Excellent Predictive Value Research Articles

The utility of 18F-fluorocholine PET/CT in the imaging of parathyroid adenomas.

The aim of the study was to estimate the sensitivity of ¹⁸F-FCH PET/CT in preoperative localisation of hyperfunctioning parathyroid glands in patients with primary hyperparathyroidism (PHPT). Sixty-five consecutive patients with PHPT, who underwent neck ultrasound (US) and 99mTc/99mTc-MIBI dual-phase parathyroid scintigraphy, were prospectively enrolled. Twenty-two patients had unsuccessful parathyroid surgery prior to the study. PET/CT scans were performed 65.0 ± 13.3 min after injection of 218.5 ± 31.9 MBq of 18F-fluorocholine (FCH). Three experienced nuclear medicine physicians assessed the detection rate of hyperfunctioning parathyroid tissue. Response to parathyroidectomy and clinical follow-up served as a reference test. Per-patient sensitivity and positive predictive value (PPV) were calculated for patients who underwent surgery. ¹⁸F-FCH PET/CT was positive in 61 patients, and negative in 4. US and parathyroid scintigraphy showed positive and negative results in 20, 45 and 17, 48, respectively. US showed nodular goitre in 31 patients and chronic thyroiditis in 9 patients. Parathyroid surgery was performed in 43 (66%) patients. ¹⁸F-FCH PET/CT yielded a sensitivity of 100% (95% CI: 87.99-100) and PPV of 85.7% (95% CI: 70.77-94.06). Similar values were observed in patients with chronic thyroiditis, nodular goitre, and patients after an unsuccessful parathyroid surgery. PET/CT identified hyperparathyroidism complications (kidney stones, osteoporotic bone fractures, and brown tumours) in 11 patients. ¹⁸F-FCH PET/CT effectively detected hyperfunctioning parathyroid tissue and its complications. The method showed excellent sensitivity and positive predictive value, including patients with nodular goitre, chronic thyroiditis, and prior unsuccessful parathyroidectomy. PET/CT performance was superior to neck ultrasound and parathyroid scintigraphy.

Predictive value of arterial blood lactate/serum albumin ratio for myocardial injury in elderly patients with severe community-acquired pneumonia.

To investigate the predictive value of arterial blood lactate (Lac)/serum albumin (Alb) ratio (Lac/Alb) on myocardial injury in elderly patients with severe community-acquired pneumonia (SCAP).Seventy-two elderly SCAP patients hospitalized in the intensive care unit (ICU) of the emergency department of Hebei General Hospital from March 2020 to March 2021 were included, and the general data and arterial blood Lac and serum Alb levels were collected, and Lac/Alb values were calculated. The patients were divided into myocardial injury group (n = 25) and nonmyocardial injury group (n = 47) according to whether the myocardial injury occurred during their ICU stay, and the predictive value of Lac/Alb on myocardial injury in elderly patients with SCAP was assessed using receiver operating characteristic curve and area under the curve.There were no statistically significant differences in age and gender between the 2 groups (both P > .05), and there were no statistical differences in oxygenation index, procalcitonin, C-reactive protein, lymphocyte count, and Alb levels between the 2 groups (all P > .05). Neutrophil count, neutrophil\\lymphocyte ratio, serum creatinine, Lac, and Lac/Alb levels were significantly higher in patients in the myocardial injury group than in the nonmyocardial injury group [13.90 (11.07,19.67) × 109/L vs 10.79 (8.16,14.23) × 109/L, 26.48 (20.07,31.88) vs 17.79 (9.85,27.23), 135.71 (81.50,284.75) μmol/L vs 76.30 (60.30,140.30) μmol/L, 3.0 (2.2,4.5) mmol/L vs 2.1 (1.6,3.1) mmol/L, 1.34 (0.88,2.16) vs 0.78 (0.60,1.12), all P < .05]. Patients in the myocardial injury group had a significantly higher mortality rate in the ICU than in the nonmyocardial injury group (72.0% vs 36.2%, P < .01). Neutrophils, neutrophil/lymphocyte ratio, serum creatinine, Lac, and Lac/Alb showed a weak positive correlation with myocardial injury in patients (all P < .05). The area under the curve of Lac/Alb for predicting myocardial injury in elderly patients with SCAP was 0.737 (95% confidence interval 0.620–0.834), and the sensitivity and specificity of the prediction with 1.21 as the cutoff value were 60.00% and 78.72%, respectively.Lac/Alb has an excellent predictive value for myocardial injury in elderly SCAP patients.

