A comparison of propofol-to-BIS post-operative intensive care sedation by means of target controlled infusion, Bayesian-based and predictive control methods: an observational, open-label pilot study.

PURPOSE: We evaluated the feasibility and robustness of three methods for propofol-to-bispectral index (BIS) post-operative intensive care sedation, a manually-adapted target controlled infusion protocol (HUMAN), a computer-controlled predictive control strategy (EPSAC) and a computer-controlled Bayesian rule-based optimized control strategy (BAYES). METHODS: Thirty-six patients undergoing short lasting sedation following cardiac surgery were included to receive propofol to maintain a BIS between 40 and 60. Robustness of control for all groups was analysed using prediction error and spectrographic analysis. RESULTS: Although similar time courses of measured BIS were obtained in all groups, a higher median propofol effect-site concentration (CePROP) was required in the HUMAN group compared to the BAYES and EPSAC groups. The time course analysis of the remifentanil effect-site concentration (CeREMI) revealed a significant increase in CeREMI in the EPSAC group compared to BAYES and HUMAN during the case. Although similar bias and divergence in control was found in all groups, larger control inaccuracy was observed in HUMAN versus EPSAC and BAYES. Spectrographic analysis of the system behavior shows that BAYES covers the largest spectrum of frequencies, followed by EPSAC and HUMAN. CONCLUSIONS: Both computer-based control systems are feasible to be used during ICU sedation with overall tighter control than HUMAN and even with lower required CePROP. EPSAC control required higher CeREMI than BAYES or HUMAN to maintain stable control. Clinical trial number: NCT00735631.

Long-term outcome and health-related quality of life in difficult-to-wean patients with and without ventilator dependency at ICU discharge: a retrospective cohort study.

BACKGROUND: Long-term outcome and quality of life (QOL) in patients requiring prolonged mechanical ventilation after failure to wean in the ICU is scarcely documented. We aimed to evaluate long-term survival and QOL in patients discharged from the ICU with a tracheostomy for difficult weaning, and with or without ventilator dependency at ICU discharge. METHODS: We retrospectively investigated post-ICU trajectories and survival in patients requiring tracheostomy for difficult weaning admitted to the medical ICU of a tertiary center between 1999 and 2013, discriminating between patients who were ventilator dependent or were weaned at ICU discharge. In 2014, a QOL assessment was done in survivors with the use of the Short Form Health Survey (SF-36) and the Severe Respiratory Insufficiency questionnaire. RESULTS: A total of 114 patients was included, of whom 59 were ventilator dependent and 55 were weaned at ICU discharge. One-year survival rates were 73 % and 69 %, respectively. Overall QOL scores for physical functioning were low, and not significantly different between patients ventilated and those weaned at ICU discharge; scores for social functioning and mental health were less below norm and similar between both groups. CONCLUSIONS: Long-term survival in patients discharged from the ICU with tracheostomy and ventilator dependency after failure to wean was not significantly different from that of patients with tracheostomy and weaned at ICU discharge. Despite the physical QOL scores being low in both groups, mental QOL was acceptable. Given the intrinsic limitations of this retrospective study, prospective and preferentially multicenter studies are required to confirm these preliminary results.

A survey of beta-lactam antibiotics and vancomycin dosing strategies in intensive care units and general wards in Belgian hospitals.

