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1.
Ann Lab Med ; 42(1): 24-35, 2022 Jan 01.
Artigo em Inglês | MEDLINE | ID: mdl-34374346

RESUMO

Background: Laboratory parameter abnormalities are commonly observed in COVID-19 patients; however, their clinical significance remains controversial. We assessed the prevalence, characteristics, and clinical impact of laboratory parameters in COVID-19 patients hospitalized in Daegu, Korea. Methods: We investigated the clinical and laboratory parameters of 1,952 COVID-19 patients on admission in nine hospitals in Daegu, Korea. The average patient age was 58.1 years, and 700 (35.9%) patients were men. The patients were classified into mild (N=1,612), moderate (N=294), and severe (N=46) disease groups based on clinical severity scores. We used chi-square test, multiple comparison analysis, and multinomial logistic regression to evaluate the correlation between laboratory parameters and disease severity. Results: Laboratory parameters on admission in the three disease groups were significantly different in terms of hematologic (Hb, Hct, white blood cell count, lymphocyte%, and platelet count), coagulation (prothrombin time and activated partial thromboplastin time), biochemical (albumin, aspartate aminotransferase, alanine aminotransferase, lactate, blood urea nitrogen, creatinine, and electrolytes), inflammatory (C-reactive protein and procalcitonin), cardiac (creatinine kinase MB isoenzyme and troponin I), and molecular virologic (Ct value of SARS-CoV-2 RdRP gene) parameters. Relative lymphopenia, prothrombin time prolongation, and hypoalbuminemia were significant indicators of COVID-19 severity. Patients with both hypoalbuminemia and lymphopenia had a higher risk of severe COVID-19. Conclusions: Laboratory parameter abnormalities on admission are common, are significantly associated with clinical severity, and can serve as independent predictors of COVID-19 severity. Monitoring the laboratory parameters, including albumin and lymphocyte count, is crucial for timely treatment of COVID-19.


Assuntos
COVID-19 , Análise de Dados , Humanos , Laboratórios , Masculino , Pessoa de Meia-Idade , República da Coreia/epidemiologia , Estudos Retrospectivos , SARS-CoV-2
2.
Recurso na Internet em Português | LIS - Localizador de Informação em Saúde | ID: lis-48438

RESUMO

O CovacManaus alcançou a etapa de seis meses de acompanhamento dos participantes e divulgou na segunda-feira (13/9) os primeiros dados do estudo. Entre os vacinados, 91% apresentaram anticorpos detectáveis após a primeira dose e 99,8% após a segunda dose


Assuntos
Comorbidade , Vacinas , Análise de Dados
3.
BMC Health Serv Res ; 21(1): 936, 2021 Sep 08.
Artigo em Inglês | MEDLINE | ID: mdl-34496839

RESUMO

BACKGROUND: This study aimed to reduce the total waiting time for high-end health screening processes. METHOD: The subjects of this study were recruited from a health screening center in a tertiary hospital in northern Taiwan from September 2016 to February 2017, where a total of 2342 high-end customers participated. Three policies were adopted for the simulation. RESULTS: The first policy presented a predetermined proportion of customer types, in which the total waiting time was increased from 72.29 to 83.04 mins. The second policy was based on increased bottleneck resources, which provided significant improvement, decreasing the total waiting time from 72.29 to 28.39 mins. However, this policy also dramatically increased the cost while lowering the utilization of this health screening center. The third policy was adjusting customer arrival times, which significantly reduced the waiting time-with the total waiting time reduced from 72.29 to 55.02 mins. Although the waiting time of this policy was slightly longer than that of the second policy, the additional cost was much lower. CONCLUSIONS: Scheduled arrival intervals could help reduce customer waiting time in the health screening department based on the "first in, first out" rule. The simulation model of this study could be utilized, and the parameters could be modified to comply with different health screening centers to improve processes and service quality.


