bluuebunny/crossref_metadata_2025_split huggingface dataset:
Prediction of the development of acute kidney injury following cardiac surgery by machine learning
Authors: Tseng Po-Yu , Chen Yi-Ting , Wang Chuen-Heng , Chiu Kuan-Ming , Peng Yu-Sen , Hsu Shih-Ping , Chen Kang-Lung , Yang Chih-Yu , Lee Oscar Kuang-Sheng 
Published: July 2020

Abstract
Background
Cardiac surgery–associated acute kidney injury (CSA-AKI) is a major complication that results in increased morbidity and mortality after cardiac surgery. Most established prediction models are limited to the analysis of nonlinear relationships and fail to fully consider intraoperative variables, which represent the acute response to surgery. Therefore, this study utilized an artificial intelligence–based machine learning approach thorough perioperative data-driven learning to predict CSA-AKI.

Methods
A total of 671 patients undergoing cardiac surgery from August 2016 to August 2018 were enrolled. AKI following cardiac surgery was defined according to criteria from Kidney Disease: Improving Global Outcomes (KDIGO). The variables used for analysis included demographic characteristics, clinical condition, preoperative biochemistry data, preoperative medication, and intraoperative variables such as time-series hemodynamic changes. The machine learning methods used included logistic regression, support vector machine (SVM), random forest (RF), extreme gradient boosting (XGboost), and ensemble (RF + XGboost). The performance of these models was evaluated using the area under the receiver operating characteristic curve (AUC). We also utilized SHapley Additive exPlanation (SHAP) values to explain the prediction model.

Results
Development of CSA-AKI was noted in 163 patients (24.3%) during the first postoperative week. Regarding the efficacy of the single model that most accurately predicted the outcome, RF exhibited the greatest AUC (0.839, 95% confidence interval [CI] 0.772–0.898), whereas the AUC (0.843, 95% CI 0.778–0.899) of ensemble model (RF + XGboost) was even greater than that of the RF model alone. The top 3 most influential features in the RF importance matrix plot were intraoperative urine output, units of packed red blood cells (pRBCs) transfused during surgery, and preoperative hemoglobin level. The SHAP summary plot was used to illustrate the positive or negative effects of the top 20 features attributed to the RF. We also used the SHAP dependence plot to explain how a single feature affects the output of the RF prediction model.

Conclusions
In this study, machine learning methods were successfully established to predict CSA-AKI, which determines risks following cardiac surgery, enabling the optimization of postoperative treatment strategies to minimize the postoperative complications following cardiac surgeries.
Association between delirium in the intensive care unit and subsequent neuropsychiatric disorders
Authors: Brown Kyla N. , Soo Andrea , Faris Peter , Patten Scott B. , Fiest Kirsten M. , Stelfox Henry T. 
Published: July 2020

AbstractBackgroundPatients in the intensive care unit (ICU) are known to be at increased risk of developing delirium, but the risk of subsequent neuropsychiatric disorders is unclear. We therefore sought to examine the association between the presence of delirium in the ICU and incident neuropsychiatric disorders (including depressive, anxiety, trauma-and-stressor-related, and neurocognitive disorders) post-ICU stay among adult medical-surgical ICU patients.MethodsRetrospective cohort study utilizing clinical and administrative data from both inpatient and outpatient healthcare visits to identify the ICU cohort and diagnostic information 5 years prior to and 1 year post-ICU stay. Patients ≥ 18 years of age admitted to one of 14 medical-surgical ICUs across Alberta, Canada, January 1, 2014–June 30, 2016, and survived to hospital discharge were included. The main outcome of interest was a new diagnosis of any neuropsychiatric disorder 1 year post-ICU stay. The exposure variable was delirium during the ICU stay identified through any positive delirium screen by the Intensive Care Unit Delirium Screening Checklist (ICDSC) during the ICU stay.ResultsOf 16,005 unique patients with at least one ICU admission, 4033 patients were included in the study of which 1792 (44%) experienced delirium during their ICU stay. The overall cumulative incidence of any neuropsychiatric disorder during the subsequent year was 19.7% for ICU patients. After adjusting for hospital characteristics using log-binomial regression, patients with delirium during the ICU stay had a risk ratio (RR) of 1.14 (95% confidence interval [CI] 0.98–1.33) of developing any neuropsychiatric disorder within 1 year post-ICU compared to those who did not experience delirium. Delirium was significantly associated with neurocognitive disorders (RR 1.59, 95% CI 1.08–2.35), but not depressive disorders (RR 1.16, 95% CI 0.92–1.45), anxiety (RR 1.16, 95% CI 0.92–1.47), and trauma-and-stressor-related (RR 0.82, 95% CI 0.53–1.28) disorders.ConclusionsThe diagnosis of new onset of neurocognitive disorders is associated with ICU-acquired delirium. In this study, significant associations were not observed for depressive, anxiety, and trauma-and-stressor-related disorders.
The single recombinant M. tuberculosis protein DPPD provides enhanced performance of skin testing among HIV-infected tuberculosis patients
Authors: Badaro Roberto , Machado Bruna. A. S. , Duthie Malcolm S. , Araujo-Neto C. A. , Pedral-Sampaio D. , Nakatani Maria , Reed Steven G. 
Published: July 2020

