Long-term Trend and Change Point Analysis on Runoff and Sediment Flux into the Sea from the Yellow River during the Period of 1950-2018

2020 ◽  
Vol 99 (sp1) ◽  
pp. 203
Author(s):  
Yi Sui ◽  
Hongyuan Shi ◽  
Zaijin You ◽  
Shouwen Qiao ◽  
Jiacheng Sun
2017 ◽  
Vol 4 (suppl_1) ◽  
pp. S433-S434
Author(s):  
Mutoh Yoshikazu ◽  
Takeshi Nishijima ◽  
Noriko Tanaka ◽  
Yosuke Inaba ◽  
Yoshimi Kikuchi ◽  
...  

Abstract Background Although CD4 count is an important marker for prognosis of patients infected with HIV-1, how long and how much CD4 count will increase after initiation of cART are still unknown. Hence, the aim of this study is, using change point analysis, to examine the long-term CD4 count restoration among well-controlled HIV-1 patients. Methods In this single-center cohort study at AIDS Clinical Center, Tokyo, we examined HIV-1 infected patients who initiated cART between January 2004 and January 2012 and achieved HIV viral load of <200 copies/mL within first 48 weeks of treatment and maintained viral suppression (VL <200 copies/mL) for at least 4 years. cART was defined as combination regimen which consisted of NNRTI, PI, or INSTI, plus two NRTIs. All patients were followed until censoring (defined by VL >200 copies/mL, discontinuation of cART for >30 days, lost to follow-up for >1 year, initiating chemotherapy for malignancy, or death), or at end of the observation period (September 30, 2015). Change point analysis was performed to determine the time point where the restoration of CD4 count becomes plateau. Results Of 752 patients, 708 (94.2%) were male and 89.9% was MSM. The median age was 39.3 years [IQR, 32–45] and the median baseline CD4 count and %CD4 were 172 cells/mm3 [IQR, 61–254], and 13.8% [IQR, 7.7–18.5], respectively. The median follow-up period was 87.0 months [IQR, 65.2–109.2] and 134 were followed over ten years. With change point analysis, both longitudinal increase of CD4 count and %CD4 increased linearly until 78.6 and 62.2 months, respectively. Stratified by baseline CD4 count (<200 cells/mm3, 200–350 cells/mm3, and >350 cells/mm3), CD4 count increased linearly until 76.2, 62.4, and 58.6 months, respectively. Moreover, the percentage of patient who achieved 500 cells/mm3 during study period was 63.5%, 87.2%, and 92.0%, respectively. Conclusion With change point analysis, restoration of CD4 count and %CD4 continued increasing linearly until 6.5 and 5 years of cART, respectively. Patients with lower baseline CD4 count showed longer CD4 count recovery than those with higher baseline CD4; however, their CD4 count did not recover as high as those with higher baseline CD4 count. Disclosures All authors: No reported disclosures.


Author(s):  
Albert E. Beaton ◽  
James R. Chromy
Keyword(s):  

2021 ◽  
Vol 38 (10) ◽  
pp. 1791-1802
Author(s):  
Peiyan Chen ◽  
Hui Yu ◽  
Kevin K. W. Cheung ◽  
Jiajie Xin ◽  
Yi Lu

AbstractA dataset entitled “A potential risk index dataset for landfalling tropical cyclones over the Chinese mainland” (PRITC dataset V1.0) is described in this paper, as are some basic statistical analyses. Estimating the severity of the impacts of tropical cyclones (TCs) that make landfall on the Chinese mainland based on observations from 1401 meteorological stations was proposed in a previous study, including an index combining TC-induced precipitation and wind (IPWT) and further information, such as the corresponding category level (CAT_IPWT), an index of TC-induced wind (IWT), and an index of TC-induced precipitation (IPT). The current version of the dataset includes TCs that made landfall from 1949–2018; the dataset will be extended each year. Long-term trend analyses demonstrate that the severity of the TC impacts on the Chinese mainland have increased, as embodied by the annual mean IPWT values, and increases in TCinduced precipitation are the main contributor to this increase. TC Winnie (1997) and TC Bilis (2006) were the two TCs with the highest IPWT and IPT values, respectively. The PRITC V1.0 dataset was developed based on the China Meteorological Administration’s tropical cyclone database and can serve as a bridge between TC hazards and their social and economic impacts.


Sign in / Sign up

Export Citation Format

Share Document