Sedation is required to tolerate mechanical ventilation in patients with sepsis and septic shock. Caution should be used with dosing strategies in this patient population. It is recommended that an analgesia-first approach be used, and sedatives added as needed. Propofol and dexmedetomidine are the preferred agents, as recommended by the Society for Critical Care Medicine's Assess, Prevent, and Manage Pain, Both Spontaneous Awakening Trials and Spontaneous Breathing Trials, Choice of analgesia and sedation, Delirium: Assess, Prevent, and Manage, Early mobility and Exercise, and Family engagement and empowerment bundle. Further research is needed for best practices in patients requiring higher-dose sedatives.

Background Inflammation is a sequela of cardiovascular critical illness and a risk factor for mortality. Objectives This study aimed to evaluate the association between white blood cell count (WBC) and mortality in a broad population of patients admitted to the cardiac intensive care unit (CICU). Methods This retrospective cohort study included patients admitted to the Mayo Clinic CICU between 2007 and 2018. We analyzed WBC as a continuous variable and then categorized WBC as low (<4.0 x 10(3)/mL), normal (>= 4.0 to <11.0 x 10(3)/mL), high (>= 11.0 to <22.0 x 10(3)/mL), or very high (>= 22.0 x 10(3)/mL). The association between WBC and in-hospital mortality was evaluated using multivariable logistic regression and random forest models. Results We included 11,699 patients with a median age of 69.3 years (37.6% females). Median WBC was 9.6 (IQR: 7.4-12.7). Mortality was higher in the low (10.5%), high (12.0%), and very high (33.3%) WBC groups relative to the normal WBC group (5.3%). A rising WBC was incrementally associated with higher in-hospital mortality after adjustment (AICc adjusted OR: 1.03 [95% CI: 1.02-1.04] per 1 x 10(3) increase in WBC). After adjustment, only the high (AICc adjusted OR: 1.37 [95% CI: 1.15-1.64]) and very high (AICc adjusted OR: 1.99 [1.47-2.71]) WBC groups remained associated with increased risk of in-hospital mortality. Conclusions Leukocytosis is associated with an increased mortality risk in a diverse cohort of CICU patients. This readily available marker of systemic inflammation may be useful for risk stratification within the increasingly complex CICU patient population.

Limited data exist regarding outcomes after coronary angiography (CAG) and percutaneous coronary intervention (PCI) in patients aged ≥90 years admitted to the cardiac intensive care unit (CICU) with acute coronary syndrome (ACS). We studied sequential CICU patients ≥90 years admitted with ACS from 2007 to 2018. Three therapeutic approaches were defined: (1) No CAG; (2) CAG without PCI (CAG/No PCI); and (3) CAG with PCI (CAG/PCI). In-hospital mortality was evaluated using multivariable logistic regression. All-cause 1-year mortality was evaluated using Kaplan-Meier and multivariable Cox proportional hazards analysis. The study included 239 patients with a median age of 92 (range 90 to 100) years (57% females; 45% ST-elevation myocardial infarction; 8% cardiac arrest; 16% shock). The No CAG group had higher Day 1 Sequential Organ Failure Assessment scores, more co-morbidities, worse kidney function, and fewer ST-elevation myocardial infarctions. In-hospital mortality was 20.8% overall and did not differ between the No CAG (n = 103; 21.4%), CAG/No PCI (n = 47; 21.3%), and CAG/PCI (n = 90; 20.0%) groups, before or after adjustment. Overall 1-year mortality was 52.5% and did not differ between groups before or after adjustment. Median survival was 6.9 months overall and 41.2% of hospital survivors died within 1 year of CICU admission. CICU patients aged ≥90 years with ACS have a substantial burden of illness with high in-hospital and 1-year mortality that was not lower in those who underwent CAG or PCI. These results suggest that careful patient selection for invasive coronary procedures is essential in this vulnerable population.

