Predicting operative outcomes of total shoulder arthroplasty using the model for end-stage liver disease score

Background

The aim of this study was to assess the efficacy of the Model for End-Stage Liver Disease (MELD) score in predicting postoperative complications following total shoulder arthroplasty (TSA).

Methods

The American College of Surgeons National Surgical Quality Improvement database was queried for all patients who underwent TSA between 2015 and 2019. The study population was subsequently classified into two categories: those with a MELD score ≥ 10 and those with a MELD score < 10. A total of 5265 patients undergoing TSA between 2015 and 2019 were included in this study. Among these, 4690 (89.1%) patients had a MELD score ≥ 10, while 575 (10.9%) patients had a MELD score < 10. Postoperative complications within 30 days of the TSA were collected. Multivariate logistic regression analysis was conducted to explore the correlation between a MELD score ≥ 10 and postoperative complications. The anchor based optimal cutoff was calculated by receiver operating characteristic analysis to determine the MELD score cutoff that most accurately predicts a specific complication. Youden's index (J) determined the optimal cutoff point calculation for the maximum sensitivity and specificity; these were deemed to be "acceptable" if the area under curve (AUC) was greater than 0.7 and "excellent" if greater than 0.8.

Results

Multivariate regression analysis found a MELD score ≥ 10 to be independently associated with higher rates of reoperation (OR, 2.08; P = .013), cardiac complications (OR, 3.37; P = .030), renal complications (OR, 7.72; P = .020), bleeding transfusions (OR, 3.23; P < .001), and nonhome discharge (OR, 1.75; P < .001). The receiver operating characteristic analysis showed that AUC for a MELD score cutoff of 7.61 as a predictor of renal complications was 0.87 (excellent) with sensitivity of 100.0% and specificity of 70.0%. AUC for a MELD score cutoff of 7.76 as a predictor of mortality was 0.76 (acceptable) with sensitivity of 81.8% and specificity of 71.0%.

Conclusion

A MELD score ≥ 10 was correlated with high rates of reoperation, cardiac complications, renal complications, bleeding transfusions, and nonhome discharge following TSA. MELD score cutoffs of 7.61 and 7.76 were effective in predicting renal complications and mortality, respectively.

The clinical utility of cystatin C based eGFR in assessing renal function among HIV/AIDs patients on ART at Mildmay Uganda

BACKGROUND

In clinical practice, Measurement of estimated glomerular filtration rates (eGFR) is the gold standard assessing renal function the glomerular filtration rate often estimated from plasma creatinine. Several studies have shown Cystatin C based eGFR (Cys C) to be a better parameter for the diagnosis of impaired renal function. Cystatin C based eGFR has been proposed as a potential renal function marker but its use in HIV&AIDS patients has not been well evaluated.

METHODS

A cross sectional study was carried out on 914 HIV&AIDS patients on antiretroviral therapy (ART) attending Mildmay Uganda for care and treatment between January to March 2015. Serum Cystatin C based eGFR was measured using the particle enhanced immunoturbidimetric assay. Creatinine was analyzed using enzymatic Creatinine PAP method and creatinine clearance was calculated according to C&G.

RESULTS

The sensitivity of Cystatin C based eGFR was 15.1% (95% CI = 8.4, 24) with specificity 99.3% (95% CI = 98- 99.7). The positive and negative predictive values were 70.0% (95% CI 45.7-88.1) and 91.2% (95% CI 98.11-92.94) respectively. The positive likelihood ratio was 18.81 and negative likelihood ratio was 0.85. Cystatin C based eGFR had diagnostic accuracy of 90.7 and area under curve was 0.768.

CONCLUSION

Cystatin C based eGFR exhibited a high specificity and a high positive likelihood ratio in diagnosis of kidney disease among HIV&AIDS patients. Cystatin C based eGFR can be used as a confirmatory test.

Multiomics Analysis Revealed Colorectal Cancer Pathogenesis

Gut microbiota-derived microbial compounds may link to the pathogenesis of colorectal cancer (CRC). However, the role of the host-microbiome in the incidence and progression of CRC remains elusive. We performed 16S rRNA sequencing, metabolomics, and proteomic studies on samples from 85 CRC patients who underwent colonoscopy examination and found two distinct changed patterns of microbiome in CRC patients. The relative abundances of Catabacter and Mogibacterium continuously increased from intramucosal carcinoma to advanced stages, whereas Clostridium, Anaerostipes, Vibrio, Flavonifractor, Holdemanella, and Hungatella were significantly altered only in intermediate lesions. Fecal metabolomics analysis exhibited consistent increases in bile acids, indoles, and urobilin as well as a decrease in heme. Serum metabolomics uncovered the highest levels of bilin, glycerides, and nucleosides together with the lowest levels of bile acids and amino acids in the stage of intermediate lesions. Three fecal and one serum dipeptides were elevated in the intermediate lesions. Proteomics analysis of colorectal tissues showed that oxidation and autophagy through the PI3K/Akt-mTOR signaling pathway contribute to the development of CRC. Diagnostic analysis showed multiomics features have good predictive capability, with AUC greater than 0.85. Our overall findings revealed new candidate biomarkers for CRC, with potentially significant diagnostic and prognostic capabilities.

Methods of determining optimal cut-point of diagnostic biomarkers with application of clinical data in ROC analysis: an update review

INTRODUCTION

An important application of ROC analysis is the determination of the optimal cut-point for biomarkers in diagnostic studies. This comprehensive review provides a framework of cut-point election for biomarkers in diagnostic medicine.

METHODS

Several methods were proposed for the selection of optional cut-points. The validity and precision of the proposed methods were discussed and the clinical application of the methods was illustrated with a practical example of clinical diagnostic data of C-reactive protein (CRP), erythrocyte sedimentation rate (ESR) and malondialdehyde (MDA) for prediction of inflammatory bowel disease (IBD) patients using the NCSS software.

RESULTS

Our results in the clinical data suggested that for CRP and MDA, the calculated cut-points of the Youden index, Euclidean index, Product and Union index methods were consistent in predicting IBD patients, while for ESR, only the Euclidean and Product methods yielded similar estimates. However, the diagnostic odds ratio (DOR) method provided more extreme values for the optimal cut-point for all biomarkers analyzed.

CONCLUSION

Overall, the four methods including the Youden index, Euclidean index, Product, and IU can produce quite similar optimal cut-points for binormal pairs with the same variance. The cut-point determined with the Youden index may not agree with the other three methods in the case of skewed distributions while DOR does not produce valid informative cut-points. Therefore, more extensive Monte Carlo simulation studies are needed to investigate the conditions of test result distributions that may lead to inconsistent findings in clinical diagnostics.

Classification performance of sEMG and kinematic parameters for distinguishing between non-lame and induced lameness conditions in horses

Despite its proven research applications, it remains unknown whether surface electromyography (sEMG) can be used clinically to discriminate non-lame from lame conditions in horses. This study compared the classification performance of sEMG absolute value (sEMGabs) and asymmetry (sEMGasym) parameters, alongside validated kinematic upper-body asymmetry parameters, for distinguishing non-lame from induced fore- (iFL) and hindlimb (iHL) lameness. Bilateral sEMG and 3D-kinematic data were collected from clinically non-lame horses (n = 8) during in-hand trot. iFL and iHL (2-3/5 AAEP) were induced on separate days using a modified horseshoe, with baseline data initially collected each day. sEMG signals were DC-offset removed, high-pass filtered (40 Hz), and full-wave rectified. Normalized, average rectified value (ARV) was calculated for each muscle and stride (sEMGabs), with the difference between right and left-side ARV representing sEMGasym. Asymmetry parameters (MinDiff, MaxDiff, Hip Hike) were calculated from poll, withers, and pelvis vertical displacement. Receiver-operating-characteristic (ROC) and area under the curve (AUC) analysis determined the accuracy of each parameter for distinguishing baseline from iFL or iHL. Both sEMG parameters performed better for detecting iHL (0.97 ≥ AUC ≥ 0.48) compared to iFL (0.77 ≥ AUC ≥ 0.49). sEMGabs performed better (0.97 ≥ AUC ≥ 0.49) than sEMGasym (0.76 ≥ AUC ≥ 0.48) for detecting both iFL and iHL. Like previous studies, MinDiff Poll and Pelvis asymmetry parameters (MinDiff, MaxDiff, Hip Hike) demonstrated excellent discrimination for iFL and iHL, respectively (AUC > 0.95). Findings support future development of multivariate lameness-detection approaches that combine kinematics and sEMG. This may provide a more comprehensive approach to diagnosis, treatment, and monitoring of equine lameness, by measuring the underlying functional cause(s) at a neuromuscular level.

Development of recombinant capsid protein-based single serum dilution ELISA for sero-detection of porcine circovirus type 2 infection in pigs

Porcine Circovirus 2 (PCV2) is the major causative agent of postweaning multisystemic wasting syndrome (PMWS) of swine and is one of the reasons for severe economic loss in swine industry. In India, there is a considerable prevalence rate of PCV2 infection in pig population, PCV2d being the most prominent genotype. Proper sero-diagnosis and sero-surveillance of the disease is formulated as an effective control measure. In this study, a recombinant capsid protein-based single serum dilution indirect ELISA was developed for determination of antibody titre of the infected pigs. The capsid protein (Cap) of PCV2d was produced in Saccharomyces cerevisiae cells and the capsid protein was purified by affinity chromatography. This recombinant protein was used as a coating antigen to develop a cost effective, highly sensitive and specific single serum dilution ELISA. The in-house developed ELISA was optimized to be used in a 1:200 single serum dilution. The developed ELISA along with a commercial ELISA kit were compared with a sensitive immuno-peroxidase assay (IPMA) by receiver-operating characteristics (ROC) test. Our results showed that the developed single serum dilution ELISA had a higher sensitivity and specificity in comparison to the commercial ELISA. The area under the ROC curve (AUC) also confirmed that the developed ELISA had a better overall diagnostic performance in comparison to the commercial ELISA kit.

Evaluating joint confidence region of hypervolume under ROC manifold and generalized Youden index

In biomarker evaluation/diagnostic studies, the hypervolume under the receiver operating characteristic manifold (HUM K $$ {\mathrm{HUM}}_K $$ ) and the generalized Youden index (J K $$ {J}_K $$ ) are the most popular measures for assessing classification accuracy under multiple classes. WhileHUM K $$ {\mathrm{HUM}}_K $$ is frequently used to evaluate the overall accuracy,J K $$ {J}_K $$ provides direct measure of accuracy at the optimal cut-points. Simultaneous evaluation ofHUM K $$ {\mathrm{HUM}}_K $$ andJ K $$ {J}_K $$ provides a comprehensive picture about the classification accuracy of the biomarker/diagnostic test under consideration. This article studies both parametric and non-parametric approaches for estimating the confidence region ofHUM K $$ {\mathrm{HUM}}_K $$ andJ K $$ {J}_K $$ for a single biomarker. The performances of the proposed methods are investigated by an extensive simulation study and are applied to a real data set from the Alzheimer's Disease Neuroimaging Initiative.

