Search

Spreading depolarizations (SDs) have been linked to infarct volume expansion following ischemic stroke. Therapeutic hypothermia provides a neuroprotective effect after ischemic stroke. This study aimed to evaluate the effect of hypothermia on the propagation of SDs and infarct volume in an ischemic swine model. Through left orbital exenteration, middle cerebral arteries were surgically occluded (MCAo) in 16 swine. Extensive craniotomy and durotomy were performed. Six hypothermic and five normothermic animals were included in the analysis. An intracranial temperature probe was placed right frontal subdural. One hour after ischemic onset, mild hypothermia was induced and eighteen hours of electrocorticographic (ECoG) and intrinsic optical signal (IOS) recordings were acquired. Postmortem, 4 mm-thick slices were stained with 2,3,5-triphenyltetrazolium chloride to estimate the infarct volume. Compared to normothermia (36.4 ± 0.4°C), hypothermia (32.3 ± 0.2°C) significantly reduced the frequency and expansion of SDs (ECoG: 3.5 ± 2.1, 73.2 ± 5.2% vs. 1.0 ± 0.7, 41.9 ± 21.8%; IOS 3.9 ± 0.4, 87.6 ± 12.0% vs. 1.4 ± 0.7, 67.7 ± 8.3%, respectively). Further, infarct volume among hypothermic animals (23.2 ± 1.8% vs. 32.4 ± 2.5%) was significantly reduced. Therapeutic hypothermia reduces infarct volume and the frequency and expansion of SDs following cerebral ischemia.

Crowdsourcing methods facilitate the production of scientific information by non-experts. This form of citizen science (CS) is becoming a key source of complementary data in many fields to inform data-driven decisions and study challenging problems. However, concerns about the validity of these data often constrain their utility. In this paper, we focus on the use of citizen science data in addressing complex challenges in environmental conservation. We consider this issue from three perspectives. First, we present a literature scan of papers that have employed Bayesian models with citizen science in ecology. Second, we compare several popular majority vote algorithms and introduce a Bayesian item response model that estimates and accounts for participants' abilities after adjusting for the difficulty of the images they have classified. The model also enables participants to be clustered into groups based on ability. Third, we apply the model in a case study involving the classification of corals from underwater images from the Great Barrier Reef, Australia. We show that the model achieved superior results in general and, for difficult tasks, a weighted consensus method that uses only groups of experts and experienced participants produced better performance measures. Moreover, we found that participants learn as they have more classification opportunities, which substantially increases their abilities over time. Overall, the paper demonstrates the feasibility of CS for answering complex and challenging ecological questions when these data are appropriately analysed. This serves as motivation for future work to increase the efficacy and trustworthiness of this emerging source of data., Comment: 25 pages, 10 figures

In DISCHARGE-1, a recent Phase III diagnostic trial in aneurysmal subarachnoid haemorrhage patients, spreading depolarization variables were found to be an independent real-time biomarker of delayed cerebral ischaemia. We here investigated based on prospectively collected data from DISCHARGE-1 whether delayed infarcts in the anterior, middle, or posterior cerebral artery territories correlate with (i) extravascular blood volumes; (ii) predefined spreading depolarization variables, or proximal vasospasm assessed by either (iii) digital subtraction angiography or (iv) transcranial Doppler-sonography; and whether spreading depolarizations and/or vasospasm are mediators between extravascular blood and delayed infarcts. Relationships between variable groups were analysed using Spearman correlations in 136 patients. Thereafter, principal component analyses were performed for each variable group. Obtained components were included in path models with a priori defined structure. In the first path model, we only included spreading depolarization variables, as our primary interest was to investigate spreading depolarizations. Standardised path coefficients were 0.22 for the path from extravascular bloodcomponent to depolarizationcomponent (P = 0.010); and 0.44 for the path from depolarizationcomponent to the first principal component of delayed infarct volume (P < 0.001); but only 0.07 for the direct path from bloodcomponent to delayed infarctcomponent (P = 0.36). Thus, the role of spreading depolarizations as a mediator between blood and delayed infarcts was confirmed. In the principal component analysis of extravascular blood volume, intraventricular haemorrhage was not represented in the first component. Therefore, based on the correlation analyses, we also constructed another path model with bloodcomponent without intraventricular haemorrhage as first and intraventricular haemorrhage as second extrinsic variable. We found two paths, one from (subarachnoid) bloodcomponent to delayed infarctcomponent with depolarizationcomponent as mediator (path coefficients from bloodcomponent to depolarizationcomponent = 0.23, P = 0.03; path coefficients from depolarizationcomponent to delayed infarctcomponent = 0.29, P = 0.002), and one from intraventricular haemorrhage to delayed infarctcomponent with angiographic vasospasmcomponent as mediator variable (path coefficients from intraventricular haemorrhage to vasospasmcomponent = 0.24, P = 0.03; path coefficients from vasospasmcomponent to delayed infarctcomponent = 0.35, P < 0.001). Human autopsy studies shaped the hypothesis that blood clots on the cortex surface suffice to cause delayed infarcts beneath the clots. Experimentally, clot-released factors induce cortical spreading depolarizations that trigger (i) neuronal cytotoxic oedema and (ii) spreading ischaemia. The statistical mediator role of spreading depolarization variables between subarachnoid blood volume and delayed infarct volume supports this pathogenetic concept. We did not find that angiographic vasospasm triggers spreading depolarizations, but angiographic vasospasm contributed to delayed infarct volume. This could possibly result from enhancement of spreading depolarization-induced spreading ischaemia by reduced upstream blood supply.