Introduction: Patients with sepsis who need intensive care unit (ICU) admission for short-term monitoring (< 48 hr) with low-dose vasopressors could be candidates for minimally invasive sepsis (MIS) approach outside the ICU. We aimed to describe such patients and develop a prediction model to find candidates for MIS approach. Methods: In a secondary analysis of institutional data, we identified adults (≥18 yr) with septic shock admitted to the Mayo Clinic medical ICU from emergency. MIS approach candidates were with < 48 hr of ICU stay, without advanced respiratory support or renal replacement therapy and alive at ICU & hospital discharge. Comparison group consisted of septic shock patients with an ICU stay of >48 hr who didn’t need advanced respiratory support before ICU admission. Wilcoxon rank, Chi Square, and Fisher’s exact tests were used to compare baseline characteristics. Logistic regression and prediction profiler were used to select predictive variables and assign cut-offs. Using points assigned to variables based on OR and clinical rational, a nominal logistic regression model was created. Model discrimination & calibration were assessed by receiver operating characteristic (ROC) curves and Hosmer-Lemeshow (H-L) goodness-of-fit test. Results: Out of 1795 MICU admissions, 109 patients (6 %) met MIS approach criteria and 97 in comparison group. MIS group was younger with lower respiratory rate, temperature, lactate, creatinine, BUN, and WBCs (p < 0.05 for all). Predictive variables (age >65 yr, O2 flow >4 L/mint, temperature < 37℃, creatinine >1.6 mg/dL, lactate >3 mmol/L, WBCs >15x109, heart rate >100 beats/mint, and respiration rate >25 breaths/ mint) were translated into an 8-point score. Model discrimination yielded ROC: AUC of 80%. Model fit was confirmed by agreement between observed and predicted probability and was well calibrated (H-L p = 0.94). MIS score cut-off of 3 resulted in a predictive model OR of 0.15 (CI: 0.08–0.28) and a negative predictive value of 91% [(CI: 88.69-92.92) (using prevalence of MIS patients ~20%)] Conclusions: Study implies that a significant minority of sepsis patients can be managed outside the ICU. Once validated in an independent, prospective sample our prediction model can be used to identify candidates for minimally invasive management outside of ICU

Objective: To identify and describe characteristics of patients with sepsis who could be treated with minimally invasive sepsis (MIS) approach without intensive care unit (ICU) admission and to develop a prediction model to select candidates for MIS approach. Methods: A secondary analysis of the electronic database of patients with sepsis at Mayo Clinic, Rochester, MN. Candidates for the MIS approach were adults with septic shock and less than 48 hours of ICU stay, who did not require advanced respiratory support and were alive at hospital discharge. Comparison group consisted of septic shock patients with an ICU stay of more than 48 hours without advanced respiratory support at the time of ICU admission. Results: Of 1795 medical ICU admissions, 106 patients (6%) met MIS approach criteria. Predictive variables (age >65 years, oxygen flow >4 L/min, temperature <37 degrees C, creatinine >1.6 mg/dL, lactate >3 mmol/L, white blood cells >15 x 10(9)/L, heart rate >100 beats/min, and respiration rate >25 breaths/min) selected through logistic regression were translated into an 8-point score. Model discrimination yielded the area under the receiver operating characteristic curve of 79% and was well fitted (Hosmer-Lemeshow P = 0.94) and calibrated. The MIS score cutoff of 3 resulted in a model odds ratio of 0.15 (95% confidence interval, 0.08-0.28) and a negative predictive value of 91% (95% confidence interval, 88.69-92.92). Conclusions: This study identifies a subset of low-risk septic shock patients who can potentially be managed outside the ICU. Once validated in an independent, prospective sample our prediction model can be used to identify candidates for MIS approach.

We compared three hospitalized patient cohorts and conducted mechanistic studies to determine if lipotoxicity worsens COVID-19. Cohort-1 (n = 30) compared COVID-19 patients dismissed home to those requiring intensive-care unit (ICU) transfer. Cohort-2 (n = 116) compared critically ill ICU patients with and without COVID-19. Cohort-3 (n = 3969) studied hypoalbuminemia and hypocalcemia's impact on COVID-19 mortality. Patients requiring ICU transfer had higher serum albumin unbound linoleic acid (LA). Unbound fatty acids and LA were elevated in ICU transfers, COVID-19 ICU patients and ICU non-survivors. COVID-19 ICU patients (cohort-2) had greater serum lipase, damage-associated molecular patterns (DAMPs), cytokines, hypocalcemia, hypoalbuminemia, organ failure and thrombotic events. Hypocalcemia and hypoalbuminemia independently associated with COVID-19 mortality in cohort-3. Experimentally, LA reacted with albumin, calcium and induced hypocalcemia, hypoalbuminemia in mice. Endothelial cells took up unbound LA, which depolarized their mitochondria. Inmice, unbound LA increased DAMPs, cytokines, causing endothelial injury, organ failure and thrombosis. Therefore, excessive unbound LA in the circulation may worsen COVID-19 outcomes.