Semi-supervised ROC analysis for reliable and streamlined evaluation of phenotyping algorithms

OBJECTIVE

High-throughput phenotyping will accelerate the use of electronic health records (EHRs) for translational research. A critical roadblock is the extensive medical supervision required for phenotyping algorithm (PA) estimation and evaluation. To address this challenge, numerous weakly-supervised learning methods have been proposed. However, there is a paucity of methods for reliably evaluating the predictive performance of PAs when a very small proportion of the data is labeled. To fill this gap, we introduce a semi-supervised approach (ssROC) for estimation of the receiver operating characteristic (ROC) parameters of PAs (eg, sensitivity, specificity).

MATERIALS AND METHODS

ssROC uses a small labeled dataset to nonparametrically impute missing labels. The imputations are then used for ROC parameter estimation to yield more precise estimates of PA performance relative to classical supervised ROC analysis (supROC) using only labeled data. We evaluated ssROC with synthetic, semi-synthetic, and EHR data from Mass General Brigham (MGB).

RESULTS

ssROC produced ROC parameter estimates with minimal bias and significantly lower variance than supROC in the simulated and semi-synthetic data. For the 5 PAs from MGB, the estimates from ssROC are 30% to 60% less variable than supROC on average.

DISCUSSION

ssROC enables precise evaluation of PA performance without demanding large volumes of labeled data. ssROC is also easily implementable in open-source R software.

CONCLUSION

When used in conjunction with weakly-supervised PAs, ssROC facilitates the reliable and streamlined phenotyping necessary for EHR-based research.

Diagnostic Accuracy of Biomarkers and International Ovarian Tumor Analysis Simple Rules in Diagnosis of Ovarian Cancer

This study investigated whether combining International Ovarian Tumor Analysis (IOTA) Simple Rules with tumor biomarkers would improve the diagnostic accuracy for early detection of adnexal malignancies. Receiver operating characteristic curve analysis of suspected adnexal tumors was performed in 226 women admitted for surgery at the University Clinical Center of Kosovo. Primary outcome was the diagnostic accuracy of the combination of adnexal mass biomarkers and IOTA Simple Rules. IOTA Simple Rules combined with biomarker indications increased the diagnostic accuracy of classifying adnexal masses. Data analysis of individual measures showed that ferritin had the lowest rate of sensitivity.

Sensitivity and specificity of secondary dose calculation for head and neck treatment plans

PURPOSE

Secondary dose calculation (SDC) with an independent algorithm is one option to perform plan-specific quality assurance (QA). While measurement-based QA can potentially detect errors in plan delivery, the dose values are typically only compared to calculations on homogeneous phantom geometries instead of patient CT data. We analyzed the sensitivity and specificity of an SDC software by purposely introducing different errors and determined thresholds for optimal decisions.

METHODS

Thirty head and neck VMAT plans and 30 modifications of those plans, including errors related to density and beam modelling, were recalculated using RadCalc with a Monte Carlo algorithm. Decision thresholds were obtained by receiver operating characteristics (ROC) analysis. For comparison, measurement-based QA using the ArcCHECK phantom was carried out and evaluated in the same way.

RESULTS

Despite optimized decision thresholds, none of the systems was able to reliably detect all errors. ArcCHECK analysis using a 2%/2 mm criterion with a threshold of 91.1% had an area under the curve (AUC) of 0.80. Evaluating differences in recalculated and planned DVH parameter of the target structures in RadCalc with a 2% threshold an AUC of 0.86 was achieved. Out-of-field deviations could be attributed to weaknesses in the beam model.

CONCLUSIONS

Secondary dose calculation with RadCalc is an alternative to established measurement-based phantom QA. Different tools catch different errors; therefore, a combination of approaches should be preferred.

Are smartphones and low-cost external microphones comparable for measuring time-domain acoustic parameters?

PURPOSE

This study examined and compared the diagnostic accuracy and correlation levels of the acoustic parameters of the audio recordings obtained from smartphones on two operating systems and from dynamic and condenser types of external microphones.

METHOD

The study included 87 adults: 57 with voice disorder and 30 with a healthy voice. Each participant was asked to perform a sustained vowel phonation (/a/). The recordings were taken simultaneously using five microphones AKG-P220, Shure-SM58, Samson Go Mic, Apple iPhone 6, and Samsung Galaxy J7 Pro microphones in an acoustically insulated cabinet. Acoustic examinations were performed using Praat version 6.2.09. The data were examined using Pearson correlation and receiver-operating characteristic (ROC) analyses.

RESULTS

The parameters with the highest area under curve (AUC) values among all microphone recordings in the time-domain analyses were the frequency perturbation parameters. Additionally, considering the correlation coefficients obtained by synchronizing the microphones with each other and the AUC values together, the parameter with the highest correlation coefficient and diagnostic accuracy values was the jitter-local parameter.

CONCLUSION

Period-to-period perturbation parameters obtained from audio recordings made with smartphones show similar levels of diagnostic accuracy to external microphones used in clinical conditions.

Elevated concentrations of Neu5Ac and Neu5,9Ac2 in human plasma: potential biomarkers of cardiovascular disease

Cardiovascular disease (CVD) is a group of health conditions affecting the heart and vascular system with very high prevalence and mortality rates. The presence of CVD is characterised by high levels of inflammation which have previously been associated with increased plasma concentrations of N-acetyl neuraminic acid (Neu5Ac). While Neu5Ac has been studied in the context of CVD, Neu5,9Ac2 has not, despite being the second most abundant sialic acid in human plasma. A small-scale pilot study of thirty plasma samples from patients with diagnosed CVD, and thirty age and sex-matched healthy controls, was designed to gain insight into sialic acids as biomarkers for CVD and potential future areas of study. Each sample was assayed for Neu5Ac and Neu5,9Ac2 concentrations. Mean Neu5Ac and Neu5,9Ac2 concentrations were significantly elevated in patients with CVD compared to healthy controls (Neu5Ac: P < 0.001; Neu5,9Ac2: P < 0.04). Receiver operator curve (ROC) analysis indicated that both Neu5Ac and Neu5,9Ac2 have reasonable predictive power for the presence of CVD (Neu5Ac AUC: 0.86; Neu5,9Ac2 AUC: 0.71). However, while Neu5Ac had both good sensitivity (0.82) and specificity (0.81), Neu5,9Ac2 had equivalent specificity (0.81) but very poor sensitivity (0.44). A combination marker of Neu5Ac + Neu5,9Ac2 showed improvement over Neu5Ac alone in terms of predictive power (AUC: 0.93), sensitivity (0.87), and specificity (0.90). Comparison to a known inflammatory marker, high sensitivity c-reactive protein (hs-CRP: P-value: NS, ROC:0.50) was carried out, showing that both Neu5Ac and Neu5,9Ac2 outperformed this marker. Further to this, hs-CRP values were combined with the three different sialic acid markers to determine any effect on the AUC values. A slight improvement in AUC was noted for each of the combinations, with Neu5Ac + Neu5,9Ac2 + hs-CRP giving the best AUC of 0.97 overall. Thus, Neu5Ac would appear to offer good potential as a predictive marker for the presence of CVD, which the addition of Neu5,9Ac2 predictive power improves, with further improvement seen by the addition of hs-CRP.

Characterization of a miRNA Signature with Enhanced Diagnostic and Prognostic Power for Patients with Bladder Carcinoma

Bladder carcinoma is globally among the most prevalent cancers and is associated with a high mortality rate at advanced stages. Its detection relies on invasive diagnostic methods that are unpleasant for the patient. Non-invasive molecular biomarkers, such as miRNAs, could serve as alternatives for early detection and prognosis of this malignancy. We designed a computational approach that combines transcriptome profiling, survival analyses, and calculation of diagnostic power in order to isolate miRNA signatures with high diagnostic and prognostic utility. Our analysis of TCGA-BLCA data from 429 patients yielded one miRNA signature, consisting of five upregulated and three downregulated miRNAs with cumulative diagnostic power that outperforms current diagnostic methods. The same miRNAs have a strong prognostic significance since their expression is associated with the overall survival of bladder cancer patients. We evaluated the expression of this signature in 19 solid cancer types, supporting its unique diagnostic utility for bladder carcinoma. We provide computational evidence regarding the functional implications of this miRNA signature in cell cycle regulation, demonstrating its abundance in body fluids, including peripheral blood and urine. Our study characterized a novel miRNA signature with the potential to serve as a non-invasive method for bladder cancer diagnosis and prognosis.

Discriminant Analysis of Aroma Differences between Cow Milk Powder and Special Milk Powder (Donkey, Camel, and Horse Milk Powder) in Xinjiang Based on GC-IMS and Multivariate Statistical Methods

In order to explore the aromatic differences between Xinjiang cow milk powder and specialty milk powder (donkey, camel, and horse milk powder), Gas Chromatography-Ion Mobility Spectrometry (GC-IMS) analysis was employed to investigate the volatile compounds in these four types of milk powders. A total of 61 volatile substances were detected, with ketones, aldehydes, and alcohols being the primary flavor components in the milk powders. While the aromatic components of the different milk powders showed similarities in terms of types, there were significant differences in their concentrations, exhibiting distinct characteristics for each type. The Partial Least Squares Discriminant Analysis (PLS-DA) showed that there were 15, 14, and 23 volatile compounds that could be used for discrimination of cow milk powder against specialty milk powders, respectively. And it was validated by Receiver Operating Characteristic (ROC) analysis, and finally, 8, 6, and 19 volatile compounds were identified as valid differential marker substances. To facilitate visual discrimination between the different milk powders, we established GC-IMS fingerprint spectra based on the final discriminant markers. These studies provide theoretical guidance for the application of volatile compounds to discriminate adulteration of milk powder marketed in Xinjiang.

Voice Handicap Index: Cut-Off Points for Screening European Portuguese With Voice Disorders

OBJECTIVES

To determine cut-off values of the Voice Handicap Index (VHI) and the shortened version (VHI-10) for European Portuguese (EP) with voice disorders. In addition, to analyze the discriminatory power of individual items of the VHI-10 and the ability to detect differences in various Ear Nose and Throat (ENT) diagnoses.

STUDY DESIGN

Cross-sectional cohort study.

