Greatest Discriminatory Power Research Articles

Usefulness of biomarkers to predict prognosis after heart transplant

Introduction and objectivesHeart transplant (HT) represents a major physiological stress, resulting in elevated levels of analytical biomarkers. This study aimed to determine whether changes in biomarker levels after HT can identify patients with a poor prognosis. MethodsA prospective longitudinal noninterventional study was conducted in 149 consecutive patients undergoing HT from July 2017 to July 2023. Biomarkers were assessed before HT and at 6, 24, 48, 72, and 96hours after HT. The biomarkers analyzed were high-sensitivity troponin T, N-terminal pro-B-type natriuretic peptide (NT-proBNP), creatinine, and lactic acid. The primary outcome was a composite of death and severe primary graft failure (PGF). ResultsNT-proBNP and troponin levels remained highly elevated throughout the period and stabilized from the first 24hours post-HT. Lactate levels stabilized after the first 24hours, and creatinine from the second day onward. Exitus occurred in 23 (15%) of the patients, and severe PGF in 26 (17%). All biomarkers were significantly associated with the incidence of the combined event (P <.0001). Receiver operating characteristic curve analysis at 24hours showed significant areas under the curve (P=.0001). The greatest discriminatory power was observed for the NT-proBNP curve. A value of 10 000 pg/mL had a sensitivity of 90% and specificity of 80%. ConclusionsA significant elevation of post-HT analytical biomarkers was associated with mortality and/or severe PGF. Among the biomarkers analyzed, NT-proBNP was the most accurate in classifying patients.

Consequences of domestication in eastern oyster: Insights from whole genomic analyses.

Selective breeding for production traits has yielded relatively rapid successes with high-fecundity aquaculture species. Discovering the genetic changes associated with selection is an important goal for understanding adaptation and can also facilitate better predictions about the likely fitness of selected strains if they escape aquaculture farms. Here, we hypothesize domestication as a genetic change induced by inadvertent selection in culture. Our premise is that standardized culture protocols generate parallel domestication effects across independent strains. Using eastern oyster as a model and a newly developed 600K SNP array, this study tested for parallel domestication effects in multiple independent selection lines compared with their progenitor wild populations. A single contrast was made between pooled selected strains (1-17 generations in culture) and all wild progenitor samples combined. Population structure analysis indicated rank order levels of differentiation as [wild - wild] < [wild - cultured] < [cultured - cultured]. A genome scan for parallel adaptation to the captive environment applied two methodologically distinct outlier tests to the wild versus selected strain contrast and identified a total of 1174 candidate SNPs. Contrasting wild versus selected strains revealed the early evolutionary consequences of domestication in terms of genomic differentiation, standing genetic diversity, effective population size, relatedness, runs of homozygosity profiles, and genome-wide linkage disequilibrium patterns. Random Forest was used to identify 37 outlier SNPs that had the greatest discriminatory power between bulked wild and selected oysters. The outlier SNPs were in genes enriched for cytoskeletal functions, hinting at possible traits under inadvertent selection during larval culture or pediveliger setting at high density. This study documents rapid genomic changes stemming from hatchery-based cultivation of eastern oysters, identifies candidate loci responding to domestication in parallel among independent aquaculture strains, and provides potentially useful genomic resources for monitoring interbreeding between farm and wild oysters.

Utilidad de los biomarcadores en el trasplante cardiaco para predecir el pronóstico

Introduction and objectivesHeart transplant (HT) represents a major physiological stress, resulting in elevated levels of analytical biomarkers. This study aimed to determine whether changes in biomarker levels after HT can identify patients with a poor prognosis. MethodsA prospective longitudinal noninterventional study was conducted in 149 consecutive patients undergoing HT from July 2017 to July 2023. Biomarkers were assessed before HT and at 6, 24, 48, 72, and 96hours after HT. The biomarkers analyzed were high-sensitivity troponin T, N-terminal pro-B-type natriuretic peptide (NT-proBNP), creatinine, and lactic acid. The primary outcome was a composite of death and severe primary graft failure (PGF). ResultsNT-proBNP and troponin levels remained highly elevated throughout the period and stabilized from the first 24hours post-HT. Lactate levels stabilized after the first 24hours, and creatinine from the second day onward. Exitus occurred in 23 (15%) of the patients, and severe PGF in 26 (17%). All biomarkers were significantly associated with the incidence of the combined event (P <.0001). Receiver operating characteristic curve analysis at 24hours showed significant areas under the curve (P=.0001). The greatest discriminatory power was observed for the NT-proBNP curve. A value of 10 000 pg/mL had a sensitivity of 90% and specificity of 80%. ConclusionsA significant elevation of post-HT analytical biomarkers was associated with mortality and/or severe PGF. Among the biomarkers analyzed, NT-proBNP was the most accurate in classifying patients.

