population statistics were expressed as mean ± standard deviation (SD). Comparison between
the included and excluded patient groups was performed using the Mann-Whitney test for
continuous variables and Chi square test for categorical variables.
Patients were analysed individually. A simple linear regression was used to study the
relationship between each parameter and the corresponding PetCO2 during a time interval of 5,
10, 15 and 20 seconds. An individual patient model was made using a univariate analysis with
PetCO2 as the dependent variable. The proportion of variance in PetCO2 by a variable was
expressed as the partial eta-squared coefficient (partial η² or Pη²). A variable with a partial
eta-squared less than 0.01 and/or not statistically significant P-value was not further included
in the patient model. This resulted in a statistical model per patient, which optimally described
the individual set of parameters that could quantitatively predict changes in PetCO2.
14
Results
1. Patient population
From 22nd of October to 15th of April 51 patients suffering from OHCA were resuscitated by
the MICU of the GUH. 23/51 patients (47%) were excluded from the study. 27/51 (53%)
patients were included for further analysis. Patients’ characteristics of both groups are
summarised in Table 2.
Table 2 : Patients’ characteristics
Included patients
Excluded patients
27 (53%)
24 (47%)
60 (18)
62 (17)
Male
22 (82%)
21 (88%)
Female
5 (18%)
5 (12%)
Yes
10 (37%)
12 (50%)
No
17 (63%)
15 (50%)
Asystole
21 (78%)
17 (71%)
VF/VT
3 (11%)
2 (8%)
PEA
3 (11%)
5 (21%)
Sinus rhythm
7 (70%)
5 (42%)
Paced rhythm
0 (0%)
2 (17%)
AF
3 (30%)
2 (17%)
VT
0 (0%)
3 (25%)
Number of patients
Age (years)
P
0.75
Sex (n)
0.56
ROSC (n)
0.35
Initial rhythm (n)
0.62
Rhythm if ROSC (n)
0.15
SD = standard deviation; ROSC = return of spontaneous circulation; VF = ventricular fibrillation;
VT = ventricular tachycardia; PEA/EMD = pulseless electrical activity; AF = atrial fibrillation
There were no significant differences between both groups regarding demographic data.
2. Univariate analysis
A simple linear regression analysis was made for each set of parameters of each individual
patient. This demonstrated that both the median and summation of all parameters, made
15
during a time interval of 20 seconds before each ventilation, had superior R² values, with a
corresponding statistically significant P-value, when compared with a time interval of either
5, 10 or 15 seconds.
Table 3 shows the descriptive statistics for all variables in the entire included patient
population.
Table 3: Descriptive statistics of measured variables of included patients (n = 27)
PetCO2
CD
ΔCP
PIP
Ppeak
Pvent
#C
AUCc
Dur
Mean
23
5.3
23
8
35
13
23
507
393
Median
21
5.1
22
9
34
16
23
502
302
SD
12
1.0
7
6
8
5
9
142
335
Min
4
3.0
3
0.02
16
-8
1
103
51
Max
71
8.9
46
21
68
29
54
1198
1634
All variables were measured 20 seconds before each ventilation; for CD, ΔCP, Ppeak, Pvent and AUCc median
values were calculated during this time interval
PetCO2= end-tidal CO2 tension (in mm Hg); CD = compression depth (in cm); ΔCP = intrathoracic pressure
difference (in mm H2O); PIP = average intrathoracic pressure (in mm H2O); Ppeak = peak pressure (in mm H2O);
Pvent = ventilatory pressure (in mm H2O); #C = number of compressions given; AUCc = area under the curve of
the compression peaks; Dur = duration of the resuscitation (in seconds); SD = standard deviation; Min =
minimum; Max = maximum
In total there were 3457 CO2 measurements. The mean PetCO2 was 23 mmHg (± 12mmHg).
The mean duration of CPR was 393 seconds (± 335 seconds).
A univariate model per patient was developed to explain changes in PetCO2 quantitatively. We
aimed at a “tolerance level” lower than one and a “variation inflation factor” less than three
for all used variables, thus avoiding multicollinearity between the used variables. The
variables used in each patient model were measured in a time interval of 20 seconds before
each ventilation. Table 4 shows these individual univariate models.