METHODS

All participants completed the EP VHI and a 4-point self-assessment of voice disorder severity. The case group (subjects with voice disorders) underwent assessment through strobovideolaryngoscopy examinations by ENT surgeons and perceptual analyses by speech-language pathologists (SLPs). In contrast, the control group was evaluated solely by SLPs. Data were analyzed using a receiver-operating characteristic curve to determine the accuracy and cut-off values of the VHI and VHI-10.

RESULTS

The study involved a sample of 350 adults (171 cases and 179 controls), predominantly women aged 18-88 years. The area under curve (AUC) for VHI and VHI-10 was 0.997 [95% confidence interval (CI): 0.992-1] and 0.998 [95% CI: 0.995-0.999], respectively. Optimal cut-off values were identified as 13.5 for VHI (0.994 sensitivity and 0.989 specificity) and 5.5 for VHI-10 (0.977 sensitivity and 0.955 specificity). Each individual item within the VHI-10 significantly contributed to the overall assessment, exhibiting varying discriminatory power ranging from excellent (AUC = 0.937) to poor (AUC = 0.637). Significant differences were found in the case group between neurogenic disorders and healthy larynx (P = 0.014), structural and physiologic minor laryngeal abnormalities (P = 0.006), and inflammatory disorders (P = 0.043).

CONCLUSIONS

The VHI and the VHI-10 exhibited accurate screening properties for predicting EP speakers with voice disorders.

Benchmarking different docking protocols for predicting the binding poses of ligands complexed with cyclooxygenase enzymes and screening chemical libraries

Introduction

Non-steroidal anti-inflammatory drugs (NSAIDs) constitute an important class of pharmaceuticals acting on cyclooxygenase COX-1 and COX-2 enzymes. Due to their numerous severe side effects, it is necessary to search for new selective, safe, and effective anti-inflammatory drugs. In silico design of novel therapeutics plays an important role in nowadays drug discovery pipelines. In most cases, the design strategies require the use of molecular docking calculations. The docking procedure may require case-specific condition for a successful result. Additionally, many different docking programs are available, which highlights the importance of identifying the most proper docking method and condition for a given problem.

Methods

In the current work, the performances of five popular molecular docking programs, namely, GOLD, AutoDock, FlexX, Molegro Virtual Docker (MVD) and Glide to predict the binding mode of co- crystallized inhibitors in the structures of known complexes available for cyclooxygenases were evaluated. Furthermore, the best performers, Glide, AutoDock, GOLD and FlexX, were further evaluated in docking-based virtual screening of libraries consisted of active ligands and decoy molecules for cyclooxygenase enzymes and the obtained docking scores were assessed by receiver operating characteristics (ROC) analysis.

Results

The results of docking experiments indicated that Glide program outperformed other docking programs by correctly predicting the binding poses (RMSD less than 2 Å) of all studied co-crystallized ligands of COX-1 and COX-2 enzymes (i.e., the performance was 100%). However, the performances of the other studied docking methods for correctly predicting the binding poses of the ligands were between 59% to 82%. Virtual screening results treated by ROC analysis revealed that all tested methods are useful tools for classification and enrichment of molecules targeting COX enzymes. The obtained AUCs range between 0.61-0.92 with enrichment factors of 8 - 40 folds.

Conclusion

The obtained results support the importance of choosing appropriate docking method for predicting ligand-receptor binding modes, and provide specific information about docking calculations on COXs ligands.

Inflammatory biomarkers in sebum for identifying skin damage in patients with a Stage I pressure ulcer in the pelvic region: A single centre observational, longitudinal cohort study with elderly patients

Pressure Ulcers (PU) are a major burden for affected patients and healthcare providers. Current detection methods involve visual assessments of the skin by healthcare professionals. This has been shown to be subjective and unreliable, with challenges associated with identifying erythema in darker colour skin. Although there exists a number of promising non-invasive biophysical techniques such as ultrasound, capacitance measurements, and thermography, the present study focuses on directly measuring the changes in the inflammatory status of the skin and underlying tissues. Therefore, in this study, we aim to analyse inflammatory cytokines collected through non-invasive sampling techniques to detect early signs of skin damage. Thirty hospitalised patients presenting with Stage I PU were recruited to evaluate the inflammatory response of skin at the site of damage and an adjacent healthy control site. Sebutapes were collected over three sessions to investigate the temporal changes in the inflammatory response. The panel of cytokines investigated included high-abundance cytokines, namely, IL-1α and IL-1RA, and low abundance cytokines; IL-6, IL-8, TNF-α, INF-γ, IL-33, IL-1β and G-CSF. Spatial and temporal differences between sites were assessed and thresholds were used to determine the sensitivity and specificity of each biomarker. The results suggest significant (P < .05) spatial changes in the inflammatory response, with upregulation of IL-1α, IL-8, and G-CSF as well as down-regulation of IL-1RA over the Stage I PU compared with the adjacent control site. There were no significant temporal differences between the three sessions. Selected cytokines, namely, IL-1α, IL-1RA, IL-8, G-CSF, and the ratio IL-1α/IL-1RA offered clear delineation in the classification of healthy and Stage-I PU skin sites, with receiver operating characteristic curves demonstrating high sensitivity and specificity. There were limited influences of intrinsic and extrinsic factors on the biomarker response. Inflammatory markers provided a high level of discrimination between the sites presenting with Stage I PU and an adjacent healthy skin site, in a cohort of elderly inpatients. Indeed, the ratio of IL-1α to IL-1RA provided the highest sensitivity and specificity, indicative that inflammatory homeostasis is affected at the PU site. There was a marginal influence of intrinsic and extrinsic factors, demonstrating the localised effects of the inflammation. Further studies are required to investigate the potential of inflammatory cytokines incorporated within Point of Care technologies, to support routine clinical use.

Leptin, resistin and fetuin a concentration as the potential useful biomarkers in stable COPD - An exploratory study

Adipokines, which have pleiotropic activities, are known to be involved in inflammation as adipocytokines. The aim of the current study was to investigate selected adipocytokine levels in the serum of stable chronic obstructive pulmonary disease COPD patients and healthy controls, to assess a potential association between the investigated biomarkers and selected parameters and to conduct receiving operating curve (ROC) analysis. Twenty-five COPD patients and 30 healthy controls were enrolled in the current study. Serum levels of adiponectin, leptin, resistin, chemerin and fetuin A were measured using an enzyme-linked immunosorbent assay (ELISA) method. Both leptin and resistin concentrations were significantly elevated in COPD patients and differentiated them from control subjects. Fetuin A levels were lower in COPD patients and may be related to the disease. Further studies in larger cohorts are needed to confirm the findings of this exploratory study.

Comprehensive transcriptomics and metabolomics analyses reveal that hyperhomocysteinemia is a high risk factor for coronary artery disease in a chinese obese population aged 40-65: a prospective cross-sectional study

BACKGROUND

Clinical observations suggest a complex relationship between obesity and coronary artery disease (CAD). This study aimed to characterize the intermediate metabolism phenotypes among obese patients with CAD and without CAD.

METHODS

Sixty-two participants who consecutively underwent coronary angiography were enrolled in the discovery cohort. Transcriptional and untargeted metabolomics analyses were carried out to screen for key molecular changes between obese patients with CAD (CAD obese), without CAD (Non-CAD obese), and Non-CAD leans. A targeted GC-MS metabolomics approach was used to further identify differentially expressed metabolites in the validation cohorts. Regression and receiver operator curve analysis were performed to validate the risk model.

RESULTS

We found common aberrantly expressed pathways both at the transcriptional and metabolomics levels. These pathways included cysteine and methionine metabolism and arginine and proline metabolism. Untargeted metabolomics revealed that S-adenosylhomocysteine (SAH), 3-hydroxybenzoic acid, 2-hydroxyhippuric acid, nicotinuric acid, and 2-arachidonoyl glycerol were significantly elevated in the CAD obese group compared to the other two groups. In the validation study, targeted cysteine and methionine metabolomics analyses showed that homocysteine (Hcy), SAH, and choline were significantly increased in the CAD obese group compared with the Non-CAD obese group, while betaine, 5-methylpropanedioic acid, S-adenosylmethionine, 4-PA, and vitamin B2 (VB2) showed no significant differences. Multivariate analyses showed that Hcy was an independent predictor of obesity with CAD (hazard ratio 1.7; 95%CI 1.2-2.6). The area under the curve based on the Hcy metabolomic (HCY-Mtb) index was 0.819, and up to 0.877 for the HCY-Mtb.index plus clinical variables.

CONCLUSION

This is the first study to propose that obesity with hyperhomocysteinemia is a useful intermediate metabolism phenotype that could be used to identify obese patients at high risk for developing CAD.

Relationship between image information content and observer performance in digital intraoral radiography

OBJECTIVES

This study conducted a receiver operating characteristic (ROC) analysis by applying improved cluster signal-to-noise (CSN) analysis to digital intraoral radiographs and develop an observer-free method of analyzing image quality related to the observer performance in the detection task.

METHODS

Two aluminum step phantoms with a thickness interval of 1.0 mm were used for this study. One phantom had holes of increasing depth (from 0.05 to 0.35 mm) and the other had no holes. Phantom images were obtained under various exposure dose and image capture modes using a dental X-ray unit, a photostimulable phosphor imaging plate, and scanner system. These phantom images were analyzed using the FindFoci plugin in ImageJ software. Subsequently, true positive rates (TPRs) and false positive rates (FPRs) were calculated by analyzing phantom images with and without holes. We constructed ROC curves by plotting the TPRs against the FPRs and calculated the area under the ROC curve (AUC). Using the same phantom images with holes, eight observers assessed the number of detectable holes. Correlations between observer detection performance and AUC values were evaluated.

RESULTS

AUC values increased as the exposure dose increased and showed different tendencies depending on the image capture mode. The AUC values showed a high correlation with observer detection performance (r = 0.76).

CONCLUSIONS

AUC values obtained from CSN analysis reflect image quality and replace the observer detection performance test of image quality.