AbstractDiagnostic testing for M. tuberculosis infection has advanced with QuantiFERON and GeneXpert, but simple cost-effective alternatives for widespread TB screening has remained elusive and purified protein derivative (PPD)-based tuberculin skin testing (TST) remains the most widely used method. PPD-based tests have reduced performance, however, in BCG vaccinees and in individuals with immune deficiencies. We compared the performance of skin testing with the recombinant DPPD protein against that of a standard PPD-based skin test. Our data indicates similar performance of DPPD and PPD (r2 = 0.7689) among HIV-negative, active TB patients, all of whom presented greater than 10 mm induration following administration. In contrast to results demonstrating that PPD induced indurations greater than 5 mm (i.e., the recommended threshold for positive results in this population) in only half (19 of 38) of the HIV positive TB patients, 89.5% (34 of 38) of these participants developed indurations greater than 5 mm when challenged with DPPD. Importantly, none of the patients that were positive following PPD administration were negative following DPPD administration, indicating markedly improved sensitivity of DPPD among HIV-infected individuals. Our data indicate that DPPD has superior performance in skin testing than the current TST standard.
Motor data-regularized nonnegative matrix factorization for ego-noise suppression
Authors: Schmidt Alexander , Brendel Andreas , Haubner Thomas , Kellermann Walter 
Published: July 2020

AbstractEgo-noise, i.e., the noise a robot causes by its own motions, significantly corrupts the microphone signal and severely impairs the robot’s capability to interact seamlessly with its environment. Therefore, suitable ego-noise suppression techniques are required. For this, it is intuitive to use also motor data collected by proprioceptors mounted to the joints of the robot since it describes the physical state of the robot and provides additional information about the ego-noise sources. In this paper, we use a dictionary-based approach for ego-noise suppression in a semi-supervised manner: first, an ego-noise dictionary is learned and subsequently used to estimate the ego-noise components of a mixture by computing a weighted sum of dictionary entries. The estimation of the weights is very sensitive against other signals beside ego-noise contained in the mixture. For increased robustness, we therefore propose to incorporate knowledge about the physical state of the robot to the estimation of the weights. This is achieved by introducing a motor data-based regularization term to the estimation problem which promotes similar weights for similar physical states. The regularization is derived by representing the motor data as a graph and imprints the intrinsic structure of the motor data space onto the dictionary model. We analyze the proposed method and evaluate its ego-noise suppression performance for a large variety of different movements and demonstrate the superiority of the proposed method compared to an approach without using motor data.
Area double cluster head APTEEN routing protocol-based particle swarm optimization for wireless sensor networks
Authors: Zhang Bowen , Wang Shubin , Wang Minghao 
Published: July 2020

