bluuebunny/crossref_metadata_2025_split huggingface dataset:
Comparing the prognostic value of geriatric health indicators: a population-based study
Authors: Zucchelli Alberto , Vetrano Davide L. , Grande Giulia , Calderón-Larrañaga Amaia , Fratiglioni Laura , Marengoni Alessandra , Rizzuto Debora 
Published: October 2019

Abstract

Background
The identification of individuals at increased risk of poor health-related outcomes is a priority. Geriatric research has proposed several indicators shown to be associated with these outcomes, but a head-to-head comparison of their predictive accuracy is still lacking. We therefore aimed to compare the accuracy of five geriatric health indicators in predicting different outcomes among older persons: frailty index (FI), frailty phenotype (FP), walking speed (WS), multimorbidity, and a summary score including clinical diagnoses, functioning, and disability (the Health Assessment Tool; HAT).

Methods
Data were retrieved from the Swedish National Study on Aging and Care in Kungsholmen, an ongoing longitudinal study including 3363 people aged 60+. To inspect the accuracy of geriatric health indicators, we employed areas under the receiver operating characteristic curve (AUC) for the prediction of 3-year and 5-year mortality, 1-year and 3-year unplanned hospitalizations (1+), and contacts with healthcare providers in the 6 months before and after baseline evaluation (2+).

Results
FI, WS, and HAT showed the best accuracy in the prediction of mortality [AUC(95%CI) for 3-year mortality 0.84 (0.82–0.86), 0.85 (0.83–0.87), 0.87 (0.85–0.88) and AUC(95%CI) for 5-year mortality 0.84 (0.82–0.86), 0.85 (0.83–0.86), 0.86 (0.85–0.88), respectively]. Unplanned hospitalizations were better predicted by the FI [AUC(95%CI) 1-year 0.73 (0.71–0.76); 3-year 0.72 (0.70–0.73)] and HAT [AUC(95%CI) 1-year 0.73 (0.71–0.75); 3-year 0.71 (0.69–0.73)]. The most accurate predictor of multiple contacts with healthcare providers was multimorbidity [AUC(95%CI) 0.67 (0.65–0.68)]. Predictions were generally less accurate among younger individuals (< 78 years old).

Conclusion
Specific geriatric health indicators predict clinical outcomes with different accuracy. Comprehensive indicators (HAT, FI, WS) perform better in predicting mortality and hospitalization. Multimorbidity exhibits the best accuracy in the prediction of multiple contacts with providers.
Tissue diagnosis during colorectal cancer surgery using optical sensing: an in vivo study
Authors: Baltussen E. J. M. , Brouwer de Koning S. G. , Sanders J. , Aalbers A. G. J. , Kok N. F. M. , Beets G. L. , Hendriks B. H. W. , Sterenborg H. J. C. M. , Kuhlmann K. F. D. , Ruers T. J. M. 
Published: October 2019

Abstract
Background
In colorectal cancer surgery there is a delicate balance between complete removal of the tumor and sparing as much healthy tissue as possible. Especially in rectal cancer, intraoperative tissue recognition could be of great benefit in preventing positive resection margins and sparing as much healthy tissue as possible. To better guide the surgeon, we evaluated the accuracy of diffuse reflectance spectroscopy (DRS) for tissue characterization during colorectal cancer surgery and determined the added value of DRS when compared to clinical judgement.

Methods
DRS spectra were obtained from fat, healthy colorectal wall and tumor tissue during colorectal cancer surgery and results were compared to histopathology examination of the measurement locations. All spectra were first normalized at 800 nm, thereafter two support vector machines (SVM) were trained using a tenfold cross-validation. With the first SVM fat was separated from healthy colorectal wall and tumor tissue, the second SVM distinguished healthy colorectal wall from tumor tissue.

Results
Patients were included based on preoperative imaging, indicating advanced local stage colorectal cancer. Based on the measurement results of 32 patients, the classification resulted in a mean accuracy for fat, healthy colorectal wall and tumor of 0.92, 0.89 and 0.95 respectively. If the classification threshold was adjusted such that no false negatives were allowed, the percentage of false positive measurement locations by DRS was 25% compared to 69% by clinical judgement.

