bluuebunny/crossref_metadata_2025_split huggingface dataset:
Noninvasive Machine Learning Screening Model for Dacryocystitis Based on Ocular Surface Indicators
Authors: Song Xuefei , Li Lunhao , Han Fuchang , Liao Shenghui , Xiao Caiwen 
Published: July 2021

Background:Dacryocystitis is an orbital disease that can be easily misdiagnosed. The most common diagnostic tools for dacryocystitis are computed tomography, lacrimal duct angiography, and lacrimal tract irrigation. Yet, those are invasive methods, which are not conducive to extensive screening.Objective:To explore the significance of ocular surface indicators and demographic data in the screening of dacryocystitis.Materials and Methods:Data were prospectively collected from 56 patients with dacryocystitis (56 eyes) and 56 healthy individuals. Collected indicators included demographic information (gender, age), ocular surface data of tear meniscus height, objective scatter index (OSI), and clinical diagnosis. The model features were screened out by machine learning to establish a dacryocystitis screening model.Results:Tear meniscus height, OSI_maximum Lyapunov exponent, basic OSI, median of OSI, mean of OSI, slope coefficient of OSI linear regression, coefficient of variation in OSI, interquartile range of OSI, and other 8 parameters were used as model parameters to establish a dacryocystitis screening model with an overall detection accuracy of 85.71%.Conclusions:This new screening model that is based on ocular surface indicators provides a new option for noninvasive screening of dacryocystitis.
Appropriateness of Computed Tomography Scanning in the Diagnosis of Craniosynostosis
Authors: Margulies Ilana G. , Graziano Francis , Goel Pedram , Xu Hope , Bui Anthony H. , Brown Stav , Sanati-Mehrizy Paymon , Morgenstern Peter F. , Urata Mark M. , Taub Peter J. 
Published: July 2021

Introduction:
Although physicians from a variety of specialties encounter infants with possible craniosynostosis, judicious use of computed tomography (CT) imaging is important to avoid unnecessary radiation exposure and healthcare expense. The present study seeks to determine whether differences in specialty of ordering physician affects frequency of resulting diagnostic confirmations requiring operative intervention.

Methods:
Radiology databases from 2 institutions were queried for CT reports or indications that included “craniosynostosis” or “plagiocephaly.” Patient demographics, specialty of ordering physician, confirmed diagnosis, and operative interventions were recorded. Cost analysis was performed using the fixed unit cost for a head CT to calculate the expense before 1 study led to operative intervention.

Results:
Three hundred eighty-two patients were included. 184 (48.2%) CT scans were ordered by craniofacial surgeons, 71 (18.6%) were ordered by neurosurgeons, and 127 (33.3%) were ordered by pediatricians. One hundred four (27.2%) patients received a diagnosis of craniosynostosis requiring operative intervention. Craniofacial surgeons and neurosurgeons were more likely than pediatricians to order CT scans that resulted in a diagnosis of craniosynostosis requiring operative intervention (P < 0.001), with no difference between craniofacial surgeons and neurosurgeons (P = 1.0). The estimated cost of obtaining an impact CT scan when ordered by neurosurgeons or craniofacial surgeons as compared to pediatricians was $2369.69 versus $13,493.75.

Conclusions:
Clinicians who more frequently encounter craniosynostosis (craniofacial and neurosurgeons) had a higher likelihood of ordering CT images that resulted in a diagnosis of craniosynostosis requiring operative intervention. This study should prompt multi-disciplinary interventions aimed at improving evaluation of pretest probability before CT imaging.
Analysis of the Effect of Weight Loss on Eustachian Tube Function by Transnasal Videoendoscopy
Authors: Eravci Fakih Cihat , Yildiz Bariş Doğu , Özcan Kürşat Murat , Moran Münevver , Çolak Mustafa , Karakuş Mehmet Fatih , Karakurt Süleyman Emre , Ikinciogullari Aykut , Dere Haci Hüseyin 
Published: July 2021

Objective:
To investigate the effect of weight loss after bariatric surgery on eustachian tube (ET) function with video endoscopy.