Towards a multi-parametric fragility model for Italian masonry buildings based on the informative level

This study provides a multi-parametric fragility model for Italian masonry buildings, which varies based on available information about buildings characteristics, sources from data of varying accuracy level. Three increasing levels are considered: limited, extensive, and exhaustive. These levels correspond to different degree of knowledge about the building stock, ranging from detailed in situ inspections, where a comprehensive understanding of nearly all the building features is achievable, to the case where it must necessarily rely upon a limited data (census data). This multilevel classification is established based on the number of explanatory parameters employed in defining building taxonomies. The parameters considered in this study are derived from post-earthquake damage data collected after the 2009 L'Aquila earthquake. They have undergone a thorough review and a refinement process and have been supplemented with 2001 census data to overcome the critical issue of data completeness. In addition to providing information about the geometric and typological characteristics of residential masonry buildings, the same data source also yields insights into the extent of damage sustained by these buildings. This, in turn, enables the derivation of a Damage Probability Matrix (DPM), obtained as a function on ground motion intensity values evaluated from ShakeMap of the event. The outcomes of a nonparametric statistical test, applied on DPMs, are used to drive an agglomerative clustering procedure, to establishing a hierarchical ranking of the parameters in term of their discriminatory power. The absolute (number of cases where the null testing hypothesis is rejected) and the relative (examining the test’s strength) comparison of the outcomes, allows to identify the parameters with the greatest discriminatory power. These are the one that define the branches of the taxonomies under consideration. Conversely, the less influential parameters with regard to seismic vulnerability are eligible to be grouped together, allowing the definition of a more compact taxonomy. This approach yields distinct sets of fragility curves, contingent upon the information level gained for the specific building stock being investigated, ranging from census data to comprehensive in-situ surveys. A last focus on the impact of the enhancement in the level of knowledge on seismic vulnerability is also done.

Analysis and Evaluation of the Influence of Selected Factors on the Occurrence of Defects in Polish Housing Construction Using the Example of the Lower Silesia Region

In literature relevant to this topic, attention is mainly paid to the qualitative and quantitative identification of defects in housing construction, and the factors that cause these defects. There is a research gap regarding the quantitative relationships between factors and defects, and the identification of factors that have a decisive impact on the occurrence of defects. The authors’ contribution to research regarding quality management in construction investments involves the identification of defects in residential buildings, identification of factors that generate construction defects occurring at various stages of the investment process, and also the assessment of their discriminatory power. This analysis used the results of technical inspections of buildings carried out in Poland in 2017–2020 in the Lower Silesia region. The study of the factors that influence quality in housing construction was carried out using the diagnostic survey method and the survey technique. Discriminant analysis was used for the calculations, with a number of influence factors being found. The following factors have the greatest discriminatory power: C1—a lack of internal control of design documentation before the start of the construction of the facility; C15—a lack of stability of the team (high staff turnover) that conducts contract tenders; C30—a lack of executive potential for preparing the facility for technical acceptance. Identifying the relationships between factors and quality, measured by the number and type of defects, will constitute the basis for developing procedures for conducting and controlling construction works and taking appropriate preventive actions in the form of employee training.

Intermittent body composition analysis as monitoring tool for muscle wasting in critically ill COVID-19 patients

