Assessing perceived quality of primary care under hospital-township health centre integration: A cross-sectional study in China

Since the new round of health care reform in 2009, the vertical integration of hospitals and primary health institutions has become widely implemented in China as an efficient method for improving quality of primary care. This study aimed to answer the following questions: (a) What is the perceived quality of township health centres (THCs) under integration? (B) What differences could be observed among the three typical integration models, namely, private hospital-THC integration, public hospital-THC integration, and loose collaboration? Two rounds of cross-sectional surveys were conducted from November 2016 to June 2018. The Chinese version of the Primary Care Assessment Tool was used to evaluate perceived quality of sample THCs, and 1118 adult patients were interviewed in total. Multiple linear regressions were employed to compare the quality scores between two survey rounds and among different integration models after controlling for potential confounders. The results revealed that the quality of care significantly improved under private hospital-THC integration as observed by comparing two survey rounds, while no change or slight changes were observed in the other two models. The difference observed among the three models was that the perceived quality of THCs integrated with private hospitals was worse than that of THCs integrated with public hospitals and THCs under loose collaboration, while no significant difference was observed between public hospital-THC integration and loose collaboration. Increased attention should be given to highlighting the tight integration between hospitals and THCs and the different roles played by private and public hospitals in the current reform.     

Uncertainty evaluation at three spatial scales for the NDVI-based VWC estimation method used in the SMAP algorithm

Vegetation water content (VWC) is the key input parameter for a soil moisture retrieval algorithm based on microwave remote sensing, and VWC uncertainty can limit the estimated accuracy of soil moisture. There has been little research on VWC algorithm development and validation in China, and the uncertainty of the VWC estimation method has not been well evaluated. Therefore, the aim of this study is to evaluate the uncertainty of the VWC estimation method used in the SMAP (Soil Moisture Active Passive) algorithm on three spatial scales (the point-scale, 30 m scale, and 1 km scale) for maize in northeast China. Results from three ground experimental datasets showed that the SMAP VWC estimation method was strongly biased with an average overestimation of 1.16 kg m^?2,1.04 kg m^?2, and 1.13 kg m^?2 for the point-scale, 30 m scale, and 1 km scale respectively, and maximum bias occurred in the mid-stage of maize. Also, a new power relationship between NDVI (Normalized Difference Vegetation Index) and VWC was proposed for the 30 m scale based on Sentinel 2 NDVI and field VWC values from 2017 experiment, with respective R² (coefficient of determination) and Root Mean Squared Error (RMSE) values of 0.80 and 0.67 kg m^?2. The results confirmed that this power relationship was still suitable for VWC estimation at the 1 km scale, and it has smaller bias than the original SMAP VWC method. Future work will be carried out to evaluate the applicability of this VWC estimation method over a lager region. It is expected that it can improve the accuracy of soil moisture by providing high precision VWC input parameters.     

基于剂量组学预测肺癌患者放射性肺炎发生的研究

目的 探讨剂量组学在预测肺癌根治性放疗患者放射性肺炎发生中的应用潜能。方法 回顾性收集行根治性放疗的314例肺癌患者的临床资料、放疗剂量文件、定位及随访CT图像,根据临床资料及影像学随访资料对放射性肺炎进行分级,提取全肺的剂量组学特征,构建机器学习模型。应用1000次自助抽样法（bootstrap）的最小绝对值收敛和选择算子嵌套逻辑回归（LASSO‐LR）及1000次bootstrap的赤池信息量准则（AIC）向后法筛选与放射性肺炎相关的剂量组学特征,随机按照7∶3划分为训练集及验证集,应用逻辑回归建立预测模型,并应用ROC曲线及校正曲线评价模型的性能。结果 共提取120个剂量组学特征,经LASSO‐LR降维筛选得到12个特征进入“特征池”,再经过AIC向后法筛选,最终筛选出6个剂量组学特征进行模型构建,训练集AUC为0.77（95%CI为0.65~0.87）,独立验证集AUC为0.72（95%CI为0.64~0.81）。结论 利用剂量组学建立的预测模型具有预测放射性肺炎发生的潜力,但仍需继续纳入多中心数据及前瞻性数据进一步挖掘剂量组学的应用潜能。     

经自然腔道取标本手术在结直肠外科手术中的应用进展

随着腔镜技术的进一步发展以及微创理念应用于结直肠外科疾病的诊治中,结直肠相关疾病的诊治发生了翻天覆地的变化。由传统的经腹手术到腹腔镜手术、经自然腔道手术,再到经自然腔道取标本手术(NOSES),结直肠疾病的外科诊治在微创领域取得了巨大成果。NOSES技术是目前结直肠外科在微创领域前沿的手术方式之一,它通过经直肠、阴道取标本来避免了腹壁的辅助取标本切口,从而将结直肠外科手术进一步微创化。NOSES技术集传统腹腔镜手术的优势与现代微创外科的理念于一体,它在确保手术效果的基础上集中体现了微创、加速康复外科、功能外科、"无疤"等理念的特点。本文主要就国内外各中心开展NOSES技术在结直肠外科诊治开展中的相关经验、心得和体会进行综述。