Background Neuroinflammation causing disruption of the blood-brain barrier and immune cell extravasation into the brain parenchyma may cause delirium; however, knowledge of the exact pathophysiologic mechanism remains incomplete. The purpose of our study was to determine whether cytokine profiles differ depending on whether delirium occurs in the setting of sepsis, coronavirus disease 2019 (COVID-19), or recent surgery. Methods This prospective observational cohort study involved 119 critically ill patients admitted to a multidisciplinary intensive care unit (ICU) during 2019 and 2020. Delirium was identified using the validated confusion assessment method for the ICU. Multiple delirium risk factors were collected daily including clinical characteristics, hospital course, lab values, vital signs, surgical exposure, drug exposure, and COVID-19 characteristics. Serums samples were collected within 12 hours of ICU admission and cytokine levels were measured. Results: The following proinflammatory cytokines were elevated in our delirium population: tumor necrosis factor (TNF)-α, interleukin (IL)-6, IL-18, C-C motif ligand (CCL) 2, CCL3, C-X-C motif chemokine ligand (CXCL)1, CXCL10, IL-8, IL-1 receptor antagonist, and IL-10. Analysis of relative cytokine levels in those patients that developed delirium in the setting of sepsis, COVID-19, and recent surgery showed elevations of CCL2, CXCL10, and TNF-α in both the sepsis and COVID-19 group in comparison to the postsurgical population. In the postsurgical group, granulocyte colony-stimulating factor was elevated and CXCL10 was decreased relative to the opposing groups. Conclusions We identify several cytokines and precipitating factors known to be associated with delirium. However, our study suggests that the cytokine profile associated with delirium is variable and contingent upon delirium precipitating factors.

Background: Delirium is common in patients with severe coronavirus disease-19 (COVID-19). The purpose of our study was to determine whether severe COVID-19 is an independent risk factor for the development of delirium in patients treated in the intensive care unit (ICU). Methods: This prospective observational cohort study involved 162 critically ill patients admitted to a multidisciplinary ICU during 2019 and 2020. A validated screening tool was used to diagnose delirium. Multiple delirium risk factors were collected daily including clinical characteristics, hospital course, lab values, vital signs, surgical exposure, drug exposure, and COVID-19 characteristics. After univariate analysis, a multivariate logistic regression analysis was performed to determine independent risk factors associated with the development of delirium. Results: In our study population, 50 (31%) patients developed delirium. A total of 39 (24.1%) tested positive for COVID-19. Initial analysis showed COVID-19 to be more prevalent in those patients that developed delirium (40% vs. 17%; P = 0.003). Multivariate analysis showed opioid use (odds ratio [OR]: 24 [95% confidence intervals (CI): 16–27]; P ≤ 0.001), benzodiazepine use (OR: 23 [95% CI: 16–63] P = 0.001), and estimated mortality based on acute physiology and chronic health evaluation IV score (OR: 1.04 [95% CI: 1.01–1.07] P = 0.002) to be independently associated with delirium development. COVID-19 (OR: 1.44 [95% CI: 0.13–10.6]; P = 0.7) was not found to be associated with delirium. Conclusion: Delirium is prevalent in critically ill patients admitted to the ICU, including those with COVID-19. However, after adjustment for important covariates, we found in this cohort that COVID-19 was not an independent risk factor for delirium.

