Enhancing liver fibrosis diagnosis and treatment assessment: a novel biomechanical markers-based machine learning approach.

Accurate diagnosis and treatment assessment of liver fibrosis face significant challenges, including inherent limitations in current techniques like sampling errors and inter-observer variability. Addressing this, our study introduces a novel machine learning (ML) framework, which integrates light gradient boosting machine and multivariate imputation by chained equations to enhance liver status assessment using biomechanical markers. Building upon our previously established multiscale mechanical characteristics in fibrotic and treated livers, this framework employs Gaussian Bayesian optimization for post-imputation, significantly improving classification performance. Our findings indicate a marked increase in the precision of liver fibrosis diagnosis and provide a novel, quantitative approach for assessing fibrosis treatment. This innovative combination of multiscale biomechanical markers with advanced ML algorithms represents a transformative step in liver disease diagnostics and treatment evaluation, with potential implications for other areas in medical diagnostics.

Recommendations and guidelines for endoscope reprocessing: Current position statement of digestive endoscopic society of Taiwan.

Reprocessing of gastrointestinal (GI) endoscopes and accessories is an essential part of patient safety and quality control in GI endoscopy centers. However, current endoscopic reprocessing guidelines or procedures are not adequate to ensure patient-safe endoscopy. Approximately 5.4 % of the clinically used duodenoscopes remain contaminated with high-concern microorganisms. Thus, the Digestive Endoscopy Society of Taiwan (DEST) sets standards for the reprocessing of GI endoscopes and accessories in endoscopy centers. DEST organized a task force working group using the guideline-revision process. These guidelines contain principles and instructions of step-by-step for endoscope reprocessing. The updated guidelines were established after a thorough review of the existing global and local guidelines, systematic reviews, and health technology assessments of clinical effectiveness. This guideline aims to provide detailed recommendations for endoscope reprocessing to ensure adequate quality control in endoscopy centers.

Assessment of visual function in blind mice and monkeys with subretinally implanted nanowire arrays as artificial photoreceptors.

Retinal prostheses could restore image-forming vision in conditions of photoreceptor degeneration. However, contrast sensitivity and visual acuity are often insufficient. Here we report the performance, in mice and monkeys with induced photoreceptor degeneration, of subretinally implanted gold-nanoparticle-coated titania nanowire arrays providing a spatial resolution of 77.5 µm and a temporal resolution of 3.92 Hz in ex vivo retinas (as determined by patch-clamp recording of retinal ganglion cells). In blind mice, the arrays allowed for the detection of drifting gratings and flashing objects at light-intensity thresholds of 15.70-18.09 µW mm-2, and offered visual acuities of 0.3-0.4 cycles per degree, as determined by recordings of visually evoked potentials and optomotor-response tests. In monkeys, the arrays were stable for 54 weeks, allowed for the detection of a 10-µW mm-2 beam of light (0.5° in beam angle) in visually guided saccade experiments, and induced plastic changes in the primary visual cortex, as indicated by long-term in vivo calcium imaging. Nanomaterials as artificial photoreceptors may ameliorate visual deficits in patients with photoreceptor degeneration.

Measurement properties of the patient global assessment numerical rating scale in moderate-to-severe psoriasis.

