bluuebunny/crossref_metadata_2025_split huggingface dataset:
Generating evidence for precision medicine: considerations made by the Ubiquitous Pharmacogenomics Consortium when designing and operationalizing the PREPARE study
Authors: van der Wouden Cathelijne H. , Böhringer Stefan , Cecchin Erika , Cheung Ka-Chun , Dávila-Fajardo Cristina Lucía , Deneer Vera H.M. , Dolžan Vita , Ingelman-Sundberg Magnus , Jönsson Siv , Karlsson Mats O. , Kriek Marjolein , Mitropoulou Christina , Patrinos George P. , Pirmohamed Munir , Rial-Sebbag Emmanuelle , Samwald Matthias , Schwab Matthias , Steinberger Daniela , Stingl Julia , Sunder-Plassmann Gere , Toffoli Giuseppe , Turner Richard M. , van Rhenen Mandy H. , van Zwet Erik , Swen Jesse J. , Guchelaar Henk-Jan 
Published: April 2020

Objectives
Pharmacogenetic panel-based testing represents a new model for precision medicine. A sufficiently powered prospective study assessing the (cost-)effectiveness of a panel-based pharmacogenomics approach to guide pharmacotherapy is lacking. Therefore, the Ubiquitous Pharmacogenomics Consortium initiated the PREemptive Pharmacogenomic testing for prevention of Adverse drug Reactions (PREPARE) study. Here, we provide an overview of considerations made to mitigate multiple methodological challenges that emerged during the design.

Methods
An evaluation of considerations made when designing the PREPARE study across six domains: study aims and design, primary endpoint definition and collection of adverse drug events, inclusion and exclusion criteria, target population, pharmacogenomics intervention strategy, and statistical analyses.

Results
Challenges and respective solutions included: (1) defining and operationalizing a composite primary endpoint enabling measurement of the anticipated effect, by including only severe, causal, and drug genotype-associated adverse drug reactions; (2) avoiding overrepresentation of frequently prescribed drugs within the patient sample while maintaining external validity, by capping drugs of enrolment; (3) designing the pharmacogenomics intervention strategy to be applicable across ethnicities and healthcare settings; and (4) designing a statistical analysis plan to avoid dilution of effect by initially excluding patients without a gene–drug interaction in a gatekeeping analysis.

Conclusion
Our design considerations will enable quantification of the collective clinical utility of a panel of pharmacogenomics-markers within one trial as a proof-of-concept for pharmacogenomics-guided pharmacotherapy across multiple actionable gene–drug interactions. These considerations may prove useful to other investigators aiming to generate evidence for precision medicine.
Pediatric Procedural Sedation in the Emergency Setting
Authors: Lucich Elizabeth A. , Adams Nicholas S. , Goote Paige C. , Girotto John A. , Ford Ronald D. 
Published: April 2020

Background:
Pediatric emergency department (ED) visits are common. Many are due to injury, which require procedural treatments with sedation. There are many well researched independent predictors of adverse events for pediatric procedural sedation. The duration of sedation as a predictor of adverse events has not been well studied. This study aims to determine the complication rate and severity of procedural sedation as well as determine if the duration of sedation is correlated with an increased risk of complications.

Methods:
After Institutional Review Board approval, a retrospective study was performed on all patients seen at Helen Devos Children’s ED who received sedation from August 1, 2011, to August 15, 2016. Study variables included age, weight, type of procedure, American Society of Anesthesiologist (ASA) physical status class, Mallampati score, comorbidities, sedation medication, sedation time, and complication. A logistic regression was performed assessing risk factors for complications. Statistical significance was assessed at P < 0.05.

Results:
There were 1,814 patients included in the study. Median sedation time was 20 minutes. There were 70 (3.9%) total complications. Controlling for age, weight, comorbidities, ASA class, Mallampati score, and total sedation medication, sedation time was a significant predictor of a complication (odds ratio: 1.021; 95% CI, 1.004–1.039).