16
Table 4: Patients’ individual model using univariate analysis
Patient ID
Pη² model°
ΔCP
B
1
22102010
<0.001
2
24102010
0.475
3
30102010
0.203
4
28112010
0.129
5
06122010
0.383
0.16
6
08122010a
0.513
7
08122010b
8
CD
Pη²
B
ΣPvent
PIP
Pη²
B
Pη²
B
AUCc
Pη²
B
#C
Pη²
B
Category
Pη²
N
0.29
0.10
1.35
0.12
0.013
0.004
-1.75
0.10
0.02
11.81
0.24
-0.023
<0.01
5.11
0.45
0.451
-0.096
0.06
1.33
0.25
08122010c
0.304
-0.26
0.05
9
25122010
0.289
10
31122010
0.692
11
25012011
0.205
0.29
12
04022011
0.364
0.74
13
10202011
14
0.21
C,T
-0.39
-0.004
-0.002
0.10
0.13
0.05
C
N
0.29
0.47
0.11
C
C
0.029
0.001
-0.001
0.18
2.79
0.28
0.07
-2.78
0.12
<0.01
0.91
0.33
0.41
0.09
0.523
2.23
0.15
-0.001
0.20
19022011
0.122
0.81
0.12
15
24022011
0.315
0.14
0.02
16
25022011
0.648
0.067
0.04
1.34
0.56
17
27022011
0.324
0.44
0.03
6.21
0.30
-0.035
0.27
0.16
0.062
C
N
0.041
0.29
C,T
-0.001
0.23
C,T
-0.10
0.03
C
0.38
0.014
0.07
0.018
0.06
0.29
C
C,T
C
-0.22
0.05
0.00033
0.19
0.297
0.10
0.45
0.14
C,T
C
-0.010
0.03
C
17
Patient ID
Pη² model°
ΔCP
B
CD
Pη²
18
28022011
0.514
19
11032011
0.237
0.29
0,14
20
18032011
0.140
0.25
0,15
21
21032011
0.239
1.9
0,28
22
28032011
0.597
23
29032011
<0.001
24
02042011
0.562
25
05042011a
0.366
-0.072
0,05
26
05042011b
0.584
-0.94
0,34
27
14042011
0.351
B
Pη²
3.18
0.35
5.95
ΣPvent
PIP
B
Pη²
AUCc
#C
Category
B
Pη²
B
Pη²
0.049
0.37
0.008
0.02
C
-0.004
<0.01
-0.019
0.21
C,T
B
Pη²
0.15
C,T
T
3.53
0.12
-0.002
0.26
-0.046
0.36
0.74
0.52
C
N
-14.21
0.32
-7.79
0.34
-0.002
0.18
1.88
0.29
0.001
0.16
-0.24
0.21
-0.072
0.02
-0.025
0.18
C
0.038
0.13
1.16
0.16
C,T
C,T
C
All variables were measured in a time interval of 20 seconds before each ventilation; for CD, ΔCP, Ppeak, Pvent and AUCc median values were calculated during this time interval
PetCO2 was the dependent variable in all patients
° All patients models, with the exception of patients 1 and 23, had an P < 0,001
Pη² = partial eta-squared coefficient; B = estimate of the parameter; ΔCP = median intrathoracic pressure difference (in mmH 2O); CD = median compression depth (in cm); PIP = average
intrathoracic pressure (in mm H2O); ΣPvent = sum of ventilation pressures (in mm H2O); AUCc = median area under the curve of compression peaks; #C = the number of compression
given
Category = categorisation of the pump mechanism; N = no discernable pump mechanism; C = cardiac pump mechanism; T = thoracic pump mechanism; C,T = both a cardiac and thoracic
pump mechanism
18
In two (7%) out of 27 included patients, we were not able to fit a model to explain changes in
PetCO2. The partial eta-squared for all other patients ranged from 0.122 to 0.692 with
corresponding P-values lower than 0.001. A categorisation was made of the patients
according to the parameters used in each patient’s model to describe changes in PetCO2:

Average intrathoracic pressure and sum of ventilation pressures were considered as
neutral variables. According to our hypothesis, we stated that excessive intrathoracic
pressure (either by increased PIP directly or indirectly by increasing the Pvent)
correlated with a decreased CO, due to inhibition of venous return. When venous
return is inhibited, neither pump mechanism will function properly.

