10:40   Cardiovascular 1: In-vivo Monitoring
Chair: Chris de Korte
15 mins
Sjoerd Niehof, Ernst Smits, Tim Nijhuis, Steven Hovius, Henk Stam, Ruud Selles
Abstract: Introduction Cold intolerance frequently occurs after a hand trauma, most probably due to secondary peripheral nerve injury cause by the trauma. Cold intolerance is defined as an abnormal cold pain sensation after exposure to mild or severe cold. While the pathophysiology of cold intolerance is unknown, it is often assumed patients with cold intolerance have a disrupted thermoregulation of the hands and therefore are unable to compensate for a cold environment. To evaluate this, we cooled the hands of digital fracture patients with and without complaints of cold intolerance in cold water and measured the rewarming patterns with videothermography. Methods Thirteen control subjects and eighteen hand fracture patients participated in this study. Both hands were immersed for 90 seconds in water of 13°C. Rewarming at room temperature was registered with a computer-assisted infrared thermograph (ThermaCAM SC2000) with a frame rate of 1 per second. Mean temperature readings of the fingertips were exported to matlab for further analysis. The start and stop of active (due to vasodilatation) re-warming for each finger was determined based on the second derivative of temperature in time. The total amount of heat (Q) added to the digits was calculated as the area under the temperature curve. In addition, the average re-warming per second (Q/s) was calculated for each finger. Results Nine fracture patients (50%) had abnormal cold intolerance based on the Cold Intolerance Severity Scale. The rewarming duration of the involved fingers (312 seconds) was not significantly different from the non-involved fingers (323 seconds). We found a decreased or absent active rewarming in one or more fingers in in 3 of the controls (23%) and 6 of the patients (33%. We found no significant difference between the Q-values of the involved and non-involved hands in the patients and between patients and controls. Similarly, we found no significant differences in Q/s between involved and uninvolved hand of the patients or between patients and controls. Conclusion The pathophysiology of post-traumatic cold intolerance is unknown, although it is often assumed to be related to a disturbed thermoregulation of the hands. However, this has only been studied in nerve injury patients, where indeed abnormal rewarming was found [1]. In this study, we found no abnormal rewarming in the hands of hand fracture patients, despite the high incidence of cold intolerance in these patients (50%). This finding indicates that cold intolerance may not be the result of abnormal thermoregulation in these patients, which may give important insight into the treatment options for cold intolerance in these patients and suggest that there is an alternative cause for cold intolerance.
15 mins
Anne van der Eijk, Jenny Dankelman, Sander Schutte, Bert Smit, Huib Simonsz
Abstract: Background: Worldwide, approximately 8% of the babies is born before 37 weeks of pregnancy. Due to underdevelopment of the lungs, these preterm infants need supplemental oxygen therapy to survive. To prevent negative side-effects due to excessive blood oxygen levels, the oxygen saturation of the arterial blood (SaO2) and the partial pressure of arterial oxygen (PaO2) need to be monitored closely. The SaO2 and the PaO2 are related by the “Oxygen Dissociation-curve” (OD-curve). The OD-curve is not fixed, but shifts horizontally under influence of e.g. the presence of fetal haemoglobin (HbF), pH, and temperature (Bohr-effect). As monitoring the PaO2 is difficult and labour intensive, in clinical practice only the SaO2 is monitored continuously. To maintain the SaO2 within certain limits, an alarm is used. When the SaO2 is outside of preset alarm limits, an alarm sounds and the nursing staff manually adjusts the amount of oxygen supplied to the preterm infant. However, due to the Bohr-effect, dangerously high PaO2 values could occur when SaO2 is still within alarm limits. Methods: Inclusion criteria were: 1) need for supplemental oxygen therapy, 2) gestational age at