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Background The use of machine learning is becoming increasingly popular in many disciplines, but there is still an implementation gap of machine learning models in clinical settings. Lack of trust in models is one of the issues that need to be addressed in an effort to close this gap. No models are perfect, and it is crucial to know in which use cases we can trust a model and for which cases it is less reliable. Methods Four different algorithms are trained on the eICU Collaborative Research Database using similar features as the APACHE IV severity-of-disease scoring system to predict hospital mortality in the ICU. The training and testing procedure is repeated 100 times on the same dataset to investigate whether predictions for single patients change with small changes in the models. Features are then analysed separately to investigate potential differences between patients consistently classified correctly and incorrectly. Results A total of 34 056 patients (58.4%) are classified as true negative, 6 527 patients (11.3%) as false positive, 3 984 patients (6.8%) as true positive, and 546 patients (0.9%) as false negatives. The remaining 13 108 patients (22.5%) are inconsistently classified across models and rounds. Histograms and distributions of feature values are compared visually to investigate differences between groups. Conclusions It is impossible to distinguish the groups using single features alone. Considering a combination of features, the difference between the groups is clearer. Incorrectly classified patients have features more similar to patients with the same prediction rather than the same outcome.

IntroductionPostoperative delirium is common in older cardiac surgery patients and associated with negative short-term and long-term outcomes. The alpha-2-adrenergic receptor agonist dexmedetomidine shows promise as prophylaxis and treatment for delirium in intensive care units (ICU) and postoperative settings. Clonidine has similar pharmacological properties and can be administered both parenterally and orally. We aim to study whether repurposing of clonidine can represent a novel treatment option for delirium, and the possible effects of dexmedetomidine and clonidine on long-term cognitive trajectories, motor activity patterns and biomarkers of neuronal injury, and whether these effects are associated with frailty status.Methods and analysisThis five-centre, double-blind randomised controlled trial will include 900 cardiac surgery patients aged 70+ years. Participants will be randomised 1:1:1 to dexmedetomidine or clonidine or placebo. The study drug will be given as a continuous intravenous infusion from the start of cardiopulmonary bypass, at a rate of 0.4 µg/kg/hour. The infusion rate will be decreased to 0.2 µg/kg/hour postoperatively and be continued until discharge from the ICU or 24 hours postoperatively, whichever happens first.Primary end point is the 7-day cumulative incidence of postoperative delirium (Diagnostic and Statistical Manual of Mental Disorders, fifth edition). Secondary end points include the composite end point of coma, delirium or death, in addition to delirium severity and motor activity patterns, levels of circulating biomarkers of neuronal injury, cognitive function and frailty status 1 and 6 months after surgery.Ethics and disseminationThis trial is approved by the Regional Committee for Ethics in Medical Research in Norway (South-East Norway) and by the Norwegian Medicines Agency. Dissemination plans include publication in peer-reviewed medical journals and presentation at scientific meetings.Trial registration numberNCT05029050.

Background Whole body ischemia and reperfusion injury after cardiac arrest leads to the massive inflammation clinically manifested in the post-cardiac arrest syndrome. Previous studies on the inflammatory effect on circulatory failure after cardiac arrest have either investigated a selected patient group or a limited part of the inflammatory mechanisms. We examined the association between cardiac arrest characteristics and inflammatory biomarkers, and between inflammatory biomarkers and circulatory failure after cardiac arrest, in an unselected patient cohort. Methods This was a prospective study of 50 consecutive patients with out-of-hospital cardiac arrest. Circulation was invasively monitored from admission until day five, whereas inflammatory biomarkers, i.e. complement activation, cytokines and endothelial injury, were measured daily. We identified predictors for an increased inflammatory response, and associations between the inflammatory response and circulatory failure. Results We found a marked and broad inflammatory response in patients after cardiac arrest, which was associated with clinical outcome. Long time to return of spontaneous circulation and high lactate level at admission were associated with increased complement activation (TCC and C3bc), pro-inflammatory cytokines (IL-6, IL-8) and endothelial injury (syndecan-1) at admission. These biomarkers were in turn significantly associated with lower mean arterial blood pressure, lower cardiac output and lower systemic vascular resistance, and increased need of circulatory support in the initial phase. High levels of TCC and IL-6 at admission were significantly associated with increased 30-days mortality. Conclusion Inflammatory biomarkers, including complement activation, cytokines and endothelial injury, were associated with increased circulatory failure in the initial period after cardiac arrest.

