A retrospective analysis reveals a predictor of survival for the patient with paraquat intoxication.

Feasible and accurate predictors are urgently needed to evaluate the survival for patients with paraquat poisoning since the high mortality of paraquat poisoning always resulted in the loss of both life and money. Multiple predictors have been developed to predict prognosis of the patients with PQ poisoning, which however heavily depend on the time of admission to hospitals. Here we reported a feasible and accurate prognosis predictor for patients with paraquat poisoning that is independent of the time of admission to hospitals. Patients with paraquat poisoning were enrolled in this study according to the inclusion and exclusion criteria, which were grouped into survivors and non-survivors based on the 90-days follow-up investigation. The concentration of paraquat in serum and urine, and the baseline clinical parameters associated with the injuries of the liver, kidney, and lung were evaluated to predict the survival of these patients by using receiver operating characteristic curve (ROC) analysis, univariate and multivariate cox regression analyses. A total of 114 patients was included in this study with a survival rate of 54.4%. The median survival days of non-survivors were 6.0 (95%Cl: 4.0-7.8). A new predictor, namely paraquat concentration-associated multiorgan injury index (PCAMII), was established by integrating serum and urine paraquat concentration, serum creatinine, alanine aminotransferase, aspartate transaminase, total and direct bilirubin, at different weighting coefficients, with the accuracy of about 90%. The model to predict the survival probability by PCAMII was established with good fitness (R2 = 0.9325), providing the simulated survival rates comparable to the clinical data. PCAMII, which is independent of hospital admission time, is a feasible and accurate marker to predict the survival rate of patients with PQ poisoning.

Plasma profiling of amino acids distinguishes acute gout from asymptomatic hyperuricemia.

Gout and hyperuricemia are highly prevalent metabolic diseases caused by high level of uric acid. Amino acids (AAs) involve in various biochemical processes including the biosynthesis of uric acid. However, the role of AAs in discriminating gout from hyperuricemia remains unknown. Here, we report that the plasma AAs profile can distinguish acute gout (AG) from asymptomatic hyperuricemia (AHU). We established an LC-MS/MS-based method to measure the plasma AAs without derivatization for the AG and AHU patients, and healthy controls. We found that the plasma profiling of AAs separated the AG patients from AHU patients and controls visually in both principal component analysis and orthogonal partial least-squares discriminant analysis (OPLS-DA) models. In addition, L-isoleucine, L-lysine, and L-alanine were suggested as the key mediators to distinguish the AG patients from AHU and control groups based on the S-plot analysis and variable importance in the projection values in the OPLS-DA models, volcano plot, and the receiver operating characteristic curves. In addition, the saturation of monosodium urate in the AA solutions at physiologically mimic status supported the changes in plasma AAs facilitating the precipitation of monosodium urate. This study suggests that L-isoleucine, L-lysine, and L-alanine could be the potential markers to distinguish the AG from AHU when the patients have similar blood levels of uric acid, providing new strategies for the prevention, treatment, and management of acute gout.

Use of Contrast-Enhanced Ultrasound to Study Relationship between Serum Uric Acid and Renal Microvascular Perfusion in Diabetic Kidney Disease.

PURPOSE: To investigate the relationship between uric acid and renal microvascular perfusion in diabetic kidney disease (DKD) using contrast-enhanced ultrasound (CEUS) method. MATERIALS AND METHODS: 79 DKD patients and 26 healthy volunteers were enrolled. Renal function and urine protein markers were tested. DKD patients were subdivided into two groups including a normal serum uric acid (SUA) group and a high SUA group. Contrast-enhanced ultrasound (CEUS) was performed, and low acoustic power contrast-specific imaging was used for quantitative analysis. RESULTS: Normal controls (NCs) had the highest levels of AUC, AUC1, and AUC2. Compared to the normal SUA DKD group, high SUA DKD patients had significantly higher IMAX, AUC, and AUC1 (P < 0.05). DKD patients with low urinary uric acid (UUA) excretion had significantly higher AUC2 compared to DKD patients with normal UUA (P < 0.05). CONCLUSION: Hyperuricemia in DKD patients was associated with a renal ultrasound image suggestive of microvascular hyperperfusion. The CEUS parameter AUC1 holds promise as an indicator for renal microvascular hyperperfusion, while AUC2 might be a useful indicator of declining glomerular filtration rate in DKD patients with decreased excretion of uric acid.

Diagnostic value of quantitative contrast-enhanced ultrasound (CEUS) for early detection of renal hyperperfusion in diabetic kidney disease.

PURPOSE: To investigate the diagnostic value of quantitative contrast-enhanced ultrasound (CEUS) for early detection of renal hyperperfusion in diabetic kidney disease (DKD). MATERIALS AND METHODS: 55 DKD patients with estimated glomerular filtration rate (eGFR) >30 ml/min/1.73 m(2) and 26 normal controls (NCs) were enrolled. Clinical data was well documented. Blood samples were drawn for evaluation of renal function including blood urea nitrogen (BUN), serum creatinine (SCr) and serum uric acid (SUA), and urine samples were assayed for total protein quantification, and various microprotein markers. According to eGFR level, DKD patients were divided into early-stage DKD (eGFR ≥90 ml/min/1.73 m(2), n = 18) and middle-stage DKD (eGFR 30-90 ml/min/1.73 m(2), n = 37). Based on urinary microalbumin/creatinine ratio (MALB/UCR), early-stage DKD patients were further classified into two groups: MALB/UCR <10 g/mol (n = 11) and MALB/UCR ≥10 g/mol (n = 7). Then, CEUS was performed to observe the real-time renal perfusion, and low acoustic power contrast-specific imaging was used for quantitative analysis. RESULTS: The renal perfusion images of CEUS were well developed successively. The corresponding perfusion curves based on echo-power signals in time series were constructed. Quantitative analysis showed that area under the descending curve (AUC2) was significantly increased in early-stage DKD compared to middle-stage DKD (p < 0.05), but AUC showed no significant difference. Further comparison between different MALB/UCR levels of early-stage DKD showed that patients with MALB/UCR ≥10 g/mol had significantly increased levels of AUC, AUC2 and proteinuria than patients with low MALB/UCR (p < 0.05). Also, high MALB/UCR DKD patients had increased proteinuria but similar eGFR compared to low MALB/UCR patients. CONCLUSION: Renal microvascular hyperperfusion may be responsible for overt proteinuria until decline of renal filtration in DKD. AUC2 could be an early and sensitive marker for early renal injury and renal microvascular hyperperfusion in DKD.