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Background Cardiotoxicity is a leading cause of mortality among breast cancer patients treated with chemotherapy. Therefore, an early risk assessment is vital for the clinical prevention and treatment of cardiotoxicity in breast cancer patients treated with chemotherapy, although a recognized tool is scant in our country. Objective To develop a cardiotoxic risk assessment scale for breast cancer patients undergoing chemotherapy and to test its reliability and validity. Methods Through reviewing relevant domestic and international literatures, a pool involving items to assess the risk of cardiotoxicity in breast cancer patients treated with chemotherapy was created. Semi-structured interviews with healthcare providers at Jiangsu Cancer Hospital from September to October 2022 were performed by purposive sampling, thus primarily forming a tool of items for the cardiotoxic risk assessment scale. In addition, breast cancer patients treated with chemotherapy in Jiangsu Cancer Hospital were randomly selected for a pre-survey and validation of the reliability and validity of the scale. Ranked by the score of the cardiotoxic risk assessment scale, the top 27% of participants were assigned into the high-score group, and the remaining were in the low-score group. Cronbach's α coefficient was used to evaluate the internal consistency of the scale. Validity of the scale was verified by measuring the item-level content validity index (I-CVI) and scale-level content validity index (S-CVI). Exploratory factor analysis was performed to assess the structural validity. Receiver operating characteristic (ROC) curves were plotted, and the area under tcurve (AUC) was calculated to determine the predictive validity. Results Twenty healthcare providers were included in the semi-structured interviews. After two rounds of expert consultations, a 19-item cardiotoxic risk assessment scale in breast cancer patients treated with chemotherapy was developed. In this study, there were 79 patients in the low-score group and 83 in the high-score group. No significant differences in the history of smoking, endocrine treatment and immunotherapy were detected between the two groups (P>0.05). Correlation analysis showed that the history of smoking and immunotherapy was not significantly correlated with the total scores (P>0.05). Eventually, three items of smoking history, history of endocrine treatment and history of immunotherapy were removed, forming a 16-item scale. The Cronbach's α coefficient, test-retest reliability and inter-rater reliability were 0.739, 0.983 and 0.984, respectively. Content validity results showed that I-CVI ranged from 0.83 to 1.00, and S-CVI was 0.98. Predictive validity results showed the AUC of 0.887 (95%CI=0.827-0.947, P

Objective To analyze the clinical distribution of Klebsiella pneumoniae isolates, screen for the multidrug resistance of Klebsiella pneumoniae strains to commonly used antimicrobial drugs, and provide reference for the prevention and control of hospital-acquired infections and rational clinical use of antimicrobial drugs. Methods Various clinical specimens collected from January 2018 to December 2022 at the Zhongda Hospital Affiliated to Southeast University were cultured to isolate bacteria. The VITEK automated microbial analyzer was used to identify the bacterial species. A total of 3 342 non-repetitive Klebsiella pneumoniae isolates were obtained during this period. Each Klebsiella pneumoniae strain was subjected to drug susceptibility testing using automated antimicrobial systems, disk diffusion methods, or standard broth microdilution methods to determine the antibiotic resistance profiles of Klebsiella pneumoniae. The detection rate of Klebsiella pneumoniae in clinical specimens and its association with specimen sources or department categories were analyzed. Results Klebsiella pneumoniae isolates were obtained from sputum (42.07%), urine (14.81%), and blood (10.29%). The departments with higher detection rates of Klebsiella pneumoniae were Intensive Care Unit (ICU) (35.19%), Neurosurgery (6.28%), and Respiratory and Critical Care Medicine (5.42%). The resistance identification results showed the highest resistance rate to ampicillin (100.00%) and the lowest resistance rate to amikacin (4.22%). Annual analysis of resistance rates to carbapenems in Klebsiella pneumoniae isolates from 2018 to 2021 revealed an increasing trend: 2.94%, 4.66%, 7.90%, and 15.35%, respectively. However, in 2022, the resistance rate started to decrease (5.38%). Carbapenem-resistant Klebsiella pneumoniae strains were predominantly of the KPC type, and there was a statistically significant difference in the resistance rates to commonly used antimicrobial drugs between carbapenem-resistant Klebsiella pneumoniae and carbapenem-sensitive Klebsiella pneumoniae(P＜0.01). Conclusion Klebsiella pneumoniae maintains a high level of clinical isolation rate, along with high resistance rates. Therefore, it is necessary to strengthen the prevention and control of hospital-acquired bacterial infections and surveillance of drug resistance. Rational selection of antimicrobial drugs should be employed for the treatment of Klebsiella pneumoniae infections.

