RESUMEN
BACKGROUND: Most studies had shown a linear relationship between serum albumin (sALB) and the prevalence of diabetic retinopathy (DR). Thus, the purpose of this study is to investigate whether their relationship is non-linear. METHODS: We included 426 patients with type 2 diabetes who were hospitalized in Guangdong Provincial People's Hospital from December 2017 to November 2018. The outcome was the prevalence of DR. A two-piecewise logistics regression model was performed to identify the non-linear relationship between sALB and the prevalence of DR. The inflection point was calculated to determine the saturation effect through the maximum likelihood ratio and a recursive algorithm. RESULTS: DR was diagnosed in 167 of 426 type 2 diabetic patients. The relationship between sALB and DR was nonlinear. When sALB was less than 38.10 g/L, a significant negative association was observed (OR = 0.82; 95% CI, 0.72-0.94; P = 0.0037), while no significant association was observed when sALB was greater than 38.10 g/L (OR = 1.12; 95% CI, 0.92-1.35; P = 0.2637). CONCLUSIONS: The relationship between sALB and the prevalence of DR is non-linear. sALB is negatively associated with the prevalence of DR when sALB is less than 38.10 g/L. Our findings need to be confirmed by further prospective research.
Asunto(s)
Diabetes Mellitus Tipo 2 , Retinopatía Diabética , Humanos , Algoritmos , Estudios Transversales , Diabetes Mellitus Tipo 2/complicaciones , Retinopatía Diabética/sangre , Retinopatía Diabética/diagnóstico , Retinopatía Diabética/metabolismo , Albúmina SéricaRESUMEN
Semiconductor detector is widely used in energy dispersive X-ray fluorescence measurements due to its excellent performance. In this paper, Si-PIN and CdTe semiconductor detectors were studied, performances of the two detectors were compared in material properties, detection efficiency, energy resolution and other aspects. Focused on the performance of the detectors influenced by the thickness of detector sensitive area, energy of incident X-ray, shaping time of post-stage circuit, and analyzed the differences of energy spectrum caused by escape peaks and hole trailing. Aiming at the problem of incomplete hole collection in detector, a digital multi-channel analyzer (DMCA) based on FPGA with rise-time discriminator was designed, it could reduce the influence of hole trailing effectively and improve energy resolution. The experimentation results indicate that the detection efficiency of Si-PIN and CdTe is roughly equal when energy is below 15 keV while CdTe has much higher detection efficiency than Si-PIN when energy is above 15 keV. The optimum forming time of the Si-PIN detector is about 10 µs, and the CdTe detector is about 2.6 µs, so the CdTe detector is more suitable for the high count rate condition. Si-PIN detector has better energy resolution than CdTe detector for different energy incident X-ray. CdTe detector has obvious hole tailing effect and the energy resolution of CdTe detector is significantly improved by using DMCA with rise-time discrimination.
RESUMEN
In order to research the effect of X-ray fluorescence (XRF) analysis on the results in the sample's micro particles, MCNPX models had been established for an X-ray fluorescence analyzer in this paper. It had studied the characteristics of the samples with different particle sizes, the fluorescence peak counts, the peak to total ratios and the peak to source ratios. A micro particle analysis experiment had been designed for its verification. The results showed that: as for the relationship between the fluorescence intensity and the particle sizes, the MCNPX calculations were consistent with the theoretical, but contrary with the experimental results; the reason is that some hypotheses about samples in the MCNPX models were contrary with the actual states; the samples were crushed by grinding to small particles and tableting process, the MCNPX calculations and experimental results can be conversion; when the particle sizes of the samples reached the certain sizes, the fluorescence peak counts, the peak to total ratios and the peak to source ratios were stable value; within a particular size range, the influence of the particle size effects cannot be ignored, otherwise this influence can be ignored. The research methods and conclusions in this paper can provide a technical reference guide for X-ray analysis in practices.
RESUMEN
X-ray tube is the most commonly used equipment in X-ray fluorescence spectrum analysis as excitation source whose primary spectrum has become a major source of the background of X-ray fluorescence spectrum. Background subtraction should go before further analysis of this spectrum. The accuracy of the estimation of the background directly affect the results of subsequent processing steps. In this paper, the tube excitation component of X fluorescence spectrum is analyzed with an estimation method of background intensity against their background characteristics, and structuring theoretical spectral lines based on the measured spectral lines in order to evaluate the effect of spectral processing algorithms. The method utilizes the measured X-ray fluorescence spectrum which does not contain the characteristic peak of the spectrum, In order to estimate the composition of the original spectrum of the X-ray tube. It uses the spectrum that contains the continuous background for interpolating the entire measured spectrum, thereby avoiding overlapping the spectral characteristic peaks or improperly estimating full width at half maximum. This paper compared SNIP, Fourier transform method and the background subtraction method using the measured spectral lines. Using this method to estimate the background is closer to the theoretical background. The results showe that the method for X-ray fluorescence spectrum by X-ray tube excitation is accurate in this article, this method can be used to deduct continuous background, and good applied effectiveness has been achieved in the background subtraction of the actually measured X-ray fluorescence spectrometry.
