bluuebunny/crossref_metadata_2025 huggingface dataset:
Mechanisms of Cognitive Impairment in Depression. May Probiotics Help?
Authors: Dobielska Maria , Bartosik Natalia Karina , Zyzik Kamil A. , Kowalczyk Edward , Karbownik Michał Seweryn
Published: June 2022

Depression is the major cause of disability globally. Apart from lowered mood and accompanying symptoms, it leads to cognitive impairment that altogether predicts disadvantaged social functioning. Reduced cognitive function in depression appears a bit neglected in the field of clinical and molecular psychiatry, while it is estimated to occur in two-thirds of depressed patients and persist in at least one third of remitted patients. This problem, therefore, requires elucidation at the biomolecular and system levels and calls for improvement in therapeutic approach. In this review study, we address the above-mentioned issues by discussing putative mechanisms of cognitive decline in depression: (1) increased oxidative stress and (2) inflammation, (3) disturbed hypothalamus-pituitary-adrenals axis, and (4) reduced monoamines functionality. Moreover, we acknowledge additional underpinnings of cognitive impairment in depressed elderly: (5) vascular-originated brain ischemia and (6) amyloid-beta plaque accumulation. Additionally, by reviewing molecular, pre-clinical and clinical evidence, we propose gut microbiota-targeted strategies as potential adjuvant therapeutics. The study provides a consolidated source of knowledge regarding mechanisms of cognitive impairment in depression and may path the way toward improved treatment options.
A Joint Regional Analysis of Resistance Combinations in Escherichia coli in Humans and Different Food-Producing Animal Populations in Germany Between 2014 and 2017
Authors: Suwono Beneditta , Eckmanns Tim , Kaspar Heike , Tenhagen Bernd-Alois
Published: June 2022

A joint comparative regional analysis of different resistance combinations across human and veterinary medicine has not been previously conducted in Germany. This study analyses 16 resistance combinations from four antibiotics in E. coli from different human and food-producing animal populations in three German regions: East, North West and South West. The E. coli data were collected from the three national surveillance and monitoring systems for antimicrobial resistance (AMR) bacteria in humans (ARS), food-safety (Zoonosis Monitoring) and animal pathogens (GERM-Vet) from January 2014 to December 2017. Analyses were performed using cluster analysis (hierarchical clustering, average linkage) in R. We included data from 537,215 E. coli isolates from human clinical isolates, from clinical as well as non-clinical isolates from food-producing animals and from food. The majority of the data originated from the North West region. There were two main clusters built on 54 different human and animal populations. We observed close similarities of resistance combinations in human isolates from the different regions within the same human populations from outpatient cares, general wards and ICUs. These resistance combinations clustered separately from non-clinical isolates from broilers, turkeys, cattle and pigs; except for some of clinical isolates from these populations which clustered closely to isolates from human populations. Frequently, the resistance combinations in E. coli isolates from farms clustered closely to the resistance combinations in isolates from slaughterhouses from broilers and turkeys over all regions. However, the resistance combinations in E. coli isolates from retail meat populations tended to cluster separately within their respective populations in between all regions.
Perception of Global Participants of ITEC Nations on Country's Preparedness and Response to COVID-19 Pandemic
Authors: Upadhyay Kritika , Goel Sonu , Soundappan Kathirvel
Published: June 2022

Background

The Coronavirus disease 2019 (COVID-19) pandemic has exposed the public health preparedness and response system across the world. The current study was conducted to gauge the perception of public health professionals of Indian Technical and Economic Cooperation (ITEC) countries regarding the preparedness and responses of their countries in mitigating the COVID-19 pandemic.

Methodology

Three capacity-building programs, namely “Managing COVID-19 Pandemic–Experience and Best practices of India” were conducted by PGIMER, Chandigarh, for public health professionals from ITEC countries from April to May 2021 in which 97 participants from 13 countries have participated. The tools used in the study were adapted from WHO's COVID-19 Strategic Preparedness and Response (SPRP), Monitoring and Evaluation Framework, interim guidelines for Critical preparedness, readiness and response actions for COVID-19, and a strategic framework for emergency preparedness, and finalized using Delphi technique. The overall preparedness of managing COVID-19 was rated using five-point Likert scale, whereas the overall score for the country in combating the COVID-19 pandemic was assessed using 10 point scale.

Results

We found that the perception of public health professionals to government response regarding COVID-19 for fostering improvement on COVID-19 situation was “moderate” with respect to transmission and surveillance mechanism, uniform reporting mechanism, and availability of adequate personal protective equipment (PPE) for health workers. However, the participants rated government response as “poor” in the availability of multisectoral national operational plan, human resource capacity, availability of trained rapid response team (RRT), preparedness in prevention and clinical management, training of healthcare workers, communication and community engagement strategies, facilities to test samples of patients, and transparent governance and administration.