P200 The diagnostic yield of pan-enteric capsule endoscopy in inflammatory bowel disease: A systematic review and meta-analysis

Abstract Background Capsule endoscopy (CE) is a non-invasive diagnostic modality enabling real time video imaging of the gastrointestinal (GI) mucosa with an ingestible recording device. Major technological advancements now allow pan-enteric capsule endoscopy (PCE) to thoroughly assess the entire GI tract. CE is increasingly utilised in the inflammatory bowel disease (IBD) diagnostic algorithm. Our aim was to evaluate the diagnostic accuracy of PCEs in IBD. Methods We comprehensively searched electronic databases (MEDLINE, SCOPUS, EMBASE and Cochrane Central Register of Controlled Trials) for studies comparing the diagnostic accuracy of PCE with colonoscopy or magnetic resonance enterography (MRE). Prospective studies with ≥ 10 IBD patients were included in our final analysis. Diagnostic accuracy and yield were calculated for the detection of active IBD. Meta-analysis of proportions was performed to assess for an incremental benefit between modalities. The risk of bias was determined by the Quality Assessment of Diagnostic Accuracy in Systematic Reviews (QUADAS-2). Data was analysed by calculating forest plots and the use of the I2 statistic for heterogeneity. Results Fourteen studies, including 797 patients, were identified comparing PCE diagnostic yield with colonoscopy or MRE. Seven studies evaluated PCE diagnostic yield in CD and 7 studies in UC. There was a low risk of bias for the majority of included studies; only 1 study was found to have a high risk of bias. In CD, there was a trend to superiority of PCE over MRE and colonoscopy (individually and for pooled outcomes) with a pooled odds ratio (OR) of 1.25 (95% CI 0.85–1.86) (Fig 1) for the detection of CD. This translates to an incremental benefit in diagnostic yield of 5% and 7% for PCE compared with MRE and colonoscopy respectively. PCE performed comparably with colonoscopy in the terminal ileum and colon with ORs of 1.19 (95% CI 0.78–1.79) (Fig 2), and 1.14 (95% CI 0.76–1.71) (Fig 3) respectively. PCEs had a diagnostic sensitivity for the detection of UC of 93.8% (95% CI 87.6%-97.0%) (Fig 4) and a specificity of 69.8% (95% CI, 38.2%-89.6%). This equates to a diagnostic OR of 24.0 (95% CI 10.4–55.3). Subgroup analysis suggested that newer PCEs had greater diagnostic yield than the earlier devices (for UC and CD). Conclusion PCEs have a comparable diagnostic yield to colonoscopy and MRE in Crohn’s disease. This was true for the small and large bowel, giving PCE an advantage over standard CE as a single pan-enteric assessment tool for CD. Limitations include the standardisation of PCE scoring systems and the lack of transmural assessment. In UC, PCE has an excellent diagnostic sensitivity and positive predictive value, but is limited by the lack of histologic assessment and poor specificity.

Establishment of an Artificial Neural Network Model Using Immune-Infiltration Related Factors for Endometrial Receptivity Assessment.

Background: A comprehensive clinical strategy for infertility involves treatment and, more importantly, post-treatment evaluation. As a component of assessment, endometrial receptivity does not have a validated tool. This study was anchored on immune factors, which are critical factors affecting embryonic implantation. We aimed at establishing novel approaches for assessing endometrial receptivity to guide clinical practice. Methods: Immune-infiltration levels in the GSE58144 dataset (n = 115) from GEO were analysed by digital deconvolution and validated by immunofluorescence (n = 23). Then, modules that were most associated with M1/M2 macrophages and their hub genes were selected by weighted gene co-expression network as well as univariate analyses and validated using the GSE5099 macrophage dataset and qPCR analysis (n = 19). Finally, the artificial neural network model was established from hub genes and its predictive efficacy validated using the GSE165004 dataset (n = 72). Results: Dysregulation of M1 to M2 macrophage ratio is an important factor contributing to defective endometrial receptivity. M1/M2 related gene modules were enriched in three biological processes in macrophages: antigen presentation, interleukin-1-mediated signalling pathway, and phagosome acidification. Their hub genes were significantly altered in patients and associated with ribosomal, lysosomal, and proteasomal pathways. The established model exhibited an excellent predictive value in both datasets, with an accuracy of 98.3% and an AUC of 0.975 (95% CI 0.945–1). Conclusions: M1/M2 polarization influences endometrial receptivity by regulating three gene modules, while the established ANN model can be used to effectively assess endometrial receptivity to inform pregnancy and individualized clinical management strategies.