ObjectivesSARS-CoV-2 virus infection can lead to acute respiratory distress syndrome (ARDS), which can be complicated by severe muscle wasting. Until now, data on muscle loss of critically ill COVID-19 patients are limited, while computed tomography (CT) scans for clinical follow-up are available. We sought to investigate the parameters of muscle wasting in these patients by being the first to test the clinical application of body composition analysis (BCA) as an intermittent monitoring tool.MaterialsBCA was conducted on 54 patients, with a minimum of three measurements taken during hospitalization, totaling 239 assessments. Changes in psoas- (PMA) and total abdominal muscle area (TAMA) were assessed by linear mixed model analysis. PMA was calculated as relative muscle loss per day for the entire monitoring period, as well as for the interval between each consecutive scan. Cox regression was applied to analyze associations with survival. Receiver operating characteristic (ROC) analysis and Youden index were used to define a decay cut-off.ResultsIntermittent BCA revealed significantly higher long-term PMA loss rates of 2.62% (vs. 1.16%, p < 0.001) and maximum muscle decay of 5.48% (vs. 3.66%, p = 0.039) per day in non-survivors. The first available decay rate did not significantly differ between survival groups but showed significant associations with survival in Cox regression (p = 0.011). In ROC analysis, PMA loss averaged over the stay had the greatest discriminatory power (AUC = 0.777) for survival. A long-term PMA decline per day of 1.84% was defined as a threshold; muscle loss beyond this cut-off proved to be a significant BCA-derived predictor of mortality.ConclusionMuscle wasting in critically ill COVID-19 patients is severe and correlates with survival. Intermittent BCA derived from clinically indicated CT scans proved to be a valuable monitoring tool, which allows identification of individuals at risk for adverse outcomes and has great potential to support critical care decision-making.

Detection of differences of cardiorespiratory metrics between non-invasive respiratory support modes using machine learning methods

Many preterm infants require invasive mechanical ventilation in the first days of life. Once ventilation is removed, non-invasive respiratory support assists the transition to spontaneous breathing. Three common support modes are Nasal Continuous Positive Airway Pressure (CPAP), Non-Invasive Neurally Adjusted Ventilatory Assist (NIV-NAVA), and Nasal Intermittent Positive Pressure Ventilation (NIPPV). Cardiorespiratory behavior under these supports is not well understood. We hypothesized that if behavior changed with the support, then machine learning should be able to distinguish them, and the most discriminatory features would indicate how the behaviors differ. To test this, we recorded cardiorespiratory signals from infants during CPAP, NIV-NAVA, and NIPPV immediately following extubation. Forty-five metrics related to the amplitude and frequency of these signals were computed at each time and six summary statistics computed for each metric. The feature set was reduced by principal component analysis and used to train a Random Forest classifier. We found that (1) Classification of the three modes performed poorly (accuracy = 58.6%); (2) Classification of CPAP from NIV-NAVA or NIPPV performed well (accuracy = 81.5%). Thus, cardiorespiratory behavior during CPAP is significantly different from NIV-NAVA or NIPPV. The features with the greatest discriminatory power were related to the amplitude of respiratory movements and the correlation between the ribcage and abdomen movements. These results serve to direct further investigation with clinical relevance. Thus, infants with shallow breathing may benefit from the support with largest amplitude respiratory movements, while infants with asynchronous chest and abdominal movements may benefit from the modality with the most correlated movements.

Selenium nutritional status and its association with SLEDAI-2K, HOMA-IR and lipid profile in Juvenile Systemic Lupus Erythematosus patients.

To assess nutritional status regarding selenium in adolescents with Juvenile Systemic Lupus Erythematosus (jSLE) and analyze possible associations with disease activity, insulin resistance and lipid profile. This was an observational, cross-sectional study of 31 female adolescents with jSLE and 31 healthy female volunteers as a comparison group. We obtained demographic, anthropometric (weight, stature, waist, and neck circumferences), and clinical data (disease activity measured by SLEDAI-2K) from both groups; laboratory data including: lipid profile, plasma selenium, erythrocyte glutathione peroxidase activity (GPx), plasma malondialdehyde (MDA), ultrasensitive C-reactive protein (usCRP), insulin levels, and glycemia (Homeostasis Model Assessment for Insulin Resistance-HOMA-IR). Mean age at diagnosis of jSLE group was 15.9±1.7years, with mean disease duration of 3.6±2.6years. 48% of patients and controls had below-reference Se levels (≤46mcg/L). GPx was more frequently below reference levels (<4.171U/L) in the jSLE group, compared to controls. A ROC curve was used to assess the power of the variables to discriminate between both groups; insulin (AUC = 0.712; CI 95% 0.584-0.840), waist-to-height ratio (AUC = 0.704; CI 95% 0.572-0.837), and HOMA-IR (AUC = 0.689; CI 95% 0.556-0.822) were the variables with the greatest discriminatory power. Linear regression showed an independent inverse association between Se levels and c-LDL; no such correlation was found for GPx activity. SLEDAI-2K and HOMA-IR showed no association with levels of Se and GPx activity. Approximately, 50% of jSLE adolescents had below reference Se levels. The frequency of inadequate GPx values was higher in patients, compared to controls. There was an independent inverse association between Se and c-LDL levels in both groups; this was not the case for HOMA-IR and SLEDAI-2K. The data show the importance of assessing Se nutritional status in jSLE patients.