OBJECTIVES:The pathophysiology of delirium is complex and incompletely understood. Inflammation is hypothesized to be integral to its development due to effects on blood brain barrier integrity, facilitation of leukocyte extravasation into brain parenchyma, and propagation of neuroinflammation. Septic shock is the prototypical condition associated with ICU delirium; however, the relative contribution of resultant hypotension and systemic inflammation to the development of delirium is unknown. DESIGN:This was a prospective exploratory study. SETTING:A multidisciplinary ICU at an academic medical center in Phoenix, AZ. PATIENTS:Critically ill patients older than or equal to 18 years old admitted to the ICU. INTERVENTIONS:None. MEASUREMENTS AND MAIN RESULTS:Screening for delirium was performed using the Confusion Assessment Method for the ICU tool. The levels of C-C motif ligand 2 (CCL2), C-C motif ligand 3, C-X-C motif chemokine ligand 1, C-X-C motif chemokine ligand 10, and interleukin-8 were measured in serum samples obtained within 12 hours of ICU admission. Univariate and multivariate analyses were performed to assess the association of delirium with patient data pertaining to hospital course, laboratory values, vital signs, medication administration, and levels of the aforementioned chemokines. Forty-one of 119 patients (34.5%) in the study cohort developed ICU delirium. Each chemokine studied was associated with delirium on univariate analyses; however, CCL2 was the only chemokine found to be independently associated with the development of delirium on multivariable analysis. The association of increased CCL2 levels with delirium remained robust in various models controlling for age, presence of shock, Sequential Organ Failure Assessment score, Acute Physiology and Chronic Health Evaluation IV score, mean arterial pressure at presentation, lowest mean arterial pressure, and total opioid, midazolam, propofol, and dexmedetomidine exposure. CONCLUSIONS:The demonstrated relationship between CCL2 and delirium suggests this chemokine may play a role in the development of delirium and warrants further investigation.

Objective: Peripherally inserted central catheters are a popular means of obtaining central venous access in critically ill patients. However, there is limited data regarding the rapidity of the peripherally inserted central catheter procedure in the presence of acute illness or obesity, both of which may impede central venous catheter placement. We aimed to determine the feasibility, safety, and duration of peripherally inserted central catheter placement in critically ill patients, including obese patients and patients in shock. Methods: This retrospective cohort study was performed using data on 55 peripherally inserted central catheters placed in a 30-bed multidisciplinary intensive care unit in Mayo Clinic Hospital, Phoenix, Arizona. Information on the time required to complete each step of the peripherally inserted central catheter procedure, associated complications, and patient characteristics was obtained from a prospectively assembled internal quality assurance database created through random convenience sampling. Results: The Median Procedure Time, beginning with the first needle puncture and ending when the procedure is complete, was 14 (interquartile range: 9–20) min. Neither critical illness nor obesity resulted in a statistically significant increase in the time required to complete the peripherally inserted central catheter procedure. Three (5.5%) minor complications were observed. Conclusion: Critical illness and obesity do not delay the acquisition of vascular access when placing a peripherally inserted central catheter. Concerns of delayed vascular access in critically ill patients should not deter a physician from selecting a peripherally inserted central catheter to provide vascular access when it would otherwise be appropriate.

Objective. Dexterous movement involves the activation and coordination of networks of neuronal populations across multiple cortical regions. Attempts to model firing of individual neurons commonly treat the firing rate as directly modulating with motor behavior. However, motor behavior may additionally be associated with modulations in the activity and functional connectivity of neurons in a broader ensemble. Accounting for variations in neural ensemble connectivity may provide additional information about the behavior being performed. Approach. In this study, we examined neural ensemble activity in primary motor cortex (M1) and premotor cortex (PM) of two male rhesus monkeys during performance of a center-out reach, grasp and manipulate task. We constructed point process encoding models of neuronal firing that incorporated task-specific variations in the baseline firing rate as well as variations in functional connectivity with the neural ensemble. Models were evaluated both in terms of their encoding capabilities and their ability to properly classify the grasp being performed. Main results. Task-specific ensemble models correctly predicted the performed grasp with over 95% accuracy and were shown to outperform models of neuronal activity that assume only a variable baseline firing rate. Task-specific ensemble models exhibited superior decoding performance in 82% of units in both monkeys (p  <  0.01). Inclusion of ensemble activity also broadly improved the ability of models to describe observed spiking. Encoding performance of task-specific ensemble models, measured by spike timing predictability, improved upon baseline models in 62% of units. Significance. These results suggest that additional discriminative information about motor behavior found in the variations in functional connectivity of neuronal ensembles located in motor-related cortical regions is relevant to decode complex tasks such as grasping objects, and may serve the basis for more reliable and accurate neural prosthesis.