Conclusion
This study shows the potential of DRS for the use of tissue classification during colorectal cancer surgery. Especially the low false positive rate obtained for a false negative rate of zero shows the added value for the surgeons.
Trail registration This trail was performed under approval from the internal review board committee (Dutch Trail Register NTR5315), registered on 04/13/2015, https://www.trialregister.nl/trial/5175.
Preterm births and associated factors among mothers who gave birth in Axum and Adwa Town public hospitals, Northern Ethiopia, 2018
Authors: Aregawi Gebrekiros , Assefa Nega , Mesfin Firehiwot , Tekulu Fissaha , Adhena Tesfay , Mulugeta Mussie , Gebreayezgi Guesh 
Published: October 2019

AbstractObjectiveThe objective of this study was to determine the prevalence and associated factors of preterm births among mothers who gave birth in Axum and Adwa public hospitals, Tigray, North Ethiopia, 2018.ResultThis study showed that 13.3% from the total 472 mothers gave a preterm birth. Being a rural resident (AOR = 2.13, 95% CI (1.07,4.22), short inter pregnancy interval (AOR = 5.4, 95% CI (1.32, 22.05), previous preterm birth (AOR = 3.74, 95% CI (1.03, 16.34), Premature rupture of membrane (AOR = 4.14, 95% CI (1.92, 8.89), induced onset of labor (AOR = 2.49, 95% CI (1.06, 5.85) multiple pregnancy (AOR = 5.69, 95% CI (2.27, 14.28), malaria during pregnancy (AOR = 4.71, 95% CI (1.98, 11.23), Presence of chronic illness (AOR = 4.55, 95% CI (1.83, 11.26) were significantly associated with preterm birth.
HutZ is required for biofilm formation and contributes to the pathogenicity of Edwardsiella piscicida
Authors: Shi Yan-Jie , Fang Qing-Jian , Huang Hui-Qin , Gong Chun-Guang , Hu Yong-Hua 
Published: October 2019

AbstractEdwardsiella piscicidais a severe fish pathogen. Haem utilization systems play an important role in bacterial adversity adaptation and pathogenicity. In this study, a speculative haem utilization protein, HutZEp, was characterized inE. piscicida.hutZEpis encoded with two other genes,hutWandhutX, in an operon that is similar to the haem utilization operonhutWXZidentified inV. cholerae. However, protein activity analysis showed that HutZEpis probably not related to hemin utilization. To explore the biological role of HutZEp, a markerlesshutZEpin-frame mutant strain, TX01ΔhutZ, was constructed. Deletion ofhutZEpdid not significantly affect bacterial growth in normal medium, in iron-deficient conditions, or in the presence of haem but significantly retarded bacterial biofilm growth. The expression of known genes related to biofilm growth was not affected byhutZEpdeletion, which indicated that HutZEpwas probably a novel factor promoting biofilm formation inE. piscicida. Compared to the wild-type TX01, TX01ΔhutZexhibited markedly compromised tolerance to acid stress and host serum stress. Pathogenicity analysis showed that inactivation ofhutZEpsignificantly impaired the ability ofE. piscicidato invade and reproduce in host cells and to infect host tissue. In contrast to TX01, TX01ΔhutZwas defective in blocking host macrophage activation. The expression ofhutZEpwas directly regulated by the ferric uptake regulator Fur. This study is the first functional characterization of HutZ in a fish pathogen, and these findings suggested that HutZEpis essential forE. piscicidabiofilm formation and contributes to host infection.
Direct admission to the intensive care unit from the emergency department and mortality in critically ill hematology patients
Authors: Peyrony Olivier , Chevret Sylvie , Meert Anne-Pascale , Perez Pierre , Kouatchet Achille , Pène Frédéric , Mokart Djamel , Lemiale Virginie , Demoule Alexandre , Nyunga Martine , Bruneel Fabrice , Lebert Christine , Benoit Dominique , Mirouse Adrien , Azoulay Elie 
Published: October 2019

Abstract

Background
The aim of this study was to assess the benefit of direct ICU admission from the emergency department (ED) compared to admission from wards, in patients with hematological malignancies requiring critical care.

Methods
Post hoc analysis derived from a prospective, multicenter cohort study of 1011 critically ill adult patients with hematologic malignancies admitted to 17 ICU in Belgium and France from January 2010 to May 2011. The variable of interest was a direct ICU admission from the ED and the outcome was in-hospital mortality. The association between the variable of interest and the outcome was assessed by multivariable logistic regression after multiple imputation of missing data. Several sensitivity analyses were performed: complete case analysis, propensity score matching and multivariable Cox proportional-hazards analysis of 90-day survival.