Evidence for distinct neuro-metabolic phenotypes in humans

Advances in magnetic resonance imaging have shown how individual differences in the structure and function of the human brain relate to health and cognition. The relationship between individual differences and the levels of neuro-metabolites, however, remains largely unexplored – despite the potential for the discovery of novel behavioural and disease phenotypes. In this study, we measured 14 metabolite levels, normalised as ratios to total-creatine, with 1H magnetic resonance spectroscopy (MRS) acquired from the bilateral anterior cingulate cortices of six healthy participants, repeatedly over a period of four months. ANOVA tests revealed statistically significant differences of 3 metabolites and 3 commonly used combinations (total-choline, glutamate + glutamine and total-N-acetylaspartate) between the participants, with scyllo-inositol (F=85, p=6e-26) and total-choline (F=39, p=1e-17) having the greatest discriminatory power. This was not attributable to structural differences. When predicting individuals from the repeated MRS measurements, a leave-one-out classification accuracy of 88% was achieved using a support vector machine based on scyllo-inositol and total-choline levels. Accuracy increased to 98% with the addition of total-N-acetylaspartate and myo-inositol – demonstrating the efficacy of combining MRS with machine learning and metabolomic methodology. These results provide evidence for the existence of neuro-metabolic phenotypes, which may be non-invasively measured using widely available 3 Tesla MRS. Establishing these phenotypes in a larger cohort and investigating their connection to brain health and function presents an important area for future study.

Impairment of Cardiac Autonomic Nerve Function in Pre-school Children With Intractable Epilepsy.

Objective: Intractable epilepsy and uncontrolled seizures could affect cardiac function and the autonomic nerve system with a negative impact on children's growth. The aim of this study was to investigate the variability and complexity of cardiac autonomic function in pre-school children with pediatric intractable epilepsy (PIE).Methods: Twenty four-hour Holter electrocardiograms (ECGs) from 93 patients and 46 healthy control subjects aged 3–6 years were analyzed by the methods of traditional heart rate variability (HRV), multiscale entropy (MSE), and Kurths–Wessel symbolization entropy (KWSE). Receiver operating characteristic (ROC) curve analysis was used to estimate the overall discrimination ability. Net reclassification improvement (NRI) and integrated discrimination improvement (IDI) models were also analyzed.Results: Pre-school children with PIE had significantly lower HRV measurements than healthy controls in time (Mean_RR, SDRR, RMSSD, pNN50) and frequency (VLF, LF, HF, LF/HF, TP) domains. For the MSE analysis, area 1_5 in awake state was lower, and areas 6_15 and 6_20 in sleep state were higher in PIE with a significant statistical difference. KWSE in the PIE group was also inferior to that in healthy controls. In ROC curve analysis, pNN50 had the greatest discriminatory power for PIE. Based on both NRI and IDI models, the combination of MSE indices (wake: area1_5 and sleep: area6_20) and KWSE (m = 2, τ = 1, α = 0.16) with traditional HRV measures had greater discriminatory power than any of the single HRV measures.Significance: Impaired HRV and complexity were found in pre-school children with PIE. HRV, MSE, and KWSE could discriminate patients with PIE from subjects with normal cardiac complexity. These findings suggested that the MSE and KWSE methods may be helpful for assessing and understanding heart rate dynamics in younger children with epilepsy.

A Novel Inflammatory Index Is Sufficient to Identify Hemophagocytic Lymphohistiocytosis in Adult Patients with Hematologic Malignancies