AbstractAPTEEN is a typical routing protocol for wireless sensor networks, but when clustering, cluster heads are randomly selected, which makes it easy to select nodes with low residual energy as cluster heads, thus forming network holes. At the same time, in multi hop transmission, the cluster head near the sink node is overloaded due to forwarding a large amount of data. Aiming at these problems, this paper introduces PSO algorithm and proposes ADCH-EPE-APTEEN routing protocol. In order to make the particle swarm optimization algorithm more suitable for routing protocol, this paper first proposes DCA-PSO based on particle swarm optimization algorithm. DCA-PSO uses the classification adaptive change inertia weight for different states of particles in the optimization process. At the same time, dynamic learning factor is used to improve the influence of particle experience and other particle experience on convergence speed and to improve the optimization accuracy and speed of the algorithm. Secondly, when APTEEN routing protocol is networked, the cluster head is selected by DCA-PSO, in which the residual energy of nodes, the location of nodes, and the energy distribution around nodes are fully taken into consideration. Thirdly, considering the distance between nodes and the sink node, the residual energy and the energy distribution around nodes, a front area is set up in the cluster located in the upper half and the assistant cluster head is selected in the front area through the DCA-PSO algorithm. The simulation results show that the DCA-PSO algorithm can significantly improve the search speed and precision compared with the PSO algorithm. Compared with APTEEN routing protocol, the ADCH-EPE-APTEEN routing protocol can reduce the network energy consumption rate and extend network lifetime by 173%.
Weak and strong convergence Bregman extragradient schemes for solving pseudo-monotone and non-Lipschitz variational inequalities
Authors: Jolaoso Lateef Olakunle , Aphane Maggie 
Published: July 2020

AbstractIn this paper, we introduce Bregman subgradient extragradient methods for solving variational inequalities with a pseudo-monotone operator which are not necessarily Lipschitz continuous. Our algorithms are constructed such that the stepsizes are determined by an Armijo line search technique, which improves the convergence of the algorithms without prior knowledge of any Lipschitz constant. We prove weak and strong convergence results for approximating solutions of the variational inequalities in real reflexive Banach spaces. Finally, we provide some numerical examples to illustrate the performance of our algorithms to related algorithms in the literature.
Existence and uniqueness of solutions for a class of higher-order fractional boundary value problems with the nonlinear term satisfying some inequalities
Authors: Wang Fang , Liu Lishan , Wu Yonghong 
Published: July 2020

AbstractThis paper focuses on a class of hider-order nonlinear fractional boundary value problems. The boundary conditions contain Riemann–Stieltjes integral and nonlocal multipoint boundary conditions. It is worth mentioning that the nonlinear term and the boundary conditions contain fractional derivatives of different orders. Based on the Schauder fixed point theorem, we obtain the existence of solutions under the hypothesis that the nonlinear term satisfies the Carathéodory conditions. We apply the Banach contraction mapping principle to obtain the uniqueness of solutions. Moreover, by using the theory of spectral radius we prove the uniqueness and nonexistence of positive solutions. Finally, we illustrate our main results by some examples.
Risk factors for mortality among drug-resistant tuberculosis patients registered for drug-resistant treatment in Amhara region, Ethiopia: a historical cohort study
Authors: Ketema Daniel Bekele , Alene Muluneh , Assemie Moges Agazhe , Yismaw Leltework , Merid Mehari Woldemariam 
Published: July 2020

Abstract
Background
The emergency of drug resistant tuberculosis is a major public health concern worldwide including Ethiopia. However, little is known about risk factors of mortality among drug resistant tuberculosis patients in the study site. Thus, this study was aimed to estimate the risks factors for mortality among drug resistant tuberculosis patients registered for drug-resistant treatment in Amhara region, Ethiopia.

Methods
An institutional-based retrospective cohort study was carried out among laboratory-confirmed drug-resistant tuberculosis patients (n = 498) who were initiated treatment for drug-resistant tuberculosis between September 1, 2010, and December 31, 2017. The demographic and clinical characteristics of the patients were obtained from the register of patients treated for drug-resistant tuberculosis. The data were entered using EpiData version 4.2 and exported to Stata Version 14.1 for further analysis. Descriptive measures were used to characterize the study participants. Kaplan-Meier was used to estimate the survival time of the patients. Cox proportional hazard model was used to identify risk factors for mortality. Hazard Ratio (HR) with 95% confidence interval was used to report the strength of association between risk factors and mortality.