Results
Direct ICU admission from the ED occurred in 266 (26.4%) cases, 84 of whom (31.6%) died in the hospital versus 311/742 (41.9%) in those who did not. After adjustment, direct ICU admission from the ED was associated with a decreased in-hospital mortality (adjusted OR: 0.63; 95% CI 0.45–0.88). This was confirmed in the complete cases analysis (adjusted OR: 0.64; 95% CI 0.45–0.92) as well as in terms of hazard of death within the 90 days after admission (adjusted HR: 0.77; 95% CI 0.60–0.99). By contrast, in the propensity score-matched sample of 402 patients, direct admission was not associated with in-hospital mortality (adjusted OR: 0.92; 95% CI 0.84–1.01).

Conclusions
In this study, patients with hematological malignancies admitted to the ICU were more likely to be alive at hospital discharge if they were directly admitted from the ED rather than from the wards. Assessment of early predictors of poor outcome in cancer patients admitted to the ED is crucial so as to allow early referral to the ICU and avoid delays in treatment initiation and mis-orientation.
Predicting Ailanthus altissima presence across a managed forest landscape in southeast Ohio
Authors: Iverson Louis R. , Rebbeck Joanne , Peters Matthew P. , Hutchinson Todd , Fox Timothy 
Published: October 2019

AbstractBackgroundThe negative impacts of the exotic tree,Ailanthus altissima(tree-of-heaven, stink tree), is spreading throughout much of the Eastern United States. When forests are disturbed, it can invade and expand quickly if seed sources are nearby.MethodsWe conducted studies at the highly dissected Tar Hollow State Forest (THSF) in southeastern Ohio USA, whereAilanthusis widely distributed within the forest, harvests have been ongoing for decades, and prescribed fire had been applied to about a quarter of the study area. Our intention was to develop models to evaluate the relationship ofAilanthuspresence to prescribed fire, harvesting activity, and other landscape characteristics, using this Ohio location as a case study. Field assessments of the demography ofAilanthusand other stand attributes (e.g., fire, harvesting, stand structure) were conducted on 267 sample plots on a 400-m grid throughout THSF, supplemented by identification ofAilanthusseed-sources via digital aerial sketch mapping during the dormant season. Statistical modeling tools Random Forest (RF), Classification and Regression Trees (CART), and Maxent were used to assess relationships among attributes, then model habitats suitable forAilanthuspresence.ResultsIn all, 41 variables were considered in the models, including variables related to management activities, soil characteristics, topography, and vegetation structure (derived from LiDAR). The most important predictor ofAilanthuspresence was some measure of recent timber harvest, either mapped harvest history (CART) or LiDAR-derived canopy height (Maxent). Importantly, neither prescribed fire or soil variables appeared as important predictors ofAilanthuspresence or absence in any of the models of the THSF.ConclusionsThese modeling techniques provide tools and methodologies for assessing landscapes forAilanthusinvasion, as well as those areas with higher potentials for invasion should seed sources become available. Though a case study on an Ohio forest, these tools can be modified for use anywhereAilanthusis invading.
Multidisciplinary Software Design for the Routine Monitoring and Assessment of Pain in Palliative Care Services: The Development of PainCheck
Authors: Allsop Matthew J. , Johnson Owen , Taylor Sally , Hackett Julia , Allen Peter , Bennett Michael I. , Bewick Bridgette M. 
Published: October 2019

PURPOSE The use of health information technology (HIT) to support patient and health professional communication is emerging as a core component of modern cancer care. Approaches to HIT development for cancer care are often underreported, despite their implementation in complex, multidisciplinary environments, typically supporting patients with multifaceted needs. We describe the development and evaluation of an e-health tool for pain management in patients with advanced cancer, arising from collaboration between health researchers and a commercial software development company. METHODS We adopted a research-led development process, involving patients with advanced cancer and their health professionals, focusing on use within real clinical settings. A software development approach (disciplined agile delivery) was combined with health science research methods (ie, diary studies, face-to-face interviews, questionnaires, prototyping, think aloud, process reviews, and pilots). Three software iterations were managed through three disciplined agile delivery phases to develop PainCheck and prepare it for use in a clinical trial. RESULTS Findings from development phases (inception, elaboration, and construction) informed the design and implementation of PainCheck. During the transition phase, where PainCheck was evaluated in a randomized clinical trial, there was variation in the extent of engagement by patients and health professionals. Prior personal experience and confidence with HIT led to a gatekeeping effect among health professionals, who were reluctant to introduce PainCheck to patients. Patients who did use PainCheck seemed to benefit, and no usability issues were reported. CONCLUSION Health science research methods seemed to help in the development of PainCheck, although a more rigorous application of implementation science methodologies might help to elucidate further the barriers and facilitators to adoption and inform an evidence-based plan for future implementation.
Clinical Data Extraction and Normalization of Cyrillic Electronic Health Records Via Deep-Learning Natural Language Processing
Authors: Zhao Boyang 
Published: October 2019

