Anesthesia Patient Monitoring 2050.

The monitoring of vital signs in patients undergoing anesthesia began with the very first case of anesthesia and has evolved alongside the development of anesthesiology ever since. Patient monitoring started out as a manually performed, intermittent, and qualitative assessment of the patient's general well-being in the operating room. In its evolution, patient monitoring development has responded to the clinical need, for example, when critical incident studies in the 1980s found that many anesthesia adverse events could be prevented by improved monitoring, especially respiratory monitoring. It also facilitated and perhaps even enabled increasingly complex surgeries in increasingly higher-risk patients. For example, it would be very challenging to perform and provide anesthesia care during some of the very complex cardiovascular surgeries that are almost routine today without being able to simultaneously and reliably monitor multiple pressures in a variety of places in the circulatory system. Of course, anesthesia patient monitoring itself is enabled by technological developments in the world outside of the operating room. Throughout its history, anesthesia patient monitoring has taken advantage of advancements in material science (when nonthrombogenic polymers allowed the design of intravascular catheters, for example), in electronics and transducers, in computers, in displays, in information technology, and so forth. Slower product life cycles in medical devices mean that by carefully observing technologies such as consumer electronics, including user interfaces, it is possible to peek ahead and estimate with confidence the foundational technologies that will be used by patient monitors in the near future. Just as the discipline of anesthesiology has, the patient monitoring that accompanies it has come a long way from its beginnings in the mid-19th century. Extrapolating from careful observations of the prevailing trends that have shaped anesthesia patient monitoring historically, patient monitoring in the future will use noncontact technologies, will predict the trajectory of a patient's vital signs, will add regional vital signs to the current systemic ones, and will facilitate directed and supervised anesthesia care over the broader scope that anesthesia will be responsible for.

The effects of physical and temporal certainty on human locomotion with discrete underfoot perturbations.

Foot placement can be selected to anticipate upcoming perturbations, but it is unclear how this anticipatory strategy is influenced by available response time or precise knowledge of the perturbation's characteristics. This study investigates anticipatory and reactive locomotor strategies for repeated underfoot perturbations with varying levels of temporal certainty, physical certainty, and available response time. Thirteen healthy adults walked with random underfoot perturbations from a mechanized shoe. Temporal certainty was challenged by presenting the perturbations with or without warning. Available response time was challenged by adjusting the timing of the warning before the perturbation. Physical certainty was challenged by making perturbation direction (inversion or eversion) unpredictable for certain conditions. Linear-mixed effects models assessed the effect of each condition on the percentage change of margin of stability and step width. For perturbations with one stride or less of response time, we observed few changes to step width or margin of stability. As response time increased to two strides, participants adopted wider steps in anticipation of the perturbation (P=0.001). Physical certainty had little effect on gait for the step of the perturbation, but participants recovered normal gait sooner when the physical nature of the perturbation was predictable (P<0.001). Despite having information about the timing and direction of upcoming perturbations, individuals do not develop perturbation-specific feedforward strategies. Instead, they use feedback control to recover normal gait after a perturbation. However, physical certainty appears to make the feedback controller more efficient and allows individuals to recover normal gait sooner.

Noninvasive Urine Oxygen Monitoring and the Risk of Acute Kidney Injury in Cardiac Surgery.

BACKGROUND: Acute kidney injury (AKI) is a common complication of cardiac surgery. An intraoperative monitor of kidney perfusion is needed to identify patients at risk for AKI. The authors created a noninvasive urinary oximeter that provides continuous measurements of urinary oxygen partial pressure and instantaneous urine flow. They hypothesized that intraoperative urinary oxygen partial pressure measurements are feasible with this prototype device and that low urinary oxygen partial pressure during cardiac surgery is associated with the subsequent development of AKI. METHODS: This was a prospective observational pilot study. Continuous urinary oxygen partial pressure and instantaneous urine flow were measured in 91 patients undergoing cardiac surgery using a novel device placed between the urinary catheter and collecting bag. Data were collected throughout the surgery and for 24 h postoperatively. Clinicians were blinded to the intraoperative urinary oxygen partial pressure and instantaneous flow data. Patients were then followed postoperatively, and the incidence of AKI was compared to urinary oxygen partial pressure measurements. RESULTS: Intraoperative urinary oxygen partial pressure measurements were feasible in 86/91 (95%) of patients. When urinary oxygen partial pressure data were filtered for valid urine flows greater than 0.5 ml · kg-1 · h-1, then 70/86 (81%) and 77/86 (90%) of patients in the cardiopulmonary bypass (CPB) and post-CPB periods, respectively, were included in the analysis. Mean urinary oxygen partial pressure in the post-CPB period was significantly lower in patients who subsequently developed AKI than in those who did not (mean difference, 6 mmHg; 95% CI, 0 to 11; P = 0.038). In a multivariable analysis, mean urinary oxygen partial pressure during the post-CPB period remained an independent risk factor for AKI (relative risk, 0.82; 95% CI, 0.71 to 0.95; P = 0.009 for every 10-mmHg increase in mean urinary oxygen partial pressure). CONCLUSIONS: Low urinary oxygen partial pressures after CPB may be associated with the subsequent development of AKI after cardiac surgery.