Conclusions:
Pediatric patients can safely undergo procedural sedation in the ED. This study demonstrates a high safety profile for long procedural sedations with slight increases in risk as sedation time increases. There is no identifiable time where the duration of sedation significantly increases the risk of complication.
Locoregional Flap Closure for High-risk Multilevel Spine Surgery
Authors: Rinkinen Jacob R. , Weitzman Rachel E. , Clain Jason B. , Lans Jonathan , Shin John H. , Eberlin Kyle R. 
Published: April 2020

Background:
Postoperative wound complications pose a challenge to patients undergoing complex spine surgery. Long-term sequelae can be devastating including decreased quality of life, meningitis, prolonged hospital stay, and need for reoperation. Among high-risk patients, postoperative wound complications have been shown to approach 40% in the literature. The aim of this study was to identify predictive factors for postoperative complications following soft-tissue reconstruction after high-risk spine surgery with the hypothesis that it would result in significantly fewer postoperative wound complications.

Methods:
A retrospective review of 67 consecutive spine operations at an academic, tertiary care center was performed, evaluating outcomes with a single plastic surgeon in conjunction with the spine surgery team. Data regarding patient demographics, perioperative risk variables, flap type, location of defect, and postoperative outcomes were obtained through retrospective chart review. Complications included soft-tissue complications and a number of reoperations. A bivariate analysis was used to identify predictors of postoperative complication. These data were compared to literature-reported averages.

Results:
A total of 67 consecutive spinal reconstructive operations were included with a mean follow-up of 11.8 months. Thirty-seven patients (55.2%) underwent immediate reconstruction at the time of the index operation, and 30 (44.8%) underwent delayed reconstruction for secondary wound healing problems following the index operation (in which plastic surgery was not involved). The majority of both immediate (95%, n = 35) and delayed (100%, n = 30) patients was defined as high risk based on literature standards. Patients in this series demonstrated a 7.5% complication rate, compared to 18.7% complication rate in the literature. We did not find a difference between major wound complications in the immediate (8.1%) or delayed (6.7%) reconstructive setting (P > 0.99). There were no specific variables identified that predicted postoperative complications.

Conclusion:
This study illustrates a postoperative complication rate of 7.5% among patients undergoing paraspinous or locoregional muscle flap closure by plastic surgery, which is significantly lower than that reported in contemporary literature for these high-risk patients.
De-novo nonalcoholic fatty liver disease at 5 years after liver transplantation: prevalence and predictive factors
Authors: Tejedor-Tejada Javier , Valenzuela Esteban Fuentes , Muñoz Rodrigo Nájera , Gómez Laura Hernandez , García-Pajares Félix , Álvarez Carolina Almohalla , Sánchez-Martín Fátima , Alonso-Martín Carmen , Sánchez-Antolín Gloria 
Published: April 2020

Background and aims:
Nonalcoholic fatty liver disease (NAFLD) is a long-term complication after liver transplantation. Our aims were to determine de-novo-NAFLD at 5-year post-liver transplantation and identify predictive risk factors.

Methods:
This was a retrospective analysis of de-novo-NAFLD at 5-year post-liver transplantation. NAFLD was defined as the radiological evidence of steatosis. Data from transplanted patients between November 2001 and May 2014 were collected. Noninvasive fibrosis scores were calculated. Predictors of de-novo NAFLD and survival were assessed by multivariate analyses and Kaplan–Meier method.

Results:
A total of 252 liver transplantations were evaluated after applying exclusion criteria, (78.6% men) with 54.9 years old (SD ± 9.5). Prevalence of de-novo NAFLD at 5-year post-liver transplantation was 36.1%. Cardiovascular events were presented in 19.88% and 23.08% of non-NAFLD and NAFLD patients, (P = 0.58). On multivariate analysis, male sex (OR, 5.40; P = 0.001), obesity (OR, 3.72; P = 0.017), metabolic syndrome (OR, 4.69; P < 0.001) and de-novo diabetes (OR, 2.79; P = 0.018), were predictive. Significant fibrosis (≥F2) was presented in 58–86%. The mean survival in NAFLD and control group was 166.3 and 173.6 months, respectively (P = 0 0.50).