BACKGROUND: Patient global assessment (PtGA) has been recommended as one of the core domains in psoriasis clinical trials. Among multiple versions of PtGA, the single-question, 11-point PtGA numeric rating scale (NRS) remains to be validated in patients with plaque psoriasis. OBJECTIVES: To evaluate the psychometric characteristics of an 11-point PtGA NRS for disease severity in patients with moderate-to-severe plaque psoriasis. METHODS: Data were analysed from 759 patients with moderate-to-severe psoriasis in the Shanghai Psoriasis Effectiveness Evaluation CoHort (SPEECH), a prospective, multicentre and observational registry assessing the comparative effectiveness and safety of biologics (adalimumab, ustekinumab, secukinumab or ixekizumab), conventional systemic therapies (acitretin or methotrexate) and phototherapy. RESULTS: The test-retest reliability of the PtGA NRS showed good agreement (intraclass correlation coefficient range 0.79-0.83). No floor or ceiling effects of PtGA NRS were observed. The PtGA NRS was significantly correlated with the Psoriasis Area and Severity Index (PASI), static Physician Global Assessment (sPGA), body surface area, Dermatology Quality of Life Index (DLQI) and Hospital Anxiety and Depression Scale. Relatively large correlations of PtGA NRS with PASI and the DLQI 'symptoms and feelings' domain (all correlations ≥ 0.4 except at baseline) supported convergent validity. The presence of psoriatic arthritis or joint symptoms had no significant association with the PtGA NRS. In multivariate regression analyses, the PtGA NRS at baseline was predicted by age, lesion extent, lesion intensity, patients' symptoms and feelings, and impact on work or school. The PtGA NRS displayed known-groups validity with the PASI, sPGA and DLQI score bands. The PtGA NRS was responsive to change in PASI and DLQI after treatment. Anchor- and distribution-based approaches supported -3 as the minimal important difference for PtGA NRS. An absolute PtGA NRS ≤ 2 during follow-up was concordant with the state of minimal disease activity based on a 90% reduction in PASI (PASI 90) or PASI 90 plus a DLQI of 0/1. Sensitivity analysis using subgroup comparison and multiple imputation model yielded consistent conclusions. CONCLUSIONS: The PtGA NRS showed good reliability, validity and responsiveness in patients with psoriasis, and was feasible in clinical trials and daily practice.

Rethinking the complexity and uncertainty of spatial networks applied to forest ecology.

Characterizing tree spatial patterns and interactions are helpful to reveal underlying processes assembling forest communities. Spatial networks, despite their complexity, are powerful to examine spatial interactions at an individual level using well-defined patterns. However, complex forestation networks introduce uncertainties. Validation methods are needed to assess whether network-based metrics can identify different processes. Here, we constructed three types of networks, which reflect various aspects of tree competition. Based on five spatial null models and 199 Monte-Carlo simulations, we were able to select network-based metrics that exhibited well performance in distinguishing different processes. This technique was then applied to a tropical forest dataset in Costa Rica. We found that the average node degree and the clustering coefficient are good metrics like the paired correlation function. In addition, the network approach can identify fine-scale spatial variations of tree competition and its underlying causes. Our analyzes also indicate that a bit of caution is needed when defining the network structure as well as designing network-based metrics. We suggested that validation techniques using corresponding spatial null models are critically important to reduce the negative effects caused by uncertainties of the network.

Epidemiological Variations in the Global Burden of Psoriasis, an Analysis With Trends From 1990 to 2017.

Background: Although there have been many epidemiological studies, research focusing on psoriasis' health burden on a global scale is still lacking. Trends and variations in the global health burden of psoriasis are evaluated by time, age, gender, geographical location, and socioeconomic status, using disability-adjusted life years (DALYs) from the Global Burden of Disease Study. Methods: The health burden of psoriasis was evaluated by DALYs, which combined years lost to disability (a morbidity component) with years of life lost (a mortality component). The global and national DALYs number, crude DALYs rate, and age-standardized DALYs rate were obtained from the GBD 2017 study database. The corresponding human development index (HDI) was collected from the United Nations Development Programme. Results: From 1990 to 2017, the DALYs number and crude DALYs rate due to psoriasis increased by 73 and 22%, respectively. In comparison, the age-standardized DALYs rate showed a slight increase. Patients in the age range of 65-69 years bear a more significant psoriasis burden. Both males and females showed an increasing trend in burden caused by psoriasis over the past 27 years, with females bearing a more significant psoriasis burden than males. The health burden of psoriasis was substantially unequal in geography with a Gini coefficient of 0.27. The concentration indexes indicated a socioeconomic associated inequality in psoriasis burden with values of 0.22, accounting for 48.64% variance across countries (R2 = 0.4864, p < 0.001). Between-nation inequality in the distribution of psoriasis burden continued to decline throughout the past 27 years. Gini coefficients of psoriasis burden decreased from 0.280 in 1990 to 0.265 in 2017. The concentration indexes indicated the same trend with 0.236 in the 1990s and 0.223 in 2017. Conclusions: Global health progress in psoriasis together with inequality in the past few decades. Although the inequality of psoriasis burden has shown some improvement during the past 27 years, disparities still exist in age, gender, geographical location, as well as socioeconomic status. The findings of this study highlight the global importance of psoriasis and is important in policy planning for psoriasis services on a global scale.