birth <30 weeks, 3) birth weight <1250 grams, and 4) postnatal age between 3 and 9 days at the start of data recording. In each subject, the SaO2 and PaO2 values were recorded simultaneously. SaO2 data was obtained by a pulse oximeter placed on the foot or hand of the preterm infant (SpO2). PaO2 data was obtained by a transcutaneous sensor placed on the chest or the abdomen (tcPO2). Nursing staff aimed to keep the SpO2 between 88% and 94%. The SpO2 level was classified as “low”, “good” or “high” for values of <88%, 88%-94%, and >94% respectively. The PaO2 level was classified as “low”, “good” or “high” for levels of <6 kPa, 6-10 kPa, or >10 kPa respectively [1]. The goal was to determine: 1) how often the SpO2 level corresponds to the tcPO2 levels, and 2) how often oxygen values exceed the alarm limits. Results: 6 preterm infants (birth weight: η = 789 +/- 231 grams, gestational age at birth: η = 27 +/- 1 2/7 weeks, postnatal age: η = 7 +/- 3 days) were included. In total 191 hours of data (range: 17 - 47 hours, F = 1Hz) were collected. SpO2 was “high”, “good” or “low” for respectively 41%, 46%, and 13% of the time. PaO2 was “high”, “good”, or “low” for respectively 13%, 42%, and 44% of the time. The tcPO2 and SpO2 corresponded 9% (high), 20% (good), and 10% (low) of the time. For 31% of the recorded time SpO2 was “high” while tcPO2 was “low or good”. For 5% of the recorded time SpO2 was “good or low”, while tcPO2 was “high”. Conclusions: The indicated SpO2 level does not match the tcPO2 level most of the time. This incongruity may be caused by inaccurate measurements of the pulse oximeter and/or the transcutaneous sensor. The incongruity may also be caused by the presence of HbF in the blood. HbF causes a left shift of the OD-curve (i.e. decrease in PaO2 at constant SaO2). The level of HbF varies due to natural decay after birth, and blood transfusions. The presence of HbF may also explain the relatively low tcPO2 levels while SpO2 levels were good or high. 1. Sola, A., L. Chow, and M. Rogido, Pulse oximetry in neonatal care in 2005. A comprehensive state of the art review. 2005. p. 266-81.
15 mins
Tim Marcus, Gert-Jan Mauritz, Anton Vonk-Noordegraaf
Abstract: Objective To explore in pulmonary arterial hypertension (PAH) whether the cause of interventricular asynchrony lies in onset of shortening or duration of shortening. Background In PAH, leftward ventricular septal bowing (LVSB) is probably caused by a left-to-right (L-R) delay in myocardial shortening. Methods In 21 PAH patients (mean pulmonary arterial pressure 55±13 mmHg and ECG-QRS width 100±16 ms), MRI myocardial tagging (14 ms temporal resolution) was applied. For the Left Ventricular (LV) free wall, septum and Right Ventricular (RV) free wall, the onset time (Tonset) and peak time (Tpeak) of circumferential shortening were calculated. RV wall tension was estimated by the Laplace law. Results Tonset was 51±23, 65±4 and 52±22 ms for LV, septum and RV respectively. Tpeak was 293±58, 267±22 and 387±50 ms for LV, septum and RV. Maximum LVSB was at 395±45 ms, coinciding with septal overstretch and RV Tpeak. The L-R delay in Tonset was -1±16 ms (p=0.84), and the L-R delay in Tpeak 94±41 ms (p<0.001). The L-R delay in Tpeak was not related with the QRS width, but was associated with RV wall tension (p<0.05). The L-R delay in Tpeak correlated with leftward septal curvature (p<0.05), and correlated negatively with LV end-diastolic volume (p<0.05) and SV (p<0.05). Discussion: The mechanism of the prolonged RV systole in PAH is probably the increased RV wall tension as shown by the correlation between L-R peak delay and RV wall tension. This mechanism is supported by measurements in rat cardiac trabeculae which provided evidence that an increased load of myocytes leads to a slower and prolonged shortening velocity [1]. Conclusion In PAH, the L-R delay in myocardial peak shortening is caused by lengthening of the duration of RV shortening. This L-R delay is related to LVSB, decreased LV filling and decreased stroke volume. Reference: [1] Van Heuningen R, Rijnsburger WH and Ter Keurs HE. Sarcomere length control in striated muscle. Am J Physiol Heart Circ Physiol. 242: H411-H420, 1982.