Conclusion

A poor level of preparedness of countries in diverse domains of managing the COVID-19 pandemic was observed. As the global threat of COVID-19 is still looming, great efforts on building a robust preparedness and response system for COVID-19 and similar pandemics are urgently required.
Detection of Dengue Virus From Aedes aegypti (Diptera, Culicidae) in Field-Caught Samples From Makkah Al-Mokarramah, Kingdom of Saudi Arabia, Using RT-PCR
Authors: Ali Elfadol Obeid Mohamed , Babalghith Ahmed Omer , Bahathig Adil Omer Saeed , Dafalla Ommer Mohamedelhassan , Al-Maghamsi Ibrahim Wasal , Mustafa Nasr Eldien Ali Gaafar , AL-Zahrani Abdullah Ahmad Abdullah , Al-Mahmoudi Sameer Mohammed Yousef , Abdel-Latif Mohamed E.
Published: June 2022

Dengue fever (DF) is endemic to Makkah and Jeddah, the Kingdom of Saudi Arabia (KSA). However, until recently, the circulation of dengue virus (DENV) in Aedes mosquitoes in these areas was unknown. Serological surveillance of DENV in Ae aegypti is a powerful tool for early detection of dengue outbreaks and essential for developing effective control strategies. Therefore, this research aimed to examine a sample of adult Ae aegypti mosquitoes from Makkah, KSA, to detect DENV. In total, 1295 Ae aegypti mosquitoes were collected from the field from target areas of Makkah with a high incidence and prevalence of DF. The samples were divided into 259 coded pools (five mosquitoes in each) and preserved in 1.5 mL plastic tubes. The tubes were labeled, capped, and stored at−86°C until use. RT-PCR was used to detect DENV in the samples. All positive pools were confirmed by RT-PCR. The RT-PCR products were analyzed by gel electrophoresis (1.5% agarose in Tris-acetate EDTA buffer), stained with ethidium bromide, and visualized. DENV was isolated from six female Ae Aegypti collected from six pools (out of 259 pools). No other viruses were detected. Only five of the nine target localities had positive pools. Samples from the remaining four localities yielded negative results. Four DENV-positive mosquitoes were collected at the aquatic stages, and two were collected at the adult stage. These results show the circulation of DENV in adult mosquitoes and offspring, indicating vertical transmission of DENV. In conclusion, this study found that, in Makkah, DENV is circulating in dengue vectors with a high significance rate, suggesting the possibility of a dengue outbreak in the future; therefore, a sensitive surveillance system is vital to predict the outbreak and for early intervention and control.
Comparative Analysis of the Status and Influencing Factors of Immunization Among Children Between Registered and Floating Population
Authors: Xiong Yan , Xue Yaqing , Jiao Guojin , Xie Jun , Cheng Jingmin
Published: June 2022

Background

A vaccine is an effective tool to reduce the gap between the rich and the poor and improve health equity, through which a number of serious childhood diseases can be successfully prevented or eradicated. This study is aimed to compare the current situation of vaccination and related factors among children in China's registered residents and floating population, to provide a reference for achieving the 100% vaccination rate in China.

Methods

The data used for this study are from the 2017 National Migrants Dynamic Monitoring Special Survey data. A self-designed questionnaire was used to collect information, such as socio-demographics, vaccination status of children, and so on, on the registered population and floating population. Descriptive statistics and a chi-square independence test were used to describe the information and to compare the vaccination status of children under different sociodemographic characteristics. Binary logistic regression was employed to analyze influencing factors associated with vaccination of children.

Results

The findings showed that 94.39% of children in registered residence were completely vaccinated, which was significantly higher than that of the floating children (91.68%,p< 0.001). The region, parents' education level, and marital status were found to be significant risk factors for complete vaccination of children regardless of the registered or floating population. In addition, ethnicity and length of time to the nearest medical institution were unique risk factors for complete vaccination of children in registered residence. And, health record was an independent influencing factor for vaccination of children of floating population.

Conclusion

Compared with registered population, floating population was at a disadvantage in using basic public health services, especially in children's vaccination. To achieve 100% vaccination for children, particular interventions should be taken for different populations.
Three Exposure Metrics for Fine Particulate Matter Associated With Outpatient Visits for Acute Lower Respiratory Infection Among Children in Guangzhou, China
Authors: Xiao Danxia , Guo Wenchun , Xu Debo , Chen Jiamin , Liang Zhenyu , Zhang Xiao
Published: June 2022

Ambient fine particulate matter (PM2.5) is associated with an elevated risk of acute lower respiratory infections (ALRI). However, this association has not been examined using alternative exposure metrics. We collected outpatient data of patients with ALRI aged <14 years from the administrative database of a large tertiary hospital in Guangzhou, China, from 2013 to 2019. Ambient PM2.5 was measured using three metrics: (a) daily mean, (b) daily excessive concentration hours (DECH), and (c) hourly peak. Generalized additive models were fitted to estimate the excess risk (ER) associated with PM2.5. A total of 105,639 ALRI (35,310 pneumonia and 68,218 bronchiolitis) outpatient visits were identified during the study period. An interquartile range increment in PM2.5 DECH was consistently associated with the highest ER of ALRI-related outpatient visits: 12.30% (95% confidence interval [CI]: 9.49–15.18%), compared with 11.20% (95% CI: 8.34–14.13%) for daily mean and 9.73% (95% CI: 6.97–12.55%) for hourly peak. The associations between the three metrics of PM2.5 and ALRI-related outpatient visits were stronger in the cold season than in the warm season. Future studies should consider PM2.5 DECH as an alternative method of exposure measurement, in addition to daily mean and hourly peak concentrations of PM2.5.
Associations of Socioeconomic Status and Healthy Lifestyle With Incidence of Dyslipidemia: A Prospective Chinese Governmental Employee Cohort Study
Authors: Li Ling , Ouyang Feiyun , He Jun , Qiu Dan , Luo Dan , Xiao Shuiyuan
Published: June 2022

Objective

The purpose of the study was to test whether primary lifestyles mediate associations of SES with incidence of dyslipidemia and to explore interaction relations of lifestyles and SES with incidence of dyslipidemia.

