bluuebunny/crossref_metadata_2025_split huggingface dataset:
Changing temporal trends in patient volumes in a pediatric emergency department during a COVID-19 pandemic lockdown: a retrospective cohort study
Authors: Mullan Paul C. , Vazifedan Turaj 
Published: July 2022

ABSTRACTObjectiveEmergency department (ED) teams have had to adjust limited staffing resources to meet the fluctuating levels of patient volume and acuity during the COVID-19 pandemic. Historically, Mondays have had the highest reported ED volumes. We are unaware of any studies reporting on the change of this Monday effect during the COVID-19 pandemic.MethodsThis retrospective, observational study of a single pediatric ED compared a pandemic lockdown period (3/23/2020-11/1/2020) with a seasonally comparative period (3/25/2019-11/3/2019). We compared the mean number of patients who arrived on Monday versus any other specific weekday (Tuesday, Wednesday, Thursday, or Friday) and the aggregate of other weekdays (Tuesday to Friday) for both study periods. Secondary analyses investigated overall mean volumes, admission rates, and differences in triage acuity levels.ResultsThere were 31,377 and 18,098 patients in the comparative and pandemic periods. The mean number of ED visits on Mondays in the comparative period was significantly more than any other weekday and the aggregate of weekdays (latter p<0.001). In contrast, there were no significant differences in the mean number of ED visits on Mondays in the pandemic period relative to any other weekday and the aggregate of weekdays (all p>0.05). The pandemic period had significantly lower mean volumes, higher admission rates, and more patients with higher acuity levels.ConclusionThe previously experienced Monday effect of increased relative ED patient volumes was not seen during the pandemic period. This change has operational implications for scheduling ED staffing resources. Larger database studies are needed to determine the generalizability of these findings.
Feasibility of and Experience with Telehealth Based Patient Self-referral for COVID-19 Monoclonal Antibody Therapy
Authors: Gupta Ishaan , Purekal Sophia , Shaikh Yahya , Michtalik Henry J. , Eid Shaker M. , Wortman Laura , Vaeth MaryJane E. , Locke Charles F S , Hoemeke Elizabeth , Hariharan Raena , Callahan Charles D. , Ficke James R. , Pimenta Isabel , Auwaerter Paul G. , Kantsiper Melinda E. ,   CONQUER COVID Consortium, Siddiqui Zishan K. 
Published: July 2022

AbstractBackgroundMonoclonal antibody (mAb) treatment for COVID-19 has been underutilized due to logistical challenges, lack of access and variable treatment awareness among patients and providers. The use of telehealth during the pandemic provides an opportunity to increase access to COVID care.MethodsThis is a single-center descriptive study of telehealth-based patient self-referral for mAb therapy between March 1, 2021 to October 31, 2021 at Baltimore Convention Center Field Hospital (BCCFH).ResultsAmong the 1001 self-referral patients, the mean age was 47, and most were female (57%) white (66%), and had a primary care provider (62%). During the study period, self-referrals increased from 14 per month in March to 427 in October resulting in a 30-fold increase. About 57% of self-referred patients received a telehealth visit, and of those 82% of patients received mAb infusion therapy, either onsite or at other infusion sites. The median time from self-referral to onsite infusion was 2 days (1-3 IQR).DiscussionOur study shows the integration of telehealth with a self-referral process improved access to mAb infusion. A high proportion of self-referrals were appropriate and led to timely treatment. Incorporation of self-referral and telehealth for monoclonal antibody therapy led to successful timely infusions. This approach helped those without traditional avenues for care and avoided potential delay for patients seeking referral from their medical providers.
Altered affinity to ACE2 and reduced Fc functional antibodies to SARS-CoV-2 RBD variants
Authors: Haycroft Ebene R , Davis Samantha K , Ramanathan Pradhipa , Lopez Ester , Purcell Ruth A , Tan Li Lynn , Pymm Phillip , Wines Bruce D , Hogarth P Mark , Wheatley Adam K , Juno Jennifer A. , Redmond Samuel , Gheradin Nicholas A , Godfrey Dale I , Tham Wai-Hong , Selva Kevin John , Kent Stephen J , Chung Amy W 
Published: July 2022