Quantitative ultrasound of the calcaneus (QUS): A valuable tool in the identification of patients with non-metastatic prostate cancer requiring screening for osteoporosis

Non-metastatic prostate cancer (PCa) patients are at increased risk for osteoporosis and fractures mainly due to androgen deprivation therapy (ADT)-associated hypogonadism, but this remains largely underdiagnosed and untreated. In this study, we examine the value of pre-screening calcaneal QUS in identifying patients who should be referred for screening for osteoporosis using dual-energy X-Ray absorptiometry (DXA). In a single-center retrospective cross-sectional cohort study, we analysed data on DXA and calcaneal QUS measurements systematically collected between 2011 and 2013 in all non-metastatic PCa patients attending our Uro-Oncological Clinic at the Leiden University Medical Center. Receiver operating characteristic curves were used to assess the positive (PPV) and negative (NPV) predictive values of QUS T-scores of 0, -1.0, and - 1.8 in identifying DXA-diagnosed osteoporosis (T-scores ≤ - 2.5 and ≤ -2) at lumbar spine and/or femoral neck. Complete sets of data were available in 256 patients, median age 70.9 (53.6-89.5) years; 93.0 % had received local treatment, 84.4 % with additional ADT. Prevalence of osteoporosis and osteopenia was respectively 10.5 % and 53 %. Mean QUS T-score was -0.54 ± 1.58. Whereas PPV at any QUS T-score was <25 %, precluding the use of QUS as surrogate for DXA in screening for osteoporosis, QUS T-scores of -1.0 to 0.0 had a NPV of ≥94.5 % for DXA T-scores ≤ 2.5 and ≤ -2 at any site, confidently identifying patients least likely to have osteoporosis, thereby significantly reducing the number of patients requiring DXA screening for diagnosing osteoporosis by up to two-third. Osteoporosis screening is a significant unmet need in non-metastatic prostate cancer patients treated with ADT, and QUS may represent a valuable alternative pre-screening strategy to overcome logistics, time demands, and economic barriers encountered with current strategies for osteoporosis screening in these patients.

Summary

Osteoporosis and associated increased fracture risk are common in non-metastatic prostate carcinoma, mainly due to androgen deprivation therapy, but these often remain underdiagnosed and untreated. We demonstrate that QUS is a safe, less costly pre-screen tool that reduces by up to two-third the number of patients requiring referral for DXA for osteoporosis screening.

[Evaluation of the dynamics of detection of viable SARS-CoV-2 (Coronaviridae: Betacoronavirus: Sarbecovirus) in biological samples obtained from patients with COVID-19 in a health care setting, as one of the indicators of the infectivity of the virus]

INTRODUCTION

The study of the mechanisms of transmission of the SARS-CoV-2 virus is the basis for building a strategy for anti-epidemic measures in the context of the COVID-19 pandemic. Understanding in what time frame a patient can spread SARS-CoV-2 is just as important as knowing the transmission mechanisms themselves. This information is necessary to develop effective measures to prevent infection by breaking the chains of transmission of the virus. The aim of the work is to identify the infectious SARS-CoV-2 virus in patient samples in the course of the disease and to determine the duration of virus shedding in patients with varying severity of COVID-19.

MATERIALS AND METHODS

In patients included in the study, biomaterial (nasopharyngeal swabs) was subjected to analysis by quantitative RT-PCR and virological determination of infectivity of the virus.

RESULTS

We have determined the timeframe of maintaining the infectivity of the virus in patients hospitalized with severe and moderate COVID-19. Based on the results of the study, we made an analysis of the relationship between the amount of detected SARS-CoV-2 RNA and the infectivity of the virus in vitro in patients with COVID-19. The median time of the infectious virus shedding was 8 days. In addition, a comparative analysis of different protocols for the detection of the viral RNA in relation to the identification of the infectious virus was carried out.

CONCLUSION

The obtained data make it possible to assess the dynamics of SARS-CoV-2 detection and viral load in patients with COVID-19 and indicate the significance of these parameters for the subsequent spread of the virus and the organization of preventive measures.

Comparison of Diagnostic Value of the SARC-F and Its Four Modified Versions in Polish Community-Dwelling Older Adults

Purpose

Sarcopenia is associated with adverse outcomes in elderly persons, including functional disability, falls, and even death. Therefore, older adults should be routinely screened for sarcopenia. Due to the unsatisfactory sensitivity of the SARC-F questionnaire, four modified versions have been elaborated: SARC-CalF, SARC-F+EBM, SARC-F+AC, and SARC-CalF+AC. The diagnostic performance of the four modifications of SARC-F has yet to be compared.

Materials and Methods

We performed the sensitivity/specificity analysis and compared the overall diagnostic accuracy of the five questionnaires in 260 community-dwelling volunteers aged ≥ 60 yrs from Poland. The study was performed against three reference standards: the European Working Group on Sarcopenia in Older People (EWGSOP1), EWGSOP2, and modified EWGSOP2 criteria.

Results

The prevalence of sarcopenia based on these criteria was 20.8%, 11.2%, and 17.3%, respectively. Concerning the three reference standards, the sensitivity of SARC-F, SARC-CalF, SARC-F+EBM, SARC-F+AC, and SARC-CalF+AC ranged from 31.5-44.8%, 57.4-65.5%, 48.1-62.1%, 71.4-79.2% and 71.4-79.2%, respectively. The specificity ranged from 86.6-87.4%, 86.1-90.3%, 82.3-84.0%, 69.4-78.2%, and 72.1-79.7%, respectively. The AUCs of SARC-F, SARC-CalF, SARC-F+EBM, SARC-F+AC, and SARC-CalF+AC ranged from 0.643-0.700, 0.757-0.792, 0.740-0.775, 0.767-0.812 and 0.771-0.852, respectively.

Conclusion

The SARC-F questionnaire has low diagnostic accuracy, which limits its usefulness as a sarcopenia screening tool. Incorporating two simple anthropometric measurements, ie, arm and calf circumference, notably improves the diagnostic performance of SARC-F. Based on our results, SARC-CalF+AC seems to be the best screening tool for sarcopenia screening in community-dwelling older adults.

Evaluation of the Sysmex UF-4000i urine analyzer as a screening test to rule out urinary tract infection and reduce urine cultures

INTRODUCTION

Urinary tract infection (UTI) diagnosis by urine culture is time- and labor- consuming. In the Ibn Rochd microbiology laboratory, up to 70% of urine culture samples yield no growth or insignificant growth.

OBJECTIVE

To evaluate the new generation of Sysmex UF-4000i fluorescence flow cytometry analyzer with a blue semiconducting laser as a method to rule out negative urine samples for UTI, in comparison of urine culture.

MATERIAL AND METHODS

Flow cytometry and microbiological analysis were performed on 502 urine samples included in the study. We used ROC analysis to determine cutoff points at which optimal sensitivity and specificity are achieved for clinical use.

RESULTS

Our results showed that bacteria count at a cut-off of 100/μL, and/or the leucocytes count ≥ 45/μL are the optimal indicator for positive culture results. At these cut off, bacteria sensitivity (SE), specificity (SP), Positive predictive value (PPV) and negative predictive value (NPV) were 97,3%, 95%, 87,8% and 98,8% respectively. For leucocytes, SE, SP, PPV and NPV were 99,1%, 95,8%, 88,6% and 99,7% respectively.

DISCUSSION AND CONCLUSION

The bacterial and leucocytes counts generated by UF-4000i analysis may be useful in our context as a rapid screening to exclude UTI by reducing about 70% of urines cultures and then workload. Nevertheless, further validation is needed for different patient groups especially with urological disease or immunocompromised patients.

Leucine aminopeptidase 3:a promising serum biomarker candidate for nonalcoholic steatohepatitis diagnosis

BACKGROUND & AIMS

Nonalcoholic steatohepatitis (NASH) is a highly prevalent liver disease that lacks targeted therapeutic drugs and non-invasive diagnostic methods. Increasing evidence demonstrated that aberrant expression of leucine aminopeptidase 3 (LAP3) is involved in NASH. Herein, we aimed to investigate whether LAP3 can be a promising serum biomarker for NASH diagnosis.

METHODS

Liver tissues and serum from NASH rats, serum from NASH patients, and liver biopsies from chronic hepatitis B (CHB) patients combined with NASH (CHB+NASH) were obtained to evaluate the LAP3 level. Correlation analysis was conducted to evaluate the association between LAP3 expression and clinical indexes in CHB patients and CHB+NASH patients. ROC curve analysis of LAP3 in the serum and liver was applied to assess whether LAP3 can be a promising biomarker for NASH diagnosis.

RESULTS

LAP3 was significantly upregulated in serum and hepatocytes of NASH rats and patients with NASH. Correlation analysis revealed that LAP3 in the liver of CHB patients and CHB+NASH patients showed a strong positive correlation with lipidome indicators total cholesterol (TC) and triglyceride (TG), and liver fibrosis indicator hyaluronic acid (HA), which showed a negative correlation with the international normalized ratio of prothrombin coagulation (INR) and liver injury indicator aspartate aminotransferase (AST). For NASH, the diagnostic accuracy of ALT > LAP3 > AST, the sensitivity LAP3 (0.87) > ALT (0.5957) > AST (0.2941), the specificity AST (0.975) > ALT (0.9) > LAP3 (0.5).

CONCLUSION

Our data urge that LAP3 can serve as a promising serum biomarker candidate for NASH diagnosis.

Relative decline in serum albumin help to predict anastomotic leakage for female patients following sphincter-preserving rectal surgery

BACKGROUND

Patients with normal preoperative serum albumin still suffer from a significant reduction in serum albumin after major abdominal surgery. The current study aims to explore the predictive value of ∆ALB for AL in patients with normal serum albumin and examine whether there is a gender difference in the prediction of AL.

METHODS

Medical reports of consecutive patients undergoing elective sphincter-preserving rectal surgery between July 2010 and June 2016 were reviewed. Receiver operating characteristic (ROC) analysis was adopted to examine the predictive ability of ∆ALB and determine the cut-off value according to the Youden index. The logistic regression model was performed identify independent risk factors for AL.

RESULTS

Out of the 499 eligible patients, 40 experienced AL. Results of the ROC analyses showed that ΔALB displayed a significant predictive value for females, and the AUC value was 0.675 (P = 0.024), with a sensitivity of 93%. In male patients, the AUC was 0.575 (P = 0.22), but did not reach a significant level. In the multivariate analysis, ∆ALB ≥ 27.2% and low tumor location prove to be independent risk factors for AL in female patients.

CONCLUSIONS

The current study suggested that there may be a gender difference in the prediction of AL and ∆ ALB can serve as a potential predictive biomarker for AL in females. A cut-off value of the relative decline in serum albumin can help predict AL in female patients as early as postoperative day 2. Although our study needs further external validation, our findings may provide an earlier, easier and cheaper biomarker for the detection of AL.

Development of prediction models based on respiratory assessments to determine the need for non-invasive ventilation in patients with myotonic dystrophy type 1

INTRODUCTION

Myotonic dystrophy type 1 is a slowly progressive, multisystem, autosomal dominant disorder, in which the impairments of respiratory systems represent one of the main causes of death.

OBJECTIVE

The aim of our study is to develop prediction models to identify the most appropriate test(s) providing indication for NIV.