Conclusion:
De-novo NAFLD at fifth-year post-liver transplantation is frequently and associated with cardiovascular comorbidity. Male sex, obesity, de-novo diabetes and metabolic syndrome were factors associated with de-novo NAFLD. A significant proportion of patients had advanced fibrosis. This group trends toward worse patients’ survival.
Nursing Work Environment and Patient Outcomes in a Hospital Context
Authors: Nascimento Ana , Jesus Élvio 
Published: April 2020

OBJECTIVE
The aims of this study were to summarize the current state of knowledge regarding the relationship between nursing work environment (NWE) and patient outcomes and to identify gaps in the literature.

BACKGROUND
There was an increased awareness of the impact of NWE on patient outcomes, in particular, related to safety and quality of care.

METHOD
Scoping review was conducted. Studies published between 2002 and the 1st quarter of 2018 were included to provide an overview of the research on the associations between NWE and patient outcomes.

RESULTS
Of 2238 titles and abstracts identified, 35 studies were included, and publication ranged from 2005 to 2018. All studies included were observational, 4 had a longitudinal design, and the remaining studies were cross-sectional. Evidence indicates that better NWE decreases the risk of patient adverse events and increases the quality of care.

CONCLUSIONS
The associations between different dimensions of NWE and patient outcomes should be explored.
Self-reported COVID-19 symptoms on Twitter: An analysis and a research resource
Authors: Sarker Abeed , Lakamana Sahithi , Hogg-Bremer Whitney , Xie Angel , Al-Garadi Mohammed Ali , Yang Yuan-Chi 
Published: April 2020

AbstractObjectiveTo mine Twitter to quantitatively analyze COVID-19 symptoms self-reported by users, compare symptom distributions against clinical studies, and create a symptom lexicon for the research community.Materials and methodsWe retrieved tweets using COVID-19-related keywords, and performed semi-automatic filtering to curate self-reports of positive-tested users. We extracted COVID-19-related symptoms mentioned by the users, mapped them to standard concept IDs (UMLS), and compared the distributions to those reported in early studies from clinical settings.ResultsWe identified 203 positive-tested users who reported 1002 symptoms using 668 unique expressions. The most frequently-reported symptoms were fever/pyrexia (66.1%), cough (57.9%), body ache/pain (42.7%), fatigue (42.1%), headache (37.4%), and dyspnea (36.3%) amongst users who reported at least 1 symptom. Mild symptoms, such as anosmia (28.7%) and ageusia (28.1%) were frequently reported on Twitter, but not in clinical studies.ConclusionThe spectrum of COVID-19 symptoms identified from Twitter may complement those identified in clinical settings.
Increased PCR screening capacity using a multi-replicate pooling scheme
Authors: Viehweger A. , Kühnl F. , Brandt C. , König B. , Rodloff A. C. 
Published: April 2020

AbstractEffective public health response to viral outbreaks such as SARS-CoV-2 require reliable information about the spread of the infecting agent. Often real-time PCR screening of large populations is a feasible method to generate this information. Since test capacities are usually limited, pooling of test specimens is often necessary to increase screening capacity, provided that the test sensitivity is not significantly compromised. However, when a traditional pool is tested positive, all samples in the pool need individual retesting, which becomes ineffective at a higher proportion of positive samples. Here, we report a new pooling protocol that mitigates this problem by replicating samples across multiple pools. The resulting pool set allows the sample status to be resolved more often than with traditional pooling. At 2% prevalence and 20 samples per pool, our protocol increases screening capacity by factors of 5 and 2 compared to individual testing and traditional pooling, respectively. The corresponding software to layout and resolve samples is freely available under a BSD license (https://github.com/phiweger/clonepool).
Spatial variability of nitrogen dioxide and formaldehyde and residential exposure of children in the industrial area of Viadana, Northern Italy
Authors: Marcon Alessandro , Panunzi Silvia , Stafoggia Massimo , Badaloni Chiara , de Hoogh Kees , Guarda Linda , Locatelli Francesca , Silocchi Caterina , Ricci Paolo , Marchetti Pierpaolo 
Published: April 2020

