Prediction Model for Postoperative Pressure Injury in Patients with Acute Type A Aortic Dissection.

OBJECTIVE: To establish a risk assessment model to predict postoperative National Pressure Injury Advisory Panel stage 2 or higher pressure injury (PI) risk in patients undergoing acute type A aortic dissection surgery. METHODS: This retrospective assessment included consecutive patients undergoing acute type A aortic dissection surgery in the authors' hospital from September 2017 to June 2021. The authors used LASSO (logistic least absolute shrinkage and selection operator) regression analysis to identify the most relevant variables associated with PI by running cyclic coordinate descent with 10-times cross-validation. The variables selected by LASSO regression analysis were subjected to multivariate logistic analysis. A calibration plot, receiver operating characteristic curve, and decision curve analysis were used to validate the model. RESULTS: There were 469 patients in the study, including 94 (27.5%) with postoperative PI. Ten variables were selected from LASSO regression: body mass index, diabetes, Marfan syndrome, stroke, preoperative skin moisture, hemoglobin, albumin, serum creatinine, platelet, and d-dimer. Four risk factors emerged after multivariate logistic regression: Marfan syndrome, preoperative skin moisture, albumin, and serum creatinine. The area under the receiver operating characteristic curve of the model was 0.765. The calibration plot and the decision curve analysis both suggested that the model was suitable for predicting postoperative PI. CONCLUSIONS: This study built an efficient predictive model that could help identify high-risk patients.

Human aortic smooth muscle cell regulation by METTL3 via upregulation of m6A NOTCH1 modification and inhibition of NOTCH1.

Background: Thoracic aortic dissection (TAD) is a very serious vascular condition that requires immediate treatment. Phenotypic conversion of human aortic smooth muscle cells (HASMCs) has been reported to be a causal factor for TAD development. Genetic variations affecting RNA modification may play a functional role in TAD. In this study, we aimed to explore the potential role of the methyltransferase like 3 (METTL3) and notch homolog 1 (NOTCH1) N6-methyladenosine (m6A) modification mechanisms in HASMCs. Methods: HASMCs were cultured. METTL3 was knocked down and overexpressed. Then, both METTL3 and NOTCH1 were simultaneously knocked down in HASMCs. HASMC proliferation was determined using Cell Counting Kit-8 (CCK-8). METTL3, NOTCH1, α-smooth muscle actin (α-SMA), smooth muscle protein 22-alpha (SM22α), and calponin expressions were monitored with quantitative real-time polymerase chain reaction (qRT-PCR) and Western blotting. An m6A dot blot assay was used to examine the m6A modification levels. The NOTCH1 3' untranslated region (3'UTR) m6A modification was analyzed using SRAMP and RMBase v. 2.0. A methylated RNA immunoprecipitation (MeRIP) assay was used to evaluate the METTL3 overexpression effect on m6A modification of NOTCH1 messenger RNA (mRNA). A dual-luciferase assay was used to investigate the effect of METTL3 binding of the NOTCH1 mRNA m6A modification site. YTH domain family 2 (YTHDF2)-RNA immunoprecipitation (RIP) was used to detect the change in YTHDF2's ability to bind to NOTCH1 mRNA after METTL3 overexpression. Results: Overexpression of METTL3 inhibited α-SMA, SM22α, calponin, and NOTCH1 expressions and promoted HASMC proliferation. Knocking down METTL3 had the opposite effect. The cointerference of the METTL3 and NOTCH1 results suggested that METTL3 regulated NOTCH1, contributing to HASMC phenotypic changes. The MeRIP assay showed that the m6A modification of NOTCH1 mRNA increased after METTL3 overexpression. The dual-luciferase assay indicated that the NOTCH1 mRNA m6A modification site and METTL3 overexpression promoted NOTCH1 mRNA degradation. YTHDF2-RIP further demonstrated that the binding ability of YTHDF2 and NOTCH1 mRNA was enhanced after METTL3 overexpression. Conclusions: METTL3 regulated the phenotypic changes of HASMC by upregulating m6A modification of NOTCH1 and inhibiting NOTCH1.

