Evaluation of the ACS NSQIP surgical risk calculator in patients undergoing common bile duct exploration.

PURPOSE: The American College of Surgeons National Surgical Quality Improvement Program (ACS NSQIP) surgical risk calculator is a risk stratification tool to help predict risks of postoperative complications, which is important for informed decision-making. The purpose of this study was to evaluate the accuracy of the calculator in predicting postoperative complications in patients undergoing common bile duct (CBD) exploration. METHODS: A retrospective chart review was completed for 305 patients that underwent open and laparoscopic CBD exploration at a single institution from 2010 to 2018. Patient demographics and preoperative risk factors were entered into the calculator, and the predicted complication risks were compared with observed complication rates. Brier score, C-statistic, and Hosmer-Lemeshow regression analysis were used to assess discrimination and calibration. RESULTS: The observed rate exceeded the predicted rate for any complication (35.1% vs. 21%), return to operating room (5.9% vs. 3.6%), death (3.3% vs. 1%), and sepsis (3% vs. 2.4%). The model performed best in predicting serious complication (Brier 0.087, C-statistic 0.818, Hosmer-Lemeshow 0.695), surgical site infection (Brier 0.068, C-statistic 0.670, Hosmer-Lemeshow 0.292), discharge to rehabilitation facility (Brier 0.041, C-statistic 0.907, Hosmer-Lemeshow 0.638), and death (Brier 0.028, C-statistic 0.898, Hosmer-Lemeshow 0.004). In multivariable analysis, there was no statistically significant predicted complication type that affected the type of surgery. CONCLUSION: The calculator was accurate in predicting serious complication, surgical site infection, discharge to rehabilitation facility, and death. However, the model displayed poor predictive ability in all other complications that were analyzed.

Cognitive Alterations in Old Mice Are Associated with Intestinal Barrier Dysfunction and Induced Toll-like Receptor 2 and 4 Signaling in Different Brain Regions.

Emerging evidence implicate the 'microbiota-gut-brain axis' in cognitive aging and neuroinflammation; however, underlying mechanisms still remain to be elucidated. Here, we assessed if potential alterations in intestinal barrier function and microbiota composition as well as levels of two key pattern-recognition receptors namely Toll-like receptor (TLR) 2 and TLR4, in blood and different brain regions, and depending signaling cascades are paralleling aging associated alterations of cognition in healthy aging mice. Cognitive function was assessed in the Y-maze and intestinal and brain tissue and blood were collected in young (4 months old) and old (24 months old) male C57BL/6 mice to determine intestinal microbiota composition by Illumina amplicon sequencing, the concentration of TLR2 and TLR4 ligands in plasma and brain tissue as well as to determine markers of intestinal barrier function, senescence and TLR2 and TLR4 signaling. Cognitive function was significantly impaired in old mice. Also, in old mice, intestinal microbiota composition was significantly altered, while the relative abundance of Gram-negative or Gram-positive bacteria in the small and large intestines at different ages was not altered. Moreover, intestinal barrier function was impaired in small intestine of old mice, and the levels of TLR2 and TLR4 ligands were also significantly higher in both portal and peripheral blood. Furthermore, levels of TLR2 and TLR4 ligands, and downstream markers of TLR signaling were higher in the hippocampal and prefrontal cortex of old mice compared to young animals. Taken together, our results suggest that even in 'healthy' aging, cognitive function is impaired in mice going along with an increased intestinal translocation of TLR ligands and alterations of TLR signaling in several brain regions.

Individualized antimicrobial dose optimization: a systematic review and meta-analysis of randomized controlled trials.

BACKGROUND: Therapeutic drug monitoring and Model-informed precision dosing allow dose individualization to increase drug effectivity and reduce toxicity. OBJECTIVES: To evaluate the available evidence on the clinical efficacy of individualized antimicrobial dosing optimization. METHODS: Data sources: PubMed, Embase, Web of Science, and Cochrane Library databases from database inception to 11 November 2022. STUDY ELIGIBILITY CRITERIA: Published peer-reviewed randomized controlled trials. PARTICIPANTS: Human subjects aged ≥18 years receiving an antibiotic or antifungal drug. INTERVENTIONS: Patients receiving individualized antimicrobial dose adjustment. ASSESSMENT OF RISK OF BIAS: Cochrane risk-of-bias tool for randomized trials. METHODS OF DATA SYNTHESIS: The primary outcome was the risk of mortality. Secondary outcomes included target attainment, treatment failure, clinical and microbiological cure, length of stay, treatment duration, and adverse events. Effect sizes were pooled using a random-effects model. Statistical heterogeneity was assessed by inconsistency testing (I2). RESULTS: Ten randomized controlled trials were included in the meta-analysis (1241 participants; n = 624 in the individualized antimicrobial dosing group and n = 617 in the control group). Individualized antimicrobial dose optimization was associated with a numerical decrease in mortality (risk ratio [RR] = 0.86; 95% CI, 0.71-1.05), without reaching statistical significance. Moreover, it was associated with significantly higher target attainment rates (RR = 1.41; 95% CI, 1.13-1.76) and a significant decrease in treatment failure (RR = 0.70; 95% CI, 0.54-0.92). Individualized antimicrobial dose optimization was associated with improvement, but not significant in clinical cure (RR = 1.33; 95% CI, 0.94-1.33) and microbiological outcome (RR = 1.25; CI, 1.00-1.57), as well as with a significant decrease in the risk of nephrotoxicity (RR = 0.55; 95% CI, 0.31-0.97). CONCLUSIONS: This meta-analysis demonstrated that target attainment, treatment failure, and nephrotoxicity were significantly improved in patients who underwent individualized antimicrobial dose optimization. It showed an improvement in mortality, clinical cure or microbiological outcome, although not significant.