Materials and Methods:
The present study was conducted as a prospective cohort and was completed with 19 patients. Three-step tympanometry (basal, Toynbee, Valsalva), dynamic slow-motion video endoscopy, and the Eustachian Tube Dysfunction Questionnaire-7 (ETDA-7) were applied to the patients preoperatively before bariatric surgery and in the postoperative 6th month. Dynamic slow-motion video endoscopy was graded between 0 and 3, or classified as patulous, as indicated in the literature.

Results:
The mean body mass index of 6 male and 13 female patients decreased from 47.3 ± 4.6 to 31.2 ± 5.4. Grade decline (median 2 ± 1) was experienced in all patients in DSVE, and 1 patient resulted as patulous ET. The ETDA-7 scores decreased in11 patients, remained stable in 7 patients, and increased in 1 patient with patulous ET. The statistical analysis of the preoperative and postoperative DSVE grading and ETDA-7 scores, excluding the patulous ET patient, was found to be significant (P
= 0.001 and P
= 0.003, respectively). There was no significant change in any of the tympanometry parameters (P > 0.05).

Conclusions:
Rapid weight loss with bariatric surgery results in an improvement in both the DSVE images and in the complaints of ET dysfunction in the majority of patients, but in some patients it may result in patulous ET. Therefore, preoperative evaluation of the ET with DSVE and questioning the patient's complaints are important in predicting patients who may develop patulous ET.
Local Control and Survival After Induction Chemotherapy and Ablative Radiation Versus Resection for Pancreatic Ductal Adenocarcinoma With Vascular Involvement
Authors: Jolissaint Joshua S. , Reyngold Marsha , Bassmann Jared , Seier Kenneth P. , Gönen Mithat , Varghese Anna M. , Yu Kenneth H. , Park Wungki , O’Reilly Eileen M. , Balachandran Vinod P. , D’Angelica Michael I. , Drebin Jeffrey A. , Kingham T. Peter , Soares Kevin C. , Jarnagin William R. , Crane Christopher H. , Wei Alice C. 
Published: July 2021

Objective:
We sought to compare overall survival (OS) and disease control for patients with localized pancreatic ductal adenocarcinoma (PDAC) treated with ablative dose radiotherapy (A-RT) versus resection.

Summary Background Data:
Locoregional treatment for PDAC includes resection when possible or palliative RT. A-RT may offer durable tumor control and encouraging survival.

Methods:
This was a single-institution retrospective analysis of patients with PDAC treated with induction chemotherapy followed by A-RT [≥98 Gy biologically effective dose (BED) using 15–25 fractions in 3–4.5 Gy/fraction] or pancreatectomy.

Results:
One hundred and four patients received A-RT (49.8%) and 105 (50.2%) underwent resection. Patients receiving A-RT had larger median tumor size after induction chemotherapy [3.2 cm (undetectable-10.9) vs 2.6 cm (undetectable-10.7), P < 0.001], and were more likely to have celiac or hepatic artery encasement (48.1% vs 11.4%, P <0.001), or superior mesenteric artery encasement (43.3% vs 9.5%, P < 0.001); however, there was no difference in the degree of SMV/PV involvement (P = 0.123). There was no difference in locoregional recurrence/progression at 18-months between A-RT and resection; cumulative incidence was 16% [(95% confidence interval (CI) 10%–24%] versus 21% (95% CI 14%–30%), respectively (P
= 0.252). However, patients receiving A-RT had a 19% higher 18-month cumulative incidence of distant recurrence/progression [58% (95% CI 48%–67%) vs 30% (95% CI 30%–49%), P
= 0.004]. Median OS from completion of chemotherapy was 20.1 months for A-RT patients (95% CI 16.4–23.1 months) versus 32.9 months (95% CI 29.7–42.3 months) for resected patients (P < 0.001).

