Serum sodium on admission affects postoperative in-hospital mortality in acute aortic dissection patients.
Ontology highlight
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 |
REPOSITORIES: biostudies-literature
Similar Datasets
Project description:BackgroundPatients admitted on weekends have higher mortality than those admitted on weekdays. However, whether the "weekend effect" results in a higher mortality after admission for acute aortic dissection (AAD),-classified according to Stanford types-remains unclear. This study aimed to examine the association between admission day and in-hospital mortality in AAD Type A and B.MethodsWe used data from the Japanese registry of all Cardiac and Vascular Diseases Diagnostic Procedure Combination, a nationwide claim-based database with data from 953 certified hospitals, and enrolled in-patients with AAD admitted between April 1, 2012, and March 31, 2016. Based on the admission day, we stratified patients into groups (Weekdays, Saturdays, and Sundays/holidays). The influence of the admission day on in-hospital mortality was assessed via multi-level logistic regression analysis. We also performed a Stanford type-based stratified analysis.ResultsAmong the included 25,641 patients, in-hospital mortality was 16.0%. The prevalence of patients admitted with AAD was relatively higher on weekdays. After adjustment for covariates, patients admitted on a Sunday/holiday showed an increased risk of in-hospital mortality (odds ratio [OR] 1.20; 95% confidence interval [CI] 1.07-1.33, p<0.001) than patients admitted on weekdays. Among patients admitted on a Sunday/holiday, only the subgroup of Stanford Type A showed a significantly increased risk of in-hospital mortality. (Stanford Type A, non-surgery vs. surgery groups: 95% CI 1.06-1.48 vs. 1.17-1.68, p<0.001 for both groups, OR 1.25 vs. 1.41, respectively, Stanford Type B, non-surgery vs. surgery groups: 95% CI 0.64-1.09 vs. 0.40-2.10; p = 0.182 vs. 0.846; OR 0.84 vs. 0.92).ConclusionsIn conclusion, patients with AAD Type A admitted on a Sunday/holiday may have an increased in-hospital mortality risk.
| S-EPMC8601417 | biostudies-literature
Project description:Background: Evidence between admission systolic blood pressure (SBP) and in-hospital deaths in acute type A aortic dissection (AAD) patients is inadequate. Here, we examined the relationship between SBP and in-hospital deaths in AAD patients. Methods: 703 AAD patients were enrolled from January 2014 to December 2018. The independent and dependent variables targeted were admission SBP and in-hospital deaths, respectively. Gender, age, body mass index (BMI), chronic renal insufficiency, smoking, hypertension, diabetes, laboratory indicators, and management were used as covariates. Results: The 703 participants had a mean age of 50.48 ± 11.35. About 76.24% of the participants were male. After adjusting for confounders, there was a negative correlation between AAD patients' admission SBP and in-hospital deaths (OR = 0.88, 95%CI 0.80-0.96). Consequently, a non-linear relationship of point 120 (mmHg) was detected between admission SBP and in-hospital deaths for AAD patients. Confidence intervals and effect sizes of the right (SBP >120 mmHg) and left (SBP ≤ 120 mmHg) sides of the inflection point were 0.96 (0.85-1.09) and 0.67 (0.51-0.88), respectively. The change in the male population and non-diabetes people was more pronounced according to subgroup analysis. Conclusions: Correlation between admission SBP and in-hospital mortality of AAD patients is non-linear. SBP negatively correlated with in-hospital mortality when ≤120 mmHg.
| S-EPMC8329236 | biostudies-literature
Project description:BackgroundHyperlactatemia may be caused by increased production due to tissue hypoxia or non-hypoxia. The aim of this study was first to identify risk factors for postoperative hyperlactatemia (POHL) after Stanford type A acute aortic dissection surgery (AADS) and construct a predictive model, and second to evaluate the impact of POHL on prognosis.MethodsThis retrospective study involved patients undergoing AADS from January 2016 to December 2019 in Wuhan Union Hospital. Multivariate logistic regression analysis was performed to identify independent risk factors for POHL. A nomogram predicting POHL was established based on these factors and was validated in the original dataset. The receiver operating characteristic curve was drawn to assess the ability of postoperative lactate levels to predict the in-hospital mortality.ResultsA total of 188 patients developed POHL after AADS (38.6%). Male gender, surgery history, red blood cell transfusion and cardiopulmonary bypass time were identified as independent predictors. The C-index of the prediction model for POHL was 0.72, indicating reasonable discrimination. The model was well calibrated by visual inspection and goodness-of-fit test (Hosmer-Lemeshow χ2 = 10.25, P = 0.25). Decision and clinical impact curves of the model showed good clinical utility. The overall in-hospital mortality rate was 10.1%. Postoperative lactate levels showed a moderate predictive power for postoperative in-hospital mortality (C-index: 0.72).ConclusionWe developed and validated a prediction model for POHL in patients undergoing AADS, which may have clinical utility in personal risk evaluation and preventive interventions. The POHL could be a good predictor for in-hospital mortality.