Results
Death was observed among 14.2% (n = 70) of the 498 patients who met the inclusion criteria. The incidence rate of death was 8.20 (95% CI: 7.62, 20.50) per 1000 Person-months in the course of follow-up. The median age was 29.30 years (IQR:23–41). Age 45 years and above (adjusted hazard ratio (AHR) = 1.28: 95% CI: 1.10, 1.68), smoking cigarette (AHR = 1.39: 95% CI:1.27,3.18), tuberculosis related complication (AHR = 9.31:95% CI:5.11,16.97), anemia (AHR = 3.04:95% CI:1.14, 9.20), HIV/AIDS (AHR = 1.34:95% CI:1.25, 3.35), previous tuberculosis treatment history (AHR = 1.37:95% CI:1.16, 1.86), and diabetes mellitus (AHR = 1.85:95% CI:1.24,5.71) were identified risk factors for mortality.

Conclusions
This study concluded that drug-resistant tuberculosis mortality remains high in the study site. Age 45 years and above, smoking cigarette, tuberculosis related clinical complication, being anemic at baseline, HIV/AID, previous tuberculosis treatment history, and diabetes mellitus were identified risk factors for mortality. Continual support of the integration of TB/HIV service with emphasis and working on identified risk factors may help in reducing drug-resistant tuberculosis mortality.
Treating infections with ionizing radiation: a historical perspective and emerging techniques
Authors: van Dijk B. , Lemans J. V. C. , Hoogendoorn R. M. , Dadachova E. , de Klerk J. M. H. , Vogely H. C. , Weinans H. , Lam M. G. E. H. , van der Wal B. C. H. 
Published: July 2020

AbstractBackgroundWidespread use and misuse of antibiotics have led to a dramatic increase in the emergence of antibiotic resistant bacteria, while the discovery and development of new antibiotics is declining. This has made certain implant-associated infections such as periprosthetic joint infections, where a biofilm is formed, very difficult to treat. Alternative treatment modalities are needed to treat these types of infections in the future. One candidate that has been used extensively in the past, is the use of ionizing radiation. This review aims to provide a historical overview and future perspective of radiation therapy in infectious diseases with a focus on orthopedic infections.MethodsA systematic search strategy was designed to select studies that used radiation as treatment for bacterial or fungal infections. A total of 216 potentially relevant full-text publications were independently reviewed, of which 182 focused on external radiation and 34 on internal radiation. Due to the large number of studies, several topics were chosen. The main advantages, disadvantages, limitations, and implications of radiation treatment for infections were discussed.ResultsIn the pre-antibiotic era, high mortality rates were seen in different infections such as pneumonia, gas gangrene and otitis media. In some cases, external radiation therapy decreased the mortality significantly but long-term follow-up of the patients was often not performed so long term radiation effects, as well as potential increased risk of malignancies could not be investigated. Internal radiation using alpha and beta emitting radionuclides show great promise in treating fungal and bacterial infections when combined with selective targeting through antibodies, thus minimizing possible collateral damage to healthy tissue.ConclusionThe novel prospects of radiation treatment strategies against planktonic and biofilm-related microbial infections seem feasible and are worth investigating further. However, potential risks involving radiation treatment must be considered in each individual patient.
Indirect comparison of efficacy between different antibiotic prophylaxis against the intracranial infection after craniotomy
Authors: Cao Yulong , Wang Bin , Shan Jiao , Gong Zhizhong , Kuang Jiqiu , Gao Yan 
Published: July 2020

Abstract
Background
Many studies had shown that prophylactic use of antibiotics could significantly reduce the intracranial infection (ICI) rate of craniotomy. However, there has been no comparison of these antibiotics.