Comparison between video head impulse and videonystagmography in patients with vertiginous migraine

Background and aim In addition to the classic migraine symptoms of vertigo, dizziness, and imbalance, vestibular migraine causes vertigo, dizziness, and imbalance. The video head impulse test (VHIT) is a novel approach for determining the function of each semicircular canal. Although videonystagmography (VNG) is an effective tool for identifying peripheral vertigo, not all patients with central vertigo can be easily detected. The goal of this research is to confirm the findings of the functional outcome of VHIT versus VNG in patients with vertiginous migraine. Patients and methods We selected 40 patients (both sexes) with vestibular migraine and 25 normal individuals as control. Both groups were subjected to complete clinical examination after thorough history taking, laboratory investigations, VHIT, and VNG. Results VNG had excellent predictive value in the patients’ group (95% confidence interval=0.891–0.998, P=0.0001) with a 96.6% sensitivity and 86.2% specificity, while VHIT had poor predictive value with a sensitivity of 100% and specificity of 48.1% (95% confidence interval=0.523–0.779, P=0.099). Conclusion VNG has a specificity and sensitivity for the prognosis of vestibular migraine that is virtually identical to VHIT.

Noninvasively predict the micro-vascular invasion and histopathological grade of hepatocellular carcinoma with CT-derived radiomics

ObjectivesThis research aims to predict the micro-vascular invasion and histopathologic grade of hepatocellular carcinoma with the CT-derived radiomics. MethodsThe clinical and image data of 82 patients were accessed from the TCGA-LIHC collection in The Cancer Imaging Archive. Then the radiomics features were extracted from the CT images. For obtaining the appropriate feature subset, the redundant features were removed by means of intra-class agreement analysis, the Student t test, LASSO-regression and support vector machine (SVM) Recursive feature elimination (SVM-RFE). Then several machine-learning-based classifiers including SVM and random forest (RF) were established. To accurately evaluate the tumor grade and MVI with the integration of the Radiomics and clinical insights, the nomogram-based clinical models were constructed. The diagnostic performance was evaluated with ROC analysis. Results7 and 10 radiomics features were selected via LASSO regression and SVM-RFE for identifying the tumor grade with regard to 13 and 10 features selected via LASSO regression and SVM-RFE for evaluating the MVI. The combination of the classifier—RF and the selection strategy of SVM-RFE yielded the best performance for grading HCC (AUC: 0.898). Differently, the combination of the classifier—RF and the selection strategy of LASSO regression resulted in the best performance for identifying MVI (AUC: 0.876). Finally, two nomograms were constructed with radiomics score (Rscore) and clinical risk factors, which showed excellent predictive value for both tumor grade (AUC: 0.928) and MVI (AUC: 0.945). ConclusionCT-derived radiomics were valuable for noninvasively assessing the micro-vascular invasion and histopathologic grade of hepatocellular carcinoma.

Identification of prognostic metabolic genes in adrenocortical carcinoma and establishment of a prognostic nomogram: A bioinformatic study.

Adrenocortical carcinoma is an invasive malignancy with poor prognosis, high recurrence rate and limited therapeutic options. Therefore, it is necessary to establish an effective method to diagnose and evaluate the prognosis of patients, so as to realize individualized treatment and improve their survival rate.This study investigated metabolic genes that may be potential therapeutic targets for Adrenocortical carcinoma (ACC). Level 3 gene expression data from the ACC cohort and the relevant clinical information were obtained from The Cancer Genome Atlas (TCGA) database. To verify, other ACC datasets (GSE76021, GSE19750) were downloaded from the Gene Expression Omnibus (GEO) database. The ACC datasets from TCGA and GEO were used to screen metabolic genes through the Molecular Signatures Database using gene set enrichment analysis. Then, the overlapping metabolic genes of the 2 datasets were identified.A signature of five metabolic genes (CYP11B1, GSTM2, IRF9, RPL31, and UBE2C) was identified in patients with ACC. The signature could be used to divide the patients with ACC into high- and low-risk groups based on their median risk score. Multivariate Cox regression analysis was performed to determine the independent prognostic factors of ACC. Time-dependent receiver operating characteristic (ROC) curve analysis was conducted to assess the prediction accuracy of the prognostic signature. Last, a nomogram was established to assess the individualized prognosis prediction model.The results indicated that the signature of 5 metabolic genes had excellent predictive value for ACC. These findings might help improve personalized treatment and medical decisions.

Predictive Biomarkers for Postmyocardial Infarction Heart Failure Using Machine Learning: A Secondary Analysis of a Cohort Study.