Objective To observe the practice of standard management of outpatient complaints and improve the quality of outpatient medical care. Methods Total of 72 cases of outpatient complaints received from July 2020 to august 2020 were included as the control group, and another 72 cases of outpatient complaints received from September 2020 to October 2020 were included as the observation group. Cases of outpatient complaints in the control group were addressed by using a conventional method, and those in the observation group were addressed by using a standard management procedure. The incidence of medical dispute and patient satisfaction were compared between two groups. Results There were 6 cases of medical dispute reported in the control group. T he satisfaction rate was 98. 61%(71/72) in the observation group, which was higher than 84. 72%(61/72) in the control group. Conclusion Standardized treatment of outpatient complaints not only mediate doctor-patient disputes, but also protect the rights and interests of both sides. The practice of standardized treatment may improve the overall service quality of the hospital and the satisfaction of patients. (目的 探讨门诊投诉规范化处理的实践效果。方法 将2020年7月—8月接收的72份投诉案例设为对照组, 将2020年9月—10月接收的72份投诉案例设为观察组。对照组采取常规方法接待和处理, 观察组严格执行门诊投诉规范处置。统计2组医疗纠纷发生情况, 比较2组当事患者对处置过程的满意度。结果 观察组未发生医疗纠纷, 对照组发生医疗纠纷6(8. 33%)起。观察组当事患者对处置流程的满意度为98. 61%(71/72), 对照组为84. 72%(61/72)。结论 规范处置门诊投诉, 能够有效控制医患纠纷, 保障医患双方的权益, 有助于提高医院整体服务质量, 提升患者满意度。)

Dragon fruit stem disease significantly affects both the quality and yield of dragon fruit. Therefore, there is an urgent need for an efficient, high-precision intelligent detection method to address the challenge of disease detection. To address the limitations of traditional methods, including slow detection and weak micro-integration capability, this paper proposes an improved YOLOv8-G algorithm. The algorithm reduces computational redundancy by introducing the C2f-Faster module. The loss function was modified to the structured intersection over union (SIoU), and the coordinate attention (CA) and content-aware reorganization feature extraction (CARAFE) modules were incorporated. These enhancements increased the model's stability and improved its accuracy in recognizing small targets. Experimental results showed that the YOLOv8-G algorithm achieved a mean average precision (mAP) of 83.1% and mAP50:95 of 48.3%, representing improvements of 3.3% and 2.3%, respectively, compared to the original model. The model size and floating point operations per second (FLOPS) were reduced to 4.9 MB and 6.9 G, respectively, indicating reductions of 20% and 14.8%. The improved model achieves higher accuracy in disease detection while maintaining a lighter weight, serving as a valuable reference for researchers in the field of dragon fruit stem disease detection. [ABSTRACT FROM AUTHOR]

To achieve an accurate measurement of tread size after fixed-length cutting, this paper proposes a point-cloud-based tread size measurement method. Firstly, a mathematical model of corner points and a reprojection error is established, and the optimal solution of the number of corner points is determined by the non-dominated sorting genetic algorithm II (NSGA-II), which reduces the reprojection error of the RGB-D camera. Secondly, to address the problem of the low accuracy of the traditional pixel metric ratio measurement method, the random sampling consensus point cloud segmentation algorithm (RANSAC) and the oriented bounding box (OBB) collision detection algorithm are introduced to complete the accurate detection of the tread size. By comparing the absolute error and relative error data of several groups of experiments, the accuracy of the detection method in this paper reaches 1 mm, and the measurement deviation is between 0.14% and 2.67%, which is in line with the highest accuracy standard of the national standard. In summary, the RGB-D visual inspection method constructed in this paper has the characteristics of low cost and high inspection accuracy, which is a potential solution to enhance the pickup guidance of tread size measurement. [ABSTRACT FROM AUTHOR]