Inclusion of interleukin-6 improved the performance of postoperative acute lung injury prediction for patients undergoing surgery for thoracic aortic disease.

Background: We studied acute lung injury (ALI) in thoracic aortic disease (TAD) patients and investigated the predictive effect of interleukin-6 (IL-6) in acute lung injury after thoracic aortic disease. Methods: Data on 188 TAD patients, who underwent surgery between January 2016 to December 2021 at our hospital, were enrolled in. We analyzed acute lung injury using two patient groups. Patients with No-ALI were 65 and those with ALI were 123. Univariate logistic, LASSO binary logistic regression model and multivariable logistic regression analysis were performed for acute lung injury. Results: Preoperative IL-6 level was lower (15.80[3.10,43.30] vs. 47.70[21.40,91.60] pg/ml, p < 0.001) in No-ALI group than in ALI group. The cut-off points, determined by the ROC curve, were preoperative IL-6 > 18 pg/ml (area under the curve: AUC = 0.727). Univariate logistic regression analysis showed 19 features for TAD appeared to be early postoperative risk factors of acute lung injury. Using LASSO binary logistic regression, 19 features were reduced to 9 potential predictors (i.e., Scrpost + PLTpost + CPB > 182 min + D-dimerpost + D-dimerpre + Hypertension + Age > 58 years + IL6 > 18 pg/ml + IL6). Multivariable logistic regression analysis showed that Postoperative creatinine, CPB > 182 min and IL-6 > 18 pg/ml were early postoperative risk factors for ALI after TAD, and the odds ratios (ORs) of postoperative creatinine, CPB > 182 min and IL-6 > 18 pg/ml were 1.006 (1.002-1.01), 4.717 (1.306-19.294) and 2.96 (1.184-7.497), respectively. When postoperative creatinine, CPB > 182 min and IL-6 > 18 pg/ml (AUC = 0.819), the 95% confidence interval [CI] was 0.741 to 0.898. Correction curves were nearly diagonal, suggesting that the nomogram fit well. The DCA curve was then drawn to demonstrate clinical applicability. The DCA curve showed that the threshold probability of a patient is in the range of 30% to 90%. Conclusions: The inclusion of interleukin-6 demonstrated good performance in predicting ALI after TAD surgery.

Prognostic significance of neutrophil count on in-hospital mortality in patients with acute type A aortic dissection.

Backgrounds: The goal of this study was to assess the impact of neutrophil count, in patients with acute type A aortic dissection (ATAAD). Methods: This study retrospectively collected data from patients between September 2017 and June 2021. Youden's index was used to determine the optimal cut-off value for the neutrophil count and patients were divided into two subgroups. A restricted cubic spline (RCS) was used to model the relationship between variables and in-hospital mortality. The least absolute shrinkage and selection operator (LASSO) method and multivariate logistic regression analyses were used to investigate the independent prognostic factors for in-hospital mortality in patients with ATAAD. Results: A total of 467 patients were enrolled in this study. In-hospital mortality was 7.28%. The group with elevated neutrophil counts had significantly higher mortality than the group with decreased neutrophil counts (10.8% vs. 3.2%, P = 0.02). This data shows that elevated neutrophil count was significantly associated with in-hospital mortality (OR 3.07, 95% CI 1.22-7.62, P = 0.02). Conclusions: Neutrophil count is an independent risk factor for in-hospital mortality in patients with ATAAD. It is an effective inflammatory index, which can be individualized for patients.

Significant Prediction of In-hospital Major Adverse Events by D-Dimer Level in Patients With Acute Type A Aortic Dissection.

