Laboratory Test Variables Research Articles

Effects of pretreatment HIV drug resistance on the virological response of HIV-infected patients after 3-year antiretroviral therapy

Objective: To investigate the impact of pretreatment drug resistance (PDR) on virological effect among HIV-infected patients having received antiretroviral therapy (ART) after three years. Methods: The baseline survey of PDR among HIV-infected patients was conducted in 2018, with a three-year follow up study. The clinic data and virological laboratory test variables were statistically analyzed. Results: Of the 2 433 participants, 41.6% (1 012/2 433) were aged between 18 and 34, 82.8% (2 015/2 433) were males, 46.9% (1 142/2 433) had education of high school or above, 22.4% (544/2 433) were farmers, 33.8% (823/2 433) were unmarried, 48.1% (1 169/2 433) were infected heterosexually and 41.3% (1 004/2 433) were with CRF07_BC. The prevalence of PDR was 4.5% (109/2 433). The prevalence of virological suppression failure (viral load ≥50 copies/ml) and drug resistance at three years follow up after ART was 8.1%(196/2 433) and 2.5%(60/2 433) respectively. The prevalence of virological suppression failure and drug resistance at three years follow up after ART were 18.3% (20/109) and 7.6% (176/2 324), and 4.6% (5/109) and 2.4% (55/2 324) among participants with PDR and non-PDR, respectively. The results of multivariate logistic regression model showed that illiteracy (aOR=3.26, 95%CI: 1.82-5.86), primary and junior high school education (aOR=1.54, 95%CI: 1.09-2.18), CD4+T lymphocyte count <200/μl (aOR=2.77, 95%CI: 1.75-4.37) and CD4+T lymphocyte count 200-499/μl (aOR=1.55, 95%CI: 1.10-2.18) at a three year follow up visit after ART, missed drugs in the past month (aOR=4.24, 95%CI: 2.92-6.17), and PDR (aOR=2.84, 95%CI: 1.67-4.85) were statistically significant with virological suppression failure on treatment. Conclusions: The prevalence of PDR in China at a low level currently, and the virological suppression failure rate is low after three years of ART. It is necessary to strengthen drug resistance monitoring of HIV-infected patients and pay attention to the influence of PDR on treatment effect.

60P Machine learning based on blood biomarkers predicts fast progression in advanced NSCLC patients treated with immunotherapy

Fast progression (FP) represents a detrimental situation for advanced non-small cell lung cancer (NSCLC) patients undergoing immune checkpoint inhibitor (ICI) therapy. We here aimed to develop an advanced NSCLC-specific predictive framework for identification of clinical FP using machine learning (ML) methods based on blood test biomarkers. We extracted atezolizumab-treated patients from 4 multicenter clinical trials, namely OAK, BIRCH, POPLAR and FIR. FP was defined as either a ≥50% increase in the sum of largest diameters within 6 weeks or death due to disease progression within 12 weeks. The patients of the OAK trial were taken for for model training, and the patients of the other trials were used for independent validation. By using 21 pretreatment laboratory test variables, seven ML approaches including the LASSO, GLM, SVM, Decision Tree model (DT), the Random Forest model (RF), the eXtreme Gradient Boosting model (XGB), and the Generalized Boosted Regression Models (GBM), a prediction model for FP was developed. The performance was evaluated using the receiver operating characteristic (ROC) curve and the precision-recall curve. The prevalence of FP was 7.6% (118 of 1546) in all atezolizumab treated patients. The most important variables for the prediction model were: C-Reactive Protein (CRP), Neutrophil-Lymphocyte Ratio (NLR), Platelet-Lymphocyte Ratio (PLR), Lymphocyte-Neutrophil-Monocyte Ratio (LMR), Lactate Dehydrogenase (LDH), and Alanine Transaminase (ALT). The XGBoost method with 6 biomarkers demonstrated a robust performance: Area under the ROC Curve (AUC) were 0.8433, 0.6602, and 0.7978 in the training cohort (OAK) and validation cohort 1 (BIRCH) and 2 (merged POPLAR and FIR), respectively. In addition, the absolute difference in median survival between the FP and non-FP groups was significant for both progression-free survival (PFS) and overall survival (OS) (P <0.001). The identified ML method-based, 6 blood biomarkers including, the XGBoost method allow discrimination of FP in advanced NSCLC patients before ICI therapy, which should improve personalized therapeutic decision-making in ICI therapy for NSCLC.

