Clinical Risk Predictors Research Articles

Comprehensive Review of Future Liver Remnant (FLR) Assessment and Hypertrophy Techniques Before Major Hepatectomy: How to Assess and Manage the FLR.

The regenerative capacities of the liver and improvements in surgical techniques have expanded the possibilities of resectability. Liver resection is often the only curative treatment for primary and secondary malignancies, despite the risk of post-hepatectomy liver failure (PHLF). This serious complication (with a 50% mortality rate) can be avoided by better assessment of liver volume and function of the future liver remnant (FLR). The aim of this review was to understand and assess clinical, biological, and imaging predictors of PHLF risk, as well as the various hypertrophy techniques, to achieve an adequate FLR before hepatectomy. We reviewed the state of the art in liver regeneration and FLR hypertrophy techniques. The use of new biological scores (such as the aspartate aminotransferase/platelet ratio index + albumin-bilirubin [APRI+ALBI] score), concurrent utilization of 99mTc-mebrofenin scintigraphy (HBS), or dynamic hepatocyte contrast-enhanced MRI (DHCE-MRI) for liver volumetry helps predict the risk of PHLF. Besides portal vein embolization, there are other FLR optimization techniques that have their indications in case of risk of failure (e.g., associating liver partition and portal vein ligation for staged hepatectomy, liver venous deprivation) or in specific situations (transarterial radioembolization). There is a need to standardize volumetry and function measurement techniques, as well as FLR hypertrophy techniques, to limit the risk of PHLF.

Body mass index and the prevalence of high-risk colorectal adenomas in a population undergoing screening colonoscopy in Alberta, Canada.

There is limited evidence regarding body mass index (BMI) as an early marker of high-risk adenoma (HRA) at the time of screening colonoscopy. Because high-risk adenomas (HRA) can develop into colorectal cancer (CRC), BMI could serve as an important clinical predictor of future risk of CRC. We examined data from 1831 adults undergoing screening colonoscopy at the Forzani & MacPhail Colon Cancer Screening Center in Alberta, Canada. We fit multivariable logistic regression models to examine the association between BMI and HRA. Non-linear relationships for BMI on HRA were also evaluated using restricted cubic splines. The mean BMI in patients with HRA was 28.2kg/m2 compared to 27.4kg/m2 in patients without adenomas (t test: p=0.003). In the adjusted models, those with a BMI over 30kg/m2 had 1.45 (95% CI 1.05-2.00) times the odds of HRA detected during colonoscopy compared to those with a BMI below 25kg/m2. Examining BMI as continuous, the odds of HRA were 1.20 (95% CI 1.04-1.37) times higher for every 5kg/m2 increase in BMI. The findings of this study suggest that excess body mass is associated with higher risk of HRA among a screening population and may be useful an early marker of future disease.

Reference values of carotid intima-media thickness and arterial stiffness in Chinese adults based on ultrasound radio frequency signal: A nationwide, multicenter study.

Carotid intima-media thickness (IMT) and diameter, stiffness, and wave reflections, are independent and important clinical biomarkers and risk predictors for cardiovascular diseases. The purpose of the present study was to establish nationwide reference values of carotid properties for healthy Chinese adults and to explore potential clinical determinants. A total of 3053 healthy Han Chinese adults (1922 women) aged 18-79years were enrolled at 28 collaborating tertiary centers throughout China between April 2021 and July 2022. The real-time tracking of common carotid artery walls was achieved by the radio frequency (RF) ultrasound system. The IMT, diameter, compliance coefficient, β stiffness, local pulse wave velocity (PWV), local systolic blood pressure, augmented pressure (AP), and augmentation index (AIx) were then automatically measured and reported. Data were stratified by age groups and sex. The relationships between age and carotid property parameters were analyzed by Jonckheere-Terpstra test and simple linear regressions. The major clinical determinants of carotid properties were identified by Pearson's correlation, multiple linear regression, and analyses of covariance. All the parameters of carotid properties demonstrated significantly age-related trajectories. Women showed thinner IMT, smaller carotid diameter, larger AP, and AIx than men. The β stiffness and PWV were significantly higher in men than women before forties, but the differences reversed after that. The increase rate of carotid IMT (5.5μm/year in women and 5.8μm/year in men) and diameter (0.03mm/year in both men and women) were similar between men and women. For the stiffness and wave reflections, women showed significantly larger age-related variations than men as demonstrated by steeper regression slopes (all P for age by sex interaction <0.05). The blood pressures, body mass index (BMI), and triglyceride levels were identified as major clinical determinants of carotid properties with adjustment of age and sex. The age- and sex-specific reference values of carotid properties measured by RF ultrasound for healthy Chinese adults were established. The blood pressures, BMI, and triglyceride levels should be considered for clinical application of corresponding reference values.