Assuntos
Inteligência Ambiental , Análise de Dados , Simulação por Computador , Atenção à Saúde , Humanos , Projetos Piloto , Listas de Espera
4.
Math Biosci Eng ; 18(5): 5409-5426, 2021 06 18.
Artigo em Inglês | MEDLINE | ID: mdl-34517494

RESUMO

After a major outbreak of the coronavirus disease (COVID-19) starting in late December 2019, there were no new cases reported in mainland China for the first time on March 18, 2020, and no new cases reported in Hong Kong Special Administrative Region on April 20, 2020. However, these places had reported new cases and experienced a second wave since June 11, 2020. Here we develop a stochastic discrete-time epidemic model to evaluate the risk of COVID-19 resurgence by analyzing the data from the beginning of the outbreak to the second wave in these three places. In the model, we use an input parameter to represent a few potential risks that may cause a second wave, including asymptomatic infection, imported cases from other places, and virus from the environment such as frozen food packages. The effect of physical distancing restrictions imposed at different stages of the outbreak is also included in the model. Model simulations show that the magnitude of the input and the time between the initial entry and subsequent case confirmation significantly affect the probability of the second wave occurrence. Although the susceptible population size does not change the probability of resurgence, it can influence the severity of the outbreak when a second wave occurs. Therefore, to prevent the occurrence of a future wave, timely screening and detection are needed to identify infected cases in the early stage of infection. When infected cases appear, various measures such as contact tracing and quarantine should be followed to reduce the size of susceptible population in order to mitigate the COVID-19 outbreak.


Assuntos
COVID-19 , Análise de Dados , Busca de Comunicante , Humanos , Quarentena , SARS-CoV-2
5.
Sensors (Basel) ; 21(17)2021 Aug 24.
Artigo em Inglês | MEDLINE | ID: mdl-34502593

RESUMO

Data analysis plays an increasingly valuable role in sports. The better the data that is analysed, the more concise training methods that can be chosen. Several solutions already exist for this purpose in the tennis industry; however, none of them combine data generation with a wristband and classification with a deep convolutional neural network (CNN). In this article, we demonstrate the development of a reliable shot detection trigger and a deep neural network that classifies tennis shots into three and five shot types. We generate a dataset for the training of neural networks with the help of a sensor wristband, which recorded 11 signals, including an inertial measurement unit (IMU). The final dataset included 5682 labelled shots of 16 players of age 13-70 years, predominantly at an amateur level. Two state-of-the-art architectures for time series classification (TSC) are compared, namely a fully convolutional network (FCN) and a residual network (ResNet). Recent advances in the field of machine learning, like the Mish activation function and the Ranger optimizer, are utilized. Training with the rather inhomogeneous dataset led to an F1 score of 96% in classification of the main shots and 94% for the expansion. Consequently, the study yielded a solid base for more complex tennis analysis tools, such as the indication of success rates per shot type.


Assuntos
Esportes , Tênis , Análise de Dados , Aprendizado de Máquina , Redes Neurais de Computação
6.
Comput Intell Neurosci ; 2021: 1890120, 2021.
Artigo em Inglês | MEDLINE | ID: mdl-34504519

RESUMO

With the development of society and the promotion of science and technology, English, as the largest universal language in the world, is used by more and more people. In the life around us, there is information in English all the time. However, because the process of manual recognition of English letters is very labor-intensive and inefficient, the demand for computer recognition of English letters is increasing. This paper studies the influence of the parameters of BP neural network and genetic algorithm on the whole network, including the input, output, and number of hidden layer nodes. Finally, it improves and determines the settings and values of the relevant parameters. On this basis, it shows the rationality of the selected parameters through experiments. The results show that only GA-BP neural network and feature data mining algorithm can complete feature extraction and become the main function of feature classification at the same time. After enough initial data sample analysis training, the GA-BP neural network was found to have good data fault tolerance and feature recognition. The experimental results show that the genetic algorithm can find the best weights and thresholds and the weights and thresholds are given to the BP neural network. After training, the recognition of handwritten letters can be realized. Finally, the convergence of the two algorithms is compared through experiments, which shows that the overall performance of the BP neural network algorithm is improved after genetic algorithm optimization. It can be seen that the genetic algorithm has a good effect in improving the BP neural network and this method has a broad prospect in English feature recognition.