Background There are few biomarkers with an excellent predictive value for postacute myocardial infarction (MI) patients who developed heart failure (HF). This study aimed to screen candidate biomarkers to predict post-MI HF. Methods This is a secondary analysis of a single-center cohort study including nine post-MI HF patients and eight post-MI patients who remained HF-free over a 6-month follow-up. Transcriptional profiling was analyzed using the whole blood samples collected at admission, discharge, and 1-month follow-up. We screened differentially expressed genes and identified key modules using weighted gene coexpression network analysis. We confirmed the candidate biomarkers using the developed external datasets on post-MI HF. The receiver operating characteristic curves were created to evaluate the predictive value of these candidate biomarkers. Results A total of 6,778, 1,136, and 1,974 genes (dataset 1) were differently expressed at admission, discharge, and 1-month follow-up, respectively. The white and royal blue modules were most significantly correlated with post-MI HF (dataset 2). After overlapping dataset 1, dataset 2, and external datasets (dataset 3), we identified five candidate biomarkers, including FCGR2A, GSDMB, MIR330, MED1, and SQSTM1. When GSDMB and SQSTM1 were combined, the area under the curve achieved 1.00, 0.85, and 0.89 in admission, discharge, and 1-month follow-up, respectively. Conclusions This study demonstrates that FCGR2A, GSDMB, MIR330, MED1, and SQSTM1 are the candidate predictive biomarker genes for post-MI HF, and the combination of GSDMB and SQSTM1 has a high predictive value.

Effectiveness of LODS, OASIS, and SAPS II to predict in-hospital mortality for intensive care patients with ST elevation myocardial infarction

The relationship between three scoring systems (LODS, OASIS, and SAPS II) and in-hospital mortality of intensive care patients with ST segment elevation myocardial infarction (STEMI) is currently inconclusive. The baseline data, LODS score, OASIS score, SAPS II score, and in-hospital prognosis of intensive care patients with STEMI were retrieved from the Medical Information Mart for Intensive Care IV database. Propensity score matching analysis was performed to reduce bias. Receiver operating characteristic curves (ROC) were drawn for the three scoring systems, and comparisons between the areas under the ROC curves (AUC) were conducted. Decision curve analysis (DCA) was performed to determine the net benefits of the three scoring systems. LODS and SAPS II were independent risk factors for in-hospital mortality. For the study cohort, the AUCs of LODS, OASIS, SAPS II were 0.867, 0.827, and 0.894; after PSM, the AUCs of LODS, OASIS, SAPS II were 0.877, 0.821, and 0.881. A stratified analysis of the patients who underwent percutaneous coronary intervention/coronary artery bypass grafting (PCI/CABG) or not was conducted. In the PCI/CABG group, the AUCs of LODS, OASIS, SAPS II were 0.853, 0.825, and 0.867, while in the non-PCI/CABG group, the AUCs of LODS, OASIS, SAPS II were 0.857, 0.804, and 0.897. The results of the Z test suggest that the predictive value of LODS and SAPS II was not statistically different, but both were higher than OASIS. According to the DCA, the net clinical benefit of LODS was the greatest. LODS and SAPS II have excellent predictive value, and in most cases, both were higher than OASIS. With a more concise composition and greater clinical benefit, LODS may be a better predictor of in-hospital mortality for intensive care patients with STEMI.

M6A Regulator-Mediated Methylation Modification Patterns and Characteristics of Immunity in Blood Leukocytes of COVID-19 Patients.

Both RNA N6-methyladenosine (m6A) modification of SARS-CoV-2 and immune characteristics of the human body have been reported to play an important role in COVID-19, but how the m6A methylation modification of leukocytes responds to the virus infection remains unknown. Based on the RNA-seq of 126 samples from the GEO database, we disclosed that there is a remarkably higher m6A modification level of blood leukocytes in patients with COVID-19 compared to patients without COVID-19, and this difference was related to CD4+ T cells. Two clusters were identified by unsupervised clustering, m6A cluster A characterized by T cell activation had a higher prognosis than m6A cluster B. Elevated metabolism level, blockage of the immune checkpoint, and lower level of m6A score were observed in m6A cluster B. A protective model was constructed based on nine selected genes and it exhibited an excellent predictive value in COVID-19. Further analysis revealed that the protective score was positively correlated to HFD45 and ventilator-free days, while negatively correlated to SOFA score, APACHE-II score, and crp. Our works systematically depicted a complicated correlation between m6A methylation modification and host lymphocytes in patients infected with SARS-CoV-2 and provided a well-performing model to predict the patients’ outcomes.

