bluuebunny/crossref_metadata_2025_split huggingface dataset:
Telemedicine treatment of patients with mental disorders during and after the first COVID-19 pandemic lockdown in Germany – an observational study on feasibility and patient satisfaction
Authors: Link Karsten , Christians Svenja , Hoffmann Wolfgang , Grabe Hans Jörgen , van den Berg Neeltje 
Published: September 2023

Abstract
Introduction
In response to the COVID-19 pandemic, a general lockdown was enacted across Germany in March 2020. As a consequence, patients with mental health conditions received limited or no treatment in day hospitals and outpatient settings. To ensure continuity of care, the necessary technological preparations were made to enable the implementation of telemedical care via telephone or video conferencing, and this option was then used as much as possible. The aim of this study was to investigate the satisfaction and acceptance with telemedical care in a heterogeneous patient group of psychiatric outpatients in Germany during the first COVID-19 lockdown.

Methods
In this observational study, patients in ongoing or newly initiated outpatient psychiatric therapy as well as those who had to be discharged from the day clinic ahead of schedule received telemedical treatment via telephone. Data collection to assess the patients’ and therapists’ satisfaction with and acceptance of the telemedical care was adjusted to the treatment setting.

Results
Of 60 recruited patients, 57 could be included in the analysis. 51.6% of the patients and 52.3% of their therapists reported that the discussion of problems and needs worked just as well over the phone as in face-to-face consultations. In the subgroup of patients who were new to therapy due to being discharged from hospital early, acceptance was higher and telemedicine was rated as equally good in 87.5% of contacts. Both patients and therapists felt that telemedicine care during lockdown was an alternative for usual therapy in the outpatient clinic and that the option of telemedicine care should continue for the duration of the coronavirus pandemic.

Discussion
The results show a clear trend towards satisfaction with and acceptance of telemedicine care in a heterogeneous group of unselected psychiatric patients. Although the number of patients is small, the results indicate that the mostly positive results of telemedicine concepts in research projects can probably be transferred to real healthcare settings.

Conclusions
Telemedicine can be employed in healthcare for psychiatric patients either an alternative treatment option to maintain continuity of care or as a potential addition to regular care.
Excess mortality during the Coronavirus disease pandemic in Korea
Authors: Han Changwoo , Jang Hoyeon , Oh Juhwan 
Published: September 2023

Abstract
Background
Although the ongoing epidemics of Coronavirus disease 2019 (COVID-19) may have affected the mortality trend of the nation, the national level assessment of excess mortality (changes in overall mortality in the entire population) is still scarce in Korea. Therefore, this study evaluated the excess mortality during the COVID-19 pandemic in Korea using the certified mortality data.

Methods
Monthly mortality and population data from January 2013 to June 2022 was obtained from the National Health Insurance Service database and Statistics Korea. A quasi-Poisson interrupted time-series model adjusted for age structure, population, seasonality, and long-term trends was used to estimate the counterfactual projections (expected) of mortality during the COVID-19 pandemic (March 2020 to June 2022). The absolute difference (observed—expected) and ratio (observed / expected) of mortality were calculated. Stratified analysis based on pandemic years (years 2020, 2021, and 2022), sex, and age groups (aged 0–4, 5–19, 20–64, and ≥ 65 years) were conducted.

Results
An 8.7% increase in mortality was observed during the COVID-19 pandemic [absolute difference: 61,277 persons; ratio (95% confidence interval (CI)): 1.087 (1.066, 1.107)]. The gap between observed and estimated mortality became wider with continuation of the pandemic [ratio (95% CI), year 2020: 1.021 (1.003, 1.040); year 2021: 1.060 (1.039, 1.080), year 2022: 1.244 (1.219, 1.270)]. Although excess mortality across sex was similar, the adult [aged 20–64, ratio (95% CI): 1.059 (1.043, 1.076)] and elderly [aged 65-, ratio (95% CI): 1.098 (1.062, 1.135)] population showed increased excess mortality during the pandemic.