Low initial trough concentration of rituximab is associated with unsatisfactory response of first-line R-CHOP treatment in patients with follicular lymphoma with grade 1/2.

For follicular lymphoma (FL) with grade 1/2, the complete response (CR) rate of the first-line R-CHOP treatment was significantly low. In this study, we assessed the rationality of the administration of rituximab for FL patients with grade 1/2 based on concentration-response relationship analyses. Thus, we conducted a prospective pharmacokinetic (PK) study in 68 FL patients with grades 1-3 treated with R-CHOP at 21-day intervals. Plasma rituximab concentrations were quantified using ELISA and the population PK modeling was established with Phoenix® NLMETM. The first cycle trough concentration (C1-trough) of rituximab was a significant independent risk factor for achieving CR in matched-pair logistic regression analysis, rather than the concentrations in later cycles; the recommendatory minimum optimal C1-trough was 13.60 µg/mL. Patients with grade 1/2 had significantly lower C1-trough compared with grade 3 (12.21 µg/mL vs. 23.45 µg/mL, P < 0.001), only 30% patients with grade 1/2 could reach 13.60 µg/mL, compared with 91.67% in patients with grade 3, which was in accord with its unsatisfactory CR rates (43.33% vs. 76.32%). The stage indicating the tumor burden (the target) was a crucial influence factor for C1-trough, accounting for 40.70% of its variability, 70% patients with grade 1/2 were stage IV in this study, since the systemic therapy only started at the disseminated disease stage. The initial dose of 1800 mg was recommended by Monte Carlo simulation for patients with grade 1/2. In summary, low C1-trough accounted for low-grade FL's unsatisfactory CR rate, designing the first dosage of rituximab should be a very important component of individualized therapy for FL.

Guaranteed cost control of hybrid-triggered networked systems with stochastic cyber-attacks.

This paper is concerned with guaranteed cost control for a hybrid-triggered networked system subject to stochastic cyber-attacks. First, a hybrid-triggered mechanism including time-triggered mechanism and event-triggered mechanism is proposed to mitigate the pressure of network transmission, in which the switching between two mechanisms satisfies Bernoulli distribution. Second, the closed-loop system subject to the hybrid communication scheme and stochastic cyber-attacks is modelled as a stochastic system with an interval time-varying delay. Then, based on the Lyapunov-Krasovskii functional approach, two theorems are presented for guaranteeing the mean-square stability of the studied system. Finally, the effectiveness of the proposed method is demonstrated through a numerical example.

Identification of Pancreatic Injury in Patients with Elevated Amylase or Lipase Level Using a Decision Tree Classifier: A Cross-Sectional Retrospective Analysis in a Level I Trauma Center.

BACKGROUND: In trauma patients, pancreatic injury is rare; however, if undiagnosed, it is associated with high morbidity and mortality rates. Few predictive models are available for the identification of pancreatic injury in trauma patients with elevated serum pancreatic enzymes. In this study, we aimed to construct a model for predicting pancreatic injury using a decision tree (DT) algorithm, along with data obtained from a population-based trauma registry in a Level I trauma center. METHODS: A total of 991 patients with elevated serum levels of amylase (>137 U/L) or lipase (>51 U/L), including 46 patients with pancreatic injury and 865 without pancreatic injury between January 2009 and December 2016, were allocated in a ratio of 7:3 to training (n = 642) or test (n = 269) sets. Using the data on patient and injury characteristics as well as laboratory data, the DT algorithm with Classification and Regression Tree (CART) analysis was performed based on the Gini impurity index, using the rpart function in the rpart package in R. RESULTS: Among the trauma patients with elevated amylase or lipase levels, three groups of patients were identified as having a high risk of pancreatic injury, using the DT model. These included (1) 69% of the patients with lipase level ≥306 U/L; (2) 79% of the patients with lipase level between 154 U/L and 305 U/L and shock index (SI) ≥ 0.72; and (3) 80% of the patients with lipase level <154 U/L with abdomen injury, glucose level <158 mg/dL, amylase level <90 U/L, and neutrophil percentage ≥76%; they had all sustained pancreatic injury. With all variables in the model, the DT achieved an accuracy of 97.9% (sensitivity of 91.4% and specificity of 98.3%) for the training set. In the test set, the DT achieved an accuracy of 93.3%, sensitivity of 72.7%, and specificity of 94.2%. CONCLUSIONS: We established a DT model using lipase, SI, and additional conditions (injury to the abdomen, glucose level <158 mg/dL, amylase level <90 U/L, and neutrophils ≥76%) as important nodes to predict three groups of patients with a high risk of pancreatic injury. The proposed decision-making algorithm may help in identifying pancreatic injury among trauma patients with elevated serum amylase or lipase levels.

