Analysis of the factors influencing moderate to poor performance status in patients with cancer after chemotherapy: a cross-sectional study comparing three models.

There are no models for assessing the factors that determine moderate to poor performance status in patients with cancer after chemotherapy. This study investigated the influencing factors and identified the best model for predicting moderate-poor performance status. A convenience sampling method was used. Demographic and clinical data and evaluation results for fatigue, pain, quality of life and Eastern Cooperative Oncology Group status were collected three days after the end of chemotherapy. Decision tree, random forest and logistic regression models were constructed. Ninety-four subjects in the case group had moderate to poor performance status, and 365 subjects in the control group had no or mild activity disorders. The random forest model was the most accurate model. Physical function, total protein, general quality of life within one week before chemotherapy, hemoglobin, pain symptoms and globulin were the main factors. Total protein and hemoglobin levels reflect nutritional status, and globulin levels are an index of liver function. Therefore, physical function, nutritional status, general quality of life and pain symptoms within one week before chemotherapy and liver function can be used to predict moderate-poor performance status. Nurses should pay more attention to patients with poor physical function, poor nutritional status, lower quality of life and pain symptoms after chemotherapy.

A mega study of antibiotics contamination in Eastern aquatic ecosystems of China: occurrence, interphase transfer processes, ecotoxicological risks, and source modeling.

Understanding the occurrence, sources, transfer mechanisms, fugacity, and ecotoxicological risks of antibiotics play a pivotal role in improving the sustainability and ecological health of freshwater ecosystems. Therefore, in order to determine the levels of antibiotics, water and sediment samples were collected from multiple Eastern freshwater ecosystems (EFEs) of China, including Luoma Lake (LML), Yuqiao Reservoir (YQR), Songhua Lake (SHL), Dahuofang Reservoir (DHR), and Xiaoxingkai Lake (XKL), and were analyzed using Ultra Performance Liquid Chromatography/Tandem Mass Spectrometry (UPLC-MS/MS). EFEs regions are particularly interesting due to higher urban density, industrialization, and diverse land use in China. The findings revealed that a collective total of 15 antibiotics categorized into four families, which included sulfonamides (SAs), fluoroquinolones (FQs), tetracyclines (TCs), and macrolides (MLs), exhibited high detection frequencies, indicating widespread antibiotic contamination. The pollution levels in the water phase were in the order of LML > DHR > XKL > SHL > YQR. The sum concentration of individual antibiotics for each water body ranged from not detected (ND) to 57.48 ng/L (LML), ND to 12.25 ng/L (YQR), ND to 57.7 ng/L (SHL), ND to 40.50 ng/L (DHR), and ND to 26.30 ng/L (XKL) in the water phase. Similarly, in the sediment phase, the sum concentration of individual antibiotics ranged from ND to 15.35 ng/g, ND to 198.75 ng/g, ND to 1233.34 ng/g, ND to 388.44 ng/g, and ND to 862.19 ng/g, for LML, YQR, SHL, DHR, and XKL, respectively. Interphase fugacity (ffsw) and partition coefficient (Kd) indicated dominant resuspension of antibiotics from sediment to water, causing secondary pollution in EFEs. Two groups of antibiotics, namely MLs (erythromycin, azithromycin, and roxithromycin) and FQs (ofloxacin and enrofloxacin), showed a medium-high level of adsorption tendency on sediment. Source modeling (PMF5.0) identified wastewater treatment plants, sewage, hospitals, aquaculture, and agriculture as the major antibiotic pollution sources in EFEs, contributing between 6% and 80% to different aquatic bodies. Finally, the ecological risk posed by antibiotics ranged from medium to high in EFEs. This study offers valuable insights into the levels, transfer mechanisms, and risks associated with antibiotics in EFEs, enabling the formulation of large-scale policies for pollution control.