Background Spreading depolarization (SD) has been linked to the impairment of neurovascular coupling. However, the association between SD occurrence and cerebrovascular pressure reactivity as a surrogate of cerebral autoregulation (CA) remains unclear. Therefore, we analyzed CA using the long-pressure reactivity index (L-PRx) during SDs in patients with aneurysmal subarachnoid hemorrhage (aSAH). Methods A retrospective study of patients with aSAH who were recruited at two centers, Heidelberg (HD) and Berlin (BE), was performed. Continuous monitoring of mean arterial pressure (MAP) and intracranial pressure (ICP) was recorded. ICP was measured using an intraparenchymal probe in HD patients and was measure in BE patients through external ventricular drainage. Electrocorticographic (ECoG) activity was continuously recorded between 3 and 13 days after hemorrhage. Autoregulation according to L-PRx was calculated as a moving linear Pearson’s correlation of 20-min averages of MAP and ICP. For every identified SD, 60-min intervals of L-PRx were averaged, plotted, and analyzed depending on SD occurrence. Random L-PRx recording periods without SDs served as the control. Results A total of 19 patients (HD n = 14, BE n = 5, mean age 50.4 years, 9 female patients) were monitored for a mean duration of 230.4 h (range 96–360, STD ± 69.6 h), during which ECoG recordings revealed a total number of 277 SDs. Of these, 184 represented a single SD, and 93 SDs presented in clusters. In HD patients, mean L-PRx values were 0.12 (95% confidence interval [CI] 0.11–0.13) during SDs and 0.07 (95% CI 0.06–0.08) during control periods (p p p Conclusions Neuromonitoring for simultaneous assessment of cerebrovascular pressure reactivity using 20-min averages of MAP and ICP measured by L-PRx during SD events is feasible. SD occurrence was associated with significant increases in L-PRx values indicative of CA disturbances. An impaired CA was found during SD in clusters when using an intraparenchymal probe. This preliminary study validates the use of cerebrovascular reactivity indices to evaluate CA disturbances during SDs. Our results warrant further investigation in larger prospective patient cohorts.

Many research domains use data elicited from ‘citizen scientists’ when a direct measure of a process is expensive or infeasible. However, participants may report incorrect estimates or classifications due to their lack of skill. We demonstrate how Bayesian hierarchical models can be used to learn about latent variables of interest, while accounting for the participants’ abilities. The model is described in the context of an ecological application that involves crowdsourced classifications of georeferenced coral-reef images from the Great Barrier Reef, Australia. The latent variable of interest is the proportion of coral cover, which is a common indicator of coral reef health. The participants’ abilities are expressed in terms of sensitivity and specificity of a correctly classified set of points on the images. The model also incorporates a spatial component, which allows prediction of the latent variable in locations that have not been surveyed. We show that the model outperforms traditional weighted-regression approaches used to account for uncertainty in citizen science data. Our approach produces more accurate regression coefficients and provides a better characterisation of the latent process of interest. This new method is implemented in the probabilistic programming language Stan and can be applied to a wide number of problems that rely on uncertain citizen science data.

