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BackgroundPrevention measures for palliative care and the provision of discharge planning services for inpatients in Taiwan before and during the COVID-19 pandemic had not been investigated. This study was aimed to investigate the factors associated with heightened palliative care needs and increased mortality rates.MethodsThis research adopts a retrospective case–control study design. The investigation encompasses patients admitted before the pandemic (from January 1, 2019, to May 31, 2019) and during the COVID-19 pandemic (from January 1, 2020, to May 31, 2020). The case group consisted of 231 end-of-life inpatients during the pandemic, control group was composed of the pool of inpatients with pre-pandemic and matched with cases by sex and age in a 1:1 ratio.ResultsThe results showed that the prevalence of respiratory failure symptoms (p = 0.004), residing in long-term care facilities (p = 0.017), palliative care needs assessment scores (p = 0.010), as well as the provision of guidance for nasogastric tube feeding (p = 0.002), steam inhalation (p = 0.003), turning and positioning (p

As global population growth and the use of household appliances increase, residential electricity consumption has surged, leading to challenges in maintaining a balanced electrical load. This surge often results in localized and intermittent power outages, adversely affecting residential electricity reliability and the profitability of power supply companies. Addressing this, we propose a novel CNN-BiLSTM-SA model, combining Convolutional Neural Network (CNN), Bidirectional Long Short-Term Memory (BiLSTM), and Self-Attention (SA) mechanisms, to accurately predict residential electricity consumption. The model integrates temporal feature extraction through the CNN module, correlation capture via BiLSTM, and intrinsic feature analysis using SA mechanisms, enhancing predictive accuracy. Our experimental results demonstrate the model’s precision, outperforming existing methods in key performance metrics. Additionally, ablation studies affirm the synergistic design of CNN-BiLSTM-SA’s network components, contributing to its overall efficacy.

Abstract Background and objective Cancer ratio (CR), which is defined as serum lactate dehydrogenase (LDH) to pleural fluid adenosine deaminase (ADA) ratio, has been reported to be a useful diagnostic marker for malignant pleural effusion (MPE). Whether its diagnostic accuracy is affected by age remains unknown. This study aimed to investigate the effects of age on the diagnostic accuracy of CR. Methods The participants in this study were from a prospective cohort (SIMPLE cohort, n = 199) and a retrospective cohort (BUFF cohort, n = 158). All participants were patients with undiagnosed pleural effusion (PE). We used receiver operating characteristic (ROC) curves to evaluate the diagnostic accuracy of CR. The effect of age on the diagnostic accuracy of CR was investigated by adjusting the upper limit of age for participant enrolment. Results Eighty-eight MPE patients were verified in the SIMPLE cohort, and thirty-five MPE patients were verified in the BUFF cohort. The AUCs of CR in the SIMPLE and BUFF cohorts were 0.60 (95% CI: 0.52–0.68) and 0.63 (95% CI: 0.54–0.71), respectively. In both cohorts, the AUCs of CR decreased with the advancement of age. Conclusion Age can affect the diagnostic accuracy of CR for MPE. CR has limited diagnostic value in older patients. Key message Cancer ratio is a promising diagnostic marker for malignant pleural effusion. This study revealed that its diagnostic accuracy decreased in older patients. Its diagnostic accuracy is overestimated by previous studies using tuberculosis and pneumonia patients as controls.

Abstract Background T cell acute lymphoblastic leukemia (T-ALL) defines a group of hematological malignancies with heterogeneous aggressiveness and highly variable outcome, making therapeutic decisions a challenging task. We tried to discover new predictive model for T-ALL before treatment by using a specific pipeline designed to discover aberrantly active gene. Results The expression of 18 genes was significantly associated with shorter survival, including ACTRT2, GOT1L1, SPATA45, TOPAZ1 and ZPBP (5-GEC), which were used as a basis to design a prognostic classifier for T-ALL patients. The molecular characterization of the 5-GEC positive T-ALL unveiled specific characteristics inherent to the most aggressive T leukemic cells, including a drastic shut-down of genes located on the mitochondrial genome and an upregulation of histone genes, the latter characterizing high risk forms in adult patients. These cases fail to respond to the induction treatment, since 5-GEC either predicted positive minimal residual disease (MRD) or a short-term relapse in MRD negative patients. Conclusion Overall, our investigations led to the discovery of a homogenous group of leukemic cells with profound alterations of their biology. It also resulted in an accurate predictive tool that could significantly improve the management of T-ALL patients.