Methods
An electronic database search was performed, from inception to June 102,020. Randomized controlled trials (RCT) using different intravenous antibiotics (IVA) against the ICIs after craniotomy were considered. The primary outcome was the incidence rates of ICIs. An indirect treatment comparison (ITC) was conducted to compare the protective effect among the diverse antibiotic prophylaxis to prevent ICIs after craniotomy. Risk of potential bias was assessed.

Results
A total of 3214 patients after craniotomy in 11 studies were included, 159 patients experienced postoperative ICI, including 33 patients in the antibacterial group and 126 in the control group. The calculate results of meta-analysis showed that except fusidic acid, preoperative intravenous injection of cephalosporin, clindamycin, vancomycin, and penicillin can significantly reduce the incidence of ICI after craniotomy, and ITC showed there was no statistically significance difference in the rates of post craniotomy ICI between the various antibiotics.

Conclusion
The current evidence shows that low-grade antibacterial drugs can be selected to prevent ICI after craniotomy, but this may be due to the limited number of studies per antibiotic. It still needs more high-quality, large sample RCT to confirm.

Systemic review registration
PROSPERO CRD42019133369.
Macroeconomic, institutional and financial determinants of current account balances: a panel data assessment
Authors: Altayligil Yasin Baris , Çetrez Murat 
Published: July 2020

AbstractThis study aims to find out the fundamental macroeconomic, institutional and financial determinants of current account balances by using panel data analysis method. The analysis is carried out by using the data for the period between 1986 and 2013 of 97 developing and developed countries. We find that the determinants of current account balances can be related to the factors such as fiscal balance, growth, terms of trade, exchange rate, trade openness, stage of economic development, oil dependency, financial market development, macroeconomic stability and institutional quality. A rise in growth rate, real effective exchange rate, fiscal deficit, trade openness, institutional quality, financial market development and stage of development generates larger current account deficits. A rise in terms of trade, inflation rate (representing macroeconomic stability), crude oil export reduces the current account deficits. For industrial countries, macroeconomic stability and growth also have the opposite effect on current account balances compared with other groups. The legal system and property rights, voice and accountability, political stability and absence of violence, political risks are identified as the institutional determinants of current account balances.
Design of an interface for teaching cardiovascular physiology to anesthesia clinicians with a patient simulator connected to a minimally invasive cardiac output monitor (LiDCO rapid®)
Authors: Chaló Daniela , Marques Joana , Mendes Henrique , Sancho Consuelo 
Published: July 2020

AbstractCardiovascular physiology can be simulated in patient simulators but is limited to the simulator monitor curves and parameters, missing some important data that today is known as essential to fluid management and therapeutic decision in critical ill and high-risk surgical patients. Our main objective was to project and implement a unidirectional communication channel between a pre-existing patient simulator and a minimally invasive cardiac output monitor (LiDCO rapid®); a monitor that connects to real patients and interprets the arterial wave. To connect the patient simulator to the hemodynamic monitor, firstly, we had to assess both systems and design a communication channel between them. LiDCO monitor accepts as an input an analog voltage varying between 0 V and 5 V and that every volt is directly proportional to a blood pressure (mmHg) value ranging from 0 mmHg (0 V) to 500 mmHg (5 V). A Raspberry Pi 0 (Rpi0) with a WIFI chip integrated was needed and added to a digital analogue converter connected to the board. We designed a system that allowed us to collect, interpret and modify data, and feed it to the LiDCO rapid® monitor. We had developed a Python® script with three independent threads and a circular buffer to handle the data transmission between both systems. The LiDCO hemodynamic monitor successfully received data sent from our setup like a real patient arterial wave pulse and interpreted it to estimate several hemodynamic parameters, as cardiac output, stroke volume, systemic vascular resistance, pulse pressure variation, and stroke volume variation. The connection between the patient simulator and the LiDCO monitor is being used to create arterial curves and other hemodynamic parameters for clinical scenarios where residents and anesthesiologists can simulate a variety of unstable hemodynamic conditions, preparing them to face similar situations with real patients in a safe environment and with their own monitors.