Elevated plasma Galectin-3 is associated with major adverse kidney events and death after ICU admission

Background Galectin-3 (Gal-3) is a proinflammatory and profibrotic protein especially overexpressed after Acute Kidney Injury (AKI). The early renal prognostic value of Gal-3 after AKI in critically ill patients remains unexplored. The objective was to evaluate the prognostic value of plasma level of Gal-3 for Major Adverse Kidney Events (MAKE) and mortality 30 days after ICU admission across AKI stages. Methods This is an ancillary study of a prospective, observational, multicenter cohort (FROG-ICU). AKI was defined using KDIGO definition. Results Two thousand and seventy-six patients had a Gal-3 plasma level measurement at ICU admission. Seven hundred and twenty-three (34.8%) were females and the median age was 63 [51, 74] years. Eight hundred and seven (38.9%) patients developed MAKE, 774 (37.3%) had AKI and mortality rate at 30 days was 22.4% (N = 465). Patients who developed MAKE had higher Gal-3 level at admission compared to patients without (30.2 [20.8, 49.2] ng/ml versus 16.9 [12.7, 24.3] ng/ml, p < 0.001, respectively. The area under the receiver operating characteristic curve of Gal-3 to predict MAKE was 0.76 CI95% [0.74–0.78], p < 0.001. Gal-3 was associated with MAKE (OR 1.80 CI95% [1.68–1.93], p < 0.001, non-adjusted and OR 1.37 CI95% [1.27–1.49], p < 0.001, adjusted). The use of Gal-3 improved prediction performance of prediction model including SAPSII, Screatadm, pNGAL with a NRI of 0.27 CI95%(0.16–0.38), p < 0.001. Median Gal-3 was higher in non-survivors than in survivors at 30 days (29.2 [20.2, 49.2] ng/ml versus 18.8 [13.3, 29.2] ng/ml, p < 0.001, respectively). Conclusion Plasma levels of Gal-3 were strongly associated with renal function, with an increased risk of MAKE and death after ICU admission. Trial registration ClinicalTrials.gov NCT01367093. Registered on 6 June 2011. Graphical abstract

The convergence level and influencing factors of China’s digital economy and real economy based on grey model and PLS- SEM

The paper constructs a research model mainly based on the Deng’s correlation analysis model on the convergence level measurement, the GM (1,1) coordinated development prediction model and PLS-Structural Equation Model (PLS-SEM) analysis model on the influencing factors. The data about China’s digital economy and real economy from 2005 to 2019 (totaled 2,250) is adopted to conduct an empirical analysis of the convergence level from 2005 to 2019 and predict the development trend from 2020 to 2029. The paper could further analyze the influencing factors of convergence, in an attempt to put forward relevant development suggestions. We hope the study could provide an objective reference and theoretical basis for improving the convergence level in China in some extent.