Precise fluid administration is important to prevent hypo- or hypervolemia. However, the accuracy of scales marked on intravenous (IV) fluid plastic bags had remained unknown. Ten 1 L sized IV crystalloids were prepared from each of three manufacturers (H, J, and D). At each scale, the actual volume of the IV fluid was measured. Differences with the measured volumes for each scale were investigated between the three manufacturers. All initial total volume was greater than 1 L. Except for the full-filled level, H overfilled, whereas J and D filled less. For J and D, the maximal differences between the scale and the measured volume were about 200 mL. Fluid volumes of each scale were significantly different among the three manufacturers (P < 0.001). It is inaccurate to measure the amount of fluid depending on the IV bag scales. Clinicians must use electronic infusion pumps for accurate fluid administration.

Purpose: Diagnostic biomarkers of pancreatic ductal adenocarcinoma (PDAC) have been used for early detection to reduce its dismal survival rate. However, clinically feasible biomarkers are still rare. Therefore, in this study, we developed an automated multi-marker enzyme-linked immunosorbent assay (ELISA) kit using 3 biomarkers (leucine-rich alpha-2-glycoprotein [LRG1], transthyretin [TTR], and CA 19-9) that were previously discovered and proposed a diagnostic model for PDAC based on this kit for clinical usage. Methods: Individual LRG1, TTR, and CA 19-9 panels were combined into a single automated ELISA panel and tested on 728 plasma samples, including PDAC (n = 381) and normal samples (n = 347). The consistency between individual panels of 3 biomarkers and the automated multi-panel ELISA kit were accessed by correlation. The diagnostic model was developed using logistic regression according to the automated ELISA kit to predict the risk of pancreatic cancer (high-, intermediate-, and low-risk groups). Results: The Pearson correlation coefficient of predicted values between the triple-marker automated ELISA panel and the former individual ELISA was 0.865. The proposed model provided reliable prediction results with a positive predictive value of 92.05%, negative predictive value of 90.69%, specificity of 90.69%, and sensitivity of 92.05%, which all simultaneously exceed 90% cutoff value. Conclusion This diagnostic model based on the triple ELISA kit showed better diagnostic performance than previous markers for PDAC. In the future, it needs external validation to be used in the clinic.