Background: Pleural fluid (PF) carcinoembryonic antigen (CEA) is a widely used diagnostic marker for malignant pleural effusion (MPE). Recent studies revealed that PF to serum CEA was also a promising diagnostic parameter for MPE. Objective: We aimed to investigate whether PF to serum CEA ratio and delta CEA (PF minus serum CEA) provided added value to PF CEA in diagnosing MPE. Methods: Patients with pleural effusion in a retrospective cohort (BUFF) and a prospective cohort (SIMPLE) were included. The clinical characteristics of the patients were extracted from their medical records. The diagnostic value of CEA ratio and delta CEA was estimated by a receiver operating characteristics (ROC) curve, net reclassification improvement (NRI), and integrated discrimination improvement (IDI). Results: A total of 148 patients in the BUFF cohort and 164 patients in the SIMPLE cohort were enrolled. The BUFF cohort had 46 MPE patients and 102 benign pleural effusion (BPE) patients, and the SIMPLE cohort had 85 MPE patients and 79 BPE patients. In both cohorts, MPE patients had significantly higher PF CEA, serum CEA, CEA ratio, and delta CEA. The area under ROC curves (AUCs) of PF CEA, CEA ratio, and delta CEA were 0.78 (95% CI: 0.67–0.88), 0.80 (95% CI: 0.72–0.89) and 0.83 (95% CI: 0.75–0.91) in the BUFF cohort, and 0.89 (95% CI: 0.83–0.94), 0.86 (95% CI: 0.80–0.92), and 0.84 (95% CI: 0.78–0.91) in the SIMPLE cohort. The differences between the AUCs of PF CEA, CEA ratio, and delta CEA did not reach statistical significance. The continuous NRI and IDI of CEA ratio and delta CEA were

Background: Tinnitus and uveitis have shared commonality in pathophysiology in terms of autoimmunity. However, no studies that have linked any association between the conditions of tinnitus and uveitis. Methods: This is a retrospective study conducted from the Taiwan National Health Insurance database in order to investigate whether tinnitus patients are at increased risk of uveitis. Patients newly diagnosed with tinnitus between 2001 and 2014 were recruited and followed up until 2018. The endpoint of interest was a diagnosis of uveitis. Results: A total of 31,034 tinnitus patients and 124,136 matched comparisons were analyzed. Tinnitus patients were found to have a significantly higher cumulative incidence for uveitis than those without the diagnosis of tinnitus with incidence rate of 1.68 (95% CI 1.55–1.82) per 10 000 person-months for tinnitus group and 1.48 (95% CI 1.42–1.54) per 10 000 person-months for non-tinnitus group. Conclusion: Tinnitus patients were found to have increased risk of developing uveitis. [ABSTRACT FROM AUTHOR]

This study endeavors to formulate a comprehensive methodology for establishing a Geological Knowledge Base (GKB) tailored to fracture-cavity reservoir outcrops within the North Tarim Basin. The acquisition of quantitative geological parameters was accomplished through diverse means such as outcrop observations, thin section studies, unmanned aerial vehicle scanning, and high-resolution cameras. Subsequently, a three-dimensional digital outcrop model was generated, and the parameters were standardized. An assessment of traditional geological knowledge was conducted to delineate the knowledge framework, content, and system of the GKB. The basic parameter knowledge was extracted using multiscale fine characterization techniques, including core statistics, field observations, and microscopic thin section analysis. Key mechanism knowledge was identified by integrating trace elements from filling, isotope geochemical tests, and water-rock simulation experiments. Significant representational knowledge was then extracted by employing various methods such as multiple linear regression, neural network technology, and discriminant classification. Subsequently, an analogy study was performed on the karst fracture-cavity system (KFCS) in both outcrop and underground reservoir settings. The results underscored several key findings: (1) Utilization of a diverse range of techniques, including outcrop observations, core statistics, unmanned aerial vehicle scanning, high-resolution cameras, thin section analysis, and electron scanning imaging, enabled the acquisition and standardization of data. This facilitated effective management and integration of geological parameter data from multiple sources and scales. (2) The GKB for fracture-cavity reservoir outcrops, encompassing basic parameter knowledge, key mechanism knowledge, and significant representational knowledge, provides robust data support and systematic geological insights for the intricate and in-depth examination of the genetic mechanisms of fracture-cavity reservoirs. (3) The developmental characteristics of fracturecavities in karst outcrops offer effective, efficient, and accurate guidance for fracture-cavity research in underground karst reservoirs. The outlined construction method of the outcrop geological knowledge base is applicable to various fracture-cavity reservoirs in different layers and regions worldwide. [ABSTRACT FROM AUTHOR]