RESUMEN

Objective: To predict the optimal cut-off values for screening and predicting metabolic syndrome(MetS) in a middle-aged and elderly Chinese population using 13 obesity and lipid-related indicators, and to identify the most suitable predictors. Methods: The data for this cross-sectional investigation came from the China Health and Retirement Longitudinal Study (CHARLS), including 9457 middle-aged and elderly people aged 45-98 years old. We examined 13 indicators, including waist circumference (WC), body mass index (BMI), waist-height ratio (WHtR), visceral adiposity index (VAI), a body shape index (ABSI), body roundness index (BRI), lipid accumulation product index (LAP), conicity index (CI), Chinese visceral adiposity index (CVAI), triglyceride-glucose index (TyG-index) and their combined indices (TyG-BMI, TyG-WC, TyG-WHtR). The receiver operating characteristic curve (ROC) was used to determine the usefulness of indicators for screening for MetS in the elderly and to determine their cut-off values, sensitivity, specificity, and area under the curve (AUC). Association analysis of 13 obesity-related indicators with MetS was performed using binary logistic regression analysis. Results: A total of 9457 middle-aged and elderly Chinese were included in this study, and the overall prevalence of the study population was 41.87% according to the diagnostic criteria of NCEP ATP III. According to age and gender, the percentage of males diagnosed with MetS was 30.67% (45-54 years old: 30.95%, 55-64 years old: 41.02%, 65-74 years old: 21.19%, ≥ 75 years old: 6.84%). The percentage of females diagnosed with MetS was 51.38% (45-54 years old: 31.95%, 55-64 years old: 39.52%, 65-74 years old: 20.43%, ≥ 75 years old: 8.10%). The predictive power of Tyg-related parameters was more prominent in both sexes. In addition, LAP and CVAI are also good at predicting MetS. ABSI had a poor prediction ability. Conclusions: Among the middle-aged and elderly population in China, after adjusting for confounding factors, all the indicators except ABSI had good predictive power. The predictive power of Tyg-related parameters was more prominent in both sexes. In addition, LAP and CVAI are also good at predicting MetS.

Asunto(s)

RESUMEN

Head and neck squamous cell carcinoma (HNSC) is one of most common malignancies with high mortality worldwide. Importantly, the molecular heterogeneity of HNSC complicates the clinical diagnosis and treatment, leading to poor overall survival outcomes. To dissect the complex heterogeneity, recent studies have reported multiple molecular subtyping systems. For instance, HNSC can be subdivided to four distinct molecular subtypes: atypical, basal, classical, and mesenchymal, of which the mesenchymal subtype is characterized by upregulated epithelial-mesenchymal transition (EMT) and associated with poorer survival outcomes. Despite a wealth of studies into the complex molecular heterogeneity, the regulatory mechanism specific to this aggressive subtype remain largely unclear. Herein, we developed a network-based bioinformatics framework that integrates lncRNA and mRNA expression profiles to elucidate the subtype-specific regulatory mechanisms. Applying the framework to HNSC, we identified a clinically relevant lncRNA LNCOG as a key master regulator mediating EMT underlying the mesenchymal subtype. Five genes with strong prognostic values, namely ANXA5, ITGA5, CCBE1, P4HA2, and EPHX3, were predicted to be the putative targets of LNCOG and subsequently validated in other independent datasets. By integrative analysis of the miRNA expression profiles, we found that LNCOG may act as a ceRNA to sponge miR-148a-3p thereby upregulating ITGA5 to promote HNSC progression. Furthermore, our drug sensitivity analysis demonstrated that the five putative targets of LNCOG were also predictive of the sensitivities of multiple FDA-approved drugs. In summary, our bioinformatics framework facilitates the dissection of cancer subtype-specific lncRNA regulatory mechanisms, providing potential novel biomarkers for more optimized treatment of HNSC.