A patient wherein compression depth and/or number of compression explained the
greatest fraction of PetCO2 variation, was considered using a “‘cardiac pump
mechanism” to generate flow during resuscitation

A patient wherein intrathoracic pressure difference explained the greatest fraction of
PetCO2variation, was considered using a “thoracic pump mechanism” to generate flow
during resuscitation

A patient that used a combination of both categories mentioned above, or wherein area
under the curve of the compression peaks explained the greatest fraction of PetCO2
variation, was considered to use a combined “cardiac and thoracic pump mechanism”.
In 9/27 (33%) patients compression depth and/or rate were the discriminating factors
determining increase in PetCO2. In 4/27 (15%) patients there existed a negative relationship
between these parameters and PetCO2. Only in one (4%) patient ΔCP was the only parameter
explaining changes in PetCO2. For the other nine (33%) patients, a combination of
compression parameters and of the intrathoracic pressure difference and/or the area under the
curve of the compression peaks were the discriminating factors responsible for changes in
PetCO2. Although all patients received precordial compressions and intermittent ventilations,
the first group was categorized as using a “cardiac pump mechanism”, the second as a
“thoracic pump mechanism” and the third group as a combined “cardiac and thoracic pump
mechanism”.
In 18/27 (67%) patients compression depth was the most important factor to explain changes
in PetCO2. Four of these 18 patients showed a negative correlation between compression depth
and PetCO2, leading to a decrease of this value from 2 to 14 mm Hg when compression depth
was increased with one centimetre. These four patients also showed a negative association
19
between Pvent and/or PIP and PetCO2, indicating that in increased depth may be associated with
an increased intrathoracic pressure, inhibiting venous return. An increase of one centimetre
depth in the remaining 14 patients would increase PetCO2 from 1 to 12 mmHg. While only one
quarter of all patients incorporated the number of compression in a 20 seconds time interval
before each ventilation into their unique patient model, this parameter showed great influence
when predicting PetCO2. In six of these patients, an increase of ten compressions in a twenty
second time interval increased PetCO2 from 1 to 12 mmHg. Only one of these patient showed
a negative association between the number of compressions and PetCO2.
In fifteen (56%) patients, a relationship existed between PetCO2 and ΔCP. In only 1/15
patients the intrathoracic pressure difference was the parameter solely explaining changes in
PetCO2. ΔCP together with other pressure and compression related parameters explained
changes in PetCO2 in the remaining 14/15 patients. These patients were therefore classified
using a combined “cardiac and thoracic pump mechanism” to explain changes in PetCO2. In
10/15 patients the intrathoracic pressure difference was positively correlated with PetCO2,
meaning that an increase in ΔCP of 10 mmH2O in this patient group would lead to an increase
of PetCO2 of 1 to 19 mmHg. The 5/15 remaining patients demonstrated a negative association
between ΔCP and PetCO2. An increase of ΔCP of 10 mmH2O would decrease PetCO2 from 0
to 9 mmHg.
These same five patients also exhibited a negative association between average intrathoracic
pressure and/or sum of ventilation pressure, meaning that an increased intrathoracic pressure
resulted in a decrease in PetCO2. In eight other patients, showing a correlation between ΔCP
and PetCO2, a similar relationship between these neutral pressure variables and PetCO2 was
found. This resulted in a total of 13/27 (48%) patients who had a negative association between
PIP or Pvent and PetCO2. An increased Pvent was associated with lower PetCO2 in the majority of
patients who integrated this variable in their respective models. On the contrary an increased
PIP was only associated with lower PetCO2 in 6 out of 11 patients who had this variable built
into their model.
20
Discussion
To our knowledge, this is the first study that combined information from both cardiac
compressions and intrathoracic pressures to study their relationship with PetCO2 in patients
suffering from out-of-hospital cardiac arrest. Several other studies (Schultz et al., 1994;
Aufderheide et al., 2004; Yannopoulos et al., 2005) have measured intrathoracic pressures in
an experimental resuscitation setting, but this is the first attempt to combine these data in a
pre-hospital resuscitation setting.
In our study all resuscitated patients received precordial chest compressions and ventilations
according to standard resuscitation guidelines (Deakin et al., 2010). It has been demonstrated
both in animals (Marn-Pernat et al, 2001; Berg et al., 2001) and human studies (KramerJohansen, 2006) that cardiac compression are the determining factor for high-quality CPR.
