Tag: pubmed

Math Biosci Eng. 2022 Apr 2;19(6):5738-5753. doi: 10.3934/mbe.2022268.

ABSTRACT

With the development of science and technology, digital economy has penetrated into traditional manufacturing industry extensively and deeply, which has motivated the progress of the digital transformation for traditional manufacturing industry. Through comparative analysis of theoretical mechanism of synergetic development, this paper researches the order degree model and the synergy degree model based on the social shaping of technology theory to evaluate the synergetic degree of the digital transformation for China’s traditional manufacturing industry. An empirical study is presented based on the proposed models and the spatial analysis method by using the statistical data of Yangtze River Delta in China from 2014 to 2019. The results were consistent with the actual situation and indicated that the model fully reflect the dynamic interaction between systems, which is a sound basis for scientific judgment and effective decision-making when seeking to the digital transformation of traditional manufacturing industry.

PMID:35603376 | DOI:10.3934/mbe.2022268

Math Biosci Eng. 2022 Mar 28;19(6):5446-5481. doi: 10.3934/mbe.2022256.

ABSTRACT

We describe a preliminary effort to model the growth and progression of glioblastoma multiforme, an aggressive form of primary brain cancer, in patients undergoing treatment for recurrence of tumor following initial surgery and chemoradiation. Two reaction-diffusion models are used: the Fisher-Kolmogorov equation and a 2-population model, developed by the authors, that divides the tumor into actively proliferating and quiescent (or necrotic) cells. The models are simulated on 3-dimensional brain geometries derived from magnetic resonance imaging (MRI) scans provided by the Barrow Neurological Institute. The study consists of 17 clinical time intervals across 10 patients that have been followed in detail, each of whom shows significant progression of tumor over a period of 1 to 3 months on sequential follow up scans. A Taguchi sampling design is implemented to estimate the variability of the predicted tumors to using 144 different choices of model parameters. In 9 cases, model parameters can be identified such that the simulated tumor, using both models, contains at least 40 percent of the volume of the observed tumor. We discuss some potential improvements that can be made to the parameterizations of the models and their initialization.

PMID:35603364 | DOI:10.3934/mbe.2022256

Educ Inf Technol (Dordr). 2022 May 17:1-26. doi: 10.1007/s10639-022-11106-4. Online ahead of print.

ABSTRACT

Educational institutions abruptly implemented online higher education to cope with sanitary distance restrictions in 2020, causing an increment in student failure. This negative impact attracts the analyses of online higher education as a critical issue for educational systems. The early identification of students at risk is a strategy to cope with this issue by predicting their performance. Computational techniques are projected helpful in performing this task. However, the accurateness of predictions and the best model selection are goals in progress. This work objective is to describe two experiments using student grades of an online higher education program to build and apply three classifiers to predict student performance. In the literature, the three classifiers, a Probabilistic Neural Network, a Support Vector Machine, and a Discriminant Analysis, have proved efficient. I applied the leave-one-out cross-validation method, tested their performances by five criteria, and compared their results through statistical analysis. The analyses of the five performance criteria support the decision on which model applies given particular prediction goals. The results allow timely identification of students at risk of failure for early intervention and predict which students will succeed.

PMID:35603317 | PMC:PMC9110636 | DOI:10.1007/s10639-022-11106-4

Commun Med (Lond). 2022 Mar 2;2:21. doi: 10.1038/s43856-022-00081-z. eCollection 2022.

ABSTRACT

BACKGROUND: Survivors of childhood cancer can develop adverse health events later in life. Infrequent occurrences and scarcity of structured information result in analytical and statistical challenges. Alternative statistical approaches are required to investigate the basis of late effects in smaller data sets.

METHODS: Here we describe sex-specific health care use, mortality and causal associations between primary diagnosis, treatment and outcomes in a small cohort (n = 2315) of 5-year survivors of childhood cancer (n = 2129) in southern Sweden and a control group (n = 11,882; age-, sex- and region-matched from the general population). We developed a constraint-based method for causal inference based on Bayesian estimation of distributions, and used it to investigate health care use and causal associations between diagnoses, treatments and outcomes. Mortality was analyzed by the Kaplan-Meier method.

RESULTS: Our results confirm a significantly higher health care usage and premature mortality among childhood cancer survivors as compared to controls. The developed method for causal inference identifies 98 significant associations (p < 0.0001) where most are well known (n = 73; 74.5%). Hitherto undescribed associations are identified (n = 5; 5.1%). These were between use of alkylating agents and eye conditions, topoisomerase inhibitors and viral infections; pituitary surgery and intestinal infections; and cervical cancer and endometritis. We discuss study-related biases (n = 20; 20.4%) and limitations.

CONCLUSIONS: The findings contribute to a broader understanding of the consequences of cancer treatment. The study shows relevance for small data sets and causal inference, and presents the method as a complement to traditional statistical approaches.