METHODS

DM1 patients attending the NEMO Clinical Center (Milan) between January 2008 and July 2020, who had been subjected to a complete battery of respiratory tests, were retrospectively recruited. Demographic, clinical, and anthropometric characteristics were collected, as well as arterial blood gas (ABG) analysis, spirometry, respiratory muscle strength, cough efficacy, and nocturnal oximetry as respiratory assessments. Patients were stratified in those requiring NIV and those with normal respiratory function.

RESULTS

Out of 151 DM1 patients (median age: 44 years [35.00-53.00]; male/female ratio: 0.80 (67/84)), 76 had an indication for NIV initiation (50.33%). ABG, spirometry, and nocturnal oximetry prediction models resulted in an excellent discriminatory ability in distinguishing patients who needed NIV from those who did not (AUC of 0.818, 0.808, and 0.935, respectively). An easy-to-use calculator was developed to automatically determine a score of NIV necessity based on the prediction equations generated from each aforementioned prediction model.

CONCLUSIONS

The proposed prediction models may help to identify which patients are at a higher risk of requiring ventilator support and therefore help in defining individual management plans and criteria for specific interventions early in the disease course.

Clinical Features and Computed Tomography Radiomics-Based Model for Predicting Pancreatic Ductal Adenocarcinoma and Focal Mass-Forming Pancreatitis

Objective: To establish a predictive model distinguishing focal mass-forming pancreatitis (FMFP) from pancreatic ductal adenocarcinoma (PDAC) based on computed tomography (CT) radiomics and clinical data. Methods: A total of 78 FMFP patients (FMFP group) and 120 PDAC patients (PDAC group) who were admitted to Xiangyang No.1 People's Hospital and Xiangyang Central Hospital from February 2012 to May 2021 and were pathologically diagnosed were included in this study, and were input to set up the training set and test set at a ratio of 7:3. The 3Dslicer software was used to extract the radiomic features and radiomic scores (Radscores) of the 2 groups, and the clinical data (age, gender, etc), CT imaging features (lesion location, size, enhancement degree, vascular wrapping, etc) and CT radiomic features of the 2 groups were compared. Logistic regression was used to screen the independent risk factors of the 2 groups, and multiple prediction models (clinical imaging model, radiomics model, and combined model) were established. Then the receiver operating characteristic (ROC) analysis and decision curve analysis (DCA) were conducted to compare the prediction performance and net benefit of the models. Results: The multivariate logistic regression results indicated that dilation of the main pancreatic duct, vascular wrapping, Radscore1 and Radscore2 were independent influencing factors for distinguishing FMFP from PDAC. In the training set, the combined model showed the best predictive performance (area under the ROC curve [AUC] 0.857, 95% CI [0.787-0.910]), significantly higher than the clinical imaging model (AUC 0.650, 95% CI [0.565-0.729]) and the radiomics model (AUC 0.812, 95% CI [0.759-0.890]). DCA confirmed that the combined model had the highest net benefit. These results were further validated by the test set. Conclusion: The combined model based on clinical-CT radiomics data can effectively identify FMFP and PDAC, providing a reference for clinical decision-making.

Elevated Expression of miR-296 in Human Placentas and Serum Samples From Pregnancies With Preeclampsia

Background: Preeclampsia (PE) is a hypertensive disorder of pregnancy characterized by widespread maternal endothelial dysfunction. Although clinical signs subside following delivery, long-term risks associated with PE include hypertension, stroke, and cardiovascular disease. MicroRNAs (miRNAs) are emerging as critical regulators of biological function, and while alterations to the miRNAs have been described in the context of pregnancy and PE, the postpartum implications of PE on miRNA expression are unknown. In the present study, we aimed to determine the clinical performance of miR-296 in PE. Methods: First, the clinical information and outcomes of all the participants were collected and analyzed. Afterward, the miR-296 expressions in the serum samples from healthy pregnant women and women with PE at different periods were detected using quantitative real-time polymerase chain reaction (qRT-PCR). Then, the receive operation characteristic (ROC) curve was used to determine the diagnostic value of miR-296 in PE. Finally, the at-term placentals were collected, the expressions of miR-296 in different groups were compared at first blood collection and at delivery. Results: In this study, we found that miR-296 expression was significantly increased in the placenta samples from PE patients compared with that in healthy controls both in early onset group (EOPE, p < 0.01) and late onset group (LOPE, p < 0.01). Furthermore, results of ROC analysis showed miR-296 might be a putative biomarker for early onset preeclampsia and late onset preeclampsia diagnosis with an area under the curve (AUC) of 0.84 (95% confidence interval 0.75-0.92) and 0.85 (95% confidence interval 0.77-0.93). Last but not the least, the expressions of miR-296 were significantly increased (p < 0.05) in serum samples of EOPE and LOPE patients (p < 0.001), and serum and placental levels of the miR-296 was positively correlated for EOPE (r = 0.5574, p < 0.001) and LOPE (r = 0.6613, p < 0.001) patients, respectively. Meanwhile, compared with those at first blood collection, the expression of miR-296 in EOPE (p = 0.05) and LOPE (p = 0.01) were significantly decreased at delivery. Conclusion: miR-296 may function as a putative diagnostic biomarker for PE and contribute to identifying at-risk mothers in pregnancy.

Development of stroke predictive model in community-dwelling population: A longitudinal cohort study in Southeast China

Background

Stroke has been the leading cause of death and disability in the world. Early recognition and treatment of stroke could effectively limit brain damage and vastly improve outcomes. This study aims to develop a highly accurate prediction model of stroke with a list of lifestyle behaviors and clinical characteristics to distinguish high-risk groups in the community-dwelling population.

Methods

Participants in this longitudinal cohort study came from the community-dwelling population in Suzhou between November 2018 and June 2019. A total of 4,503 residents participated in the study, while stroke happened to 22 participants in the 2-year follow-up period. Baseline information of each participant was acquired and enrolled in this study. T-test, Chi-square test, and Fisher's exact test were used to examine the relationship of these indexes with stroke, and a prediction scale was constructed by multivariate logistic regression afterward. Receiver operating characteristic analysis was applied to testify to the prediction accuracy.

Results

A highly accurate prediction model of stroke was constructed by age, gender, exercise, meat and vegetarian diet, BMI, waist circumference, systolic blood pressure, Chinese visceral adiposity index, and waist-height ratio. Two additional prediction models for overweight and non-overweight individuals were formulated based on crucial risk factors, respectively. The stroke risk prediction models for community-dwelling and overweight populations had accuracies of 0.79 and 0.82, severally. Gender and exercise were significant predictors (χ² > 4.57, p < 0.05) in the community-dwelling population model, while homocysteine (χ² = 4.95, p < 0.05) was significant in the overweight population model.

Conclusion

The predictive models could predict 2-year stroke with high accuracy. The models provided an effective tool for identifying high-risk groups and supplied guidance for improving prevention and treatment strategies in community-dwelling population.

Infective Endocarditis: Predictive Factors for Diagnosis and Mortality in Surgically Treated Patients

Background: Diagnosis of infective endocarditis (IE) often is challenging, and mortality is high in such patients. Our goal was to characterize common diagnostic tools to enable a rapid and accurate diagnosis and to correlate these tools with mortality outcomes. Methods: Because of the possibility of including perioperative diagnostics, only surgically treated patients with suspected left-sided IE were included in this retrospective, monocentric study. A clinical committee confirmed the diagnosis of IE. Results: 201 consecutive patients (age 64 ± 13 years, 74% male) were finally diagnosed with IE, and 14 patients turned out IE-negative. Preoperative tests with the highest sensitivity for IE were positive blood cultures (89.0%) and transesophageal echocardiography (87.5%). In receiver operating characteristics, vegetation size revealed high predictive power for IE (AUC 0.800, p < 0.001) with an optimal cut-off value of 11.5 mm. Systemic embolism was associated with mortality, and N-terminal prohormone of B-type natriuretic peptide (NT-proBNP) had predictive power for mortality. Conclusion: If diagnostic standard tools remain inconclusive, we suggest employing novel cut-off values to increase diagnostic accuracy and accelerate diagnosis. Patients with embolism or elevated NT-proBNP deserve a closer follow-up.

Plasma Neurofilament Light Chain (NF-L) Is a Prognostic Biomarker for Cortical Damage Evolution but Not for Cognitive Impairment or Epileptogenesis Following Experimental TBI

Plasma neurofilament light chain (NF-L) levels were assessed as a diagnostic biomarker for traumatic brain injury (TBI) and as a prognostic biomarker for somatomotor recovery, cognitive decline, and epileptogenesis. Rats with severe TBI induced by lateral fluid-percussion injury (n = 26, 13 with and 13 without epilepsy) or sham-operation (n = 8) were studied. During a 6-month follow-up, rats underwent magnetic resonance imaging (MRI) (day (D) 2, D7, and D21), composite neuroscore (D2, D6, and D14), Morris-water maze (D35−D39), and a 1-month-long video-electroencephalogram to detect unprovoked seizures during the 6th month. Plasma NF-L levels were assessed using a single-molecule assay at baseline (i.e., naïve animals) and on D2, D9, and D178 after TBI or a sham operation. Plasma NF-L levels were 483-fold higher on D2 (5072.0 ± 2007.0 pg/mL), 89-fold higher on D9 (930.3 ± 306.4 pg/mL), and 3-fold higher on D176 32.2 ± 8.9 pg/mL after TBI compared with baseline (10.5 ± 2.6 pg/mL; all p < 0.001). Plasma NF-L levels distinguished TBI rats from naïve animals at all time-points examined (area under the curve [AUC] 1.0, p < 0.001), and from sham-operated controls on D2 (AUC 1.0, p < 0.001). Plasma NF-L increases on D2 were associated with somatomotor impairment severity (ρ = −0.480, p < 0.05) and the cortical lesion extent in MRI (ρ = 0.401, p < 0.05). Plasma NF-L increases on D2 or D9 were associated with the cortical lesion extent in histologic sections at 6 months post-injury (ρ = 0.437 for D2; ρ = 0.393 for D9, p < 0.05). Plasma NF-L levels, however, did not predict somatomotor recovery, cognitive decline, or epileptogenesis (p > 0.05). Plasma NF-L levels represent a promising noninvasive translational diagnostic biomarker for acute TBI and a prognostic biomarker for post-injury somatomotor impairment and long-term structural brain damage.

Use of serum procalcitonin (PCT) level and PCT mRNA expression as a potential clinical biomarker in cats with bacterial and viral infections

OBJECTIVES

The aim of this study was to investigate the use of procalcitonin (PCT) as a biomarker in differentiating bacterial infections from viral infections in cats. In addition, the relationship between PCT and mortality rate was also examined.

