bluuebunny/crossref_metadata_2025_split huggingface dataset:
Pediatric Musculoskeletal Coccidioidomycosis in Central California: A Single Center Experience
Authors: Naeem Fouzia , Gerardi Joseph , Gholve Purushottam , Merriott Daniel , Hassan Rida , McCarty James 
Published: April 2022

Background:
Published literature on musculoskeletal coccidioidomycosis is sparse and limited to case reports and case series. This is one of the largest case series to describe the clinical presentation, diagnosis, medical and surgical management and outcomes of pediatric musculoskeletal coccidioidomycosis at a tertiary care hospital.

Method:
A retrospective case review was performed on patients ≤ 21 years old who were followed at a tertiary care center with a diagnosis of musculoskeletal coccidioidomycosis from January 1, 2007, to December 31, 2020. Descriptive data are expressed as medians and interquartile range (IQR) for continuous variables or as frequency and percentage for categorical variables. Categorical values were compared using the χ
2 test.

Results:
Forty-one patients were identified. The median age was 12.8 years, and most were male (71%), Latinx (66%) and healthy (71%). Limb swelling (66%), bone pain (54%) and joint pain (46%) were the most common presenting symptoms. Multiple bone involvement was present in 29% while 12% had the joint disease, and craniofacial (n = 10) and metacarpal/metatarsal bones (n=9) were the most commonly involved sites. Elevated Coccidioides complement fixation (CF) titers ≥1:32 were seen in 90% of the patients. Thirty-three patients (81%) required surgical interventions and of these 16 (48%) required additional surgical procedures. Eleven patients (27%) had disease relapse. Children >13 years of age were more likely to have > 1 organ involvement (16 vs. 7, P = 0.04), multiple bone involvement (10 vs. 2, P = 0.004) and maximum Coccidioides CF titers >1:128 (13 vs. 6, P = 0.02).

Conclusions:
In endemic areas, musculoskeletal coccidioidomycosis causes a substantial disease burden in children and should be considered in the differential diagnosis of those presenting with bone and joint pain or swelling. Early diagnosis and treatment are essential to minimize long-term morbidity and mortality.
Management and Outcome of Febrile Infants ≤60 days, With Emphasis on Infants ≤21 Days Old, in Swedish Pediatric Emergency Departments
Authors: Orfanos Ioannis , Elfving Kristina , Sotoca Fernandez Jorge , Wennlund Lovisa , Weiber Sofia , Eklund Erik A. , Alfvén Tobias 
Published: April 2022

Background:
Management of febrile infants ≤60 days of age varies, and the age for routine investigations and antibiotic-treatment is debated. The American Academy of Pediatrics recommended age threshold for lumbar puncture (LP) is 21 days and for blood culture 60 days. We describe management and adverse outcome of febrile infants ≤60 days old, in Sweden.

Methods:
Retrospective cross-sectional study of infants ≤60 days of age with fever without source evaluated in 4 University pediatric emergency departments, between 2014 and 2017. Adverse outcome was defined as delayed-treated invasive bacterial infection (IBI: meningitis or bacteremia).

Results:
We included 1701 infants. In infants ≤21 days old, LP was performed in 16% (95% CI: 12–20) and blood culture in 43% (95% CI: 38–48). Meningitis was diagnosed in 5 (1.3%; 95% CI: 0.4–3.0) and bacteremia in 12 (4.5%; 95% CI: 2.6–7.0) infants. Broad-spectrum antibiotics were not administered to 66% (95% CI: 61–71), of which 2 (0.8%; 95% CI: 0.1–2.8) diagnosed with IBI (1 meningitis and 1 bacteremia). In the 29–60 days age group, blood culture was performed in 21% (95% CI: 19–24), and broad-spectrum antibiotics were not administered to 84% (95% CI: 82–86), with no case of delayed-treated bacteremia.