Diversity of electroencephalographic patterns during propofol-induced burst suppression.

Burst suppression is a brain state consisting of high-amplitude electrical activity alternating with periods of quieter suppression that can be brought about by disease or by certain anesthetics. Although burst suppression has been studied for decades, few studies have investigated the diverse manifestations of this state within and between human subjects. As part of a clinical trial examining the antidepressant effects of propofol, we gathered burst suppression electroencephalographic (EEG) data from 114 propofol infusions across 21 human subjects with treatment-resistant depression. This data was examined with the objective of describing and quantifying electrical signal diversity. We observed three types of EEG burst activity: canonical broadband bursts (as frequently described in the literature), spindles (narrow-band oscillations reminiscent of sleep spindles), and a new feature that we call low-frequency bursts (LFBs), which are brief deflections of mainly sub-3-Hz power. These three features were distinct in both the time and frequency domains and their occurrence differed significantly across subjects, with some subjects showing many LFBs or spindles and others showing very few. Spectral-power makeup of each feature was also significantly different across subjects. In a subset of nine participants with high-density EEG recordings, we noted that each feature had a unique spatial pattern of amplitude and polarity when measured across the scalp. Finally, we observed that the Bispectral Index Monitor, a commonly used clinical EEG monitor, does not account for the diversity of EEG features when processing the burst suppression state. Overall, this study describes and quantifies variation in the burst suppression EEG state across subjects and repeated infusions of propofol. These findings have implications for the understanding of brain activity under anesthesia and for individualized dosing of anesthetic drugs.

Propofol for treatment resistant depression: A randomized controlled trial.

Background: Anesthetic agents including ketamine and nitrous oxide have shown antidepressant properties when appropriately dosed. Our recent open-label trial of propofol, an intravenous anesthetic known to elicit transient positive mood effects, suggested that it may also produce robust and durable antidepressant effects when administered at a high dose that elicits an electroencephalographic (EEG) burst-suppression state. Here we report findings from a randomized controlled trial ( NCT03684447 ) that compared two doses of propofol. We hypothesized greater improvement with a high dose that evoked burst suppression versus a low dose that did not. Methods: Participants with moderate-to-severe, treatment-resistant depression were randomized to a series of 6 treatments at low versus high dose (n=12 per group). Propofol infusions were guided by real-time processed frontal EEG to achieve predetermined pharmacodynamic criteria. The primary and secondary depression outcome measures were the 24-item Hamilton Depression Rating Scale (HDRS-24) and the Patient Health Questionnaire (PHQ-9), respectively. Secondary scales measured suicidal ideation, anxiety, functional impairment, and quality of life. Results: Treatments were well tolerated and blinding procedures were effective. The mean [95%-CI] change in HDRS-24 score was -5.3 [-10.3, -0.2] for the low-dose group and -9.3 [-12.9, -5.6] for the high-dose group (17% versus 33% reduction). The between-group effect size (standardized mean difference) was -0.56 [-1.39, 0.28]. The group difference was not statistically significant (p=0.24, linear model). The mean change in PHQ-9 score was -2.0 [-3.9, -0.1] for the low dose and -4.8 [-7.7, -2.0] for the high dose. The between-group effect size was -0.73 [-1.59, 0.14] (p=0.09). Secondary outcomes favored the high dose (effect sizes magnitudes 0.1 - 0.9) but did not generally reach statistical significance (p>0.05). Conclusions: The medium-sized effects observed between doses in this small, controlled, clinical trial suggest that propofol may have dose-dependent antidepressant effects. The findings also provide guidance for subsequent trials. A larger sample size and additional treatments in series are likely to enhance the ability to detect dose-dependent effects. Future work is warranted to investigate potential antidepressant mechanisms and dose optimization.