Outcomes of Six Specific Types of Post-Hospital Brain Injury Rehabilitation Programs.

OBJECTIVE: Evaluate outcomes of intensive posthospital brain injury rehabilitation programs compared to supported living (SL) programs; explore variations in outcome by diagnostic category (traumatic brain injury, stroke, and other acquired brain injury [ABI]) and specific program type. SETTING: Data were obtained from Residential Neurobehavioral, Residential Neurorehabilitation, Home and Community Neurorehabilitation, Day Treatment, Outpatient Neurorehabilitation, and SL programs serving individuals with ABI. PARTICIPANTS: A total of 2120 individuals with traumatic brain injury, stroke, or other ABI participated in this study. MAIN MEASURES: The main measures are sex, age, time since injury, and Mayo-Portland Adaptability Inventory (4th edition; MPAI-4). DESIGN: Retrospective analyses of demographic variables and MPAI-4 Total, index, and subscale Rasch-derived T-scores on admission and discharge. RESULTS: Gains on MPAI-4  Total T-scores were significantly greater for the intensive rehabilitation (IR) group in comparison to stable functioning in the SL group (F = 236.69, P < .001, partial η2 = .101) while controlling for admission/time 1 scores; similar results were found for MPAI-4 indices and subscales. For the IR cohort, discharge scores differed by diagnostic category after controlling for admission scores for the Total MPAI-4 T-score (F = 22.65, P < .001, partial η2 = .025), as well as all indices and subscales. A statistically significant interaction between program type and diagnostic group on discharge MPAI-4 Total T-scores (F = 2.55, P = .018, partial η2 = .01) after controlling for admission scores indicated that differing outcomes across diagnoses also varied by program type. Varying significant main effects and interactions were apparent for MPAI-4 indices and subscales with generally small effect sizes. CONCLUSIONS: Significant gains on MPAI-4 variables across IR program types compared to no change over a comparable period of time for SL programs supports the effectiveness of posthospital brain injury rehabilitation. This finding in the presence of small effect sizes on outcome variables for program type and for significant interactions between program type and diagnostic category suggests that participants generally were appropriately matched to program type and benefited from interventions provided through specific program types.

Distinguishing Characteristics of Admissions to Various Types of Posthospital Brain Injury Rehabilitation Programs.

OBJECTIVE: Describe and compare the demographic characteristics and disability profiles of individuals admitted to 6 types of posthospital brain injury rehabilitation (PHBIR) programs. SETTING: Data from Residential Neurobehavioral, Residential Neurorehabilitation, Home and Community Neurorehabilitation, Day Treatment, Outpatient Neurorehabilitation, and Supported Living programs serving individuals with acquired brain injury (ABI). PARTICIPANTS: Two thousand twenty-eight individuals with traumatic brain injury (TBI), stroke, or other ABI. MAIN MEASURES: Sex, age, time since injury, and Mayo-Portland Adaptability Inventory, 4th edition (MPAI-4). DESIGN: Retrospective analyses of demographic variables and MPAI-4 Total, Index, and subscale Rasch-derived T-scores on admission comparing diagnostic categories and program types within diagnostic categories. RESULTS: Participants with TBI were predominantly male, and those with stroke were generally older. Admissions to more intensive and supervised programs (residential neurobehavioral and residential neurorehabilitation) generally showed greater disability than admissions to home and community programs who were more disabled than participants in day treatment and outpatient programs. Residential neurobehavioral and supported living program participants generally were male and had TBI. Home and community admissions tended to be more delayed than residential neurorehabilitation admissions. The majority of those with other ABI were admitted to outpatient rather than more intensive programs. Additional analyses demonstrated significant differences in MPAI-4 profiles among the various program types. CONCLUSIONS: Admissions with TBI, stroke, and other ABI to PHBIR differ in demographic factors and disability profiles. When examined within each diagnostic category, demographic features and disability profiles also distinguish among admissions to the various program types. Results provide insights about decision-making in referral patterns to various types of PHBIR programs, although other factors not available for analysis (eg, participant/family preference, program, and funding availability) likely also contribute to admission patterns.