Blood lead level in Chinese adults with and without coronary artery disease.

BACKGROUNDThe Trial to Assess Chelation Therapy study found that edetate disodium (disodium ethylenediaminetetraacetic acid) chelation therapy significantly reduced the incidence of cardiac events in stable post-myocardial infarction patients, and a body of epidemiological data has shown that accumulation of biologically active metals, such as lead and cadmium, is an important risk factor for cardiovascular disease. However, limited studies have focused on the relationship between angiographically diagnosed coronary artery disease (CAD) and lead exposure. This study compared blood lead level (BLL) in Chinese patients with and without CAD.METHODSIn this prospective, observational study, 450 consecutive patients admitted to Beijing Anzhen Hospital with suspected CAD from November 1, 2018, to January 30, 2019, were enrolled. All patients underwent coronary angiography, and an experienced heart team calculated the SYNTAX scores (SXscore) for all available coronary angiograms. BLLs were determined with atomic absorption spectrophotometry and compared between patients with angiographically diagnosed CAD and those without CAD.RESULTSIn total, 343 (76%) patients had CAD, of whom 42% had low (0−22), 22% had intermediate (23−32), and 36% had high (≥ 33) SXscore. BLLs were 36.8 ± 16.95 μg/L in patients with CAD and 31.2 ± 15.75 μg/L in those without CAD (P = 0.003). When BLLs were categorized into three groups (low, middle, high), CAD prevalence increased with increasing BLLs (P < 0.05). In the multivariate regression model, BLLs were associated with CAD (odds ratio (OR): 1.023, 95% confidence interval (CI): 1.008−1.039; P = 0.0017). OR in the high versus low BLL group was 2.36 (95% CI: 1.29−4.42,P = 0.003). Furthermore, BLLs were independently associated with intermediate and high SXscore (adjusted OR: 1.050, 95% CI: 1.036–1.066; P < 0.0001). CONCLUSIONBLLs were significantly associated with angiographically diagnosed CAD. Furthermore, BLLs showed excellent predictive value for SXscore, especially for complex coronary artery lesions.

Abstract 9415: Body Mass Index, Waist Circumference and Waist-Hip Ratio in South Asians With Acute Coronary Syndrome

Introduction: Acute coronary syndrome (ACS) is the leading cause of death worldwide, even higher in South Asian countries. South Asia shows a higher incidence of ACS and an increasing trend of overweight and obesity. Methods: This cross-sectional descriptive study was conducted at the Teaching Hospital Peradeniya, Sri Lanka, among the patients presenting with ACS. An interviewer-administered structured questionnaire was used to collect data and to take anthropometric measurements. They were analysed to obtain the body mass index (BMI) and the waist-hip ratio. Results: A total of 780 patients with ACS were included in the study with a mean age of 60.8 ± 11.3 years. Among them, 316 (40.5%) were females. The mean BMI of females was 25.2 ± 4.4 kg m -2 which was higher than that of males 23.9 ± 3.8 kg m -2 , showing a statistically significant difference (p=0.003). The prevalence of overweight and obesity was 37.6% and 21.2%, respectively, significantly higher than the normal values for the ordinary Sri Lankan population (p=0.002). In females, the prevalence of obesity (31.2%) was significantly higher than in males (13.5%) (p=0.000). In males, the prevalence of overweight (40.6%) was significantly higher than in females (33.8%) (p=0.000). The mean waist circumference and waist-hip ratio in females were 88.8 ± 13.8 cm and 0.93 ± 0.10, respectively, which were significantly above the cut-off values for the risk of metabolic complications for South Asians 80 cm (p=0.000) and 0.85 (p=0.000). In males, the mean waist circumference was 86.9 ± 12.9 cm, significantly below the cut-off value for the South Asians (p=0.009), and the mean waist-hip ratio was 0.98, significantly above the cut-off point for South Asians (p=0.000). Conclusions: The proportion of overweight and obesity is significantly higher among the South Asians with ACS than the average South Asian population, confirming them as risk factors for cardiovascular diseases. In females, obesity is more associated with the development of ACS than in males. A higher waist circumference and the waist-hip ratio has an excellent predictive value of ACS in females. However, in males, though the waist-hip ratio has an excellent predictive value of ACS, waist circumference shows a negative correlation.

Omitting SLNB in Breast Cancer: Is a Nomogram the Answer?

