Dataset Information

Serum sodium on admission affects postoperative in-hospital mortality in acute aortic dissection patients.

ABSTRACT:

Background

Acute aortic dissection (AAD) is very fatal without surgical treatment. Higher serum sodium can increase in-hospital mortality of many diseases; however, the effect of serum sodium on postoperative in-hospital mortality in AAD patients remains unknown.

Methods

We collected a total of 415 AAD patients from January 2015 to December 2019. Patients were classified into four categories (Q1-Q4) according to the admission serum sodium quartile. The cox proportional hazards model evaluated the association between serum sodium and in-hospital mortality. All-cause in-hospital mortality was set as the endpoint.

Results

By adjusting many covariates, cox proportional hazards model revealed the in-hospital mortality risk of both Q3 and Q4 groups was 3.086 (1.242-7.671, P = 0.015) and 3.370 (1.384-8.204, P = 0.007) respectively, whereas the risk of Q2 group was not significantly increased. Univariate and multiple Cox analysis revealed that Stanford type A, serum glucose, α-hydroxybutyrate dehydrogenase and serum sodium were risk factors correlated with in-hospital death in AAD patients.

Conclusion

The study indicates that the admission serum sodium of AAD patients has a vital impact on postoperative hospital mortality.

SUBMITTER: Huang P

PROVIDER: S-EPMC8673641 | biostudies-literature | 2021

REPOSITORIES: biostudies-literature

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Publications

Serum sodium on admission affects postoperative in-hospital mortality in acute aortic dissection patients.

Huang Pengfei P Wang Hongyan H Ma Dong D Zhao Yongbo Y Liu Xiao X Su Peng P Zhang Jinjin J Ma Shuo S Pan Zhe Z Shi Juexin J Hou Fangfang F Zhang Nana N Zheng Xiaohui X Liu Nan N Zhang Ling L

PloS one 20211215 12

<h4>Background</h4>Acute aortic dissection (AAD) is very fatal without surgical treatment. Higher serum sodium can increase in-hospital mortality of many diseases; however, the effect of serum sodium on postoperative in-hospital mortality in AAD patients remains unknown.<h4>Methods</h4>We collected a total of 415 AAD patients from January 2015 to December 2019. Patients were classified into four categories (Q1-Q4) according to the admission serum sodium quartile. The cox proportional hazards mod ...[more]

PMID: 34910742

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Project description:Background: Acute aortic dissection is a potentially fatal cardiovascular disorder associated with high mortality. However, current predictive models show a limited ability to efficiently and flexibly detect this mortality risk, and have been unable to discover a relationship between the mortality rate and certain variables. Thus, this study takes an artificial intelligence approach, whereby clinical data-driven machine learning was utilized to predict the in-hospital mortality of acute aortic dissection. Methods: Patients diagnosed with acute aortic dissection between January 2015 to December 2018 were voluntarily enrolled from the Second Xiangya Hospital of Central South University in the study. The diagnosis was defined by magnetic resonance angiography or computed tomography angiography, with an onset time of the symptoms being within 14 days. The analytical variables included demographic characteristics, physical examination, symptoms, clinical condition, laboratory results, and treatment strategies. The machine learning algorithms included logistic regression, decision tree, K nearest neighbor, Gaussian naive bayes, and extreme gradient boost (XGBoost). Evaluation of the predictive performance of the models was mainly achieved using the area under the receiver operating characteristic curve. SHapley Additive exPlanation was also implemented to interpret the final prediction model. Results: A total of 1,344 acute aortic dissection patients were recruited, including 1,071 (79.7%) patients in the survivor group and 273 (20.3%) patients in non-survivor group. The extreme gradient boost model was found to be the most effective model with the greatest area under the receiver operating characteristic curve (0.927, 95% CI: 0.860-0.968). The three most significant aspects of the extreme gradient boost importance matrix plot were treatment, type of acute aortic dissection, and ischemia-modified albumin levels. In the SHapley Additive exPlanation summary plot, medical treatment, type A acute aortic dissection, and higher ischemia-modified albumin level were shown to increase the risk of hospital-based mortality.

Project description:BackgroundThe correlation between rhabdomyolysis and postoperative acute kidney injury has been reported in several surgical procedures. As a good predictor of rhabdomyolysis-related acute kidney injury, an elevated serum myoglobin level was often observed after total aortic arch replacement combined with frozen elephant trunk implantation. However, the correlation between serum myoglobin and acute kidney injury in such patients had not been established.MethodsTotally 398 stanford type A aortic dissection patients who underwent total aortic arch replacement combined with frozen elephant trunk implantation were enrolled in this retrospective study. The correlations between serum myoglobin and acute kidney injury as well as the 30-day mortality were assessed.ResultsOverall, 268(67.3%) patients had acute kidney injury (KDIGO stage 1 or higher) and 75(18.8%) had severe acute kidney injury (KDIGO stage 2&3). Patients who developed acute kidney injury had higher level of perioperative serum myoglobin than patients without acute kidney injury. After adjusting for known acute kidney injury risk factors, logarithmically transformed preoperative serum myoglobin [OR = 1.58 (95% CI, 1.26-1.95), P < 0.001] and postoperative day 1 serum myoglobin [OR = 3.47 (95%CI, 2.27-5.29), P < 0.001] were associated with severe acute kidney injury. These correlation persisted after adjustment for decline in filtration via change in serum creatinine (ΔCr) and biomarkers of cardiac and kidney injury, including N-terminal prohormone of brain natriuretic peptide, cardiac troponin I, creatine kinase-MB, serum creatinine and Cystatin C. Compared with the clinical model, sMb considerably improved the risk discrimination and reclassification for AKI.ConclusionFor stanford type A aortic dissection patients underwent total aortic arch replacement with frozen elephant trunk implantation, serum myoglobin can improve postoperative acute kidney injury risk classification. Rhabdomyolysis may be an important supplement to the existing knowledge on the mechanism of acute kidney injury.

Dataset Information

Serum sodium on admission affects postoperative in-hospital mortality in acute aortic dissection patients.

Background

Methods

Results

Conclusion

Publications

Serum sodium on admission affects postoperative in-hospital mortality in acute aortic dissection patients.

Similar Datasets

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