Event-Triggered Asynchronous Guaranteed Cost Control for Markov Jump Discrete-Time Neural Networks With Distributed Delay and Channel Fading.

This paper is concerned with the guaranteed cost control problem for a class of Markov jump discrete-time neural networks (NNs) with event-triggered mechanism, asynchronous jumping, and fading channels. The Markov jump NNs are introduced to be close to reality, where the modes of the NNs and guaranteed cost controller are determined by two mutually independent Markov chains. The asynchronous phenomenon is considered, which increases the difficulty of designing required mode-dependent controller. The event-triggered mechanism is designed by comparing the relative measurement error with the last triggered state at the process of data transmission, which is used to eliminate dispensable transmission and reduce the networked energy consumption. In addition, the signal fading is considered for the effect of signal reflection and shadow in wireless networks, which is modeled by the novel Rice fading models. Some novel sufficient conditions are obtained to guarantee that the closed-loop system reaches a specified cost value under the designed jumping state feedback control law in terms of linear matrix inequalities. Finally, some simulation results are provided to illustrate the effectiveness of the proposed method.

Epidemiology of Bone Fracture in Female Trauma Patients Based on Risks of Osteoporosis Assessed using the Osteoporosis Self-Assessment Tool for Asians Score.

Background: Osteoporotic fractures are defined as low-impact fractures resulting from low-level trauma. However, the exclusion of high-level trauma fractures may result in underestimation of the contribution of osteoporosis to fractures. In this study, we aimed to investigate the fracture patterns of female trauma patients with various risks of osteoporosis based on the Osteoporosis Self-Assessment Tool for Asians (OSTA) score. Methods: According to the data retrieved from the Trauma Registry System of a Level I trauma center between 1 January 2009 and 31 December 2015, a total of 6707 patients aged ≥40 years and hospitalized for the treatment of traumatic bone fracture were categorized as high-risk (OSTA < -4, n = 1585), medium-risk (-1 ≥ OSTA ≥ -4, n = 1985), and low-risk (OSTA > -1, n = 3137) patients. Two-sided Pearson's, chi-squared, or Fisher's exact tests were used to compare categorical data. Unpaired Student's t-test and Mann-Whitney U-test were used to analyze normally and non-normally distributed continuous data, respectively. Propensity-score matching in a 1:1 ratio was performed with injury mechanisms as adjusted variables to evaluate the effects of OSTA-related grouping on the fracture patterns. Results: High- and medium-risk patients were significantly older, had higher incidences of comorbidity, and were more frequently injured from a fall and bicycle accident than low-risk patients did. Compared to low-risk patients, high- and medium-risk patients had a higher injury severity and mortality. In the propensity-score matched population, the incidence of fractures was only different in the extremity regions between high- and low-risk patients as well as between medium- and low-risk patients. The incidences of femoral fractures were significantly higher in high-risk (odds ratio [OR], 3.4; 95% confidence interval [CI], 2.73-4.24; p < 0.001) and medium-risk patients (OR, 1.4; 95% CI, 1.24-1.54; p < 0.001) than in low-risk patients. In addition, high-risk patients had significantly lower odds of humeral, radial, patellar, and tibial fractures; however, such lower odds were not found in medium- risk than low-risk patients. Conclusions: The fracture patterns of female trauma patients with high- and medium-risk osteoporosis were different from that of low-risk patients exclusively in the extremity region.