METHODS

Forty-five cats were included in the study. The cats were categorised into two groups: bacterial (n = 20) and viral (n = 25) infection. Serum PCT level and PCT mRNA expression were analysed from blood samples collected before treatment.

RESULTS

Serum PCT level and PCT mRNA expression of the cats with presumed bacterial infection were higher than those with viral infection (P = 0.001 and P = 0.001, respectively). The receiver operating characteristic (ROC) curve analysis revealed an area under the ROC curve value of 0.888 for serum PCT and 0.850 for PCT mRNA expression. There was no statistically significant difference among respiratory, urinary and gastrointestinal tract infections regarding serum PCT level and PCT mRNA expression in the presumed bacterial infection group (P = 0.741 and P = 0.141, respectively). In the presumed bacterial infection group, serum PCT level and PCT mRNA expression in the non-surviving cats were higher than those of the surviving cats (P = 0.021 and P = 0.026, respectively).

CONCLUSIONS AND RELEVANCE

Serum PCT level and PCT mRNA expression were considered efficient biomarkers in cats to distinguish a bacterial infection from a viral infection. Moreover, ROC curve analysis was highly accurate in the discriminative capacity of these two parameters. PCT level and PCT mRNA expression offer substantial assistance in an efficient therapeutic approach and in avoiding unnecessary antibiotic use in feline clinical practice, particularly in emergency patients and those with non-specific clinical signs, decreasing the mortality rate. However, it should be noted that these data are only research data. More detailed future studies are needed.

Firms' solidity before an exogenous shock: Covid-19 pandemic in Italy

In this paper we study the structural robustness of the Italian business system, using the Covid-19 pandemic as an exogenous event to test it. To this aim, we use the ROC (Receiver Operating Characteristics) methodology, quite new for economics, to classify Italian firms according to their economic solidity, obtaining a taxonomy based on a wide set of characteristics. Our results show that the number of "Solid" firms is less than one-fifth of all Italian enterprises but they represent the lion's share in terms of employment and value added. "Fragile" and "At Risk" firms, albeit much less relevant for the creation of value added, account for over one-third of total employment, so they may be a worrisome issue for policymakers. Solidity conditions have clearly both a size and sector-related dimension: At Risk and Fragile conditions prevail among firms of smaller economic size (a broad definition of firm size) and among those operating in Construction and Other services. Finally, we find that factors such as firms' performance, and internal and external organization, although significant, play a less relevant role than economic size and digitalization/innovation in determining Italian firms' resilience to exogenous shocks such as the Covid-19 one.

Comparison of 10 obesity-related indices for predicting hypertension based on ROC analysis in Chinese adults

Objective

To compare the predictive performance of the percentage body fat (PBF), body mass index (BMI), waist circumference (WC), hip circumference (HC), waist-hip ratio (WHR), waist-height ratio (WHtR), a body shape index (ABSI), body roundness index (BRI), abdominal volume index (AVI), and conicity index (CI) for identifying hypertension.

Methods

A cross-sectional study was conducted among 2,801 adults (1,499 men and 1,302 women) aged 18 to 81 in Ningbo, China. The receiver operator characteristic (ROC) analysis and multiple non-parametric Z tests were used to compare the areas under the curve (AUC). The maximum Youden's indices were used to determine the optimal cut-off points of 10 obesity-related indices (ORI) for hypertension risk.

Results

The AUC of all the indices were statistically significant (P < 0.05). The AUC of all the indices in men and women were 0.67-0.73 and 0.72-0.79, respectively. Further non-parametric Z tests showed that WHR had the highest AUC values in both men [0.73 (95% CI: 0.70, 0.76)] and women (0.79 (95% CI: 0.75, 0.83)], and several central ORI (men: WHR, WC, BRI, AVI, and CI, 0.71-0.73; women: WC, WHR, and AVI, 0.77-0.79) were higher than general ORI (PBF and BMI, 0.68 in men; 0.72-0.75 in women), with adjusted P < 0.05. The optimal cut-off points for identifying hypertension in men and women were as follows: PBF (23.55%, 32.55%), BMI (25.72 kg/m², 23.46 kg/m²), HC (97.59 cm, 94.82 cm), WC (90.26 cm, 82.78 cm), WHR (0.91, 0.88), WHtR (0.51, 0.55), ABSI (0.08 m^7/6/kg^2/3, 0.08 m^7/6/kg^2/3), BRI (4.05, 4.32), AVI (16.31 cm², 13.83 cm²), and CI (1.23 m^2/3/kg^1/2, 1.27 m^2/3/kg^1/2). Multivariate logistic regression models showed that all indices were statistically significant (P < 0.05) with the adjusted ORs (per 1-SD increase) at 1.39-2.06 and ORs (over the optimal cut-off points) at 1.80-2.64.

Conclusions

All 10 ORI (PBF, BMI, HC, WC, WHR, WHtR, ABSI, BRI, AVI, and CI) can effectively predict hypertension, among which WHR should be recommended as the best predictor. Central ORI (WHR, WC, and AVI) had a better predictive performance than general ORIs (PBF and BMI) when predicting the risk of hypertension.

Prognostic Potential of the Body Composition Indices in Predicting Positive Changes in Resting Blood Pressure after High-Intensity Interval Training in Adolescents

This study aimed to investigate the prognostic potential of body composition indices in predicting the improvement in resting blood pressure after 10 weeks of high-intensity interval training (HIIT) implemented in physical education lessons. The participants were 141 adolescents aged 16 years. Independent variables were body mass index (BMI), fat mass index (FMI), muscle mass index (SMI), and mass to fat ratio (MFR); dependent variables were systolic and diastolic blood pressure (SBP, DBP) and its indices: pulse pressure (PP), mid-blood pressure (MBP), and mean arterial pressure (MAP). The receiver operating curve (ROC) method was employed. SMI and MFR are body composition indices with prognostic potential to predict positive changes in SBP in males (SMI: AUC = 0.82; p < 0.001, MFR = 0.70; p = 0.039) and MFR in females (AUC = 0.72; p = 0.035). The respective cut-off point values used to classify participants as a beneficiary of HIIT intervention concerning SBP were SMI = 7.84 and MFR = 2.43 in males, and for SMI = 10.12 and MFR = 1.94 in females. Body composition indices based on skeletal muscle (SMI, MFR) were more likely to predict positive changes in SBP after HIIT intervention in adolescents. PP, MBP, and MAP did not reflect the detecting power of SMI and MFR. However, these thresholds' utility is limited to adolescents of 16 years of age.

Expression pattern and diagnostic value of ferroptosis-related genes in acute myocardial infarction

BACKGROUND

Ferroptosis is a form of regulatory cell death (RCD) caused by iron-dependent lipid peroxidation. The role of ferroptosis in the process of acute myocardial infarction (AMI) is still unclear and requires further study. Therefore, it is helpful to identify ferroptosis related genes (FRGs) involved in AMI and explore their expression patterns and molecular mechanisms.

METHODS

The AMI-related microarray datasets GSE66360 and GSE61144 were obtained using the Gene Expression Omnibus (GEO) online database. GO annotation, KEGG pathway enrichment analysis and Protein-protein interaction (PPI) analysis were performed for the common significant differential expression genes (CoDEGs) in these two datasets. The FRGs were obtained from the FerrDb V2 and the differentially expressed FRGs were used to identify potential biomarkers by receiver operating characteristic (ROC) analysis. The expression of these FRGs was verified using external dataset GSE60993 and GSE775. Finally, the expression of these FRGs was further verified in myocardial hypoxia model.

RESULTS

A total of 131 CoDEGs were identified and these genes were mainly enriched in the pathways of "inflammatory response," "immune response," "plasma membrane," "receptor activity," "protein homodimerization activity," "calcium ion binding," "Phagosome," "Cytokine-cytokine receptor interaction," and "Toll-like receptor signaling pathway." The top 7 hub genes ITGAM, S100A12, S100A9, TLR2, TLR4, TLR8, and TREM1 were identified from the PPI network. 45 and 14 FRGs were identified in GSE66360 and GSE61144, respectively. FRGs ACSL1, ATG7, CAMKK2, GABARAPL1, KDM6B, LAMP2, PANX2, PGD, PTEN, SAT1, STAT3, TLR4, and ZFP36 were significantly differentially expressed in external dataset GSE60993 with AUC ≥ 0.7. Finally, ALOX5, CAMKK2, KDM6B, LAMP2, PTEN, PTGS2, and ULK1 were identified as biomarkers of AMI based on the time-gradient transcriptome dataset of AMI mice and the cellular hypoxia model.

CONCLUSION

In this study, based on the existing datasets, we identified differentially expressed FRGs in blood samples from patients with AMI and further validated these FRGs in the mouse time-gradient transcriptome dataset of AMI and the cellular hypoxia model. This study explored the expression pattern and molecular mechanism of FRGs in AMI, providing a basis for the accurate diagnosis of AMI and the selection of new therapeutic targets.

Development of a Multidimensional Pain Questionnaire in Professional Dance (MPQDA): a pilot study

Background

Pain is part of the everyday life of professional dancers. It can indicate health risks and impair the ability to work. Suitable screening tools can be used to identify pain and its risk potential. A comprehensive, multidimensional, differentiated assessment tool for pain in professional dance does not currently exist.

Methods

An initial questionnaire was developed in German and English and was assessed in a qualitative pretest. In a field study with a cross-sectional design including n = 72 dancers from Germany (n = 36 responses each in the English and German language versions), the questionnaire was optimized by item analysis, its psychometric properties (dimensionality, construct validity, reliability) were examined and the ability of the pain dimensions to classify the subjective ability to work in training was analyzed (ROC analysis).

Results

The developed Multidimensional Pain Questionnaire in Professional Dance (MPQDA) was reduced and optimized in its psychometric properties. Following questions were reduced in their items or answer categories: pain localizations (from 20 to 15 regions), accompanying symptoms (from 6 to 3 items), sensory and affective pain quality (from 20 to 10 items), pain frequency (from 4 to 3 answer categories), and the motives of working with pain (from 14 to 12 items). Regarding the subjective ability to work in training, the variables of the ability to work in rehearsals and in performances, as well as the accompanying symptoms of tension and mobility restrictions, showed a relatively good classification ability (Area under the Curve (AUC) ≥ 0.7 in the 95% confidence interval) and significant, moderate to strong correlations (Somers' D > 0.25, p < 0.05). The classification ability of the other pain dimensions was largely absent or poor.

Conclusion

The MPQDA differentiates various pain dimensions in professional dancers and is available in a compatible manner in German and English. The clinical relevance needs to be explored further in the future.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13102-022-00580-5.