Cell type-specific network analysis in Diversity Outbred mice identifies genes potentially responsible for human bone mineral density GWAS associations.

Genome-wide association studies (GWASs) have identified many sources of genetic variation associated with bone mineral density (BMD), a clinical predictor of fracture risk and osteoporosis. Aside from the identification of causal genes, other difficult challenges to informing GWAS include characterizing the roles of predicted causal genes in disease and providing additional functional context, such as the cell type predictions or biological pathways in which causal genes operate. Leveraging single-cell transcriptomics (scRNA-seq) can assist in informing BMD GWAS by linking disease-associated variants to genes and providing a cell type context for which these causal genes drive disease. Here, we use large-scale scRNA-seq data from bone marrow-derived stromal cells cultured under osteogenic conditions (BMSC-OBs) from Diversity Outbred (DO) mice to generate cell type-specific networks and contextualize BMD GWAS-implicated genes. Using trajectories inferred from the scRNA-seq data, we identify networks enriched with genes that exhibit the most dynamic changes in expression across trajectories. We discover 21 network driver genes, which are likely to be causal for human BMD GWAS associations that colocalize with expression/splicing quantitative trait loci (eQTL/sQTL). These driver genes, including Fgfrl1 and Tpx2, along with their associated networks, are predicted to be novel regulators of BMD via their roles in the differentiation of mesenchymal lineage cells. In this work, we showcase the use of single-cell transcriptomics from mouse bone-relevant cells to inform human BMD GWAS and prioritize genetic targets with potential causal roles in the development of osteoporosis.

Epileptic spasms relapse is associated with response latency but not conventional attributes of post-treatment EEG.

Relapse of epileptic spasms after initial treatment of infantile epileptic spasms syndrome (IESS) is common. However, past studies of small cohorts have inconsistently linked relapse risk to etiology, treatment modality, and EEG features upon response. Using a large single-center IESS cohort, we set out to quantify the risk of epileptic spasms relapse and identify specific risk factors. We identified all children with epileptic spasms at our center using a clinical EEG database. Using the electronic medical record, we confirmed IESS syndrome classification and ascertained treatment, response, time to relapse, etiology, EEG features, and other demographic factors. Relapse-free survival analysis was carried out using Cox proportional hazards regression. Among 599 children with IESS, 197 specifically responded to hormonal therapy and/or vigabatrin (as opposed to surgery or other second-line treatments). In this study, 41 (21%) subjects exhibited relapse of epileptic spasms within 12 months of response. Longer duration of IESS prior to response (>3 months) was strongly associated with shorter latency to relapse (hazard ratio = 3.11; 95% CI 1.59-6.10; p = 0.001). Relapse was not associated with etiology, developmental status, or any post-treatment EEG feature. This study suggests that long duration of IESS before response is the single largest clinical predictor of relapse risk, and therefore underscores the importance of prompt and successful initial treatment. Further study is needed to evaluate candidate biomarkers of epileptic spasms relapse and identify treatments to mitigate this risk. Relapse of infantile spasms is common after initially successful treatment. With study of a large group of children with infantile spasms, we determined that relapse is linked to long duration of infantile spasms. In contrast, relapse was not associated with the cause of infantile spasms, developmental measures, or EEG features at the time of initial response. Further study is needed to identify tools to predict impending relapse of infantile spasms.

