Small cell lung cancer (SCLC) is a highly malignant disease that has garnered significant attention in terms of treatment modalities and course management. Gaining an understanding of the clinical characteristics of SCLC, acquiring proficiency in screening, diagnosis, and treatment methods for this condition, as well as promptly addressing any adverse reactions to treatment are essential foundations for developing a scientific and rational pathological management plan for SCLC. By utilizing an intelligent whole course follow-up management platform, dynamic follow-up, timely warnings, and early interventions can enable high-quality whole life cycle management. This article aims to review the current treatment landscape of SCLC while exploring the challenges associated with implementing a comprehensive process-oriented management approach. The goal is to provide valuable insights for better managing SCLC patients and ultimately improving their quality of life and prognosis.
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Humans ; Small Cell Lung Carcinoma/diagnosis* ; Lung Neoplasms/diagnosis* ; Quality of Life ; Follow-Up Studies

Objective To investigate the suitable habitats of Phlebotomus chinensis in Gansu Province, so as provide insights into effective management of mountain-type zoonotic visceral leishmaniasis (MT-ZVL). Methods The geographical coordinates of locations where MT-ZVL cases were reported were retrieved in Gansu Province from 2015 to 2023, and data pertaining to 26 environmental variables were captured, including 19 climatic variables (annual mean temperature, mean diurnal range, isothermality, temperature seasonality, maximum temperature of the warmest month, minimum temperature of the coldest month, temperature annual range, mean temperature of the wettest quarter, mean temperature of the driest quarter, mean temperature of the warmest quarter, mean temperature of the coldest quarter, annual precipitation, precipitation of the wettest month, precipitation of the driest month, precipitation seasonality, precipitation of the wettest quarter, precipitation of the driest quarter, precipitation of the warmest quarter, and precipitation of the coldest quarter), five geographical variables (elevation, annual normalized difference vegetation index, vegetation type, landform type and land use type), and two population and economic variables (population distribution and gross domestic product). Twelve species distribution models were built using the biomod2 package in R project, including surface range envelope (SRE) model, generalized linear model (GLM), generalized additive model (GAM), multivariate adaptive regression splines (MARS) model, generalized boosted model (GBM), classification tree analysis (CTA) model, flexible discriminant analysis (FDA) model, maximum entropy (MaxEnt) model, optimized maximum entropy (MAXNET) model, artificial neural network (ANN) model, random forest (RF) model, and extreme gradient boosting (XGBOOST) model. The performance of 12 models was evaluated using the area under the receiver operating characteristic curve (AUC), true skill statistics (TSS), and Kappa coefficient, and single models with high performance was selected to build the optimal ensemble models. Factors affecting the survival of Ph. chinensis were identified based on climatic, geographical, population and economic variables. In addition, the suitable distribution areas of Ph. chinensis were predicted in Gansu Province under shared socioeconomic pathway 126 (SSP126), SSP370 and SSP585 scenarios based on climatic data during the period from 1991 to 2020, from 2041 to 2060 (2050s), and from 2081 to 2100 (2090s) . Results A total of 11 species distribution models were successfully built for prediction of potential distribution areas of Ph. chinensis in Gansu Province, and the RF model had the highest predictive accuracy (AUC = 0.998). The ensemble model built based on the RF model, XGBOOST model, GLM, and MARS model had an increased predictive accuracy (AUC = 0.999) relative to single models. Among the 26 environmental factors, precipitation of the wettest quarter (12.00%), maximum temperature of the warmest month (11.58%), and annual normalized