Deep learning-based phenotyping for genome wide association studies of sudden death syndrome in soybean

Using a reliable and accurate method to phenotype disease incidence and severity is essential to unravel the complex genetic architecture of disease resistance in plants, and to develop disease resistant cultivars. Genome-wide association studies (GWAS) involve phenotyping large numbers of accessions, and have been used for a myriad of traits. In field studies, genetic accessions are phenotyped across multiple environments and replications, which takes a significant amount of labor and resources. Deep Learning (DL) techniques can be effective for analyzing image-based tasks; thus DL methods are becoming more routine for phenotyping traits to save time and effort. This research aims to conduct GWAS on sudden death syndrome (SDS) of soybean [Glycine max L. (Merr.)] using disease severity from both visual field ratings and DL-based (using images) severity ratings collected from 473 accessions. Images were processed through a DL framework that identified soybean leaflets with SDS symptoms, and then quantified the disease severity on those leaflets into a few classes with mean Average Precision of 0.34 on unseen test data. Both visual field ratings and image-based ratings identified significant single nucleotide polymorphism (SNP) markers associated with disease resistance. These significant SNP markers are either in the proximity of previously reported candidate genes for SDS or near potentially novel candidate genes. Four previously reported SDS QTL were identified that contained a significant SNPs, from this study, from both a visual field rating and an image-based rating. The results of this study provide an exciting avenue of using DL to capture complex phenotypic traits from images to get comparable or more insightful results compared to subjective visual field phenotyping of traits for disease symptoms.

A copro-antigen ELISA for the detection of ascarid infections in chickens

A reliable method of diagnosing the most prevalent helminth infections in chickens is vital for developing effective control strategies. Ascaridia galli and Heterakisgallinarum are phylogenetically close nematode species that can elicit the development of cross-reactive antibodies in chickens. Therefore, an enzyme-linked immunoassay (ELISA) based on Ascaridia galli antigens in faeces of chickens to detect and quantify infections with both A. galli and H. gallinarum was developed. The ELISA utilised polyclonal antibodies that were obtained from rabbits immunised with soluble antigens isolated from A. galli. In two separate experiments, chickens were kept as uninfected controls or were orally infected with either 100 or 1000 of embryonated eggs of A. galli or H.gallinarum. Faecal samples were collected after 28-30 weeks post-infection. The ELISA was then used to quantify the concentration of soluble worm antigens in faecal samples, i.e., the amount of antigen per gram faeces, APG. The APG from infected chickens was significantly higher than non-infected groups in both experiments (P 0.001). Both 100 and 1000 infection dose groups were not significantly different (P = 0.999) in the experiment with H. gallinarum, whereas in the experiment with A. galli, APG was significantly higher in the 1000 infection group (P 0.001). A receiver operation characteristics (ROC) analysis that evaluates the qualitative performance of diagnostics tests was used to calculate the assay parameters within each mono-infection experiment. The result showed that the assay had a high diagnostics accuracy with an area-under-curve (AUC) of 0.99 in detecting infection in A. galli infected chickens and a moderate-high accuracy (AUC = 0.89) in birds infected with H. gallinarum. The diagnostic sensitivity and specificity of the assay at the optimal cut-off point equivalent to Youden index were 93% and 100% for detecting infections in A. galli experiment and 85% and 92% in H. gallinarum experiment, respectively. The correlation between faecal antigen concentration and all worm burden parameters was positive but generally low (r < 0.33), which provided less information about infection intensities. Nonetheless, these results indicate that a reliable and accurate qualitative diagnosis of the two most prevalent intestinal nematodes in chickens can be achieved using a non-invasive copro-antigen ELISA assay.

Identification of early predictors for infected necrosis in acute pancreatitis

Background

In acute pancreatitis, secondary infection of pancreatic necrosis is a complication that mostly necessitates interventional therapy. A reliable prediction of infected necrotizing pancreatitis would enable an early identification of patients at risk, which however, is not possible yet.

Methods

This study aims to identify parameters that are useful for the prediction of infected necrosis and to develop a prediction model for early detection. We conducted a retrospective analysis from the hospital information and reimbursement data system and screened 705 patients hospitalized with diagnosis of acute pancreatitis who underwent contrast-enhanced computed tomography and additional diagnostic puncture or drainage of necrotic collections. Both clinical and laboratory parameters were analyzed for an association with a microbiologically confirmed infected pancreatic necrosis. A prediction model was developed using a logistic regression analysis with stepwise inclusion of significant variables. The model quality was tested by receiver operating characteristics analysis and compared to single parameters and APACHE II score.

Results

We identified a total of 89 patients with necrotizing pancreatitis, diagnosed by computed tomography, who additionally received biopsy or drainage. Out of these, 59 individuals had an infected necrosis. Eleven parameters showed a significant association with an infection including C-reactive protein, albumin, creatinine, and alcoholic etiology, which were independent variables in a predictive model. This model showed an area under the curve of 0.819, a sensitivity of 0.692 (95%-CI [0.547–0.809]), and a specificity of 0.840 (95%-CI [0.631–0.947]), outperforming single laboratory markers and APACHE II score. Even in cases of missing values predictability was reliable.

Conclusion

A model consisting of a few single blood parameters and etiology of pancreatitis might help for differentiation between infected and non-infected pancreatic necrosis and assist medical therapy in acute necrotizing pancreatitis.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12876-022-02490-9.

Establishing Accelerometer Cut-Points to Classify Walking Speed in People Post Stroke

While accelerometers could be used to monitor important domains of walking in daily living (e.g., walking speed), the interpretation of accelerometer data often relies on validation studies performed with healthy participants. The aim of this study was to develop cut-points for waist- and ankle-worn accelerometers to differentiate non-ambulation from walking and different walking speeds in people post stroke. Forty-two post-stroke persons wore waist and ankle accelerometers (ActiGraph GT3x+, AG) while performing three non-ambulation activities (i.e., sitting, setting the table and washing dishes) and while walking in self-selected and brisk speeds. Receiver operating characteristic (ROC) curve analysis was used to define AG cut-points for non-ambulation and different walking speeds (0.41−0.8 m/s, 0.81−1.2 m/s and >1.2 m/s) by considering sensor placement, axis, filter setting and epoch length. Optimal data input and sensor placements for measuring walking were a vector magnitude at 15 s epochs for waist- and ankle-worn AG accelerometers, respectively. Across all speed categories, cut-point classification accuracy was good-to-excellent for the ankle-worn AG accelerometer and fair-to-excellent for the waist-worn AG accelerometer, except for between 0.81 and 1.2 m/s. These cut-points can be used for investigating the link between walking and health outcomes in people post stroke.

Implementation of TG-218 for patient specific QA Tolerance and Action Limits determination: Gamma passing rates evaluation using 3DVH software

PURPOSE

To determine the tolerance (TL) and action limits (AL) of gamma passing rates (%GP) for Volumetric-Modulated Arc Therapy (VMAT) patient-specific quality assurance (PSQA), according to the AAPM TG-218 recommendations, and to evaluate comparatively the clinical relevance of 2D%GP and 3D%GP.

MATERIALS AND METHODS

PSQA was performed for 100 head and neck (H&N) and 73 prostate cancer VMAT treatment plans. Measurements were acquired using a cylindrical water equivalent phantom, hollow in the center, allowing measurements with homogeneous or heterogeneous inserts. LINAC delivered dose distributions were compared to the ones calculated from the treatment planning system (TPS) through gamma index. TL and AL were determined through the computation of 2D%GP, using the recommended acceptance criteria. Dose-volume histograms (DVH) were reconstructed from the measurements using a commercially available software, to detect the dosimetric differences (%DE) between the compared dose distributions. Utilizing the estimated dose on the patient anatomy, structure specific %GP (3D%GP) were calculated. The 3D%GP were compared to the 2D%GP ones, based on their correlation with the %DE. Each metric's sensitivity was determined through receiver operator characteristic (ROC) analysis.

RESULTS

TL and AL were in concordance with the universal ones, regarding the prostate cancer cases, but were lower for the H&N cases. Evaluation of %DE did not deem the plans unacceptable. The 2D%GP and the 3D%GP did not differ significantly regarding their correlation with %DE. For prostate plans, %GP sensitivity was higher than for H&N cases.

CONCLUSIONS

Determination of institutional specific TL and AL allow the monitoring of the PSQA procedure, yet for plans close to the limits clinically relevant metrics should be used before they are deemed unacceptable, for the process to be of higher sensitivity and efficiency. This article is protected by copyright. All rights reserved.

Identifying Immunological and Clinical Predictors of COVID-19 Severity and Sequelae by Mathematical Modeling

Since its emergence as a pandemic in March 2020, coronavirus disease (COVID-19) outcome has been explored via several predictive models, using specific clinical or biochemical parameters. In the current study, we developed an integrative non-linear predictive model of COVID-19 outcome, using clinical, biochemical, immunological, and radiological data of patients with different disease severities. Initially, the immunological signature of the disease was investigated through transcriptomics analysis of nasopharyngeal swab samples of patients with different COVID-19 severity versus control subjects (exploratory cohort, n=61), identifying significant differential expression of several cytokines. Accordingly, 24 cytokines were validated using a multiplex assay in the serum of COVID-19 patients and control subjects (validation cohort, n=77). Predictors of severity were Interleukin (IL)-10, Programmed Death-Ligand-1 (PDL-1), Tumor necrosis factors-α, absolute neutrophil count, C-reactive protein, lactate dehydrogenase, blood urea nitrogen, and ferritin; with high predictive efficacy (AUC=0.93 and 0.98 using ROC analysis of the predictive capacity of cytokines and biochemical markers, respectively). Increased IL-6 and granzyme B were found to predict liver injury in COVID-19 patients, whereas interferon-gamma (IFN-γ), IL-1 receptor-a (IL-1Ra) and PD-L1 were predictors of remarkable radiological findings. The model revealed consistent elevation of IL-15 and IL-10 in severe cases. Combining basic biochemical and radiological investigations with a limited number of curated cytokines will likely attain accurate predictive value in COVID-19. The model-derived cytokines highlight critical pathways in the pathophysiology of the COVID-19 with insight towards potential therapeutic targets. Our modeling methodology can be implemented using new datasets to identify key players and predict outcomes in new variants of COVID-19.

Derivation and performance of an end-of-life practice score aimed at interpreting worldwide treatment-limiting decisions in the critically ill

Background

Limitations of life-sustaining interventions in intensive care units (ICUs) exhibit substantial changes over time, and large, contemporary variation across world regions. We sought to determine whether a weighted end-of-life practice score can explain a large, contemporary, worldwide variation in limitation decisions.