AbstractThe emergence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants remains a formidable challenge to worldwide public health. The receptor binding domain (RBD) of the SARS-CoV-2 spike protein is a hotspot for mutations, reflecting its critical role at the ACE2 interface during viral entry. We comprehensively investigated the impact of RBD mutations, including 6 variants of concern (VOC) or interest (Alpha, Beta, Gamma, Delta, Kappa and Omicron) and 33 common point mutations, on IgG recognition, FcγR-engagement, and ACE2-binding inhibition in plasma from BNT162b2-vaccine recipients (two-weeks following second dose) and mild-to-moderate COVID-19 convalescent subjects using our custom bead-based 39-plex array. We observed that IgG-recognition and FcγR-binding antibodies were most profoundly decreased against Beta and Omicron RBDs, as well as point mutations G446S, found in Omicron, and N501T, a key mutation found in animal adapted SARS-CoV-2 viruses. Measurement of RBD-ACE2 binding affinity via Biolayer Interferometry showed all VOC RBDs have enhanced affinity to human ACE2. Furthermore we demonstrate that human ACE2 polymorphisms, E35K (rs1348114695), K26R (rs4646116) and S19P (rs73635825), have altered binding kinetics to the RBD of VOCs potentially affecting virus-host interaction and thereby host susceptibility.
Abnormal thrombosis and neutrophil activation increases the risk of hospital-acquired sacral pressure injuries and morbidity in patients with COVID-19
Authors: Narang Jatin , Jatana Samreen , Ponti András K. , Musich Ryan , Gallop Joshua , Wei Angela H. , Seck Sokhna , Johnson Jessica , Kokoczka Lynne , Nowacki Amy S. , McBride Jeffrey D. , Mireles-Cabodevila Eduardo , Gordon Steven , Cooper Kevin , Fernandez Anthony P. , McDonald Christine 
Published: July 2022

AbstractHospitalized patients have an increased risk of developing hospital-acquired sacral pressure injury (HASPI). However, it is unknown whether SARS-CoV-2 infection affects HASPI development. To explore the role of SARS-CoV-2 infection in HASPI development, we conducted a single institution, multi-hospital, retrospective study of all patients hospitalized for ≥5 days from March 1, 2020 to December 31, 2020. Patient demographics, hospitalization information, ulcer characteristics, and 30-day-related morbidity were collected for all patients with HASPIs, and intact skin was collected from HASPI borders in a patient subset. We determined the incidence, disease course, and short-term morbidity of HASPIs in COVID-19(+) patients, and characterized the skin histopathology and tissue gene signatures associated with HASPIs in COVID-19 disease. COVID-19(+) patients had a 63% increased HASPI incidence rate, HASPIs of more severe ulcer stage (OR 2.0, p<0.001), and HASPIs more likely to require debridement (OR 3.1, p=0.04) compared to COVID-19(-) patients. Furthermore, COVID-19(+) patients with HASPIs had 2.2x odds of a more severe hospitalization course compared to COVID-19(+) patients without HASPIs. HASPI skin histology from COVID-19(+) patients predominantly showed thrombotic vasculopathy, with the number of thrombosed vessels being significantly greater than HASPIs from COVID-19(-) patients. Transcriptional signatures of COVID-19(+) samples were enriched for innate immune responses, thrombosis, and neutrophil activation genes. SARS-CoV-2 viral transcripts were detected in skin tissue of COVID-19(+) patients with severe disease. Overall, our results suggest that immunologic dysregulation secondary to SARS-CoV-2 infection, including neutrophil dysfunction and abnormal thrombosis, may play a pathogenic role in development of HASPIs in patients with severe COVID-19.One Sentence SummarySARS-CoV-2-induced immune dysregulation contributes to pressure-induced sacral skin ulceration in hospitalized patients with severe COVID-19.
Application of ARIMA, hybrid ARIMA and Artificial Neural Network Models in predicting and forecasting tuberculosis incidences among children in Homa Bay and Turkana Counties, Kenya
Authors: Stephen Siamba , Argwings Otieno , Julius Koech 
Published: July 2022

