Objective To observe the correlation between homocysteine (Hcy) and serum uric acid (SUA) and retinopathy in type 2 diabetes mellitus (T2DM), preliminary study on its predictive value. MethodsA retrospective study. From January 2020 to March 2021, a total of 324 T2DM patients hospitalized in Department of Endocrinology, Cangzhou Central Hospital of Hebei Province were included. Fasting blood glucose (FBG), glycated hemoglobin (HbA1C), triglycerides (TG), low density lipoprotein cholesterol (LDL-C), high density lipoprotein cholesterol (HDL-C), serum creatinine (Scr), blood urea nitrogen (BUN), Hcy, SUA, peripheral blood endothelial progenitor cells (EPC), circulating endothelial cells (CEC) were counted and homeostasis model assessment for insulin resistance (HOMA-IR) was calculated. According to the absence or presence of diabetic retinopathy (DR), the patients were divided into non DR (NDR) group and DR group with 100 and 214 cases, respectively. Clinical data and laboratory biochemical indexes of the two groups were compared and observed. The logistic regression was used to analyze the independent risk factors for DR in T2DM patients. Smooth curve fitting was used to analyze the curve relationship between Hcy, SUA and DR, and ROC area (AUC) of Hcy, SUA; their combined prediction of DR in T2DM patients was calculated by receiver operating characteristic curve (ROC curve), and the predictive value of Hcy and SUA for DR in T2DM patients was evaluated. ResultsDiabetic course (t=5.380), systolic blood pressure (t=2.935), hypertension (χ2=10.248), diabetic nephropathy (χ2=9.515), diabetic peripheral neuropathy (χ2=24.501), FBG (t=3.945), HbA1C (t=3.336) and TG in DR Group (t=2.898), LDL-C (t=3.986), Scr (t=2.139), SUA (t=7.138), HOMA-IR (t=3.237), BUN (t=3.609), Hcy (t=2.363) and CEC (t=19.396) were significantly higher than those in NDR group. The difference was statistically significant (P＜0.05). EPC (t=9.563) and CPC (t=7.684) levels were significantly lower than those of NDR group, and the difference was statistically significant (P＜0.05). Logistic regression analysis showed that diabetes course, SBP, hypertension, FBG, HbA1C, LDL-C, SUA, Hcy, EPC, CPC and CEC were all independent risk factors for developing DR in T2DM patients (P＜0.05). The smooth curve fitting analysis showed that Hcy and SUA were positively correlated with the occurrence of DR. After adjusting for confounding factors, when Hcy≥15 μmol/L, the risk of DR Increased by 14% for every 1 μmol/L increase in Hcy [odds ratio (OR)=0.92, 95% confidence interval (CI) 0.88-0.98, P＜0.05]. When Hcy＜15 μmol/L, there was no significant difference (OR=0.96, 95%CI 0.92-1.08, P＞0.05). When SUA≥304 μmol/L, the risk of DR increased by 17%, every 20 μmol/L SUA increased (OR=0.80, 95%CI 0.68-0.94, P＜0.05). When SUA＜304 μmol/L, the difference was not statistically significant (OR=0.83, 95%CI 0.72-0.95, P＞0.05). ROC curve analysis results showed that the AUC values of Hcy, SUA and Hcy combined with SUA in predicting the occurrence of DR in T2DM patients were 0.775 (95%CI 0.713-0.837, P＜0.001), 0.757 (95%CI 0.680-0.834, P＜0.001) and 0.827 (95%CI 0.786-0.868, P＜0.001). Hcy combined with SUA showed better predictive efficiency. ConclusionsThe abnormal increase of Hcy and SUA levels in T2DM patients are closely related to the occurrence of DR, they are independent risk factors for the occurrence of DR. Hcy combined with SUA has high predictive value for the occurrence of DR.
ObjectiveTo determine the diagnosis method for an elderly male patient with hematuria by means of evidence-based practice, so as to provide references for clinical diagnosis.
MethodWe searched databases including PubMed, EMbase, and The Cochrane Library up to Nov. 2014, to collect relevant diagnostic evidence for elderly patients with hematuria.
ResultsCompared with MRI, CT had higher sensitivity and specificity in determination of lesion location in where the hematuria was caused by tumor.
ConclusionsCT scan may be better for patients with hematuria to determine the location of lesion.
Objective To identify independent risk factors for in-hospital all-cause mortality in patients with sepsis and to integrate them into the quick Sequential Organ Failure Assessment (qSOFA) score to construct modified models, thereby improving the ability of the original qSOFA to predict mortality risk. Methods This retrospective study included adult patients who met the Sepsis-3 criteria for sepsis and were admitted to the Intensive Care Unit or Emergency Intensive Care Unit of Zigong Fourth People’ s Hospital between January 2018 and December 2023. Demographic characteristics, vital signs, comorbidities, and laboratory parameters were collected, and the Sequential Organ Failure Assessment (SOFA) and qSOFA scores were calculated. Multivariable logistic regression analysis was used to identify independent predictors of in-hospital mortality. Independent predictors were dichotomized according to cut-off values derived from receiver operating characteristic (ROC) curves and combined with qSOFA to construct new models. The ROC analysis with bootstrap validation was used to assess predictive performance, and comparative performance was further evaluated using net reclassification improvement (NRI) and integrated discrimination improvement (IDI). Results A total of 218 patients were included. Multivariable logistic regression analysis identified blood urea nitrogen (BUN) [odds ratio (OR)=1.100, 95% confidence interval (CI) (1.040, 1.170)] and qSOFA [OR=2.610, 95%CI (1.450, 4.920)] as independent risk factors for in-hospital mortality, whereas high-density lipoprotein cholesterol (HDL-C) was an independent protective factor [OR=0.250, 95%CI (0.065, 0.841)]. After dichotomization by ROC-derived cut-off values, BUN and HDL-C were incorporated into qSOFA to generate B-qSOFA, H-qSOFA, and BH-qSOFA. Bootstrap ROC analysis showed that BH-qSOFA exhibited the highest discriminatory ability compared with all combined models as well as the conventional SOFA and qSOFA scores [area under the curve=0.803, 95%CI (0.735, 0.863)]. NRI and IDI analyses demonstrated that BH-qSOFA provided incremental prognostic improvement over qSOFA (NRI=0.969, IDI=0.165), B-qSOFA (NRI=0.644, IDI=0.054), and H-qSOFA (NRI=0.804, IDI=0.091) (all P<0.05). Conclusions Elevated BUN and qSOFA and decreased HDL-C are independent predictors of in-hospital mortality in sepsis. The BH-qSOFA model is simple and clinically practical, exhibits superior predictive performance over the original qSOFA. It may serve as a useful early instrument for prognostic risk stratification in patients with sepsis.
Objective To evaluate the effect of epristeride on gross hematuria secondary to transurethral resection of prostate (TURP). Methods A total of 50 patients with gross hematuria secondary to TURP were divided into two groups: 25 patients were treated with routine treatment plus 5 mg epristeride, twice a day for 3 months, while the other 25 only received routine treatment. Results At the 6-month follow-up visit, gross hematuria recurred in 63% of patients in the control group, but in only 30% of patients in the epristeride group. The difference was statistically significant (Plt;0.05). Moreover, the grade of gross hematuria was significantly lower in the epristeride group (Plt;0.05). Conclusion Epristeride appears to be effective in treating gross hematuria secondary to TURP.