Methods

The 2015–2016 (Ethicus-2) vs. 1999–2000 (Ethicus-1) comparison study was a two-period, prospective observational study assessing the frequency of limitation decisions in 4952 patients from 22 European ICUs. The worldwide Ethicus-2 study was a single-period prospective observational study assessing the frequency of limitation decisions in 12,200 patients from 199 ICUs situated in 8 world regions. Binary end-of-life practice variable data (1 = presence; 0 = absence) were collected post hoc (comparison study, 22/22 ICUs, n = 4592; worldwide study, 186/199 ICUs, n = 11,574) for family meetings, daily deliberation for appropriate level of care, end-of-life discussions during weekly meetings, written triggers for limitations, written ICU end-of-life guidelines and protocols, palliative care and ethics consultations, ICU-staff taking communication or bioethics courses, and national end-of-life guidelines and legislation. Regarding the comparison study, generalized estimating equations (GEE) analysis was used to determine associations between the 12 end-of-life practice variables and treatment limitations. The weighted end-of-life practice score was then calculated using GEE-derived coefficients of the end-of-life practice variables. Subsequently, the weighted end-of-life practice score was validated in GEE analysis using the worldwide study dataset.

Results

In comparison study GEE analyses, end-of-life discussions during weekly meetings [odds ratio (OR) 0.55, 95% confidence interval (CI) 0.30–0.99], end-of-life guidelines [OR 0.52, (0.31–0.87)] and protocols [OR 15.08, (3.88–58.59)], palliative care consultations [OR 2.63, (1.23–5.60)] and end-of-life legislation [OR 3.24, 1.60–6.55)] were significantly associated with limitation decisions (all P < 0.05). In worldwide GEE analyses, the weighted end-of-life practice score was significantly associated with limitation decisions [OR 1.12 (1.03–1.22); P = 0.008].

Conclusions

Comparison study-derived, weighted end-of-life practice score partly explained the worldwide study’s variation in treatment limitations. The most important components of the weighted end-of-life practice score were ICU end-of-life protocols, palliative care consultations, and country end-of-life legislation.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13054-022-03971-9.

Baseline anxiety, and early anxiety/depression improvement in anxious depression predicts treatment outcomes with escitalopram: A CAN-BIND-1 study report

INTRODUCTION

Although anxiety symptoms frequently co-occur with major depressive disorder, few studies examined the prediction of treatment outcomes among participants with anxious depression receiving antidepressants. We investigated whether baseline anxiety, and early improvements in anxiety and depression symptoms predict eventual treatment outcomes.

METHODS

111 participants with anxious depression, defined using ≥ 10 on GAD-7, received escitalopram (10-20 mg) for 8 weeks. Covariate-adjusted logistic regression was conducted to examine the impact of baseline anxiety, and to assess the extent week 2 anxiety (GAD-7) and depression (QIDS-SR) percentage improvement associates with week 8 anxiety (GAD-7) and depression (MADRS) response/remission. Optimum improvement thresholds were identified using receiving-operating-curve analysis and their predictive values assessed.

RESULTS

Greater percentage improvement in anxiety and depression after the first 2 weeks of treatment significantly increased odds of achieving week 8 anxiety and depression response/remission (OR:1.01-1.04, p<0.05). Early anxiety (68.4%/87.2%) and depression (52.2%/83.0%) improvement thresholds around 30 and 40% provided moderate to high positive predictive value (PPV) for predicting week 8 anxiety response/remission, as well as moderate to high negative predictive value (NPV) for predicting week 8 depression response/remission (anxiety:70.8%/91.7%; depression:72.2%/90.1%). Baseline anxiety severity predicted anxiety outcomes at weeks 2 and 8.

LIMITATIONS

Trial lacked placebo group.

CONCLUSION

In anxious depression, early improvement in anxiety may be better than depression in predicting anxiety outcomes, with similar or higher PPVs. Both improvement types perform similarly in predicting depression outcomes, with the lack of improvement predictive of non-response and non-remission. Finally, baseline anxiety predicts eventual anxiety but not depression outcomes.

Application of the skew exponential power distribution to ROC curves

The bi-Normal ROC model and corresponding metrics are commonly used in medical studies to evaluate the discriminatory ability of a biomarker. However, in practice, many clinical biomarkers tend to have skewed or other non-Normal distributions. And while the bi-Normal ROC model's AUC tends to be unbiased in this setting, providing a reasonable measure of global performance, the corresponding decision thresholds tend to be biased. To correct this bias, we propose using an ROC model based on the skew exponential power (SEP) distribution, whose additional parameters can accommodate skewed, heavy tailed, or other non-Normal distributions. Additionally, the SEP distribution can be used to evaluate whether the bi-Normal model would be appropriate. The performance of these ROC models and the non-parametric approach are evaluated via a simulation study and applied to a real data set involving infections from Klebsiella pneumoniae. The SEP based ROC-model provides some efficiency gains with respect to estimation of the AUC and provides cut-points with improved classification rates. As such, in the presence non-Normal data, we suggest using the proposed SEP ROC model.

SUBCLINICAL HYPOTHYROIDISM AS A CONTRIBUTOR TO MACROVASCULAR COMPLICATIONS IN PATIENTS WITH TYPE 2 DIABETES MELLITUS

This study aimed to evaluate changes of the lipid panel data in patients with comorbid type 2 diabetes mellitus (T2DM) and subclinical hypothyroidism (SCH) and to identify the probable prognostic values of the lipid profile for macrovascular complication (MVC) development. The study included 370 patients presented with only T2DM and 30 patients suffering from both T2DM and SCH. Receiver operating characteristic (ROC) analysis was used to identify prognostically significant values of the lipid profile with the optimal ratio of sensitivity and specificity for MVC development. All lipid profile values in the patients with T2DM combined with SCH were significantly higher compared to those with only T2DM. At the same time, SCH + T2DM increased the risk of exceeding target levels of triglycerides by 2.9 times and HDL-C by 4.1 times. Analysis of lipid profile values according to macrovascular involvement showed that total cholesterol, LDL-C and non-HDL-C in patients with T2DM and SCH were significantly higher compared to those with only T2DM. The levels of triglycerides >1.65 mmol/L, non-HDL-C >3.74 mmol/L and remnant cholesterol >0.74 mmol/L determined by the ROC analysis can be used for stratification of patients with T2DM combined with SCH into the category of increased risk of MVC development.

Peptide Biomarkers for the Diagnosis of Dengue Infection

In a world with an increasing population at risk of exposure to arthropod-borne flaviviruses, access to timely and accurate diagnostic tests would impact profoundly on the management of cases. Twenty peptides previously identified using a flavivirus proteome-wide microarray were evaluated to determine their discriminatory potential to detect dengue virus (DENV) infection. This included nine peptides recognized by IgM antibodies (PM peptides) and 11 peptides recognized by IgG antibodies (PG peptides). A bead-based multiplex peptide immunoassay (MPIA) using the Luminex technology was set-up to determine Ab binding levels to each of these peptides in a panel of 323 carefully selected human serum samples. Sera are derived from individuals either infected with different viruses, namely, the four DENV serotypes, Zika virus (ZIKV), yellow fever virus (YFV), chikungunya virus (CHIKV), West Nile virus (WNV) and Human immunodeficiency virus (HIV), or receiving vaccination against YFV, tick-borne encephalitis (TBEV), and Japanese encephalitis virus (JEV). Additionally, a set of healthy controls were included. We targeted a minimum specificity of 80% for all the analysis. The PG-9 peptide had the best sensitivity (73%) when testing DENV sera from acute patients (A-DENV; <8 days since symptom onset). With sera from convalescent DENV patients (C-DENV; >10 days since symptom onset) the FPG-1 peptide was the best seromarker with a sensitivity of 86%. When combining all A-DENV and C-DENV samples, peptides PM-22 and FPG-1 had the best-diagnostic performance with a sensitivity of 60 and 61.1%, and areas under the curve (AUC) of 0.7865 and 0.8131, respectively. A Random forest (RF) algorithm was used to select the best combination of peptides to classify DENV infection at a targeted specificity >80%. The best RF model for PM peptides that included A-DENV and C-DENV samples, reached a sensitivity of 72.3%, while for PG peptides, the best RF models for A-DENV only, C-DENV only and A-DENV + C-DENV reached a sensitivity of 88.9%, 89.1%, and 88.3%, respectively. In conclusion, the combination of multiple peptides constitutes a founding set of seromarkers for the discrimination of DENV infected individuals from other flavivirus infections.

Potential Molecular Mechanisms and Remdesivir Treatment for Acute Respiratory Syndrome Corona Virus 2 Infection/COVID 19 Through RNA Sequencing and Bioinformatics Analysis

Introduction:

Severe acute respiratory syndrome corona virus 2 (SARS-CoV-2) infections (COVID 19) is a progressive viral infection that has been investigated extensively. However, genetic features and molecular pathogenesis underlying remdesivir treatment for SARS-CoV-2 infection remain unclear. Here, we used bioinformatics to investigate the candidate genes associated in the molecular pathogenesis of remdesivir-treated SARS-CoV-2-infected patients.

Methods:

Expression profiling by high-throughput sequencing dataset (GSE149273) was downloaded from the Gene Expression Omnibus, and the differentially expressed genes (DEGs) in remdesivir-treated SARS-CoV-2 infection samples and nontreated SARS-CoV-2 infection samples with an adjusted P value of <.05 and a |log fold change| > 1.3 were first identified by limma in R software package. Next, pathway and gene ontology (GO) enrichment analysis of these DEGs was performed. Then, the hub genes were identified by the NetworkAnalyzer plugin and the other bioinformatics approaches including protein-protein interaction network analysis, module analysis, target gene—miRNA regulatory network, and target gene—TF regulatory network. Finally, a receiver-operating characteristic analysis was performed for diagnostic values associated with hub genes.

Results:

A total of 909 DEGs were identified, including 453 upregulated genes and 457 downregulated genes. As for the pathway and GO enrichment analysis, the upregulated genes were mainly linked with influenza A and defense response, whereas downregulated genes were mainly linked with drug metabolism—cytochrome P450 and reproductive process. In addition, 10 hub genes (VCAM1, IKBKE, STAT1, IL7R, ISG15, E2F1, ZBTB16, TFAP4, ATP6V1B1, and APBB1) were identified. Receiver-operating characteristic analysis showed that hub genes (CIITA, HSPA6, MYD88, SOCS3, TNFRSF10A, ADH1A, CACNA2D2, DUSP9, FMO5, and PDE1A) had good diagnostic values.

Conclusion:

This study provided insights into the molecular mechanism of remdesivir-treated SARS-CoV-2 infection that might be useful in further investigations.