Enhanced identification of women at risk for preterm birth via quantitative ultrasound: a prospective cohort study

Historically, clinicians have relied on medical risk factors and clinical symptoms for preterm birth risk assessment. In nulliparous women, clinicians may rely solely on reported symptoms to assess for the risk of preterm birth. The routine use of ultrasound during pregnancy offers the opportunity to incorporate quantitative ultrasound scanning of the cervix to potentially improve assessment of preterm birth risk. This study aimed to investigate the efficiency of quantitative ultrasound measurements at relatively early stages of pregnancy to enhance identification of women who might be at risk for spontaneous preterm birth. A prospective cohort study of pregnant women was conducted with volunteer participants receiving care from the University of Illinois Hospital in Chicago, Illinois. Participants received a standard clinical screening followed by 2 research screenings conducted at 20±2 and 24±2 weeks. Quantitative ultrasound scans were performed during research screenings by registered diagnostic medical sonographers using a standard cervical length approach. Quantitative ultrasound features were computed from calibrated raw radiofrequency backscattered signals. Full-term birth outcomes and spontaneous preterm birth outcomes were included in the analysis. Medically indicated preterm births were excluded from the analysis. Using data from each visit, logistic regression with Akaike information criterion feature selection was conducted to derive predictive models for each time frame based on historical clinical and quantitative ultrasound features. Model evaluations included a likelihood ratio test of quantitative ultrasound features, cross-validated receiver operating characteristic curve analysis, sensitivity, and specificity. On the basis of historical clinical features alone, the best predictive model had an estimated receiver operating characteristic area under the curve of 0.56±0.03. By the time frame of Visit 1, a predictive model using both historical clinical and quantitative ultrasound features provided a modest improvement in the area under the curve (0.63±0.03) relative to that of the predictive model using only historical clinical features. By the time frame of Visit 2, the predictive model using historical clinical and quantitative ultrasound features provided significant improvement (likelihood ratio test, P<.01), with an area under the curve of 0.69±0.03. Accurate identification of women at risk for spontaneous preterm birth solely through historical clinical features has been proven to be difficult. In this study, a history of preterm birth was the most significant historical clinical predictor of preterm birth risk, but the historical clinical predictive model performance was not statistically significantly better than the no-skill level. According to our study results, including quantitative ultrasound yields a statistically significant improvement in risk prediction as the pregnancy progresses.

TCT-38 Long-Term Clinical Outcomes and Risk Predictors for Mortality After Minimally Invasive Aortic Valve Surgery

TCT-38 Long-Term Clinical Outcomes and Risk Predictors for Mortality After Minimally Invasive Aortic Valve Surgery

Multidrug-resistant bacterial infection in adult patients following cardiac surgery: clinical characteristics and risk factors