Extended and continuous infusions with beta-lactam antibiotics have been suggested as a means of pharmacokinetic and pharmacodynamic optimisation of antimicrobial therapy. Vancomycin is also frequently administered in continuous infusion, although more for practical reasons. A survey was undertaken to investigate the recommendations by the local antibiotic management teams (AMTs) in Belgian acute hospitals concerning the administration (intermittent, extended or continuous infusion) and therapeutic drug monitoring of four beta-lactam antibiotics (ceftazidime, cefepime, piperacillin-tazobactam, meropenem) and vancomycin for adult patients with a normal kidney function. A structured questionnaire survey comprising three domains was developed and approved by the members of the Belgian Antibiotic Policy Coordination Committee (BAPCOC). The questionnaire was sent by e-mail to the official AMT correspondents of 105 Belgian hospitals, followed by two reminders. The response rate was 32 %, with 94 %, 59 %, 100 %, 100 % and 100 % of the participating Belgian hospitals using ceftazidime, cefepime, piperacillin-tazobactam, meropenem and vancomycin, respectively. Comparing intensive care unit (ICU) with non-ICU wards showed a higher implementation of extended or continuous infusions for ceftazidime (81 % vs. 41 %), cefepime (35 % vs. 10 %), piperacillin-tazobactam (38 % vs. 12 %), meropenem (68 % vs. 35 %) and vancomycin (79 % vs. 44 %) on the ICU wards. A majority of the hospitals recommended a loading dose prior to the first dose. For vancomycin, the loading dose and the trough target concentration were too low based on the current literature. This survey shows that extended and continuous infusions with beta-lactams and vancomycin are widely implemented in Belgian hospitals.

Antimicrobial prescription in severe COVID-19 and CAP: a matched case-control study.

BACKGROUND: In severe coronavirus diseases 2019 (COVID-19), a high and potentially excessive use of antimicrobials for suspected bacterial co-infection and intensive care unit (ICU)-acquired infections has been repeatedly reported. OBJECTIVES: To compare an ICU cohort of community-acquired pneumonia (CAP) with a cohort of severe COVID-19 pertaining to co-infections, ICU-acquired infections and associated antimicrobial consumption. METHODS: We retrospectively compared a cohort of CAP patients with a cohort of COVID-19 patients matched according to organ failure, ICU length of stay (LOS) and ventilation days. Patient data such as demographics, infection focus, probability and severity, ICU severity scores and ICU and in-hospital mortality, days of antimicrobial therapy (DOT) and number of antimicrobial prescriptions, using an incremental scale, were registered and analysed. The total number of cultures (sputum, urinary, blood cultures) was collected and corrected for ICU LOS. FINDINGS: CAP patients (n = 148) were matched to COVID-19 patients (n = 74). Significantly less sputum cultures (68.2% versus 18.9%, P < 0.05) and bronchoalveolar lavages (BAL) (73.7% versus 36.5%, P < 0.05) were performed in COVID-19 patients. Six (8.1%) COVID-19 patients were diagnosed with a co-infection. Respectively, 58 of 148 (39.2%) CAP and 38 of 74 (51.4%) COVID-19 patients (P = 0.09) developed ICU-acquired infections. Antimicrobial distribution, both in the number of prescriptions and DOT, was similar in both cohorts. CONCLUSIONS: We found a low rate of microbiologically confirmed bacterial co-infection and a high rate of ICU-acquired infections in COVID-19 patients. Infection probabilities, antimicrobial prescriptions and DOT were comparable with a matched CAP cohort.

A novel time series analysis approach for prediction of dialysis in critically ill patients using echo-state networks.

BACKGROUND: Echo-state networks (ESN) are part of a group of reservoir computing methods and are basically a form of recurrent artificial neural networks (ANN). These methods can perform classification tasks on time series data. The recurrent ANN of an echo-state network has an 'echo-state' characteristic. This 'echo-state' functions as a fading memory: samples that have been introduced into the network in a further past, are faded away. The echo-state approach for the training of recurrent neural networks was first described by Jaeger H. et al. In clinical medicine, until this moment, no original research articles have been published to examine the use of echo-state networks. METHODS: This study examines the possibility of using an echo-state network for prediction of dialysis in the ICU. Therefore, diuresis values and creatinine levels of the first three days after ICU admission were collected from 830 patients admitted to the intensive care unit (ICU) between May 31 th 2003 and November 17th 2007. The outcome parameter was the performance by the echo-state network in predicting the need for dialysis between day 5 and day 10 of ICU admission. Patients with an ICU length of stay <10 days or patients that received dialysis in the first five days of ICU admission were excluded. Performance by the echo-state network was then compared by means of the area under the receiver operating characteristic curve (AUC) with results obtained by two other time series analysis methods by means of a support vector machine (SVM) and a naive Bayes algorithm (NB). RESULTS: The AUC's in the three developed echo-state networks were 0.822, 0.818, and 0.817. These results were comparable to the results obtained by the SVM and the NB algorithm. CONCLUSIONS: This proof of concept study is the first to evaluate the performance of echo-state networks in an ICU environment. This echo-state network predicted the need for dialysis in ICU patients. The AUC's of the echo-state networks were good and comparable to the performance of other classification algorithms. Moreover, the echo-state network was more easily configured than other time series modeling technologies.

