bluuebunny/crossref_metadata_2025_split huggingface dataset:
Prevalence, Trends, and Associated Factors of Hypertensive Crisis in Peruvian Adults, 2014-2019
Authors: Ocon Victor Calderon , Peredo Fiorella Cueva , Bernabé-Ortiz Antonio 
Published: May 2023

Abstract

Objectives:To determine the prevalence and trend over time of the hypertensive crisis, as well as sociodemographic and behavioral factors associated with it in Peruvian adults.Materials and methods:Cross-sectional analysis of the Demographic and Family Health Survey (ENDES) from 2014 to 2019. The dependent variable was hypertensive status, with three categories: normotensive, hypertensive, and those with hypertensive crisis (CH). HC was defined as systolic blood pressure ≥180 mmHg or diastolic blood pressure ≥110 mmHg. Associated variables of interest were evaluated using multinomial logistic regression, and the trend of HC was assessed using the Cochrane-Armitage test.Results:A total of 166,741 participants were analyzed, mean age 43.5 (± 16.4) years, 54.4% were women, and 75.5% came from urban areas. The prevalence of hypertensive crisis was 1.3% (95% CI: 1.2% - 1.4%), and this estimate decreased from 1.6% in 2014 to 1.1% in 2019 (p< 0.001). Cases of hypertensive crises were more frequent in older individuals, especially those aged 60+ (OR = 80.6), males (OR = 1.43), urban residents (OR = 1.25), overweight (OR 1.65) or obese (OR = 2.41) and having diabetes (OR = 2.22).Conclusions:The presence of hypertensive crisis was relatively common in the general Peruvian population. There is a need to improve the strategies for diagnosis, treatment, and control of hypertension in our context to reduce the cases of hypertensive crisis.
Using Deep Learning Models to Predict the Risk of Peripheral Neuropathy on Diabetic Patients
Authors: Lee Tsair-Fwu , Chiu Chi-Min , Tseng Chin-Dar , Huang Hong-Zhi , Lin Chih-Hsueh , Lin Guang-Zhi , Lee Shen-Hao , Yang Jack , Lin Kun-Der 
Published: May 2023

Abstract
To establish a suitable deep learning model in order to predict the risk of diabetic Peripheral Neuropathy (DPN) by using fundus photography images of type II diabetic patients with artificial intelligence (AI) approach. From the year 2013 to 2017, by using a diabetes care database established by the Department of Endocrinology and Metabolism of Kaohsiung Datong Hospital (KMTTH) and the Affiliated Hospital of Kaohsiung Medical University (KMUH), a corresponding retrospective study of fundus photographic images of patients with type II diabetes mellitus was performed. Patients with Type II diabetes who have undergone clinical routine treatment and have routine ophthalmoscopy were analyzed and classified according to the results of the Nerve Conduction Velocity (NCV) method. Soon after the patient's personal information was removed, the image is preprocessed by adaptive histogram equalization (CLAHE) to limit the contrast variation. These preprocessed images were then divided into training, validation, and test sets. Another two sets of Rotated image data were also incorporated for enhancements to build prediction models through four deep learning architectures: InceptionNet, VGGNet, ResNet, and ConvMixer DPN model, respectively. In this study, a classification model for predicting the severity of DPN was successfully established through four deep learning architectures. The accuracies of the four DPN prediction models established in this study were 0.94, 0.90, 0.97, and 0.96; AUC values have achieved at 0.92, 0.93, 0.95, and 0.96; specificity analyses were 1.00, 0.92, 1.00, and 0.98; The combined sensitivity values of mild and moderate to severe DPN reached 0.84, 0.90, 0.90, and 0.92, respectively. An AI-assisted diagnostic model was successfully established to predict the severity of diabetic peripheral neuropathy (DPN), which could determine whether the patient has DPN from the retinal fundus images obtained after ophthalmoscopy and with its associated severity; therefore, it is an efficient, non-invasive method of DPN detection.
Global, regional and national burden of human cystic echinococcosis from 1990 to 2019: a systematic analysis for the Global Burden of Disease Study 2019
Authors: Miao Li-yuan , Tian Tian , Wang Wei , Zhou Xiao-Nong 
Published: May 2023