BackgroundThe prevalence of infections with multidrug-resistant organism (MDRO) pose great challenges for anti-infective therapy. Previous research on MDRO infections after cardiac surgery was limited. Therefore, understanding and mastering the clinical characteristics and risk predictors of MDRO infection after cardiac surgery is of great significance for standardized management of perioperative patients.MethodsThe medical records of adult patients with MDRO infection after cardiac surgery from January 2018 to October 2021 were collected, and patients were divided into MDR infection group (n = 176) and non-MDR infection group (n = 233). Univariate and multivariate regression analysis of variables was performed to determine the risk predictors of MDRO infection.ResultsThe incidence of MDRO infection was 8.6%. Acinetobacter baumannii, Klebsiella pneumoniae and Pseudomonas aeruginosa were the most common, accounting for 37.3%, 23.5% and 18.0%, respectively. The main infection type were lower respiratory tract infection (LTRI = 29.0%). Univariate analysis showed that underwent coronary artery bypass graft (CABG) (P = 0.001) and secondary operation (P = 0.008), pre-infection exposure to vancomycin (P < 0.001) and linezolid (P = 0.002), combination antibiotics (P < 0.001), four antibiotics in combination (P = 0.005), glucocorticoid use (P = 0.029), preoperative hypoalbuminemia (P = 0.003) were risk factors for post-operative MDRO infection. Multivariate regression analysis showed that underwent CABG (OR = 1.228, 95%CI = 1.056∽1.427, P = 0.008), secondary operation (OR = 1.910, 95%CI = 1.131∽3.425, P = 0.015) and pre-infection exposure to linezolid (OR = 3.704, 95%CI = 1.291∽10.629, P = 0.005) were independent risk predictors for MDRO infection. The risk of MDRO infection increased with the length of stay in the ICU (P < 0.001) and the length of stay before diagnosis of infection (P = 0.003), and the difference was statistically significant. Meanwhile, the length of stay after infection (P = 0.005) and the total length of hospital stay (P < 0.001) were significantly longer in the MDRO infection group, and the all-cause mortality was numerically higher in the MDRO infection group (31.3% versus 23.2%).ConclusionsThe morbidity and mortality of MDRO infection was high in adult cardiac surgery, and many risk factors influence the occurrence of MDRO infection. In the future, clinicians should focus on high-risk patients, strengthen multidisciplinary collaboration on infection prevention and control measures, reduce the morbidity and mortality of MDRO infection, and improve the prognosis of in-hospital patients.

Novel Genetic Risk Variants and Clinical Predictors Associated With Primary Sclerosing Cholangitis in Patients With Ulcerative Colitis.

Patients with ulcerative colitis (UC) who are likely to have primary sclerosing cholangitis (PSC) should be identified because PSC can influence UC clinical behavior and outcomes.The aim of this study was to establish a model incorporating clinical and genetic risk predictors that identifies patients with UC at risk of developing PSC. We conducted a retrospective case-control study. Inflammatory bowel disease cohorts from multiple institutions were used as discovery and replicate datasets. Quality control criteria, including minor allele frequency, call rates, Hardy-Weinberg equilibrium, cryptic relatedness, and population stratification (through principal components), were used. Discriminative accuracy was evaluated with area under the receiver operating characteristic curve. Fifty-seven of 581 patients (9.8%) with UC had PSC. Multivariate analysis showed that patients with UC-PSC had more extensive disease (odds ratio [OR], 5.42; P = 1.57E-04), younger diagnosis age (younger than 20 years; OR, 2.22; P = 0.02), and less smoking (OR, 0.42; P = 0.02) than those with UC. After linkage disequilibrium pruning and multivariate analyses, 3 SNPs (rs3131621 at 6p21.33; rs9275596 and rs11244 at 6p21.32) at the HLA region were found associated with a 2- to 3-fold increased risk of PSC. Our model demonstrated good discriminatory power (area under the receiver operating characteristic curve, 88%). Three variants in HLA (6p21.3) region significantly distinguished patients with UC-PSC from patients with UC alone. Once further validated in an independent large cohort, our model could be used to identify patients with UC at risk of PSC, and it could also help guide disease management.

Systematic review of the incidence and clinical risk predictors of atrial fibrillation and permanent pacemaker implantation for bradycardia in Fabry disease

IntroductionFabry disease (FD) is an X-linked lysosomal storage disorder caused by enzyme deficiency, leading to glycosphingolipid accumulation. Cardiac accumulation triggers local tissue injury, electrical instability and arrhythmia. Bradyarrhythmia and atrial...

