bluuebunny/crossref_metadata_2025_split huggingface dataset:
Central Line Access is Predictive of Diagnostic Blood Loss and Transfusion in the Surgical Intensive Care Unit
Authors: Adkins Brian D , Deanda Abe , Trieu Judy A , Polineni Srinivas , Okorodudu Anthony O , Yates Sean G 
Published: November 2021

Abstract
Background: Diagnostic laboratory testing (DLT) is a source of blood loss in critically ill patients. Approximately half of patients admitted to the intensive care unit (ICU) present with anemia, with the remainder developing a multifactorial anemia with etiologies including central venous catheter (CVC) placement. Consequently, about a third of ICU patients require red blood cell (RBC) transfusion, a practice associated with poorer clinical outcomes. Our objectives were to characterize DLT blood loss in the surgical intensive care unit (SICU), and its relationship with anemia, RBC transfusion, and CVC placement.Methods: An observational study was performed by retrospective chart review of patients admitted to a SICU over 1-year. The number of DLT blood draws, average volume of blood drawn, and estimated discard volume were recorded along with clinical and laboratory findings. Results: A cohort of 292 patients (mean age 62.2 years, male to female ratio 1.5) underwent 299 hospitalizations with an average daily DLT blood loss of 14.3 mL (229.5 mL per admission). Among admissions, 51.2% presented with anemia and 95.3% were anemic at discharge, with 32% of patients receiving an RBC transfusion. Patients with greater DLT-associated blood loss had lower discharge hemoglobin (p=<0.001). Admissions requiring CVC (49.8%), demonstrated a significantly greater number of DLT blood draws, increased DLT-associated blood loss, higher rates of RBC transfusion, and an increased length of stay.Conclusions: Findings from this study suggest that DLT blood loss contributes to anemia in the SICU and the presence and duration of CVC leads to increased testing, blood loss, anemia, and is predictive of RBC transfusion.
Development of a Machine Learning Model for the Prediction of the Real Time Mortality in Patients in the Intensive Care Unit
Authors: Yang Jaeyoung , Lim Hong-Gook , Park Wonhyeong , Kim Dongseok , Yoon Jin Sun , Lee Sang-Min , Kim Kwangsoo 
Published: November 2021

Abstract
BackgroundPrediction of mortality in intensive care units is very important. Thus, various mortality prediction models have been developed for this purpose. However, they do not accurately reflect the changing condition of the patient in real time. The aim of this study was to develop and evaluate a machine learning model that predicts short-term mortality in the intensive care unit using four easy-to-collect vital signs.MethodsTwo independent retrospective observational cohorts were included in this study. The primary training cohort included the data of 1968 patients admitted to the intensive care unit at the Veterans Health Service Medical Center, Seoul, South Korea, from January 2018 to March 2019. The external validation cohort comprised the records of 409 patients admitted to the medical intensive care unit at Seoul National University Hospital, Seoul, South Korea, from January 2019 to December 2019. Datasets of four vital signs (heart rate, systolic blood pressure, diastolic blood pressure, and peripheral capillary oxygen saturation [SpO2]) measured every hour for 10 h were used for the development of the machine learning model. The performances of mortality prediction models generated using five machine learning algorithms, Random Forest (RF), XGboost, perceptron, convolutional neural network, and Long Short-Term Memory, were calculated and compared using area under the receiver operating characteristic curve (AUROC) values and an external validation dataset.ResultsThe machine learning model generated using the RF algorithm showed the best performance. Its AUROC was 0.922, which is much better than the 0.8408 of the Acute Physiology and Chronic Health Evaluation II. Thus, to investigate the importance of variables that influence the performance of the machine learning model, machine learning models were generated for each observation time or vital sign using the RF algorithm. The machine learning model developed using SpO2 showed the best performance (AUROC, 0.89). ConclusionsThe mortality prediction model developed in this study using data from only four types of commonly recorded vital signs is simpler than any existing mortality prediction model. This simple yet powerful new mortality prediction model could be useful for early detection of probable mortality and appropriate medical intervention, especially in rapidly deteriorating patients.
Models To Predict The Short-Term Survival of Acute-On-Chronic Liver Failure Patients Following Liver Transplantation
Authors: Yang Min , Peng Bo , Zhuang Quan , Li Junhui , Liu Hong , Cheng Ke , Ming Yingzi 
Published: November 2021