Assuntos
Idioma , Redes Neurais de Computação , Algoritmos , Análise de Dados , Mineração de Dados , Humanos
7.
Comput Intell Neurosci ; 2021: 2491116, 2021.
Artigo em Inglês | MEDLINE | ID: mdl-34504520

RESUMO

In recent years, deep learning has made good progress and has been applied to face recognition, video monitoring, image processing, and other fields. In this big data background, deep convolution neural network has also received more and more attention. In order to extract the ancient Chinese characters effectively, the paper will discuss the structure model, pool process, and network training of deep convolution neural network and compare the algorithm with the traditional machine learning algorithm. The results show that the accuracy and recall rate of the Chinese characters in the plaque of Ming Dynasty can reach the peak, 81.38% and 81.31%, respectively. When the number of training samples increases to 50, the recognition rate of MFA is 99.72%, which is much higher than other algorithms. This shows that the algorithm based on deep convolution neural network and big data analysis has excellent performance and can effectively identify the Chinese characters under different dynasties, different sample sizes, and different interference factors, which can provide a powerful reference for the extraction of ancient Chinese characters.


Assuntos
Big Data , Análise de Dados , Algoritmos , China , Redes Neurais de Computação
8.
Comput Intell Neurosci ; 2021: 6592938, 2021.
Artigo em Inglês | MEDLINE | ID: mdl-34527043

RESUMO

The current music teaching can effectively improve students' music emotional expression indirectly. How to use the PSO-BP neural network to realize the quantitative research of music emotional expression is the current development trend. Based on this, this paper studies the influence factors of music emotion expression based on PSO-BP neural network and big data analysis. Firstly, a music emotion expression analysis model based on PSO-BP neural network algorithm is proposed. The autocorrelation function is used to simulate the emotion expression information in music. Through the maximum value of the autocorrelation function curve in the detection process, the vocal music signal is restored, and then the emotion expressed is analyzed. Secondly, the influence factors of PSO-BP neural network algorithm in music emotion expression are analyzed. The improved PSO-BP neural network algorithm and multidimensional data model are used for comprehensive analysis to accurately analyze the emotion in music expression, and the fuzzy evaluation method and analytic hierarchy process are used for quality evaluation. Finally, the validity of the music emotion analysis model is verified by many experiments.


Assuntos
Análise de Dados , Música , Algoritmos , Emoções , Humanos , Redes Neurais de Computação
9.
Yearb Med Inform ; 30(1): 176-184, 2021 Aug.
Artigo em Inglês | MEDLINE | ID: mdl-34479389

RESUMO

OBJECTIVES: We examine the knowledge ecosystem of COVID-19, focusing on clinical knowledge and the role of health informatics as enabling technology. We argue for commitment to the model of a global learning health system to facilitate rapid knowledge translation supporting health care decision making in the face of emerging diseases. METHODS AND RESULTS: We frame the evolution of knowledge in the COVID-19 crisis in terms of learning theory, and present a view of what has occurred during the pandemic to rapidly derive and share knowledge as an (underdeveloped) instance of a global learning health system. We identify the key role of information technologies for electronic data capture and data sharing, computational modelling, evidence synthesis, and knowledge dissemination. We further highlight gaps in the system and barriers to full realisation of an efficient and effective global learning health system. CONCLUSIONS: The need for a global knowledge ecosystem supporting rapid learning from clinical practice has become more apparent than ever during the COVID-19 pandemic. Continued effort to realise the vision of a global learning health system, including establishing effective approaches to data governance and ethics to support the system, is imperative to enable continuous improvement in our clinical care.