Correlation of Clinical Risk Scores for Unstable Angina with the Angiographic Extent and Severity of Coronary Artery Disease

Objective: In patients presenting with Unstable Angina the correlation of clinical risk predictors and clinical risk scores with angiographic extent of Coronary Artery Disease (CAD) is less well understood. The objective is to assess the correlation of various clinical risk scores for unstable angina and individual clinical risk factors with the extent and severity of coronary artery disease as assessed by coronary angiography. Materials and Methods: The present study was a single centre, hospital based, observational, cross-sectional, descriptive study conducted at a tertiary care teaching and research institute in South India. One hundred and fifty patients presenting with chest pain consistent with unstable angina were assessed for existence of independent clinical predictors and calculations were done for their 5 clinical risk scores. Coronary angiography was performed in all the patients leading to the generation of Modified Gensini score and its correlation with the various clinical risk scores was done. Results: Presence of dyslipidemia and diabetes were stronger predictors of Modified Gensini score. TIMI, GRACE&amp; HEART risk scores had moderate correlation with angiographic severity while FRISC and PURSUIT scoring systems had a weak correlation. Conclusion: Presence of dyslipidemia and diabetes significantly affect the extent of CAD. Thus their presence in patients presenting with unstable angina assign them to the high risk category. Angiographic extent of CAD was strongly correlated with TIMI, GRACE and HEART risk scores, thus emphasizing on their use in risk stratification and in identifying the category of patients likely to make the most out of an early invasive strategy.

Abstract 5375: Learned phenotypic embeddings enable scalable imputation of high-content molecular data elucidating prognostic chromatin signatures

Abstract Emerging high-content data modalities like functional genomics and spatial proteomics have enormous potential to reveal determinants of phenotypic plasticity that underlie variability in clinical outcomes, but to date these modalities are only collected in modestly sized research cohorts (&amp;lt; 200-400 patients), where we lack power to detect subtype-specific or prognostic signatures. To study intertumor heterogeneity on a much larger scale (&amp;gt;10,000 patients), we developed a machine learning framework based on self-supervised embeddings that allows scalable imputation of high-content data on large standard of care datasets. Our framework starts by learning a phenotypic embedding of tumor state based solely on H&amp;E histology images, allowing the embedding to be trained on large patient cohorts regardless of availability of molecular covariates. It then learns to predict genomic or proteomic labels from the lower-dimensional phenotypic embeddings. This model can be used for imputation in much larger cohorts, where only clinical outcome and histology are available. To demonstrate our method, we use the TCGA ATAC-seq data, which is available for 400 patients across 23 cancer types. By learning self-supervised embeddings of histology, our framework was able to impute ATAC-seq for 5,000 peaks in 11,000 patients across 31 cancer types, with high accuracy in held out samples (R2 = 0.61). To our knowledge, this represents the broadest available pan-cancer chromatin landscape. The imputed ATAC-seq reveals a subset of peaks that are significantly associated with overall survival (OS) in multiple cancer types (e.g., Breast (BC) ATAC-only HR 1.75, p: 8.6E-3). Genes proximal to these peaks are strongly enriched for well characterized oncogenes, and also several novel genes with functions in cellular metabolism and chromatin remodeling whose expression is not known to be prognostic in our disease settings. Finally, we developed models to predict OS from H&amp;E slide embeddings and from imputed ATAC-seq, both pan-cancer and in specific tumor types. Both models significantly outperform baseline stage and molecular subtype clinical risk predictors (e.g., BC baseline HR: 2.44, p: 3E-6 vs. embedding/imputed ATAC HR 3.78, 2E-9, p for improvement 2E-9) and, interestingly, we find that adding an ATAC-seq based risk score to an embedding-based risk score significantly improves disease-specific survival prediction (HCC embedding-only HR: 2.13, p: 8E-5 vs. HCC embedding/imputed ATAC HR: 2.65, p: 1E-6). This suggests that histopathology images are a rich source of prognostic information beyond that which is captured by traditional pathologist grading. Overall, our work highlights the ability to use self-supervised embeddings of histopathology to impute biological covariates on large, standard-of-care cohorts, empowering novel insights into disease mechanisms and patient outcome. Citation Format: Christopher S. Probert, Zachary R. McCaw, Navami Jain, Daphne Koller. Learned phenotypic embeddings enable scalable imputation of high-content molecular data elucidating prognostic chromatin signatures. [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 5375.