Abstract
Background: Cystic echinococcosis (CE) is a neglected tropical parasitic disease that poses huge disease, social and economic burdens in the world. Although great strides have been achieved, multiple challenges remain to achieve the ambitious goal targeting CE set in the WHO roadmap for neglected tropical diseases 2021–2030. Estimates of the disease burden due to CE facilitate the progress towards eliminations; however, there is little knowledge on global morbidity, mortality and disability-adjusted life years (DALYs) of CE until now. This study aimed to present the most up-to-date data about the global, regional and national disease burden due to CE from 1990 to 2019 and to project trends in the next 10 years.
Methods: We measured the global, regional and national morbidity, mortality and DALYs of CE from 1990 to 2019 based on the Global Burden of Disease Study 2019 (GBD 2019) data, and we examined the correlation between socioeconomic development levels and the disease burden of CE. In addition, the disease burden due to CE was projected using Bayesian age-period-cohort analysis with integrated nested Laplace approximations from 2020 to 2030.
Results: The global number of CE cases increased from 134,980 [95% uncertainty interval (UI): (93,141 to 195,144)] in 1990 to 207,368 [95% UI: (6,347,183 to 8,769,520)] in 2019 [estimated annual percentage change (EAPC) = 0.54], and the age-standardized incidence rate (ASIR) of CE reduced from 2.65/105 [95% UI: (1.87/105 to 3.7/105)] in 1990 to 2.6/105 [95% UI: (1.72/105 to 3.79/105)] in 2019 (EAPC = ‒0.18). The number of deaths, DALYs, age-standardized mortality rate (ASMR) and age-standardized DALYs rate due to CE all appeared a tendency towards a decline from 1990 to 2019. A higher disease burden of CE was measured in women than in men in 2019. There was a significant difference in ASMR of CE in regions specified by socio-demographic index (SDI) and lower burdens of CE were estimated in high SDI regions. The global ASIR of CE was projected to appear a tendency towards a decline from 2020 to 2030; however, the ASMR and age-standardized DALY rate were projected to rise.
Conclusions: Our data may provide data-based evidence for public health officials and policy-makers to formulate and implement cost-benefit interventions to tackle the disease burden attributable to CE. More health resources are recommended to be allocated to low SDI regions, women and the elderly at ages of 55 to 65 years to reduce the disease burden of CE.
A quantitative study to predict the risk of recurrence after radiotherapy for cervical cancer based on multi-sequence MRI imagingomics
Authors: Dai Zhenhuo , Lin Kaiwu , Lin Yuanrong , Chen Ya , Zheng Jiwei , Lin Li 
Published: May 2023

Abstract
Background With the increasing clinical application of radiomics,the ability of magnetic resonance imaging omics to diagnose and predict the prognosis of diseases has attracted extensive attention in the scientific research community, and its application in the diagnosis, staging and treatment efficacy evaluation of cervical cancer has been gradually got attention..Methods All 52 patients in the radiotherapy group were cervical cancer patients and were diagnosed and treated with radiotherapy at our hospital from July 2019 to December 2021, while the healthy control group was selected from 41 healthy patients. The MRI performance of the two groups and the MRI performance of the patients in the radiotherapy group before and after treatment were observed separately. In addition, their ADC values were compared and the changes in ADC values before and after treatment were compared in patients with different prognosis in the radiotherapy group, compared the texture analysis parameters of patients with and without postoperative recurrence in radiotherapy group, and analyzed the predictive efficacy of MRI texture analysis parameters on the recurrence of cervical cancer patients after radiotherapy by ROC.Results The inorganic mass and DWI values of patients with cervical cancer increased with their grading and ADC decreased with them; Comparing the ADC values before and after radiotherapy, it was found that the values in the radiotherapy group were obviously lower than those in the healthy group (P < 0.05); a total of 16 patients (30.77%) received radiotherapy, they had recurrence within 6 months after radiotherapy and 36 patients (69.23%) had no recurrence in the radiotherapy group; according to the recurrence of patients after radiotherapy. The ROC curve analysis showed that the area under the curve of entropy value was the largest, which confirmed its diagnostic effectiveness.Conclusion Multi-series MRI imaging omics is of high clinical value in predicting the risk of recurrence after radiotherapy for cervical cancer patients.
Peatland porewater chemistry reveals field redox ranges for specific decomposition processes
Authors: Boonman Jim , Harpenslager Sarah Faye , Dijk Gijs van , Hefting Mariet M. , Smolders Alfons J.P. , de Riet Bas van , Velde Ype van der 
Published: May 2023