Conclusions:
The rates of LP, blood culture and broad-spectrum antibiotics were low. Despite that, there were few delayed-treated IBIs, but 2 of the 17 infants ≤21 days of age with IBI were not timely treated, which prompts the need for a safer approach for this age group. Also, the utility of routine blood culture for all febrile infants 29–60 days old could be questioned.
Analysis of non-human primate models for evaluating prion disease therapeutic efficacy
Authors: Mortberg Meredith A , Minikel Eric Vallabh , Vallabh Sonia M 
Published: April 2022

ABSTRACTPrion disease is a fatal neurodegenerative disease caused by the conformational corruption of the prion protein (PrP), encoded by the prion protein gene (PRNP). While no disease-modifying therapy is currently available, genetic and pharmacological proofs of concept support development of therapies that lower PrP levels in the brain. In light of proposals for clinical testing of such drugs in presymptomatic individuals at risk for genetic prion disease, extensive nonclinical data are likely to be required, with extra attention paid to choice of animal models. Uniquely, the entire prion disease process can be faithfully modeled through transmission of human prions to non-human primates (NHPs), raising the question of whether NHP models should be used to assess therapeutic efficacy. Here we systematically aggregate data from N=527 prion-inoculated animals spanning six decades of research studies. Using this dataset, we assess prion strain, route of administration, endpoint, and passage number to characterize the relationship of tested models to currently prevalent human subtypes of prion disease. We analyze the incubation times observed across diverse models and perform power calculations to assess the practicability of testing prion disease therapeutic efficacy in NHPs. We find that while some models may theoretically be able to support therapeutic efficacy studies, pilot studies would be required to confirm incubation time and attack rate before pivotal studies could be designed, cumulatively requiring several years. The models with the shortest and most tightly distributed incubation times are those with smaller brains and weaker homology to humans. Our findings indicate that it would be challenging to conduct efficacy studies in NHPs in a paradigm that honors the potential advantages of NHPs over other available models, on a timeframe that would not risk unduly delaying patient access to promising drug candidates.
Extraction of Sleep Information from Clinical Notes of Patients with Alzheimer’s Disease Using Natural Language Processing
Authors: Sivarajkumar Sonish , Tam Thomas Yu Chow , Ahamed Mohammad Haneef , Viggiano Samuel , Oniani David , Visweswaran Shyam , Wang Yanshan 
Published: April 2022

AbstractObjectiveAlzheimer’s Disease (AD) is the most common form of dementia in the United States. Sleep is one of the lifestyle-related factors that has been shown critical for optimal cognitive function in old age. However, there is a lack of research studying the association between sleep and AD incidence. A major bottleneck for conducting such research is that the traditional way to acquire sleep information is time-consuming, inefficient, non-scalable, and limited to patients’ subjective experience.Materials and MethodsA gold standard dataset is created from manual annotation of 570 randomly sampled clinical note documents from the adSLEEP, a corpus of 192,000 de-identified clinical notes of 7,266 AD patients retrieved from the University of Pittsburgh Medical Center (UPMC). We developed a rule-based Natural Language Processing (NLP) algorithm, machine learning models, and Large Language Model(LLM)-based NLP algorithms to automate the extraction of sleep-related concepts, including snoring, napping, sleep problem, bad sleep quality, daytime sleepiness, night wakings, and sleep duration, from the gold standard datasetResultsRule-based NLP algorithm achieved the best performance of F1 across all sleep-related concepts. In terms of Positive Predictive Value (PPV), rule-based NLP algorithm achieved 1.00 for daytime sleepiness and sleep duration, machine learning models: 0.95 and for napping, 0.86 for bad sleep quality and 0.90 for snoring; and LLAMA2 with finetuning achieved PPV of 0.93 for Night Wakings, 0.89 for sleep problem, and 1.00 for sleep duration.DiscussionAlthough sleep information is infrequently documented in the clinical notes, the proposed rule-based NLP algorithm and LLM-based NLP algorithms still achieved promising results. In comparison, the machine learning-based approaches didn’t achieve good results, which is due to the small size of sleep information in the training data.ConclusionThe results show that the rule-based NLP algorithm consistently achieved the best performance for all sleep concepts. This study focused on the clinical notes of patients with AD, but could be extended to general sleep information extraction for other diseases.
Cannabis potential effects to prevent or attenuate SARS-COV2 contagion
Authors: Herrera-Gómez Paula M. , Echeverri-Cataño Luis F. , Giraldo S , Ruiz Colorado- Y , Vélez van Meerbeke Alberto 
Published: April 2022