| S-EPMC8436469 | biostudies-literature
Project description:Triggering events for acute aortic dissections are incompletely understood. We sought to investigate whether there is an association between admission for acute type A aortic dissection (ATAAD) to the University of Michigan Medical Center and the reported annual influenza activity by the Michigan Department of Health and Human Services. From 1996-2019 we had 758 patients admitted for ATAAD with 3.1 admissions per month during November-March and 2.5 admissions per month during April-October (p?=?0.01). Influenza reporting data by the Michigan Department of Health and Human Services became available in 2009. ATAAD admissions for the period 2009-2019 (n?=?455) were 4.8 cases/month during peak influenza months compared to 3.5 cases/month during non-peak influenza months (p?=?0.001). ATAAD patients admitted during influenza season had increased in-hospital mortality (11.0% vs. 5.8%, p?=?0.024) and increased 30-day mortality (9.7 vs. 5.4%, p?=?0.048). The results point to higher admission rates for ATAAD during months with above average influenza rates. Future studies need to investigate whether influenza virus infection affects susceptibility for aortic dissection, and whether this risk can be attenuated with the annual influenza vaccine in this patient population.
| S-EPMC7070060 | biostudies-literature
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.
| S-EPMC8484712 | biostudies-literature
Project description:Background:Although there are several biomarkers for identifying in-hospital mortality in acute type A aortic dissection (AAD), timely as well as perfect prediction in-hospital mortality is still not attained. Herein, we intend to develop as well to validate an in-hospital mortality risk independent predictive nomogram for AAD patients. Methods:From January 2014 to December 2018, 703 individuals with AAD were involved in this study. They were indiscriminately categorized into training (n=520) and validation (n=183) sets. The univariate and multivariate analyses were used to screen in-hospital mortality predictors from the entire training set data. The predictors were used to establish a nomogram which was confirmed via internal as well as external authentication. This validation included discriminative capacity defined by the receiver operating characteristic (ROC) curve area under the curve (AUC) and the predictive precision via calibration curves. Results:There was 33.43% in-hospital mortality overall incidence. The uric acid, D-dimer, C-reactive protein and management were individually related to in-hospital mortality as per multivariate logistic regression. On the basis of four variables with internal of AUC 0.901 and external validation of AUC 0.903, a nomogram was established. Calibration plots showed that the predicted and actual in-hospital mortality probabilities were fitted well on both internal and external validation. Conclusions:This recommended nomogram can calculate the specific possibility of in-hospital mortality with good precision, high discrimination, and probable clinical application in AAD patients.
| S-EPMC7139052 | biostudies-literature
Project description:Acute aortic dissection occurs due to a primary tear in the aortic intima, with blood from the aortic lumen entering the adjacent diseased media. In the clinical setting, practitioners often hesitate before the use of anti-thrombotic drugs in the acute phase of aortic dissection. Therefore, we examined the clinical course in patients who had already received antithrombotic therapies at the onset of acute aortic dissection, and who were given anti-thrombotic drugs in the acute phase during hospitalization. We retrospectively enrolled 685 consecutive patients with acute aortic dissection (type A/B: 454/231), who were transferred to Kurume University Hospital from 2004 to 2020. In types A and B, there were no significant differences between in-hospital mortality with or without antithrombotic therapies at the onset (14.3% vs. 16.4%, p = 0.66 in type A, 2.6% vs. 7.3%, p = 0.29 in type B). Patients in type A who survived more than a day and were treated with anti-thrombotic drugs during hospitalization had significantly lower in-hospital mortality compared with those who received no anti-thrombotic drugs in the acute phase (2.2% vs. 16.1%, p < 0.001), while there was no significant difference between in-hospital mortality in the two type-B groups (2.4% vs. 4.9%, p = 0.48). Although there were variations in response among patients with acute aortic dissection, anti-thrombotic drugs did not worsen in-hospital mortality for patients with acute aortic dissection, indicating that medical staff should not hesitate to administer anti-thrombotic drugs if indicated.