Introduction: Hemophagocytic lymphohistiocytosis (HLH) is a life-threatening hyper-inflammatory syndrome which may occur in adults with hematologic malignancies (HM). The diagnosis of HLH in this context (HM-HLH) is hindered by a number of factors. First, the currently used HLH 2004 diagnostic criteria are derived from pediatric patients commonly with HLH-associated genetic lesions, a very different population than adults with cancer. Second, most parameters used for diagnosis of HLH are directly impacted by the underlying HM and may reflect the presence of the malignant clone itself rather than an inflammatory process. Finally, appropriate diagnostic cutoff values for laboratory abnormalities in HM-HLH have not been defined. In this study we determine the diagnostic value of the laboratory components of the HLH 2004 diagnostic criteria and establish optimal cutoffs for the diagnosis of HM-HLH in HM patients. Methods: This is a multicenter, retrospective study of adult patients with a hematologic malignancy in whom sCD25 was measured because of clinically suspected HM-HLH or as part of routine screening of patients with a newly diagnosed hematologic malignancy, between January 2012 and March 2020. We considered patients fulfilling the five of eight of the HLH 2004 diagnostic criteria to have HM-HLH. Patients fulfilling fewer than five criteria were assigned to the HM group. These cohorts were well balanced in terms of disease distribution. We established the optimal cutoffs for laboratory parameters used for the diagnosis of HM-HLH using receiver operating curves (ROC) in a discovery cohort and tested their performance in a validation cohort. In order to improve the results obtained using the individual ROC, we then created a combined ROC using parameters demonstrating the highest individual performance (highest area under the curve (AUC)), in order to develop a diagnostic index. Finally, we examined the performance of each parameter in each cohort by using a contingency table and Chi-square and Fisher's exact test to determine the positive predictive value (PPV), negative predictive value (NPV), sensitivity, specificity and likelihood ratio (LR) of disease for each parameter. Results: 212 adults with HM with or without HLH in whom testing for HLH was performed were included in the study. HMs were: B cell lymphoma (41%), T cell lymphoma (26%), Hodgkin lymphoma (9%), acute myeloid leukemia (8%), myelodysplastic syndrome (8%), myeloproliferative neoplasms (5%) and chronic lymphocytic leukemia (4%). 99 (47%) patients had HM-HLH. Despite considerable overlap in laboratory values between the patient groups, all parameters apart from fibrinogen were able to distinguish HM-HLH from HM alone, with ferritin and sCD25 having the greatest discriminatory power. ROC analysis revealed an optimal cutoff value of &amp;gt;5,600 U/mL for sCD25 (sensitivity/specificity 76%/78%, AUC=0.83) and &amp;gt;1,300 ng/ml for ferritin (sensitivity/specificity 76%/76%, AUC=0.83). Combining the two markers to create a novel inflammatory index (HM-INFL) yielded superior diagnostic ability (AUC =0.86). Using HLH 2004 cutoff levels the HM-INFL index had a sensitivity of 94% and NPV of 94% and when using the optimal cutoff levels, it had a specificity of 92% and PPV of 90% (Table 1). Conclusions: HM-INFL is an index comprising only ferritin and sCD25. Using the original HLH 2004 cutoffs the index is an effective screening tool. Using our newly defined cutoff levels obtained by ROC analysis it is highly specific and can be used as a confirmatory test for the diagnosis of HLH in HM patients. These findings also support the hypothesis that HLH in the context of HM is an inflammatory condition associated with immune dysregulation. Disclosures Miller: Foundation Medicines, Inc.: Consultancy. Daver:Daiichi Sankyo: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Bristol-Myers Squibb: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Pfizer: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Karyopharm: Research Funding; Servier: Research Funding; Genentech: Research Funding; AbbVie: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Astellas: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Novimmune: Research Funding; Gilead: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Amgen: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Trovagene: Research Funding; Fate Therapeutics: Research Funding; ImmunoGen: Research Funding; Novartis: Consultancy, Membership on an entity's Board of Directors or advisory committees; Celgene: Consultancy, Membership on an entity's Board of Directors or advisory committees; Jazz: Consultancy, Membership on an entity's Board of Directors or advisory committees; Trillium: Consultancy, Membership on an entity's Board of Directors or advisory committees; Syndax: Consultancy, Membership on an entity's Board of Directors or advisory committees; Amgen: Consultancy, Membership on an entity's Board of Directors or advisory committees; KITE: Consultancy, Membership on an entity's Board of Directors or advisory committees; Agios: Consultancy, Membership on an entity's Board of Directors or advisory committees. Jordan:Sobi: Consultancy.

Accuracy and limitations for spectroscopic prediction of leaf traits in seasonally dry tropical environments