Abstract
Background: Acute-on-chronic liver failure (ACLF) is featured with rapid deterioration of chronic liver disease and poor short-term prognosis. Liver transplantation (LT) is recognized as the curative option for ACLF. However, there is no standard in the prediction of the short-term survival among ACLF patients following LT.Method: Preoperative data of 132 ACLF patients receiving LT at our center were investigated retrospectively. Cox regression was performed to determine the risk factors for short-term survival among ACLF patients following LT. Five conventional score systems (the MELD score, ABIC, CLIF-C OFs, CLIF-SOFAs and CLIF-C ACLFs) in forecasting short-term survival were estimated through the receiver operating characteristic (ROC). Four machine-learning (ML) models, including support vector machine (SVM), logistic regression (LR), multi-layer perceptron (MLP) and random forest (RF), were also established for short-term survival prediction.Results: Cox regression analysis demonstrated that creatinine (Cr) and international normalized ratio (INR) were the two independent predictors for short-term survival among ACLF patients following LT. The ROC curves showed that the area under the curve (AUC) ML models was much larger than that of conventional models in predicting short-term survival. Among conventional models the model for end stage liver disease (MELD) score had the highest AUC (0.704), while among ML models the RF model yielded the largest AUC (0.940). Conclusion:Compared with the traditional methods, the ML models showed good performance in the prediction of short-term prognosis among ACLF patients following LT and the RF model perform the best. It is promising to optimize organ allocation and promote transplant survival based on the prediction of ML models.
A Unilateral Robotic Knee Exoskeleton to Assess the Role of Natural Gait Assistance in Hemiparetic Patients
Authors: Lora-Millan Julio Salvador , Sanchez-Cuesta Francisco José , Romero Juan Pablo , Moreno Juan C. , Rocon Eduardo 
Published: November 2021

Abstract
Background: Hemiparetic gait is characterized by strong asymmetries that could severely affect the quality of life of stroke survivors. This asymmetry is due to motor deficits in the paretic leg and the resulting compensations in the non-paretic limb. In this study, we aim to evaluate the effect of actively promoting gait symmetry in hemiparetic patients by assessing the behavior of both paretic and non-paretic lower limbs. This paper introduces the design and validation of the REFLEX prototype, a unilateral active Knee-Ankle-Foot Orthosis able to naturally assist the paretic limb of hemiparetic patients during gait.Methods: REFLEX uses an Adaptive Frequency Oscillator to estimate the continuous gait phase of the non-paretic limb. Based on this estimation, the device synchronically assists the paretic leg following two different control strategies: (1) Replicating the movement of the sound leg or (2) Inducing a healthy gait pattern on the paretic leg. Technical validation of the system was implemented on three healthy subjects, while the effect of the generated assistance was assessed in three stroke patients. Results: Preliminary results proved the feasibility of the REFLEX prototype to assist gait by reinforcing symmetry. They also pointed out that the assistance of the paretic leg resulted in a decrease of the compensatory strategies developed by the non-paretic limb to achieve a functional gait. Notably, better results were attained when the assistance was provided according to a standard healthy pattern, which initially might suppose a lower symmetry but enabled a healthier evolution of the motion of the non-paretic limb.Conclusions: This work presents the preliminary validation of the REFLEX prototype, a unilateral knee exoskeleton for gait assistance in hemiparetic patients. The experimental results indicate that assisting the paretic leg of hemiparetic patients based on the movement of their non-paretic one is a valuable strategy for reducing the compensatory mechanisms developed by their sound limb.
p53 Missense Mutation is Associated with Immune Cell PD-L1 Expression in Triple-negative Breast Cancer
Authors: Wang Bin , Wang Kun , Yu Jian , Liu Long , Liang Ke , Xing Ai-yan 
Published: November 2021