Machine learning in infection management using routine electronic health records: tools, techniques, and reporting of future technologies.

BACKGROUND: Machine learning (ML) is increasingly being used in many areas of health care. Its use in infection management is catching up as identified in a recent review in this journal. We present here a complementary review to this work. OBJECTIVES: To support clinicians and researchers in navigating through the methodological aspects of ML approaches in the field of infection management. SOURCES: A Medline search was performed with the keywords artificial intelligence, machine learning, infection∗, and infectious disease∗ for the years 2014-2019. Studies using routinely available electronic hospital record data from an inpatient setting with a focus on bacterial and fungal infections were included. CONTENT: Fifty-two studies were included and divided into six groups based on their focus. These studies covered detection/prediction of sepsis (n = 19), hospital-acquired infections (n = 11), surgical site infections and other postoperative infections (n = 11), microbiological test results (n = 4), infections in general (n = 2), musculoskeletal infections (n = 2), and other topics (urinary tract infections, deep fungal infections, antimicrobial prescriptions; n = 1 each). In total, 35 different ML techniques were used. Logistic regression was applied in 18 studies followed by random forest, support vector machines, and artificial neural networks in 18, 12, and seven studies, respectively. Overall, the studies were very heterogeneous in their approach and their reporting. Detailed information on data handling and software code was often missing. Validation on new datasets and/or in other institutions was rarely done. Clinical studies on the impact of ML in infection management were lacking. IMPLICATIONS: Promising approaches for ML use in infectious diseases were identified. But building trust in these new technologies will require improved reporting. Explainability and interpretability of the models used were rarely addressed and should be further explored. Independent model validation and clinical studies evaluating the added value of ML approaches are needed.

Systematic surveillance cultures as a tool to predict involvement of multidrug antibiotic resistant bacteria in ventilator-associated pneumonia.

OBJECTIVE: To assess prediction of multidrug resistant (MDR) pathogens in ventilator-associated pneumonia (VAP) by systematic surveillance cultures (SC) and to assess the contribution of SC to initial antibiotic therapy. DESIGN: Prospective cohort study of patients with microbiologically confirmed VAP. Comparison of actual early antibiotic coverage with three hypothetical empirical schemes. SETTING: A 50-bed university hospital ICU. SC consisted of oral, nasal, urinary and rectal samples upon admission, 3-weekly urinary and 1-weekly oral, nasal, and rectal samples in all patients, 3-weekly tracheal aspirates in intubated patients. RESULTS: MDR pathogens were found in 86 of 199 VAP episodes. Sensitivity of SC to predict MDR pathogens was 69% (tracheal SC) and 82% (all SC); specificity was 96% (tracheal) and 91% (all), respectively. Appropriate antibiotic coverage within 24 h and 48 h following MDR VAP was 77% and 89%, respectively. A carbapenem-based empirical scheme would have been equally appropriate (83% vs. 77% at 24 h; 83% vs. 89% at 48 h), but a beta-lactam-fluoroquinolone empirical therapy would have been less (59% vs. 77% at 24 h; 59% vs. 89% at 48 h) as would have been beta-lactam-aminoglycoside therapy (68% vs. 77% at 24 h; 68% vs. 89% at 48 h). Empirical comparators would have resulted in significantly more prescription of broad-spectrum antibiotics within the first 48 h. CONCLUSIONS: With MDR pathogens highly prevalent, systematic SC predicted MDR pathogens causing VAP in 69% to 82% and may have contributed to high rates of early appropriate antibiotic therapy with limited use of broad-spectrum antimicrobials.