Conclusion:
Ablative radiation is a promising new treatment option for PDAC, offering locoregional disease control similar to that associated with resection and encouraging survival.
Neuromuscular junction disorders beyond myasthenia gravis
Authors: Oh Shin J. 
Published: July 2021

Purpose of review
To give an overview of the recent data on three autoimmune neuromuscular junction disorders with the recent Food Drug Administration (FDA) approval of amifampridine [3,4-Diaminopyridine (3,4-DAP) and 3,4-diaminopyridine phosphate (3,4-DAPP) for the treatment of Lambert-Eaton myasthenic syndrome (LEMS).

Recent findings
In LEMS, the most important recent development is the introduction of FDA approved amifampridine for the symptomatic treatment. Randomized controlled studies showed an extremely effective improvement with amifampridine with daily dose of ≤ 80 mg with minimal side reactions. The next important development is in the electrodiagnostic criteria. Now 10 s exercise and an incremental response ≥ 60% either after 10 s exercise or at the high-rate stimulation in the repetitive nerve stimulation test are recommended as the standard tests.
In 2016, myasthenia-gravis Lambert-Eaton overlap syndrome (MLOS) was coined as new syndrome for patients with myasthenia gravis and LEMS combined symptoms in same patients.
In Isaacs syndrome, voltage gated calcium channel antibody order is no longer recommended because of low specificity for immunotherapy responsive disorders. Instead, ‘ leucine-rich glioma-inactivated 1 (LGI1) and contactin-associated like-2 (CASPR2) autoantibody tests’ are recommended.

Summary
In LEMS, amifampridine (3,4 DAP and 3,4-DAPP) is approved by the FDA as an effective symptomatic treatment. MLOS is coined as new syndrome recently. In Isaacs syndrome, LGI1 and CASPR2 antibody tests are recommended.
Genetic therapy for congenital myopathies
Authors: Maani Nika , Karolczak Sophie , Dowling James J. 
Published: July 2021

Purpose of review
There has been an explosion of advancement in the field of genetic therapies. The first gene-based treatments are now in clinical practice, with several additional therapeutic programs in various stages of development. Novel technologies are being developed that will further advance the breadth and success of genetic medicine.
Congenital myopathies are an important group of neuromuscular disorders defined by structural changes in the muscle and characterized by severe clinical symptoms caused by muscle weakness. At present, there are no approved drug therapies for any subtype of congenital myopathy.
In this review, we present an overview of genetic therapies and discuss their application to congenital myopathies.

Recent findings
Several candidate therapeutics for congenital myopathies are in the development pipeline, including ones in clinical trial. These include genetic medicines such as gene replacement therapy and antisense oligonucleotide-based gene knockdown. We highlight the programs related to genetic medicine, and also discuss congenital myopathy subtypes where genetic therapy could be applied.

Summary
Genetic therapies are ushering in an era of precision medicine for neurological diseases. Congenital myopathies are conditions ideally suited for genetic medicine approaches, and the first such therapies will hopefully soon be reaching congenital myopathy patients.
Variants of SARS-COV-2 and the Death Toll
Authors: Saito Takesi 
Published: July 2021

AbstractNew variants of SARS-COV-2 have been found in various countries. Especially, the UK has been attacked by India’s Delta Plus, and the spread of infection has been very rapid, since it is extremely infectious. Fortunately, however, the number of deaths has been stayed flat, where deaths are reported to be those who are not yet received a shot of COVID-19 vaccine. In this short not, we would like to consider why the number of deaths is so small, compared with high cases, around the infection peak, when the basic reproduction number is very large.
Polygenic Risk Prediction using Gradient Boosted Trees Captures Non-Linear Genetic Effects and Allele Interactions in Complex Phenotypes
Authors: Elgart Michael , Lyons Genevieve , Romero-Brufau Santiago , Kurniansyah Nuzulul , Brody Jennifer A. , Guo Xiuqing , Lin Henry J , Raffield Laura , Gao Yan , Chen Han , de Vries Paul , Lloyd-Jones Donald M. , Lange Leslie A , Peloso Gina M , Fornage Myriam , Rotter Jerome I , Rich Stephen S , Morrison Alanna C , Psaty Bruce M , Levy Daniel , Redline Susan ,   the NHLBI’s Trans-Omics in Precision Medicine (TOPMed) Consortium, Sofer Tamar 
Published: July 2021