Abstract
BackgroundImmunotherapy is an important treatment for triple-negative breast cancer (TNBC). The programmed death ligand 1 (PD-L1) is a pivotal biomarker in TNBC, and its expression is closely related to immunotherapy response. Therefore, the association of p53 expression and mutation and PD-L1 expression was explored. Methods and Results PD-L1 expression and p53 mutation and expression were evaluated by immunohistochemistry. PD-L1 expression and expression levels between p53 mutation (missense and nonsense) and wild type; no-expression/loss vs. expression; and missense vs. nonsense groups were compared. PD-L1 expression was found mainly in tumor-infiltrating immune cells (ICs) in TNBC. Positive PD-L1 expression was associated with a high Ki67 index. There was a significant association between p53 mutation, especially missense mutation and higher histological grade, and PD-L1 expression in ICs. Compared with p53 nonsense mutation, cases with missense mutations tended to display more PD-L1 positive ICs. However, PD-L1 expression in ICs was not significantly different between the p53 mutation and expression groups. Conclusionsp53 missense mutation is partially involved in the regulatory expression of PD-L1. Both p53 missense mutation and PD-L1 expression may be potential targets for improving immunotherapy response in TNBC.
Establishment of a 5 DNA Methylation Site Prognostic Signature Associated with N6-Methyladenosine in Lung Adenocarcinoma
Authors: Yuan Liqiang , Jiang Wei , Xu Zhanyu , Deng Kung , Sun Yu , Qin Junqi , Huang Liuliu , Zheng Tiaozhan , Zheng Zhiwen , Qin Fanglu , Li Shikang 
Published: November 2021

Abstract
Background: There is a high incidence of lung adenocarcinoma (LUAD). Even with surgery, targeted therapy and immunotherapy, the survival rate of LUAD patients is still low. N6-methyladenosine (m6A) and DNA methylation markers can help with the diagnosis and treatment of LUAD patients. Therefore, it is necessary to identify a novel m6A-related DNA methylation sites signature to predict the survival of patients with LUAD. Methods: In this study, we screened 15 m6A-related genes and their 217 methylation sites. RNA sequencing data of 15 genes and the clinicopathological parameters of TCGA-LUAD were obtained from the TCGA database (http://cancergenome.nih.gov/). The LUAD-DNA CpG site information was obtained from the Illumina Human Methylation 450 BeadChip (Illumina, San Diego, CA, United States). The methylation sites related to prognosis were screened using univariate COX analysis, and the independent predictors of LUAD patients were identified using multivariate COX analysis of least absolute shrinkage and selection operator (LASSO) Cox regression analysis. Finally, a model with 5 methylation sites as the main body to predict the prognosis of OS in patients with LUAD was obtained. According to the risk grouping of the prediction model, Kaplan-Meier curve and the receiver operating characteristic (ROC) curve were performed in the test and training sets to assess the predicted capacity of the model. In addition, a nomogram constructed by combining the risk score of methylation group and other related clinicopathological factors to verify the reliability of our model.Results: We constructed a m6A-related 5-DNA methylation site model to predict OS in LUAD patients. According to the results of the Kaplan-Meier curve, both the test set and the training set, the high-risk group showed a worse prognosis. The AUCs of the 5 DNA methylation signature at 1, 5 and 10 years in test datasets were 0.730, 0.649 and 0.726, respectively, and 0.679, 0.656 and 0.732 in training datasets. Finally, we constructed a nomogram to further verify the reliability of the model.Conclusion: In this study, we analyzed the methylation sites of m6A-related genes and established a m6A-related 5-DNA methylation site model to predict OS in LUAD patients.
Spinal obstruction-related versus craniocervical junction related syringomyelia: a comparative study of spinal cord injury
Authors: chenghua yuan , guan jian , du yueqi , fang zeyu , wang xinyu , yao qingyu , zhang can , jia shanhang , liu zhenlei , wang kai , duan wanru , wang xingwen , wang zuowei , wu hao , chen zan , jian fengzeng 
Published: November 2021