difference vegetation index (11.29%) had the greatest contributions to suitable habitats distribution of Ph. sinensis. Under the climatic conditions from 1991 to 2020, the potential suitable habitat area for Ph. chinensis in Gansu Province was approximately 5.80 × 10⁴ km², of which the highly suitable area was 1.42 × 10⁴ km², and primarily concentrated in the southernmost region of Gansu Province. By the 2050s, the unsuitable and lowly suitable areas for Ph. chinensis in Gansu Province had decreased by varying degrees compared to that of 1991 to 2020 period, while the moderately and highly suitable areas exhibited expansion and migration. By the 2090s, under the SSP126 scenario, the suitable habitat area for Ph. chinensis increased significantly, and under the SSP585 scenario, the highly suitable areas transformed into extremely suitable areas, also showing substantial growth. Future global warming is conducive to the survival and reproduction of Ph. chinensis. From the 2050s to the 2090s, the highly suitable areas for Ph. chinensis in Gansu Province will be projected to expand northward. Under the SSP126 scenario, the suitable habitat area for Ph. chinensis in Gansu Province is expected to increase by 194.75% and 204.79% in the 2050s and 2090s, respectively, compared to that of the 1991 to 2020 period. Under the SSP370 scenario, the moderately and highly suitable areas will be projected to increase by 164.40% and 209.03% in the 2050s and 2090s, respectively, while under the SSP585 scenario, they are expected to increase by 195.98% and 211.66%, respectively. Conclusions The distribution of potential suitable habitats of Ph. sinensis gradually shifts with climatic changes. Intensified surveillance and management of Ph. sinensis is recommended in central and eastern parts of Gansu Province to support early warning of MT-ZVL.

Objective In order to strengthen the connotation construction of hospitals,promote high-quality develop-ment,improve the quality of medical services,improve operational efficiency,and explore and practice the performance manage-ment mode in combination with the characteristics of the hospital's own development.Methods Take a tertiary children's spe-cialty hospital in Wuxi as an example,optimize the internal performance appraisal management system of the hospital,and con-duct dynamic monitoring and management of the whole appraisal process.Results The sample hospital constructed a multifacet-ed performance management system,and the performance appraisal results of the national tertiary public hospital in 2022 were significantly improved,and the various appraisal indexes,such as the percentage of fourth-level surgery,the intensity of antimi-crobial drug use,the value of CMI,the satisfaction degree of the medical staff,and the satisfaction degree of the outpatients,were kept optimized.Conclusion The continuous optimization of the performance management model has improved the hospital's level of refined management,the efficiency of collaboration between departments,the efficiency of resource allocation,and the efficiency of economic operation,stimulated the work motivation of medical staff,and improved the quality of medical services.

Objective:To develop a deep learning-based system for real-time recognition and classification of portal hypertensive gastropathy (PHG) and evaluate its ability to assist junior endoscopists.Methods:A total of 2 848 gastroscopy images from 832 patients with liver cirrhosis were selected from Digestive Endoscopy Center databases of Renmin Hospital of Wuhan University, Wuhan Hospital of Traditional Chinese and Western Medicine, and the Second Hospital of Jingzhou from January 2015 to October 2023. This system referred to 3 endoscopic features of Baveno Ⅱ scoring system. Three models were developed respectively for gastric antral vascular ectasia (GAVE), mosaic-like pattern (MLP), and red marks (RM). The specific classification references were as follows: (1) GAVE model: 0 no, 1 yes; (2) MLP model: 0 no, 1 mild, 2 severe; (3) RM model: 0 no, 1 isolated, 2 fused. The classification results for endoscopic characteristics of PHG of 3 endoscopy experts were taken as the gold standard. The yolov8-m model was used for