Service-oriented subscription management of medical decision data in the intensive care unit.

OBJECTIVES: This paper addresses the design of a platform for the management of medical decision data in the ICU. Whenever new medical data from laboratories or monitors is available or at fixed times, the appropriate medical support services are activated and generate a medical alert or suggestion to the bedside terminal, the physician's PDA, smart phone or mailbox. Since future ICU systems will rely ever more on medical decision support, a generic and flexible subscription platform is of high importance. METHODS: Our platform is designed based on the principles of service-oriented architectures, and is fundamental for service deployment since the medical support services only need to implement their algorithm and can rely on the platform for general functionalities. A secure communication and execution environment are also provided. RESULTS: A prototype, where medical support services can be easily plugged in, has been implemented using Web service technology and is currently being evaluated by the Department of Intensive Care of the Ghent University Hospital. To illustrate the platform operation and performance, two prototype medical support services are used, showing that the extra response time introduced by the platform is less than 150 ms. CONCLUSIONS: The platform allows for easy integration with hospital information systems. The platform is generic and offers user-friendly patient/service subscription, transparent data and service resource management and priority-based filtering of messages. The performance has been evaluated and it was shown that the response time of platform components is negligible compared to the execution time of the medical support services.

Support vector machine versus logistic regression modeling for prediction of hospital mortality in critically ill patients with haematological malignancies.

BACKGROUND: Several models for mortality prediction have been constructed for critically ill patients with haematological malignancies in recent years. These models have proven to be equally or more accurate in predicting hospital mortality in patients with haematological malignancies than ICU severity of illness scores such as the APACHE II or SAPS II 1. The objective of this study is to compare the accuracy of predicting hospital mortality in patients with haematological malignancies admitted to the ICU between models based on multiple logistic regression (MLR) and support vector machine (SVM) based models. METHODS: 352 patients with haematological malignancies admitted to the ICU between 1997 and 2006 for a life-threatening complication were included. 252 patient records were used for training of the models and 100 were used for validation. In a first model 12 input variables were included for comparison between MLR and SVM. In a second more complex model 17 input variables were used. MLR and SVM analysis were performed independently from each other. Discrimination was evaluated using the area under the receiver operating characteristic (ROC) curves (+/- SE). RESULTS: The area under ROC curve for the MLR and SVM in the validation data set were 0.768 (+/- 0.04) vs. 0.802 (+/- 0.04) in the first model (p = 0.19) and 0.781 (+/- 0.05) vs. 0.808 (+/- 0.04) in the second more complex model (p = 0.44). SVM needed only 4 variables to make its prediction in both models, whereas MLR needed 7 and 8 variables in the first and second model respectively. CONCLUSION: The discriminative power of both the MLR and SVM models was good. No statistically significant differences were found in discriminative power between MLR and SVM for prediction of hospital mortality in critically ill patients with haematological malignancies.

Outcome in patients perceived as receiving excessive care across different ethical climates: a prospective study in 68 intensive care units in Europe and the USA.