AbstractPolygenic risk scores (PRS) are commonly used to quantify the inherited susceptibility for a given trait. However, the standard PRS fail to account for non-linear and interaction effects between single nucleotide polymorphisms (SNPs). Machine learning algorithms can be used to account for such non-linearities and interactions. We trained and validated polygenic prediction models for five complex phenotypes in a multi-ancestry population: total cholesterol, triglycerides, systolic blood pressure, sleep duration, and height. We used an ensemble method of LASSO for feature selection and gradient boosted trees (XGBoost) for non-linearities and interaction effects. In an independent test set, we found that combining a standard PRS as a feature in the XGBoost model increases the percentage variance explained (PVE) of the prediction model compared to the standard PRS by 25% for sleep duration, 26% for height, 44% for systolic blood pressure, 64% for triglycerides, and 85% for total cholesterol. Machine learning models trained in specific racial/ethnic groups performed similarly in multi-ancestry trained models, despite smaller sample sizes. The predictions of the machine learning models were superior to the standard PRS in each of the racial/ethnic groups in our study. However, among Blacks the PVE was substantially lower than for other groups. For example, the PVE for total cholesterol was 8.1%, 12.9%, and 17.4% for Blacks, Whites, and Hispanics/Latinos, respectively. This work demonstrates an effective method to account for non-linearities and interaction effects in genetics-based prediction models.
Forecasts of weekly incident and cumulative COVID-19 mortality in the United States: A comparison of combining methods
Authors: Taylor Kathryn S. , Taylor James W. 
Published: July 2021

AbstractBackgroundForecasting models have played a pivotal role in health policy decision making during the coronavirus disease-2019 (COVID-19) pandemic. A combined forecast from multiple models will be typically more accurate than an individual forecast, but there are few examples of studies of combined forecasts of COVID-19 data, focusing mainly on simple mean and median ‘ensembles’ and involving short forecast evaluation periods. We aimed to investigate the accuracy of different ways of combining probabilistic forecasts of weekly COVID-19 mortality data, including two weighted methods that we developed previously, on an extended dataset and new dataset, and evaluate over a period of 52 weeks.MethodsWe considered 95% interval and point forecasts of weekly incident and cumulative COVID-19 mortalities between 16 May 2020 and 8 May 2021 in multiple locations in the United States. We compared the accuracy of simple and more complex combining methods, as well as individual models.ResultsThe average of the forecasts from the individual models was consistently more accurate than the average performance of these models (the mean combination), which provides a fundamental motivation for combining. Weighted combining performed well for both incident and cumulative mortalities, and for both interval and point forecasting. Our inverse score with tuning method was the most accurate overall. The median combination was a leading method in the last quarter for both mortalities, and it was consistently more accurate than the mean combination for point forecasting. For interval forecasts of cumulative mortality, the mean performed better than the median. The best performance of the leading individual model was in point forecasting.ConclusionsCombining forecasts can improve the contribution of probabilistic forecasting to health policy decision making during epidemics, and, when there are sufficient historical data on forecast accuracy, weighted combining provides the most accurate method.
An Open Repository of Real-Time COVID-19 Indicators
Authors: Reinhart Alex , Brooks Logan , Jahja Maria , Rumack Aaron , Tang Jingjing , Agrawal Sumit , Saeed Wael Al , Arnold Taylor , Basu Amartya , Bien Jacob , Cabrera Ángel A. , Chin Andrew , Chua Eu Jing , Clark Brian , Colquhoun Sarah , DeFries Nat , Farrow David C. , Forlizzi Jodi , Grabman Jed , Gratzl Samuel , Green Alden , Haff George , Han Robin , Harwood Kate , Hu Addison J. , Hyde Raphael , Hyun Sangwon , Joshi Ananya , Kim Jimi , Kuznetsov Andrew , Motte-Kerr Wichada La , Lee Yeon Jin , Lee Kenneth , Lipton Zachary C. , Liu Michael X. , Mackey Lester , Mazaitis Kathryn , McDonald Daniel J. , McGuinness Phillip , Narasimhan Balasubramanian , O’Brien Michael P. , Oliveira Natalia L. , Patil Pratik , Perer Adam , Politsch Collin A. , Rajanala Samyak , Rucker Dawn , Scott Chris , Shah Nigam H. , Shankar Vishnu , Sharpnack James , Shemetov Dmitry , Simon Noah , Smith Benjamin Y. , Srivastava Vishakha , Tan Shuyi , Tibshirani Robert , Tuzhilina Elena , Van Nortwick Ana Karina , Ventura Valérie , Wasserman Larry , Weaver Benjamin , Weiss Jeremy C. , Whitman Spencer , Williams Kristin , Rosenfeld Roni , Tibshirani Ryan J. 
Published: July 2021

