Purpose: Neuroendocrine prostate cancer (NEPC) represents a particularly aggressive subtype of prostate cancer with a challenging prognosis. The purpose of this investigation is to craft and confirm the reliability of nomograms that can accurately forecast the 1-, 3-, and 5-year overall survival (OS) and cancer-specific survival (CSS) rates for individuals afflicted with NEPC. Materials and Methods: Data pertaining to patients diagnosed with NEPC within the timeframe of 2010 to 2020 was meticulously gathered and examined from the Surveillance, Epidemiology, and End Results Program (SEER). To predict OS and CSS, we devised and authenticated two distinct nomograms, utilizing predictive variables pinpointed through both univariate and multivariate Cox regression analyses. Results: The study encompassed 393 of NEPC patients, who were systematically divided into training and validation cohorts at a 2:1 ratio. Key prognostic factors were isolated, verified, and integrated into the respective nomograms for OS and CSS. The performance metrics, denoted by C-indices, stood at 0.730, 0.735 for the training set, and 0.784, 0.756 for the validation set. The precision and clinical relevance of the nomograms were further corroborated by the analysis of receiver operating characteristic curves, calibration plots, and decision curve analyses. Conclusions The constructed nomograms have demonstrated impressive efficacy in forecasting the 1-, 3-, and 5-year OS and rates for patients with NEPC. Implementing these predictive tools in clinical settings is anticipated to considerably enhance the care and treatment planning for individuals diagnosed with this aggressive form of prostate cancer, thus providing tailored and more precise prognostic assessments.

Purpose: Neuroendocrine prostate cancer (NEPC) represents a particularly aggressive subtype of prostate cancer with a challenging prognosis. The purpose of this investigation is to craft and confirm the reliability of nomograms that can accurately forecast the 1-, 3-, and 5-year overall survival (OS) and cancer-specific survival (CSS) rates for individuals afflicted with NEPC. Materials and Methods: Data pertaining to patients diagnosed with NEPC within the timeframe of 2010 to 2020 was meticulously gathered and examined from the Surveillance, Epidemiology, and End Results Program (SEER). To predict OS and CSS, we devised and authenticated two distinct nomograms, utilizing predictive variables pinpointed through both univariate and multivariate Cox regression analyses. Results: The study encompassed 393 of NEPC patients, who were systematically divided into training and validation cohorts at a 2:1 ratio. Key prognostic factors were isolated, verified, and integrated into the respective nomograms for OS and CSS. The performance metrics, denoted by C-indices, stood at 0.730, 0.735 for the training set, and 0.784, 0.756 for the validation set. The precision and clinical relevance of the nomograms were further corroborated by the analysis of receiver operating characteristic curves, calibration plots, and decision curve analyses. Conclusions The constructed nomograms have demonstrated impressive efficacy in forecasting the 1-, 3-, and 5-year OS and rates for patients with NEPC. Implementing these predictive tools in clinical settings is anticipated to considerably enhance the care and treatment planning for individuals diagnosed with this aggressive form of prostate cancer, thus providing tailored and more precise prognostic assessments.

Purpose: Neuroendocrine prostate cancer (NEPC) represents a particularly aggressive subtype of prostate cancer with a challenging prognosis. The purpose of this investigation is to craft and confirm the reliability of nomograms that can accurately forecast the 1-, 3-, and 5-year overall survival (OS) and cancer-specific survival (CSS) rates for individuals afflicted with NEPC. Materials and Methods: Data pertaining to patients diagnosed with NEPC within the timeframe of 2010 to 2020 was meticulously gathered and examined from the Surveillance, Epidemiology, and End Results Program (SEER). To predict OS and CSS, we devised and authenticated two distinct nomograms, utilizing predictive variables pinpointed through both univariate and multivariate Cox regression analyses. Results: The study encompassed 393 of NEPC patients, who were systematically divided into training and validation cohorts at a 2:1 ratio. Key prognostic factors were isolated, verified, and integrated into the respective nomograms for OS and CSS. The performance metrics, denoted by C-indices, stood at 0.730, 0.735 for the training set, and 0.784, 0.756 for the validation set. The precision and clinical relevance of the nomograms were further corroborated by the analysis of receiver operating characteristic curves, calibration plots, and decision curve analyses. Conclusions The constructed nomograms have demonstrated impressive efficacy in forecasting the 1-, 3-, and 5-year OS and rates for patients with NEPC. Implementing these predictive tools in clinical settings is anticipated to considerably enhance the care and treatment planning for individuals diagnosed with this aggressive form of prostate cancer, thus providing tailored and more precise prognostic assessments.