training. The training dataset, validation dataset, and test dataset were allocated at a ratio of 8∶1∶1. The test dataset was used to evaluate the performance of models and their auxiliary effects on endoscopists. The accuracy, recall, precision, specificity and Kappa coefficient were calculated. Results:The accuracy, recall, specificity of GAVE model were 96.0% (48/50), 87.5% (7/8) and 97.6% (41/42). There was no significant difference between its accuracy and the gold standard ( χ2=316.226, P=1.000). The precision of GAVE1 and GAVE0 were 87.5% (7/8) and 97.6% (41/42) respectively. The accuracy of MLP model was 84.1% (132/157), and there was no significant difference compared with the gold standard ( χ2=3.286, P=0.193). The precision and recall of MLP2 were 88.2% (15/17) and 75.0% (15/20). The precision and recall of MLP1 were 77.9% (60/77) and 88.2% (60/68). The precision and recall of MLP0 were 90.5% (57/63) and 82.6% (57/69). The accuracy of RM model was 87.9% (123/140), and there was no significant difference compared with the gold standard ( χ2=2.891, P=0.409). The precision and recall of RM2 were 94.7% (18/19) and 78.3% (18/23). The precision and recall of RM1 were 72.2% (26/36) and 81.3% (26/32). The precision and recall of RM0 were 92.9% (79/85) and 92.9% (79/85). The mean accuracy of the three junior endoscopists, with and without the assistance of the GAVE model, MLP model, and RM model, respectively increased from 95.3% to 99.3%, from 83.9% to 91.9%, and from 81.9% to 83.1%. The overall consistency analysis of the 3 junior endoscopists with the gold standard indicated that the consistency of the GAVE model before and after assistance was extremely strong (both an overall Kappa of 1.000); the consistency before assistance of the MLP model was moderate (with an overall Kappa of 0.601), which increased to extremely strong after assistance (with an overall Kappa of 0.964); and the consistency of the RM model before and after assistance was also relatively strong (with an overall Kappa of 0.792 before and 0.798 after). Conclusion:The deep learning system accurately identifies and classifies PHG features and significantly enhances diagnostic performance of junior endoscopists.

Objective In order to strengthen the connotation construction of hospitals,promote high-quality develop-ment,improve the quality of medical services,improve operational efficiency,and explore and practice the performance manage-ment mode in combination with the characteristics of the hospital's own development.Methods Take a tertiary children's spe-cialty hospital in Wuxi as an example,optimize the internal performance appraisal management system of the hospital,and con-duct dynamic monitoring and management of the whole appraisal process.Results The sample hospital constructed a multifacet-ed performance management system,and the performance appraisal results of the national tertiary public hospital in 2022 were significantly improved,and the various appraisal indexes,such as the percentage of fourth-level surgery,the intensity of antimi-crobial drug use,the value of CMI,the satisfaction degree of the medical staff,and the satisfaction degree of the outpatients,were kept optimized.Conclusion The continuous optimization of the performance management model has improved the hospital's level of refined management,the efficiency of collaboration between departments,the efficiency of resource allocation,and the efficiency of economic operation,stimulated the work motivation of medical staff,and improved the quality of medical services.

Objective:To develop a deep learning-based system for real-time recognition and classification of portal hypertensive gastropathy (PHG) and evaluate its ability to assist junior endoscopists.Methods:A total of 2 848 gastroscopy images from 832 patients with liver cirrhosis were selected from Digestive Endoscopy Center databases of Renmin Hospital of Wuhan University, Wuhan Hospital of Traditional Chinese and Western Medicine, and the Second Hospital of Jingzhou from January 2015 to October 2023. This system referred to 3 endoscopic features of Baveno Ⅱ scoring system. Three models were developed respectively for gastric antral vascular ectasia (GAVE), mosaic-like pattern (MLP), and red marks (RM). The specific classification references were as follows: (1) GAVE model: 0 no, 1 yes; (2) MLP model: 0 no, 1 mild, 2 severe; (3) RM model: 0 no, 1 isolated, 2 fused. The classification results for endoscopic characteristics of PHG of 3 endoscopy experts were taken as the gold standard. The yolov8-m model was used for training. The training dataset, validation dataset, and test dataset were allocated at a ratio of 8∶1∶1. The test dataset was used to evaluate the performance of models and their auxiliary effects on endoscopists. The accuracy, recall, precision, specificity and Kappa coefficient were calculated. Results:The accuracy, recall, specificity of GAVE model were 96.0% (48/50), 87.5% (7/8) and 97.6% (41/42). There was no significant difference between its accuracy and the gold standard ( χ2=316.226, P=1.000). The precision of GAVE1 and GAVE0 were 87.5% (7/8) and 97.6% (41/42) respectively. The accuracy of MLP model was 84.1% (132/157), and there was no significant difference compared with the gold standard ( χ2=3.286, P=0.193). The precision and recall of MLP2 were 88.2% (15/17) and 75.0% (15/20). The precision and recall of MLP1 were 77.9% (60/77) and 88.2% (60/68). The precision and recall of MLP0 were 90.5% (57/63) and 82.6% (57/69). The accuracy of RM model was 87.9% (123/140), and there was no significant difference compared with the gold standard ( χ2=2.891, P=0.409). The precision and recall of RM2 were 94.7% (18/19) and 78.3% (18/23). The precision and recall of RM1 were 72.2% (26/36) and 81.3% (26/32). The precision and recall of RM0 were 92.9% (79/85) and 92.9% (79/85). The mean accuracy of the three junior endoscopists, with and without the assistance of the GAVE model, MLP model, and RM model, respectively increased from 95.3% to 99.3%, from 83.9% to 91.9%, and from 81.9% to 83.1%. The overall consistency analysis of the 3 junior endoscopists with the gold standard indicated that the consistency of the GAVE model before and after assistance was extremely strong (both an overall Kappa of 1.000); the consistency before assistance of the MLP model was moderate (with an overall Kappa of 0.601), which increased to extremely strong after assistance (with an overall Kappa of 0.964); and the consistency of the RM model before and after assistance was also relatively strong (with an overall Kappa of 0.792 before and 0.798 after). Conclusion:The deep learning system accurately identifies and classifies PHG features and significantly enhances diagnostic performance of junior endoscopists.

Objective To investigate the spatiotemporal clustering characteristics of the reported incidence of visceral leishmaniasis (VL) in Gansu Province from 1993 to 2023, so as to provide insights into the containment of VL and prevention of VL recurrence. Methods County (district)-level epidemical data of VL in Gansu Province from 1993 to 2023 were collected, and the geographical information database of reported VL incidence in Gansu Province was created according to the county-level administrative code and electronic maps in Gansu Province. In addition, the spatial autocorrelation analysis and hot spot analysis of the reported VL incidence were performed in Gansu Province using the software ArcGIS 10.8. Results A total of 2 597 VL cases were reported in Gansu Province from 1993 to 2023, with an annual average incidence rate of 3.036/10⁵. Spatial autocorrelation analysis showed spatial clustering of the reported VL incidence in Gansu Province (Moran’s I = 0.605, Z = 5.240, P < 0.001), appearing high-high clustering features (Getis-Ord G = 0.080, Z = 4.137, P < 0.001), and high-high clustering of the reported incidence of VL was identified in Diebu County, Tanchang County, Zhouqu County and Wenxian County. Hot spot analysis showed hot-spot areas of the reported VL incidence in Tanchang County, Zhouqu County, Wudu District and Wenxian County along the Bailong River basins and cold-spot areas in Qin’an County and Gangu County. Conclusions There was spatial clustering and hot spots of the reported VL incidence in Gansu Province from 1993 to 2023. Intensified surveillance and control is required to prevent the spread of VL.