Conclusions
Despite Korea's successful quarantine policy response, the continued epidemic has led to an excess mortality. The estimated mortality exceeded the number of deaths from COVID-19 infection. Excess mortality should be monitored to estimate the overall impact of the pandemic on a nation.
Development and validation of a novel nomogram to predict the risk of the prolonged postoperative length of stay for lumbar spinal stenosis patients
Authors: Yasin Parhat , Cai Xiaoyu , Mardan Muradil , Xu Tao , Abulizi Yakefu , Aimaiti Abasi , Yang Huan , Sheng Weibin , Mamat Mardan 
Published: September 2023

Abstract
Background
Lumber spinal stenosis (LSS) is the increasingly reason for spine surgery for elder patients since China is facing the fastest-growing aging population. The aim of this research was to create a model to predict the probabilities of requiring a prolonged postoperative length of stay (PLOS) for lumbar spinal stenosis patients, minimizing the healthcare burden.

Methods
A total of 540 LSS patients were enrolled in this project. The outcome was a prolonged PLOS after spine surgery, defined as hospitalizations ≥ 75th percentile for PLOS, including the day of discharge. The least absolute shrinkage and selection operator (LASSO) was used to identify independent risk variables related to prolonged PLOS. Multivariable logistic regression analysis was utilized to generate a prediction model utilizing the variables employed in the LASSO approach. The receiver operating characteristic (ROC) curve’s area under the curve (AUC) and the calibration curve’s respective curves were used to further validate the model’s calibration with predictability and discriminative capabilities. By using decision curve analysis, the resulting model’s clinical effectiveness was assessed.

Results
Among 540 individuals, 344 had PLOS that was within the usual range of P75 (8 days), according to the interquartile range of PLOS, and 196 had PLOS that was above the normal range of P75 (prolonged PLOS). Four variables were incorporated into the predictive model, named: transfusion, operation duration, blood loss and involved spine segments. A great difference in clinical scores can be found between the two groups (P < 0.001). In the development set, the model’s AUC for predicting prolonged PLOS was 0.812 (95% CI: 0.768–0.859), while in the validation set, it was 0.830 (95% CI: 0.753–0.881). The calibration plots for the probability showed coherence between the expected probability and the actual probability both in the development set and validation set respectively. When intervention was chosen at the potential threshold of 2%, analysis of the decision curve revealed that the model was more clinically effective.

Conclusions
The individualized prediction nomogram incorporating five common clinical features for LSS patients undergoing surgery can be suitably used to smooth early identification and improve screening of patients at higher risk of prolonged PLOS and minimize health care.
Scale development to measure the patient perception of patient-centered care of dentists in primary care settings of Thailand: a measurement invariance test
Authors: Khamnil Yutthana , Kao-iean Surasak , Pisarnturakit Pagaporn Pantuwadee 
Published: September 2023

Abstract
Background
Patient-centered care is essential for providing quality services thoroughly at the primary care level, but it is unclear and lacks measurement. This study aimed to develop a reliable and valid instrument to measure patient perception of patient-centered care in primary dental care in Thailand and test the measurement invariance between large and small community hospitals.

Methods
The initial set of 45 items for the patient perception of Patient-Centered Care of Dentist Scale (PCCDS-P version) was developed using a mixed-method approach, which included a literature review, a content validity test, cognitive interviews, and a pre-test. A multistage sampling strategy was used to recruit dental patients or their parents or caregivers from community hospitals across Thailand. Validity was examined through exploratory factor analysis (EFA) and confirmatory factor analysis (CFA). Reliability was assessed using Cronbach's alpha coefficient and the intraclass correlation coefficient. Furthermore, a multi-group analysis was conducted to compare the responses of patients from large and small community hospitals.

Results
Three hundred thirty-six and One thousand one hundred sixty-seven samples were randomized for EFA and CFA, respectively. The final PCCDS-P version consists of 7 factors with satisfactory reliability and validity and is composed of 42 items: dentist-patient relationship, disease-illness, integrated care, communication, shared information and decision-making, holistic, and empathy and anxiety management. The CFA showed the model fit was consistent with the entire sample. The metric invariance analysis showed that the factor loadings were invariant across patient groups. Overall, Cronbach's alpha coefficient and intraclass correlation coefficient were satisfactory.