AbstractMedical cannabis has gained an exponential interest in recent years. Therapeutic targets have been broadened from specific applications over pain control, chemotherapy side effects, treatment-resistant epilepsies and multiple sclerosis, among others. Several in vitro and animal studies, along with few human controlled studies, suggest cannabinoids have a potential therapeutic role over medical conditions comporting inflammatory mechanisms. Given the tremendous world-wide impact of the COVID-19 pandemic, research efforts are converging towards the use of cannabinoids to attenuate severe or fatal forms of the disease. The present survey aims to explore possible correlations between cannabis use, either recreational or medical, over the presence of SARS-COV-2 contagion, along with the symptom’s severity. 4026 surveys were collected via electronic form. Results suggest a relation between any type of cannabis use and a lower risk of SARS-COV-2 contagion (p=0,004; OR=0,689, IC95% 0,534-0,889). Despite several methodological limitations, the present survey steps up the urge to expand our understanding on cannabinoids potential use on human controlled studies, that can better arm us in the fight against the current COVID-19 pandemic.
What (if anything) is going on? Examining longitudinal associations between social media use and mental ill-health among young people
Authors: Kelly Yvonne , Xue Baowen , Booker Cara , Sacker Amanda , Lacey Rebecca , Ploubidis George , Patalay Praveetha 
Published: April 2022

AbstractObjectivesIn mid-adolescence, to 1) examine cyclical associations between social media use and mental ill health by investigating longitudinal and bidirectional associations, dose response relationships, and changes in social media use and in mental health; 2) assess potential interaction effects between social media use and mental health with pre-existing early life vulnerabilities.MethodsLongitudinal data on 12,114 participants from the Millennium Cohort Study on social media use, depressive symptoms, self-harm and early life risk factors were used.ResultsWe found little support for the existence of cyclical relationships between social media use and mental health. Where detected, effect sizes were small. Dose response associations were seen in the direction of mental health to social media (depressive symptoms 1 time OR=1.22, 2 times OR=1.71; self-harm 1 time OR=1.17, 2 times OR=1.53), but not for social media to mental health. Changes in social media use and changes in mental health were not associated with each other. We found no evidence to suggest that either social media use or mental health interacted with pre-existing risk for mental ill health.ConclusionsFindings highlight the possibility that observed longitudinal associations between social media use and mental health might reflect other risk processes or vulnerabilities and/or the precision of measures used. More detailed and frequently collected prospective data about online experiences, including those from social media platforms themselves will help to provide a clearer picture of the relationship between social media use and mental health.
Physical activity-correlated changes in plasma enzyme concentrations in fragile sarcolemmal muscular dystrophies
Authors: Blank Paul S. , Golding Adriana E. , Benavides Ivonne Morales , Waters Hang , Mekhedov Elena , Bezrukov Ludmila , Wachter Rebecca D. , Mikhailenko Irina , Brown Robert H. , Bönnemann Carsten G. , Demidowich Andrew P. , Jain Minal S. , Yanovski Jack A. , Zimmerberg Joshua 
Published: April 2022

STRUCTURED ABSTRACTBackground and ObjectivesMuscular dystrophies associated with decreased sarcolemma integrity lack validated clinical measures of sarcolemma fragility that can be used to assess disease progression and the effects of therapies designed to reduce sarcolemma fragility. We conducted a pilot study to test the hypothesis that physical activity leads to significant changes in muscle-derived plasma enzymes in participants with “fragile sarcolemmal muscular dystrophies” (FSMD).MethodsWe enrolled ambulatory individuals clinically affected with genetically confirmed FSMD neither taking anti-inflammatory medications nor having relevant co-morbidities for an inpatient study. Over five days, blood samples at 20 time points were obtained. Plasma enzymes alanine and aspartate aminotransferase (ALT, AST), creatine kinase (CK), and lactate dehydrogenase (LDH), all found in muscle, were measured before and after routine morning activities and motor function testing. Analysis of Z-transformed time series data led to feature and kinetic models that revealed activity-dependent feature and kinetic parameters.ResultsAmong the 11 enrolled participants, (LGMD Type 2B/R2 Dysferlin-related (4F/1M), LGMD Type 2L/R12 Anoctamin-5-related (3F/2M), LGMD Type 2I/R9 FKRP-related (1M)), plasma enzymes increased with activity. The average % change +/- SEM with morning activity across all participants was ALT 12.8 ± 2.8%, AST 11.6 ± 2.9%, CK 12.9 ± 2.8%, and LDH 12.2 ± 3.9%, suggesting the increases originate from the same stimulated source, presumably skeletal muscle. For ALT, AST, CK, and LDH, characteristic kinetic features include (a) elevated enzyme activities on arrival that decreased overnight; (b) a longer decay trend observed over the week, and (c) for ALT, AST, and CK, a similar decay trend observed with post-morning activity blood draws.DiscussionControlled activity-dependent changes in plasma ALT, AST, and CK on time scales of days to weeks can serve as common outcome measures for sarcolemma integrity and may be efficient and effective tools for monitoring disease progression and treatment efficacy for both individuals and patient populations. In addition, this study provides data that may benefit patient management as it can inform guidance on duration and type of activity that minimizes muscle damage.
Summaries, Analysis and Simulations of Recent COVID-19 Epidemics in Mainland China
Authors: Min Lequan 
Published: April 2022