Robinette, Elizabeth; Weant, Kyle; Hassig, Tanna; Smith, Ryan; Field, Larry Author Information

ABSTRACT Introduction Electromyogram (EMG)-based pattern recognition control of prosthetic limbs is the current state of the art. However, these systems commonly fail when the user attempts to use the limb in a different position from which it was trained, resulting in significantly reduced functionality. Robust models for decoding EMG signals, accounting for specific changes that occur with positional variation, are needed to reduce this negative effect. Methods Ten able-bodied participants and two participants with transradial amputation were included in the study. Participants were fitted with surface EMG electrodes as well as a network of inertial measurement units (IMUs) to monitor limb position during tasks. Positional covariates including elbow angle, hand height, and forearm angle were analyzed for impact on EMG signal features to drive the generation of unique LDA classifier algorithms. Offline analysis of classification error for each control scheme was then completed. Results Elbow angle demonstrated the strongest impact on the EMG signal. Hand height also demonstrated a consistent increase in EMG signal with increasing height. Incorporating these specific covariates into classifier algorithms improved performance compared with classifiers trained in the conventional fashion (single-position EMG). However, able-bodied participants demonstrated lowest classification error when data from random-training positions were incorporated (10.3% vs. 17.2% single position, P < 0.001). These results were even more dramatic in participants with amputation (with five training repetitions: 7.14% vs. 32.08%, P < 0.001). Performance differences between single-position and random-position training for individuals with amputations were significantly larger when the user was wearing his/her prosthesis than otherwise. Conclusions Incorporating position-specific covariates into myoelectric classification algorithms can dramatically improve robustness and classification accuracy when using the prosthesis in the user's entire workspace. In single-position training paradigms, classification error rates were 39.22% and 32.18%, respectively, for two participants with amputation and resulted in unusable classifiers. Conversely, classification errors were at 10% for able-bodied and near 7% for participants with amputation when at least five training repetitions were used to train either a random position or position-specific classifier. As position-tracking hardware becomes smaller and can be implemented into socket designs, incorporating this information into classifier algorithms can dramatically reduce the limb-position effect. Current users can experience reduction of the limb-position effect through training in multiple random positions.

Brain-machine interfaces (BMIs) are a rapidly progressing technology with the potential to restore function to victims of severe paralysis via neural control of robotic systems. Great strides have been made in directly mapping a user's cortical activity to control of the individual degrees of freedom of robotic end-effectors. While BMIs have yet to achieve the level of reliability desired for widespread clinical use, environmental sensors (e.g., RGB-D cameras for object detection) and prior knowledge of commonmovement trajectories hold great potential for improving system performance. Here, we present a novel sensor fusion paradigm for BMIs that capitalizes on information able to be extracted from the environment to greatly improve the performance of control. This was accomplished by using dynamic movement primitives to model the 3-D endpoint trajectories of manipulating various objects. We then used a switching unscented Kalman filter to continuously arbitrate between the 3-D endpoint kinematics predicted by the dynamic movement primitives and control derived from neural signals. We experimentally validated our system by decoding 3-D endpoint trajectories executed by a nonhuman primate manipulating four different objects at various locations. Performance using our system showed a dramatic improvement over using neural signals alone, with median distance between actual and decoded trajectories decreasing from 31.1 to 9.9 cm, and mean correlation increasing from 0.80 to 0.98. Our results indicate that our sensor fusion framework can dramatically increase the fidelity of neural prosthetic trajectory decoding.