DNA barcoding aids in generating a preliminary checklist of the lichens and allied fungi of Calvert Island, British Columbia: Results from the 2018 Hakai Terrestrial BioBlitz.

Background: Bioblitzes are a tool for the rapid appraisal of biodiversity and are particularly useful in remote and understudied regions and for understudied taxa. Lichens are an example of an often overlooked group, despite being widespread in virtually all terrestrial ecosystems and having many important ecological functions. New information: We report the lichens and allied fungi collected during the 2018 terrestrial bioblitz conducted on Calvert Island on the Central Coast of British Columbia, Canada. We identified 449 specimens belonging to 189 species in 85 genera, increasing the total number of species known from Calvert Island to 194, and generated Internal Transcribed Spacer (ITS) sequences for 215 specimens from 121 species. Bryoriafurcellata, Chaenothecopsislecanactidis and C.nigripunctata were collected for the first time in British Columbia. We also found Pseudocyphellariarainierensis, which is listed as Special Concern on the federal Species at Risk Act, and other rarely reported species in British Columbia including Opegraphasphaerophoricola, Protomicarealimosa, Raesaeneniahuuskonenii and Sareadifformis. We demonstrate that DNA barcoding improves the scope and accuracy of expert-led bioblitzes by facilitating the detection of cryptic species and allowing for consistent identification of chemically and morphologically overlapping taxa. Despite the spatial and temporal limitations of our study, the results highlight the value of intact forest ecosystems on the Central Coast of British Columbia for lichen biodiversity, education and conservation.

Deep learning-based facial analysis for predicting difficult videolaryngoscopy: a feasibility study.

While videolaryngoscopy has resulted in better overall success rates of tracheal intubation, airway assessment is still an important prerequisite for safe airway management. This study aimed to create an artificial intelligence model to identify difficult videolaryngoscopy using a neural network. Baseline characteristics, medical history, bedside examination and seven facial images were included as predictor variables. ResNet-18 was introduced to recognise images and extract features. Different machine learning algorithms were utilised to develop predictive models. A videolaryngoscopy view of Cormack-Lehane grade of 1 or 2 was classified as 'non-difficult', while grade 3 or 4 was classified as 'difficult'. A total of 5849 patients were included, of whom 5335 had non-difficult and 514 had difficult videolaryngoscopy. The facial model (only including facial images) using the Light Gradient Boosting Machine algorithm showed the highest area under the curve (95%CI) of 0.779 (0.733-0.825) with a sensitivity (95%CI) of 0.757 (0.650-0.845) and specificity (95%CI) of 0.721 (0.626-0.794) in the test set. Compared with bedside examination and multivariate scores (El-Ganzouri and Wilson), the facial model had significantly higher predictive performance (p < 0.001). Artificial intelligence-based facial analysis is a feasible technique for predicting difficulty during videolaryngoscopy, and the model developed using neural networks has higher predictive performance than traditional methods.

Postoperative pulmonary complications in older patients undergoing elective surgery with a supraglottic airway device or tracheal intubation.

The two most commonly used airway management techniques during general anaesthesia are supraglottic airway devices and tracheal tubes. In older patients undergoing elective non-cardiothoracic surgery under general anaesthesia with positive pressure ventilation, we hypothesised that a composite measure of in-hospital postoperative pulmonary complications would be less frequent when a supraglottic airway device was used compared with a tracheal tube. We studied patients aged ≥ 70 years in 17 clinical centres. Patients were allocated randomly to airway management with a supraglottic airway device or a tracheal tube. Between August 2016 and April 2020, 2900 patients were studied, of whom 2751 were included in the primary analysis (1387 with supraglottic airway device and 1364 with a tracheal tube). Pre-operatively, 2431 (88.4%) patients were estimated to have a postoperative pulmonary complication risk index of 1-2. Postoperative pulmonary complications, mostly coughing, occurred in 270 of 1387 patients (19.5%) allocated to a supraglottic airway device and 342 of 1364 patients (25.1%) assigned to a tracheal tube (absolute difference -5.6% (95%CI -8.7 to -2.5), risk ratio 0.78 (95%CI 0.67-0.89); p < 0.001). Among otherwise healthy older patients undergoing elective surgery under general anaesthesia with intra-operative positive pressure ventilation of their lungs, there were fewer postoperative pulmonary complications when the airway was managed with a supraglottic airway device compared with a tracheal tube.