RESUMEN

Objectives: We performed a virtual screening of olive secoiridoids of the OliveNetTM library to predict SARS-CoV-2 PLpro inhibition. Benchmarked molecular docking protocol that evaluated the performance of two docking programs was applied to execute virtual screening. Molecular dynamics stability analysis of the top-ranked olive secoiridoid docked to PLpro was also carried out. Methods: Benchmarking virtual screening used two freely available docking programs, AutoDock Vina 1.1.2. and AutoDock 4.2.1. for molecular docking of olive secoiridoids to a single PLpro structure. Screening also included benchmark structures of known active and decoy molecules from the DEKOIS 2.0 library. Based on the predicted binding energies, the docking programs ranked the screened molecules. We applied the usual performance evaluation metrices to evaluate the docking programs using the predicted ranks. Molecular dynamics of the top-ranked olive secoiridoid bound to PLpro and computation of MM-GBSA energy using three iterations during the last 50 ps of the analysis of the dynamics in Desmond supported the stability prediction. Results and discussions: Predictiveness curves suggested that AutoDock Vina has a better predictive ability than AutoDock, although there was a moderate correlation between the active molecules rankings (Kendall's correlation of rank (τ) = 0.581). Interestingly, two same molecules, Demethyloleuropein aglycone, and Oleuroside enriched the top 1 % ranked olive secoiridoids predicted by both programs. Demethyloleuropein aglycone bound to PLpro obtained by docking in AutoDock Vina when analyzed for stability by molecular dynamics simulation for 50 ns displayed an RMSD, RMSF<2 Å, and MM-GBSA energy of -94.54 ± 6.05 kcal/mol indicating good stability. Molecular dynamics also revealed the interactions of Demethyloleuropein aglycone with binding sites 2 and 3 of PLpro, suggesting a potent inhibition. In addition, for 98 % of the simulation time, two phenolic hydroxy groups of Demethyloleuropein aglycone maintained two hydrogen bonds with Asp302 of PLpro, specifying the significance of the groups in receptor binding. Conclusion: AutoDock Vina retrieved the active molecules accurately and predicted Demethyloleuropein aglycone as the best inhibitor of PLpro. The Arabian diet consisting of olive products rich in secoiridoids benefits from the PLpro inhibition property and reduces the risk of viral infection.

RESUMEN

Background: The study of microbial communities and their applications have been leveraged by advances in sequencing techniques and bioinformatics tools. The Oxford Nanopore Technologies long-read sequencing by nanopores provides a portable and cost-efficient platform for sequencing assays. While this opens the possibility of sequencing applications outside specialized environments and real-time analysis of data, complementing the existing efficient library preparation protocols with streamlined bioinformatic workflows is required. Results: Here we present NanoRTax, a Nextflow pipeline for nanopore 16S rRNA gene amplicon data that features state-of-the-art taxonomic classification tools and real-time capability. The pipeline is paired with a web-based visual interface to enable user-friendly inspections of the experiment in progress. NanoRTax workflow and a simulated real-time analysis were used to validate the prediction of adult Intensive Care Unit patient mortality based on full-length 16S rRNA sequencing data from respiratory microbiome samples. Conclusions: This constitutes a proof-of-concept simulation study of how real-time bioinformatic workflows could be used to shorten the turnaround times in critical care settings and provides an instrument for future research on early-response strategies for sepsis.

RESUMEN

Background & Aims: Non-invasive stratification of the liver decompensation risk remains unmet in people with compensated cirrhosis. This study aimed to develop a non-invasive tool (NIT) to predict hepatic decompensation. Methods: This retrospective study recruited 689 people with compensated cirrhosis (median age, 54 years; 441 men) from 5 centres from January 2016 to June 2020. Baseline abdominal computed tomography (CT), clinical features, and liver stiffness were collected, and then the first decompensation was registered during the follow-up. The spleen-based model was designed for predicting decompensation based on a deep learning segmentation network to generate the spleen volume and least absolute shrinkage and selection operator (LASSO)-Cox. The spleen-based model was trained on the training cohort of 282 individuals (Institutions I-III) and was validated in 2 external validation cohorts (97 and 310 individuals from Institutions IV and V, respectively) and compared with the conventional serum-based models and the Baveno VII criteria. Results: The decompensation rate at 3 years was 23%, with a 37.6-month median (IQR 21.1-52.1 months) follow-up. The proposed model showed good performance in predicting decompensation (C-index ≥0.84) and outperformed the serum-based models (C-index comparison test p <0.05) in both the training and validation cohorts. The hazard ratio (HR) for decompensation in individuals with high risk was 7.3 (95% CI 4.2-12.8) in the training and 5.8 (95% CI 3.9-8.6) in the validation (log-rank test, p <0.05) cohorts. The low-risk group had a negligible 3-year decompensation risk (≤1%), and the model had a competitive performance compared with the Baveno VII criteria. Conclusions: This spleen-based model provides a non-invasive and user-friendly method to help predict decompensation in people with compensated cirrhosis in diverse healthcare settings where liver stiffness is not available. Lay summary: People with compensated cirrhosis with larger spleen volume would have a higher risk of decompensation. We developed a spleen-based model and validated it in external validation cohorts. The proposed model might help predict hepatic decompensation in people with compensated cirrhosis when invasive tools are unavailable.