Methods

We included 9,901 individuals at baseline from January 2018 to November 2019, and incidence data were updated to 31 December 2020. Dyslipidemia was defined as total cholesterol (TC) 6.2 mmol/L TC ≥ or triglycerides (TG) ≥2.3 mmol/L or low-density lipoprotein cholesterol (LDL-C) ≥4.1 mmol/L or high-density lipoprotein cholesterol (HDL-C) <1.0 mmol/L; or physician diagnosed dyslipidemia or lipid-lowering drugs use. Lifestyles, socioeconomic factors, and personal characteristics were collected by a questionnaire. A latent class analysis based on education, family income, and occupational position was used to assess the SES. Lifestyle score was calculated using cigarette smoking, alcohol consumption, physical activity, and diet. Cox proportional hazard models and multivariate analyses were used to explore the associations. The mediation effect was evaluated using bootstrap method.

Results

Participant mean age was 36.5 years (SD = 0.11). The cumulative incidence of dyslipidemia was 11.0% over a mean follow-up of 13.4 months. Compared with participants of high SES, those with low SES had higher risk of incidence of dyslipidemia [hazard ratio 1.32, 95% confidence interval (CI): 1.01–1.73], after adjusting for lifestyle scores and other covariates. The proportion mediated by lifestyles was 5.41% (95%CI: 4.17–7.11). A significant additive interaction was found between lifestyles and SES, whereas association between lifestyle and incidence of dyslipidemia was stronger among those of high SES. Additionally, individuals with low SES and no or one healthy lifestyle behavior had a higher risk of developing dyslipidemia than those with high SES and 3 or 4 healthy lifestyles.

Conclusion

Unhealthy lifestyles play a small moderating role in socioeconomic inequity in incidence of dyslipidemia among Chinese governmental employees, suggesting that promoting healthy lifestyles alone may not significantly reduce socioeconomic inequalities in health, and measures to address other social determinants of health should also be considered alongside.
Fertility Intention and Related Factors for Having a Second or Third Child Among Childbearing Couples in Shanghai, China
Authors: Zhu Chenfeng , Yan Li , Wang Yang , Ji Sifan , Zhang Yiqin , Zhang Jian
Published: June 2022

Background and Purpose

As the global fertility rate declines, China has issued two and three-child policies in the past 10 years. Therefore, this study serves to evaluate fertility intention rates and related factors in couples intending to have a second child and third child.

Methods

A cross-sectional survey was conducted in mainland China from July to August 2021. Couples with one or two children were invited to participate in our study in order to collect information about more than one child fertility intention and the possibly related factors. Odds ratios (ORs) and their corresponding 95% confidence intervals (CIs) were calculated and adjusted for potential confounding factors.

Results

Data was collected from a total of 1,026 couples. Among couples with one child, 130 (16.2%) couples had the intention to have a second child. Additionally, only 9.4% of couples with two children desired to have third child. The study revealed large differences in socioeconomic and personal factors between the two groups. For couples with intentions for a second-child, a female age >35 years (adjusted odds ratio, aOR 1.92), a first child's age range from 3 to 6 (aOR 3.12), annual child spending as a percentage of household income >30% (aOR 2.62), and children's educational barriers (aOR 1.55) were associated with lack of intent to have a second child. Similarly, among couples with two children, parents with family financial constraints (aOR 6.18) and children's educational barriers (aOR 4.93) are more likely to have lack of intent to have a third child. Here, we report that government policies encouraging fertility (aOR 0.04) can effectly promote couples to pursue a second or third child.

Conclusion

Overall, couples with one or two children in Shanghai had a low intention to give birth to a second or third child. In order to increase the birth rates, it is necessary to implement policies to reduce the burden of raising children and provide relief to parent's pressure of rearing a child with increased free time.
Identification of Five Hub Genes Based on Single-Cell RNA Sequencing Data and Network Pharmacology in Patients With Acute Myocardial Infarction
Authors: Song Ziguang , Gao Pingping , Zhong Xiao , Li Mingyang , Wang Mengmeng , Song Xiang
Published: June 2022

Acute myocardial infarction (AMI) has a high mortality. The single-cell RNA sequencing (scRNA-seq) method was used to analyze disease heterogeneity at the single-cell level. From the Gene Expression Omnibus (GEO) database (GSE180678), AMI scRNA-seq were downloaded and preprocessed by the Seurat package. Gene expression data came from GSE182923. Cell cluster analysis was conducted. Cell types were identified. Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO) analyses were performed on hub genes. Drugs were predicted by protein–protein interaction (PPI) and molecular docking. In total, 7 cell clusters were defined based on the scRNA-seq dataset, and the clusters were labeled as 5 cell types by marker genes. Hematopoietic stem cell types as a differential subgroups were higher in AMI than in healthy tissues. From available databases and PPI analysis, 52 common genets were identified. Based on 52 genes, 5 clusters were obtained using the MCODE algorithm, and genes in these 5 clusters involved in immune and inflammatory pathways were determined. Correlation analysis showed that hematopoietic stem cell types were negatively correlated with ATM, CARM1, and CASP8 but positively correlated with CASP3 and PPARG. This was reversed with immune cells. Molecular docking analysis showed that DB05490 had the lowest docking score with PPARG. We identified 5 hub genes (ATM, CARM1, CASP8, CASP3, and PPARG) involved in AMI progression. Compound DB05490 was a potential inhibitor of PPAG.
Knowledge Mapping of Multicriteria Decision Analysis in Healthcare: A Bibliometric Analysis
Authors: Dai Zeqi , Xu Simin , Wu Xue , Hu Ruixue , Li Huimin , He Haoqiang , Hu Jing , Liao Xing
Published: June 2022