Aerosol generation with the use of positive pressure ventilation via supraglottic airway devices: an observational study.

The amount of aerosol generation associated with the use of positive pressure ventilation via a supraglottic airway device has not been quantified. We conducted a two-group, two-centre, prospective cohort study in which we recruited 21 low-risk adult patients scheduled for elective surgery under general anaesthesia with second-generation supraglottic airway devices. An optical particle sizer and an isokinetic sampling probe were used to record particle concentrations per second at different size distributions (0.3-10 µm) during use as well as baseline levels during two common activities (conversation and coughing). There was a median (IQR [range]) peak increase of 2.8 (1.5-4.5 [1-28.1]) and 4.1 (2.0-7.1 [1-18.2]) times background concentrations during SAD insertion and removal. Most of the particles generated during supraglottic airway insertion (85.0%) and removal (85.3%) were < 3 µm diameter. Median (IQR [range]) aerosol concentration generated by insertion (1.1 (0.6-5.1 [0.2-22.3]) particles.cm-3 ) and removal (2.1 (0.5-3.0 [0.1-18.9]) particles.cm-3 ) of SADs were significantly lower than those produced during continuous talking (44.5 (28.3-70.5 [2.0-134.5]) particles.cm-3 ) and coughing (141.0 (98.3-202.8 [4.0-296.5]) particles.cm-3 ) (p < 0.001). The aerosol levels produced were similar with the two devices. The proportion of easily inhaled and small particles (<1 µm) produced during insertion (57.5%) and removal (57.5%) was much lower than during talking (99.1%) and coughing (99.6%). These results suggest that the use of supraglottic airway devices in low-risk patients, even with positive pressure ventilation, generates fewer aerosols than speaking and coughing in awake patients.

Magnetic Resonance Imaging for Monitoring of Hepatic Disease Induced by Ebola Virus: a Nonhuman Primate Proof-of-Concept Study.

Severe liver impairment is a well-known hallmark of Ebola virus disease (EVD). However, the role of hepatic involvement in EVD progression is understudied. Medical imaging in established animal models of EVD (e.g., nonhuman primates [NHPs]) can be a strong complement to traditional assays to better investigate this pathophysiological process in vivo and noninvasively. In this proof-of-concept study, we used longitudinal multiparametric magnetic resonance imaging (MRI) to characterize liver morphology and function in nine rhesus monkeys after exposure to Ebola virus (EBOV). Starting 5 days postexposure, MRI assessments of liver appearance, morphology, and size were consistently compatible with the presence of hepatic edema, inflammation, and congestion, leading to significant hepatomegaly at necropsy. MRI performed after injection of a hepatobiliary contrast agent demonstrated decreased liver signal on the day of euthanasia, suggesting progressive hepatocellular dysfunction and hepatic secretory impairment associated with EBOV infection. Importantly, MRI-assessed deterioration of biliary function was acute and progressed faster than changes in serum bilirubin concentrations. These findings suggest that longitudinal quantitative in vivo imaging may be a useful addition to standard biological assays to gain additional knowledge about organ pathophysiology in animal models of EVD. IMPORTANCE Severe liver impairment is a well-known hallmark of Ebola virus disease (EVD), but the contribution of hepatic pathophysiology to EVD progression is not fully understood. Noninvasive medical imaging of liver structure and function in well-established animal models of disease may shed light on this important aspect of EVD. In this proof-of-concept study, we used longitudinal magnetic resonance imaging (MRI) to characterize liver abnormalities and dysfunction in rhesus monkeys exposed to Ebola virus. The results indicate that in vivo MRI may be used as a noninvasive readout of organ pathophysiology in EVD and may be used in future animal studies to further characterize organ-specific damage of this condition, in addition to standard biological assays.