Even small pauses in compressions can significantly decrease coronary perfusion pressure
(Berg et al., 2001). Our analysis demonstrated that in most patients the primary mechanism
for generating blood flow during CPR are these chest compressions. Though current CPR
guidelines advise a compression depth of at least 5 cm, our analysis demonstrated that a
compression depth of even 7 and 8 cm can significantly raise PetCO2 in some cardiac arrest
patients. This increased PetCO2 associated with a higher cardiac output (Jin et al., 2000) and
coronary perfusion pressure (Von Planta et al., 1989), which are both associated with a higher
likelihood of gaining ROSC (Grmec et al., 2011; Reynolds et al., 2010). We also showed that
the number of compressions in a time interval of twenty seconds before each CO2
measurement is an important factor in explaining changes in PetCO2. Seven patients have
incorporated this parameter in their respective models. A increase of rate with 10/minute can
lead to an increase of up to 10 mmHg in PetCO2, emphasizing the importance of a
compression rate of at least 100/minute as recommended by the current CPR guidelines
(Koster et al., 2010). Similar observations have been found in animal models where a higher
mean compression rate is associated with a higher cardiac output (Maier et al., 1984) and
coronary perfusion pressure (Feneley et al., 1988), both characterised by an increased PetCO2.
This could explain the increased PetCO2 in several patients in our research population when
compression rate would be augmented.
In numerous studies evidence has been provided proving the existence of “a thoracic pump
mechanism” (Criley et al., 1976; Werner et al., 1981; Rich et al., 1981). Besides the direct
21
cardiac compression, intrathoracic pressure differences could also be responsible for the
promulgation of blood during CPR. We introduced a new parameter to describe these
intrathoracic pressure differences. During a ventilatory cycle a ventilatory pressure is
generated. The compressions given during this cycle, are superimposed on this ventilatory
pressure waveform, creating discrete peak pressures. The difference between the peak
pressure and ventilatory pressure was defined as the intrathoracic pressure difference, ΔCP or
Delta compression pressure. It is the first time such a parameter has been used to directly
quantify the intrathoracic pressure differences. While we believe that blood flow during
resuscitation is probably generated by a combination of both cardiac compressions and
intrathoracic pressure differences, only nine patients in our study group demonstrated such a
combination. A probable explanation is the way out-of-hospital cardiac arrest patients are
currently ventilated. Patients are intubated and ventilated using a semi-closed airway circuit.
Other airway circuits should be explored to fully access the potential of this “thoracic pump
mechanism”. For example the endotracheal tube could be clamped during precordial
compressions and declamped during the intermittent ventilations. Another possibility to fully
access the “thoracic pump mechanism” is the titration of PEEP. Lastly the build-up of
ventilatory pressure could be altered, by not only changing ventilator setting but also by
exploring high-frequency jet ventilation and continuous positive airway pressure ventilation
during resuscitation. This will lead to a different ventilatory pressure waveform.
The intratracheal pressure sensors also made it possible to ascertain the average intrathoracic
pressure during the resuscitation. In several of our patients excessive intrathoracic pressure
was associated with significantly lower PetCO2. During the decompression phase, each time
the chest returns back to its neutral state, a small relative negative pressure is generated in the
thoracic cavity. This draws venous blood back to the right atrium. This negative pressure is
relative to the rest of the body. An excessive intrathoracic pressure inhibits the creation of this
negative pressure and thus inhibits the return of venous blood to the right atrium. It
subsequently decreases pulmonary circulation and PetCO2. It has been previously
demonstrated by other research groups in animal models that overzealous ventilation and
incomplete chest wall recoil can lead to increased intrathoracic pressures (Aufderheide et al.,
2004; Aufderheide et al. 2005), both resulting in a significantly lower PetCO2, coronary
perfusion pressure and cardiac output. Other studies showed a beneficial effect of an
intrathoracic pressure regulator, augmenting the negative pressure vacuum during the
decompression phase, during resuscitation of OHCA patients. It increased chances for
22
obtaining ROSC and admittance to the Intensive Care Unit (Aufderheide et al., 2005).
Increased negative intrathoracic pressures during resuscitation could also augment the
intrathoracic pressure difference, not only creating more venous return, but also driving more
blood forward. Though their study could not demonstrate causes of increased intrathoracic
pressures, it did show its negative effect on PetCO2, correlating with decreased cardiac output,
pulmonary circulation and coronary perfusion pressure.