Conclusions
The newly developed PCCDS-P version is composed of seven domains with 42 items with good reliability and validity, and it indicated measurement invariance across patients in large and small community hospitals.
Association of free-living diet composition with plasma lipoprotein(a) levels in healthy adults
Authors: Matveyenko Anastasiya , Seid Heather , Kim Kyungyeon , Ramakrishnan Rajasekhar , Thomas Tiffany , Matienzo Nelsa , Reyes-Soffer Gissette 
Published: September 2023

AbstractBackgroundLipoprotein (a) [Lp(a)] is an apoB100-containing lipoprotein with high levels being positively associated with atherosclerotic cardiovascular disease. Lp(a) levels are genetically determined. However, previous studies report a negative association between Lp(a) and saturated fatty acid intake. Currently, apoB100 lowering therapies are used to lower Lp(a) levels, and apheresis therapy is FDA approved for patients with extreme elevations of Lp(a). The current study analyzed the association of free-living diet components with plasma Lp(a) levels.MethodsDietary composition data was collected during screening visits for enrollment in previously completed lipid and lipoprotein metabolism studies at Columbia University Irving Medical Center via a standardized protocol by registered dietitians using 24 hour recalls. Data were analyzed with the Nutrition Data System for Research (Version 2018). Diet quality was calculated using the Healthy Eating Index (HEI) score. Fasting plasma Lp(a) levels were measured via an isoform-independent ELISA and apo(a) isoforms were measured using gel electrophoresis.ResultsWe enrolled 28 subjects [Black (n = 18); Hispanic (n = 7); White (n = 3)]. The mean age was 48.3 ± 12.5 years with 17 males. Median level of Lp(a) was 79.9 nmol/L (34.4–146.0) and it was negatively associated with absolute (grams/day) and relative (percent of total calories) intake of dietary saturated fatty acids (SFA) (R = -0.43,P = 0.02, SFA …(% CAL): R = -0.38,P = 0.04), palmitic acid intake (R = -0.38,P = 0.05), and stearic acid intake (R = -0.40,P = 0.03). Analyses of associations with HEI score when stratified based on Lp(a) levels > or ≤ 100 nmol/L revealed no significant associations with any of the constituent factors.ConclusionsUsing 24 hour recall, we confirm previous findings that Lp(a) levels are negatively associated with dietary saturated fatty acid intake. Additionally, Lp(a) levels are not related to diet quality, as assessed by the HEI score. The mechanisms underlying the relationship of SFA with Lp(a) require further investigation.
Secured delivery of basic fibroblast growth factor using human serum albumin-based protein nanoparticles for enhanced wound healing and regeneration
Authors: Son Boram , Kim Minju , Won Hyosub , Jung Ara , Kim Jihyun , Koo Yonghoe , Lee Na Kyeong , Baek Seung-Ho , Han Uiyoung , Park Chun Gwon , Shin Heungsoo , Gweon Bomi , Joo Jinmyoung , Park Hee Ho 
Published: September 2023

Abstract
Background
Basic fibroblast growth factor (bFGF) is one of the critical components accelerating angiogenesis and tissue regeneration by promoting the migration of dermal fibroblasts and endothelial cells associated with matrix formation and remodeling in wound healing process. However, clinical applications of bFGF are substantially limited by its unstable nature due to rapid decomposition under physiological microenvironment.

Results
In this study, we present the bFGF-loaded human serum albumin nanoparticles (HSA-bFGF NPs) as a means of enhanced stability and sustained release platform during tissue regeneration. Spherical shape of the HSA-bFGF NPs with uniform size distribution (polydispersity index < 0.2) is obtained via a simple desolvation and crosslinking process. The HSA-bFGF NPs securely load and release the intact soluble bFGF proteins, thereby significantly enhancing the proliferation and migration activity of human dermal fibroblasts. Myofibroblast-related genes and proteins were also significantly down-regulated, indicating decrease in risk of scar formation. Furthermore, wound healing is accelerated while achieving a highly organized extracellular matrix and enhanced angiogenesis in vivo.