Abstract
Peat decomposition, driven by soil metabolic processes, was responsible for 2% of the anthropogenic greenhouse gas emissions in 2019. The peat soil redox potential (Eh) and pH reflect the chemical state of the soil and the (biogeo)chemical processes that occur and are therefore linked to the rate of peat decomposition and greenhouse gas production. We related porewater chemistry (pH, NO3-, SO42-, Mn(II), Fe(II), S2- and CH4, >2000 samples) to continuous Eh measurements (2020-2022) from five agricultural drained peatland sites in the Netherlands that consist of measuring plots with and without subsoil irrigation and drainage (SSI) in order to establish Eh ranges that identify specific metabolic processes. We found that methanogenesis, reduction of SO42-, Fe(III), NO3-/ Mn(IV) and O2 occurred at Eh (at pH 5.5) of < -49 mV, -49 – 104 mV, 104- 364 mV, 364- 700 mV and >700mV respectively. Eh over depth and time closely followed temporal and spatial fluctuations in groundwater level and porewater chemistry, and revealed the extent of O2 intrusion and the occurrence of methanogenesis. Higher and more constant groundwater levels year-round tended to deplete porewater Fe(II) and SO42-, which led to more reducing Eh and higher porewater CH4 concentrations. These mechanistic insights help to optimize GHG mitigation strategies for drained peat regions.
Manoeuvre a Cross-Spectral Algorithm and Machine Learning Approach to Categorize Seizures
Authors: Ojo Stephen , Allabun Sarah , Shukla Prashant Kumar , Alqahtani Mohammed S. , Pareek Piyush Kumar , Abbas Mohamed , Wechtaisong Chitapong , Othman Manal , Soufiene Ben Othman 
Published: May 2023

Abstract

EEG signals are recordings of electrical activity in the brain, and they can be used to detect epileptic seizures. Cross-spectral analysis involves analyzing the spectral coherence between different frequency bands in EEG signals. Cross-spectral seizure detection is a technique used to detect seizures in electroencephalography (EEG) signals by analyzing the frequency content of the signal in different frequency bands. Spectral coherence is a measure of how correlated two signals are in the frequency domain, and it can be used to identify patterns in EEG signals that are characteristic of seizures. Even if the ECG, which provides a direct measure of heart rate, were polluted by noise or missing altogether, the heart rate computed from such signals would be erroneous. This necessitates the use of an accurate heart rate estimate, which is especially important when the ECG is noisy or missing. To put it another way, fusion combines cardiovascular data with no cardiovascular (NC) signals, which are not connected to cardiac activity but include signs of heartbeats. According to the results of our evaluation of standard datasets, they determined that the SSF-TKE approach is particularly successful at identifying R-peak artefacts in non-cardiovascular signals that ECG anomalies have contaminated. When tested on standard datasets, the beat SQI-based voting fusion technique demonstrated a high degree of accuracy in predicting heart rate from a fusion of multimodal information. Compared to the single signal technique, the fusion methodology out per-forms it when determining heart rate precision. This strategy was evaluated using ECG and ABP signals from a synthetic noise dataset, which was created by adding various forms of calibrated noise to clean signals and then testing the outcomes of the technique on those signals. As a result of our paper, we noticed that merging cardiovascular and no cardiovascular inputs increased the accuracy of physiological parameter assessment.
Challenges and opportunities: A case study from a European city shows the influence of biological work on bioaerosol formation from indoor biological wastewater treatment laboratory
Authors: Upadhyay Ruchi , Przystaś Wioletta , Gautam Sneha 
Published: May 2023