AbstractThe COVID-19 pandemic presented enormous data challenges in the United States. Policy makers, epidemiological modelers, and health researchers all require up-to-date data on the pandemic and relevant public behavior, ideally at fine spatial and temporal resolution. The COVIDcast API is our attempt to fill this need: operational since April 2020, it provides open access to both traditional public health surveillance signals (cases, deaths, and hospitalizations) and many auxiliary indicators of COVID-19 activity, such as signals extracted from de-identified medical claims data, massive online surveys, cell phone mobility data, and internet search trends. These are available at a fine geographic resolution (mostly at the county level) and are updated daily. The COVIDcast API also tracks all revisions to historical data, allowing modelers to account for the frequent revisions and backfill that are common for many public health data sources. All of the data is available in a common format through the API and accompanying R and Python software packages. This paper describes the data sources and signals, and provides examples demonstrating that the auxiliary signals in the COVIDcast API present information relevant to tracking COVID activity, augmenting traditional public health reporting and empowering research and decision-making.
The impact of hypoxia on B cells in COVID-19
Authors: Kotagiri Prasanti , Mescia Federica , Hanson Aimee , Turner Lorinda , Bergamaschi Laura , Peñalver Ana , Richoz Nathan , Moore Stephen D , Ortmann Brian M , Dunmore Benjamin J. , Ruffieux Helene , Morgan Michael D , Tuong Zewen Kelvin , Bashford-Rogers Rachael J M , Hosmillo Myra , Baker Stephen , Elmer Anne , Goodfellow Ian G , Gupta Ravindra K. , Kingston Nathalie , Lehner Paul J. , Matheson Nicholas J. , Richardson Sylvia , Saunders Caroline , Weekes Michael P. ,   Cambridge Institute of Therapeutic Immunology and Infectious Disease-National Institute of Health Research (CITIID-NIHR) COVID BioResource Collaboration, Göttgens Berthold , Toshner Mark , Hess Christoph , Maxwell Patrick. H. , Clatworthy Menna. R. , Nathan James A. , Bradley John R. , Lyons Paul A. , Burrows Natalie , Smith Kenneth G.C. 
Published: July 2021