Screening for psychosocial risk in caregivers of children with medical complexity during the COVID-19 pandemic: a cross-sectional study

ObjectiveThe primary objective was to quantify psychosocial risk in family caregivers (FCs) of children with medical complexity (CMC) during the COVID-19 pandemic using the Psychosocial Assessment Tool (PAT). The secondary...

Prediction of violent reoffending in people released from prison in England: External validation study of a risk assessment tool (OxRec)

We aimed to externally validate the Oxford Risk of Recidivism (OxRec) tool to estimate 1- and 2-year risk of violent reoffending in people released from prison in England.We identified individuals using administrative data shared between official prison and police services. We extracted information on criminal history, clinical and sociodemographic risk predictors, and outcomes. Predictive ability was examined using measures of calibration and discrimination for predetermined risk thresholds.In total, 1770 individuals (median age = 33 [IQR 27–40]; 92% were male) were identified. 31% and 43% reoffended within 1 and 2 years, respectively. Discrimination was good, with AUCs of 0.71 (95% CI: 0.69-0.74) for 1 year and 0.71 (0.68-0.74) for 2-year follow up. At a pre-specified threshold of 40% for 2-year risk, sensitivity was 77% (74%–80%), specificity 54% (51%–58%), PPV 56% (53%–59%) and NPV 76% (73%–79%). Simple model validation found a systematic underestimation of the probability of reoffending. However, after updating the model, calibration was good.External validations of risk assessment tools can be conducted using linked data between prison and police, and may require recalibration before implementation. In this validation, OxRec had good performance on discrimination and calibration measures. It can be considered to be used to improve decision-making about risk of serious offending and the allocation of resources.

Exploring biopsychosocial correlates of pregnancy risk and pregnancy intention in women with chronic kidney disease

IntroductionWomen with Chronic Kidney Disease (CKD) are at increased risk of adverse pregnancy and renal outcomes. It is unknown how women with CKD understand their pregnancy risk. This nine-centre, cross-sectional study aimed to explore how women with CKD perceive their pregnancy risk and its impact on pregnancy intention, and identify associations between biopsychosocial factors and perception of pregnancy risk and intention.MethodsWomen with CKD in the UK completed an online survey measuring their pregnancy preferences; perceived CKD severity; perception of pregnancy risk; pregnancy intention; distress; social support; illness perceptions and quality of life. Clinical data were extracted from local databases. Multivariable regression analyses were performed. Trial registration: NCT04370769.ResultsThree hundred fifteen women participated, with a median estimated glomerular filtration rate (eGFR) of 64 ml/min/1.73m2 (IQR 56). Pregnancy was important or very important in 234 (74%) women. Only 108 (34%) had attended pre-pregnancy counselling. After adjustment, there was no association between clinical characteristics and women’s perceived pregnancy risk nor pregnancy intention. Women’s perceived severity of their CKD and attending pre-pregnancy counselling were independent predictors of perceived pregnancy risk. Importance of pregnancy was an independent predictor of pregnancy intention but there was no correlation between perceived pregnancy risk and pregnancy intention (r = − 0.002, 95% CI − 0.12 to 0.11).DiscussionKnown clinical predictors of pregnancy risk for women with CKD were not associated with women’s perceived pregnancy risk nor pregnancy intention. Importance of pregnancy in women with CKD is high, and influences pregnancy intention, whereas perception of pregnancy risk does not.Graphical abstract

The role of single-nucleotide polymorphisms of some candidate genes of carbohydrate and fat metabolism in predicting the risk of type 2 diabetes mellitus