Cardiac complications in a geriatric population hospitalized with COVID-19: The OCTA-COVID cohort

PurposeThe geriatric population is especially vulnerable to coronavirus disease (COVID-19) and its potential complications. We sought to analyze the incidence of cardiological complications in an elderly population hospitalized for COVID-19. MethodsA prospective observational longitudinal that included patients ≥75 years of age with diagnosis of COVID-19 admitted to the Geriatric Department from March to May 2020. Epidemiological, geriatric, clinical and laboratory test variables were collected. Cardiovascular events, including de novo atrial fibrillation (AF), acute coronary syndrome (ACS), congestive heart failure (CHF), pulmonary embolism and in-hospital death, were documented. A follow-up was carried out at 12 months through a telephone interview as well as using electronic medical records, collecting cardiac events and mortality. Results305 patients were included; 190 (62.3%) were female, with median age of 87 years (interquartile range (82–91)). More than half of the patients had a history of cardiac disease, with AF being the most common and affecting 85 (27.9%) patients. During hospitalization, 112 (36.7%) patients died. Eighty-nine (29.2%) patients presented cardiac complications. Acute heart failure was the most prevalent (46; 15.1%), followed by new-onset AF (20; 6.5%), pulmonary embolism (17; 5.6%), and ACS (5; 1.6%). Patients with cardiac complications had a longer hospital stay (p<0.001). During follow-up, 29 (15.1%) died, and 40 (20.8%) patients had a cardiovascular event being CHF the most prevalent complication (16.7%). ConclusionThe incidence of cardiovascular complications in geriatric patients is high and is associated with a longer hospital stay. CHF was the most frequent event, followed by AF.

Integrated wellbore-reservoir simulations to design sand retention tests for flowback scenarios in SAGD injection wells

In the past, sand retention testing (SRT) research for steam-assisted gravity drainage (SAGD) injector was a parametric study, or general solution, rather than a case-specific solution for a particular problem in terms of testing parameters. Testing parameters were assigned based on hypothetical assumptions due to a lack of necessary field data to perform such a study. Field data are often confidential and nearly impossible to obtain for a hazardous scenario like a thermal injector flowback. The literature is rich with multiple proposed slotted liner (SL) design criteria for SAGD production wells. The SRT designed for SAGD producer takes into consideration some measurable factors to specify suitable aperture size. In contrast, SRT for the SAGD injector seems to rely on industry experience or rules of thumb. A systematic methodology, consisting of three steps, was developed for SL design using the SRT setup for SAGD injector wells. The first step involves estimating the laboratory testing variables or operational parameters based on case-specific data and reservoir simulations to assess the consequences of steam flowback. A 2D Computer Modelling Group (CMG) thermal simulator was coupled with gas flow correlation and used to predict the outcomes of SAGD injector flowback. The second step involves developing a new SRT setup dedicated to SAGD injector flowback laboratory testing. Intensive testing was performed to troubleshoot the problems associated with a high-velocity gas flow. The third and final step involves conducting six tests to verify the developed setup's performance. The consideration of thermodynamic equilibrium improved testing by avoiding inconsistent assumptions used in the previous studies. Neither low steam quality (SQ) nor high SQ flowback scenarios used in the past are found to fully represent SAGD injector flowback. SAGD injector depth and other operational parameters are linked to flowback differential pressure. In other words, one set of testing parameters cannot be representative for all SAGD injector, which makes developing design criteria a challenge. The preliminary results of SRT for SAGD injector indicate the possibility of using small aperture size slots of 0.010 inch that do not cause significant permeability reduction at laboratory scale, unlike the case for SAGD producer SRT. This may justify why the industry tends to prefer small aperture size slotted liner for SAGD injector completion. Eventually, this research should be considered as a first step only in SRT for SAGD injector flowback, and necessary methodology enhancements and facility upgrades should be investigated in future work.