RESUMEN

Objective: To determine the distribution and diagnostic value of peripheral enthesitis detected by whole-body MRI (WBMRI) in axial spondyloarthritis (axSpA) diagnosis, and to determine the value of the peripheral enthesitis score in axSpA assessment. Methods: Sixty axSpA patients [mean age of 33.2 (24.8-40.6) years] and 50 controls with chronic low back pain (LBP) [mean age of 34.7 (28.3-41.1) years] were enrolled. The gold standard was physician's comprehensive diagnosis based on current classification criteria and physical examination. All subjects underwent WBMRI, and 47 peripheral entheses were assessed for each patient with scores of 0-188. Results: WBMRI identified 155 enthesitis sites in 78.3% (n = 47) patients with axSpA. Meanwhile, 23 enthesitis sites were identified in 32% (n = 16) controls. The pelvis had the maximum number of enthesitis sites (52, 33.5%) in axSpA patients. Pelvic and anterior chest wall enthesitis had the highest sensitivity (51.67%) and specificity (100%) in axSpA diagnosis, respectively. There were different manifestations of enthesitis subtypes between axSpA patients and the control group. Osteitis was more present than soft-tissue inflammation in axSpA patients. The AUC for the number of enthesitis sites was 0.819 (95% CI 0.739-0.899), and that for the enthesitis score was 0.833 (95% CI 0.755-0.910), indicating statistically significant differences (P = 0.025). Based on the Youden index and clinical need, three enthesitis sites (sensitivity of 53.33, specificity of 98, and Youden index of 0.51) and enthesitis score (sensitivity of 58.33, specificity of 98, and Youden index of 0.56) may have the greatest value for axSpA diagnosis. Conclusion: The distribution of peripheral enthesitis can be adequately assessed by whole-body MRI, which could help diagnose axial spondyloarthritis. The enthesitis score may provide a more accurate assessment and diagnostic tool in axSpA compared with enthesitis site counting.

Asunto(s)

RESUMEN

Objective: Approximately 50% of obese Black patients with unprovoked diabetic ketoacidosis (DKA) or severe hyperglycemia (SH) at new-onset diabetes achieve near-normoglycemia remission with intensive insulin treatment. Despite the initial near-normoglycemia remission, most DKA/SH individuals develop hyperglycemia relapse after insulin discontinuation. Traditional biomarkers such as normal glucose tolerance at the time of remission were not predictive of hyperglycemia relapse. We tested whether 1-h plasma glucose (1-h PG) at remission predicts hyperglycemia relapse in Black patients with DKA/SH. Methods: Secondary analysis was performed of two prospective randomized controlled trials in 73 patients with DKA/SH at the safety net hospital with a median follow-up of 408 days. Patients with DKA/SH underwent a 5-point, 2-h 75-g oral glucose tolerance test after hyperglycemia remission. Hyperglycemia relapse is defined by fasting blood glucose (FBG) > 130 mg/dl, random blood glucose (BG) >180 mg/dl, or HbA1c > 7%. Results: During the median 408 (interquartile range: 110-602) days of follow-up, hyperglycemia relapse occurred in 28 (38.4%) participants. One-hour PG value ≥199 mg/dl discriminates hyperglycemia relapse (sensitivity: 64%; specificity: 71%). Elevated levels of 1-h PG (≥199 mg/dl) were independently associated with hyperglycemia relapse (adjusted hazard ratio: 2.40 [95% CI: 1.04, 5.56]). In a multivariable model with FBG, adding 1-h PG level enhanced the prediction of hyperglycemia relapse, with significant improvements in C-index (Δ: +0.05; p = 0.04), net reclassification improvement (NRI: 48.7%; p = 0.04), and integrated discrimination improvement (IDI: 7.8%; p = 0.02) as compared with the addition of 2-h PG (NRI: 20.2%; p = 0.42; IDI: 1.32%; p = 0.41) or HbA1c (NRI: 35.2%; p = 0.143; IDI: 5.8%; p = 0.04). Conclusion: One-hour PG at the time of remission is a better predictor of hyperglycemia relapse than traditional glycemic markers among obese Black patients presenting with DKA/SH. Testing 1-h PG at insulin discontinuation identifies individuals at high risk of developing hyperglycemia relapse.