PMID:35603279 | PMC:PMC9053221 | DOI:10.1038/s43856-022-00081-z

Commun Med (Lond). 2022 Mar 1;2:19. doi: 10.1038/s43856-022-00080-0. eCollection 2022.

ABSTRACT

BACKGROUND: The aim of the nationwide prospective seroconversion (PROSECO) study was to investigate the dynamics of anti-SARS-CoV-2 IgG antibodies in the Czech population. Here we report on baseline prevalence from that study.

METHODS: The study included the first 30,054 persons who provided a blood sample between October 2020 and March 2021. Seroprevalence was compared between calendar periods, previous RT-PCR results and other factors.

RESULTS: The data show a large increase in seropositivity over time, from 28% in October/November 2020 to 43% in December 2020/January 2021 to 51% in February/March 2021. These trends were consistent with government data on cumulative viral antigenic prevalence in the population captured by PCR testing – although the seroprevalence rates established in this study were considerably higher. There were only minor differences in seropositivity between sexes, age groups and BMI categories, and results were similar between test providing laboratories. Seropositivity was substantially higher among persons with history of symptoms (76% vs. 34%). At least one third of all seropositive participants had no history of symptoms, and 28% of participants with antibodies against SARS-CoV-2 never underwent PCR testing.

CONCLUSIONS: Our data confirm the rapidly increasing prevalence in the Czech population during the rising pandemic wave prior to the beginning of vaccination. The difference between our results on seroprevalence and PCR testing suggests that antibody response provides a better marker of past infection than the routine testing program.

PMID:35603283 | PMC:PMC9053194 | DOI:10.1038/s43856-022-00080-0

Commun Med (Lond). 2022 May 19;2:54. doi: 10.1038/s43856-022-00106-7. eCollection 2022.

ABSTRACT

BACKGROUND: The infection fatality ratio (IFR) is a key statistic for estimating the burden of coronavirus disease 2019 (COVID-19) and has been continuously debated throughout the COVID-19 pandemic. The age-specific IFR can be quantified using antibody surveys to estimate total infections, but requires consideration of delay-distributions from time from infection to seroconversion, time to death, and time to seroreversion (i.e. antibody waning) alongside serologic test sensitivity and specificity. Previous IFR estimates have not fully propagated uncertainty or accounted for these potential biases, particularly seroreversion.

METHODS: We built a Bayesian statistical model that incorporates these factors and applied this model to simulated data and 10 serologic studies from different countries.

RESULTS: We demonstrate that seroreversion becomes a crucial factor as time accrues but is less important during first-wave, short-term dynamics. We additionally show that disaggregating surveys by regions with higher versus lower disease burden can inform serologic test specificity estimates. The overall IFR in each setting was estimated at 0.49-2.53%.

CONCLUSION: We developed a robust statistical framework to account for full uncertainties in the parameters determining IFR. We provide code for others to apply these methods to further datasets and future epidemics.

PMID:35603270 | PMC:PMC9120146 | DOI:10.1038/s43856-022-00106-7

Lett Spat Resour Sci. 2022 May 17:1-17. doi: 10.1007/s12076-022-00302-y. Online ahead of print.

ABSTRACT

This paper offers an analysis of the supply of Airbnb accommodation in Rome, one of the main tourist destinations in the world, the third-largest city in Europe, by the number of Airbnb listings. The aim is to focus on the recent spatial trend of Airbnb listings, including the period of the COVID-19 pandemic, and highlight the main housing and socioeconomic characteristics of the neighbourhoods associated with a strong presence of Airbnb listings. The study is developed with quantitative methods and spatial regression (spatial lag and spatial error using OLS as a benchmark), based on data collected from the Inside Airbnb and Tomslee websites. In the period 2014-2019, the listing trend in Rome has been increasing in absolute numbers. After the start of the pandemic, the trend became negative, and the decline of Airbnb offerings is more substantial for shared accommodation. Airbnb supply is related to the distance from the city centre, the average income of the area, empty apartments, singles and the share of foreign residents coming from high-income countries. A signal of spatial diffusion of Airbnb listings emerges in the coastal area, even if they are increasingly concentrated in the historic centre, where there is a monoculture of short-term renting.

PMID:35603260 | PMC:PMC9112640 | DOI:10.1007/s12076-022-00302-y

J Prev Med Hyg. 2022 Jan 31;62(4):E943-E949. doi: 10.15167/2421-4248/jpmh2021.62.4.1801. eCollection 2021 Dec.

ABSTRACT

INTRODUCTION: Surveillance of health care-associated infections (HAIs) is an essential part of an efficient healthcare system. This study is an update on incidence and mortality rates of HAIs in Iran in 2018.

METHODS: Almost all hospitals across the country (940 hospitals) entered the data of HAIs and denominators to the Iranian Nosocomial Infections Surveillance (INIS) software. Statistics were derived from INIS.