Over the past decade, some progress has been made in identifying and characterizing variants of DNA polymorphisms of genes associated with predisposition to type 2 diabetes mellitus (T2DM). The analysis of gene polymorphisms in combination with socio-demographic, clinical and metabolic parameters can be considered as a promising approach to identify high-risk groups for the development of T2DM. The review includes foreign and domestic studies of predictive models for the risk of developing T2DM comprising single-nucleotide polymorphisms, published in the period from 2006 to 2021. The search for the literature sources was carried out on the PubMed platform. The predictive accuracy of polygenic risk scores was assessed by comparing the area under the curve (AUC). The most commonly used clinical predictors of T2DM risk are sex, age, BMI, family history of diabetes, presence of arterial hypertension, waist circumference, waist-to-hip ratio. All genetic risk models for T2DM had lower AUC values than phenotypic (clinical) risk models. The addition of genetic factors has, in turn, improved AUC compared to purely clinical risk models in many studies, which may be a useful tool for primary prevention of T2DM. However, only those polymorphisms that strongly confirm their association with the risk of developing T2DM in different populations studies should be added to predictive risk scales.

Pneumothorax in hospitalized COVID-19 patients with severe respiratory failure: Risk factors and outcome

PNX was described as an uncommon complication in COVID-19 patients but clinical risk predictors and the potential role in patient's outcome are still unclear. We assessed prevalence, risk predictors and mortality of PNX in hospitalized COVID- 19 with severe respiratory failure performing a retrospective observational analysis of 184 patients admitted to our COVID-19 Respiratory Unit in Vercelli from October 2020 to March 2021. We compared patients with and without PNX reporting prevalence, clinical and radiological features, comorbidities, and outcomes. Prevalence of PNX was 8.1% and mortality was >86% (13/15) significantly higher than in patients without PNX (56/169) (P < 0.001). PNX was more likely to occur in patients with a history of cognitive decline (HR: 31.18) who received non-invasive ventilation (NIV) (p < 0.0071) and with low P/F ratio (HR: 0.99, p = 0.004). Blood chemistry in the PNX subgroup compared to patients without PNX showed a significant increase in LDH (420 U/L vs 345 U/L, respectively p = 0.003), ferritin (1111 mg/dl vs 660 mg/dl, respectively p = 0.006) and decreased lymphocytes (HR: 4.440, p = 0.004). PNX may be associated with a worse prognosis in terms of mortality in COVID patients. Possible mechanisms may include the hyperinflammatory status associated with critical illness, the use of NIV, the severity of respiratory failure and cognitive impairment. We suggest, in selected patients showing low P/F ratio, cognitive impairment and metabolic cytokine storm, an early treatment of systemic inflammation in association with high-flow oxygen therapy as a safer alternative to NIV in order to avoid fatalities connected with PNX.

ABO Blood Groups as a Disease Marker to Predict Atrial Fibrillation Recurrence after Catheter Ablation

Chronic inflammation harbors a vulnerable substrate for atrial fibrillation (AF) recurrence after catheter ablation. However, whether the ABO blood types are associated with AF recurrence after catheter ablation is unknown. A total of 2106 AF patients (1552 men, 554 women) who underwent catheter ablation were enrolled retrospectively. The patients were separated into two groups according to the ABO blood types, the O-type (n = 910, 43.21%) and the non-O-type groups (A, B, or AB type) (n = 1196, 56.79%). The clinical characteristics, AF recurrence, and risk predictors were investigated. The non-O type blood group had a higher incidence of diabetes mellitus (11.90 vs. 9.03%, p = 0.035), larger left atrial diameters (39.43 ± 6.74 vs. 38.20 ± 6.47, p = 0.007), and decreased left ventricular ejection fractions (56.01 ± 7.33 vs. 58.65 ± 6.34, p = 0.044) than the O-type blood group. In the non-paroxysmal AF (non-PAF) patients, the non-O-type blood groups have significantly higher incidences of very late recurrence (67.46 vs. 32.54%, p = 0.045) than those in the O-type blood group. The multivariate analysis revealed the non-O blood group (odd ratio 1.40, p = 0.022) and amiodarone (odd ratio 1.44, p = 0.013) were independent predictors for very late recurrence in the non-PAF patients after catheter ablation, which could be applied as a useful disease marker. This work highlighted the potential link between the ABO blood types and inflammatory activities that contribute to the pathogenic development of AF. The presence of surface antigens on cardiomyocytes or blood cells in patients with different ABO blood types will have an impactful role in risk stratification for AF prognosis after catheter ablation. Further prospective studies are warranted to prove the translational benefits of the ABO blood types for the patients receiving catheter ablation.