Evaluación de factores asociados con mortalidad en la intoxicación por paraquat

In Colombia, paraquat poisoning (PQ) is one of the main causes of self-inflicted pesticide poisoning. There is not antidotal treatment against its toxicity, influencing an uncertain prognosis and changeful survival. Objective: To describe the prognosis of patients with PQ poisoning treated in a high-level hospital and to evaluate the association of mortality with clinical and laboratory test variables, considering its variation over time. Methods: Retrospective study between 2011 and 2018 at the Hospital San Vicente Fundación (Medellín, Colombia). Included cases diagnosed with PQ poisoning, of any age and sex. Diagnoses of concomitant intake of other toxins, underlying lung disease, and trauma were excluded. Sociodemographic and clinical characteristics were described, the effect on mortality and variation over time were analyzed, to search for prognostic research candidates. Results: Cohort of 67 patients, mostly single men, under 30 years of age, located in rural area was recruited. A mortality of 37.3% (95% CI 36.9 to 37.7%) was found, median time to death of 117 h (IQR 62h-238h). The instantaneous risk of dying for the male sex was 1.93; 95% CI 1.44 to 10.26; p = 0.007. Laboratory changes over time: AST (HR = 1.009; 95% CI; 1.007-1.012; p≤0.001), ALT (HR = 1.008; 95% CI 1.006-1.01; p≤0.001), total bilirubin (HR = 1.23; 95% CI 1,173-1.29; p≤0.001), creatinine (HR = 1.53; 95% CI 1,398-1,667; p≤0.001). Conclusion: Factors associated with mortality in PQ poisoning: ingested dose, intentional intake, male sex, and age. The change over time of AST, ALT, creatinine, and total bilirubin is related to death. Design dynamic models with clinical and laboratory test variables that include their evolution during the hospital stay can optimize the prognosis prediction.

Cerebral oxygen saturation (rSO2) during cardiopulmonary bypass (CPB) measured using the INVOS oximeter closely correlates with baseline rSO2.

Baseline cerebral regional saturation (rSO2) measured using the INVOS 5100C (Medtronic, MN, USA) varies widely among patients with cardiac and/or renal diseases. To identify significant correlates of baseline rSO2 and to investigate intraoperative rSO2 changes, we conducted a retrospective study in 494 patients undergoing on-pump cardiovascular surgery. Correlations between preoperative blood laboratory test variables and baseline rSO2 before anesthesia were examined. Intraoperative rSO2 changes were analyzed. Of all the variables examined, log-transformed B-type natriuretic peptide (BNP) most significantly and negatively correlated with baseline rSO2 (r = - 0.652, p < 0.0001). Intraoperatively, rSO2 showed the lowest value during cardiopulmonary bypass (CPB) (median rSO2: 56.2% during CPB vs. 63.9% at baseline, p < 0.0001). Although rSO2 during CPB correlated positively with hemoglobin concentration and oxygen delivery during CPB (r = 0.192, p < 0.0001; and r = 0.172, p = 0.0001, respectively), it correlated much more closely with baseline rSO2 (r = - 0.589, p < 0.0001). Thus, patients showing low baseline rSO2 primarily associated with preoperatively high BNP continued to show low rSO2 even during CPB independent of hemodynamics artificially controlled by CPB. Our findings suggest that low baseline rSO2 in patients with high BNP due to cardiac and/or renal diseases is more likely to result from tissue edema causing alterations in optical pathlength and thus in calculated rSO2 values, not readily modifiable with CPB, rather than actual cerebral hemodynamic alterations readily modifiable with CPB. These may partly explain why the INVOS oximeter is a trend monitor requiring baseline measures.

Effect of seasons and sex on the physical, hematological, and blood biochemical parameters of Noma horses.

ABSTRACTThis study aimed to evaluate the influence of seasons and sex on body size and hematological and biochemistry parameters of Noma horses, a native Japanese breed. Body size was larger in winter than in summer. Laboratory testing variables, including erythrocytic parameters and urea nitrogen, total cholesterol, and creatinine kinase levels, were higher in winter, while the eosinophil count was higher in summer. These seasonal differences may be related to increased energy consumption of horses due to heat stress. The higher eosinophil counts may have been related to the dermatitis observed in summer. Stallions tended to have smaller bodies compared with mares. Future studies are necessary to investigate the effect of stress in seasonal and sex-based groups.

A Randomized, Double-Blind, Placebo-Controlled, Two-Way Crossover Clinical Trial of ORADUR-Methylphenidate for Treating Children and Adolescents with Attention-Deficit/Hyperactivity Disorder