RESULTS: From 9,607,213 hospitalized patients, 127,953 suffered from HAI, 15.65% of whom died. The incidence rate of HAI was calculated as 4.2 per 1000 patient-days. Considering relative frequencies among HAIs, Pneumonia (29.1%) and UTIs (25.6%) were the most common types of infection. Ventilator-associated pneumonia (VAP) was the most frequent device-associated infection (DAI) 25.66 per 1000 ventilator-days, and had the highest mortality rate (43.08%). Incidence density of other DAIs was 5.43 for catheter-associated UTI and 2.86 for catheter-associated BSI per 1000 device-days. Medical ICUs had the highest incidence and percentage of deaths (15.35% and 37.63%, respectively). The most causative organisms were Escherichia coli, Acinetobacter baumannii, and Klebsiella pneumonia. The rate of methicillin-resistance Staphylococcus aureus (MRSA), vancomycin-resistant Enterococcus (VRE), and Klebsiella pneumoniae carbapenemase (KPC)-producing bacteria was about 49%, 57%, and 58% respectively.

CONCLUSION: This study provided an overview of HAIs in Iran and indicated that HAIs required special attention both in detection/reporting and in infection control measures. Future studies could be done on adherence rate of DAIs’ preventive bundles, interventions via multimodal strategies, evaluating the effect of training, and effect of antibiotic stewardship programs.

PMID:35603257 | PMC:PMC9104666 | DOI:10.15167/2421-4248/jpmh2021.62.4.1801

J Prev Med Hyg. 2022 Jan 31;62(4):E904-E908. doi: 10.15167/2421-4248/jpmh2021.62.4.2176. eCollection 2021 Dec.

ABSTRACT

BACKGROUND: The adverse effects of coronavirus infection on pregnant women and their infants are not apparent. The best strategies to deal with this disease is avoiding the infection and preventing its transmission.

PURPOSE: the present study aimed to investigate the relationship between demographic factors and levels of self-care against coronavirus in pregnant women referred to maternity wards of Kerman, southeast Iran.

METHOD: The present descriptive study was conducted on 200 pregnant women who referred to maternity wards in Kerman in 2020 and met the inclusion criteria. The required information was collected using demographic and obstetric questionnaires and a self-care checklist.

FINDINGS: The mean age of the participants was 28.89 ± 7.07. Iranian and Afghan citizens comprised 82 and 18% of the participants, respectively. The highest level of self-care measures against coronavirus in pregnant women was attributed to the use of face masks (74%), and the lowest was warning the personnel to wear masks (28%). There was a statistically significant relationship between the nationality of the participants and warning the personnel to wear facemasks (r = 0.183; p = 0.02), having a sick spouse (r=0.149;P = 0.039), and having a sick child (r = 0.191; p = 0.043), and between the husbands’ job and the patients’ demand for a private room (r = 0.173; p = 0.013). There was an inverse relationship between mothers’ age and warning the personnel about paying attention to their hygiene (r = -0.145; p = 0.04).

CONCLUSIONS: The results indicated that most pregnant women in the present study were active in self-care against coronavirus. Using face masks was more widely followed than other self-care measures; moreover, there was a relationship between personal characteristics and self-care levels.

PMID:35603249 | PMC:PMC9104661 | DOI:10.15167/2421-4248/jpmh2021.62.4.2176

J Prev Med Hyg. 2022 Jan 31;62(4):E909-E917. doi: 10.15167/2421-4248/jpmh2021.62.4.2287. eCollection 2021 Dec.

ABSTRACT

INTRODUCTION: Nutrition plays an integral part in growth and development of a child. Age-appropriate feeding is known to improve the child’s well-being and reduce the risk of specific diseases. The present study aimed to assess the awareness of parents regarding breastfeeding and complementary feeding practices.

METHODOLOGY: This health-based prospective observational study was conducted in a tertiary care hospital enrolling 95 parents with children in the age group 1-2 years. The data was analyzed using SPSS version 26 and Microsoft excel.

RESULTS: In the present study, the prevalence of exclusive breastfeeding was 73.68%. Eighty-six (90.53%) parents initiated complementary feeds at 6 months. However, only 45.26% of children were consuming adequate quantity of complementary foods. The association of child’s calorie consumption with maternal age and occupation was found to be statistically significant.

CONCLUSION: Adequate nutrition during childhood and infancy is a key factor influencing growth and development. In the present study, the overall breastfeeding and complimentary feeding practices were satisfactory. However, the quantity of complementary feeding was inadequate. Counselling the mothers on appropriate breastfeeding and complementary feeding practices during antenatal and postnatal visits may have a positive impact on infant feeding practices.

PMID:35603241 | PMC:PMC9104673 | DOI:10.15167/2421-4248/jpmh2021.62.4.2287