Our study had several limitations. First and foremost its study design. We used simple and
multiple linear regression, thus making the assumption that all used parameters had an
adequate range to analyse. In several patients the range of ΔCP and compression depth was
limited, mostly due to a short resuscitation time before obtaining ROSC. Compression depth
was also limited due to the use of ERC 2010 guidelines, advising a compression depth of at
least 5 cm in the new 2010 guidelines (Deakin et al., 2010) and a compression depth ranging
from 4 to 5 cm in the ERC 2005 guidelines (Nolan et al., 2005). This study encompasses
patients resuscitated according to both guidelines. The use of these guidelines limits the range
of available compression depths, making it sometimes difficult to relate depth to PetCO2.
Though neither patients groups were excluded, it was not always possible to fully ascertain
the pump mechanism(s) responsible for generating cardiac output in these patients. Our
current patient group showed great heterogeneity both in compression data, pressure variables
and PetCO2. The impossibility to create a generalised model to describe PetCO2 changes in the
entire patient population illustrates this heterogeneity and highlights the individual aspects of
each patient.
Another limitation is found in the methodology used to analyse the patients. All used
variables were considered to be independent, while in fact they are not. ΔCP was defined in
this study as the difference between Ppeak and Pvent, rendering this variable automatically
dependent of the other two. The peak pressure and area under the curve of the compression
peaks are dependent of depth and rate of compressions. Lastly the average intrathoracic
pressure is in fact a summation of all possible factors capable of changing the total pressure in
the thoracic cavity: compression depth and rate, ventilation pressure and peak pressure.
Neither of these intervariable dependencies are taken into account when the individual patient
models were created.
The majority of included patients presented with asystole or pulseless electrical activity. Only
five patients (10%) presented with VT/VF in the total patient population. In the included
23
group three patients (11%) presented with VF/VT. Though the incidence of patients
presenting with VF during OHCA is declining, current literature states that 20 to 40 % of
patients with OHCA will present with ventricular fibrillation (Cobb et al., 2002; Herlitz et al.,
2004). These numbers prompt the possibility that the patient models presented is this study
may primarily apply to patients presenting with asystole or PEA.
This study was set up as a pilot project, testing for the first the time the combination of
intratracheal pressure sensors and PetCO2 monitoring in a out-of-hospital resuscitation setting.
Especially during the initial phase of the study, we encountered several technical difficulties
with the PetCO2 sensor, pressure transducers and/or the Oxylog 3000 ventilator. Consequently
only 53% of patients suffering from OHCA were included in this study. We had no previous
experience with the PetCO2 sensor in our emergency department prior to the start of this study.
Several episodes of technical malfunctioning of the PetCO2 sensor led to the exclusion of five
patients during the months of February and April (5/51, 10%). The pressure transducers were
omitted or applied only after obtaining ROSC in several resuscitations (10/51, 20%). Another
recurring problem is the clogging of the small tube of the pressure sensors, placed in the
endotracheal tube, due to bloody or mucous secretions (3/51, 6%). During the development of
the pressure measurement apparatus, both a different internal diameter and different method
for cutting off the ends of the small tube were tried. Unfortunately a solution has yet to be
found. Difficult ventilation in patients was another problem. During this study an Oxylog
3000 ventilator with intermittent positive pressure ventilation was used. When encountering a
patients with severe airway disease or airway obstruction, the airway pressure spiked and the
ventilator automatically provided an oscillatory airflow pattern, producing rapid changes of
airway pressures. This airflow pattern generated a jerky inspiratory pattern with very high
airway pressures. A bench study confirmed these observations (Frank et al., 2005). It made
the analysis of the corresponding pressure waveform practically impossible, leading to patient
exclusion (2/51, 4%).
Patients who were exclusively manually ventilated were excluded from the study. The minute
volume and ventilator frequency during manual ventilation changes constantly, generating a
different and unpredictable pressure waveform compared to mechanical ventilation. It has
been demonstrated that PetCO2 in situations of low flow is limited by the cardiac output and
not by ventilatory changes (Blumenthal and Voorhees, 1997; Jin et al., 2000). A porcine
model also showed that diminishing the minute volume with 50% will not alter the PetCO2 nor
the PaCO2 in resuscitated pigs (Winkler et al., 1998). Despite these two observations, we
24
opted to omit these patients for further analysis to avoid any possible alterations in PetCO2 due
to changes in ventilatory pattern.