Spreading depolarizations (SDs) are characterized by near-complete breakdown of the transmembrane ion gradients, cytotoxic edema, and glutamate release. SDs are associated with poor neurological outcomes in cerebrovascular diseases and brain trauma. Ketamine, a N-methyl-d-aspartate receptor antagonist, has shown to inhibit SDs in animal models and in humans. However, little is known about its SD-inhibitory effect during long-term administration. Lissencephalic animal models have shown that ketamine loses its SD-blocking effect after some minutes to hours. Physio-anatomical differences between lissencephalic and the more evolved gyrencephalic animals may affect their SDs-blocking effect. Therefore, information from the last may have more translational potential. Therefore, the aim of this study was to investigate the 18 h-effect of s-ketamine as a basis for its possible long-term clinical use for neuroprotection. For this purpose, two gyrencephalic swine brain models were used. In one, SDs were elicited through topical application of KCl; in the other model, SDs were spontaneously induced after occlusion of the middle cerebral artery. S-ketamine was administered at therapeutic human doses, 2, 4 and 5 mg/kg BW/h for up to 18 h. Our findings indicate that s-ketamine significantly reduces SD incidence and expansion without clear evidence of loss of its efficacy. Pharmacological susceptibility of SDs to s-ketamine in both the ischemic gyrencephalic brain and well-perfused brain was observed. SDs were most potently inhibited by s-ketamine doses that are above the clinically recommended (4 mg/kg BW/h and 5 mg/kg BW/h). Nonetheless, such doses are given by neurointensivists in individual cases. Our results give momentum to further investigate the feasibility of a multicenter, neuromonitoring-guided, proof-of-concept clinical trial.

Building on a strong foundation of philosophy, theory, methods and computation over the past three decades, Bayesian approaches are now an integral part of the toolkit for most statisticians and data scientists. Whether they are dedicated Bayesians or opportunistic users, applied professionals can now reap many of the benefits afforded by the Bayesian paradigm. In this paper, we touch on six modern opportunities and challenges in applied Bayesian statistics: intelligent data collection, new data sources, federated analysis, inference for implicit models, model transfer and purposeful software products., Comment: 27 pages, 8 figures

Objective Spreading depolarizations (SD) are characterized by breakdown of transmembrane ion gradients and excitotoxicity. Experimentally, N-methyl-d-aspartate receptor (NMDAR) antagonists block a majority of SDs. In many hospitals, the NMDAR antagonist s-ketamine and the GABAA agonist midazolam represent the current second-line combination treatment to sedate patients with devastating cerebral injuries. A pressing clinical question is whether this option should become first-line in sedation-requiring individuals in whom SDs are detected, yet the s-ketamine dose necessary to adequately inhibit SDs is unknown. Moreover, use-dependent tolerance could be a problem for SD inhibition in the clinic. Methods We performed a retrospective cohort study of 66 patients with aneurysmal subarachnoid hemorrhage (aSAH) from a prospectively collected database. Thirty-three of 66 patients received s-ketamine during electrocorticographic neuromonitoring of SDs in neurointensive care. The decision to give s-ketamine was dependent on the need for stronger sedation, so it was expected that patients receiving s-ketamine would have a worse clinical outcome. Results S-ketamine application started 4.2 ± 3.5 days after aSAH. The mean dose was 2.8 ± 1.4 mg/kg body weight (BW)/h and thus higher than the dose recommended for sedation. First, patients were divided according to whether they received s-ketamine at any time or not. No significant difference in SD counts was found between groups (negative binomial model using the SD count per patient as outcome variable, p = 0.288). This most likely resulted from the fact that 368 SDs had already occurred in the s-ketamine group before s-ketamine was given. However, in patients receiving s-ketamine, we found a significant decrease in SD incidence when s-ketamine was started (Poisson model with a random intercept for patient, coefficient − 1.83 (95% confidence intervals − 2.17; − 1.50), p p p p Conclusions These results provide a foundation for a multicenter, neuromonitoring-guided, proof-of-concept trial of ketamine and midazolam as a first-line sedative regime.