PURPOSE A substantial portion of medical data is unstructured. Extracting data from unstructured text presents a barrier to advancing clinical research and improving patient care. In addition, ongoing studies have been focused predominately on the English language, whereas inflected languages with non-Latin alphabets (such as Slavic languages with a Cyrillic alphabet) present numerous linguistic challenges. We developed deep-learning–based natural language processing algorithms for automatically extracting biomarker status of patients with breast cancer from three oncology centers in Bulgaria. METHODS We used dual embeddings for English and Bulgarian languages, encoding both syntactic and polarity information for the words. The embeddings were subsequently aligned so that they were in the same vector space. The embeddings were used as input to convolutional or recurrent neural networks to derive the biomarker status of estrogen receptor, progesterone receptor, and human epidermal growth factor receptor 2. RESULTS We showed that we can resolve ambiguity in highly variable medical text containing both Latin and Cyrillic text. Final models incorporating both English and Bulgarian syntax and polarity embeddings achieved F1 scores of 0.90 or higher for all estrogen receptor, progesterone receptor, and human epidermal growth factor receptor 2 biomarkers. The models were robust against human errors originally found in the training set. In addition, such models can be extended for analyzing text containing words not seen during training. CONCLUSION By using several techniques that incorporate dual-word embeddings encoding syntactic and polarity information in two languages followed by deep neural network architectures, we show that researchers can extract and normalize parameters within medical data. The principles described here can be used to analyze Cyrillic or Latin mixed medical text and extract other parameters.
Effect of Public Deliberation on Patient Attitudes Regarding Consent and Data Use in a Learning Health Care System for Oncology
Authors: Jagsi Reshma , Griffith Kent A. , Jones Rochelle D. , Krenz Chris , Gornick Michele , Spence Rebecca , De Vries Raymond , Hawley Sarah T. , Zon Robin , Bolte Sage , Sadeghi Navid , Schilsky Richard L. , Bradbury Angela R. 
Published: October 2019

PURPOSE We sought to generate informed and considered opinions regarding acceptable secondary uses of deidentified health information and consent models for oncology learning health care systems. METHODS Day-long democratic deliberation sessions included 217 patients with cancer at four geographically and sociodemographically diverse sites. Patients completed three surveys (at baseline, immediately after deliberation, and 1-month follow-up). RESULTS Participants were 67.3% female, 21.7% black, and 6.0% Hispanic. The most notable changes in perceptions after deliberation related to use of deidentified medical-record data by insurance companies. After discussion, 72.3% of participants felt comfortable if the purpose was to make sure patients receive recommended care ( v 79.5% at baseline; P = .03); 24.9% felt comfortable if the purpose was to determine eligibility for coverage or reimbursement ( v 50.9% at baseline; P < .001). The most notable change about secondary research use related to believing it was important that doctors ask patients at least once whether researchers can use deidentified medical-records data for future research. The proportion endorsing high importance decreased from baseline (82.2%) to 68.7% immediately after discussion ( P < .001), and remained decreased at 73.1% ( P = .01) at follow-up. At follow-up, non-Hispanic whites were more likely to consider it highly important to be able to conduct medical research with deidentified electronic health records (96.8% v 87.7%; P = .01) and less likely to consider it highly important for doctors to get a patient’s permission each time deidentified medical record information is used for research (23.2% v 51.6%; P < .001). CONCLUSION This research confirms that most patients wish to be asked before deidentified medical records are used for research. Policies designed to realize the potential benefits of learning health care systems can, and should be, grounded in informed and considered public opinion.
Oxygenation of Styrenes Catalyzed by N-Doped Carbon Incarcerated Cobalt Nanoparticles
Authors: Yasukawa Tomohiro , Kobayashi Shū 
Published: October 2019