Computed Tomography Imaging for Monitoring of Marburg Virus Disease: a Nonhuman Primate Proof-Of-Concept Study.

Marburg virus (MARV) is a highly virulent zoonotic filovirid that causes Marburg virus disease (MVD) in humans. The pathogenesis of MVD remains poorly understood, partially due to the low number of cases that can be studied, the absence of state-of-the-art medical equipment in areas where cases are reported, and limitations on the number of animals that can be safely used in experimental studies under maximum containment animal biosafety level 4 conditions. Medical imaging modalities, such as whole-body computed tomography (CT), may help to describe disease progression in vivo, potentially replacing ethically contentious and logistically challenging serial euthanasia studies. Towards this vision, we performed a pilot study, during which we acquired whole-body CT images of 6 rhesus monkeys before and 7 to 9 days after intramuscular MARV exposure. We identified imaging abnormalities in the liver, spleen, and axillary lymph nodes that corresponded to clinical, virological, and gross pathological hallmarks of MVD in this animal model. Quantitative image analysis indicated hepatomegaly with a significant reduction in organ density (indicating fatty infiltration of the liver), splenomegaly, and edema that corresponded with gross pathological and histopathological findings. Our results indicated that CT imaging could be used to verify and quantify typical MVD pathogenesis versus altered, diminished, or absent disease severity or progression in the presence of candidate medical countermeasures, thus possibly reducing the number of animals needed and eliminating serial euthanasia. IMPORTANCE Marburg virus (MARV) is a highly virulent zoonotic filovirid that causes Marburg virus disease (MVD) in humans. Much is unknown about disease progression and, thus, prevention and treatment options are limited. Medical imaging modalities, such as whole-body computed tomography (CT), have the potential to improve understanding of MVD pathogenesis. Our study used CT to identify abnormalities in the liver, spleen, and axillary lymph nodes that corresponded to known clinical signs of MVD in this animal model. Our results indicated that CT imaging and analyses could be used to elucidate pathogenesis and possibly assess the efficacy of candidate treatments.

Longitudinal analyses using 18F-Fluorodeoxyglucose positron emission tomography with computed tomography as a measure of COVID-19 severity in the aged, young, and humanized ACE2 SARS-CoV-2 hamster models.

This study compared disease progression of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) in three different models of golden hamsters: aged (≈60 weeks old) wild-type (WT), young (6 weeks old) WT, and adult (14-22 weeks old) hamsters expressing the human-angiotensin-converting enzyme 2 (hACE2) receptor. After intranasal (IN) exposure to the SARS-CoV-2 Washington isolate (WA01/2020), 2-deoxy-2-[fluorine-18]fluoro-D-glucose positron emission tomography with computed tomography (18F-FDG PET/CT) was used to monitor disease progression in near real time and animals were euthanized at pre-determined time points to directly compare imaging findings with other disease parameters associated with coronavirus disease 2019 (COVID-19). Consistent with histopathology, 18F-FDG-PET/CT demonstrated that aged WT hamsters exposed to 105 plaque forming units (PFU) developed more severe and protracted pneumonia than young WT hamsters exposed to the same (or lower) dose or hACE2 hamsters exposed to a uniformly lethal dose of virus. Specifically, aged WT hamsters presented with a severe interstitial pneumonia through 8 d post-exposure (PE), while pulmonary regeneration was observed in young WT hamsters at that time. hACE2 hamsters exposed to 100 or 10 PFU virus presented with a minimal to mild hemorrhagic pneumonia but succumbed to SARS-CoV-2-related meningoencephalitis by 6 d PE, suggesting that this model might allow assessment of SARS-CoV-2 infection on the central nervous system (CNS). Our group is the first to use (18F-FDG) PET/CT to differentiate respiratory disease severity ranging from mild to severe in three COVID-19 hamster models. The non-invasive, serial measure of disease progression provided by PET/CT makes it a valuable tool for animal model characterization.