Objective

Multicriteria decision analysis (MCDA) is a useful tool in complex decision-making situations, and has been used in medical fields to evaluate treatment options and drug selection. This study aims to provide valuable insights into MCDA in healthcare through examining the research focus of existing studies, major fields, major applications, most productive authors and countries, and most common journals in the domain.

Methods

A bibliometric analysis was conducted on the publication related to MCDA in healthcare from the Web of Science Core Collection (WoSCC) database on 14 July 2021. Three bibliometric software (VOSviewer, R-bibliometrix, and CiteSpace) were used to conduct the analysis including years, countries, institutes, authors, journals, co-citation references, and keywords.

Results

A total of 410 publications were identified with an average yearly growth rate of 32% (1999–2021), from 196 academic journals with 23,637 co-citation references by 871 institutions from 70 countries/regions. The United States was the most productive country (n = 80). Universiti Pendidikan Sultan Idris (n = 16), Université de Montréal (n = 13), and Syreon Research Institute (n = 12) were the top productive institutions. A A Zaidan, Mireille Goetghebeur and Zoltan Kalo were the biggest nodes in every cluster of authors' networks. The top journals in terms of the number of articles (n = 17) and citations (n = 1,673) were Value in Health and Journal of Medical Systems, respectively. The extant literature has focused on four aspects, including the analytic hierarchy process (AHP), decision-making, health technology assessment, and healthcare waste management. COVID-19 and fuzzy TOPSIS received careful attention from MCDA applications recently. MCDA in big data, telemedicine, TOPSIS, and fuzzy AHP is well-developed and an important theme, which may be the trend in future research.

Conclusion

This study uncovers a holistic picture of the performance of MCDA-related literature published in healthcare. MCDA has a broad application on different topics and would be helpful for practitioners, researchers, and decision-makers working in healthcare to advance the wheel of medical complex decision-making. It can be argued that the door is still open for improving the role of MCDA in healthcare, whether in its methodology (e.g., fuzzy TOPSIS) or application (e.g., telemedicine).
Multiplex Serology for Measurement of IgG Antibodies Against Eleven Infectious Diseases in a National Serosurvey: Haiti 2014–2015
Authors: Chan YuYen , Martin Diana , Mace Kimberly E. , Jean Samuel E. , Stresman Gillian , Drakeley Chris , Chang Michelle A. , Lemoine Jean F. , Udhayakumar Venkatachalam , Lammie Patrick J. , Priest Jeffrey W. , Rogier Eric William
Published: June 2022

Background

Integrated surveillance for multiple diseases can be an efficient use of resources and advantageous for national public health programs. Detection of IgG antibodies typically indicates previous exposure to a pathogen but can potentially also serve to assess active infection status. Serological multiplex bead assays have recently been developed to simultaneously evaluate exposure to multiple antigenic targets. Haiti is an island nation in the Caribbean region with multiple endemic infectious diseases, many of which have a paucity of data for population-level prevalence or exposure.

Methods

A nationwide serosurvey occurred in Haiti from December 2014 to February 2015. Filter paper blood samples (n = 4,438) were collected from participants in 117 locations and assayed for IgG antibodies on a multiplex bead assay containing 15 different antigens from 11 pathogens: Plasmodium falciparum, Toxoplasma gondii, lymphatic filariasis roundworms, Strongyloides stercoralis, chikungunya virus, dengue virus, Chlamydia trachomatis, Treponema pallidum, enterotoxigenic Escherichia coli, Entamoeba histolytica, and Cryptosporidium parvum.

Results

Different proportions of the Haiti study population were IgG seropositive to the different targets, with antigens from T. gondii, C. parvum, dengue virus, chikungunya virus, and C. trachomatis showing the highest rates of seroprevalence. Antibody responses to T. pallidum and lymphatic filariasis were the lowest, with <5% of all samples IgG seropositive to antigens from these pathogens. Clear trends of increasing seropositivity and IgG levels with age were seen for all antigens except those from chikungunya virus and E. histolytica. Parametric models were able to estimate the rate of seroconversion and IgG acquisition per year for residents of Haiti.