Fatigue resulting from shift work and extended hours can compromise patient care and the safety and health of nurses, as well as increasing nursing turnover and health care costs.This research aimed to identify aspects of nurses' work patterns associated with increased risk of reporting fatigue-related outcomes.A national survey of work patterns and fatigue-related outcomes in 6 practice areas expected to have high fatigue risk (child health including neonatology, cardiac care/intensive care, emergency and trauma, in-patient mental health, medical, and surgical nursing).The 5-page online questionnaire included questions addressing: demographics, usual work patterns, work in the previous two weeks, choice about shifts, and four fatigue-related outcomes - having a sleep problem for at least 6 months, sleepiness (Epworth Sleepiness Scale), recalling a fatigue-related error in clinical practice in the last 6 months, and feeling close to falling asleep at the wheel in the last 12 months. The target population was all registered and enrolled nurses employed to work in public hospitals at least 30 h/week in one of the 6 practice areas. Participation was voluntary and anonymous.Respondents (n = 3133) were 89.8% women and 8% Māori (indigenous New Zealanders), median age 40 years, range 21-71 years (response rate 42.6%). Nurses were more likely than New Zealand adults in general to report chronic sleep problems (37.73% vs 25.09%, p 0.0001) and excessive sleepiness (33.75% vs 14.9%, p 0.0001). Fatigue-related error(s) in the last 6 months were recalled by 30.80% and 64.50% reported having felt sleepy at the wheel in the last 12 months. Logistic regression analyses indicated that fatigue-related outcomes were most consistently associated with shift timing and sleep. Risk increased with more night shifts and decreased with more nights with sleep between 11 p.m. and 7 a.m. and on which nurses had enough sleep to feel fully rested. Risk also increased with roster changes and more shift extensions greater than 30 min and decreased with more choice about shifts. Comparisons between intensive care/cardiac care and in-patient mental health nursing highlight that fatigue has different causes and consequences in different practice areas.Findings confirm the need for a more comprehensive and adaptable approach to managing fatigue. We advocate an approach that integrates safety management and scientific principles with nursing and management expertise. It should be data-driven, risk-focused, adaptable, and resilient in the face of changes in the services required, the resources available, and the overall goals of the healthcare system.

Bayesian methods are becoming increasingly popular in sports analytics. Identified advantages of the Bayesian approach include the ability to model complex problems, obtain probabilistic estimates and predictions that account for uncertainty, combine information sources and update learning as new data become available. The volume and variety of data produced in sports activities over recent years and the availability of software packages for Bayesian computation have contributed significantly to this growth. This comprehensive survey reviews and characterizes the latest advances in Bayesian statistics in sports, including methods and applications. We found that a large proportion of these articles focus on modeling/predicting the outcome of sports games and on the development of statistics that provides a better picture of athletes’ performance. We provide a description of some of the advances in basketball, football and baseball. We also summarise the sources of data used for the analysis and the most commonly used software for Bayesian computation. We found a similar number of publications between 2013 and 2018 as compared to those published in the three previous decades, which is an indication of the growing adoption rate of Bayesian methods in sports.

Spreading depolarization (SD) is a fundamental pathophysiological mechanism of both pannecrotic and selective neuronal lesions following deprivation of energy. SD with brain injury has been reported including in one patient during an intracranial operation. However, the incidence of SDs in operative resections is unknown. We performed (a) retrospective analysis of intraoperative AC-recordings of 69 patients and (b) a prospective study using intraoperative near-DC recording. All patients had the diagnosis of pharmaco-resistant epilepsy. Both studies were designed to determine the incidence and characteristics of SDs intraoperatively. In the retrospective analysis, we used intraoperative electrocorticography (iECoG) recordings obtained from AC-recording of 69 patients. In the prospective analysis, we used an Octal Bio Amp and Power Lab ECoG recorder with near-DC range. In the retrospective study, we included 69 patients with a mean of 1 h 3 min of iECoG recordings. In the prospective study, we recruited 20 patients with near DC recordings. A total of 35 h 41 min of iECoG recordings with mean of 2 h 32 min/patient were analyzed. We did not find SD in either study. SDs were not detected during intraoperative recordings of epilepsy surgery using AC- or DC-amplifiers.