AbstractWe found that cobalt nanoparticle catalysts supported on nitrogen-doped carbon could facilitate oxygenation of styrenes in a heterogeneous manner. Both the nitrogen dopant and cobalt species were essential to promote the reactions. Based on several mechanistic studies, the formation of radical intermediates on cobalt nanoparticles is proposed.
Protocol for an app-based affective control training for adolescents: proof-of-principle double-blind randomized controlled trial
Authors: Schweizer Susanne , Leung Jovita T. , Kievit Rogier , Speekenbrink Maarten , Trender William , Hampshire Adam , Blakemore Sarah-Jayne 
Published: October 2019

Background: 75% of all mental health problems have their onset before the end of adolescence. Therefore, adolescence may be a particularly sensitive time period for preventing mental health problems. Affective control, the capacity to engage with goal relevant and inhibit distracting information in affective contexts, has been proposed as a potential target for prevention. In this study, we will explore the impact of improving adolescents’ affective control capacity on their mental health. Methods: The proof-of-principle double-blind randomized controlled trial will compare the effectiveness of an app-based affective control training (AffeCT) to a placebo training (P-Training) app. In total, 200 (~50% females) adolescents (11-19 years) will train for 14 days on their training app. The AffeCT will include three different n-back tasks: visuospatial, auditory and dual (i.e., including both modalities). These tasks require participants to flexibly engage and disengage with affective and neutral stimuli (i.e., faces and words). The P-Training will present participants with a perceptual matching task. The three versions of the P-Training tasks vary in the stimuli included (i.e., shapes, words and faces). The two training groups will be compared on gains in affective control, mental health, emotion regulation and self-regulation, immediately after training, one month and one year after training. Discussion: If, as predicted, the proposed study finds that AffeCT successfully improves affective control in adolescents, there would be significant potential benefits to adolescent mental health. As a free app, the training would also be scalable and easy to disseminate across a wide range of settings. Trial registration: The trial was registered on December 10th 2018 with the International Standard Randomised Controlled Trial Number (Registration number: ISRCTN17213032).
Machine Learning–Based Computational Models Derived From Large-Scale Radiographic-Radiomic Images Can Help Predict Adverse Histopathological Status of Gastric Cancer
Authors: Li Qiong , Qi Liang , Feng Qiu-Xia , Liu Chang , Sun Shu-Wen , Zhang Jing , Yang Guang , Ge Ying-Qian , Zhang Yu-Dong , Liu Xi-Sheng 
Published: October 2019

INTRODUCTION:
Adverse histopathological status (AHS) decreases outcomes of gastric cancer (GC). With the lack of a single factor with great reliability to preoperatively predict AHS, we developed a computational approach by integrating large-scale imaging factors, especially radiomic features at contrast-enhanced computed tomography, to predict AHS and clinical outcomes of patients with GC.

METHODS:
Five hundred fifty-four patients with GC (370 training and 184 test) undergoing gastrectomy were retrospectively included. Six radiomic scores (R-scores) related to pT stage, pN stage, Lauren & Borrmann (L&B) classification, World Health Organization grade, lymphatic vascular infiltration, and an overall histopathologic score (H-score) were, respectively, built from 7,000+ radiomic features. R-scores and radiographic factors were then integrated into prediction models to assess AHS. The developed AHS-based Cox model was compared with the American Joint Committee on Cancer (AJCC) eighth stage model for predicting survival outcomes.

RESULTS:
Radiomics related to tumor gray-level intensity, size, and inhomogeneity were top-ranked features for AHS. R-scores constructed from those features reflected significant difference between AHS-absent and AHS-present groups (P < 0.001). Regression analysis identified 5 independent predictors for pT and pN stages, 2 predictors for Lauren & Borrmann classification, World Health Organization grade, and lymphatic vascular infiltration, and 3 predictors for H-score, respectively. Area under the curve of models using those predictors was training/test 0.93/0.94, 0.85/0.83, 0.63/0.59, 0.66/0.63, 0.71/0.69, and 0.84/0.77, respectively. The AHS-based Cox model produced higher area under the curve than the eighth AJCC staging model for predicting survival outcomes. Furthermore, adding AHS-based scores to the eighth AJCC staging model enabled better net benefits for disease outcome stratification.

DISCUSSION:
The developed computational approach demonstrates good performance for successfully decoding AHS of GC and preoperatively predicting disease clinical outcomes.