Association of serum cystatin C levels with mortality in patients with acute type A aortic dissection

Post-operative uric acid: a predictor for 30-days mortality of acute type A aortic dissection repair

Background

Hyperuricemia is associated with aortic dissection and cardiovascular diseases. The implication of high serum uric acid (UA) level after acute aortic dissection repair remains unknown. The aim of this study is to explore the role of peri-operative serum UA level in predicting 30-days mortality with acute type A aortic dissection (AAAD) patients, who underwent surgery.

Methods

This study retrospectively enrolled 209 consecutive patients with AAAD, who underwent surgery in Xiangya Hospital from 2017 to 2020. Post-operative laboratory examinations were measured within 24 h after surgery. Univariate analysis and logistic regression analysis were used for predictor finding.

Results

209 consecutive AAAD patients were included, 14.3% (n = 30) were dead within 30 days after surgery. By univariate analysis, we found AAAD repair patients with 30-days mortality had a higher prevalence of cerebral malperfusion, lower pre-operative fibrinogen, longer cardiopulmonary bypass and aortic crossclamp time, and higher post-operative day 1 (POD1) creatinine and urea levels. Both pre-operative (433.80 ± 152.59 vs. 373.46 ± 108.31 mmol/L, p = 0.038) and POD1 (559.78 ± 162.23 vs. 391.29 ± 145.19 mmol/L, p < 0.001) UA level were higher in mortality group than in survival group. In regression model, only cerebral malperfusion (OR, 7.938, 95% CI 1.252–50.323; p = 0.028) and POD1 UA level (OR, 2.562; 95% CI 1.635–4.014; p < 0.001) were independent predictors of 30-days mortality in AAAD repair patients. According to the ROC curve, the POD1 UA level provided positive value for 30-days mortality in AAAD repair patients with 0.799 areas under the curve. The optimum cutoff value selected by ROC curve was 500.15 mmol/L, with a sensitivity of 65% and a specificity of 86%.

Conclusion

Pre- and post-operative hyperuricemia are potentially associated with worsened outcomes in AAAD surgery patients. The POD1 UA level has a predictive role in 30-days mortality in AAAD repair patients.

Early Prediction Model of Acute Aortic Syndrome Mortality in Emergency Departments

Purpose

Acute aortic syndrome is a constellation of life-threatening medical conditions for which rapid assessment and targeted intervention are important for the prognosis of patients who are at high risk of in-hospital death. The current study aims to develop and externally validate an early prediction mortality model that can be used to identify high-risk patients with acute aortic syndrome in the emergency department.

Patients and Methods

This retrospective multi-center observational study enrolled 1088 patients with acute aortic syndrome admitted to the emergency departments of two hospitals in China between January 2017 and March 2021 for model development. A total of 210 patients with acute aortic syndrome admitted to the emergency departments of Peking University Third Hospital between January 2007 and December 2021 was enrolled for model validation. Demographics and clinical factors were collected at the time of emergency department admission. The predictive variables were determined by referring to the results of previous studies and the baseline analysis of this study. The study’s endpoint was in-hospital death. To assess internal validity, we used a fivefold cross-validation method. Model performance was validated internally and externally by evaluating model discrimination using the area under the receiver-operating characteristic curve (AUC). A nomogram was developed based on the binary regression results.

Results

In the development cohort, 1088 patients with acute aortic syndromes were included, and 88 (8.1%) patients died during hospitalization. In the validation cohort, 210 patients were included, and 20 (9.5%) patients died during hospitalization. The final model included the following variables: digestive system symptoms (OR=2.25; P=0.024), any pulse deficit (OR=7.78; P<0.001), creatinine (µmol/L)(OR=1.00; P=0.018), lesion extension to iliac vessels (OR=4.49; P<0.001), pericardial effusion (OR=2.67; P=0.008), and Stanford type A (OR=10.46; P<0.001). The model’s AUC was 0.838 (95% CI 0.784–0.892) in the development cohort and 0.821 (95% CI 0.750–0.891) in the validation cohort, and the Hosmer–Lemeshow test showed p=0.597. The fivefold cross-validation demonstrated a mean accuracy of 0.94, a mean precision of 0.67, and a mean recall of 0.13.

Conclusion

This risk prediction tool uses simple variables to provide robust prediction of the risk of in-hospital death from acute aortic syndrome and validated well in an independent cohort. The tool can help emergency clinicians quickly identify high-risk acute aortic syndrome patients, although further studies are needed for verifying the prospective data and the results of our study.

Admission LDL-C and long-term mortality in patients with acute aortic dissection: a survival analysis in China

BACKGROUND

The 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.

METHODS

We 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.

RESULTS

According 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).

CONCLUSIONS

A lower admission LDL-C level may be associated with an increased risk of long-term mortality in AAD.

ADMISSION CARDIAC TROPONINS PREDICT HOSPITAL MORTALITY IN TYPE A ACUTE AORTIC DISSECTION: A META-ANALYSIS OF ADJUSTED RISK ESTIMATES

Acute aortic dissection (AAD) is a serious medical emergency that requires early diagnosis and rapid treatment. Whether cardiac troponin could be an independent prognostic marker in patients with type A AAD is still unknown. We systematically searched Medline and Scopus to identify all observational cohort studies published before January 2020 that compared outcome (in-hospital mortality) in patients with type A AAD with and without troponin elevation on admission. Four studies with 412 patients were included in final analysis (median age 59 years, 65% of males). A total of 124 (30%) patients died during in-hospital stay, and 73% underwent surgery. Elevated troponins (39.6% of patients) were associated with an increased risk of short-term mortality (adjusted odds ratio 1.26; 95% confidence interval 1.08-1.47), with low heterogeneity among studies (I²=29.81%). Elevated troponins on admission are independently associated with increased in-hospital mortality in type A AAD.

Prognostic factors and prediction models for acute aortic dissection: a systematic review

OBJECTIVE

Our study aimed to systematically review the methodological characteristics of studies that identified prognostic factors or developed or validated models for predicting mortalities among patients with acute aortic dissection (AAD), which would inform future work.

DESIGN/SETTING

A methodological review of published studies.

METHODS

We searched PubMed and EMBASE from inception to June 2020 for studies about prognostic factors or prediction models on mortality among patients with AAD. Two reviewers independently collected the information about methodological characteristics. We also documented the information about the performance of the prognostic factors or prediction models.

RESULTS

Thirty-two studies were included, of which 18 evaluated the performance of prognostic factors, and 14 developed or validated prediction models. Of the 32 studies, 23 (72%) were single-centre studies, 22 (69%) used data from electronic medical records, 19 (59%) chose retrospective cohort study design, 26 (81%) did not report missing predictor data and 5 (16%) that reported missing predictor data used complete-case analysis. Among the 14 prediction model studies, only 3 (21%) had the event per variable over 20, and only 5 (36%) reported both discrimination and calibration statistics. Among model development studies, 3 (27%) did not report statistical methods, 3 (27%) exclusively used statistical significance threshold for selecting predictors and 7 (64%) did not report the methods for handling continuous predictors. Most prediction models were considered at high risk of bias. The performance of prognostic factors showed varying discrimination (AUC 0.58 to 0.95), and the performance of prediction models also varied substantially (AUC 0.49 to 0.91). Only six studies reported calibration statistic.

CONCLUSIONS

The methods used for prognostic studies on mortality among patients with AAD-including prediction models or prognostic factor studies-were suboptimal, and the model performance highly varied. Substantial efforts are warranted to improve the use of the methods in this population.