Generalized assessments of the accuracy of spectroscopic estimates of ecologically important leaf traits such as leaf mass per area (LMA) and leaf dry matter content (LDMC) are still lacking for most ecosystems, and particularly for non-forested and/or seasonally dry tropical vegetation. Here, we tested the ability of using leaf reflectance spectra to estimate LMA and LDMC and classify plant growth forms within the cerrado and campo rupestre seasonally dry non-forest vegetation types of Southeastern Brazil, filling an existing gap in published assessments of leaf optical properties and plant traits in such environments. We measured leaf reflectance spectra from 1648 individual plants comprising grasses, herbs, shrubs, and trees, developed partial least squares regression (PLSR) models linking LMA and LDMC to leaf spectra (400–2500 nm), and identified the spectral regions with the greatest discriminatory power among growth forms using Bhattacharyya distances. We accurately predicted leaf functional traits and identified different growth forms. LMA was overall more accurately predicted (RMSE = 8.58%) than LDMC (RMSE = 9.75%). Our model including all sampled plants was not biased towards any particular growth form, but growth-form specific models yielded higher accuracies and showed that leaf traits from woody plants can be more accurately estimated than for grasses and forbs, independently of the trait measured. We observed a large range of LMA values (31.80–620.81 g/m2) rarely observed in tropical or temperate forests, and demonstrated that values above 300 g/m2 could not be accurately estimated. Our results suggest that spectroscopy may have an intrinsic saturation point, and/or that PLSR, the current approach of choice for estimating traits from plant spectra, is not able to model the entire range of LMA values. This finding has very important implications to our ability to use field, airborne, and orbital spectroscopic methods to derive generalizable functional information. We thus highlight the need for increasing spectroscopic sampling and research efforts in drier non-forested environments, where environmental pressures lead to leaf adaptations and allocation strategies that are very different from forested ecosystems. Our findings also confirm that leaf reflectance spectra can provide important information regarding differences in leaf metabolism, structure, and chemical composition. Such information enabled us to accurately discriminate plant growth forms in these environments regardless of lack of variation in leaf economic traits, encouraging further adoption of remote sensing methods by ecologists and allowing a more comprehensive assessment of plant functional diversity.

Comparison of four lymph node staging systems for predicting prognosis for stage IV rectum cancer.

With recommendation of surgical management in primary site, both the positive and negative lymph nodes (LNs) retrieved have been emphasized to predict prognosis in stage IV rectum cancer. Therefore, we attempt to compare the prognostic performance of American Joint Committee on Cancer (AJCC) N-stage relative to lymph node ratio (LNR), log odds of metastatic lymph nodes (LODDS), and N-score in stage IV rectal cancer. Total 5,090 patients taken surgical resection of primary site in rectum cancer with distant metastasis were extracted from Surveillance, Epidemiology, and End Results Program (SEER) database. Harrell's C statistic (C-index) and Akaike's Information Criterion (AIC) were used to evaluate the discriminative ability of the different LN staging systems. Of the 3,243 patients without radiotherapy, 82.46% (n=2,675) had been found with lymph nodes metastasis with median number of 16 lymph nodes collected (IQR: 11-22). Modeled as categorical cutoff variables for further clinical usage, when number of LNs was between 12 and 25 (C-index: 0.5997, AIC: 1,698.015), 8th AJCC N-stage outperformed other three schemas with increasing C-index and less AIC value. Assessed as continuous values, the LODDS shown as the best schemas with greatest discriminatory power (C-index: 0.5971, AIC: 3,680.017), generally. On the other hand, in the cohorts of other 1274 patients taken radiation, the median number of lymph nodes retrieved was 13 (IQR: 9-18). LODDS still remained remarkable performance as continuous (C-index: 0.5912; AIC: 1,058.765) and categorical variables (C-index: 0.5700; AIC: 1,061.703), while N-staging outperformed with less than 25 lymph nodes retrieved (LNs <12 C-index: 0.5678, AIC: 481.94; 12< LNs <25 C-index: 0.5933, AIC: 390.395). When assessed as categorical variables, N-stage performed superiorly with adequate lymph nodes examined, whether the patients have got radiotherapy prior to surgery or not. LODDS showed, when assessed as a continuous variable, good discriminative ability and goodness of fit in predicting survival for stage IV rectum cancer patients regardless of radiation therapy status.

Attitudes and practices of professionals who working in the Family Health Strategy regarding the approach to drug users in the municipality of Campina Grande. Paraíba. Brazil.

The aim of this study was to evaluate the attitudes and practices of professionals of the Family Health Strategy regarding the approach to drug users in the municipality of Campina Grande. Paraíba. The cross-sectional and exploratory study carried out with 126 doctors. nurses and dentists of Primary Health Care (PHC). Variables investigated were related to sociodemographic data. professional profile. attitudes and practices about the approach to drug users according to the Integrated Plan to Confront Crack and Other Drugs. Descriptive and multivariate statistics were performed through Multiple Correspondence Analysis (MCA). Most professionals were female (88.9%) and reported questioning only sometimes about the use of drugs during the anamnesis (53.2%). Based on MCA results. variables with the greatest discriminatory power for dimension 1 were: training time (0.776). working time in the PHC (0.688). age group (0.656); while for dimension 2 were: professional category (0.383) and knowledge of drug users in their coverage area (0.166). There are important differences in attitudes and practices about the approach of drug users among professionals.