Purpose: Neuroendocrine prostate cancer (NEPC) represents a particularly aggressive subtype of prostate cancer with a challenging prognosis. The purpose of this investigation is to craft and confirm the reliability of nomograms that can accurately forecast the 1-, 3-, and 5-year overall survival (OS) and cancer-specific survival (CSS) rates for individuals afflicted with NEPC. Materials and Methods: Data pertaining to patients diagnosed with NEPC within the timeframe of 2010 to 2020 was meticulously gathered and examined from the Surveillance, Epidemiology, and End Results Program (SEER). To predict OS and CSS, we devised and authenticated two distinct nomograms, utilizing predictive variables pinpointed through both univariate and multivariate Cox regression analyses. Results: The study encompassed 393 of NEPC patients, who were systematically divided into training and validation cohorts at a 2:1 ratio. Key prognostic factors were isolated, verified, and integrated into the respective nomograms for OS and CSS. The performance metrics, denoted by C-indices, stood at 0.730, 0.735 for the training set, and 0.784, 0.756 for the validation set. The precision and clinical relevance of the nomograms were further corroborated by the analysis of receiver operating characteristic curves, calibration plots, and decision curve analyses. Conclusions The constructed nomograms have demonstrated impressive efficacy in forecasting the 1-, 3-, and 5-year OS and rates for patients with NEPC. Implementing these predictive tools in clinical settings is anticipated to considerably enhance the care and treatment planning for individuals diagnosed with this aggressive form of prostate cancer, thus providing tailored and more precise prognostic assessments.

Purpose: Neuroendocrine prostate cancer (NEPC) represents a particularly aggressive subtype of prostate cancer with a challenging prognosis. The purpose of this investigation is to craft and confirm the reliability of nomograms that can accurately forecast the 1-, 3-, and 5-year overall survival (OS) and cancer-specific survival (CSS) rates for individuals afflicted with NEPC. Materials and Methods: Data pertaining to patients diagnosed with NEPC within the timeframe of 2010 to 2020 was meticulously gathered and examined from the Surveillance, Epidemiology, and End Results Program (SEER). To predict OS and CSS, we devised and authenticated two distinct nomograms, utilizing predictive variables pinpointed through both univariate and multivariate Cox regression analyses. Results: The study encompassed 393 of NEPC patients, who were systematically divided into training and validation cohorts at a 2:1 ratio. Key prognostic factors were isolated, verified, and integrated into the respective nomograms for OS and CSS. The performance metrics, denoted by C-indices, stood at 0.730, 0.735 for the training set, and 0.784, 0.756 for the validation set. The precision and clinical relevance of the nomograms were further corroborated by the analysis of receiver operating characteristic curves, calibration plots, and decision curve analyses. Conclusions The constructed nomograms have demonstrated impressive efficacy in forecasting the 1-, 3-, and 5-year OS and rates for patients with NEPC. Implementing these predictive tools in clinical settings is anticipated to considerably enhance the care and treatment planning for individuals diagnosed with this aggressive form of prostate cancer, thus providing tailored and more precise prognostic assessments.

Debates persist regarding the efficacy and safety of azvudine, particularly its real-world outcomes. This study involved patients aged ≥60 years who were admitted to 25 hospitals in mainland China with confirmed SARS-CoV-2 infection between December 1, 2022, and February 28, 2023. Efficacy outcomes were all-cause mortality during hospitalization, the proportion of patients discharged with recovery, time to nucleic acid-negative conversion (T _NANC), time to symptom improvement (T _SI), and time of hospital stay (T _HS). Safety was also assessed. Among the 5884 participants identified, 1999 received azvudine, and 1999 matched controls were included after exclusion and propensity score matching. Azvudine recipients exhibited lower all-cause mortality compared with controls in the overall population (13.3% vs. 17.1%, RR, 0.78; 95% CI, 0.67-0.90; P = 0.001) and in the severe subgroup (25.7% vs. 33.7%; RR, 0.76; 95% CI, 0.66-0.88; P < 0.001). A higher proportion of patients discharged with recovery, and a shorter T _NANC were associated with azvudine recipients, especially in the severe subgroup. The incidence of adverse events in azvudine recipients was comparable to that in the control group (2.3% vs. 1.7%, P = 0.170). In conclusion, azvudine showed efficacy and safety in older patients hospitalized with COVID-19 during the SARS-CoV-2 omicron wave in China.

Hip fracture in the elderly is characterized by high incidence, high disability rate, and high mortality and has been recognized as a public health issue threatening their health. Surgery is the preferred choice for the treatment of elderly patients with hip fracture. However, lower extremity deep venous thrombosis (DVT) has an extremely high incidence rate during the perioperative period, and may significantly increase the risk of patients′ death once it progresses to pulmonary embolism. In response to this issue, the clinical guidelines and expert consensuses all emphasize active application of comprehensive preventive measures, including basic prevention, physical prevention, and pharmacological prevention. In this prevention system, basic prevention is the basis of physical and pharmacological prevention. However,there is a lack of unified and definite recommendations for basic preventive measures in clinical practice. To this end, the Orthopedic Nursing Professional Committee of the Chinese Nursing Association and Nursing Department of the Orthopedic Branch of the China International Exchange and Promotive Association for Medical and Health Care organized relevant nursing experts to formulate Expert consensus on perioperative basic prevention for lower extremity deep venous thrombosis in elderly patients with hip fracture ( version 2024) . A total of 10 recommendations were proposed, aiming to standardize the basic preventive measures for lower extremity DVT in elderly patients with hip fractures during the perioperative period and promote their subsequent rehabilitation.