Abstract
Bioaerosol emitted in university biological laboratories may exert adversely effects on employees and students. The occupational health and safety have been given much importance. This study aimed to monitor the risk of bioaerosol formation inside a biological wastewater treatment laboratory where other biological activities were performed along with wastewater treatment using the biological method. A single-stage impactor performed the air sampling to study concentration of bacterial and fungal bioaerosols and the diversity of air microbiota also been assessed. In early winter, 2018 MPN/m3 bacterial aerosol concentrations were observed which correlated with an increased number of occupants and their experimental activity. In contrast, the fungal concentration was found below the upper permissible limits in indoor environments, and it was influenced by seasonal change and humidity and were not influenced by number of occupants. The more significant number of morphological types of bacteria and fungi indicated diversity of air microbial community. This result suggests a moderate risk of bacterial bioaerosol to occupants working in wastewater treatment laboratory.
Angioarchitectural features of arteriovenous fistulas of cranio-cervical junction predicting the risk of clinical presentation and unfavorable outcome: insight from a multicenter cohort and pooled analysis.
Authors: Li Zongze , Zhang Hongfei , Zhao Yang , Liu Peixi , Shi Yuan , Liu Mingjian , Quan Kai , Tian Yanlong , Li Peiliang , Zhao Yuanli , Zhu Wei 
Published: May 2023

Abstract

Objective Arteriovenous fistulas (AVFs) at the cranio-cervical junction (CCJ) are uncommon conditions with complex angioarchitecture. The objective of this study was to identify the angioarchitectural features of CCJ-AVF to predict the risk of clinical presentation.Methods The study population was comprised of 68 consecutive patients with CCJ-AVF at two neurosurgical centers between 2014 and 2022, and a systematic pooled analysis of 68 cases with detailed clinical data obtained via PubMed database from 1990 to 2022. Clinical and imaging data were collected to analyze factors for subarachnoid hemorrhage (SAH), myelopathy, and modified Rankin scale (mRS) at presentation.Results The mean age of the patients was 54.5 ± 13.1 years, and 76.5% of patients were male. The most common feeding arteries was V3-medial branches(33.1%), and drainage was frequently through the anterior or posterior spinal vein/perimedullary vein (72.8%). The most common presentation was SAH(49.3%), and an associated aneurysm (adjusted OR, 7.44; 95%CI, 2.89–19.15) was a risk factor for SAH. Anterior or posterior spinal vein/perimedullary vein (adjusted OR, 2.78; 95%CI, 1.00-7.72) and male gender (adjusted OR, 3.76; 95%CI, 1.23–11.53) were associated with higher risk for myelopathy. An mRS score ≤ 2 at presentation (adjusted OR, 0.25; 95%CI, 0.09–0.71) and an associated aneurysm (adjusted OR, 0.16; 95%CI, 0.06–0.43) were protective factors. Presentation with myelopathy (adjusted OR per score, 4.73; 95%CI, 1.31–17.12) was an independent risk factors for unfavorable neurological status in untreated CCJ-AVF.Conclusion This study identifies risk factors associated with SAH, myelopathy, and unfavorable neurological status at presentation in patients with CCJ-AVF. These findings may help guide management and treatment decisions for these complex vascular malformations.
AHUS mistaken for TTP associated with COVID-19: a case report
Authors: Wu An , Wang Jiaping , Shi Cong , Yan Xiao , Ouyang Guifang , Sheng Lixia 
Published: May 2023

Abstract
Thrombotic thrombocytopenic purpura (TTP) and atypical hemolytic uremic syndrome (aHUS) are both thrombotic microangiopathies that share several clinical traits including microangiopathic hemolytic anemia, thrombocytopenia, and organic damage. There is inherent opportunity for misdiagnosis. As thrombocytopenia and thrombus are strongly related to COVID-19, it may be more difficult to tell an aHUS from a TTP when COVID-19 is present. Thus, we describe a patient presenting with severe COVID-19 who was misdiagnosed with TTP but in the end corrected to aHUS. We suggest that perform detection to ADAMTS-13 activity and complement gene mutation as soon as possible is necessary.
Toxoplasma gondii infection in pig intended for human consumption in Brazil: seroprevalence, risk factors and influence of Biosecurity Measures
Authors: Scofano Agostinho Sergio , Arruda Igor Falco , Teixeira Jessica Nogueira , Cunha Nathalie Costa , Nascimento Elmiro Rosendo , Amendoeira Maria Regina Reis , Millar Patrícia Riddell 
Published: May 2023