Sentinel lymph node biopsy (SLNB) is standard care as a staging procedure in patients with invasive breast cancer. The axillary recurrence rate, even after positive SLNB, is low. This raises serious doubts regarding the clinical value of SLNB in early breast cancer. The purpose of this study is to select patients with low suspected axillary burden in whom SLNB might be omitted. We retrospectively analyzed 2015 primary breast cancer patients between 2007 and 2015, with 982 patients allocated to the training and 961 to the validation cohort. Variables associated with nodal disease were analyzed and used to build a nomogram for predicting nodal disease. A total of 32.8% of patients had macrometastatic disease. A predictive model was constructed based on age, cN0, morphology, grade, multifocality, and tumor size with an area under the receiver operating characteristic curve (AUC) of 0.83. Considering a false-negative rate of 5%, 32.8% of patients could be spared axillary surgery. In a subanalysis of patients with relatively favorable characteristics, 26.8% had less than 5% chance of macrometastases. We present a model with excellent predictive value that can select one-third of patients in whom SLNB is deemed not necessary because of less than 5% chance of nodal involvement. Whether missing 1 in 20 patients with macrometastatic disease is worthwhile balanced against preventing side-effects of the SLN procedure remains to be established. A number of ongoing large prospective trials evaluating the outcome of omitting SLNB are awaited. Meanwhile, this nomogram may be used for individual decision-making.

An independently validated, portable algorithm for the rapid identification of COPD patients using electronic health records

Electronic health records (EHR) provide an unprecedented opportunity to conduct large, cost-efficient, population-based studies. However, the studies of heterogeneous diseases, such as chronic obstructive pulmonary disease (COPD), often require labor-intensive clinical review and testing, limiting widespread use of these important resources. To develop a generalizable and efficient method for accurate identification of large COPD cohorts in EHRs, a COPD datamart was developed from 3420 participants meeting inclusion criteria in the Mass General Brigham Biobank. Training and test sets were selected and labeled with gold-standard COPD classifications obtained from chart review by pulmonologists. Multiple classes of algorithms were built utilizing both structured (e.g. ICD codes) and unstructured (e.g. medical notes) data via elastic net regression. Models explicitly including and excluding spirometry features were compared. External validation of the final algorithm was conducted in an independent biobank with a different EHR system. The final COPD classification model demonstrated excellent positive predictive value (PPV; 91.7%), sensitivity (71.7%), and specificity (94.4%). This algorithm performed well not only within the MGBB, but also demonstrated similar or improved classification performance in an independent biobank (PPV 93.5%, sensitivity 61.4%, specificity 90%). Ancillary comparisons showed that the classification model built including a binary feature for FEV1/FVC produced substantially higher sensitivity than those excluding. This study fills a gap in COPD research involving population-based EHRs, providing an important resource for the rapid, automated classification of COPD cases that is both cost-efficient and requires minimal information from unstructured medical records.

The Prognostic Model Based on Tumor Cell Evolution Trajectory Reveals a Different Risk Group of Hepatocellular Carcinoma.

Hepatocellular carcinoma (HCC) is one of the leading causes of cancer-related death worldwide, and heterogeneity of HCC is the major barrier in improving patient outcome. To stratify HCC patients with different degrees of malignancy and provide precise treatment strategies, we reconstructed the tumor evolution trajectory with the help of scRNA-seq data and established a 30-gene prognostic model to identify the malignant state in HCC. Patients were divided into high-risk and low-risk groups. C-index and receiver operating characteristic (ROC) curve confirmed the excellent predictive value of this model. Downstream analysis revealed the underlying molecular and functional characteristics of this model, including significantly higher genomic instability and stronger proliferation/progression potential in the high-risk group. In summary, we established a novel prognostic model to overcome the barriers caused by HCC heterogeneity and provide the possibility of better clinical management for HCC patients to improve their survival outcomes.

Social Behavior Observer Checklist: Patterns of Spontaneous Behaviors Differentiate Patients With Neurodegenerative Disease From Healthy Older Adults.