Assuntos
COVID-19 , Gestão do Conhecimento , Sistema de Aprendizagem em Saúde , Informática Médica , Análise de Dados , Registros Eletrônicos de Saúde , Humanos , Disseminação de Informação , Armazenamento e Recuperação da Informação
10.
Talanta ; 234: 122620, 2021 Nov 01.
Artigo em Inglês | MEDLINE | ID: mdl-34364429

RESUMO

We developed a methodology for rapid quantification of extracellular neurotransmitters in mouse brain by PESI/MS/MS and longitudinal data analysis using the R and Stan-based Bayesian state-space model. We performed a rapid analysis for quantifying extracellular l-glutamic acid (L-Glu) and gamma-aminobutyric acid (GABA) in the mouse striatum by combined use of probe electrospray ionization/tandem mass spectrometry (PESI/MS/MS) and in vivo brain microdialysis. We optimized the PESI/MS/MS parameters with the authentic L-Glu, GABA, L-Glu-13C5,15N1, and GABA-D6 standards. We constructed calibration curves of L-Glu and GABA with the stable isotope internal standard correction method (L-Glu-13C5,15N1, and GABA-D6), demonstrating sufficient linearity (R > 0.999). Additionally, the quantitative method for L-Glu and GABA was validated with low-, middle-, and high-quality control samples. The intra- and inter-day accuracy and precision were 0.4%-7.5% and 1.7%-5.4% for L-Glu, respectively, and 0.1%-4.8% and 2.1%-5.7% for GABA, respectively, demonstrating high reproducibility of the method. To evaluate the feasibility of this method, microdialyses were performed on free-moving mice that were stimulated by high-K+-induced depolarization under different sampling conditions: 1) every 5 min for 150 min (n = 2) and 2) every 1 min for 30 min (n = 3). We applied the R and Stan-based Bayesian state-space model to each mouse's time-series data considering autocorrelation, and the model successfully detected abnormal changes in the L-Glu and GABA levels in each mouse. Thus, the L-Glu and GABA levels in all microdialysates approximately increased up to two- and seven-fold levels through high-K+-induced depolarization. Additionally, a 1-min temporal resolution was achieved using this method, thereby successfully monitoring microenvironmental changes in the extracellular L-Glu and GABA of the mouse striatum. In conclusion, this methodology using PESI/MS/MS and Bayesian state-space model allowed easy monitoring of neurotransmitters at high temporal resolutions and appropriate data interpretation considering autocorrelation of time-series data, which will reveal hidden pathological mechanisms of brain diseases, such as Parkinson's disease and Huntington's disease in the future.


Assuntos
Espectrometria de Massas por Ionização por Electrospray , Espectrometria de Massas em Tandem , Animais , Teorema de Bayes , Encéfalo , Análise de Dados , Ácido Glutâmico , Camundongos , Microdiálise , Neurotransmissores , Reprodutibilidade dos Testes , Simulação de Ambiente Espacial
11.
J Orthop Traumatol ; 22(1): 32, 2021 Aug 04.
Artigo em Inglês | MEDLINE | ID: mdl-34350524

RESUMO

BACKGROUND: Using the database of the German Cartilage Registry (KnorpelRegister DGOU), this study aims to present patient- and joint-related baseline data in a large cohort of patients with cam-derived femoroacetabular impingement syndrome (FAI) and to detect symptom-determining factors. MATERIALS AND METHODS: Requiring cam morphology as the primary pathology, 362 patients were found to be eligible for inclusion in the study. The assessment of preoperative baseline data was performed using the patient-reported outcome measure-International Hip Outcome Tool (iHOT-33). Descriptive statistics were performed to present baseline data. Univariate and multiple regression with post hoc testing were used to identify patient- and joint-related factors that might affect the preoperative iHOT-33 and its subscores, respectively. RESULTS: The study collective's mean age was 36.71 ± 10.89 years, with 246 (68%) of them being male. The preoperative mean iHOT-33 total was 46.31 ± 20.33 with the subsection "sports and recreational activities" presenting the strongest decline (26.49 ± 20.68). The parameters "age," "sex," "body mass index" (BMI), and the confirmation of "previous surgery on the affected hip" were identified to statistically affect the preoperative iHOT-33. In fact, a significantly lower mean baseline score was found in patients aged > 40 years (p < 0.001), female sex (p < 0.001), BMI ≥ 25 kg/m2 (p = 0.002) and in patients with previous surgery on the affected hip (p = 0.022). In contrast, the parameters defect grade and size, labral tears, and symptom duration delivered no significant results. CONCLUSIONS: A distinct reduction in the baseline iHOT-33, with mean total scores being more than halved, was revealed. The parameters "age > 40 years," "female sex," "BMI ≥ 25," and confirmation of "previous surgery on the affected hip" were detected as significantly associated with decreased preoperative iHOT-33 scores. These results help to identify symptom-defining baseline characteristics of cam-derived FAI syndrome. TRIAL REGISTRATION: The German Cartilage Registry is conducted in accordance with the Declaration of Helsinki and registered at germanctr.de (DRKS00005617). Registered 3 January 2014-retrospectively registered. The registration of data was approved by the local ethics committees of every participating institution. Primary approval was given by the ethics committee at the University of Freiburg (No. 105/13). https://www.drks.de/drks_web/navigate.do?navigationId=trial.HTML&TRIAL_ID=DRKS00005617.