25
Perspectives for further research
This study demonstrated that most patients used “a cardiac pump mechanism” to generate
flow during resuscitation. We demonstrated a relationship between an increase in
compression depth and PetCO2. The next phase to unravel the exact influence of cardiac
compression on cardiac output should be approached in a prospective manner. Using a
mechanical thumper or the voice feedback provided by the accelerometer, a series of fixed
compressions depths (e.g. 5 cm, 6 cm and 7 cm) should be sustained during a fixed period of
time in patients suffering from OHCA, who are intubated after application of the PetCO2
sensor and pressure sensors. This way the correct impact of deeper compressions on PetCO2
and intrathoracic pressure differences can be ascertained. It will be possible to look for the
impact of patient’s characteristics on the optimal compression depth. This could be a first step
in creating a ‘patient individual’ resuscitation.
This study also demonstrated that, although “a thoracic pump” is probably present in all
patients, only a minority of patients accessed this mechanism to amplify the cardiac output
during their resuscitation. The pressure differences in the chest were currently obtained using
different ventilatory settings. PEEP, tidal volume and respiratory frequency were different for
every patient and sometimes even during the resuscitation of a single patient. To further
ascertain the effect of intrathoracic pressure changes on circulation, these parameters should
be investigated in a prospective study. While holding all other ventilatory parameters
constant, changes in minute volume, inspiratory/expiratory time, ventilatory frequency, PEEP
or a combination of these parameters could be made. These changes will reflect themselves in
changes in the pressure waveform, altering intrathoracic pressure differences. By using
PetCO2, it would be possible to link these pressure differences to changes in cardiac output.
By changing the ventilatory parameters and coupling them to patients’ characteristics, it will
be possible to ascertain ‘patient-individual’ ventilatory parameters which are necessary to
obtain a maximised cardiac output in a specific patient.
While both superficial and deep pressure measurements were made, at present only deep
measurements are used in the analysis. The pressure difference between both measurements
makes it possible to calculate and visualize the direction of air flow and calculate the tidal
volume given during each ventilation without the need to use other equipment. This could
give the treating physician a real-life image of air movement during the resuscitation.
26
Currently the PetCO2 probe and the accelerometer are coupled to the defibrillator. The
pressure sensors, amplifiers and logger are connected to a separate external device without a
display. The treating physician had no visible access to the pressure data during the
resuscitation. Research should focus on making this pressure device more portable and usable
by means of a monitor and an application to make prospective research possible. Ideally, both
the accelerometer, PetCO2 sensor and the pressure sensors should be integrated in one device,
integrating the information of both separate devices. This device could include a monitor
visualizing both compression and pressure data and to be used at the treating physician’s
discretion.
Eventually the compression data, the pressure data, corresponding PetCO2 and patient
characteristics can be integrated in ‘a smart resuscitation system’. This automated system
could be programmed to perform resuscitation according to current guidelines or to fully
optimize both pump mechanisms in order to obtain a maximum cardiac output, reflected by a
maximized PetCO2. It could be programmed to use a ‘trial and error’ method, trying different
compression and ventilator setting, to optimize cardiac output. The responsibility for the
entire resuscitation process lies of course with the treating physician, whereas the ‘smart
resuscitation system’ is used to support the resuscitation process.
27
Conclusion
We developed a method to differentiate the effect of both the “cardiac” and “thoracic pump
mechanism”. Most patient made use of a “cardiac pump mechanism” to generate flow during
resuscitation. Only a minority of patients accessed a “thoracic pump mechanism” to further
optimize PetCO2. We believe nonetheless that both mechanisms can be used in all patients,
under appropriate circumstances. We also demonstrated that while negative intrathoracic
pressure negatively affects PetCO2, a moderately increased intrathoracic pressure showed a
beneficial effect on PetCO2.
28
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Acknowledgements
We are grateful to Prof Dr K Monsieurs for the guidance, support and helpful tips writing this
paper, to Charlotte Vankeirsbilck for the administrative support and the introduction in the
miraculous world of MSR, Zoll and Lazarus, to Dr S Lemoyne for the help with the
interpretation of the results and hints for further data processing and to Alain Kalmar for
writing the Visual Basic macro and helping with the interpretation of the results. Also to Lien
Yde for the mental support and the numerous days spent in a small windowless office. Last
but not least a big thank you for all the physicians, EMTs, nurses and administrative
personnel of the Emergency Department of the Ghent University Hospital for the data
collecting during every resuscitation.
34