Improvement of Multiple-Locus VNTR Analysis Typing Scheme for Helicobacter pylori

Aims: To improve a multiple-locus variable-number tandem-repeat (VNTR) analysis (MLVA) assay for Helicobacter pylori typing.&#x0D; Materials and Methods: Polymorphic VNTRs were searched by Gene Expert. The distribution and polymorphism of each VNTR locus were analyzed in 18 H. pylori genomes from the NCBI genome database by BLAST and were compared with a collection of 15 clinical H. pylori strains. The MLVA assay was compared with MLST-typing for discriminating H. pylori isolates.&#x0D; Results: Twelve VNTR loci were identified by bioinformatic screening of H. pylori genomes, and five of them were highly polymorphic. Therefore, an MLVA assay composed of five VNTR loci was developed with greatest discriminatory power.&#x0D; Conclusion: MLVA typing is a faster and more standardized method for studying the genetic relatedness of H. pylori isolates. At preliminary stage it is sufficient to use only 3 VNTR loci for the differentiation of H. pylori strains.

Physical performance measures in screening for reduced lean body mass in adult females with obesity

Background & aimsLittle is known about the reduction of lean body mass (LBM) in obesity, or how to identify it in standard clinical settings. We therefore aimed to assess the prevalence of low LBM in adult females with obesity, and to identify the reliability of simple tools for its screening in this population. Methods and ResultsDual-energy X-ray absorptiometry (DXA) body composition assessment was used to categorise 147 female participants with obesity as with or without low LBM, according to the new definition that takes into account both appendicular lean mass (ALM) and body mass index (BMI)—ALM/BMI <0.512. Participants were also administered the six-minute walking test, handgrip-strength test and 4-metre gait-speed test.Of the sample of 147 participants, 93 (63.3%) met the criteria for reduced LBM. Stepwise multivariate logistic regression analysis showed that the six-minute walking test was the only independent test associated with low LBM (OR = 0.992, 95%CI 0.987–0.998). Receiver operating characteristic (ROC) curve analysis found that the discriminating cut-off points of the tests considered were 470 m, 3.30 s (gait speed = 1.2 m/sec) and 23.5 kg respectively; the 4-metre gait-speed test seems to provide the best balance of sensitivity and specificity, and the greatest discriminatory power at 90% sensitivity. ConclusionsTreatment-seeking adult females with obesity display a great prevalence of reduced LBM. The six-minute walking test was the only independent test associated with low LBM, but the 4-metre gait-speed test seems to be the most accurate functional test for screening for this condition in that population.

Validity of the CR-POSSUM model in surgery for colorectal cancer in Spain (CCR-CARESS study) and comparison with other models to predict operative mortality

BackgroundTo validate and recalibrate the CR- POSSUM model and compared its discriminatory capacity with other European models such as POSSUM, P-POSSUM, AFC or IRCS to predict operative mortality in surgery for colorectal cancer.MethodsProspective multicenter cohort study from 22 hospitals in Spain. We included patients undergoing planned or urgent surgery for primary invasive colorectal cancers between June 2010 and December 2012 (N = 2749). Clinical data were gathered through medical chart review. We validated and recalibrated the predictive models using logistic regression techniques. To calculate the discriminatory power of each model, we estimated the areas under the curve - AUC (95% CI). We also assessed the calibration of the models by applying the Hosmer-Lemeshow test.ResultsIn-hospital mortality was 1.5% and 30-day mortality, 1.7%. In the validation process, the discriminatory power of the CR-POSSUM for predicting in-hospital mortality was 73.6%. However, in the recalibration process, the AUCs improved slightly: the CR-POSSUM reached 75.5% (95% CI: 67.3–83.7). The discriminatory power of the CR-POSSUM for predicting 30-day mortality was 74.2% (95% CI: 67.1–81.2) after recalibration; among the other models the POSSUM had the greatest discriminatory power, with an AUC of 77.0% (95% CI: 68.9–85.2). The Hosmer-Lemeshow test showed good fit for all the recalibrated models.ConclusionThe CR-POSSUM and the other models showed moderate capacity to discriminate the risk of operative mortality in our context, where the actual operative mortality is low. Nevertheless the IRCS might better predict in-hospital mortality, with fewer variables, while the CR-POSSUM could be slightly better for predicting 30-day mortality.Trail registrationRegistered at: ClinicalTrials.gov Identifier: NCT02488161