Objective To analyze the epidemiological characteristics of visceral leishmaniasis in Gansu Province from 2017 to 2023, so as to provide insights into formulation of the visceral leishmaniasis control strategy in the province. Methods All epidemiological features of confirmed and clinically diagnosed cases of visceral leishmaniasis reported in Gansu Province from January 1, 2017 to December 31, 2023 were retrieved from the Chinese Disease Prevention and Control Information System, and the epidemiological characteristics of visceral leishmaniasis cases were analyzed descriptively. Results A total of 280 visceral leishmaniasis cases were reported in 39 counties (cities and districts) of Gansu Province from 2017 to 2023, including 258 local cases reported in 21 endemic counties (districts) and 22 imported cases reported in 18 non-endemic areas. Of the 280 cases, there were 262 cases with mountain type zoonotic visceral leishmaniasis (MT-ZVL), 12 cases with desert-type zoonotic visceral leishmaniasis (DT-ZVL), and 6 cases with unknown type. Re-emerging MT-ZVL occurred in Maiji District, Qinzhou District, Lixian County, Kangxian County, Zhenyuan County, Qin’an County and Yongjing County, and re-emerging DT-ZVL occurred in Dunhuang City, while emerging DT-ZVL occurred in Yumen City. The five counties (districts) reporting the highest number of visceral leishmaniasis cases included Wudu District, Wenxian County, Tanchang County, Zhouqu County and Diebu County, and a total of 220 cases were reported in these five counties, accounting for 78.57% of all visceral leishmaniasis cases in the province. Visceral leishmaniasis cases were reported each month throughout the year, with the peak in July. All reported visceral leishmaniasis cases had ages of 6 months to 81 years, including 50.71% (142/280) under 15 years of age, 49.29% (138/280) at ages of 15 years and older, and of all cases under 15 years of age, children at ages of 0 to 3 years were the most commonly affected (27.14%, 76/280). Among 280 visceral leishmaniasis cases, there were 173 males and 107 females with a male to female ratio of 1.62∶1, and farmer was the most common occupation (40.36%), followed by diaspora children (37.86%). Conclusions The prevalence of visceral leishmaniasis appeared an overall tendency towards a decline in Gansu Province from 2017 to 2023; however, there are still multiple challenges for visceral leishmaniasis control in the province. Reinforced dog monitoring and management, intensified human health education and improved capability building among professionals are recommended to manage the rebounding and spread of visceral leishmaniasis.

ObjectiveTo explore the correlations between botanical characteristics， biological characteristics， growth environment， and medicinal properties of common pteridophyte-derived Chinese medicinal materials， thus providing evidence for the theory of quality evaluation through morphological identification and giving insights into the extensive and reasonable application of pteridophytes in traditional Chinese medicine （TCM）. MethodThe medicine parts， habitats， natures， tastes， and effects of the commonly used pteridophyte-derived Chinese medicinal materials were summarized. The commonly used pteridophyte-derived Chinese medicinal materials were retrieved from the Pharmacopoeia of China， Dictionary of Chinese Materia Medica， and related literature. Excel 2016， ChiPlot， Cytoscape 3.7.1， SPSS 21.0， and weiciyun software were used for statistical analysis. ResultThe frequency of the habitats followed the trend of streamside wetland>tree trunk and rock crevices>sunslope>water surface. The frequency of medicinal parts presented the trend of whole plant>rhizome>leaf>dried aboveground part>spore. The frequency of natures was in the order of cool>cold>plain>warm>hot， and that of tastes was in an order of bitter>pungent>sweet>bland>salty. The frequency of meridian tropism followed the trend of liver meridian>stomach meridian>lung meridian>kidney meridian>bladder meridian>heart meridian>large intestine meridian>spleen meridian>small intestine meridian. The effects of the pteridophyte-derived Chinese medicinal materials followed a frequency trend of clearing heat and detoxifying>promoting urination and relieving stranguria>cooling blood and stopping bleeding>activating blood and resolving stasis>dispelling wind and eliminating dampness. ConclusionThe pteridophyte-derived Chinese medicinal materials mainly have a cool nature， a bitter taste， and tropism to the liver meridian. Whole plants and roots are mainly used for medicinal purposes， and most of these plants grow in the wetlands near rivers， under trees， and in tree trunk and rock crevices. The main effects of these medicinal materials are clearing heat and detoxifying， dispelling wind and removing dampness， cooling blood and stopping bleeding， activating blood and resolving stasis， and soothing meridians and dredging collaterals. There are certain correlations between the structures， habitats， medicinal parts， and effects of pteridophyte-derived Chinese medicinal materials， which provide reference for the development and utilization of pteridophyte-derived Chinese medicinal material resources.