Conclusions

Multiplex serological assays can provide a wealth of information about population exposure to different infectious diseases. This current Haitian study included IgG targets for arboviral, parasitic, and bacterial infectious diseases representing multiple different modes of host transmission. Some of these infectious diseases had a paucity or complete absence of published serological studies in Haiti. Clear trends of disease burden with respect to age and location in Haiti can be used by national programs and partners for follow-up studies, resource allocation, and intervention planning.
The Impact of the Consistency Evaluation Policy of Generic Drugs on R&D Investment Intensity of Pharmaceutical Companies—An Empirical Study Based on the Difference-in-Differences Model
Authors: Wei Yanyi , Zhu Jialin , Qiao Jiahui , Zhang Dawei , Chen Yuwen
Published: June 2022

In 2016, China began to execute the consistency evaluation policy of generic drugs. Many scholars believed that the policy would stimulate pharmaceutical firms to increase R&D investment with a theoretical perspective, but few have conducted empirical studies. Therefore, we conduct a difference-in-differences (DID) model and use panel data of 111 A-share listed pharmaceutical firms from 2012 to 2020 to empirically study the impact of the consistency evaluation policy of generic drugs on pharmaceutical firms' R&D investment intensity. The result shows that the policy has a significant positive impact on the R&D investment intensity of firms with chemical generics, robust under the test for parallel trend test, placebo test, and the propensity score matching and difference-in-differences (PSM-DID) test. In addition, we further analyzed the impact of this policy on the R&D intensity of pharmaceutical firms according to the heterogeneity of enterprise's operational nature, regional distribution and profitability. From the perspective of time changes and the average effect, the R&D investment intensity of private pharmaceutical firms is more affected by the policy than state-owned enterprises; the R&D investment intensity of pharmaceutical firms in the eastern region is more affected by this policy than those in the central and the western; the R&D investment intensity of high-profitability pharmaceutical firms is more affected by the policy than those with low-profitability. The consistency evaluation policy is still being implemented, and its impact on pharmaceutical firms needs to be studied from different empirical research perspectives in the future.
Integrating Client Tracker Tool Into Fistula Management: Experience From the Fistula Care Plus Project in the Democratic Republic of Congo, 2017 to 2019
Authors: Paluku Justin , Kitambala Esther , Furaha Cathy Mufungizi , Bulu Bobina Rita , Habamungu Pascal , Camara Bienvenu Salim , Sidibe Sidikiba , Banze Kyongolwa Don Félicien , Tripathi Vandana , Delamou Alexandre
Published: June 2022

This study aimed to document the experience of integration and the contribution of the Client Tracker (CT) to female genital fistula (FGF) management and data quality in sites supported by the Fistula Care+ Project in the Democratic Republic of Congo (DRC), from 2017 to 2019. It was a parallel mixed methods study using routine quantitative data and qualitative data from in-depth interviews with the project staff. Quantitative findings indicated that CT forms were present in the medical records of 63% of patients; of these, 38% were completely filled out, and 29% were correctly filled out. Qualitative findings suggested that the level of use of CT in the management of FGF was associated with staff familiarity with the CT, staff understanding of concepts in the CT forms, and the CT-related additional workload. The CT has mainly contributed to improving data quality and reporting, quality of care, follow-up of fistula patients, and self-supervision of management activities. A possible simplification of the CT and/or harmonization of its content with existing routine forms, coupled with adequate continuous training of staff on record-keeping, would further contribute to maximizing CT effectiveness and sustainability.
Evaluation of the Radiographic Risk Factors of Postoperative Shoulder Imbalance in Adult Scoliosis
Authors: Ke Wencan , Wang Bingjin , Hua Wenbin , Wang Kun , Li Shuai , Yang Cao
Published: June 2022

Objective

This study aimed to evaluate the radiographic risk factors of postoperative shoulder imbalance (PSI) after adult scoliosis (AS) correction surgery.

Methods

Seventy-nine patients with AS undergoing correction surgery at a single institution were reviewed. The mean follow-up was 28 months. Patients were divided into two groups based on their radiographic shoulder height (RSH): (1) the balanced group (RSH <10 mm) and (2) the unbalanced group (RSH ≥10 mm). The preoperative and postoperative Cobb angles of the proximal thoracic (PT), main thoracic (MT), thoracolumbar/lumbar (TL/L) and upper instrumented vertebra (UIV) were measured.

Results

No significant difference was found between the balanced and unbalanced groups when the UIV was T1–2, T3–4, or below T4. Univariate analysis indicated that the unbalanced group had significantly higher postoperative RSH, lower percentage PT correction, and greater percentage MT correction. The classification and regression tree analysis revealed that when the correction percentage of PT curve was more than 55.3%, 84.4% of patients acquired shoulder balance. However, when the correction percentage of PT curve was less than 55.3%, and the correction percentage of MT curve was more than 56%, 65.7% of the patients developed PSI.

Conclusions

In AS correction surgery, a lower percentage correction of the PT curve and greater percentage correction of the MT curve were independent radiographic risk factors of PSI, regardless of the UIV level. Sufficient PT correction is required to achieve postoperative shoulder balance in AS correction surgery when the MT curve is overcorrected.
The Scope and Impact of the COVID-19 Pandemic on Neuroemergent Patient Transfers, Clinical Care and Patient Outcomes
Authors: Woodward Josha , Meza Samuel , Richards Dominick , Koro Lacin , Keegan Kevin C. , Joshi Krishna C. , Munoz Lorenzo F. , Byrne Richard W. , John Sayona
Published: June 2022

Introduction

The SARS-CoV-2 (COVID-19) pandemic continues to substantially alter previously established clinical practice patterns and has transformed patient care in American healthcare. However, studies to evaluate the impact of COVID-19 on neuroemergent patient care and associated clinical outcomes are limited. Herein, we describe the impact of COVID-19 on the Neuroemergency Transfer Program (NTP) - a novel, urban, high volume interhospital patient transfer program.