Deep-Learning-Based Whole-Lung and Lung-Lesion Quantification Despite Inconsistent Ground Truth: Application to Computerized Tomography in SARS-CoV-2 Nonhuman Primate Models.

RATIONALE AND OBJECTIVES: Animal modeling of infectious diseases such as coronavirus disease 2019 (COVID-19) is important for exploration of natural history, understanding of pathogenesis, and evaluation of countermeasures. Preclinical studies enable rigorous control of experimental conditions as well as pre-exposure baseline and longitudinal measurements, including medical imaging, that are often unavailable in the clinical research setting. Computerized tomography (CT) imaging provides important diagnostic, prognostic, and disease characterization to clinicians and clinical researchers. In that context, automated deep-learning systems for the analysis of CT imaging have been broadly proposed, but their practical utility has been limited. Manual outlining of the ground truth (i.e., lung-lesions) requires accurate distinctions between abnormal and normal tissues that often have vague boundaries and is subject to reader heterogeneity in interpretation. Indeed, this subjectivity is demonstrated as wide inconsistency in manual outlines among experts and from the same expert. The application of deep-learning data-science tools has been less well-evaluated in the preclinical setting, including in nonhuman primate (NHP) models of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection/COVID-19, in which the translation of human-derived deep-learning tools is challenging. The automated segmentation of the whole lung and lung lesions provides a potentially standardized and automated method to detect and quantify disease. MATERIALS AND METHODS: We used deep-learning-based quantification of the whole lung and lung lesions on CT scans of NHPs exposed to SARS-CoV-2. We proposed a novel multi-model ensemble technique to address the inconsistency in the ground truths for deep-learning-based automated segmentation of the whole lung and lung lesions. Multiple models were obtained by training the convolutional neural network (CNN) on different subsets of the training data instead of having a single model using the entire training dataset. Moreover, we employed a feature pyramid network (FPN), a CNN that provides predictions at different resolution levels, enabling the network to predict objects with wide size variations. RESULTS: We achieved an average of 99.4 and 60.2% Dice coefficients for whole-lung and lung-lesion segmentation, respectively. The proposed multi-model FPN outperformed well-accepted methods U-Net (50.5%), V-Net (54.5%), and Inception (53.4%) for the challenging lesion-segmentation task. We show the application of segmentation outputs for longitudinal quantification of lung disease in SARS-CoV-2-exposed and mock-exposed NHPs. CONCLUSION: Deep-learning methods should be optimally characterized for and targeted specifically to preclinical research needs in terms of impact, automation, and dynamic quantification independently from purely clinical applications.

Alternatives to remifentanil for the analgesic component of total intravenous anaesthesia: a narrative review.

Propfol-remifentanil-based total intravenous anaesthesia has dominated recent clinical practice due to its favourable pharmacokinetic profile. Interruption in remifentanil supply has presented an opportunity to diversify or even avoid the use of opioids and consider adjuncts to propofol-based total intravenous anaesthesia. Propofol, while a potent hypnotic, is not an effective analgesic. The administration of opioids, along with other adjuncts such as α-2 adrenoceptor agonists, magnesium, lidocaine, ketamine and nitrous oxide provide surgical anaesthesia and avoids large doses of propofol being required. We provide an overview of both target-control and manual infusion regimes for the alternative opioids: alfentanil, sufentanil and fentanyl. The optimal combination of hypnotic-opioid dose, titration sequence and anticipated additional postoperative analgesia required depend on the chosen combination. In addition, we include a brief discussion on the role of non-opioid adjuncts in total intravenous anaesthesia, suggested doses and expected reduction in propofol dose.

Toward the determination of sensitive and reliable whole-lung computed tomography features for robust standard radiomics and delta-radiomics analysis in a nonhuman primate model of coronavirus disease 2019.