The circulatory system is oscillatory in its nature. Oscillatory components linked to physiological processes and underlying regulatory mechanisms are identifiable in circulatory signals. Autonomic regulation is essential for the system's ability to deal with external exposure, and the integrity of oscillations may be considered a hallmark of a healthy system. Loss of complexity is seen as a consequence of several diseases and aging. Heart rate variability is known to decrease after cardiac surgery and remain reduced for up to 6 months. Oscillatory components of circulatory signals are linked to the system's overall complexity. We therefore hypothesize that the frequency distributions of circulatory signals show loss of oscillatory components after cardiac surgery and that the observed changes persist. We investigated the development of the circulatory frequency distributions of eight patients undergoing cardiac surgery by extracting three time series from conventional blood pressure and electrocardiography recordings: systolic blood pressure, heart rate, and amplitude of the electrocardiogram's R‐wave. Four 30‐min selections, representing key events of the perioperative course, were analyzed with the continuous wavelet transform, and average wavelet power spectra illustrated the circulatory frequency distributions. We identified oscillatory components in all patients and variables. Contrary to our hypothesis, they were randomly distributed through frequencies, patients, and situations, thus, not representing any reduction in the overall complexity. One patient showed loss of a 25‐s oscillation after surgery. We present a case where noise is misclassified as an oscillation, raising questions about the robustness of such analyses., Loss of complexity of biological systems is seen as a consequence of several diseases and aging, and heart rate variability is known to decrease after cardiac surgery. We explore the frequency distributions of ECG and blood pressure recordings of eight patients undergoing cardiac surgery, with the search for loss of oscillatory components and a reduction in overall complexity. Only one patient show loss of a distinct oscillation, and we do not identify any systematic reduction of complexity after cardiac surgery.

Background : Substantial investigation has been made into the correlation between Pulse Transit Time (PTT) and Blood Pressure (BP), as a possible route to achieve continuous non-invasive measurement of BP (cNIBP). We investigated whether PTT-trends could model BP-trends during episodes of rapid declines in Systolic Blood Pressure (SBP). Methods: From the freely available Medical Information Mart for Intensive Care (MIMIC-III) waveform database, we identified subjects who experienced a reduction in SBP from ≥ 120mmHg to ≤ 90 mmHg during a period of ≤ 15 minutes, for whom complete peak detection was possible. SBP was extracted from the Arterial Blood Pressure (ABP) waveform, and PTT was calculated from the R-peak of the ECG to the peak of the ABP waveform. Both SBP and PTT were processed using a moving average filter, yielding the variables SBP AV and PTT-RA AV . A moving average of continuous heart rate (HR AV ) was also analysed as a negative control to assess the effect of averaging. The intra-individual association between variables was assessed per subject using linear regression. Results: 511 patients were included for the main analysis. Median correlation coefficients (r) obtained from linear regression versus SBP AV were as follows: PTT-RA AV -0.93 (IQR -0.98 to -0.76), HR AV 0.46 (IQR -0.16 to 0.83). Regression slopes for the relationship between SBP AV and PTT-RA AV displayed a median of -2.46 mmHg/ms (IQR -3.47 mmHg/ms to -1.61 mmHg/ms). In supplementary analysis, results did not differ substantially when widening inclusion criteria, but the results were not always consistent within subjects across episodes of hypotension. Conclusions: In a large cohort of critically ill patients experiencing episodes of rapid declines in systolic blood pressure, there was a moderate-strong intra-individual correlation between averaged systolic blood pressure and averaged pulse transit time as measured from ECG R-peak to the peak of the arterial blood pressure waveform. Our findings encourage further investigation into using the pulse transit time for non-invasive real-time detection of hypotension.