Objective

To evaluate and describe the clinical impact of the COVID-19 pandemic on the NTP.

Study Design

A single-center retrospective study of prospectively collected consecutive neuroemergent patient transfer data between 2018–2021 was analyzed. Adult patients were divided based upon transfer date into a Pre-COVID (PCOV) or COVID cohort. Patient demographics, transfer characteristics and clinical data and outcomes were analyzed.

Results

3,096 patients were included for analysis. Mean age at transfer in the PCOV and COVID cohorts were 62.4 ± 0.36 and 61.1 ± 0.6 years. A significant decrease in mean transfers per month was observed between cohorts (PCOV = 97.8 vs. COV = 68.2 transfers/month, p < 0.01). Total transfer time in the PCOV cohort was 155.1 ± 3.4 min which increased to 169.3 ± 12.8 min in the COVID cohort (p = 0.13). Overall mean transfer distance was significantly longer in the PCOV cohort at 22.0 ± 0.4 miles vs. 20.3 ± 0.67 miles in the COV cohort (p = 0.03). The relative frequency of transfer diagnoses was unchanged between cohorts. A significant increase in mean inpatient length of stay was noted, 7.9 ± 0.15 days to 9.6 ± 0.33 days in the PCOV vs. COVID cohorts (p < 0.01). Ultimately, no difference in the frequency of good vs. poor clinical outcome were noted between the PCOV (79.8% and 19.4%) vs. COV (78.8% and 20.4%) cohorts.

Conclusion

The impact of COVID-19 on current healthcare dynamics are far reaching. Here, we show a significant decrease in interhospital patient transfers and increased length of stay between a Pre-COVID and COVID cohort. Further work to better elucidate the specific interplay of clinical contributors to account for these changes is indicated.
Functional Status, Mood State, and Physical Activity Among Women With Post-Acute COVID-19 Syndrome
Authors: Carter Stephen J. , Baranauskas Marissa N. , Raglin John S. , Pescosolido Bernice A. , Perry Brea L.
Published: June 2022

Objectives: While organ-specific pathophysiology has been well-described in SARS-CoV-2 infection, less is known about the attendant effects on functional status, mood state and leisure-time physical activity (PA) in post-acute COVID-19 syndrome (PASC).

Methods: A case-control design was employed to recruit 32 women (n = 17 SARS-CoV-2; n = 15 controls) matched on age (54 ± 12 years) and body mass index (27 ± 6 kg/m2) that did not differ by smoking status or history of cardiopulmonary disease. Participants completed a series of assessments including Profile of Mood States (POMS), Modified Pulmonary Functional Status and Dyspnea Questionnaire (PFSDQ-M), and Godin-Shephard Leisure-Time PA.

Results: Significant between-group differences were detected for the POMS total mood disturbance with sub-scale analyses revealing elevated tension, confusion, and lower vigor among SARS-CoV-2 participants (all p-values < 0.05). The number of SARS-CoV-2 symptoms (e.g., loss of taste/smell, muscle aches etc.) were associated (r = 0.620, p = 0.008) with confusion. SARS-CoV-2 participants exhibited poorer functional status (p = 0.008) and reduced leisure-time PA (p = 0.004) compared to controls.

Conclusion: The sequela of persistent SARS-CoV-2 symptoms elicit clear disturbances in functional status, mood state, and leisure-time PA among women with PASC. Ongoing symptom presentation affects recovery time-course and PA participation.
Validation of a Simple, Rapid, and Cost-Effective Method for Acute Rejection Monitoring in Lung Transplant Recipients
Authors: Sorbini Monica , Togliatto Gabriele , Mioli Fiorenza , Simonato Erika , Marro Matteo , Cappuccio Margherita , Arruga Francesca , Caorsi Cristiana , Mansouri Morteza , Magistroni Paola , Gambella Alessandro , Delsedime Luisa , Papotti Mauro Giulio , Solidoro Paolo , Albera Carlo , Boffini Massimo , Rinaldi Mauro , Amoroso Antonio , Vaisitti Tiziana , Deaglio Silvia
Published: June 2022

Despite advances in immunosuppression therapy, acute rejection remains the leading cause of graft dysfunction in lung transplant recipients. Donor-derived cell-free DNA is increasingly being considered as a valuable biomarker of acute rejection in several solid organ transplants. We present a technically improved molecular method based on digital PCR that targets the mismatch between the recipient and donor at the HLA-DRB1 locus. Blood samples collected sequentially post-transplantation from a cohort of lung recipients were used to obtain proof-of-principle for the validity of the assay, correlating results with transbronchial biopsies and lung capacity tests. The results revealed an increase in dd-cfDNA during the first 2 weeks after transplantation related to ischemia-reperfusion injury (6.36 ± 5.36%, p < 0.0001). In the absence of complications, donor DNA levels stabilized, while increasing again during acute rejection episodes (7.81 ± 12.7%, p < 0.0001). Respiratory tract infections were also involved in the release of dd-cfDNA (9.14 ± 15.59%, p = 0.0004), with a positive correlation with C-reactive protein levels. Overall, the dd-cfDNA percentages were inversely correlated with the lung function values measured by spirometry. These results confirm the value of dd-cfDNA determination during post-transplant follow-up to monitor acute rejection in lung recipients, achieved using a rapid and inexpensive approach based on the HLA mismatch between donor and recipient.
Machine Learning and rs-fMRI to Identify Potential Brain Regions Associated with Autism Severity
Authors: Rodrigues Igor D. , de Carvalho Emerson A. , Santana Caio P. , Bastos Guilherme S.
Published: June 2022