Neurodegenerative disease syndromes often affect personality and interpersonal behavior in addition to cognition, but there are few structured observational measures of altered social demeanor validated for this population. We developed the Social Behavior Observer Checklist (SBOCL), a 3-min checklist tool, to facilitate identification of patterns of interpersonal behavior that are diagnostically relevant to different neurodegenerative syndromes. Research assistants without formal clinical training in dementia used the SBOCL to describe participants' behavior, including 125 healthy older adults and 357 patients diagnosed with one of five neurodegenerative disease syndromes: 135 behavioral variant frontotemporal dementia (bvFTD), 57 semantic variant primary progressive aphasia (svPPA), 51 non-fluent variant PPA (nfvPPA), 65 progressive supranuclear palsy (PSP), and 49 amyloid-positive Alzheimer's disease syndrome (AD), all of whom had concurrent 3D T1 MRI scans available for voxel-based morphometry analysis. SBOCL item interrater reliability ranged from moderate to very high, and score elevations showed syndrome-specific patterns. Subscale scores derived from a degree*frequency product of the items had excellent positive predictive value for identifying patients. Specifically, scores above 2 on the Disorganized subscale, and above 3 on the Reactive and Insensitive subscales, were not seen in any healthy controls but were found in many patients with bvFTD, svPPA, nfvPPA, PSP, and AD syndromes. Both the Disorganized and Reactive subscale scores showed significant linear relationships with frontal and temporal gray matter volume that generalized across syndromes. With these initial psychometric characteristics, the SBOCL may be a useful measure to help non-experts identify patients who are appropriate for additional specialized dementia evaluation, without adding time to patient encounters or requiring the presence of an informant.

Prognostic Performance of Peripheral Blood Biomarkers in Identifying Seropositive Individuals at Risk of Developing Clinically Symptomatic Chagas Cardiomyopathy.

ABSTRACTBiomarkers for prognosis-based detection of Trypanosoma cruzi-infected patients presenting no clinical symptoms to cardiac Chagas disease (CD) are not available. In this study, we examined the performance of seven biomarkers in prognosis and risk of symptomatic CD development. T. cruzi-infected patients clinically asymptomatic (C/A; n = 30) or clinically symptomatic (C/S; n = 30) for cardiac disease and humans who were noninfected and healthy (N/H; n = 24) were enrolled (1 − β = 80%, α = 0.05). Serum, plasma, and peripheral blood mononuclear cells (PBMCs) were analyzed for heterogeneous nuclear ribonucleoprotein A1 (hnRNPA1), vimentin, poly(ADP-ribose) polymerase (PARP1), 8-hydroxy-2-deoxyguanosine (8-OHdG), copeptin, endostatin, and myostatin biomarkers by enzyme-linked immunosorbent assay (ELISA) and Western blotting. Secreted hnRNPA1, vimentin, PARP1, 8-OHdG, copeptin, and endostatin were increased by 1.4- to 7.0-fold in CD subjects versus N/H subjects (P < 0.001) and showed excellent predictive value in identifying the occurrence of infection (area under the receiver operating characteristic [ROC] curve [AUC], 0.935 to 0.999). Of these, vimentin, 8-OHdG, and copeptin exhibited the best performance in prognosis of C/S (versus C/A) CD, determined by binary logistic regression analysis with the Cox and Snell test (R2C&S = 0.492 to 0.688). A decline in myostatin and increase in hnRNPA1 also exhibited good predictive value in identifying C/S and C/A CD status, respectively. Furthermore, circulatory 8-OHdG (Wald χ2 = 15.065), vimentin (Wald χ2 = 14.587), and endostatin (Wald χ2 = 17.902) levels exhibited a strong association with changes in left ventricular ejection fraction and diastolic diameter (P = 0.001) and predicted the risk of cardiomyopathy development in CD patients. We have identified four biomarkers (vimentin, 8-OHdG, copeptin, and endostatin) that offer excellent value in prognosis and risk of symptomatic CD development. Decline in these four biomarkers and increase in hnRNPA1 would be useful in monitoring the efficacy of therapies and vaccines in halting CD.IMPORTANCE There is a lack of validated biomarkers for diagnosis of T. cruzi-infected individuals at risk of developing heart disease. Of the seven potential biomarkers that were screened, vimentin, 8-OHdG, copeptin, and endostatin exhibited excellent performance in distinguishing the clinical severity of Chagas disease. A decline in these four biomarkers can also be used for monitoring the therapeutic responses of infected patients to established or newly developed drugs and vaccines and precisely inform the patients about their progress. These biomarkers can easily be screened using the readily available plasma/serum samples in the clinical setting by an ELISA that is inexpensive, fast, and requires low-tech resources at the facility, equipment, and personnel levels.