PURPOSE: Whether the quality of the ethical climate in the intensive care unit (ICU) improves the identification of patients receiving excessive care and affects patient outcomes is unknown. METHODS: In this prospective observational study, perceptions of excessive care (PECs) by clinicians working in 68 ICUs in Europe and the USA were collected daily during a 28-day period. The quality of the ethical climate in the ICUs was assessed via a validated questionnaire. We compared the combined endpoint (death, not at home or poor quality of life at 1 year) of patients with PECs and the time from PECs until written treatment-limitation decisions (TLDs) and death across the four climates defined via cluster analysis. RESULTS: Of the 4747 eligible clinicians, 2992 (63%) evaluated the ethical climate in their ICU. Of the 321 and 623 patients not admitted for monitoring only in ICUs with a good (n = 12, 18%) and poor (n = 24, 35%) climate, 36 (11%) and 74 (12%), respectively were identified with PECs by at least two clinicians. Of the 35 and 71 identified patients with an available combined endpoint, 100% (95% CI 90.0-1.00) and 85.9% (75.4-92.0) (P = 0.02) attained that endpoint. The risk of death (HR 1.88, 95% CI 1.20-2.92) or receiving a written TLD (HR 2.32, CI 1.11-4.85) in patients with PECs by at least two clinicians was higher in ICUs with a good climate than in those with a poor one. The differences between ICUs with an average climate, with (n = 12, 18%) or without (n = 20, 29%) nursing involvement at the end of life, and ICUs with a poor climate were less obvious but still in favour of the former. CONCLUSION: Enhancing the quality of the ethical climate in the ICU may improve both the identification of patients receiving excessive care and the decision-making process at the end of life.

Design of a flexible platform for execution of medical decision support agents in the intensive care unit.

This paper addresses the design of a generic and scalable platform for the execution of medical decision support agents in the intensive care unit (ICU). As will be motivated, medical decision support agents can impose high computational load and in practical setups a large amount of such agents are typically running in parallel. Future ICU systems will rely on extensive medical decision support. However, in current systems only one workstation is typically dedicated for the execution of medical decision support agents. Therefore, we propose an architecture based on middleware technology to allow for easy distribution of the agents along multiple workstations. The architecture allows for easy integration with a general ICU data flow management architecture.

Platform for efficient switching between multiple devices in the intensive care unit.

INTRODUCTION: This article is part of the Focus Theme of METHODS of Information in Medicine on "Managing Interoperability and Complexity in Health Systems". OBJECTIVES: Handheld computers, such as tablets and smartphones, are becoming more and more accessible in the clinical care setting and in Intensive Care Units (ICUs). By making the most useful and appropriate data available on multiple devices and facilitate the switching between those devices, staff members can efficiently integrate them in their workflow, allowing for faster and more accurate decisions. This paper addresses the design of a platform for the efficient switching between multiple devices in the ICU. The key functionalities of the platform are the integration of the platform into the workflow of the medical staff and providing tailored and dynamic information at the point of care. METHODS: The platform is designed based on a 3-tier architecture with a focus on extensibility, scalability and an optimal user experience. After identification to a device using Near Field Communication (NFC), the appropriate medical information will be shown on the selected device. The visualization of the data is adapted to the type of the device. A web-centric approach was used to enable extensibility and portability. RESULTS: A prototype of the platform was thoroughly evaluated. The scalability, performance and user experience were evaluated. Performance tests show that the response time of the system scales linearly with the amount of data. Measurements with up to 20 devices have shown no performance loss due to the concurrent use of multiple devices. CONCLUSIONS: The platform provides a scalable and responsive solution to enable the efficient switching between multiple devices. Due to the web-centric approach new devices can easily be integrated. The performance and scalability of the platform have been evaluated and it was shown that the response time and scalability of the platform was within an acceptable range.

Use of continuous bispectral EEG monitoring to assess depth of sedation in ICU patients.

Monitoring the depth of sedation in patients under intensive care is difficult. Clinical assessment by the different scoring systems produces insufficient information, especially once deeply sedated patients become unresponsive to any external stimulation. Recently, the bispectral index (BIS), the result of computerized bispectral electroencephalographic monitoring, was found to be the best predictor of depth of anaesthesia during surgical intervention. This report concerns BIS monitoring in 18 randomly selected, deeply sedated, surgical patients in the intensive care unit, who were unresponsive to standard clinical stimulation (Ramsay sedation score). A wide range of BIS was observed, with 15 of the patients having a BIS below 60, indicating a state of deep sedation (or possibly over-sedation). Therefore, further studies using BIS monitoring in patients under intensive care are needed to determine if this method can guide sedation and prevent oversedation in this context and, most importantly, to analyse its final cost-benefit ratio.