AbstractBackgroundTuberculosis (TB) infections among children (below 15 years) is a growing concern, particularly in resource-limited settings. However, the TB burden among children is relatively unknown in Kenya where two-thirds of estimated TB cases are undiagnosed annually. Very few studies have used Autoregressive Integrated Moving Average (ARIMA), hybrid ARIMA, and Artificial Neural Networks (ANNs) models to model infectious diseases globally. We applied ARIMA, hybrid ARIMA, and Artificial Neural Network models to predict and forecast TB incidences among children in Homa bay and Turkana Counties in Kenya.MethodsThe ARIMA, ANN, and hybrid models were used to predict and forecast monthly TB cases reported in the Treatment Information from Basic Unit (TIBU) system for Homa bay and Turkana Counties between 2012 and 2021. The data were split into training data, for model development, and testing data, for model validation using an 80:20 split ratio respectively.ResultsThe hybrid ARIMA model (ARIMA-ANN) produced better predictive and forecast accuracy compared to the ARIMA (0,0,1,1,0,1,12) and NNAR (1,1,2) [12] models. Furthermore, using the Diebold-Mariano (DM) test, the predictive accuracy of NNAR (1,1,2) [12] versus ARIMA-ANN, and ARIMA-ANN versus ARIMA (0,0,1,1,0,1,12) models were significantly different, p<0.001, respectively. The 12-month forecasts showed a TB prevalence of 175 to 198 cases per 100,000 children in Homa bay and Turkana Counties in 2022.ConclusionThe hybrid (ARIMA-ANN) model produces better predictive and forecast accuracy compared to the single ARIMA and ANN models. The findings show evidence that the prevalence of TB among children below 15 years in Homa bay and Turkana Counties is significantly under-reported and is potentially higher than the national average.
Episodic memory impairment in patients with repetitive head injury: Initial findings of the SNAP-CTE cohort study
Authors: Erskine Ellen , Batchelor Jennifer , Maddren Michelle , Brown Eamon , Lystad Reidar , Mobbs Rowena 
Published: July 2022

AbstractBackgroundTraumatic encephalopathy syndrome (TES) is considered a long-term, neurodegenerative consequence of repetitive head injury (RHI). This cohort study aimed to characterise the episodic memory profiles (specifically, immediate and delayed memory) of individuals with RHI history through neuropsychological assessment. Hypotheses included participants demonstrating reduced episodic memory functioning, and greater reductions in functioning observed with greater years of RHI exposure.MethodsNeuropsychological assessment was conducted on 34 adults with ≥10 years of RHI exposure as a cohort study. Main outcome measures were auditory memory indices (AMI), immediate memory indices (AII), and auditory delayed memory indices (ADI). Other potential predictors of outcome variables (in addition to years of exposure duration) were also measured and factored into analysis so that they could be controlled for.ResultsAMI [t (33) = -2.4, p = .020), AII (t = -2.7, p = .012), and ADI (t = -2.7, p = .44) were all significantly below normative levels. AMI [t (33) = 4.1, p <.001), AII (t = 4.3, p <.001), and ADI (t = 3.7, p <.001) were also significantly below participants’ measured premorbid functioning. None of the comorbidities that were considered as possible confounding variables predicted the relationship of any outcome variables.ConclusionsPrevious research (1) indicated that immediate episodic memory (i.e., encoding) impairments do not appear to be associated with RHI, and our study provides evidence to the contrary. However, further research is required on larger sample sizes to further understand the relationship between RHI and encoding deficits in this complex population.What is already known on this topic?Chronic Traumatic Encephalopathy (CTE) identified at autopsy, has been loosely associated with a history of repetitive head injury (RHI) sustained in life, yet factors that account for symptoms such as defined in life as Traumatic Encephalopathy Syndrome (TES) which can include abnormal cognitive function, behavioural dysregulation and mood disturbances in this patient cohort are yet to be comprehensively investigated.What this study adds?This research is beneficial to the scientific community mainly because it contributes to the pre-existing body of literature on the neuropsychological profile of RHI. Previous research (1) has indicated that immediate episodic memory (i.e., encoding) impairments do not appear to be associated with RHI, and our study provides evidence to the contrary.How might this study affect research, practice, or policy?This research represents progress towards further discerning a neuropsychological profile of TES, thereby potentially aiding a better clinical diagnostic presentation of the disease, which can build on potential earlier diagnosis, prevention strategies and treatment pathways.
Global health open-source goggles for fluorescence-guided surgery
Authors: Shmuylovich Leonid , O’Brien Christine M. , Nwosu Karen , Achilefu Samuel 
Published: July 2022