Background: Acute type A aortic dissection (ATAAD) is a rare, life-threatening condition affecting the aorta. This study explores the relationship between the level of admission D-dimer, which was assessed during the first 2 h from admission, and in-hospital major adverse events (MAE) with ATAAD. Methods: A total of 470 patients with enhanced computed tomography (CT) confirmed diagnosis of ATAAD who underwent operation treatment in Guangdong Provincial People's hospital between September 2017 and June 2021 were enrolled in the present study. The X-tile program was used to determine the optimal D-dimer thresholds for risk. Restricted cubic spline (RSC) was performed to assess the association between D-dimer and endpoint. The perioperative data were compared between the two groups, univariate and multivariate analyses were used to investigate the risk factors of major adverse events (in-hospital mortality, gastrointestinal bleeding, paraplegia, acute kidney failure, reopen the chest, low cardiac output syndrome, cerebrovascular accident, respiratory insufficiency, MODS, gastrointestinal bleeding, and severe infection). Results: Among 470 patients, 151 (32.1%) had MAE. In-hospital mortality was 7.44%. The patients with D-dimer >14,500 ng/ml were more likely to present with acute kidney failure, low cardiac output, cerebrovascular accident, multiple organ dysfunction syndromes (MODS), gastrointestinal bleeding, and severe infection. D-dimer level was an independent risk factor for acute kidney failure (OR 2.09, 95% CI: 1.25-3.51, p = 0.005), MODS (OR 6.40, 95% CI: 1.23-33.39, p = 0.028), gastrointestinal bleeding (OR 17.76, 95% CI: 1.99-158.78, p = 0.010) and mortality (OR 3.17, 95% CI: 1.32-7.63, p = 0.010). Multivariate regression analysis of adverse events also suggested that D-dimer >14,500 ng/ml (OR 1.68, 95% CI: 1.09-2.61, p = 0.020) was the independent risk factor of major adverse events. Conclusions: Increasing D-dimer levels were independently associated with the in-hospital MAE and thus can be used as a useful prognostic biomarker before the surgery.

Prediction model for postoperative severe acute lung injury in patients undergoing acute type A aortic dissection surgery.

OBJECTIVE: This study aimed to establish a risk assessment model to predict postoperative severe acute lung injury (ALI) risk in patients with acute type A aortic dissection (ATAAD). METHODS: Consecutive patients with ATAAD admitted to our hospital were included in this retrospective assessment and placed in the postoperative severe ALI and nonsevere ALI groups based on the presence or absence of ALI within 72 h postoperatively (oxygen index [OI] ≤ 100 mmHg). Patients were then randomly divided into training and validation groups in a ratio of 8:2. Univariate and multivariate stepwise forward logistic regression analyses were used to statistically assess data and establish the prediction model. The prediction model's effectiveness was evaluated via 10-fold cross-validation of the validation group to facilitate the construction of a nomogram. RESULTS: After the screening, 479 patients were included in the study: 132 (27.6%) in the postoperative severe ALI group and 347 (72.4%) in the postoperative nonsevere ALI group. Based on multivariate logistics regression analyses, the following variables were included in the model: coronary heart disease, cardiopulmonary bypass (CPB) ≥ 257.5 min, left atrium diameter ≥ 35.5 mm, hemoglobin ≤ 139.5 g/L, preCPB OI ≤ 100 mmHg, intensive care unit OI ≤ 100 mmHg, left ventricular posterior wall thickness ≥ 10.5 mm, and neutrophilic granulocyte percentage ≥ 0.824. The area under the receiver operating characteristic (ROC) curve of the modeling group was 0.805 and differences between observed and predicted values were not deemed statistically significant via the Hosmer-Lemeshow test (χ2 = 6.037, df = 8, p = .643). For the validation group, the area under the ROC curve was 0.778, and observed and predicted value differences were insignificant when assessed using the Hosmer-Lemeshow test (χ2 = 3.3782, df = 7; p = .848). The average 10-fold cross-validation score was 0.756. CONCLUSIONS: This study established a prediction model and developed a nomogram to determine the risk of postoperative severe ALI after ATAAD. Variables used in the model were easy to obtain clinically and the effectiveness of the model was good.