AbstractProminent early features of COVID-19 include severe, often clinically silent, hypoxia and a pronounced reduction in B cells, the latter important in defence against SARS-CoV-2. This brought to mind the phenotype of mice with VHL-deficient B cells, in which Hypoxia-Inducible Factors are constitutively active, suggesting hypoxia might drive B cell abnormalities in COVID-19. We demonstrated the breadth of early and persistent defects in B cell subsets in moderate/severe COVID-19, including reduced marginal zone-like, memory and transitional B cells, changes we also observed in B cell VHL-deficient mice. This was corroborated by hypoxia-related transcriptional changes in COVID-19 patients, and by similar B cell abnormalities in mice kept in hypoxic conditions, including reduced marginal zone and germinal center B cells. Thus hypoxia might contribute to B cell pathology in COVID-19, and in other hypoxic states. Through this mechanism it may impact on COVID-19 outcome, and be remediable through early oxygen therapy.
Monitoring of COVID-19 Pandemic-related Psychopathology using Machine Learning
Authors: Enevoldsen Kenneth C. , Danielsen Andreas A. , Rohde Christopher , Jefsen Oskar H. , Nielbo Kristoffer L. , Østergaard Søren D. 
Published: July 2021

AbstractThe COVID-19 pandemic has been shown to have major impact on global mental health. We show that the developments in COVID-19 pandemic-related psychopathology can be meaningfully monitored using machine learning methods providing invaluable insights to psychiatric services and of the management of the psychological consequences of the COVID-19 pandemic. The COVID-19 pandemic-related psychopathology among patients with mental illness was found to covary with the pandemic pressure, however, was less pronounced during the second wave compared to the first wave of the pandemic - possibly due to habituation.
CLOT STIFFNESS MEASURED BY SEER SONORHEOMETRY AS A MARKER OF POOR PROGNOSIS IN HOSPITALIZED COVID-19 PATIENTS
Authors: López-Jaime Francisco José , Martín-Téllez Sandra , Doblas-Márquez Alberto , Márquez-Gómez Ignacio , Reguera-Iglesias José María , Muñoz-Pérez Manuel Isidro , Fernández-Bello Ihosvany , Montaño Adrián 
Published: July 2021

SUMMARYBackgroundHigh incidence of life-threatening thrombotic complications is observed in severely ill COVID-19 patients. D-dimer may help evaluate disease severity and predict outcomes at hospital admission. However, its non-specificity and long analysis times strongly constrain its clinical value. Viscoelastic tests (VET) are widely available rapid point-of-care devices that have been shown to detect a hypercoagulable state (increased clot stiffness and fibrinolysis shutdown) as major contributors of the thrombotic complication in COVID-19. Nevertheless, based on the data obtained so far, definitive conclusions have not been drawn.ObjectivesWe aim to evaluate the association between VET parameters, standard coagulation tests and inflammation markers assessed in COVID-19 patients at hospital admission with disease severity and outcomes.Patients/MethodsA total of 69 COVID-19 patients requiring hospitalization were included in the study. The pro-inflammatory and pro-thrombotic state was analyzed by a panel of inflammation markers (IL-6, CRP, LDH, ferritin), routine coagulation tests (PT, aPTT, platelet count, fibrinogen, D-dimer) and a SEER sonorheometry VET profile (Quantra® System).ResultsInflammatory markers IL-6, CRP, LDH and ferritin were elevated in a high percentage of patients (73.6%, 89.2%, 57.1% and 52.4%), as were coagulation-related parameters such as fibrinogen (81.4%) and D-dimer levels (66.2%). Quantra® analysis revealed increased clot stiffness (CS) in 34.8%, particularly due to increased fibrinogen contribution (FCS) in 63.7%. Increased clot stability to lysis (CSL) was observed in 32.4%. Age > 65 years, elevated values of fibrinogen, D-dimer, LDH, increased clot stiffness and resistance to clot lysis were significantly associated with worsening disease. The Quantra® FCS parameter showed a particularly high prognostic value in distinguishing patients with severe symptomatology.ConclusionThe global study of hemostasis by the whole blood point-of-care Quantra® VET system may be a powerful tool for identifying poor prognosis in COVID-19 patients at hospital admission. In particular, FCS measured by Quantra® could be established as a plausible prognostic marker to aid the clinical management of COVID-19 patients.