Objective To evaluate the molluscicidal effect of niclosamide ethanolamine salt powder?granula(PG)against Oncomelania hupensis. Methods The molluscicidal experiment was carried out by the dusting method with niclosamide etha?nolamine salt 4%PG. The experiments were respectively done in the laboratory and the tidal flats wetlands. At the same time , the niclosamide ethanolamine salt 4%dustable powder(DP)was as the control group. The single blind method was used for the quality control. The corrected mortality and the median lethal concentration(LC50)were compared between PG and DP in the molluscicidal experiment of the laboratory. The corrected mortality and the reduced rate of snails’density were compared be?tween PG and DP in the tidal flats wetlands. Results The mortality rates of the snails were 96.67%and 100%respectively on 1 d after dusting 4.0 g/m2 of 4% PG and 2.0 g/m2 of 4% DP in the laboratory. The results showed that the mortality rates of the snails were higher with 4%DP than 4%PG in each dosage(t1 d=3.60,P<0.01). The LC50(s) of 1d,3 d,7 d after dusting the molluscicide also showed that the molluscicidal effects of DP were better than PG. The corrected mortality rates were 91.71%, 92.91%,90.57%,85.33%and 71.09%,90.11%,90.13%,85.26%on 3 d,7 d,15 d,30 d after dusting with 4%PG and 4%DP,respectively,in the fields. Statistics showed that the mortality rates of snails were higher on 3 d,7 d after dusting with PG than DP(c23 d=731.57,c27 d=25.90,P<0.01),but there were no significant differences between PG and DP on 15d,30d af?ter dusting(c215 d=0.53,c230 d=0.01,P>0.05). Conclusions 4%PG has both the adsorption of powder and the penetrability of the granules. The molluscicidal effects of 4%PG and 4%DP are almost the same. However,the drift of the powder was still not effectively controlled. This problem need to be further studied.

Objective:To analyze the prognostic risk factors of patients with traumatic pancreatitis (TP) and establish an early combined prediction of multiple indicators model for TP.Methods:Patients admitted to the ICU of the First Affiliated Hospital of Zhengzhou University from June 2017 to June 2022 were collected retrospectively. Based on their prognosis, the patients were divided into two groups: the good prognosis group and the poor prognosis group. The general data such as sex, age, underlying diseases, Glasgow Coma Scale (GCS), acute physiology and chronic health evaluationⅡ (APACHEⅡ), injury severity score (ISS), bedside index for severity in acute pancreatitis (BISAP), and clinical test indices such as blood routine, blood coagulation, blood gas analysis, and liver and kidney function at admission were compared between the two groups. Univariate analysis and multivariate logistic regression analysis were used to screen the early independent predictors of poor prognosis of TP, and the prediction model of TP was established by combining all of the independent indicators. The receiver operating characteristic (ROC) curve of each independent predictor and prediction model was drawn, and the area under the curve (AUC), sensitivity, specificity, and optimal cut-off value were calculated to examine the diagnostic impact of each independent predictor and the combined prediction model.Results:There were statistically significant differences in the complication rate of mental disorders, GCS, APACHE II, combined craniocerebral injury, combined chest injury, activated partial thromboplastin time, fibrin(pro)degradation products, lactate, aspartate aminotransferase, glomerular filtration rate, amylase, lipase, NT-proBNP, myoglobin, procalcitonin, ISS, and BISAP between the good and poor prognosis groups (all P<0.05). Multivariate logistic regression analysis showed that lactate ( OR=1.636, 95% CI: 1.046-2.559), lipase ( OR=1.005, 95% CI: 1.001-1.008), and ISS ( OR=1.161, 95% CI: 1.064-1.266) were independent risk factors influencing the prognosis of patients with TP. Based on the risk factors listed above, a prediction model was created: Logit P=-9.260+0.492×lactate+0.005×lipase+0.149×ISS, and the ROC curve was plotted. The AUC curve of the prediction model was 0.96 (95% CI: 0.91-1.00). Conclusions:Lactate, lipase, and ISS are early independent risk factors associated with the prognosis of TP. Their combined multi-indicator prediction model has an excellent clinical prediction effect, which can provide a clinical reference for early prediction and treatment of TP.

This article interpretsthe expert consensus on venous catheter maintenance, including flushing and locking tube, dressing replacement and catheter maintenance, infusion connectors, catheter removal, education and training, infection control, etc. It is hoped that the expert consensus can provide a reference for clinical nurses to standardize the operations of intravenous catheter maintenance, thereby benefiting patients.

Objective:To investigate the value of fibrinogen to albumin ratio (FAR), creatinine to albumin ratio (CAR) and platelet to lymphocyte ratio (PLR) in predicting the poor prognosis of hyperlipidemic acute pancreatitis (HLAP).Methods:Clinical data of HLAP patients admitted to the hospital from January 2021 to January and December 2023 were retrospectively collected. According to the prognosis, the patients were divided into two groups: good prognosis group and poor prognosis group.The independent risk factors of HLAP in different prognostic groups were obtained by multivariate Logistic regression analysis. Receiver operating characteristic (ROC) curves were plotted to evaluate the prognostic value of FAR, CAR and PLR alone and in combination.Results:A total of 118 patients with HLAP were included, including 69 patients with good prognosis and 49 patients with poor prognosis.The difference of heart rate, lymphocyte, triglyceride, albumin, creatinine, urea nitrogen, blood calcium, blood glucose, C-reactive protein, procalcitonin, fibrinogen, FAR, CAR, PLR, Bedside indicator of acute pancreatitis Severity score, Acute Physiology and Chronic Health status score, hospitalization time assessment between the two groups was statistically significant ( P<0.05). Multivariate Logistic regression analysis showed that FAR (odds ratio ( OR) = 25.949, 95% confidence interval (95% CI):3.190 ~ 211.080, P = 0.002), CAR ( OR = 1.453, 95% CI:1.095 ~ 1.928, P = 0.010) and PLR ( OR = 1.005, 95% CI: 1.001 ~ 1.009, P = 0.020) were independent risk factors for poor prognosis in HLAP patients. ROC curve analysis showed that the area under the ROC curve (AUC) of FAR, CAR and PLR to predict poor prognosis of HLAP patients were 0.823, 0.781 and 0.652, respectively.The AUC of FAR combined with CAR, FAR combined with PLR and CAR combined with PLR were 0.840, 0.845 and 0.849, respectively.The combined ability of FAR, CAR and PLR to predict poor prognosis in HLAP patients was (AUC=0.875,95% CI:0.814 ~ 0.937). When the cut-off value was 0.387, the sensitivity was 83.7%, and the specificity was 79.7%. Conclusions:The prognostic value of FAR, CAR and PLR in HLAP patients is better than that of single or pairwise combination.