Asunto(s)

RESUMEN

Objective: To determine if the triglycerides and glucose index (TyG) can be used as a marker for insulin resistance (IR) in Argentinean schoolchildren according to age and sex. Methods: Anthropometric data, blood glucose levels, lipid profiles, and insulin levels were measured. The TyG index was defined by Ln [fasting triglyceride (mg/dL)* fasting glucose (mg/dL)/2]. A comparison of the ability of TyG to identify children with IR was performed using receiver operating characteristic (ROC) curves and the area under the ROC (AUROC) curve. IR was defined as HOMA-IR > III quartile. Results: A total of 915 (528, 57.7% males) apparently healthy schoolchildren, aged 9.3 ± 2.2, were evaluated. The AUROC using the HOMA-IR > III quartile as the dichotomous variable showed that TyG was a fair marker to identify IR (0.65, 95% CI, 0.61-0.69; p < 0.01). There was a significantly higher TyG AUROC in males (0.69, 95% CI, 0.63-0.75; p < 001) than in females (0.60, 95% CI, 0.54-0.66; p < 0.01). When children were divided according to age into two groups (5.0-9.9 and 10.0-14.9-year-olds); younger children (0.64, 95% CI, 0.58-0.69; p < 0.011) and older children (0.62, 95% CI, 0.55-0.68; p = 0.01) had a similar and fair AUROC. However, when children were divided by age and sex, females older than ten had a non-significant AUROC (0.53, 95% CI, 0.42-0.63; p = 0.61). The TyG index compared with HOMA-IR had low sensitivity and specificity, ranging from 0.62 to 0.56. Conclusion: The TyG index had a fair AUROC with low sensitivity and specificity, indicating poor discrimination in identifying IR in apparently healthy Argentinean children. The ability to use TyG for screening purposes seems limited in Argentinean schoolchildren.

RESUMEN

Background & aims: There is no "gold standard" tool for the assessment of frailty in cirrhosis. This study compares Liver Frailty Index (LFI), Short Physical Performance Battery (SPPB), Fried Frailty Criteria (FFC), and Clinical Frailty Scale (CFS) for frailty assessment and ascertains its impact on predicting mortality and hospitalizations in a cohort of outpatients with cirrhosis. Methods: 116 patients were enrolled in this prospective observational cohort study. Frailty assessment was done using LFI, SPPB, FFC, and CFS. All patients were followed up for 6 months. The primary outcome was the first of either all-cause unplanned hospitalization or all-cause mortality occurring within 6 months of the study period. Results: 100 (86.2%) males and 16 (13.8%) females with a mean age of 50.2 (48.4-51.9, 95% CI) years were included. The most common cause of cirrhosis was alcoholic liver disease (47.4%) followed by hepatitis C (12.9%) and Nonalcoholic steatohepatitis (NASH) (10.3%). There was no significant difference in prevalence of frailty based on LFI (43.1%), FFC (36.2%), CFS (44%), and SPPB (47.4%) (P > 0.05). Frail patients had worse outcomes compared to the Not frail group. At 6 months, the mortality rate in Frail patients was 42% versus 1.5% for the Not frail; hospitalization in Frail patients occurred in 92% versus 6% in the Not frail. On multivariable analysis, independent predictors of mortality were Frailty [OR 14 (1.4-54.2)], alcohol-related cirrhosis [OR 4.2 (1.1-16.3)], Child-Turcotte-Pugh (CTP) [OR 2.1 (1.4-2.9)] and Chronic liver disease questionnaire (CLDQ) [OR 0.1 (0.1-0.4)] scores. Conclusions: LFI, SPPB, FFC, and CFS are comparable in frailty assessment in patients with cirrhosis. Importantly, comparability of the commonly used scores for frailty assessment and prediction of hospitalization and mortality allows flexibility for clinical application.

RESUMEN

Background: Identifying independent and interactive associations of a wide range of diseases and multimorbidity and apolipoprotein E4 (APOE4) with dementia may help promote cognitive health. The main aim of the present study was to investigate associations of such diseases and their multimorbidity with incident dementia. Methods: In this retrospective cohort study, we included 471,485 individuals of European ancestry from the UK Biobank, aged 38-73 years at baseline (2006-10). Dementia was identified using inpatient records and death registers. The follow-up period was between March 16, 2006, and Jan 31, 2021. Findings: During a median follow-up of 11·9 years, 6189 cases of incident all-cause dementia (503 young-onset cases, 5686 late-onset cases) were documented. In multivariable-adjusted analysis, 33 out of 63 major diseases were associated with an increased risk of dementia. The hazard ratio (HR [95% CI]) ranged from 1·12 (1·06-1·19) for obesity to 14·22 (12·33-16·18) for Parkinson's disease. In addition to conventional diseases, respiratory disorders, musculoskeletal disorders, digestive disorders, painful conditions, and chronic kidney disease were associated with increased dementia risk. A larger HR for dementia was observed for a larger number of diseases (3·97 [3·51-4·48] for ≥6 diseases versus no disease). These individual diseases and multimorbidity were more predictive of young-onset dementia than of late-onset dementia. Dementia risk score incorporating multimorbidity, age, and APOE4 status had strong prediction performance (area under the curve [95% CI]: 82·2% [81·7-82·7%]). APOE4 was more predictive of late-onset dementia (HR [95% CI]: 2·90 [2·75-3·06]) than of young-onset dementia (1·26 [1·03-1·54]). Associations of painful conditions, depression, obesity, diabetes, stroke, Parkinson's disease, high cholesterol, and their multimorbidity with incident dementia were stronger among non-APOE4 carriers. Interpretation: Besides conventional diseases, numerous diseases are associated with an increased risk of dementia. These individual diseases and multimorbidity are more predictive of young-onset dementia, whereas APOE4 is more predictive of late-onset dementia. Individual diseases and multimorbidity are stronger predictors of dementia in non-APOE4 carriers. Although multiple risk factors have been adjusted for in the analysis, potential confounding from unknown factors may have biased the associations. Funding: The Fundamental Research Funds of the State Key Laboratory of Ophthalmology, Project of Investigation on Health Status of Employees in Financial Industry in Guangzhou, China (Z012014075), Science and Technology Program of Guangzhou, China (202,002,020,049).