(1) Abbasi-Asl, Reza Explaining V4 Neuron’s’ Pattern Selectivity via Convolutional Neural Network (2) Adams, Terrence Development of a Big Data Framework for Connectomic Research (3) Agarwal, Rahul Nonparametric Estimation of Band-limited Probability Density Functions: Application to Rat Entorhinal Cortical Neuron (4) Best, Matthew Using spatial patterns of primary motor corical activity to predict behavioral state (5) Brigham, Marco Non-stationary filtered shot noise processes and applications to neuronal membranes (6) Chase, Steve Recasting brain-machine interface design from a physical control system perspective (7) Climer, Jason Examining rhythmicity in extracellular recordings (8) Coffman, Brian Event-related potentials demonstrate deficits in auditory gestalt formation in schizophrenia (9) Constantino, Francisco Neural rhythm synchronizes with imagined acoustic rhythm (10) David, Stephen More isn’t always better: The essential complexity of auditory receptive fields (11) Deng, Xinyi Clusterless decoding of postion from multiunity activity using a marked point process filter (12) Dimitrov, Alex Characterizing local invariances in the ascending ferret auditory system (13) DiTullo, Ron Hypothesis testing of grid cell parameters using a maximum likelihood framework (14) Dyer, Eva Quantifying mesoscale neuroanatomy with X-ray micotomography (15) Effenberger, Felix Discovery of salient low-dimensional dynamical structure in neuronal population activity using Hopfield networks (16) Ezennaya-Gomez, Salatiel Detecting statistically significant synchronous spiking activity (17) Gao, Yu-Rong Using the Thresholded in Radon Space (TiRS) algoirthm to reveal mechanical restriction of intracortical vessel dilation during voluntary locomotion (18) Gerhard, Felipe Generative models to discover structure in neural recordings of human focal epilepsy

Myoelectric control of prosthetic devices tend to rely on classification schemes of extracted features of EMG data. Those features however, may be sensitive to arm position resulting in decreased performance in real-world applications. The effect of varying limb position in a pattern recognition system have been illustrated by documenting the change in classification accuracy as the user achieves particular limb configurations. We continue to investigate this limb position effect by observing its impact on classification accuracy as well as through an analysis of how each extracted feature of the raw EMG varies in each position. Finally, LDA classification schemes are applied both to demonstrate the effect varying limb position has on classification accuracy and to increase classification accuracy without the use of additional hardware or sensors such as accelerometers as has been done in the past. It is shown that high classification accuracy can be achieved by (1) training an LDA classifier with data from many positions, as well as (2) by utilizing an extra position LDA classifier which can weigh the grasp classifiers appropriately. The classification accuracies achieved by these methods approached that of a model relying on a perfect knowledge of arm position.

This study presents a novel adaptive myoelectric decoding algorithm for control of upper limb prosthesis. Myoelectric decoding algorithms are inherently subject to decay in decoding accuracy over time, which is caused by the changes occurring in the muscle signals. The proposed algorithm relies on an unsupervised and on demand update of the training set, and has been designed to adapt to both the slow and fast changes that occur in myoelectric signals. An update in the training data is used to counter the slow changes, whereas an update with label correction addresses the fast changes in the signals. We collected myoelectric data from an able bodied user for over four and a half hours, while the user performed repetitions of eight wrist movements. The major benefit of the proposed algorithm is the lower rate of decay in accuracy; it has a decay rate of 0.2 per hour as opposed to 3.3 for the non adaptive classifier. The results show that, long term decoding accuracy in EMG signals can be maintained over time, improving the performance and reliability of myoelectric prosthesis.

Dexterous manipulation of a multi-fingered prosthetic hand requires far more cognitive effort compared to typical 1 degree of freedom hands, which hinders their acceptance clinically. This paper presents a Myoelectrically-Operated Radio Frequency Identification (RFID) Prosthetic Hand (MORPH); an implementation of RFID with a myoelectric prosthetic hand as a means to amplify the controllable degrees of freedom. Contextual information from an object equipped with an RFID tag allows automatic preshaping along with dexterous control in an attempt to reduce the cognitive effort required to operate the terminal device. The myoelectric-RFID hybrid has been demonstrated in a proof-of-concept case study where an amputee was fitted with the device and subjected to activities adapted from the Jebsen Hand Function Test and the Smith Hand Function Evaluation with RFID-tagged and untagged items. Evaluation tests revealed that the MORPH system performed significantly better in 4 of the 8 tasks, and comparable to the control in the remainder.