Conclusion
Consequently, the HSA-bFGF NPs are suggested not only as a delivery vehicle but also as a protein stabilizer for effective wound healing and tissue regeneration.
Integrated machine learning survival framework develops a prognostic model based on inter-crosstalk definition of mitochondrial function and cell death patterns in a large multicenter cohort for lower-grade glioma
Authors: Qin Hu , Abulaiti Aimitaji , Maimaiti Aierpati , Abulaiti Zulihuma , Fan Guofeng , Aili Yirizhati , Ji Wenyu , Wang Zengliang , Wang Yongxin 
Published: September 2023

Abstract
Background
Lower-grade glioma (LGG) is a highly heterogeneous disease that presents challenges in accurately predicting patient prognosis. Mitochondria play a central role in the energy metabolism of eukaryotic cells and can influence cell death mechanisms, which are critical in tumorigenesis and progression. However, the prognostic significance of the interplay between mitochondrial function and cell death in LGG requires further investigation.

Methods
We employed a robust computational framework to investigate the relationship between mitochondrial function and 18 cell death patterns in a cohort of 1467 LGG patients from six multicenter cohorts worldwide. A total of 10 commonly used machine learning algorithms were collected and subsequently combined into 101 unique combinations. Ultimately, we devised the mitochondria-associated programmed cell death index (mtPCDI) using machine learning models that exhibited optimal performance.

Results
The mtPCDI, generated by combining 18 highly influential genes, demonstrated strong predictive performance for prognosis in LGG patients. Biologically, mtPCDI exhibited a significant correlation with immune and metabolic signatures. The high mtPCDI group exhibited enriched metabolic pathways and a heightened immune activity profile. Of particular importance, our mtPCDI maintains its status as the most potent prognostic indicator even following adjustment for potential confounding factors, surpassing established clinical models in predictive strength.

Conclusion
Our utilization of a robust machine learning framework highlights the significant potential of mtPCDI in providing personalized risk assessment and tailored recommendations for metabolic and immunotherapy interventions for individuals diagnosed with LGG. Of particular significance, the signature features highly influential genes that present further prospects for future investigations into the role of PCD within mitochondrial function.
Improved genomic prediction using machine learning with Variational Bayesian sparsity
Authors: Yan Qingsen , Fruzangohar Mario , Taylor Julian , Gong Dong , Walter James , Norman Adam , Shi Javen Qinfeng , Coram Tristan 
Published: September 2023

Abstract
Background
Genomic prediction has become a powerful modelling tool for assessing line performance in plant and livestock breeding programmes. Among the genomic prediction modelling approaches, linear based models have proven to provide accurate predictions even when the number of genetic markers exceeds the number of data samples. However, breeding programmes are now compiling data from large numbers of lines and test environments for analyses, rendering these approaches computationally prohibitive. Machine learning (ML) now offers a solution to this problem through the construction of fully connected deep learning architectures and high parallelisation of the predictive task. However, the fully connected nature of these architectures immediately generates an over-parameterisation of the network that needs addressing for efficient and accurate predictions.

Results
In this research we explore the use of an ML architecture governed by variational Bayesian sparsity in its initial layers that we have called VBS-ML. The use of VBS-ML provides a mechanism for feature selection of important markers linked to the trait, immediately reducing the network over-parameterisation. Selected markers then propagate to the remaining fully connected feed-forward components of the ML network to form the final genomic prediction. We illustrated the approach with four large Australian wheat breeding data sets that range from 2665 lines to 10375 lines genotyped across a large set of markers. For all data sets, the use of the VBS-ML architecture improved genomic prediction accuracy over legacy linear based modelling approaches.

Conclusions
An ML architecture governed under a variational Bayesian paradigm was shown to improve genomic prediction accuracy over legacy modelling approaches. This VBS-ML approach can be used to dramatically decrease the parameter burden on the network and provide a computationally feasible approach for improving genomic prediction conducted with large breeding population numbers and genetic markers.
Personalized medicine: paradigm shift in ALK positive non-small cell lung cancer: a case report
Authors: Barreira João Vasco , Mendes José Leão , Parmanande Anuraj 
Published: September 2023

Abstract
Background
Since the identification of multiple therapeutic targets, as is the case of anaplastic lymphoma kinase (ALK) translocation, the paradigm of treating patients with non-small cell lung cancer (NSCLC) has improved. In order to guarantee the possibility of longer survival outcomes with a better quality of life we must invest in the determination, in suitable time, of the consensual biomarkers and in the availability of the best treatments to our patients.