RESUMEN
Monitoring atmospheric particulate matter requires real-time analysis, such as particulate matter's concentrations, their element types and contents. An analyzer which is based on ß and X rays analysis techniques is designed to meet those demands. Applying ß-ray attenuation law and energy dispersive X-ray fluorescence analysis principle, the paper introduces the analyzer's overall design scheme, structure, FPGA circuit hardware and software for the analyzer. And the analyzer can measure atmospheric particulate matters' concentration, elements and their contents by on-line analysis. Pure elemental particle standard samples were prepared by deposition, and those standard samples were used to set the calibration for the analyzer in this paper. The analyzer can monitor atmospheric particulate matters concentration, 30 kinds of elements and content, such as TSP, PM10 and PM2.5. Comparing the measurement results from the analyzer to Chengdu Environmental Protection Agency's monitoring results for monitoring particulate matters, a high consistency is obtained by the application in eastern suburbs of Chengdu. Meanwhile, the analyzer are highly sensitive in monitoring particulate matters which contained heavy metal elements (such as As, Hg, Cd, Cr, Pb and so on). The analyzer has lots of characteristics through technical performance testing, such as continuous measurement, low detection limit, quick analysis, easy to use and so on. In conclusion, the analyzer can meet the demands for analyzing atmospheric particulate matter's concentration, elements and their contents in urban environmental monitoring.
RESUMEN
The X-ray Fluorescence Analysis(XRFA) is an important and efficient method on the element anylsis and is used in geology, industry and environment protection. But XRFA has a backdraw that the determination limit and accuracy are effected by the matrix of the sample. Now the fundamental parameter is usually used to calculate the content of elements in XRFA, and it is an efficient method if the matrix and net area of characteristic X-ray peak are obtained. But this is invalide in in-stu XRFA. Also the method of net area and the "black material" of sample are the key point of the fundamental parameter method when the Energy Dispersive X-ray Fluorescence Analysis(EDXRFA) method is used in the low content sample. In this paper a advanced fundamental parameter method is discussed. The advanced fundamental parameter method includes the spectra analysis and the fundamental parameter method, which inserts the overlapping peaks separation method into the iteration process of the fundamental parameter method. The advanced method can resolve the net area and the quantitative analysis. The advanced method is used to analyse the standard sample. Compare to the content obtained from the coefficient method, the precision of Cu, Ni and Zn is better than coeffieciency method. The result shows that the advanced method could improve the precision of the EDXRFA, so the advanced method is better than the coefficient method.
RESUMEN
In the energy dispersive X-ray fluorescence spectrum analysis, scintillation detector such as NaI (Tl) detector usually has a low energy resolution at around 8%. The low energy resolution causes problems in spectral data analysis especially in the high background and low counts condition, it is very limited to strip the overlapped spectrum, and the more overlapping the peaks are, the more difficult to peel the peaks, and the qualitative and quantitative analysis can't be carried out because we can't recognize the peak address and peak area. Based on genetic algorithm and immune algorithm, we build a new racial algorithm which uses the Euclidean distance as the judgment of evolution, the maximum relative error as the iterative criterion to be put into overlapped spectrum analysis, then we use the Gaussian function to simulate different overlapping degrees of the spectrum, and the racial algorithm is used in overlapped peak separation and full spectrum simulation, the peak address deviation is in +/- 3 channels, the peak area deviation is no more than 5%, and it is proven that this method has a good effect in energy dispersive X-ray fluorescence overlapped spectrum analysis.
RESUMEN
Waste liquid stored in the containment sumps of nuclear power plants may contain a variety of radionuclides. Real-time monitoring of containment sump waste liquid can ensure that accidents, such as leakage of cooling water, can be avoided. This paper presents the design of a radioactive monitoring system for waste liquid in a containment sump. The detector and the lead-shield in the measurement unit are optimized through Monte Carlo simulations. Experimental verification showed that the background count rate of the measurement chamber in the system was 418.3 cps, and the detection limit of the detection system was 3.01 Bq/L. Distinct gamma-ray characteristic peaks were also observable, demonstrating the system's ability to identify radioactive nuclides in the waste.