Prediction of Mortality in Patients with Isolated Traumatic Subarachnoid Hemorrhage Using a Decision Tree Classifier: A Retrospective Analysis Based on a Trauma Registry System.

Background: In contrast to patients with traumatic subarachnoid hemorrhage (tSAH) in the presence of other types of intracranial hemorrhage, the prognosis of patients with isolated tSAH is good. The incidence of mortality in these patients ranges from 0-2.5%. However, few data or predictive models are available for the identification of patients with a high mortality risk. In this study, we aimed to construct a model for mortality prediction using a decision tree (DT) algorithm, along with data obtained from a population-based trauma registry, in a Level 1 trauma center. Methods: Five hundred and forty-five patients with isolated tSAH, including 533 patients who survived and 12 who died, between January 2009 and December 2016, were allocated to training (n = 377) or test (n = 168) sets. Using the data on demographics and injury characteristics, as well as laboratory data of the patients, classification and regression tree (CART) analysis was performed based on the Gini impurity index, using the rpart function in the rpart package in R. Results: In this established DT model, three nodes (head Abbreviated Injury Scale (AIS) score ≤4, creatinine (Cr) <1.4 mg/dL, and age <76 years) were identified as important determinative variables in the prediction of mortality. Of the patients with isolated tSAH, 60% of those with a head AIS >4 died, as did the 57% of those with an AIS score ≤4, but Cr ≥1.4 and age ≥76 years. All patients who did not meet the above-mentioned criteria survived. With all the variables in the model, the DT achieved an accuracy of 97.9% (sensitivity of 90.9% and specificity of 98.1%) and 97.7% (sensitivity of 100% and specificity of 97.7%), for the training set and test set, respectively. Conclusions: The study established a DT model with three nodes (head AIS score ≤4, Cr <1.4, and age <76 years) to predict fatal outcomes in patients with isolated tSAH. The proposed decision-making algorithm may help identify patients with a high risk of mortality.

Comparison of the new Exponential Injury Severity Score with the Injury Severity Score and the New Injury Severity Score in trauma patients: A cross-sectional study.

OBJECTIVE: To compare Exponential Injury Severity Score (EISS) with Injury Severity Score (ISS) and New Injury Severity Score (NISS) in terms of their predictive capability of the outcomes and medical expenses of hospitalized adult trauma patients. SETTING: This study was based at a level I trauma center in Taiwan. METHODS: Data for 17,855 adult patients hospitalized from January 1, 2009 to December 31, 2015 were retrieved from the Trauma Registry System. The primary outcome was in-hospital mortality. Secondary outcomes were the hospital length of stay (LOS), intensive care unit (ICU) admission rate, ICU LOS, and medical expenses. Chi-square tests were used for categorical variables to determine the significance of the associations between the predictor and outcome variables. Student t-tests were applied to analyze normally distributed data for continuous variables, while Mann-Whitney U tests were used to compare non-normally distributed data. RESULTS: According to the survival rate-to-severity score relationship curve, we grouped all adult trauma patients based on EISS scores of ≥ 27, 9-26, and < 9. Significantly higher mortality rates were noted in patients with EISS ≥ 27 and those with EISS of 9-26 when compared to patients with EISS < 9; this finding concurred to the findings for groups classified by the ISS and NISS with the cut-off points set between 25 and 16. The hospital LOS, ICU admission rates, and medical expenses for patients with EISS ≥ 27 and patients with EISS of 9-26 were also significantly longer and higher than that of patients with EISS < 9. When comparing the demographics and detailed medical expenses of very severely injured adult trauma patients classified according to ISS, NISS, and EISS, patients with ISS ≥ 25 and NISS ≥ 25 both had significantly lower mortality rates, lower ICU admission rates, and shorter ICU LOS compared to patients with EISS ≥ 27. CONCLUSIONS: EISS 9 and 27 can serve as two cut-off points regarding injury severity, and patients with EISS ≥ 27 have the greatest injury severity. Additionally, these patients have the highest mortality rate, the highest ICU admission rate, and the longest ICU LOS compared to those with ISS ≥ 25 and NISS ≥ 25, suggesting that patients with EISS ≥ 27 have the worst outcome.