RESUMEN

Background: The most dreaded pandemic grappling world now, the Coronavirus Disease 2019 (COVID-19), chiefly involves the respiratory system; nevertheless, it is a multisystem disorder. Its involvement of the hepatic system is considerable; however, still emerging are its clinical implications and the effects on morbidity and mortality. Aim: The aim of this study is to report on the various aspects of its hepatic involvement by describing the alterations in tests of liver function and its significance in the disease outcome in a cohort of hospitalized COVID-19 patients at a tertiary center in northern India. Methods: This is a retrospective cohort study conducted in a tertiary-care hospital in northern India. All confirmed hospitalized COVID-19 cases aged 15 and above from Apr to Oct 2020 with no pre-existing liver disease were included. The primary endpoint was death at 28 days. Statistical analysis included descriptive analysis, sensitivity-specificity, and univariable and multivariable regression analysis as well as survival analysis. Results: A total of 708 patients with COVID-19 fulfilled the inclusion criteria included 561 (79.2%) males and 147 (20.8%) females. The median age was 49 (IQR = 25) years. Mild and moderate/severe disease were seen in 508 (71.8%) and 200 (28.2) patients, respectively. Serum bilirubin, aspartate aminotransferase (AST), and alanine aminotransferase (ALT) were elevated in 6.92%, 69.91%, and 80.22% of patients, respectively. In univariable logistic regression, AST [odds ratio; OR 1.008 95% CI (1.005-1.012) per 1 IU/L increase] and ALT [OR 1.005 95% CI (1.002-1.007) per 1 IU/L increase] were significantly associated with the odds of moderate to severe disease but only AST was significant after adjustment to age, sex, and comorbidity [adjusted odds ratio; aOR 1.007 95% CI (1.003-1.011) per 1 IU/L increase]. Serum albumin was negatively associated with the odds of moderate to severe disease and remained significant in the adjusted model [aOR 0.217 95%CI (0.149-0.316) per 1 g/dL increase].Ninety-six patients succumbed to illness [case fatality rate; CFR 13.6%). In adjusted Cox Proportional-Hazards Model for mortality, AST [adjusted hazard ratio; aHR 1.002 95% CI (1.000-1.003) per 1 IU/L increase] and serum albumin [aHR 0.396 95% CI (0.285-0.549) per 1 g/dL increase] showed significant association with mortality. Conclusion: Liver function abnormalities are common in patients with COVID-19. In particular, AST and serum albumin levels are effective predictors of disease severity and mortality and can be used as markers of fatal disease in the management as well as prognostication of COVID-19.

RESUMEN

Receiver Operating Characteristic curves have been widely used to represent the performance of diagnostic tests. The corresponding area under the curve, widely used to evaluate their performance quantitatively, has been criticized in several respects. Several proposals have been introduced to improve area under the curve by taking into account only specific regions of the Receiver Operating Characteristic space, that is, the plane to which Receiver Operating Characteristic curves belong. For instance, a region of interest can be delimited by setting specific thresholds for the true positive rate or the false positive rate. Different ways of setting the borders of the region of interest may result in completely different, even opposing, evaluations. In this paper, we present a method to define a region of interest in a rigorous and objective way, and compute a partial area under the curve that can be used to evaluate the performance of diagnostic tests. The method was originally conceived in the Software Engineering domain to evaluate the performance of methods that estimate the defectiveness of software modules. We compare this method with previous proposals. Our method allows the definition of regions of interest by setting acceptability thresholds on any kind of performance metric, and not just false positive rate and true positive rate: for instance, the region of interest can be determined by imposing that ϕ (also known as the Matthews Correlation Coefficient) is above a given threshold. We also show how to delimit the region of interest corresponding to acceptable costs, whenever the individual cost of false positives and false negatives is known. Finally, we demonstrate the effectiveness of the method by applying it to the Wisconsin Breast Cancer Data. We provide Python and R packages supporting the presented method.