Neurosurgical management of traumatic brain injury (TBI) is challenging, with only low-quality evidence. We aimed to explore differences in neurosurgical strategies for TBI across Europe.A survey was sent to 68 centers participating in the Collaborative European Neurotrauma Effectiveness Research in Traumatic Brain Injury (CENTER-TBI) study. The questionnaire contained 21 questions, including the decision when to operate (or not) on traumatic acute subdural hematoma (ASDH) and intracerebral hematoma (ICH), and when to perform a decompressive craniectomy (DC) in raised intracranial pressure (ICP).The survey was completed by 68 centers (100%). On average, 10 neurosurgeons work in each trauma center. In all centers, a neurosurgeon was available within 30 min. Forty percent of responders reported a thickness or volume threshold for evacuation of an ASDH. Most responders (78%) decide on a primary DC in evacuating an ASDH during the operation, when swelling is present. For ICH, 3% would perform an evacuation directly to prevent secondary deterioration and 66% only in case of clinical deterioration. Most respondents (91%) reported to consider a DC for refractory high ICP. The reported cut-off ICP for DC in refractory high ICP, however, differed: 60% uses 25 mmHg, 18% 30 mmHg, and 17% 20 mmHg. Treatment strategies varied substantially between regions, specifically for the threshold for ASDH surgery and DC for refractory raised ICP. Also within center variation was present: 31% reported variation within the hospital for inserting an ICP monitor and 43% for evacuating mass lesions.Despite a homogeneous organization, considerable practice variation exists of neurosurgical strategies for TBI in Europe. These results provide an incentive for comparative effectiveness research to determine elements of effective neurosurgical care.

Bayesian techniques are being quickly adopted in sports settings. The volume and variety of data produced in sports activities over the past years and the availability of software packages for Bayesian computation have contributed positively to this growth. This article provides a brief review of the latest advances in Bayesian statistics in sports, covering methods and applications. In the literature surveyed, we found a similar number of publications between 2013 and 2017 and those published in the three previous decades, which is an indication of the rapid adoption rate of Bayesian methods in sports.

Focal brain damage after aneurysmal subarachnoid haemorrhage predominantly results from intracerebral haemorrhage, and early and delayed cerebral ischaemia. The prospective, observational, multicentre, cohort, diagnostic phase III trial, DISCHARGE-1, primarily investigated whether the peak total spreading depolarization-induced depression duration of a recording day during delayed neuromonitoring (delayed depression duration) indicates delayed ipsilateral infarction.Consecutive patients (n = 205) who required neurosurgery were enrolled in six university hospitals from September 2009 to April 2018. Subdural electrodes for electrocorticography were implanted. Participants were excluded on the basis of exclusion criteria, technical problems in data quality, missing neuroimages or patient withdrawal (n = 25). Evaluators were blinded to other measures.Longitudinal MRI, and CT studies if clinically indicated, revealed that 162/180 patients developed focal brain damage during the first 2 weeks. During 4.5 years of cumulative recording, 6777 spreading depolarizations occurred in 161/180 patients and 238 electrographic seizures in 14/180. Ten patients died early; 90/170 developed delayed infarction ipsilateral to the electrodes. Primary objective was to investigate whether a 60-min delayed depression duration cut-off in a 24-h window predicts delayed infarction with >0.60 sensitivity and >0.80 specificity, and to estimate a new cut-off. The 60-min cut-off was too short. Sensitivity was sufficient [= 0.76 (95% confidence interval: 0.65–0.84), P = 0.0014] but specificity was 0.59 (0.47–0.70), i.e. While the 60-min cut-off of cumulative depression in a 24-h window indicated reversible delayed neurological deficit, only a 180-min cut-off indicated new infarction with >0.60 sensitivity and >0.80 specificity. Although spontaneous resolution of the neurological deficit is still possible, we recommend initiating rescue treatment at the 60-min rather than the 180-min cut-off if progression of injury to infarction is to be prevented.