Assuntos
Impacto Femoroacetabular , Adulto , Idoso , Artroscopia , Cartilagem , Análise de Dados , Feminino , Impacto Femoroacetabular/epidemiologia , Impacto Femoroacetabular/cirurgia , Articulação do Quadril/cirurgia , Humanos , Recém-Nascido , Masculino , Sistema de Registros , Resultado do Tratamento
13.
BMC Bioinformatics ; 22(1): 405, 2021 Aug 17.
Artigo em Inglês | MEDLINE | ID: mdl-34404349

RESUMO

BACKGROUND: The human leukocyte antigen (HLA) proteins play a fundamental role in the adaptive immune system as they present peptides to T cells. Mass-spectrometry-based immunopeptidomics is a promising and powerful tool for characterizing the immunopeptidomic landscape of HLA proteins, that is the peptides presented on HLA proteins. Despite the growing interest in the technology, and the recent rise of immunopeptidomics-specific identification pipelines, there is still a gap in data-analysis and software tools that are specialized in analyzing and visualizing immunopeptidomics data. RESULTS: We present the IPTK library which is an open-source Python-based library for analyzing, visualizing, comparing, and integrating different omics layers with the identified peptides for an in-depth characterization of the immunopeptidome. Using different datasets, we illustrate the ability of the library to enrich the result of the identified peptidomes. Also, we demonstrate the utility of the library in developing other software and tools by developing an easy-to-use dashboard that can be used for the interactive analysis of the results. CONCLUSION: IPTK provides a modular and extendable framework for analyzing and integrating immunopeptidomes with different omics layers. The library is deployed into PyPI at https://pypi.org/project/IPTKL/ and into Bioconda at https://anaconda.org/bioconda/iptkl , while the source code of the library and the dashboard, along with the online tutorials are available at https://github.com/ikmb/iptoolkit .


Assuntos
Análise de Dados , Software , Antígenos de Histocompatibilidade Classe I , Humanos , Espectrometria de Massas , Peptídeos
14.
Zhonghua Zhong Liu Za Zhi ; 43(8): 889-896, 2021 Aug 23.
Artigo em Chinês | MEDLINE | ID: mdl-34407597

