Preoperative Fasting of More Than 14 Hours Increases the Risk of Time-to-Death after Cardiothoracic Surgery in Children:A Retrospective Cohort Study

Background:Prolonged preoperative fasting can cause hypoglycemia,hyperglycemia,and intravascular volume depletion in children.We aimed to examine whether prolonged preoperative fasting is associated with in-hospital mortality and other morbidities in pediatric cardiothoracic surgery.Methods:This retrospective cohort study included children aged 0–3 years who underwent cardiac surgery between July 2014 and October 2020.The patient demographic data,surgery-related and anesthesia-related factors,and postoperative outcomes,including hypoglycemia,hyperglycemia,sepsis,length of intensive care unit stay,and in-hospital mortality,were recorded.The main exposure and outcome variables were prolonged fasting and time-to-death after surgery,respectively.The associations between prolonged fasting and perioperative death were analyzed using multivariate Cox regression analysis.Results:In total,402 patients were recruited.The incidence of perioperative mortality was 21%(85/402).The proportion of perioperative deaths was significantly higher in the prolonged fasting group than that in the normal fasting group.The proportion of postoperative bacteremia and hypoglycemia was significantly higher in the very prolonged fasting group than that in the prolonged fasting group.After adjusting for preoperative conditions and anesthesia-and surgery-related factors,preoperative prolonged fasting>14.4 h was significantly associated with time-to-death(HR[95%CI]:2.2[1.2,3.9],p=0.036).The 30-day survival rates of fasting time>14.4 h,9.25–14.4 h,and<9.25 h were 0.67(0.55,0.81),0.79(0.72,0.87),and 0.85(0.79,0.91),respectively.Conclusions:Preoperative fasting of more than 14.4 h was associated with a two-fold increase in the hazard rate of time-to-death in children who underwent cardiac surgery.

STRUCTURAL ANALYSIS OF HIGH-INDEX DAE FOR PROCESS SIMULATION

This paper deals with the structural analysis problem of dynamic lumped process high-index differential algebraic equations(DAE)models.The existing graph theoretical method depends on the change in the relative position of underspecified and overspecified subgraphs and has an effect to the value of the differential index for complex models.In this paper,we consider two methods for index reduction of such models by differentiation:Pryce’s method and the symbolic differential elimination algorithm rifsimp.They can remedy the above drawbacks.Discussion and comparison of these methods are given via a class of fundamental process simulation examples.In particular,the efficiency of Pryce’s method is illustrated as a function of the number of tanks in process design.Moreover,a range of nontrivial problems are demonstrated by the symbolic differential elimination algorithm and fast prolongation.