Thyroid hormones are metabolic indicators to evaluate the physical condition of emergency hospitalized patients, while the relationship between total triiodothyronine and the severity of emergency inpatients is still unclear. To explore the thyroid function levels of inpatients in emergency ward and the status of combined Nonthyroidal illness syndrome (NTIS), and to emphasize the importance of thyroid hormone examination for non-endocrinology inpatients. According to thyroid function of inpatients in emergency ward, they were divided into NTIS group and non-NTIS group, the hematological characteristics and TH levels of each group were analyzed. Based on clinical diagnoses, the hospitalized patients were divided into three major groups, namely infection group, non-infection group and impaired organ function group. Among them, infection group was further divided into sepsis group, lung infection group and local infection group, altogether five groups. The thyroid function levels and low values in each group were evaluated, and the correlation between hormone levels and inflammatory factors, nutritional indicators and the relationship with the risk of death was discussed. The inpatient rate in emergency ward complicated with NTIS was 62.29%, T3 was the most sensitive index of NTIS, followed by FT3. Compared to non-NTIS group, the NTIS group had an increased risk of death. The sepsis group and impaired organ function group had the highest rates of complicated NTIS, reaching 83.33% and 78.12% respectively. Spearman's correlation analysis implied T3/T4/FT3 levels were positively correlated with ALb and PLT (except T4), and negatively correlated with CRP, D-Dimer, IL-6 and Fer. The Receiver Operating Curve (ROC) and Area under the curve (AUC) showed T3 levels alone were strongly associated with the risk of death (AUC 0.750; 95% CI 0.673–0.828; P < 0.001). T3 is the most sensitive indicator for emergency patients, followed by FT3. The decrease of T3 level has a good predictive value for mortality risk. Thyroid function should be monitored in critically ill patients. [ABSTRACT FROM AUTHOR]

To address the current steel surface defect detection algorithms in practical applications involving low detection accuracy, an efficient and highly accurate strip steel surface defect detection algorithm, DEW-YOLO, is proposed in this paper. Firstly, by combining the advantages of deformable convolutional networks (DCNs), this paper innovates the C2F module in YOLOv8 and proposes a C2f_DCN module that can flexibly sample features to enhance the abilities of learning and expressing defect features of different sizes and shapes. Secondly, the explicit visual center (EVC) is introduced into the backbone network, which enhances feature extraction capabilities and adaptability and enables the model to better adjust features at different levels and scales. Finally, the original loss function is replaced with the Wise-IoU (WIoU) loss function to accurately measure the similarity between the target frames and improve the defect detection performance of the model. The experimental results on the NEU-DET dataset demonstrate that the algorithms proposed in this paper achieved a mean average precision (mAP) of 80.3% in steel surface defect detection tasks, which was a 3.9% improvement over the original YOLOv8 model. The model's inference speed reached 91 frames per second (FPS). DEW-YOLO effectively enhances the accuracy of steel defect detection and better satisfies industrial inspection requirements. [ABSTRACT FROM AUTHOR]

Single‐molecular organic photovoltaics (SMOPVs), which are based on monadic systems containing donor (D) and acceptor (A) molecule blocks that facilitate exciton dissociation, offer obvious advantages over binary or multicomponent bulk‐heterojunction (BHJ) systems, including simplified cell fabrication, stabilized morphology of the D/A interface, and extended device operation lifetime. However, limited by the development of A blocks, the power conversion efficiency (PCE, ≈5%) of SMOPVs based on molecular D–A dyads still lags conventional BHJ OPVs (over 19%). Herein, by introducing a narrow‐bandgap A–DA'D–A conjugated backbone as the A‐block, combined with the linear D‐block BDT‐3T‐R and flexible alkyl chain linker, two molecular dyads, SM‐1Y (one D‐block and one A‐block) and SM‐2Y (one D‐block and two A‐blocks), are designed and developed. Due to superior absorption spectra and better molecular stacking compared to SY‐1Y, SM‐2Y‐based SMOPV delivers a PCE of 8.13%, which is the highest value in the SMOPV reported thus far. Note that both SM‐1Y and SM‐2Y devices show much better storage and photostability stability as compared to the control BDT‐3T‐C6:Y18‐C3 binary system. [ABSTRACT FROM AUTHOR]