Antithrombin III in patients with severe sepsis: a pharmacokinetic study.

OBJECTIVES: To evaluate the safety, pharmacokinetics, and the practicability of two different antithrombin III (AT III) high-dose regimens in patients with severe sepsis. DESIGN: Prospective, open, randomized, 2 parallel groups, multinational clinical trial. SETTING: Eleven academic medical center intensive care units (ICU) in Austria, Belgium, Denmark, Germany, Norway and Sweden. PATIENTS: Thirty-three patients with severe sepsis who received standard supportive care and antimicrobial therapy, in addition to the administration of AT III. INTERVENTIONS: Patients received an intravenous loading dose of 6,000 IU AT III followed by either intermittent bolus infusions of 1,000 IU AT III every 4 h or a continuous infusion of 250 IU AT III/h for 4 days, resulting in a total dose for both dosage regimens of 30,000 IU AT III. MEASUREMENTS: All patients were evaluated for safety and all but one for pharmacokinetics. RESULTS AND CONCLUSIONS: The administration of AT III was safe and well tolerated. The overall 28-day all-cause mortality was 30% (43% intermittent bolus infusions; 21% continuous infusion). The mean probability of dying according to the SAPS II was 48%. The difference in mortality between both groups was within the range of chance. AT III plasma levels were elevated from low baseline levels to above 120% soon after onset of AT III therapy and remained at these levels for the treatment phase of 4 days. Functional and immunologic levels of AT III corresponded very well. With an overall median volume of distribution of 4.5 l (range: 2.4-6.5 l), AT III only moderately extended beyond plasma. The overall median elimination half-life was 18.6 h (range: 5.1-37.4). Overall, median response was 1.75% per IU/kg (range: 1.14-2.8). The variability of elimination parameters was quite noteworthy (CV = 41-59%), whereas distribution-related parameters showed a moderate variability (CV = 24%). In spite of this variability, both high-dose IV regimens reliably provided AT III levels above 120% for all but one patient. An increased mortality was observed for patients with a distribution volume exceeding 4.5 l (or a response < 1.7% per IU/kg). AT III distribution volumes above 4.5 l might indicate a capillary leak phenomenon. The continuous infusion regimen was slightly preferred by the investigators with regard to practicability.

On the design of a generic and scalable multilayer software architecture for data flow management in the intensive care unit.

OBJECTIVES: The current Intensive Care Information Systems (IC-ISs) collect and store monitoring data in on automated way and can replace all paper forms by an electronic equivalent, resulting in a paperless ICU. Future development of IC-ISs will now have to focus on bedside clinical decision support. The current IC-ISs are data-driven systems, with a two-layer software architecture. This software architecture is hardly maintainable and probably not the most optimal architecture to make the transition towards future systems with-decision support. The aim of this research was to address the design of an alternative software architecture based on new paradigms. METHODS: State-of-the art component, middleware and agent technology were deployed to design and implement a software architecture for ICU data flow management. RESULTS: An advanced multi-layer architecture for efficient data flow management in the ICU has been designed. The architecture is both generic and scalable, which means that it neither depends on a particular ICU nor on the deployed monitoring devices. Automatic device detection and Graphical User Interface generation are taken into account. Furthermore, a demonstrator has been developed as a proof that the proposed conceptual software architecture is feasible in practice. The core of the new architecture consists of Bed Decision Agents (BDAs). The introduction of BDAs, who perform specific dedicated tasks, improves the adaptability and maintainability of the future very complex IC-ISs. CONCLUSIONS: A software architecture, based on component, middleware and agent technology, is feasible and offers important advantages over the currently used two-layer software architecture.

Analysis of very early jugular bulb oximetry data after severe head injury: implications for the emergency management?