RESUMO

Objective: To analyze the survival benefits and treatment related toxic effects of simultaneous integrated boost intensity-modulated radiotherapy (SIB-RT) for non-operative esophageal squamous cell carcinoma patients. Methods: The data of 2 132 ESCC patients who were not suitable for surgery or rejected operation, and underwent radical radiotherapy from 2002 to 2016 in 10 hospitals of Jing-Jin-Ji Esophageal and Esophagogastric Cancer Radiotherapy Oncology Group (3JECROG) were analyzed. Among them, 518 (24.3%) cases underwent SIB (SIB group) and 1 614 (75.7%) cases did not receive SIB (No-SIB group). The two groups were matched with 1∶2 according to propensity score matching (PSM) method (caliper value=0.02). After PSM, 515 patients in SIB group and 977 patients in No-SIB group were enrolled. Prognosis and treatment related adverse effects of these two groups were compared and the independent prognostic factor were analyzed. Results: The median follow-up time was 61.7 months. Prior to PSM, the 1-, 3-, and 5-years overall survival (OS) rates of SIB group were 72.2%, 42.8%, 35.5%, while of No-SIB group were 74.3%, 41.4%, 31.9%, respectively (P=0.549). After PSM, the 1-, 3-, and 5-years OS rates of the two groups were 72.5%, 43.4%, 36.4% and 75.3%, 41.7%, 31.6%, respectively (P=0.690). The univariate survival analysis of samples after PSM showed that the lesion location, length, T stage, N stage, TNM stage, simultaneous chemoradiotherapy, gross tumor volume (GTV) and underwent SIB-RT or not were significantly associated with the prognosis of advanced esophageal carcinoma patients who underwent radical radiotherapy (P<0.05). Cox model multivariate regression analysis showed lesion location, TNM stage, GTV and simultaneous chemoradiotherapy were independent prognostic factors of advanced esophageal carcinoma patients who underwent radical radiotherapy (P<0.05). Stratified analysis showed that, in the patients whose GTV volume≤50 cm(3), the median survival time of SIB and No-SIB group was 34.7 and 30.3 months (P=0.155), respectively. In the patients whose GTV volume>50 cm(3), the median survival time of SIB and No-SIB group was 16.1 and 20.1 months (P=0.218). The incidence of radiation esophagitis and radiation pneumonitis above Grade 3 in SIB group were 4.3% and 2.5%, significantly lower than 13.1% and 11% of No-SIB group (P<0.001). Conclusions: The survival benefit of SIB-RT in patients with locally advanced esophageal carcinoma is not inferior to non-SIB-RT, but without more adverse reactions, and shortens the treatment time. SIB-RT can be used as one option of the radical radiotherapy for locally advanced esophageal cancer.


Assuntos
Neoplasias Esofágicas , Carcinoma de Células Escamosas do Esôfago , Neoplasias de Cabeça e Pescoço , Radioterapia de Intensidade Modulada , Neoplasias Gástricas , Quimiorradioterapia , Análise de Dados , Neoplasias Esofágicas/tratamento farmacológico , Neoplasias Esofágicas/radioterapia , Carcinoma de Células Escamosas do Esôfago/tratamento farmacológico , Humanos , Estudos Retrospectivos
15.
Sensors (Basel) ; 21(16)2021 Aug 18.
Artigo em Inglês | MEDLINE | ID: mdl-34451011

RESUMO

More than 40 years ago, the expansion joints on the Basel border bridge were constructed using corbels and dapped ends. The consoles had to be reinforced as part of the renovation measures due to damage caused by chloride entry and due to the increased loads. Diagonal rods, which were prestressed, were used. Fiber-optic sensors were additionally installed to these highly stressed rods in order to measure the strains and temperatures. This now makes it possible to measure the actual strains in the strengthening of the corbel, estimate fatigue loads, and set up a warning system in case of overstressing. This article presents the design of the measurement system and the analysis of the data. Furthermore, the reference measurements that can establish the relationship between the measured strains and the loads passed over are presented.


Assuntos
Análise de Dados , Tecnologia de Fibra Óptica , Veículos Automotores
16.
Zhonghua Wei Zhong Bing Ji Jiu Yi Xue ; 33(7): 786-791, 2021 Jul.
Artigo em Chinês | MEDLINE | ID: mdl-34412745