Background: Accidental hypothermia with cardiac arrest represents a challenge for pre-hospital rescuers as well as in-hospital staff. For pre-hospital personnel, the main focus is to get the patient to the correct destination without unnecessary delay. For in-hospital personnel early information is vital to assess the possibility for resuscitation with extracorporeal re-warming. The challenge is augmented when rescuers must cross national borders to reach and/or deliver the patients. We present a case where three adolescent boys suffered severe hypothermia after a canoeing accident in Sweden. Case presentation: Three 14-year-old boys were canoeing a mountain lake close to the Norwegian border when their boat capsized and they all fell into the cold water. The rescue operation was hampered by rough weather conditions, and immersion times spanned from 63 to 125 min. Flight times from the scene of accident to the nearest ECMO center in Norway (Trondheim) and Sweden (Umeå) were about 30 and 90 min respectively. Two of the victims showed no vital signs after retrieval from the water and had extremely low body temperatures. They were brought to Trondheim University Hospital where they were resuscitated successfully with extracorporeal re-warming. Unable to be weaned from ECMO in the initial phase, both patients were retrieved by mobile ECMO teams to Karolinska University Hospital, from where they were discharged to their homes with good outcomes, although with some sequelae. A third victim with moderate to severe hypothermia without cardiac arrest was treated at a local hospital, from where he after a short stay was discharged without physical sequelae. Conclusion: These cases are a reminder of the traditional mantra that «no one is dead until warm and dead». Good communication between pre- and in-hospital staff can be vital for optimizing patient treatment when handling victims of severe hypothermia, and especially when there is multiple victims. Communication between neighboring countries, but even neighboring regions within the same country, can be challenging. We encourage regions similar to ours to review protocols regarding hypothermia management, making them more robust before incidents like this take place © The Author(s). 2017. Open Access. This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/)

BACKGROUND Patient monitors in modern hospitals give heartbeat waveform data that is reduced to aggregated variables and simple thresholds for alarms. Often, the monitors give a steady stream of non-specific alarms, leading to alarm fatigue in clinicians. An alarm can be seen as a classification problem, and by applying Principal Component Analysis (PCA) to the heart rate waveform of readily available monitoring devices, the accuracy of the classification of abnormality could be highly increased. OBJECTIVE To investigate whether physiological changes could be detected by looking at the heart rate waveform. METHODS A dataset of a healthy volunteer monitored with electrocardiography (ECG) and invasive blood pressure (BP) experiencing several tilts on a tilting table was investigated. A novel way of splitting continuous data based on the heartbeat was introduced. PCA was applied to classify the heartbeats. RESULTS A classification using only the aggregated variables heart rate (HR) and BP was able to correctly identify 20.7% of the heartbeats in the vertical tilt as abnormal. A classification using the full waveforms and combining the ECG and BP signals was able to correctly identify 83.5% of the heartbeats in the vertical tilt as abnormal. A humanistic machine learning (ML) method is then proposed based on the PCA classification. CONCLUSIONS A ML method for classification of physiological variability was described. The main novelty lies in the splitting of an ECG and BP signal by the heart rate and performing a PCA on the data-table.

Rapid, accurate and robust glucose measurements are needed to make a safe artificial pancreas for the treatment of diabetes mellitus type 1 and 2. The present gold standard of continuous glucose sensing, subcutaneous (SC) glucose sensing, has been claimed to have slow response and poor robustness towards local tissue changes such as mechanical pressure, temperature changes, etc. The present study aimed at quantifying glucose dynamics from central circulation to intraperitoneal (IP) sensor sites, as an alternative to the SC location. Intraarterial (IA) and IP sensors were tested in three anaesthetized non-diabetic pigs during experiments with intravenous infusion of glucose boluses, enforcing rapid glucose level excursions in the range 70--360 mg/dL (approximately 3.8--20 mmol/L). Optical interferometric sensors were used for IA and IP measurements. A first-order dynamic model with time delay was fitted to the data after compensating for sensor dynamics. Additionally, off-the-shelf Medtronic Enlite sensors were used for illustration of SC glucose sensing. The time delay in glucose excursions from central circulation (IA) to IP sensor location was found to be in the range 0--26 s (median: 8.5 s, mean: 9.7 s, SD 9.5 s), and the time constant was found to be 0.5--10.2 min (median: 4.8 min, mean: 4.7 min, SD 2.9 min). IP glucose sensing sites have a substantially faster and more distinctive response than SC sites when sensor dynamics is ignored, and the peritoneal fluid reacts even faster to changes in intravascular glucose levels than reported in previous animal studies. This study may provide a benchmark for future, rapid IP glucose sensors.