Objective: Methylphenidate (MPH) is efficacious in reducing symptoms of attention-deficit/hyperactivity disorder (ADHD), but there are no data about the efficacy and safety of its new formulation (ORADUR®-MPH extended release, ORADUR-MPH) in patients with ADHD, which is the study objective.Method: This was a Phase III, multicenter, randomized, double-blind, placebo-controlled, two-way crossover clinical trial. One hundred children and adolescents with a clinical diagnosis of ADHD (72.7% male) received at least one dose of ORADUR-MPH or a placebo during the 2-week treatment period of each phase. The primary efficacy measure was the Swanson, Nolan, and Pelham-IV-teacher (SNAP-IV-T) form. Secondary efficacy measures included the SNAP-IV-parent form, the Clinical Global Impression: ADHD-Severity score, the Conner's Teacher's Rating Scale score, and the investigator's rating for 18 Diagnostic and Statistical Manual of Mental Disorders, 5th edition ADHD symptoms. In addition, data related to vital signs, body weight, physical examination, laboratory testing, and adverse events (AEs) were also collected. All data were analyzed on an intent-to-treat basis.Results: Without adjusting for differences in demographics and baseline measures, both treatment groups showed significant reductions in ADHD and oppositional defiant disorder symptoms after a 2-week treatment with greater effect sizes (Cohen's d) in the ORADUR-MPH group (Cohen's d ranging from −0.41 to −1.64; placebo, Cohen's d ranging from −0.26 to −1.18), except for oppositional symptoms, regardless of the informants. For the primary efficacy measure, ORADUR-MPH was significantly superior to the placebo, as evidenced by lower values for and greater reductions in the SNAP-IV-T scores at the endpoint (Cohen's d = −0.16, p = 0.005) and from baseline to the endpoint (Cohen's d = −0.19, p = 0.006), respectively. There were no serious AEs during the clinical study period. The most frequently observed AE was decreased appetite (49.1%). Most physical and laboratory test variables remained within the normal range.Conclusions: Once-daily ORADUR-MPH is an effective, well-tolerable, and safe treatment for children and adolescents with ADHD. ClinicalTrials.gov number, NCT02450890.

Prediction for Intravenous Immunoglobulin Resistance Combining Genetic Risk Loci Identified From Next Generation Sequencing and Laboratory Data in Kawasaki Disease.

Background: Kawasaki disease (KD) is the most common cause of acquired heart disease. A proportion of patients were resistant to intravenous immunoglobulin (IVIG), the primary treatment of KD, and the mechanism of IVIG resistance remains unclear. The accuracy of current models predictive of IVIG resistance is insufficient and doesn't meet the clinical expectations.Objectives: To develop a scoring model predicting IVIG resistance of patients with KD.Methods: We recruited 330 KD patients (50 IVIG non-responders, 280 IVIG responders) and 105 healthy children to explore the susceptibility loci of IVIG resistance in Kawasaki disease. A next generation sequencing technology that focused on 4 immune-related pathways and 472 single nucleotide polymorphisms (SNPs) was performed. An R package SNPassoc was used to identify the risk loci, and student's t-test was used to identify risk factors associated with IVIG resistance. A random forest-based scoring model of IVIG resistance was built based on the identified specific SNP loci with the laboratory data.Results: A total of 544 significant risk loci were found associated with IVIG resistance, including 27 previous published SNPs. Laboratory test variables, including erythrocyte sedimentation rate (ESR), platelet (PLT), and C reactive protein, were found significantly different between IVIG responders and non-responders. A scoring model was built using the top 9 SNPs and clinical features achieving an area under the ROC curve of 0.974.Conclusions: It is the first study that focused on immune system in KD using high-throughput sequencing technology. Our findings provided a prediction of the IVIG resistance by integrating the genotype and clinical variables. It also suggested a new perspective on the pathogenesis of IVIG resistance.

Clinical features, laboratory findings and persistence of virus in 10 children with coronavirus disease 2019 (COVID-19)

BackgroundA pandemic caused by SARS-CoV-2 infection (COVID-19) has rapidly spread across the globe. Although many articles have established the clinical characteristics of adult COVID-19 patients so far, limited data are available for children. The aim of this study was to reveal the clinical features, laboratory findings and nucleic acid test results of ten pediatric cases. MethodsIn this retrospective single-center cohort study, pediatric cases with COVID-19 infection were consecutively enrolled in one hospital in Huangshi, China from January 1 to March 11, 2020. ResultsA total of 10 children with COVID-19 were recruited. Of them, four were the asymptomatic type, one was the mild type, and five were the moderate type (including two subclinical ones). All patients were from family clusters. Only fever, nasal discharge and nasal congestion were observed. Lymphopenia and leukopenia were uncommon in our sample but elevated levels of lactate dehydrogenase (LDH) and alpha-hydroxybutyrate dehydrogenase (α-HBDH) were observed frequently. Of these laboratory test variables, no statistical difference was identified between asymptomatic and symptomatic patients. Abnormalities in radiological data were detected in five patients, and representative findings of chest CT images were patchy shadows and ground-glass opacities. There were two cases whose oropharyngeal nucleic acid tests reversed to positive after one negative result, and two patients whose oropharyngeal swabs tested negative but rectal swabs showed positive. ConclusionsClinical symptoms were mild in children with COVID-19. Increased levels of LDH and α-HBDH were potential clinical biomarkers for pediatric cases. More attention should be paid to the SARS-CoV-2 viral assessment of rectal swabs before patients are discharged.

