Humans ; Lung Neoplasms ; genetics ; MicroRNAs ; genetics

Objective? To investigate the application status of transitional care quality indicators for chronic disease in hospitals in China so as to provide a reference for improving transitional care quality evaluation for chronic disease. Methods? We selected nursing managers from 55 hospitals participating a national nursing conference in Shanghai in 2018 as subjects by convenience sampling. The self-designed hospital transitional care quality indicators questionnaire for chronic disease was used to investigate the usage condition of transitional care quality indicators for chronic disease in 55 hospitals. χ2 test was used to compare the utilization ratio of third-level indexes of transitional care of Class Ⅱand Class Ⅲ hospitals. Results? Among 55 hospitals, the highest usage of first-level indexes was structure index (0.813±0.164). The top 3 usage of second-level indexes included hospital readiness (0.932±0.047), patient satisfaction (0.927±0.262) and adverse event rate (0.888±0.143); the bottom 3 usage included health status of patients (0.470±0.112), external hospital extension (0.418±0.280) and connect inside and outside of hospital (0.309±0.149). In importance of second-level indexes, the top 3 usage included the adverse event rate, hospital readiness and material resources; the bottom 3 usage involved the utilization ratio of medical resources, connect inside and outside of hospital and external hospital extension. There were statistical differences in the usage rates of medical resource indexes in ClassⅡand ClassⅢ hospitals, such as readmission rate, visiting rate in emergency department, hospital stay and mortality (χ2=9.406, 5.430, 6.339, 6.339;P＜ 0.05). Conclusions? Among 55 hospitals of China, the transitional care quality evaluation for chronic disease is generally insufficient which is needed to be paid attention to. Hospitals needs to optimize the proportion of indexes, improve and pay more attention to the evaluation for process indicators and outcome indicators, and perfect management and monitor for transitional care.

Objective:To investigate the predictive value of peritoneal protein clearance (Pcl) for cardiovascular events and cardiovascular mortality in peritoneal dialysis (PD) patients.Methods:Eligible PD patients were prospectively enrolled from January 2014 to April 2015 in the PD Center of Renji Hospital, School of Medicine, Shanghai Jiao Tong University. All patients were followed up until death, withdrawing from PD, transferring to other centers, or the end of study period (October 1, 2018). The patients were divided into high Pcl group and low Pcl group by the median Pcl, and the differences of related indicators between the two groups were compared. A multiple linear regression model was used to analyze the influencing factors of Pcl. The Kaplan-Meier method and Log-rank test were used to compare the cumulative survival rates of patients between the two groups. A multivariate Cox regression model was used to estimate the risk of cardiovascular events and cardiovascular mortality in relation to Pcl in PD patients.Results:A total of 271 patients were enrolled, with 135 males (49.8%), age of (56.92±0.84) years old and a median PD duration of 38.77(19.00, 63.10) months. There were 70 patients (25.8%) comorbiding with diabetes and 81 patients (29.9%) with cardiovascular diseases (CVD). The median Pcl of this cohort was 67.93(52.31, 88.36) ml/d. Compared with the low Pcl group (Pcl<67.93 ml/d), the high Pcl group (Pcl≥67.93 ml/d) had older age, and greater proportion of CVD, body mass index (BMI), pulse pressure, brain natriuretic peptide, mass transfer area coefficient of creatinine (MTACcr), and lower serum albumin (all P<0.05). There was no significant difference in gender, dialysis duration, proportion of diabetes, proportion of angiotensin converting enzyme inhibitor and angiotensin receptor blocker, proportion of continuous ambulatory PD, high sensitivity C reactive protein, fluid removal including 24 h urine volume and 24 h ultrafiltration, and residual renal function between the two groups (all P>0.05). Multiple linear regression analysis showed that serum albumin ( β=-0.388, P<0.001), BMI ( β=0.189, P<0.001), and MTACcr ( β=0.247, P<0.001) were independently related to lg(Pcl). During the study period, 55 patients experienced one or more cardiovascular events and 39 patients had cardiovascular mortality. According to Kaplan-Meier analysis, cardiovascular mortality in the high Pcl group was higher than that of low Pcl group (Log-rank χ2=6.902, P=0.009). Multivariate Cox regression analysis showed that, high lg(Pcl) was an independent influencing factor of cardiovascular events in PD patients ( HR=7.654, 95% CI 1.676-34.945, P=0.009). Conclusions:Serum albumin, BMI and MTACcr are independently associated with Pcl, and Pcl is an independent predictor of cardiovascular events in PD patients.