It is well-known that blood glucose oscillates with a period of approximately 15 min (900 s) and exhibits an overall complex behaviour in intact organisms. This complexity is not thoroughly studied, and thus, we aimed to decipher the frequency bands entailed in blood glucose regulation. We explored high-resolution blood glucose time-series sampled using a novel continuous intravascular sensor in four pigs under general anaesthesia for almost 24 hours. In all time series, we found several interesting oscillatory components, especially in the 5000–10000 s, 500–1000 s, and 50–100 s regions (0.0002–0.0001 Hz, 0.002–0.001 Hz, and 0.02–0.01 Hz). The presence of these oscillations is not permanent, as they come and go. This is the first report of glucose oscillations in the 50–100 s range. The origin of these oscillations and their role in overall blood glucose regulation is unknown. Although the sample size is small, we believe this finding is important for our understanding of glucose regulation and perhaps for our understanding of general homeostatic regulation in intact organisms. © 2018 Skjaervold et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

This study assesses positional changes in cardiac power output and stroke work compared to classic haemodynamic variables, measured before and after elective coronary artery bypass graft surgery. The hypothesis was that cardiac power output was altered in relation to cardiac stunning. The study is a retrospective analysis of data from two previous studies performed in a tertiary care university hospital. Thirty-six patients scheduled for elective coronary artery bypass graft surgery, with relatively preserved left ventricular function, were included. A pulmonary artery catheter and a radial artery catheter were placed preoperatively. Cardiac power output and stroke work were calculated through thermodilution both supine and standing prior to induction of anaesthesia and again day one postoperatively. Virtually all systemic haemodynamic parameters changed significantly from pre- to postoperatively, and from supine to standing. Cardiac power output was maintained at 0.9-1.0 (+/- 0.3) W both pre- and postoperatively and from supine to standing on both days. Stroke work fell from pre- to postoperatively from 1.1 to 0.8 J (p

BACKGROUND The post cardiac arrest syndrome (PCAS) is responsible for the majority of in-hospital deaths following cardiac arrest (CA). The major elements of PCAS are anoxic brain injury and circulatory failure. OBJECTIVE This study aimed to investigate the clinical characteristics of circulatory failure and inflammatory responses after out-of-hospital cardiac arrest (OHCA) and to identify patterns of circulatory and inflammatory responses, which may predict circulatory deterioration in PCAS. METHODS This study is a single-center cohort study of 50 patients who receive intensive care after OHCA. The patients are followed for 5 days where detailed information from circulatory variables, including measurements by pulmonary artery catheters (PACs), is obtained in high resolution. Blood samples for inflammatory and endothelial biomarkers are taken at inclusion and thereafter daily. Every 10 min, the patients will be assessed and categorized in one of three circulatory categories. These categories are based on mean arterial pressure; heart rate; serum lactate concentrations; superior vena cava oxygen saturation; and need for fluid, vasoactive medications, and other interventions. We will analyze predictors of circulatory failure and their relation to inflammatory biomarkers. RESULTS Patient inclusion started in January 2016. CONCLUSIONS This study will obtain advanced hemodynamic data with high resolution during the acute phase of PCAS and will analyze the details in circulatory state transitions related to circulatory failure. We aim to identify early predictors of circulatory deterioration and favorable outcome after CA. CLINICALTRIAL ClinicalTrials.gov: NCT02648061; https://clinicaltrials.gov/ct2/show/NCT02648061 (Archived by WebCite at http://www.webcitation.org/6wVASuOla)