AbstractFluorescence-guided surgery (FGS), coupled with novel near infrared (NIR) fluorescent contrast agents, has significant potential to improve health but in current practice is less suitable for low resource settings. Although there are efforts to simplify FGS systems, technical, economic, and logistic challenges have hampered its global adoption. To overcome these impediments, we developed a low-cost, open-source, battery-powered and fully wearable FGS system called the fluorescence imaging augmented reality Raspberry Pi-based goggle system (FAR-Pi). Compared to current technologies that are expensive, bulky, and wall-powered, FAR-Pi has higher spatial resolution, depth of focus and fluorescence sensitivity. The FAR-Pi system has broad appeal by detecting the diverse fluorescence of NIR contrast agents undergoing clinical trials, as demonstrated by the successful identification of tumors in vivo with LS301, a tumor-targeting NIR contrast agent. As an open-source, inexpensive, and modifiable system, FAR-Pi promises to broaden access to FGS, thereby improving health worldwide.
OpenCap: 3D human movement dynamics from smartphone videos
Authors: Uhlrich Scott D. , Falisse Antoine , Kidziński Łukasz , Muccini Julie , Ko Michael , Chaudhari Akshay S. , Hicks Jennifer L. , Delp Scott L. 
Published: July 2022

AbstractMeasures of human movement dynamics can predict outcomes like injury risk or musculoskeletal disease progression. However, these measures are rarely quantified in clinical practice due to the prohibitive cost, time, and expertise required. Here we present and validate OpenCap, an open-source platform for computing movement dynamics using videos captured from smartphones. OpenCap’s web application enables users to collect synchronous videos and visualize movement data that is automatically processed in the cloud, thereby eliminating the need for specialized hardware, software, and expertise. We show that OpenCap accurately predicts dynamic measures, like muscle activations, joint loads, and joint moments, which can be used to screen for disease risk, evaluate intervention efficacy, assess between-group movement differences, and inform rehabilitation decisions. Additionally, we demonstrate OpenCap’s practical utility through a 100-subject field study, where a clinician using OpenCap estimated movement dynamics 25 times faster than a laboratory-based approach at less than 1% of the cost. By democratizing access to human movement analysis, OpenCap can accelerate the incorporation of biomechanical metrics into large-scale research studies, clinical trials, and clinical practice.
PACT - Prediction of Amyloid Cross-interaction by Threading
Authors: Wojciechowski Jakub W. , Szczurek Witold , Szulc Natalia , Szefczyk Monika , Kotulska Malgorzata 
Published: July 2022

ABSTRACTAmyloids are protein aggregates usually associated with their contribution to several diseases e.g., Alzheimer’s and Parkinson’s. However, they are also beneficially utilized by many organisms in physiological roles, such as microbial biofilm formation or hormone storage. Recent studies showed that an amyloid aggregate can affect aggregation of another protein. Such cross-interactions may be crucial for understanding the comorbidity of amyloid diseases or the influence of microbial amyloids on human amyloidogenic proteins. However, due to demanding experiments, understanding of interaction phenomena is still limited. Moreover, no dedicated computational method to predict potential amyloid interactions has been available until now. Here, we present PACT - a computational method for prediction of amyloid cross-interactions. The method is based on modeling a heterogenous fibril formed by two amyloidogenic peptides. The stability of the resulting structure is assessed using a statistical potential that approximates energetic stability of a model. Importantly, the method can work with long protein fragments and, as a purely physicochemical approach, it relies very little on training data. PACT was evaluated on data collected in the AmyloGraph database and it achieved high values of AUC (0.88) and F1 (0.82). The new method opens the possibility of high throughput studies of amyloid interactions. We used PACT to study interactions of CsgA, a bacterial biofilm protein from several bacterial species inhabiting human intestines, and human Alpha-synuclein protein which is involved in the onset of Parkinson’s disease. We show that the method correctly predicted the interactions, performing experimental validation, and highlighted the importance of specific regions in both proteins.The tool is available as a web server at:https://pact.e-science.pl/pact/. The local version can be downloaded from:https://github.com/KubaWojciechowski/PACT
Longitudinal structural change of gray matter before and after hemispherotomy
Authors: Yu Hao , Chen Yijun , Luo Junhao , Liu Qingzhu , Qin Peipei , Wang Changtong , Qu Jingli , Cai Lixin , Gong Gaolang 
Published: July 2022