Objective To investigate the clinical effect of Qiji Zhuyu Zhixue decoction in treatment of previous cesarean scar defect(PCSD)and explore the value of transvaginal two-dimensional ultrasound combined with three-dimensional power Doppler ultrasound(3D-PDUS)in the diagnosis of PCSD.Methods A total of 120 PCSD patients treated and treated in Wenzhou People's Hospital from April to October 2023 were selected as study objects,and they were randomly divided into case group(50 cases)and control group(70 cases).The case group was treated with Qiji Zhuyu Zhixue decoction,and the control group was treated with desogestrel and ethinylestradiol tablets.The clinical effects after 6 months of treatment were compared between two groups.The length,width,depth,lateral muscle thickness and volume of PCSD before and after treatment were evaluated by two-dimensional ultrasound combined with 3D-PDUS.The receiver operating characteristic curve was used to evaluate the efficacy of ultrasonic parameters in diagnosis of PCSD.Results After 6 months of treatment,the total effective rate of case group was significantly higher than that of control group(x2=21.97,P＜0.01).After treatment,the diverticulum depth and volume in case group were significantly lower than before treatment(P＜0.05).The diverticulum depth in case group was significantly lower than that in control group(P＜0.05).The lateral muscle thickness in case group was significantly greater than that before treatment and control group(P＜0.05).The area under the curve of the combined diagnosis of PCSD with diverticular depth,diverticular lateral muscle thickness and diverticular volume was 0.707.Conclusion The clinical effect of Qiji Zhuyu Zhixue decoction on PCSD is remarkable.Transvaginal two-dimensional ultrasound combined with 3D-PDUS is the first choice for the diagnosis of PCSD,and it is worth popularizing and applying.

Objective:To explore the influencing factors of insomnia disorder in perimenopausal women and construct a prediction model of insomnia disorder in perimenopausal women based on machine learning method.Methods:A case-control study was used in this study. A total of 140 perimenopausal women who were examined in Lishui Maternal and Child Health Hospital from January 2019 to June 2021 were selected as the study objects for retrospective analysis by convenient sampling method. They were divided into occurrence and non-occurrence groups based on the presence of insomnia disorders. Relevant data of the patients were collected and risk factors analysis was conducted. Multivariate Logistic regression, decision classification regression tree (CRT) and back propagation neural network (BPNN) algorithm based on machine learning, the prediction model of insomnia disorder in perimenopausal women was constructed.Results:A total of 140 perimenopausal women were included, including 88 patients (62.86%) in the occurrence group, aged (50.16 ± 4.73) years old, and 52 patients (37.14%) in the non-occurrence group, aged (47.33 ± 4.54) years old. Multivariate Logistic regression analysis showed that percapita family monthly income ( OR = 0.019, 95% CI 0.001-0.422, P<0.05), Hamilton Depression Scale (HAMD) score ( OR = 1.665, 95% CI 1.108-2.502, P<0.05) and Self-rating Anxiety Scale (SAS) score ( OR = 1.407, 95% CI 1.085-1.826, P<0.05) of the two groups were independent risk factors for the occurrence of insomnia disorder in perimenopausal women. The prediction model constructed by CRT showed that SAS score, HAMD score and percapita family monthly income were the influencing factors for the occurrence of insomnia disorder in perimenopausal women. The results of BPNN model showed that the importance ranking of influencing factors was SAS score>percapita family monthly income>HAMD score>body mass index>age>work status>daily exercise cumulative time. Among the models constructed by the three machine learning algorithms, the area under the curve of multivariate Logistic regression analysis was 0.998, the sensitivity was 96.6%, the specificity was 100.0%, which had the best predictive performance. Conclusions:In this study, the prediction model of insomnia disorder in perimenopausal women based on machine learning method has good prediction efficiency, among which the multivariate Logistic regression model has the best diagnostic efficiency, and the established prediction model has good prediction accuracy.

Hip fracture is considered as the most severe osteoporotic fracture characterized by high disability and mortality in the elderly. Improved surgical techniques and multidisciplinary team play an active role in alleviating prognosis, which places higher demands on perioperative nursing. Dysfunction, complications, and secondary impact of anaesthesia and surgery add more difficulties to clinical nursing. Besides, there still lack clinical practices in perioperative nursing for elderly patients with hip fracture in China. In this context, led by the Orthopedic Nursing Committee of Chinese Nursing Association, the Expert consensus on clinical practice in perioperative nursing for elderly patients with hip fracture ( version 2023) is developed based on the evidence-based medicine. This consensus provides 11 recommendations on elderly patients with hip fracture from aspects of perioperative health education, condition monitoring and inspection, complication risk assessment and prevention, and rehabilitation, in order to provide guiding advices for clinical practice, improve the quality of nursing and ameliorate the prognosis of elderly patients with hip fracture.