Instrumental neutron activation analysis in forensic science in Jamaica: The case of the Coral Springs beach theft

Following the theft of sand from the Coral Springs beach in Jamaica, authorities approached the International Centre for Environmental and Nuclear Sciences to determine if geochemical analysis could add evidentiary value to collected sediment samples. Forty-three beach sediments comprising of scene and suspect samples were submitted for inorganic elemental investigation by neutron activation analysis. The samples were analyzed for thirty-five elements of which nine (Al, Ca, Ce, Cr, Dy, Fe, Mn, Sc and Sr) were used in statistical evaluation including agglomerative hierarchical clustering, of the dataset. Al, Fe and Sc were the elements with greatest discriminatory power. The methodology illustrated clear similarities in elemental profiles between the donor beach and some suspected receptor beaches while excluding other suspected receptor beaches and potential donor beaches. Interrogation of the dataset provided additional and important information for the authorities and indicated that neutron activation analysis with the use of multivariate statistics can contribute significantly to geoforensic investigations.

Contamination of pine and birch wood dust with microscopic fungi and determination of its sterol contents.

Wood compounds, especially sterols, are connected with the level of contamination with microscopic fungi. Within this study, tests were conducted on wood dust samples collected at various work stations in a pine and birch timber conversion plant. Their contamination with mycobiota was measured as the concentration of ergosterol (ERG) by ultra performance liquid chromatography (UPLC). Another aim of this study was to assess the effect of contamination with microscopic fungi on the sterol contents in wood dusts. Analyses were conducted on five sterols: desmosterol, cholesterol, lanosterol, stigmasterol, and β-sitosterol using UPLC and their presence was confirmed using gas chromatography/mass spectrometry (GC/MS). The results of chemical analyses showed the greatest contamination with mycobiota in birch wood dust. We also observed varied contents of individual sterols depending on the wood dust type. Their highest concentration was detected in birch dust. The discriminant analysis covering all tested compounds as predictors showed complete separation of all tested wood dust types. The greatest discriminatory power was found for stigmasterol, desmosterol, and ergosterol.

Listeria monocytogenesCirculating in Rabbit Meat Products and Slaughterhouses in Italy: Prevalence Data and Comparison Among Typing Results

Rabbit meat has outstanding dietetic and nutritional properties. However, few data on microbiological hazards associated with rabbit productions are available. In this study, the presence of Listeria monocytogenes was determined in 430 rabbit carcasses, 256 rabbit meat cuts and products, and 599 environmental sponges collected from four Italian rabbit slaughterhouses over a period of 1 year. Prevalence of L. monocytogenes among the 1285 rabbit meat and environmental samples was 11%, with statistically significant differences between slaughterhouses. The highest prevalence (33.6%) was observed in rabbit meat cuts and products; the majority of positive environmental samples were collected from conveyor belts. Overall, 27.9% and 14.3% of rabbit cuts and carcasses, respectively, had L. monocytogenes counts higher than 1 colony-forming unit (CFU)/10 g. A selection of 123 isolates from positive samples was genotyped and serotyped to determine genetic profiles and diversity among L. monocytogenes isolates contaminating different slaughterhouses and classes of products investigated. Discriminatory power and concordance among the results obtained using multilocus variable-number tandem-repeat analysis (MLVA), multilocus sequence typing (MLST), pulsed-field gel electrophoresis (PFGE), automated EcoRI ribotyping, and serotyping were assessed. The isolates selected for typing were classified into serotypes 1/2a (52.8%), 1/2c (32.5%), and 1/2b (14.6%). The majority of the isolates were classified as ST14 (34.1%), ST9 (35.5%), ST121 (17.9%), and ST224 (14.6%). The greatest discriminatory power was observed with the MLVA typing, followed by MLST, PFGE, and ribotyping. The best bidirectional concordance was achieved between PFGE and MLST. There was 100% correlation between both MLST and MLVA with serotype. Moreover, a high unidirectional correspondence was observed between MLVA and both MLST and PFGE, as well as between PFGE and both MLST and serotyping. The results of this study show for the first time in Italy prevalence and genetic profiles of L. monocytogenes isolated in rabbit products and slaughterhouses.