Purpose: We propose a method to identify sensitive and reliable whole-lung radiomic features from computed tomography (CT) images in a nonhuman primate model of coronavirus disease 2019 (COVID-19). Criteria used for feature selection in this method may improve the performance and robustness of predictive models. Approach: Fourteen crab-eating macaques were assigned to two experimental groups and exposed to either severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) or a mock inoculum. High-resolution CT scans were acquired before exposure and on several post-exposure days. Lung volumes were segmented using a deep-learning methodology, and radiomic features were extracted from the original image. The reliability of each feature was assessed by the intraclass correlation coefficient (ICC) using the mock-exposed group data. The sensitivity of each feature was assessed using the virus-exposed group data by defining a factor R that estimates the excess of variation above the maximum normal variation computed in the mock-exposed group. R and ICC were used to rank features and identify non-sensitive and unstable features. Results: Out of 111 radiomic features, 43% had excellent reliability ( ICC > 0.90 ), and 55% had either good ( ICC > 0.75 ) or moderate ( ICC > 0.50 ) reliability. Nineteen features were not sensitive to the radiological manifestations of SARS-CoV-2 exposure. The sensitivity of features showed patterns that suggested a correlation with the radiological manifestations. Conclusions: Features were quantified and ranked based on their sensitivity and reliability. Features to be excluded to create more robust models were identified. Applicability to similar viral pneumonia studies is also possible.

Improved Durability to SARS-CoV-2 Vaccine Immunity following Coimmunization with Molecular Adjuvant Adenosine Deaminase-1.

Although severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) vaccines have demonstrated strong immunogenicity and protection against severe disease, concerns about the duration and breadth of these responses remain. In this study, we show that codelivery of plasmid-encoded adenosine deaminase-1 (pADA) with SARS-CoV-2 spike glycoprotein DNA enhances immune memory and durability in vivo. Coimmunized mice displayed increased spike-specific IgG of higher affinity and neutralizing capacity as compared with plasmid-encoded spike-only-immunized animals. Importantly, pADA significantly improved the longevity of these enhanced responses in vivo. This coincided with durable increases in frequencies of plasmablasts, receptor-binding domain-specific memory B cells, and SARS-CoV-2-specific T follicular helper cells. Increased spike-specific T cell polyfunctionality was also observed. Notably, animals coimmunized with pADA had significantly reduced viral loads compared with their nonadjuvanted counterparts in a SARS-CoV-2 infection model. These data suggest that pADA enhances immune memory and durability and supports further translational studies.

Peri-operative management of patients with Parkinson's disease.

Patients with Parkinson's disease are at higher risk of peri-operative medical and surgical complications. Multidisciplinary management, early recognition of potential complications, specialised care of medications and intra-operative protection of the vulnerable brain are all important aspects of the peri-operative management of patients with Parkinson's disease. Advances in continuous dopaminergic treatment, development of a peri-operative Parkinson's disease pathway and application of telemedicine are starting to play a role in improving peri-operative care. Management of patients with advanced Parkinson's disease is also evolving, with potential for incorporation of integrated care and changes in the anaesthetic management for deep brain stimulation surgery. There are new methods for localisation of target nuclei and increasing insight on the effects of anaesthetic drugs on microelectrode recordings and clinical outcomes. Parkinson's disease is a progressive disease, but management is improving with better peri-operative care for patients.

Peri-operative neurological monitoring with electroencephalography and cerebral oximetry: a narrative review.

Surgery and anaesthesia subject the brain to considerable stress in the peri-operative period. This may be caused by potentially neurotoxic anaesthetic drugs, impaired cerebral perfusion and reperfusion injury related to surgery or thromboembolic events. Patient monitoring using electroencephalogram and cerebral oximetry can assist in optimising depth of anaesthesia and assessment of cerebral metabolic activity. However, research findings have been contradictory as to whether these monitors can help ameliorate peri-operative neurocognitive complications. In this narrative review, we will discuss recent evidence in the use of electroencephalography and cerebral oximetry and the underlying scientific principles. It is important to appreciate the raw electroencephalographic changes under anaesthesia and those associated with ageing, in order to interpret depth of anaesthesia indices correctly. Cerebral oximetry is useful not only for the detection of cerebral desaturation but also to identify those patients who are particularly vulnerable to injury, for better risk stratification. An algorithm-based approach may be most effective in managing the episodes of cerebral desaturation.