Autism Spectrum Disorder (ASD) is a neurodevelopmental disorder characterized primarily by social impairments that manifest in different severity levels. In recent years, many studies have explored the use of machine learning (ML) and resting-state functional magnetic resonance images (rs-fMRI) to investigate the disorder. These approaches evaluate brain oxygen levels to indirectly measure brain activity and compare typical developmental subjects with ASD ones. However, none of these works have tried to classify the subjects into severity groups using ML exclusively applied to rs-fMRI data. Information on ASD severity is frequently available since some tools used to support ASD diagnosis also include a severity measurement as their outcomes. The aforesaid is the case of the Autism Diagnostic Observation Schedule (ADOS), which splits the diagnosis into three groups: ‘autism’, ‘autism spectrum’, and ‘non-ASD’. Therefore, this paper aims to use ML and fMRI to identify potential brain regions as biomarkers of ASD severity. We used the ADOS score as a severity measurement standard. The experiment used fMRI data of 202 subjects with an ASD diagnosis and their ADOS scores available at the ABIDE I consortium to determine the correct ASD sub-class for each one. Our results suggest a functional difference between the ASD sub-classes by reaching 73.8% accuracy on cingulum regions. The aforementioned shows the feasibility of classifying and characterizing ASD using rs-fMRI data, indicating potential areas that could lead to severity biomarkers in further research. However, we highlight the need for more studies to confirm our findings.
Process Mining the Performance of a Real-Time Healthcare 4.0 Systems Using Conditional Survival Models
Authors: Marshall Adele H. , Novakovic Aleksandar
Published: June 2022

As the world moves into the exciting age of Healthcare 4.0, it is essential that patients and clinicians have confidence and reassurance that the real-time clinical decision support systems being used throughout their care guarantee robustness and optimal quality of care. However, current systems involving autonomic behaviour and those with no prior clinical feedback, have generally to date had little focus on demonstrating robustness in the use of data and final output, thus generating a lack of confidence. This paper wishes to address this challenge by introducing a new process mining approach based on a statistically robust methodology that relies on the utilisation of conditional survival models for the purpose of evaluating the performance of Healthcare 4.0 systems and the quality of the care provided. Its effectiveness is demonstrated by analysing the performance of a clinical decision support system operating in an intensive care setting with the goal to monitor ventilated patients in real-time and to notify clinicians if the patient is predicted at risk of receiving injurious mechanical ventilation. Additionally, we will also demonstrate how the same metrics can be used for evaluating the patient quality of care. The proposed methodology can be used to analyse the performance of any Healthcare 4.0 system and the quality of care provided to the patient.
BAG-DSM: A Method for Generating Alternatives for Hierarchical Multi-Attribute Decision Models Using Bayesian Optimization
Authors: Gjoreski Martin , Kuzmanovski Vladimir , Bohanec Marko
Published: June 2022

Multi-attribute decision analysis is an approach to decision support in which decision alternatives are evaluated by multi-criteria models. An advanced feature of decision support models is the possibility to search for new alternatives that satisfy certain conditions. This task is important for practical decision support; however, the related work on generating alternatives for qualitative multi-attribute decision models is quite scarce. In this paper, we introduce Bayesian Alternative Generator for Decision Support Models (BAG-DSM), a method to address the problem of generating alternatives. More specifically, given a multi-attribute hierarchical model and an alternative representing the initial state, the goal is to generate alternatives that demand the least change in the provided alternative to obtain a desirable outcome. The brute force approach has exponential time complexity and has prohibitively long execution times, even for moderately sized models. BAG-DSM avoids these problems by using a Bayesian optimization approach adapted to qualitative DEX models. BAG-DSM was extensively evaluated and compared to a baseline method on 43 different DEX decision models with varying complexity, e.g., different depth and attribute importance. The comparison was performed with respect to: the time to obtain the first appropriate alternative, the number of generated alternatives, and the number of attribute changes required to reach the generated alternatives. BAG-DSM outperforms the baseline in all of the experiments by a large margin. Additionally, the evaluation confirms BAG-DSM’s suitability for the task, i.e., on average, it generates at least one appropriate alternative within two seconds. The relation between the depth of the multi-attribute hierarchical models—a parameter that increases the search space exponentially—and the time to obtaining the first appropriate alternative was linear and not exponential, by which BAG-DSM’s scalability is empirically confirmed.
Improved JPS Path Optimization for Mobile Robots Based on Angle-Propagation Theta* Algorithm
Authors: Luo Yuan , Lu Jiakai , Qin Qiong , Liu Yanyu
Published: June 2022