Severe phenotypes of B3GAT3-related disorder caused by two heterozygous variants: a case report and literature review.

BACKGROUND: Linkeropathies refers to a series of extremely rare hereditary connective tissue diseases affected by various glycosyltransferases in the biosynthesis of proteoglycans. We report for the first time two heterozygous variants of B3GAT3 in a Chinese infant, in whom Marfan syndrome was suspected at birth. CASE PRESENTATION: A 2-month-old boy from a non-consanguineous Chinese family without a family history presented severe phenotypes of joint dislocation, obvious flexion contractures of the elbow, arachnodactyly with slightly adducted thumbs, cranial dysplasia, foot abnormalities and aortic root dilation; Marfan syndrome was suspected at birth. Our patient was the youngest, at the age of 2 months, to experience aortic root dilation. Two B3GAT3 variants, NM_012200.2, c.752T>C, p.V251A and c.47C>A, p.S16*, with heterozygosity were identified in the patient by whole-exome sequencing; the variants were inherited from his parents. During close follow-up, significant changes in the cranial profile and obvious external hydrocephalus were present at the age of 7 months, which differs from previously reported cases. CONCLUSION: We diagnosed a patient with congenital heart defects at an early age with a B3GAT3-related disorder instead of Marfan syndrome and expanded the spectrum of B3GAT3-related disorders. We also provide a literature review of reported B3GAT3 cases; for at least one of the variants, this is the first report of genotype-phenotype correlations in individuals with cardiovascular defects being related to the acceptor substrate-binding subdomain of B3GAT3.

A preoperative mortality risk assessment model for Stanford type A acute aortic dissection.

BACKGROUND: Acute aortic dissection type A is a life-threatening disease required emergency surgery during acute phase. Different clinical manifestations, laboratory tests, and imaging features of patients with acute aortic dissection type A are the risk factors of preoperative mortality. This study aims to establish a simple and effective preoperative mortality risk assessment model for patients with acute aortic dissection type A. METHODS: A total of 673 Chinese patients with acute aortic dissection type A who were admitted to our hospital were retrospectively included. All patients were unable to receive surgically treatment within 3 days from the onset of disease. The patients included were divided into the survivor and deceased groups, and the endpoint event was preoperative death. Multivariable analysis was used to investigate predictors of preoperative mortality and to develop a prediction model. RESULTS: Among the 673 patients, 527 patients survived (78.31%) and 146 patients died (21.69%). The developmental dataset had 505 patients, calibration by Hosmer Lemeshow was significant (χ2 = 3.260, df = 8, P = 0.917) and discrimination by area under ROC curve was 0.8448 (95% CI 0.8007-0.8888). The validation dataset had 168 patients, calibration was significant (χ2 = 5.500, df = 8, P = 0.703) and the area under the ROC curve was 0.8086 (95% CI 0.7291-0.8881). The following independent variables increased preoperative mortality: age (OR = 1.008, P = 0.510), abrupt chest pain (OR = 3.534, P < 0.001), lactic in arterial blood gas ≥ 3 mmol/L (OR = 3.636, P < 0.001), inotropic support (OR = 8.615, P < 0.001), electrocardiographic myocardial ischemia (OR = 3.300, P = 0.001), innominate artery involvement (OR = 1.625, P = 0.104), right common carotid artery involvement (OR = 3.487, P = 0.001), superior mesenteric artery involvement (OR = 2.651, P = 0.001), false lumen / true lumen of ascending aorta ≥ 0.75 (OR = 2.221, P = 0.007). Our data suggest that a simple and effective preoperative death risk assessment model has been established. CONCLUSIONS: Using a simple and effective risk assessment model can help clinicians quickly identify high-risk patients and make appropriate medical decisions.