Abstract
Background

No prior reports have focused on spinal cord injury (SCI) characteristics or inflammation after destruction of the blood-spinal cord barrier by syringomyelia. To compare the difference of syringomyelia-related central SCI between craniocervical junction (CCJ) and post-traumatic syringomyelia (PTS) before and after decompression.
Methods

Between 2015 and 2019, 106 CCJ, 26 CCJ revision and 15 PTS patients (mean history of symptoms 71.5 ± 94.3, 88.9 ± 85.5 and 32.3 ± 48.9 months). The symptom courses were analysed with the ASIA, Klekamp and Samii scoring systems and Kaplan-Meier statistics for neurological changes. The mean follow-up was 20.7 ± 6.2, 21.7 ± 8.8 and 34.8 ± 19.4 months.
Results

Compared with the other group, the interval time after PTS was longer, but the natural history of syringomyelia was shorter (P=0.0004, 0.0173, respectively). The initial symptoms were usually paraesthesia (P=0.258), and the symptoms were mainly hypoesthesia (P=0.006), abnormal muscle strength (P=0.004), gait (P<0.0001) and abnormal urination (P<0.0001). SCI associated with PTS was more severe than that CCJ related (P=0.003). The cavities in the PTS group were primarily located at the thoracolumbar level, which was different from those in the cervical-thoracic segment at the CCJ. The rate of syrinx/cord was more than 75% (P=0.009), and the intradural adhesions tended to be more severe (P<0.0001). However, there were no significant differences in peripheral blood inflammation markers (PBIM) or long-term clinical efficacy except for the RBC (P=0.042).
Conclusion

The natural history of PTS tends to progress faster and is more severe than CCJ related. PBIM had no distinguishing effect on the difference in inflammation of syringomyelia except for the RBC. The predictive value of NLR for syringomyelia-related inflammation except in the acute phase was negative.
Two New Teleomorphic Talaromyces Species Discovered From The Estuary Soil In China
Authors: Han Pei-Jie , Sun Jian-Qiu , Wang Long 
Published: November 2021

Abstract
Two new species producing ascospores of Talaromyces sect.Talaromyces are proposed, namely, T. haitouensi (ex-type AS3.160101 T) and T. zhenhaiensis (ex-type AS3.16102 T). Morphologically, T. haitouensis is featured by moderate growth, green-yellow gymnothecia, orange-brown mycelium, and echinulate ellipsoidal ascospores. T. zhenhaiensis is characterized by fast growth, absent sporulation, cream yellow to naphthalene yellow gymnothecia and mycelium, smooth-walled ellipsoidal ascospores with one equatorial ridge. The proposal of the two new taxa is well supported by individual phylogenetic analyses based on individual sequences of BenA, CaM, Rpb2 and ITS1-5.8S-ITS2, and the concatenated BenA-CaM-Rpb2 sequence.
The viability of utilising phone-based text messages in data capture and reporting of morbidities due to Lymphatic Filariasis by Community Health Workers: A qualitative study in Kilwa district, Tanzania
Authors: Kalinga Akili , Munga Michael , Ngenya Abdallah , John Winfrida , Kisoka William , Oriyo Ndekya , Mutalemwa Prince , Mandara Wilfred , Masagati Leonard , Ogondiek John , Korir Patricia , Klarmann-Schulz Ute , Horn Sacha , Kroidl Inge , Debrah Alex , Hoerauf Achim , Mwingira Upendo 
Published: November 2021