Jugular bulb oximetry provides the first bedside available information on cerebral oxygen utilization. An extensive analysis was made of all initial jugular bulb oximetry data obtained in 150 patients within the first 12 h after severe traumatic brain injury. These data revealed initial abnormal jugular bulb saturation values in 57 patients (= 38% of study population), with a predominance of jugular bulb desaturation (observed in 45 patients). This confirms earlier reports that revealed a high incidence of disturbed and inadequate cerebral perfusion in the first hours after brain injury. Jugular bulb desaturation was especially related to systemic causes (such as a lowered cerebral perfusion pressure observed in 29 patients, and a lowered arterial carbon dioxide tension in 24 patients). These findings could have important implications for the emergency management of severely head-injured patients, as outcome might possibly be improved by better attention to all systemic factors that might reduce cerebral perfusion in the early hours after traumatic insult.

[Sequential orthotopic liver transplantation--domino transplantation]. / Die sequentielle orthotope Lebertransplantation--Dominotransplantation.

Familial amyloid polyneuropathy (FAP) is a rare indication for liver transplantation. The excised liver of the FAP patient can be transplanted into a selected patient. In the following report, sequential liver transplantation is described where a 34-year-old female FAP patient received a cadaver donor liver. The excised native liver was transplanted to a 60-year-old male patient suffering from hepatocellular carcinoma in cirrhosis due to hepatitis C.

[Liver transplantation preserving the vena cava and a temporary portocaval shunt]. / Die Lebertransplantation mit Erhalt der Vena cava und einem temporären portocavalen Shunt.

The experience with laterolateral cavocavostomy for hepatovenous reconstruction in liver transplantation is reviewed with and without the use of a temporary portocaval shunt. A total of 65 liver transplantations were analyzed. In 49 transplantations a laterolateral cavocaval anastomosis was performed (group I). In group II (n = 16) the same technique was used after a temporary portal caval shunt was constructed. Mean arterial pressure (mmHg): group I 128 +/- 34; group II 109 +/- 32. Cardiac output (l/min) decrease during the anhepatic phase was 2.3 +/- 1.9 and 1.2 +/- 1.5, respectively (P < 0.05). The peroperative blood loss measured as the number of packed cells transfused was 16.4 +/- 15.8 versus 1.2 +/- 2.3 (P < 0.04) and fresh frozen plasma 19.0 +/- 14.7 versus 3.7 +/- 4.0 (P < 0.02). Course on ICU (days), liver function tests, renal function and the need for reoperation because of bleeding were not statistically significantly different between the groups. One-year patient survival was 82.7 and 85.7%, respectively. In conclusion, we found that despite preservation of the caval flow during hepatectomy, the additional use of a temporary portocaval shunt was advantageous with regard to peroperative hemorrhage and hemodynamic stability and can potentially facilitate implantation of the liver graft.

Influence of chest physiotherapy on arterial oxygen saturation.

Two groups of ventilated patients were compared for chest physical therapy on an ICU: respiratory insufficient patients on one side and a control population on the other were submitted either to percussion or vibration therapy, and to postural drainage. Our data show a decrease in arterial oxygen saturation after CPT and after 2h monitoring; the lateral position results in a better SaO2 in the pneumonia group while SaO2 tend to decrease in the control population. However, no significant therapeutic influence of vibration nor percussion was found. Our data suggest CPT does not result in a short term respiratory benefit. Further investigations with prolonged sessions of postural drainage are required.

Jugular bulb oximetry: review on a cerebral monitoring technique.

Jugular bulb oximetry is the first available continuous monitoring method estimating the adequacy of cerebral perfusion. Despite its major technical as well as methodological shortcomings the information on the oxygen supply to demand balance of the brain seems most valuable. Especially the deleterious consequences of systemic variations (mainly concerning arterial blood pressure and CO2-tension) on the diseased brain are revealed by jugular bulb saturation values. The prevention and/or the early detection of these systemic secondary insults could have important implications as to final neurological outcome. Jugular bulb oximetry could also guide specific intracranial antihypertensive treatment, as it may reveal the pathophysiological mechanisms behind intracranial hypertension with regard to the status of cerebral perfusion (cerebral hyperemia or cerebral hypoperfusion). These insights might increase the efficacy of all treatments available for intracranial hypertension.