Abstract

Background: Toxoplasmosis, caused by Toxoplasma gondii, is a zoonotic disease highly prevalent in Brazil and poses considerable risk to public health. T. gondii is an obligate intracellular protozoan that is capable of infecting mammals and birds. In humans, the infection occurs mainly by the ingestion of raw or undercooked meat containing tissue cysts or other food items or water contaminated with sporulated oocysts, or by congenital transmission. Despite the prevalence of T. gondii in Brazil and its proven circulation among humans, animals, and the environment, there have been few studies on toxoplasmosis and its epidemiology.
Methods: Blood samples were collected from 416 pigs from 55 producer farms in 27 municipalities in the state of Espírito Santo, Brazil. An indirect immunofluorescent assay (IFA) was performed to estimate the seroprevalence of T. gondii and identify the associated risk factors.
Results: The T. gondii antibody prevalence rate in commercial swine herds from Espírito Santo was 15.4% (64/416), and the most frequent antibody titer was 1:64 (61/64) followed by 1:256 (3/64). Seropositivity for T. gondii was related to the presence of cats, existence of internal insulation fences on the farm, use of compost chambers on the farm, water sources, and the age of pigs.
Conclusions: To the best of our knowledge, this is the first study to report anti- T. gondii antibodies in the serum of pigs in the state of Espirito Santo, Brazil. This finding is important to public health because seropositive pigs can harbor tissue cysts in their meat, thereby representing a zoonotic risk for consumers of raw or undercooked porcine meat or its products.
Three Gorges Dam: Differential determinants and spatial-temporal effects of the change of snail density
Authors: Gong Yanfeng , Tong Yixin , Jiang Honglin , Xu Ning , Yin Jiangfan , Wang Jiamin , Huang Junhui , Chen Yue , Jiang Qingwu , Li Shizhu , Zhou Yibiao 
Published: May 2023

Abstract
BACKGROUND The abundance of Oncomelania hupensis snail can promote the transmission of schistosomiasis japonica. Snail distribution varies spatially and temporally in different geographical regions. Hence, we investigated differential drivers of snail density between the downstream and upstream areas of Three Gorges Dam (TGD), and spatial-temporal changes in snail abundance.METHODS We deployed the snail survey at 200 sites over 5 years to monitor a dynamic change in snail abundance within the Yangtze River basin. Corresponding variables that might affect snail abundance, such as Meteorology, vegetation, terrain, and economy, were collected from multiple data sources. We conducted the Bayesian spatial-temporal modeling framework to investigate the differential determinants and spatial-temporal effects of the change of snail density.RESULTS Obvious volatility for snail density was detected in the downstream area of TGD, whilst a small increment in the upstream area. For the downstream area of TGD, Snail density was positively associated with the average minimum temperature in January of the same year, annual normalized difference vegetation index of the previous year (NDVI), the 2nd quartile of average annual relative humidity of the previous year (RH), the 3rd quartile of RH, the 4th quartile of RH. Snail density was negatively associated with the average maximum temperature in July of the previous year, and annual night-time light of the previous year. An approximately inverted “U” curve of relative risk was detected among sites with a greater average annual ground surface temperature of the previous year. For the upstream area, snail density was positively associated with NDVI, the 2nd quartile of total precipitation of the previous year (Pre), the 3rd quartile of Pre, and the 4th quartile of Pre. Snail density was negatively associated with Slope.CONCLUSIONS Collectively, our study demonstrated a rebound in snail density between 2015 and 2019. In particular, temperature, humidity, vegetation, and human activity were the main drivers affecting the snail abundance in the downstream area of TGD, while precipitation, slope, and vegetation were the main drivers affecting the upstream snail abundance. This evidence can assist the authorities to execute more precise strategies for snail investigation and control.