15 mins
Natascha Cuper, Rowland de Roode, Ruud Verdaasdonk
Abstract: Venipunctures to draw blood for diagnostics can be cumbersome. Multiple puncture attempts are distressing, painful and traumatic, especially for small children. In neonates, it is further complicated by the vessel size and fat padding tissues in some skin areas. A practical vessel viewing system based on infrared (IR) transillumination has been developed. It allows direct viewing of vessels underneath the skin to facilitate the puncture procedure. It has, in contrast to commercial systems available, the advantage of being low cost, easy to implement in routine practice, small, flexible and child friendly. The performance of the vessel viewing system was first tested in tissue phantoms. Consequently, the system was introduced in the clinic during blood withdrawal in young children measuring relevant parameters. To prove the efficiency, an initial study was performed in young children to find the baseline for comparison when using the vessel viewing system. Failure rate and time of needle manipulation underneath the skin, which is the most painful part of the procedure, were measured. Subsequently an observational prospective study was performed, where the system was applied, during blood withdrawal procedures in 45 patients, 0 – 6 years of age. Patient characteristics such as age, skin color and baby fat were registered. Responses from the technicians were also evaluated. In the baseline study without using the vessel viewing system, the failure rate (i.e. percentage of procedures where more than one puncture was necessary to gain blood) was 13 % in children of 0 – 6 years of age. When using of the vessel viewing system, the failure rate reduced significantly to 2 %. Percentage of procedures with extended time of needle manipulation (longer then 15 s) decreased from 21 % to 7 %. Parameters like presence of baby fat and dark skin color did not show significant results due to the small group. The technicians reported a high degree of satisfaction with the system. Conclusions: The vessel viewing system proved to be effective in the clinical scenario. Pain and trauma were significantly decreased and the technicians were satisfied with the flexible and practical use of the system. Further research on the use of the system for other applications, such as visualizing arteries for placement of arterial lines prior to OR, is ongoing. REFERENCES [1] A.J.A. Duff, “Incorporating psychological approaches into routine paediatric venepuncture”, Arch.Dis.Child., Vol. 88, pp. 931937, (2003). [2] R.K. Miyake et al, “Vein Imaging: A new method of near infrared imaging, where a processed image is projected onto the skin for the enhancement of vein treatment”, Dermatol.Surg., Vol. 32, pp. 1031-1038, (2006).
15 mins
Jan Menssen, Jeroen Hopman, Djien Liem, Chris de Korte
Abstract: For an adequate function and development of the neonatal brain O2 is necessary. With Near InfraRed Spectroscopy (NIRS) relative changes in concentration of oxyhemoglobin (cO2Hb) and total hemoglobin (ctHb) in the brain can be measured based on the light absorption (optical density) at three wavelengths. Using a fast sampling (>50 Hz) continuous wave NIRS device (Oxymon®, Artinis Medical Systems), cerebral arterial (SaO2) and venous (SvO2) saturation might be calculated using the pulsations due to heart action (SaO2) and oscillations due to the respiration (SvO2) in the cO2Hb and ctHb signal. To calculate these saturations different methods can be used. Validation of these methods is required before application in a neonatal setting. We developed two different methods to calculate SaO2 and SvO2. The optical density based method computes amplitudes of the pulsations resp. oscillations in the optical density signals and converts these amplitudes to cO2Hb and ctHb. The concentration based method converts the optical density signals to cO2Hb and ctHb signals and computes the amplitudes of the pulsations resp. oscillations of these signals. For both methods, amplitudes are calculated in the frequency domain or time domain, resulting in four different algorithms. In the frequency domain algorithm, from a time series of spectra the course of the amplitudes at the heart and respiration frequency is calculated for each signal. In the time domain algorithm, successive heart beats and respirations are detected and for each signal the amplitudes determined as the difference between the maximum and minimum1. Each algorithm calculates SaO2 and SvO2 using the ratio of the amplitude of cO2Hb and ctHb found at the heart action respectively at the respiration. Validation of the methods is done with simulated data and with data measured on volunteers. Simulations are done with random uniform distributed noise at different amplitudes added to optical density signals at constant SaO2 and SvO2. In other simulations SaO2 and SvO2 is changed while a constant noise level is added to the optical density signals. For both simulations, the saturation values obtained from the four algorithms are compared with the saturation values set in the model. In vivo validation is done on NIRS measurements in volunteers. In these experiments, the inspired oxygen is decreased down to a SaO2 value of about 75%. Calculated SaO2 values for each algorithm are compared with the values obtained from a standard pulse-oximeter (Nellcor® N200) that is used as a reference. For the in vivo measurements values obtained from the algorithms based on the optical densities are significant lower compared to the values obtained from concentration based algorithms (t-test, p<0.005). In the simulations the same effect is observed, At high saturation values and low noise, the difference is small and negligible compared to other errors from noise and tissue inhomogenities. At low saturation, the optical density method is preferable, especially with the frequency domain algorithm because heart and respiration rate are easier detected.