AbstractBackgroundGlobally COVID-19 epidemics have caused tremendous disasters. China prevented effectively the spread of COVID-19 epidemics before 2022. Recently Omicron and Delta variants cause a surge in reported COVID-19 infections.MethodsUsing differential equations and real word data, this study modelings and simulates COVID-19 epidemic in mainland China, estimates transmission rates, recovery rates, and blocking rates to symptomatic and asymptomatic infections. The transmission rates and recovery rates of the foreign input COVID-19 infected individuals in mainland China have also been studied.ResultsThe simulation results were in good agreement with the real word data. The recovery rates of the foreign input symptomatic and asymptomatic infected individuals are much higher than those of the mainland COVID-19 infected individuals. The blocking rates to symptomatic and asymptomatic mainland infections are lower than those of the previous epidemics in mainland China. The blocking rate implemented between March 24-31, 2022 may not prevent the rapid spreads of COVID-19 epidemics in mainland China. For the foreign input COVID-19 epidemics, the numbers of the current symptomatic individuals and the asymptomatic individuals charged in medical observations have decreased significantly after March 17 2022.ConclusionsNeed to implement more strict prevention and control strategies to prevent the spread of the COVID-19 epidemics in mainland China. Keeping the present prevention and therapy measures to foreign input COVID-19 infections can rapidly reduce the number of foreign input infected individuals to a very low level.
Classifying REM Sleep Behavior Disorder through CNNs with Image-Based Representations of EEGs
Authors: Srivastava Saurish 
Published: April 2022

ObjectiveRapid Eye Movement Sleep Behavior Disorder (RBD) is a parasomnia with a high conversion rate to α–synucleinopathies such as Parkinson’s Disease (PD), dementia with Lewy bodies (DLB), and multiple system atrophy (MSA). The objective of this paper is to classify RBD in patients through a convolutional neural network utilizing imagebased representations of electroencephalogram (EEG) channels.MethodsAnalysis was conducted on polysomnography data from 22 patients with RBD and 12 healthy controls acquired from the Cyclic Alternating Pattern (CAP) Sleep Database. EEG channels were split into four frequency bands (theta, alpha, beta, and gamma). Power spectrum density was calculated through a Fast Fourier Transformation (FFT) and converted into 2D images through bicubic interpolation. RBD classification was accomplished through a pre-trained VGG-16 CNN with layer weights being fine-tuned.ResultsThe model was successful in classifying RBD patients over non-RBD patients and achieved 97.92% accuracy over 40 epochs. Accuracy increased dramatically with increased data generated from FFT and interpolation (62.63% to 97.92%).ConclusionsThis project proposes a novel approach toward an automatic classification of RBD and highlights the importance of deep learning models in the field. The proposed transfer learning model outperforms state-of-the-art models and preliminarily accounts for the lack of computational resources in clinical spaces, thereby increasing the accessibility of automatic classification.SignificanceBy leveraging transfer learning and raw data, the results demonstrate that a similar model for the classification of RBD patients could easily be translated to the clinical atmosphere, drastically accelerating the classification pipeline. The proposed methods are also applicable to α–synucleinopathies, including PD, DLB, and MSA.
Evaluation of Eight Lateral Flow Tests for the detection of anti-SARS-CoV-2 antibodies in a vaccinated population
Authors: Greenland-Bews Caitlin , Byrne Rachel. L. , Owen Sophie. I. , Watkins Rachel. L. , Bengey Daisy , Buist Kate , Clerkin Karina , Escadafal Camille , Finch Lorna. S. , Gould Susan , Giorgi Emanuele , Hodgkinson Andy , Mashenko Larysa , Powell Darren , Savage Helen. R. , Thompson Caitlin. R. , Turtle Lance , Wardale Jahanara , Wooding Dominic , Edwards Thomas , Atienzar Ana Cubas , Adams Emily. R. 
Published: April 2022