ABSTRACTChipboard production is a source of ambient air pollution. We assessed the spatial variability of outdoor pollutants and residential exposure of children living in proximity to the largest industry for chipboard production in Italy, aiming at evaluating the reliability of exposure estimates obtained from passive sampling for an ongoing epidemiological study.We obtained data on NO2 and formaldehyde, collected by the environmental protection agency of Lombardia region, at 25 passive sampling sites in the municipality of Viadana during 10 weeks (2017-18), and compared NO2 measurements with average weekly concentrations from continuous monitors. We compared interpolated surfaces of NO2 and formaldehyde for 2017-18 with previous maps for 2010. We assessed the relationship between residential proximity to the industry and pollutant exposures, assigned both using our maps and available countrywide/continental models based on routine monitoring data on NO2, PM10, and PM2.5.The correlation between weekly NO2 concentrations from a continuous monitor and a co-located passive sampler was high (Pearson’s r = 0.89), although passive sampling underestimated NO2 during the cold season. For both 2010 and 2017-18, we observed higher NO2 and formaldehyde concentrations in the southern part of Viadana, with hot-spots in proximity to the industry. PM10 and PM2.5 exposures were higher for children at <1km to the industry and NO2 exposure was higher at 1-1.7 km, compared to the children living at >3.5 km. The density of roads and population was also higher in proximity to the industry.Findings from a variety of exposure models suggest that children living in proximity to the chipboard industry in Viadana are more exposed to air pollution and that exposure gradients are relatively stable over time.
Is “no test is better than a bad test”? Impact of diagnostic uncertainty in mass testing on the spread of COVID-19
Authors: Gray Nicholas , Calleja Dominic , Wimbush Alexander , Miralles-Dolz Enrique , Gray Ander , De-Angelis Marco , Derrer-Merk Elfriede , Oparaji Bright Uchenna , Stepanov Vladimir , Clearkin Louis , Ferson Scott 
Published: April 2020

AbstractTesting is viewed as a critical aspect of any strategy to tackle epidemics. Much of the dialogue around testing has concentrated on how countries can scale up capacity, but the uncertainty in testing has not received nearly as much attention beyond asking if a test is accurate enough to be used. Even for highly accurate tests, false positives and false negatives will accumulate as mass testing strategies are employed under pressure, and these misdiagnoses could have major implications on the ability of governments to suppress the virus. The present analysis uses a modified SIR model to understand the implication and magnitude of misdiagnosis in the context of ending lockdown measures. The results indicate that increased testing capacity alone will not provide a solution to lockdown measures. The progression of the epidemic and peak infections is shown to depend heavily on test characteristics, test targeting, and prevalence of the infection. Antibody based immunity passports are rejected as a solution to ending lockdown, as they can put the population at risk if poorly targeted. Similarly, mass screening for active viral infection may only be beneficial if it can be sufficiently well targeted, otherwise reliance on this approach for protection of the population can again put them at risk. A well targeted active viral test combined with a slow release rate is a viable strategy for continuous suppression of the virus.
Are there causal relationships between ADHD and BMI? Evidence from multiple genetically informed designs
Authors: Liu Chao-Yu , Schoeler Tabea , Davies Neil M , Peyre Hugo , Lim Kai-Xiang , Barker Edward D , Llewellyn Clare , Dudbridge Frank , Pingault Jean-Baptiste 
Published: April 2020