Asunto(s)

RESUMEN

Introduction: Restless legs syndrome is a common and severe complication in patients undergoing peritoneal dialysis (PD), which seriously affects the life quality and prognosis of patients undergoing PD. Unfortunately, there are still no effective prevention and treatment measures. Serum hepcidin was demonstrated to be related to primary restless legs syndrome (RLS), whereas there are no studies on the relationship between serum hepcidin and RLS in patients undergoing PD. We aimed to evaluate the role and function of serum hepcidin in patients undergoing PD with RLS. Methods: A total of 51 patients undergoing PD with RLS and 102 age-and gender-matched patients undergoing PD without RLS were included. We collected the clinical data including serum hepcidin of those patients undergoing PD. We scored the severity of RLS according to the International restless leg Syndrome Research Group rating scale (IRLS). We compared the clinical characteristics of the two groups and evaluated the determinant factors of RLS by Logistic regression analysis. In addition, we evaluated the diagnostic value of serum hepcidin in patients undergoing PD with RLS by receiver operating characteristic (ROC) curve. We also analyzed the influencing factors of IRLS by multivariate linear regression analysis. Results: The duration of PD, serum hepcidin, and calcium were found to be significantly higher in patients undergoing PD with RLS than those patients undergoing PD without RLS (P < 0.001, P < 0.001, and P = 0.002, respectively). The level of hemoglobin, albumin, and RKF were significantly lower in patients undergoing PD with RLS (P = 0.002, P = 0.042, and P < 0.001, respectively). The duration of PD [odds ratio (OR) 1.038, 95% CI: 1.017, 1.060, P < 0.001], hemoglobulin level (OR 0.969, 95% CI: 0.944, 0.995, P = 0.019), calcium level (OR 9.224, 95% CI: 1.261, 67.450, P = 0.029), albumin level (OR 0.835, 95% CI: 0.757, 0.921, P < 0.001), hepcidin level (OR 1.023, 95% CI: 1.009, 1.038, P = 0.001), and RKF (OR 0.65, 95% CI: 0.495, 0.856, P = 0.002) are independent determinant factors of RLS in patients undergoing PD. Multivariate linear regression analysis revealed that, in addition to albumin, they were also independently associated with the severity of RLS. Conclusion: A significant relation was detected between serum hepcidin level and RLS in patients undergoing PD.

RESUMEN

BACKGROUND: Grade of brain tumor is thought to be the most significant and crucial component in treatment management. Recent development in medical imaging techniques have led to the introduce non-invasive methods for brain tumor grading such as different magnetic resonance imaging (MRI) protocols. Combination of different MRI protocols with fusion algorithms for tumor grading is used to increase diagnostic improvement. This paper investigated the efficiency of the Laplacian Re-decomposition (LRD) fusion algorithms for glioma grading. PROCEDURES: In this study, 69 patients were examined with MRI. The T1 post enhancement (T1Gd) and diffusion-weighted images (DWI) were obtained. To evaluated LRD performance for glioma grading, we compared the parameters of the receiver operating characteristic (ROC) curves. FINDINGS: We found that the average Relative Signal Contrast (RSC) for high-grade gliomas is greater than RSCs for low-grade gliomas in T1Gd images and all fused images. No significant difference in RSCs of DWI images was observed between low-grade and high-grade gliomas. However, a significant RSCs difference was detected between grade III and IV in the T1Gd, b50, and all fussed images. CONCLUSIONS: This research suggests that T1Gd images are an appropriate imaging protocol for separating low-grade and high-grade gliomas. According to the findings of this study, we may use the LRD fusion algorithm to increase the diagnostic value of T1Gd and DWI picture for grades III and IV glioma distinction. In conclusion, this article has emphasized the significance of the LRD fusion algorithm as a tool for differentiating grade III and IV gliomas.