Case presentation
We present a case of a caucasian male in his fifth decade of life, non-smoker, who highlights the complex journey of ALK-positive patients. This particular case, demonstrates the efficacy and tolerability of the new ALK target therapies, allowing our patients to maintain their routines without compromising the effectiveness of the therapy.

Conclusion
Focusing on the reality of ALK positive patients and the impact that this therapy has on the daily lives of our patients, we can contribute to the awareness of this specific pathology.
Development of a phytoplankton-based index of biotic integrity for ecological health assessment in the Yangtze River
Authors: Gao Wenqi , Xiong Fangyuan , Lu Ying , Qu Xiao , Xin Wei , Chen Yushun 
Published: September 2023

Abstract
Background
The application of index of biotic integrity (IBI) to evaluate river health can be an essential method for river ecosystem management. However, these types of methods were developed in small, low-order streams, and are therefore, infrequently applied to large rivers. To that end, phytoplankton communities and environmental variables were monitored in 30 sampling segments of the middle and lower reaches of the Yangtze River, China during the wet (July–August) and dry (November–December) seasons in 2017–2018. We developed a phytoplankton-based index of biotic integrity (P-IBI) and used the index to assess the ecological health of the Yangtze River. Relationships among P-IBI, its component metrics, and environmental factors were analyzed across different seasons.

Results
Results obtained from the P-IBI indicated that the phytoplankton-based ecological health of the Yangtze River was rated as “good” during both seasons, with an overall better condition in the dry season. During the wet season, there were scattered river segments with P-IBI ratings of “fair” or below. Water quality and land use appeared to shape the patterns of P-IBI. In the wet season, P-IBI negatively correlated with total phosphorus, nitrate, total suspended solids, turbidity, conductivity, and dissolved oxygen. In the dry season, P-IBI positively correlated with total nitrogen, ammonium, and nitrite, and negatively correlated with water temperature.

Conclusions
The ecological health of the Yangtze River as reflected by the P-IBI exhibited spatial and temporal variability, with the effect of water quality being greater than that of local land use. This study indicated the importance of considering seasonal effects in detecting large river ecological health. These findings enhanced our understanding of the ecological health and characterized potential benchmarks for management of the Yangtze River. These findings also may be applicable to other large rivers elsewhere.
Hospitalized patients received furosemide undergoing acute kidney injury: the risk and prediction tool
Authors: Guan Chen , Li Chenyu , Xu Lingyu , Che Lin , Wang Yanfei , Yang Chengyu , Zhang Ningxin , Liu Zengying , Zhao Long , Zhou Bin , Man Xiaofei , Luan Hong , Xu Yan 
Published: September 2023

Abstract
Purpose
Furosemide, a frequently prescribed diuretic for managing congestive heart failure and edema, remains a topic of debate regarding its potential risk of inducing acute kidney injury (AKI) in patients. Consequently, this study aims to examine the occurrence of hospital-acquired AKI (HA-AKI) in hospitalized patients who are administered furosemide and to investigate potential risk factors associated with this outcome.

Methods
This study encompassed a cohort of 22374 hospitalized patients who either received furosemide treatment or not from June 1, 2012, to December 31, 2017. Propensity score matching was employed to establish comparability between the two groups regarding covariates. Subsequently, a nomogram was constructed to predict the probability of AKI occurrence among patients who underwent furosemide treatment.

Results
The regression analysis identified the single-day total dose of furosemide as the most significant factor for AKI, followed by ICU administration, estimated glomerular filtration rate, antibiotic, statin, NSAIDs, β-blockers, proton pump inhibitor, chronic kidney disease, and 7 other indicators. Subgroup analysis revealed a synergistic effect of furosemide with surgical operation, previous treatment with β-blockers, ACEI/ARB and antibiotics, leading to an increased risk of AKI when used in combination. Subsequently, a visually represented prognostic nomogram was developed to predict AKI occurrence in furosemide users. The predictive accuracy of the nomogram was assessed through calibration analyses, demonstrating an excellent agreement between the nomogram predictions and the actual likelihood of AKI, with a probability of 77.40%.

Conclusions
Careful consideration of factors such as dosage, concurrent medication use, and renal function of the patient is necessary for clinical practice when using furosemide. Our practical prognostic model for HA-AKI associated with furosemide use can be utilized to assist clinicians in making informed decisions about patient care and treatment.