Role of Ultrasound for the Diagnosis of Uterine Prolapse in Women: A Systemic Review

Background: Uterine prolapse is the herniation of the uterus into or beyond the vagina as a result of failure of the ligamentous and fascia supports. It often coexists with prolapse of the vaginal walls, involving the bladder or rectum. Objective: The aim of this study is to evaluate the role of ultrasound for the diagnosis of uterine prolapse in young women. Methodology: In this systematic review data extracted by Medline, PubMed, science direct and Obs-gyne online library that were queried for studies published between 2000 to 2021 by using specific MeSH terms. In this systematic article we reviewed 10 retrospective style analytical studies for the collection of data. Results: 10 studies conducted between the years 2000 to 2021 were included in this systematic review. The total sample size was 2500 women aged between 10-60 years. All subjects were examined by trans-perineal three-dimensional ultrasound for the detection of uterine prolapse. Out of 2500 patient almost 1000 determine with uterine prolapse on ultrasound. Ultrasound findings had excellent predictive value for the diagnosis of clinical uterine prolapse. An eye‐ shaped vaginal canal with an antero-posterior diameter of greater than 10 mm in the rendered axial plane was a sign of uterine prolapse. This sign may be helpful for detecting concealed uterine prolapse in complex pelvic organ prolapse. In fact, uterine prolapse can often be more prominent on imaging than on clinical examination. This may be due to the fact that the functional anatomy of the levator hiatus seems to matter most for uterine descent. Conclusion: From this systematic reviewed study we concluded that Ultrasound is the most appropriate form of imaging in uro-gynecology for reasons of low cost, access and performance, and due to the fact that it provides information in real time. Trans-perineal three-dimensional 2 ultrasound can evaluate the morphological changes of levator hiatus in patients with uterine prolapse, and the area of levator hiatus has high diagnostic value for uterine prolapse. Keywords: Pelvic organ prolapse; Trans-perineal Ultrasound; Uterine Prolapse; levator ani muscles. DOI: 10.7176/JHMN/92-05 Publication date: August 31 st 2021

The Predictive Value of Right Ventricular Longitudinal Strain in Pulmonary Hypertension, Heart Failure, and Valvular Diseases.

Right ventricular (RV) systolic function has an important role in the prediction of adverse outcomes, including mortality, in a wide range of cardiovascular (CV) conditions. Because of complex RV geometry and load dependency of the RV functional parameters, conventional echocardiographic parameters such as RV fractional area change (FAC) and tricuspid annular plane systolic excursion (TAPSE), have limited prognostic power in a large number of patients. RV longitudinal strain overcame the majority of these limitations, as it is angle-independent, less load-dependent, highly reproducible, and measure regional myocardial deformation. It has a high predictive value in patients with pulmonary hypertension, heart failure, congenital heart disease, ischemic heart disease, pulmonary embolism, cardiomyopathies, and valvular disease. It enables detection of subclinical RV damage even when conventional parameters of RV systolic function are in the normal range. Even though cardiac magnetic resonance-derived RV longitudinal strain showed excellent predictive value, echocardiography-derived RV strain remains the method of choice for evaluation of RV mechanics primarily due to high availability. Despite a constantly growing body of evidence that support RV longitudinal strain evaluation in the majority of CV patients, its assessment has not become the part of the routine echocardiographic examination in the majority of echocardiographic laboratories. The aim of this clinical review was to summarize the current data about the predictive value of RV longitudinal strain in patients with pulmonary hypertension, heart failure and valvular heart diseases.

Early prediction of COVID-19 severity using extracellular vesicle COPB2.

The clinical manifestations of COVID‐19 vary broadly, ranging from asymptomatic infection to acute respiratory failure and death. But the predictive biomarkers for characterizing the variability are still lacking. Since emerging evidence indicates that extracellular vesicles (EVs) and extracellular RNAs (exRNAs) are functionally involved in a number of pathological processes, we hypothesize that these extracellular components may be key determinants and/or predictors of COVID‐19 severity. To test our hypothesis, we collected serum samples from 31 patients with mild COVID‐19 symptoms at the time of their admission for discovery cohort. After symptomatic treatment without corticosteroids, 9 of the 31 patients developed severe/critical COVID‐19 symptoms. We analyzed EV protein and exRNA profiles to look for correlations between these profiles and COVID‐19 severity. Strikingly, we identified three distinct groups of markers (antiviral response‐related EV proteins, coagulation‐related markers, and liver damage‐related exRNAs) with the potential to serve as early predictive biomarkers for COVID‐19 severity. As the best predictive marker, EV COPB2 protein, a subunit of the Golgi coatomer complex, exhibited significantly higher abundance in patients remained mild than developed severe/critical COVID‐19 and healthy controls in discovery cohort (AUC 1.00 (95% CI: 1.00‐1.00)). The validation set included 40 COVID‐19 patients and 39 healthy controls, and showed exactly the same trend between the three groups with excellent predictive value (AUC 0.85 (95% CI: 0.73‐0.97)). These findings highlight the potential of EV COPB2 expression for patient stratification and for making early clinical decisions about strategies for COVID‐19 therapy.