MiRNA-30d and miR-770-5p as potential clinical risk predictors of Vasoplegic Syndrome in Patients undergoing on-pump coronary artery bypass grafting

The aims of this study were to perform pre-surgery miRNA profiling of patients who develop Vasoplegic syndrome (VS) after coronary artery bypass grafting (CABG) and identify those miRNAs that could be used as VS prognostic tools and biomarkers. The levels of 754 microRNAs (miRNAs) were measured in whole blood samples from a cohort of patients collected right before the coronary artery bypass grafting (CABG) surgery. We compared the miRNA levels of those who developed VS (VASO group) with those who did not (NONVASO group) after surgery. Six miRNAs (hsa-miR-548c-3p, -199b-5p, -383-5p -571 -183-3p, -30d-5p) were increased and two (hsa-1236-3p, and hsa-miR770-5p) were decreased in blood of VASO compared to NONVASO groups. Receiver Operating Characteristic (ROC) curve analysis revealed that a combination of the miRNAs, hsa-miR-30d-5p and hsa-miR-770-5p can be used as VS predictors (AUC = 0.9615, p < 0.0001). The computational and functional analyses were performed to gain insights into the potential role of these dysregulated miRNAs in VS and have identified the “Apelin Liver Signaling Pathway” as the canonical pathway containing the most target genes regulated by these miRNAs. The expression of the combined miRNAs hsa-miR-30d and hsa-miR-770-5p allowed the ability to distinguish between patients who could and could not develop VS, representing a potential predictive biomarker of VS.

Simple CaroTID-VasC score to predict one-year risk of stroke in symptomatic carotid stenosis patients

BackgroundA subset of extracranial symptomatic carotid stenosis (ESCS) patients may fare well on current optimal medical therapy (OMT), and surgery may be avoided in these patients. Therefore, we aimed to develop and validate a stroke risk prediction model to stratify the risk among ESCS patients. MethodsAdult ESCS patients who denied revascularization procedures were enrolled prospectively and prescribed OMT. Patients were followed-up for twelve months after assessing the clinical, imaging, and hemodynamics-based risk predictors at baseline. Cox regression analysis was performed on predictors which were significant in univariate analysis. Beta coefficients of significant predictors in Cox regression were used to generate a numeric score. The model was internally validated using bootstrapping. ResultsA total of 20 (20.2%) out of 99 patients had event recurrence during the follow-up. Transient ischemic attack index event (P = 0.014), diabetes mellitus (P = 0.018), contralateral significant stenosis (P = 0.007), echolucent plaque (P = 0.011), and impaired vasomotor reactivity (P = 0.006) were significant predictors in Cox regression analysis. A points score (0–6) was derived from regression coefficients of the significant predictors. The area under ROC was 0.884 for the developed model and 0.832 for the bootstrapped model. Youden's index divided the score into low-risk (2.2%) and high-risk (35.8%) groups, and the difference in risk was significant (P < 0.001). ConclusionsMost ESCS patients benefited from OMT, and the CaroTID-VasC score was effective in stratifying patients for risk of endpoint occurrence. The developed model may help identify high-risk subgroups of ESCS patients and assist the decision-making of carotid interventions.