The Jump Point Search (JPS) algorithm ignores the possibility of any-angle walking, so the paths found by the JPS algorithm under the discrete grid map still have a gap with the real paths. To address the above problems, this paper improves the path optimization strategy of the JPS algorithm by combining the viewable angle of the Angle-Propagation Theta* (AP Theta*) algorithm, and it proposes the AP-JPS algorithm based on an any-angle pathfinding strategy. First, based on the JPS algorithm, this paper proposes a vision triangle judgment method to optimize the generated path by selecting the successor search point. Secondly, the idea of the node viewable angle in the AP Theta* algorithm is introduced to modify the line of sight (LOS) reachability detection between two nodes. Finally, the paths are optimized using a seventh-order polynomial based on minimum snap, so that the AP-JPS algorithm generates paths that better match the actual robot motion. The feasibility and effectiveness of this method are proved by simulation experiments and comparison with other algorithms. The results show that the path planning algorithm in this paper obtains paths with good smoothness in environments with different obstacle densities and different map sizes. In the algorithm comparison experiments, it can be seen that the AP-JPS algorithm reduces the path by 1.61–4.68% and the total turning angle of the path by 58.71–84.67% compared with the JPS algorithm. The AP-JPS algorithm reduces the computing time by 98.59–99.22% compared with the AP-Theta* algorithm.
MedicalSeg: A Medical GUI Application for Image Segmentation Management
Authors: Mata Christian , Munuera Josep , Lalande Alain , Ochoa-Ruiz Gilberto , Benitez Raul
Published: June 2022

In the field of medical imaging, the division of an image into meaningful structures using image segmentation is an essential step for pre-processing analysis. Many studies have been carried out to solve the general problem of the evaluation of image segmentation results. One of the main focuses in the computer vision field is based on artificial intelligence algorithms for segmentation and classification, including machine learning and deep learning approaches. The main drawback of supervised segmentation approaches is that a large dataset of ground truth validated by medical experts is required. In this sense, many research groups have developed their segmentation approaches according to their specific needs. However, a generalised application aimed at visualizing, assessing and comparing the results of different methods facilitating the generation of a ground-truth repository is not found in recent literature. In this paper, a new graphical user interface application (MedicalSeg) for the management of medical imaging based on pre-processing and segmentation is presented. The objective is twofold, first to create a test platform for comparing segmentation approaches, and secondly to generate segmented images to create ground truths that can then be used for future purposes as artificial intelligence tools. An experimental demonstration and performance analysis discussion are presented in this paper.
Recognition of the Airspace Affected by the Presence of Volcanic Ash from Popocatepetl Volcano Using Historical Satellite Images
Authors: Jiménez-Escalona José Carlos , Poom-Medina José Luis , Roberge Julie , Aparicio-García Ramon S. , Avila-Razo José Eduardo , Huerta-Chavez Oliver Marcel , Da Silva Rodrigo Florencio
Published: June 2022

A volcanic eruption can produce large ash clouds in the atmosphere around a volcano, affecting commercial aviation use of the airspace around the volcano. Encountering these ash clouds can cause severe damage to different parts of the aircraft, mainly the engines. This work seeks to contribute to the development of methods for observing the dispersion of volcanic ash and to complement computational methods that are currently used for the prediction of ash dispersion. The method presented here is based on the frequency of occurrence of the regions of airspace areas affected by ash emission during a volcanic eruption. Popocatepetl volcano, 60 km east of Mexico City is taken as a case study. A temporal wind analysis was carried out at different atmospheric levels, to identify the direction towards which the wind disperses ash at different times of the year. This information showed two different trends, related to seasons in the direction of dispersion: the first from November to May and the second from July to September. To identify the ash cloud and estimate its area, a set of 920 MODIS images that recorded Popocatepetl volcanic activity between 2000 and 2021 was used. These satellite images were subjected to a semi-automatic, digital pre-processing of binarization by thresholds, according to the level of the brightness temperature difference between band 31 (11 µm) and band 32 (12 µm), followed by manual evaluation of each binarized image. With the information obtained by the processing of the MODIS image, an information table was built with the geographical position of each pixel characterized by the presence of ash for each event. With these data, the areas around Popocatepetl volcano with the highest frequency of affectation by ash emissions were identified during the period analyzed. This study seeks to complement the results obtained by numerical models that make forecasts of ash dispersions and that are very important for the prevention of air navigation risks.
Remaining Useful Life Estimation of Cooling Units via Time-Frequency Health Indicators with Machine Learning
Authors: Llasag Rosero Raúl , Silva Catarina , Ribeiro Bernardete
Published: June 2022

Predictive Maintenance (PM) strategies have gained interest in the aviation industry to reduce maintenance costs and Aircraft On Ground (AOG) time. Taking advantage of condition monitoring data from aircraft systems, Prognostics and Health Maintenance (PHM) practitioners have been predicting the life span of aircraft components by applying Remaining Useful Life (RUL) concepts. Additionally, in prognostics, the construction of Health Indicators (HIs) plays a significant role when failure advent patterns are strenuous to be discovered directly from data. HIs are typically supported by data-driven models dealing with non-stationary signals, e.g., aircraft sensor time-series, in which data transformations from time and frequency domains are required. In this paper, we build time-frequency HIs based on the construction of the Hilbert spectrum and propose the integration of a physics-based model with a data-driven model to predict the RUL of aircraft cooling units. Using data from a major airline, and considering two health degradation stages, the advent of failures on aircraft systems can be estimated with data-driven Machine Learning models (ML). Specifically, our results reveal that the analyzed cooling units experience a normal degradation stage before an abnormal degradation that emerges within the last flight hours of useful life.