Purpose: We aimed to examine whether preoperative lifestyle factors are associated with mortality after cancer surgery.
Methods: This study used data from the National Health Insurance Service database in South Korea. We included all adult patients who underwent major cancer surgery between January 1, 2016, and December 31, 2018. Three lifestyle factors were evaluated preoperatively: smoking status, alcohol consumption, and physical activity.
Results: A total of 48,557 patients who underwent major cancer surgery were included in the final analysis. In the multivariable logistic regression modeling, current smokers showed 1.40-fold higher odds of 90-day mortality after cancer surgery (odds ratio, 1.40; 95% confidence interval, 1.14-1.71; P = 0.001) than never smokers. However, alcohol consumption and physical activity were not associated with 90-day mortality after cancer surgery. In the multivariable Cox regression modeling, current smokers showed 1.25-fold higher odds of 1-year mortality after cancer surgery (hazard ratio, 1.25; 95% confidence interval, 1.13-1.38; P < 0.001) than never smokers. However, alcohol consumption and physical activity were not associated with 1-year mortality after cancer surgery.
Conclusion: In conclusion, current smoking was associated with worse short- and long-term survival outcomes in South Korea, though preoperative alcohol consumption and physical activity levels were not associated with mortality after cancer surgery.
Purpose: Sepsis is one of the most common causes of death after surgery. Several conventional scoring systems have been developed to predict the outcome of sepsis; however, their predictive power is insufficient. The present study applies explainable machine-learning algorithms to improve the accuracy of predicting postoperative mortality in patients with sepsis caused by peritonitis.
Methods: We performed a retrospective analysis of data from demographic, clinical, and laboratory analyses, including the delta neutrophil index (DNI), WBC and neutrophil counts, and CRP level. Laboratory data were measured before surgery, 12-36 hours after surgery, and 60-84 hours after surgery. The primary study output was the probability of mortality. The areas under the receiver operating characteristic curves (AUCs) of several machine-learning algorithms using the Sequential Organ Failure Assessment (SOFA) and Simplified Acute Physiology Score (SAPS) 3 models were compared. 'SHapley Additive exPlanations' values were used to indicate the direction of the relationship between a variable and mortality.
Results: The CatBoost model yielded the highest AUC (0.933) for mortality compared to SAPS3 and SOFA (0.860 and 0.867, respectively). Increased DNI on day 3, septic shock, use of norepinephrine therapy, and increased international normalized ratio on day 3 had the greatest impact on the model's prediction of mortality.
Conclusion: Machine-learning algorithms increase the accuracy of predicting postoperative mortality in patients with sepsis caused by peritonitis.
Purpose: The skeletal muscle index (SMI) at the L3 level is widely used to diagnose sarcopenia. The upper thigh (UT) also reflects changes in whole-body muscle mass, but no study has examined this using the UT to diagnose sarcopenia in liver transplantation (LT). This study aimed to determine an optimal cut-off value for UT-SMI and investigate how sarcopenia diagnosed by UT-SMI correlates with outcomes in LT recipients.
Methods: In this retrospective study of 332 LT patients from 2018 to 2020, we investigated the association between sarcopenia diagnosed by UT-SMI and patient outcomes after LT.
Results: The cut-off values for UT-SMI were 38.3 cm2/m2 for females (area under the curve [AUC], 0.927; P < 0.001) and 46.7 cm2/m2 for males (AUC, 0.898; P < 0.001). The prevalence of sarcopenia diagnosed by UT-SMI was 33.4% in our cohort. Patient and graft survival rates in the UT-SMI sarcopenia group were significantly poorer than those in the UT-SMI non-sarcopenia group (P < 0.001 and P < 0.001). UT-SMI was an independent prognostic factor for patient survival (hazard ratio [HR], 2.182; 95% confidence interval [CI], 1.183-4.025; P = 0.012) and graft survival (HR, 2.227; 95% CI, 1.054-4704; P = 0.036) in our multivariable Cox analysis.
Conclusion: We confirmed that sarcopenia diagnosed by UT-SMI is associated with outcomes in LT recipients. In addition, UT-SMI was identified as an independent prognostic factor for patient survival and graft survival. Therefore, UT-SMI could be a good option for CT-based evaluations of sarcopenia in LT recipients.
Purpose: The purpose of this study was to compare the clinical outcomes of abdominal aortic graft infection (AGI) treated with removal of the graft vs. graft preservation.
Methods: The electronic databases PubMed, Embase, and Cochrane Library for studies that reported on AGI were searched. Observational studies and case series of at least 10 cases that reporting on the prevalence, microbiology, and outcomes of AGI were included.
Results: Our search identified 23 studies that met our inclusion criteria, reporting on a total of 873 patients who underwent open surgical repair (OSR) or endovascular aneurysm repair (EVAR). Of these patients, 833 received graft removal, and 40 received graft preservation. The prevalence of AGI was reported to be 1.0% (95% confidence interval [CI], 0.5%-1.8%) after OSR and 0.4% (95% CI, 0%-1.1%) after EVAR. The pooled estimates of 1-year, 2-year, and 5-year mortality were 28.7% (95% CI, 19.4%-38.8%), 36.6% (95% CI, 24.6%-49.5%), and 51.8% (95% CI, 38.4%-65.1%) in the graft removal group and 16.1% (95% CI, 4.1%-32.2%), 18.5% (95% CI, 5.7%-35.1%), and 50.0% (95% CI, 31.6%-68.4%) in the graft preservation group. The 30-day mortality rate's risk ratio (RR) for graft removal vs. preservation was 0.98 (95% CI, 0.40-2.38), while the 1-year mortality rate's RR was 3.44 (95% CI, 1.60-7.42).
Conclusion: The 30-day mortality rate of AGI treatment was found to be high, whether using graft removal or preservation. In selected patients, implementing antibiotics with graft preservation as an initial management may be helpful in reducing the mortality rate.