RESUMEN
BACKGROUND: Acute kidney injury (AKI) is a severe complication of coronavirus disease 2019 (COVID-19) and is associated with a higher risk of mortality. Understanding the risk factors contributing to COVID-19-related AKI and mortality before vaccination is important for the initiation of preventative measures and early treatment strategies. METHODS: This study included patients aged ≥18 years diagnosed with COVID-19 through polymerase chain reaction from May 2020 to July 2021, admitted in three local hospitals in Taiwan, with an extended follow-up until June 30, 2022. A median follow-up period of 250 days was used to assess AKI development and mortality. AKI was defined according to the Kidney Disease Improving Global Outcomes criteria. Multivariate Cox regression analysis of AKI and mortality-related risk factors was performed. RESULTS: Of the 720 hospitalized patients with COVID-19, 90 (22%) developed AKI. Moreover, 80%, 10.1%, and 8.9% of the patients had stage 1, 2, and 3 AKI, respectively. Patients with stage 1-3 AKI had significantly lower survival rates than those without AKI (p = 0.0012). The mean duration of post-admission AKI occurrence was 9.50 ± 11.32 days. Older age, hypoalbuminemia, and higher D-dimer and ferritin levels were associated with COVID-19 mortality. In COVID-19 AKI, in addition to older age and high D-dimer and ferritin levels, chronic kidney disease emerged as an independent risk factor. CONCLUSION: COVID-19-related AKI develops early, exhibits a temporal association with respiratory failure, and is linked to an unfavorable prognosis. The mortality rate increased according to the AKI stage (p = 0.0012). Age; albumin, D-dimer, and ferritin levels; and the underlying chronic kidney disease status upon admission are crucial factors for predicting AKI development, which increases the mortality risk. Monitoring the renal function not only within 10 days of COVID-19 onset, but also within one month after the disease onset.
RESUMEN
The transmission anode micro X-ray tube is a key component of energy dispersive X-ray Fluorescence Analysis (EDXRFA) as exciting source. So in EDXRFA we hope to get the primary X-ray spectrum which is simply distributed. In the present paper, the authors used the Monte Carlo (MC) method to study the spectrum character of the transmission anode micro X-ray tube with different thickness of target. We cut the spectrum into high energy (5keV-50keV) part and low energy (< 5 keV) part and compared them to each other. The result showed that the flux of high energy part is big and the flux of low energy part is small when the electron energy is 50 keV and the target is 4 microm thick Ag. This is better for EDXRFA.
RESUMEN
In energy dispersive X-ray fluorescence analysis technical analysis, the spectrum information processing has been being the focus of researches, spectrum smooth, peak-search, and peak area processing are the top priority, tA peak search method is based on simulated annealing algorithm principle, and to establish a new search peak model algorithm, this algorithm uses the advantages of the global convergence properties of simulated annealing and the Metropolis criterion is used as a peak valley judgment basis. A new decision criteria on peak valley array is used in this method, too. At the same time, convergence is taken from both ends of the spectrum channel address, it ends up when convergence reaches to the same optimal solution. This paper compared the algorithm with the simple comparison method, third derivative method, and the contrast experiment results, showing that this algorithm has a strong ability on X-ray fluorescence spectrum peak-search and a certain value in the actual production.
RESUMEN
Blood urea nitrogen (BUN) is an indicator of renal function and catabolic status in human body. Diabetic retinopathy (DR) is a major microvascular complication of diabetes mellitus (DM) and a serious threat to the vision of diabetic patients. We included 426 type 2 diabetic patients who visited the endocrinology department of Guangdong Provincial People's Hospital and received an ophthalmology consultation from December 2017 to November 2018. The outcome was the probability of DR in participants. Multivariable logistics analysis was used to confirm the relationship between BUN and the probability of DR. And interaction tests were conducted to find the effects of DM duration on their association. A total of 167 of 426 patients with type 2 diabetes had DR, with a probability of 39.20%. After adjusting for potential confounders, a positive association between BUN and the probability of DR (OR = 1.12; 95% CI 1.03-1.21; P = 0.0107). And a test for interaction between DM duration and BUN on the probability of DR was significant (P = 0.0295). We suggested that in patients with type 2 diabetes, BUN was positively associated with the probability of DR and the association was influenced by DM duration.