Early systemic anticoagulation reduces hospital readmission in acute necrotizing pancreatitis patients:A retrospective cohort study

Background:Early systemic anticoagulation(SAC)is a common practice in acute necrotizing pancreatitis(ANP),and its impact on in-hospital clinical outcomes had been assessed.However,whether it affects long-term outcomes is unknown.This study aimed to evaluate the effect of SAC on 90-day readmission and other long-term outcomes in ANP patients.Methods:During January 2013 and December 2018,ANP patients admitted within 7 days from the onset of abdominal pain were screened.The primary outcome was 90-day readmission after discharge.Cox proportional-hazards regression model and mediation analysis were used to define the relationship between early SAC and 90-day readmission.Results:A total of 241 ANP patients were enrolled,of whom 143 received early SAC during their hospitalization and 98 did not.Patients who received early SAC experienced a lower incidence of splanchnic venous thrombosis(SVT)[risk ratio(RR)=0.40,95%CI:0.26-0.60,P<0.01]and lower 90-day readmission with an RR of 0.61(95%CI:0.41-0.91,P=0.02)than those who did not.For the quality of life,patients who received early SAC had a significantly higher score in the subscale of vitality(P=0.03)while the other subscales were all comparable between the two groups.Multivariable Cox regression model showed that early SAC was an independent protective factor for 90-day readmission after adjusting for potential confounders with a hazard ratio of 0.57(95%CI:0.34-0.96,P=0.04).Mediation analysis showed that SVT mediated 37.0%of the early SAC-90-day readmission causality.Conclusions:The application of early SAC may reduce the risk of 90-day readmission in the survivors of ANP patients,and reduced SVT incidence might be the primary contributor.

Aggressive versus controlled fluid resuscitation in acute pancreatitis: A systematic review and meta-analysis of randomized controlled trials

Background:Early fluid resuscitation is one of the fundamental treatments for acute pancreatitis(AP),but there is no consensus on the optimal fluid rate.This systematic review and meta-analysis aimed to compare the efficacy and safety of aggressive vs.controlled fluid resuscitation(CFR)in AP.Methods:The Cochrane Central Register of Controlled Trials(CENTRAL),MEDLINE,Embase,and Web of Science databases were searched up to September 30,2022,for randomized controlled trials(RCTs)comparing aggressive with controlled rates of early fluid resuscitation in AP patients without organ failure on admission.The following keywords were used in the search strategy:"pancreatitis,""fluid therapy,""fluid resuscitation,"and"randomized controlled trial."There was no language restriction.The Grading of Recommendations Assessment,Development and Evaluation(GRADE)framework was used to assess the certainty of evidence.Trial sequential analysis(TSA)was used to control the risk of random errors and assess the conclusions.Results:A total of five RCTs,involving 481 participants,were included in this study.For primary outcomes,there was no significant difference in the development of severe AP(relative risk[RR]:1.87,95%confidence interval[CI]0.95-3.68;P=0.07;n=437;moderate quality of evidence)or hypovolemia(RR:0.98,95%CI:0.32-2.97;P=0.97;n=437;moderate quality of evidence)between the aggressive and CFR groups.A significantly higher risk of fluid overload(RR:3.25,95%CI:1.53-6.93;P<0.01;n=249;low quality of evidence)was observed in the aggressive fluid resuscitation(AFR)group than the controlled group.Additionally,the risk of intensive care unit admission(P=0.02)and the length of hospital stay(P<0.01)as partial secondary outcomes were higher in the AFR group.TSA suggested that more studies were required to draw precise conclusions.Conclusion:For AP patients without organ failure on admission,CFR may be superior to AFR with respect to both efficacy and safety outcomes.Registration:PROSPERO;https://www.crd.york.ac.uk/PROSPERO/;CRD 42022363945.

Transformers in medical image analysis

Transformers have dominated the field of natural language processing and have recently made an impact in the area of computer vision.In the field of medical image analysis,transformers have also been successfully used in to full-stack clinical applications,including image synthesis/reconstruction,registration,segmentation,detection,and diagnosis.This paper aimed to promote awareness of the applications of transformers in medical image analysis.Specifically,we first provided an overview of the core concepts of the attention mechanism built into transformers and other basic components.Second,we reviewed various transformer architectures tailored for medical image applications and discuss their limitations.Within this review,we investigated key challenges including the use of transformers in different learning paradigms,improving model efficiency,and coupling with other techniques.We hope this review would provide a comprehensive picture of transformers to readers with an interest in medical image analysis.