Background: The aim of this study was to construct a non-invasive model for acute right ventricular afterload increase by hypoxic pulmonary vasoconstriction. Intact animal models are vital to improving our understanding of the pathophysiology of acute right ventricular failure. Acute right ventricular failure is caused by increased afterload of the right ventricle by chronic or acute pulmonary hypertension combined with regionally or globally reduced right ventricular contractile capacity. Previous models are hampered by their invasiveness; this is unfortunate as the pulmonary circulation is a low-pressure system that needs to be studied in closed chest animals. Hypoxic pulmonary vasoconstriction is a mechanism that causes vasoconstriction in alveolar vessels in response to alveolar hypoxia. In this study we explored the use of hypoxic pulmonary vasoconstriction as a means to increase the pressure load on the right ventricle. Results: Pulmonary hypertension was induced by lowering the FiO2 to levels below the physiological range in eight anesthetized and mechanically ventilated pigs. The pigs were monitored with blood pressure measurements and blood gases. The mean pulmonary artery pressures (mPAP) of the animals increased from 18.3 (4.2) to 28.4 (4.6) mmHg and the pulmonary vascular resistance (PVR) from 254 (76) dyns/cm5 to 504 (191) dyns/cm5, with a lowering of FiO2 from 0.30 to 0.15 (0.024). The animals’ individual baseline mPAPs varied substantially as did their response to hypoxia. The reduced FiO2 level yielded an overall lowering in oxygen offer, but the global oxygen consumption was unaltered. Conclusions: We showed in this study that the mPAP and the PVR could be raised by approximately 100% in the study animals by lowering the FiO2 from 0.30 to 0.15 (0.024). We therefore present a novel method for minimally invasive (closed chest) right ventricular afterload manipulations intended for future studies of acute right ventricular failure. The method should in theory be reversible, although this was not studied in this work. © The Author(s) 2017. This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/ publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

Hemorrhagic shock is clinically observed as changes in macrocirculatory indices, while its main pathological constituent is cellular asphyxia due to microcirculatory alterations. The coherence between macro‐ and microcirculatory changes in different shock states has been questioned. This also applies to the hemorrhagic shock. Most studies, as well as clinical situations, of hemorrhagic shock include a “second hit” by tissue trauma. It is therefore unclear to what extent the hemorrhage itself contributes to this lack of circulatory coherence. Nine pigs in general anesthesia were exposed to a controlled withdrawal of 50% of their blood volume over 30 min, and then retransfusion over 20 min after 70 min of hypovolemia. We collected macrocirculatory variables, microcirculatory blood flow measurement by the fluorescent microspheres technique, as well as global microcirculatory patency by calculation of Pv‐aCO2, and tissue metabolism measurement by the use of microdialysis. The hemorrhage led to anticipated changes in macrocirculatory variables with a coherent change in microcirculatory and metabolic variables. In the late hemorrhagic phase, the animals' variables generally improved, probably through recruitment of venous blood reservoirs. After retransfusion, all variables were normalized and remained same throughout the study period. We find in our nontraumatic model consistent coherence between changes in macrocirculatory indices, microcirculatory blood flow, and tissue metabolic response during hemorrhagic shock and retransfusion. This indicates that severe, but brief, hemorrhage with minimal tissue injury is in itself not sufficient to cause lack of coherence between macro‐ and microcirculation. ª2017 The Authors.Physiological Reportspublished by Wiley Periodicals, Inc. on behalf ofThe Physiological Society and the American Physiological Society.This is an open access article under the terms of the Creative Commons Attribution License,which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

This thesis describes the stepwise development and testing of the components of a novel artificial endocrine pancreas, consisting of a continuous glucose monitor, an insulin infusion device and a control algorithm. The starting point was the belief that current approaches to the challenges posed by creating an artificial endocrine pancreas do not work, and we identified some of the biological mechanisms that can explain this lack of success. We further established a set of research questions with the overall goal of constructing a working artificial endocrine pancreas.The first paper describes the in vivo (pig model) testing of a prototype of a new intravascular continuous glucose monitor, the IvS-1. The study determined that the monitor was able to produce readings with a reasonably fast response time that highly agreed with simultaneously drawn blood samples. The second study examined the pharmacological properties of intravenous insulin boluses, and estimated the time delays from insulin administration until changes in the blood glucose level. The third study demonstrated that blood glucose levels were the same in the arterial and venous systems, even at times of great circulatory stress. The fourth study relied on our accumulated knowledge to enable us to construct an artificial endocrine pancreas using the IvS-1 and a novel insulin regulatory algorithm based on insulin boluses. We then regulated the blood glucose level in diabetic pigs in a proof-of-concept study.The thesis concludes by answering the research questions, and asserts that the construction of an artificial endocrine pancreas is possible from a biological standpoint However, there are several serious technological challenges that have to be overcome in order to make a stable system for in-hospital – and later outpatient – use.