RESUMO

OBJECTIVE: To investigate the association between early central venous pressure (CVP) measurement and mortality in patients with sepsis. METHODS: The adult patients with sepsis were identified from the health data of Medical Information Mart for Intensive Care-III v1.4 (MIMIC-III v1.4). Data of all adult patients with sepsis were collected, including gender, age, comorbidities, length of survival, total length of hospital stay and intensive care unit (ICU) stay, sequential organ failure assessment (SOFA) score, vital signs, laboratory test results on the first day, vasoactive agents usage, fluid input, urine output and fluid balance on the first day, need for renal replacement therapy and mechanical ventilation, diagnosis of sepsis, and the time and value of the first CVP measurement in the ICU. Patients were divided into early measurement and control groups based on whether or not they had a CVP measurement within the first 6 hours of ICU stay. According to the time of the first CVP measurement, the patients were subdivided into four subgroups: ≤ 3 hours, 4-6 hours, 7-12 hours and no measurement within 12 hours. The primary endpoint was 28-day mortality. The relationship between initial CVP and mortality was analyzed by Lowess smoothing method. Kaplan-Meier survival analysis and Log-Rank test were performed for univariate analysis. Cox regression analysis was performed for multivariate analysis to estimate the relationship between timeliness of CVP measurement and mortality. RESULTS: A total of 4 733 sepsis patients were enrolled, 1 673 of whom had CVP measured within 6 hours of admission to the ICU, and the other 3 060 patients served as the control group. There were no differences in demographic characteristics and underlying diseases between the two groups, except that the early CVP measurement group had less underlying renal failure compared with control group. The early CVP measurement group had higher lactic acid (Lac) levels and SOFA scores, indicating worse severity of disease as compared with control group. The 28-day mortality in the early CVP measurement group was significantly lower than that in the control group (34.2% vs. 40.7%, P < 0.01). The early CVP measurement group had shorter length of total hospitalization and longer length of ICU stay, higher rate of mechanical ventilation and vasoactive agents dependent, and more fluid input and fluid balanced in the first day of ICU stay compared with control group. Lowess smoothing analysis showed that a "U"-shaped relationship between initial CVP and mortality was identified, suggesting that too high or too low initial CVP was associated with worse survival. Kaplan-Meier survival analysis showed that compared with the patients without early CVP measurement within 12 hours, the cumulative survival rate of patients with CVP measured within 3 hours was significantly higher (66.7% vs. 59.1%; Log-Rank test: χ2 = 15.810, adjusted P < 0.001); while no significant difference was found in patients with CVP measured between 4 hours and 6 hours and between 7 hours and 12 hours compared with the patients without early CVP measurement within 12 hours (64.4%, 60.3% vs. 59.1%; Log-Rank test: χ2 values were 5.630 and 0.100, and adjusted P values were 0.053 and > 0.999, respectively). Cox multivariate analysis showed that the Cox proportional risk model was established by taking patients without CVP measurement within 12 hours as reference, timely CVP measurement after ICU admission was associated with reduced 28-day mortality of patients with sepsis [≤ 3 hours: hazard ratio (HR) = 0.65, 95% confidence interval (95%CI) was 0.55-0.77, P < 0.001; 4-6 hours: HR = 0.72, 95%CI was 0.60-0.87, P = 0.001; 7-12 hours: HR = 0.80, 95%CI was 0.66-0.98, P = 0.032] after the confounding variables (gender, age, SOFA score, initial Lac, renal failure, maximal blood glucose and white blood cell count, and minimal platelet count within 24 hours) were adjusted. CONCLUSIONS: Early CVP measurement is associated with decreased 28-day mortality in patients with sepsis. CVP should be considered as a valuable and easily accessible safety parameter during early fluid resuscitation.


Assuntos
Análise de Dados , Sepse , Pressão Venosa Central , Humanos , Monitorização Fisiológica , Escores de Disfunção Orgânica , Sepse/diagnóstico
18.
Biomed Res Int ; 2021: 4814888, 2021.
Artigo em Inglês | MEDLINE | ID: mdl-34337011

RESUMO

Higher heating value (HHV) is one of the properties of biomass fuels which is essential in investigating their special characteristics and potentialities. In this paper, various techniques based on Gaussian process regression (GPR) were utilized to assess this value for biomass fuels, including several kernel functions, i.e., exponential, Matern, rational quadratic, and squared exponential. An extensive databank was collected from literature. The findings were compared, and the results indicated that Exponential-based model was more accurate, with the coefficient of regression (R 2) of 0.961 and the mean relative error (% MRE) of 3.11 for total data. Compared to former models presented by previous researchers, the model proposed in this study showed a higher ability to predict output values. With various analyses, it can be concluded that the proposed method has a high rate of efficiency in assessing the HHV of various biomass.