RESUMEN

Background: Abnormal epigenetic alterations can contribute to the development of human malignancies. Identification of these alterations for early screening and prognosis of clear cell renal cell carcinoma (ccRCC) has been a highly sought-after goal. Bioinformatic analysis of DNA methylation data provides broad prospects for discovery of epigenetic biomarkers. However, there is short of exploration of methylation-driven genes of ccRCC. Methods: Gene expression data and DNA methylation data in metastatic ccRCC were sourced from the Gene Expression Omnibus (GEO) database. Differentially methylated genes (DMGs) at 5'-C-phosphate-G- 3' (CpG) sites and differentially expressed genes (DEGs) were screened and the overlapping genes in DMGs and DEGs were then subject to gene set enrichment analysis. Next, the weighted gene co-expression network analysis (WGCNA) was used to search hub DMGs associated with ccRCC. Cox regression and ROC analyses were performed to screen potential biomarkers and develop a prognostic model based on the screened hub genes. Results: Three hundred and fourteen overlapping DMGs were obtained from two independent GEO datasets. The turquoise module contained 79 hub DMGs, which represent the most significant module screened by WGCNA. Furthermore, a total of 12 hub genes (CETN3, DCAF7, GPX4, HNRNPA0, NUP54, SERPINB1, STARD5, TRIM52, C4orf3, C12orf51, and C17orf65) were identified in the TCGA database by multivariate Cox regression analyses. All the 12 genes were then used to generate the model for diagnosis and prognosis of ccRCC. ROC analysis showed that these genes exhibited good diagnostic efficiency for metastatic and non-metastatic ccRCC. Furthermore, the prognostic model with the 12 methylation-driven genes demonstrated a good prediction of 5-year survival rates for ccRCC patients. Conclusion: Integrative analysis of DNA methylation data identified 12 signature genes, which could be used as epigenetic biomarkers for prognosis of metastatic ccRCC. This prognostic model has a good prediction of 5-year survival for ccRCC patients.

RESUMEN

BACKGROUND: To evaluate the ability of four scoring systems (Ranson, BISAP, Glasgow, and APACHE II) to predict outcomes of acute pancreatitis (AP) in elderly patients. METHODS: This was a retrospective study of 918 patients presenting with AP at Zhongda Hospital Southeast University, from January 2015 to December 2018. We divided patients into two groups: 368 patients who were ≥ 60 years old, and 550 patients who were < 60 years old. Four scoring systems were used to analyze all patients. RESULTS: The severity of the disease, and mortality were significantly different between the two groups (p < 0.05), while the difference between the two groups about pancreatic necrosis is statistically insignificant (p = 0.399). The differences of the AUCs (Area under curves) for prediction of outcome of SAP (severe acute pancreatitis) between the two groups were statistically significant for Ranson and APACHE II (p < 0.05), but not for the differences between BISAP and Glasgow. All the four scoring systems were similar in terms of prediction of pancreatic necrosis and death in both groups. CONCLUSIONS: Prediction of severity, pancreatic necrosis, and death in AP for elderly patients can be performed very well by using BISAP. APACHE II is more suitable for younger patients when dealing with severity. Ranson and Glasgow can be used to evaluate all AP patients in most cases; however, Ranson is more effective for younger patients when used to assess severity.

Asunto(s)

RESUMEN

Data are conflicting regarding the optimal cutoffs of B-type natriuretic peptide (BNP) and N-terminal pro-B-type natriuretic peptide (NT-proBNP) to predict short-term mortality in patients with sepsis. We conducted a comprehensive search of several databases (MEDLINE, EMBASE, Cochrane Central Register of Controlled Trials, Cochrane Database of Systematic Reviews, and Scopus) for English-language reports of studies evaluating adult patients with sepsis, severe sepsis, and septic shock with BNP/NT-proBNP levels and short-term mortality (intensive care unit, in-hospital, 28-day, or 30-day) published from January 1, 2000, to September 5, 2017. The average values in survivors and nonsurvivors were used to estimate the receiver operating characteristic curve (ROC) using a parametric regression model. Thirty-five observational studies (3508 patients) were included (median age, 51-75 years; 12%-74% males; cumulative mortality, 34.2%). A BNP of 622 pg/mL had the greatest discrimination for mortality (sensitivity, 0.695 [95% CI, 0.659-0.729]; specificity, 0.907 [95% CI, 0.810-1.003]; area under the ROC, 0.766 [95% CI, 0.734-0.797]). An NT-proBNP of 4000 pg/mL had the greatest discrimination for mortality (sensitivity, 0.728 [95% CI, 0.703-0.753]; specificity, 0.789 [95% CI, 0.710-0.867]; area under the ROC, 0.787 [95% CI, 0.766-0.809]). In prespecified subgroup analyses, identified BNP/NT-proBNP cutoffs had higher discrimination if specimens were obtained 24 hours or less after admission, in patients with severe sepsis/septic shock, in patients enrolled after 2010, and in studies performed in the United States and Europe. There was inconsistent adjustment for renal function. In this hypothesis-generating analysis, BNP and NT-proBNP cutoffs of 622 pg/mL and 4000 pg/mL optimally predicted short-term mortality in patients with sepsis. The applicability of these results is limited by the heterogeneity of included patient populations.