| S-EPMC9600500 | biostudies-literature
Project description:BackgroundThe level of blood lipid is closely related to prognosis in cardiovascular diseases. This study aims to analyze the effect of serum low-density lipoprotein cholesterol (LDL-C) levels on the long-term mortality in acute aortic dissection (AAD). A lower admission LDL-C level is associated with an increased risk of long-term mortality in AAD.MethodsWe analyzed the data of 284 patients with AAD admitted to the First Affiliated Hospital of Shantou University Medical College from February 2016 to September 2019. Patients were followed up post-discharge. All patients were divided into either an LDL-C low-level group or an LDL-C high-level group according to the optimal cut-off point obtained by the receiver operating characteristic (ROC) curve. The endpoint outcome was long-term mortality in AAD. A survival analysis and Cox proportional hazards model were used.ResultsAccording to the Youden index, the optimal cut-off point for LDL-C was 2.755 mmol/L. The Kaplan-Meier survival analysis curves showed that the long-term mortality of the LDL-C low-level group (<2.755 mmol/L) was significantly higher than that of the LDL-C high-level group (≥2.755 mmol/L) (log-rank χ2=13.912, P<0.001). After multivariate Cox regression analysis, LDL-C <2.755 mmol/L was still significantly associated with long-term mortality in AAD (HR=3.287, 95% CI: 1.637-6.600, P=0.001). In addition, cystatin C was also an independent risk factor for the long-term prognosis of AAD (HR=1.253, 95% CI: 1.057-1.486, P=0.009).ConclusionsA lower admission LDL-C level may be associated with an increased risk of long-term mortality in AAD.
| S-EPMC8422143 | biostudies-literature
Project description:Background:This work explored the prognostic prediction capabilities of ischemia-modified albumin (IMA) in patients suffering from acute aortic dissection (AAD). Methods:We conducted a retrospective analysis using electronic health records. This study included AAD patients admitted to the Second Xiangya Hospital of Central South University from January 2015 to December 2018 in ?24 h from the onset of symptoms to hospital admission. The levels of IMA were recorded upon admittance and the final was the all-cause mortality during hospitalization. Results:This study enrolled 731 AAD patients. Among who, 160 passed away in the course of medication while 571 of them survived. Those who passed away exhibited higher levels of IMA (94.35 ± 26.84 vs. 69.14 ± 14.70, p < 0.001) than the survivors. Following the adjustment confounders, the fully adjusted model showed IMA to be an independent forecastor for in-hospital mortality for AAD patients (OR 1.10, 95% CI 1.08-1.13, p < 0.001). Analysis based on receiver operating characteristic (ROC) revealed that 79.35 ?/ml was the best threshold of IMA level. The area under the curve (AUC) based on this IMA level was 0.854 (95% CI 0.822-0.898) while the specificity and sensitivity to anticipate in-hospital death were 84.8 and 80.6%, respectively. Conclusion:Admission IMA was an independent forecastor for in-hospital mortality among people suffering from AAD.
| S-EPMC6798049 | biostudies-literature
Project description:We built up a risk stratification model to divide acute type A aortic dissection (aTAAD) patients into low- and high-risk groups, further, to evaluate the risk factors for postoperative mortality. A total of 1364 patients from 2010 to 2020 in our center were retrospectively analyzed. More than twenty clinical variables were related with postoperative mortality. The postoperative mortality of the high-risk patients was doubled than the low-risk ones (21.8% vs 10.1%). The increased operation time, combined coronary artery bypass graft, cerebral complications, re-intubation, continuous renal replacement therapy and surgical infection were risk factors of postoperative mortality in low-risk patients. In addition, postoperative lower limbs or visceral malperfusion were risk factors, axillary artery cannulation and moderate hypothermia were protective factors in high-risk patients. A scoring system for quick decision-making is needed to select appropriate surgical strategy in aTAAD patients. For low-risk patients, different surgical treatments can be performed with similar clinical prognosis. Limited arch treatment and appropriate cannulation approach are crucial in high-risk aTAAD patients.
| S-EPMC10199069 | biostudies-literature