Abstract
Background

Globally, there is recognition of the value of using mobile phones among health providers in improving health systems performance. However, in many Low- and Middle-income countries where there is shortage of health providers, Community Health Workers have assumed some responsibilities especially relating to identifying and reporting on health problems within their communities. Despite the known benefits of using mobile phone technology to deliver health services, there is limited information on the extent to which Community Health Workers are able to effectively use the technology in data collection and reporting. The aim of this study was to determine the feasibility of utilizing phone-based text messages on Lymphatic Filariasis morbidity surveillance by Community Health Workers
Methods

This was a cross sectional study whose data was collected through key informant interviews and focused group discussions among community health workers, health providers and staff of neglected tropical diseases control program. Collected transcripts were analysed through Thematic content analysis as it allowed for the identification of data codes through inductive reasoning.
Results

The use of mobile phone-based text messages in data collection and reporting lymphatic filariasis morbidity cases by Community Health Workers was perceived by study participants to be a relevant tool and feasible due to the ease of use of the technology. The tool was reported by end-users to significantly increase their performance and efficiency was gained in terms of reduced paper work, increased the number of patients accessing health care services and the ability to report in real-time. All respondents were confident that Community Health Workers were the right persons to interact with communities in tracking and reporting morbidity cases using mobile technology.
Conclusion

Mobile phone-based text messages have proven to be effective in routine workflows such as, data collection and reporting on Lymphatic Filariasis morbidity cases, patient to provider communication, decision making and supportive supervision. Mobile phones have also improved efficiency and general performance of end users in terms of increased number of cases identified and efficiency gained in terms of reduced paper work and the ability to collect and report in real-time.
Patient Satisfaction with Healthcare at a Tertiary Hospital in Northern Malawi: Results from a Triangulated Cross-sectional Survey
Authors: Sinyiza Frank Watson , Kaseka Paul Uchizi , Chisale Master Rodgers , Chimbatata Chikondi Sharon , Mbakaya Balwani Chingatichifwe , Kamudumuli Pocha Samuel , Wu Tsung-Shu Joseph , Kayira Alfred Bornwell 
Published: November 2021

Abstract
BackgroundIn 2016 the Malawi government embarked on several interrelated health sector reforms aimed at improving the quality of health services at all levels of care and attain Universal Health Coverage by 2030. Patient satisfaction with services is an important proxy measure of quality. We assessed patient satisfaction at a tertiary hospital in Northern Malawi to understand the current state in the country. MethodsWe conducted exit interviews with patients aged18 years and above using a 28 statement interviewer administered questionnaire. Patients were asked to express their level of agreement to the statements on a five-point Likert scale – strongly disagree to strongly agree, corresponding to scores of 1 to 5. Overall patient satisfaction was calculated by summing up the scores and diving the sum by the number of statements. Scores >3 constituted satisfaction while scores ≤3 constituted dissatisfaction. Patient self-rated satisfaction was determined from a single statement that asked patients to rate their satisfaction with services on a five-point Likert scale. We also solicited inputs from patients on aspects of hospital care that needed improvement. Responses were reviewed and grouped into themes. Recurring themes are presented according to frequencies.ResultsOverall patient satisfaction was 8.4% (95% CI: 5.2% - 12.9%). Patient self-rated satisfaction was 8.9% (95% CI: 5.5% - 13.4%). Patients raised six major issues that dampened their healthcare seeking experience including health workers reporting late to work, doctors not listening to patients concerns and neither examining them properly nor explaining the diagnosis, shortage of medicines, diagnostics and medical equipment, unprofessional conduct of health workers, poor sanitation and cleanliness, and health workers behaviour of favouring or priotising their relatives and friends over other patients.ConclusionWe found very low levels of patient satisfaction, suggesting that quality of services in the public health sector is still low. It is therefore critical to accelerate and innovate the Ministry of Health’s quality improvement initiatives to attain Malawi’s health goals.