Introduction Measuring cardiac output (CO) with the pulmonary artery catheter intermittent bolus thermodilution technique (PAC-IBTD) is less precise with spontaneous breathing compared to controlled ventilation. We aimed to test if precision could be improved in spontaneous breathing by synchronizing the measurement with respiration or using instructed respiration in 18 post-operative cardiac surgery patients. Methods We performed eight CO measurements with PAC-IBTD using cold saline in three different situations; in random order: 1) random compared to respiration, 2) timed to the start of expiration, and 3) synchronized with a slow exhalation through a PEP-flute. We calculated the standard deviation (SD), coefficient of variation (CV), and precision in the total material and in the three situations using a linear mixed effects model. Results A total of 408 CO measurements were performed in 17 included patients. There were no differences between the three study situations regarding mean or precision. The overall CO was 6.0 ± 1.4 l/min (mean ± SD), CV 6.2% and precision 12.2% for single measurements. Averaging three measurements increased the precision to 7.0%. Conclusion We could not improve the precision of PAC-IBTD in spontaneously breathing patients by synchronizing the measurements with respiration.

One of several unsolved challenges in the construction of an artificial endocrine pancreas (a system for automatically adjusting the blood glucose level) is the positioning of the glucose sensor. We believe the best positioning to be either intraarterial or in a central vein. It is therefore important to know whether the glucose content in these blood locations is the same. We conducted a post hoc analysis of previously collected data from pigs exposed to gross inflammatory and circulatory stress. Paired arterial and mixed venous glucose values were compared with a mixed effects model. We found the blood glucose values from the arterial and mixed venous blood to be the same.

Continuous biological signals, like blood pressure recordings, exhibit nonlinear and nonstationary properties which must be considered during their analysis. Heart rate variability analyses have identified several frequency components and their autonomic origin. There is need for more knowledge on the time-changing properties of these frequencies. The power spectrum, continuous wavelet transform and Hilbert–Huang transform are applied on a continuous blood pressure signal to investigate how the different methods compare to each other. The Hilbert–Huang transform shows high ability to analyze such data, and can, by identifying instantaneous frequency shifts, provide new insights into the nature of these kinds of data.

The aim of this study was to construct a glucose regulatory algorithm by employing the natural pulsatile pattern of insulin secretion and the oscillatory pattern of resting blood glucose levels and further to regulate the blood glucose level in diabetic pigs by this method. We developed a control algorithm based on repetitive intravenous bolus injections of insulin and combined this with an intravascular blood glucose monitor. Four anesthetized pigs were used in the study. The animals developed a mildly diabetic state from streptozotocin pretreatment. They were steadily brought within the blood glucose target range of 4.5–6.0 mmol/L in 21 to 121 min and kept within that range for 128 to 238 min (hypoglycemic values varied from 2.9 to 51.1 min). The study confirmed our hypotheses regarding the feasibility of this new principle for blood glucose control, and the algorithm was constantly improved during the study to produce the best results in the last animals. The main obstacles were the drift of the IvS-1 sensor and problems with the calibration procedure, which calls for an improvement in the sensor stability before this method can be applied fully in new studies in animals and humans. Copyright © 2013 Nils K. Skjaervold et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Our group is attempting to construct an artificial pancreas based on intravenous glucose monitoring and intravenous insulin delivery. To do so, the pharmacology of intravenous insulin administration must be studied. We used a pig model to determine the inherent lag time in the insulin/blood glucose system. The goal was to suggest a method that reduces the blood glucose level in a rapid and yet predictable manner.Six pigs received continuous intravenous insulin infusions at 0.04, 0.08, or 0.4 IU/kg/h for 60 min. Two pigs received short-term intravenous infusions at 0.4 IU/kg/h for 2 min, repeated five times at 60-min intervals. Four animals received five intravenous insulin bolus injections at 60-min intervals, two at 0.01 IU/kg and two 0.02 IU/kg, with a final dose of 0.04 IU/kg. The blood glucose level was measured every 1-5 min.A high rate of intravenous insulin infusion led to rapid declines in blood glucose levels. The same rapid decline was achieved when the infusion was halted after 2 min. Using the latter method and with intravenous insulin boluses, blood glucose levels started to rise again after approximately 15-20 min. Insulin boluses led to a first detectable decrease in blood glucose level after 2-6 min and to a maximum rate of decrease shortly thereafter.We found that intravenous bolus injections of insulin lowered blood glucose levels rapidly and predictably. Repetitive small intravenous insulin boluses together with an accurate and fast-responding intravascular continuous glucose monitor should be studied as a method of closed-loop glycemic control.