Funder: Projekt DEAL, The ability of photoacoustic imaging to measure functional tissue properties, such as blood oxygenation sO[Formula: see text], enables a wide variety of possible applications. sO[Formula: see text] can be computed from the ratio of oxyhemoglobin HbO[Formula: see text] and deoxyhemoglobin Hb, which can be distuinguished by multispectral photoacoustic imaging due to their distinct wavelength-dependent absorption. However, current methods for estimating sO[Formula: see text] yield inaccurate results in realistic settings, due to the unknown and wavelength-dependent influence of the light fluence on the signal. In this work, we propose learned spectral decoloring to enable blood oxygenation measurements to be inferred from multispectral photoacoustic imaging. The method computes sO[Formula: see text] pixel-wise, directly from initial pressure spectra [Formula: see text], which represent initial pressure values at a fixed spatial location [Formula: see text] over all recorded wavelengths [Formula: see text]. The method is compared to linear unmixing approaches, as well as pO[Formula: see text] and blood gas analysis reference measurements. Experimental results suggest that the proposed method is able to obtain sO[Formula: see text] estimates from multispectral photoacoustic measurements in silico, in vitro, and in vivo.

El presente trabajo de investigación, se realizó con el objetivo de que los efectivos policiales de la Dirección Nacional de Investigación de Lavado de Activos, (DIRILA), al momento de estructurar su caso, tengan en consideración la regulación de la ignorancia dolosa en el delito de lavado de activos y que los investigados pretextando ignorancia, sean excluidos de los procesos materia de investigación. Por medio de un cuestionario estructurado se encuestó a 243 policías de la Dirección de Investigación de Lavado de Activos, haciendo un total de 143 policías encuestados. La investigación es con un enfoque cuantitativo, de tipo no experimental, descriptiva correlacional no experimental de corte transversal. Se utilizó como instrumento cuestionario de preguntas. Lima Este Escuela de Posgrado Gestión de Políticas Públicas

Contains fulltext : 238746.pdf (Publisher’s version ) (Closed access) Recent biomarker innovations hold potential for transforming diagnosis, prognostic modeling, and precision therapeutic targeting of traumatic brain injury (TBI). However, many biomarkers, including brain imaging, genomics, and proteomics, involve vast quantities of high-throughput and high-content data. Management, curation, analysis, and evidence synthesis of these data are not trivial tasks. In this review, we discuss data management concepts and statistical and data sharing strategies when dealing with biomarker data in the context of TBI research. We propose that application of biomarkers involves three distinct steps-discovery, evaluation, and evidence synthesis. First, complex/big data has to be reduced to useful data elements at the stage of biomarker discovery. Second, inferential statistical approaches must be applied to these biomarker data elements for assessment of biomarker clinical utility and validity. Last, synthesis of relevant research is required to support practice guidelines and enable health decisions informed by the highest quality, up-to-date evidence available. We focus our discussion around recent experiences from the International Traumatic Brain Injury Research (InTBIR) initiative, with a specific focus on four major clinical projects (Transforming Research and Clinical Knowledge in TBI, Collaborative European NeuroTrauma Effectiveness Research in TBI, Collaborative Research on Acute Traumatic Brain Injury in Intensive Care Medicine in Europe, and Approaches and Decisions in Acute Pediatric TBI Trial), which are currently enrolling subjects in North America and Europe. We discuss common data elements, data collection efforts, data-sharing opportunities, and challenges, as well as examine the statistical techniques required to realize successful adoption and use of biomarkers in the clinic as a foundation for precision medicine in TBI.

COVID-19 is characterized by acute respiratory distress syndrome progression, which ranges from mild to severe. A percentage of critically ill patients will require endotracheal intubation and mechanical ventilation; therefore, Mexican engineers from different places have had the initiative of creating mechanical ventilators. Although artificial ventilator is one of the last resources for the most severely ill patients, there are patients who are on the verge of not meeting the criteria for intubation; if they are directly intubated, the opportunity for them to overcome the severe phase with high concentration supplemental oxygen would be be missed. Intubation per se induces lung damage, increases the risk of superinfection, and the number of days of ICU stay. Furthermore, non-selective use of artificial ventilators decreases the opportunity for patients who require a ventilator to survive and increases institutional care costs of both human and material resources.