AbstractWith the distribution of COVID-19 vaccinations across the globe and the limited access in many countries, quick determination of an individual’s antibody status could be beneficial in allocating limited vaccine doses in low- and middle-income countries (LMIC). Antibody lateral flow tests (LFTs) have potential to address this need as a quick, point of care test, they also have a use case for identifying sero-negative individuals for novel therapeutics, and for epidemiology. Here we present a proof-of-concept evaluation of eight LFT brands using sera from 95 vaccinated individuals to determine sensitivity for detecting vaccination generated antibodies. All 95 (100%) participants tested positive for anti-spike antibodies by the chemiluminescent microparticle immunoassay (CMIA) reference standard post-dose two of their SARS-CoV-2 vaccine: BNT162b2 (Pfizer/BioNTech, n=60), AZD1222 (AstraZeneca, n=31), mRNA-1273 (Moderna, n=2) and Undeclared Vaccine Brand (n=2). Sensitivity increased from dose one to dose two in six out of eight LFTs with three tests achieving 100% sensitivity at dose two in detecting anti-spike antibodies. These tests are quick, low-cost point-of-care tools that can be used without prior training to establish antibody status and may prove valuable for allocating limited vaccine doses in LMICs to ensure those in at risk groups access the protection they need. Further investigation into their performance in vaccinated peoples is required before more widespread utilisation is considered.
EARLY OUTPATIENT TREATMENT OF COVID-19: A RETROSPECTIVE ANALYSIS OF 392 CASES IN ITALY
Authors: Cosentino Marco , Vernocchi Veronica , Martini Stefano , Marino Franca , Allasino Barbara , Balzola Maria , Burigana Fabio , Dallari Alberto , Pagano Carlo Servo Florio , Palma Antonio , Rango Mauro ,   the IppocrateOrg Association Working Group for the Early Outpatient Treatment of COVID-19
Published: April 2022

AbstractIntroductionThe pandemic of severe acute respiratory syndrome (SARS)-coronavirus-2 (CoV-2) disease 2019 (COVID-19) was declared in march 2020. Knowledge of COVID-19 pathophysiology soon provided a strong rationale for the early use of anti-inflammatory, antiplatelet and anticoagulant drugs, however the evidence was only slowly and partially incorporated into institutional guidelines. Unmet needs of COVID-19 outpatients were soon taken care of by networks of physicians and researchers, using pharmacotherapeutic approaches based on the best available experiences.MethodsObservational retrospective study investigating characteristics, management and outcomes in COVID-19 patients taken care of in Italy by physicians volunteering within the IppocrateOrg Association, one of the main international assistance networks, between 1st november 2020 and 31st march 2021.ResultsTen doctors took part in the study and provided data about 392 consecutive COVID-19 patients. Patients’ mean age was 48,5 years (range: 0,5-97). They were 51,3% females and were taken care of when in COVID-19 stage 0 (15,6%), 1 (50,0%), 2a (28,8%), 2b (5,6%). Many patients were overweight (26%) or obese (11,5%), with chronic comorbidities (34,9%), mainly cardiovascular (23%) and metabolic (13,3%). Drugs most frequently prescribed included: vitamins and supplements (98,7%), aspirin (66,1%), antibiotics (62%), glucocorticoids (41,8%), hydroxychloroquine (29,6%), enoxaparin (28,6%), colchicine (8,9%), oxygen therapy (6,9%), ivermectin (2,8%). Hospitalization occurred in 5,8% of total cases, mainly in patients taken care of when in stage 2b (27,3%). Altogether, 390 patients (99,6%) recovered, one patient (0,2%) was lost at follow up, and one patient (0,2%) died after hospitalization. One doctor reported one grade 1 adverse drug reaction (ADR) (transient or mild discomfort), and 3 doctors reported in total 8 grade 2 ADR (mild to moderate limitation in activity).ConclusionsThis is the first study describing attitudes and behaviors of physicians caring for COVID-19 outpatients, and the effectiveness and safety of COVID-19 early treatment in the real world. COVID-19 lethality in our cohort was 0,2%, while the overall COVID-19 lethality in Italy in the same period was between 3% and 3,8%. The use of individual drugs and drug combinations described in this study appears therefore effective and safe, as indicated by the few and mild ADR reported. Present evidence should be carefully considered by physicians caring for COVID-19 patients as well as by political decision makers managing the current global crisis.