Assuntos
Biocombustíveis/análise , Análise de Dados , Calefação , Modelos Teóricos , Distribuição Normal , Reprodutibilidade dos Testes
19.
J Urban Health ; 98(Suppl 1): 69-78, 2021 08.
Artigo em Inglês | MEDLINE | ID: mdl-34414511

RESUMO

Food is an important determinant of health, featuring prominently in the Sustainable Development Goals. The term "big data" is seldom used in relation to food, partly because food data are scattered across different sectors. The increasing availability of food-related data presents an opportunity to glean new insights on food and food systems. These insights may enhance the quality of products and services and improve decision-making on optimizing food availability, all to the end of producing better health. Yet, knowledge gaps remain about the unique opportunities and challenges linked to big data on food and their use in decision-making. This scoping review explored the available literature linking food with big data and decision-making, using the following research question: What is the current literature on data about food, and how are these data used in decision-making? We searched PubMed until 29 February 2020 and Embase, Web of Sciences, and the Cochrane Database of Systematic Reviews until 8 March 2020. We included studies written in English and conducted narrative analyses to identify relevant themes from included studies. Sixteen studies fulfilled our eligibility criteria, including big data analyses, modelling studies, and reviews. These studies described the added value of using big data and how evidence from big data had or can be used for decision-making, as well as challenges and opportunities for such use. The majority of the included studies examined the link between food and big data, while hypothesizing of how these insights could inform decision-making, including policies, interventions, programs, and financing. There were only two examples wherein big data on food informed decision-making directly. The review highlights several false dichotomies in how the subject is approached in the literature and the importance of context, both between and within countries, in shaping the availability and types of data that can be used as meaningful evidence to inform decision-making. This review shows the paucity of research around the intersection of food, big data, and decision-making, as well as the potential in using big data on food systems to the end of informing decisions to improve the health of populations. Future research and decision-making around health systems can benefit from examining the full spectrum of perspectives on the subject. Future research and decision-making around health systems can also employ the steadfast embrace of technology, which will potentially reduce disparities in big data availability, to the end of improving the health of populations.


Assuntos
Big Data , Desenvolvimento Sustentável , Análise de Dados , Humanos , Revisões Sistemáticas como Assunto
20.
Nat Commun ; 12(1): 4988, 2021 08 17.
Artigo em Inglês | MEDLINE | ID: mdl-34404781

RESUMO

Glycans are fundamental cellular building blocks, involved in many organismal functions. Advances in glycomics are elucidating the essential roles of glycans. Still, it remains challenging to properly analyze large glycomics datasets, since the abundance of each glycan is dependent on many other glycans that share many intermediate biosynthetic steps. Furthermore, the overlap of measured glycans can be low across samples. We address these challenges with GlyCompare, a glycomic data analysis approach that accounts for shared biosynthetic steps for all measured glycans to correct for sparsity and non-independence in glycomics, which enables direct comparison of different glycoprofiles and increases statistical power. Using GlyCompare, we study diverse N-glycan profiles from glycoengineered erythropoietin. We obtain biologically meaningful clustering of mutant cell glycoprofiles and identify knockout-specific effects of fucosyltransferase mutants on tetra-antennary structures. We further analyze human milk oligosaccharide profiles and find mother's fucosyltransferase-dependent secretor-status indirectly impact the sialylation. Finally, we apply our method on mucin-type O-glycans, gangliosides, and site-specific compositional glycosylation data to reveal tissues and disease-specific glycan presentations. Our substructure-oriented approach will enable researchers to take full advantage of the growing power and size of glycomics data.


Assuntos
Vias Biossintéticas , Glicômica , Polissacarídeos/biossíntese , Transporte Biológico , Vias Biossintéticas/genética , Análise por Conglomerados , Análise de Dados , Eritropoetina/metabolismo , Fucosiltransferases/genética , Gangliosídeos , Técnicas de Inativação de Genes , Glicosilação , Humanos , Mucinas
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