RESUMEN

The purpose was to analyze the value of quantitative parameters of DCE-MRI in evaluating micro-infiltration of malignant bone tumors. METHODS: Thirty-nine New Zealand white rabbits were used to establish malignant bone tumor models by implanting VX2 tumor fragments into the right tibiae. After three weeks, models were examined by conventional MRI and DCE-MRI; then the right tibiae were cut into sagittal sections and partitioned into histology slices for comparison with microscopic findings. Micro-infiltration groups were selected and the range of infiltration was determined under the microscope, and corresponding DCE images analyzed to obtain the quantitative parameters include Ktrans, Kep, ve and vp in parenchyma areas, micro-infiltration areas and simple edema areas. One-way ANOVA was used to compare the differences of the parameters between the three areas. Receiver operating characteristic curves (ROCs) were plotted to determine the accuracy of different parameters by area under curves (AUCs). RESULTS: 22 cases (22/39, 56.4%) were included in the micro-infiltration group and the infiltration depth ranged from 1.3 mm to 4.6 mm, with an average depth of 3.2 mm ± 0.8 mm. The statistical results of quantitative parameters in the three areas were as follows: Ktrans values were (0.494 ± 0.052), (0.403  ±  0.049), (0.173 ± 0.047) min-1 (p = =0.000), Kep values were (1.959 ± 0.65), (1.528 ± 0.372), (1.174 ± 0.486) min-1 (p = =0.000), ve values were (0.247 ± 0.068), (0.283 ± 0.057), (0.168 ± 0.062) min-1 (p = =0.000), vp values were (0.125 ± 0.036), (0.108 ± 0.033), (0.098 ± 0.025) min-1 (p = =0.022), respectively. Ktrans and Kep values had significant difference in the three areas after comparing between-groups, respectively. However, there were no significant difference in vp values between parenchyma and micro-infiltration areas (p = =0.078), micro-infiltration and simple edema areas (p = =0.315), and ve values between parenchyma and micro-infiltration areas (p = =0.056). The ve values were higher in parenchyma and micro-infiltration areas then simple edema areas. Ktrans had highest accuracy in differentiating different areas (AUC > 0.9), respectively. CONCLUSION: Quantitative parameters Ktrans, Kep and ve can assess the extent of intramedullary invasion of malignant bone tumors. Ktrans have highest accuracy in differentiating different regions.

RESUMEN

BACKGROUND AND PURPOSE: Dysphagia is a common, severe and dose-limiting toxicity after oncological treatment of head and neck cancer (HNC). This study aims to investigate relationships between radiation doses to structures involved in normal swallowing and patient-reported as well as clinically measured swallowing function in HNC patients after curative (chemo-) radiation therapy (RT) with focus on late effects. MATERIALS AND METHODS: Patients (n = 90) with HNC curatively treated with RT ±â€¯chemotherapy in 2007-2015 were assessed for dysphagia post-treatment by telephone interview and videofluoroscopy (VFS). A study-specific symptom score was used to determine patient-reported dysphagia. The Penetration-Aspiration Scale (PAS) was applied to determine swallowing function by VFS (PAS ≥ 4/ ≥ 6 = moderate/severe dysphagia). Thirteen anatomical structures involved in normal swallowing were individually delineated on the patients' original planning CT scans and associated dose-volume histograms (DVHs) retrieved. Relationships between structure doses and late toxicity were investigated through univariable and multivariable logistic regression analysis (UVA/MVA) accounting for effects by relevant clinical factors. RESULTS: Median assessment time was 7 months post-RT (range: 5-34 months). Mean dose to the contralateral parotid gland and supraglottic larynx as well as maximum dose to the contralateral anterior digastric muscle predicted patient-reported dysphagia (AUC = 0.64-0.67). Mean dose to the pharyngeal constrictor muscle, the larynx, the supraglottic larynx and the epiglottis, as well as maximum dose to the contralateral submandibular gland predicted moderate and severe dysphagia by VFS (AUC = 0.71-0.80). CONCLUSION: The patients in this cohort were consecutively identified pre-treatment, and were structurally approached and assessed for dysphagia after treatment at a specific time point. In addition to established dysphagia organs-at-risk (OARs), our data suggest that epiglottic and submandibular gland doses are important for swallowing function post-RT. Keeping DVH thresholds below V60 = 60% and V60 = 17%, respectively, may increase chances to reduce occurrence of severe late dysphagia. The results need to be externally validated in future studies.