AbstractBackgroundAttention-deficit/hyperactivity disorder (ADHD) and Body Mass Index (BMI) are associated. However, it remains unclear whether this association reflects causal relationships in either direction, or confounding. Here, we implemented genetically informed methods to examine bidirectional causality and potential confounding.MethodsThree genetically informed methods were employed: (1) cross-lagged twin-differences analysis to assess bidirectional effects of ADHD symptoms and BMI at ages 8, 12, 14 and 16 years in 2,386 pairs of monozygotic twins from the Twins Early Development Study (TEDS), (2) within- and between-family ADHD and BMI polygenic score (PS) analysis in 3,320 pairs of dizygotic TEDS twins and (3) two-sample bidirectional Mendelian randomization (MR) using summary statistics from Genome-Wide Association Studies (GWAS) on ADHD (N=55,374) and BMI (N=806,834).ResultsMixed results were obtained across the three methods. Twin-difference analyses provided little support for cross-lagged associations between ADHD symptoms and BMI over time. PS analyses were consistent with bidirectional relationships between ADHD and BMI with plausible time-varying effects from childhood to adolescence. MR findings were also consistent with bidirectional causal effects between ADHD and BMI. Multivariable MR suggested the presence of substantial confounding in bidirectional relationships.ConclusionsThe three methods converged to highlight multiple sources of confounding in the association between ADHD and BMI. PS and MR analyses suggested plausible causal relationships in both directions. Possible explanations for mixed causal findings across methods are discussed.Key messagesWithin-family polygenic score and Mendelian randomization analyses were consistent with bidirectional causal effects between ADHD and BMI.Findings from different genetically informed methods suggested that multiple sources of confounding are at play, including genetic and shared environmental confounding, population stratification, assortative mating and dynastic effects.The ADHD polygenic score increasingly associated with BMI phenotype from childhood to adolescence, suggesting an increasing role of ADHD in the aetiology of BMI across the development. Conversely, BMI polygenic score association with ADHD phenotypes tended to decrease across the development.Addressing mixed evidence will require increased sample sizes to implement novel methods such as within-family MR.
Machine learning to predict 5-year survival among pediatric Acute Myeloid Leukemia patients and development of OSPAM-C online survival prediction tool
Authors: Das Ashis Kumar , Mishra Shiba , Mishra Devi Kalyan , Gopalan Saji Saraswathy 
Published: April 2020

Abstract:BackgroundAcute myeloid leukemia (AML) accounts for a fifth of childhood leukemia. Although survival rates for AML have greatly improved over the past few decades, they vary depending on demographic and AML type factors.ObjectivesTo predict the five-year survival among pediatric AML patients using machine learning algorithms and deploy the best performing algorithm as an online survival prediction tool.Materials and methodsPediatric patients (0 to 14 years) with a microscopically confirmed AML were extracted from the Surveillance Epidemiology and End Results (SEER) database (2000-2011) and randomly split into training and test datasets (80/20 ratio). Four machine learning algorithms (logistic regression, support vector machine, gradient boosting, and K nearest neighbor) were trained on features to predict five-year survival. Performances of the algorithms were compared, and the best performing algorithm was deployed as an online prediction tool.ResultsA total of 1,477 patients met our inclusion criteria. The gradient boosting algorithm was the best performer in terms of discrimination and predictive ability. It was deployed as the online survival prediction tool named OSPAM-C (https://ashis-das.shinyapps.io/ospam/).ConclusionsOur study provides a framework for the development and deployment of an online survival prediction tool for pediatric patients with AML. While external validation is needed, our survival prediction tool presents an opportunity to reach informed clinical decision-making for AML patients.
Modeling projections for COVID-19 pandemic by combining epidemiological, statistical, and neural network approaches
Authors: Uhlig Steffen , Nichani Kapil , Uhlig Carsten , Simon Kirsten 
Published: April 2020

ABSTRACTAs the number of people affected by COVID-19 disease caused by the novel coronavirus SARS-CoV-2 ebbs and flows in different national and sub-national regions across the world, it is evident that our lifestyle and socio-economic trajectories will have to be adapted and adjusted to the changing scenarios. Novel forecasting tools and frameworks provide an arguable advantage to facilitate this adapting and adjusting process, by promoting efficient resource management at individual and institutional levels. Based on deterministic compartment models we propose an empirical top-down modeling approach to provide epidemic forecasts and risk calculations for (local) outbreaks. We use neural networks to develop leading indicators based on available data for different regions. These indicators are not only used to assess the risk of a (new) outbreak or to determine the effectiveness of a measure at an early stage, but also in parametric models to determine an effective forecast, along with the associated uncertainty. Based on initial results, we show the performance of such an approach and its robustness against inherent disturbances in epidemiological surveillance data. We foresee such a statistical framework to drive web-based automatic platforms to democratize the dissemination of prognosis results.