AbstractBackgroundHemispherotomy is an effective surgery developed to treat refractory epilepsy caused by diffuse unihemispheric pathologies. Post-surgery neuroplastic mechanisms supporting behavioral recovery after left and right hemispherotomy as well as their difference remain largely unclear.MethodsIn a large cohort of 57 pediatric patients who underwent hemispherotomy, voxel-wise GMV in unaffected regions (contralesional cerebrum and bilateral cerebellum) and behavioral abilities were assessed before and after surgery. Using linear mixed models, we evaluated changes in GMV and behavioral scores, and how GMV changes correlated with improvements in behavioral scores. In addition, three machine learning regression algorithms were applied to assess whether preoperative GMV can predict postoperative behavior.ResultsIn the two patient groups (29 left hemispherotomy patients, age of surgery mean ± standard deviation = 3.5 ± 2.5; 28 right hemispherotomy patients, age of surgery 4.6 ± 2.5), widespread increases in the postoperative GMV in the contralateral cerebrum and ipsilateral cerebellum but decreases in the postoperative GMV in the contralateral cerebellum were consistently observed. Importantly, the decrease in GMV in the contralateral cerebellum was significantly correlated with improvement in behavioral scores in right but not left hemispherotomy patients. Moreover, the preoperative GMV around the most longitudinally changed locations significantly predicted postoperative behavioral scores in left but not right hemispherotomy patients.ConclusionsOur findings indicate an important role for the contralateral cerebellum in the recovery after right hemispherotomy, and postoperative behavioral scores can be predicted with preoperative GMV features.What is already known on this topicThe contralesional cerebrum plays a key role in the recovery after hemispherotomy.What this study addsDespite suffering from gray matter atrophy, GMV decrease in contralesional cerebellum is associated with improvement in behavioral score in patients after hemispherotomy.How this study might affect research, practice or policyThese results provide novel insight into the prominence of the contralateral cerebellum in the recovery after hemispherotomy and highlight the clinical role of presurgery GMV in the prediction of postsurgery behavior.
Corticostriatal Beta Power Changes Associated with Cognitive Function in Parkinson’s Disease
Authors: Paulo DL , Qian H , Subramanian D , Johnson GW , Hett K , Kao C , Roy N , Dhima K , Claassen DO , Bick SK 
Published: July 2022

AbstractCognitive impairment (CI) is the most frequent nonmotor symptom in Parkinson’s Disease (PD) and is associated with deficits in executive functions such as working memory. Previous studies have demonstrated that caudate beta power is involved in learning and working memory. Decreased dopamine in motor cortico-striato-thalamo-cortical (CSTC) circuits results in increased beta power and PD motor symptoms. Analogous changes in cognitive CSTC circuits, including the caudate and dorsolateral prefrontal cortex (DLPFC), may contribute to PD CI. The objective of our study is to evaluate whether beta power changes in caudate and DLPFC contribute to cognitive impairment in PD patients. To investigate this, we used local field potential (LFP) recordings during deep brain stimulation surgery in 15 PD patients. LFP signals from DLPFC and caudate were performed at rest and during a verbal working memory task. We examined beta power changes during the working memory task and relationship of beta power to pre-operative neuropsychological testing results. Beta power decreased in both DLPFC and caudate during encoding of correct trials, whereas beta power increased in DLPFC and caudate during feedback for correct responses. Subjects with cognitive impairment showed smaller decreases in caudate and DLPFC beta power during encoding, greater increases in beta power during feedback, and lower average resting-state beta power. Additionally, reduced caudate beta power during encoding correlated with better memory scores on pre-operative neuropsychological testing, while greater DLPFC beta power during feedback correlated with worse scores in the attention domain. Our findings suggest that similar to the relationship between beta power in motor CSTC circuits and PD motor symptoms, beta power changes in parallel cognitive CSTC circuits may be correlated with cognitive symptoms in PD patients.