Effective optimization of SARS-CoV-2 laboratory testing variables in an era of supply chain constraints.

RT-PCR-based assays for the detection of SARS-CoV-2 have played an essential role in the current COVID-19 pandemic. However, the sample collection and test reagents are in short supply, primarily due to supply chain issues. Thus, to eliminate testing constraints, we have optimized three key process variables: RNA extraction and RT-PCR reactions, different sample types and media to facilitate SARS-CoV-2 testing. By performing various validation and bridging studies, we have shown that various sample types such as nasopharyngeal swab, bronchioalveolar lavage and saliva, collected using conventional nasopharyngeal swabs, ESwab or 3D-printed swabs and, preserved in viral transport media, universal transport media, 0.9% sodium chloride or Amies media are compatible with RT-PCR assay for COVID-19. Besides, the reduction of PCR reagents by up to fourfold also produces reliable results.

Predicting Missing Values in Medical Data Via XGBoost Regression

The data in a patient's laboratory test result is a notable resource to support clinical investigation and enhance medical research. However, for a variety of reasons, this type of data often contains a non-trivial number of missing values. For example, physicians may neglect to order tests or document the results. Such a phenomenon reduces the degree to which this data can be utilized to learn efficient and effective predictive models. To address this problem, various approaches have been developed to impute missing laboratory values; however, their performance has been limited. This is due, in part, to the fact no approaches effectively leverage the contextual information 1) in individual or 2) between laboratory test variables. We introduce an approach to combine an unsupervised prefilling strategy with a supervised machine learning approach, in the form of extreme gradient boosting (XGBoost), to leverage both types of context for imputation purposes. We evaluated the methodology through a series of experiments on approximately 8,200 patients' records in the MIMIC-III dataset. The results demonstrate that the new model outperforms baseline and state-of-the-art models on 13 commonly collected laboratory test variables. In terms of the normalized root mean square derivation (nRMSD), our model exhibits an imputation improvement by over 20%, on average. Missing data imputation on the temporal variables can be largely improved via prefilling strategy and the supervised training technique, which leverages both the longitudinal and cross-sectional context simultaneously.

Risk Prediction for Poor Outcome and Death in Hospital In-Patients with COVID-19: Derivation in Wuhan, China and External Validation in London, UK

Background: Accurate risk prediction of clinical outcome would usefully inform clinical decisions and intervention targeting in COVID-19. The aim of this study was to derive and validate risk prediction models for poor outcome and death in adult inpatients with COVID-19. Methods: Model derivation using data from Wuhan, China used logistic regression with death and poor outcome (death or severe disease) as outcomes. Predictors were demographic, comorbidity, symptom and laboratory test variables. The best performing models were externally validated in data from London, UK. Findings: 4.3% of the derivation cohort (n=775) died and 9.7% had a poor outcome, compared to 34.1% and 42.9% of the validation cohort (n=226). In derivation, prediction models based on age, sex, neutrophil count, lymphocyte count, platelet count, C-reactive protein and creatinine had excellent discrimination (death c-index=0.91, poor outcome c-index=0.88), with good-to-excellent calibration. Using two cut-offs to define low, high and very-high risk groups, derivation patients were stratified in groups with observed death rates of 0.34%, 15.0% and 28.3% and poor outcome rates 0.63%, 8.9% and 58.5%. External validation discrimination was good (c-index death=0.74, poor outcome=0.72) as was calibration. However, observed rates of death were 16.5%, 42.9% and 58.4% and poor outcome 26.3%, 28.4% and 64.8% in predicted low, high and very-high risk groups. Interpretation: Our prediction model using demography and routinely-available laboratory tests performed very well in internal validation in the lower-risk derivation population, but less well in the much higher-risk external validation population. Further external validation is needed. Collaboration to create larger derivation datasets, and to rapidly externally validate all proposed prediction models in a range of populations is needed, before routine implementation of any risk prediction tool in clinical care. Funding Statement: HW and HZ are supported by Medical Research Council and Health Data Research UK Grant (MR/S004149/1), Industrial Strategy Challenge Grant (MC_PC_18029) and Wellcome Institutional Translation Partnership Award (PIII054). RD is supported by the National Institute for Health Research (NIHR) Biomedical Research Centre at South London and Maudsley NHS Foundation Trust and King’s College London. DMB is funded by a UKRI Innovation Fellowship as part of Health Data Research UK MR/S00310X/1 (https://www.hdruk.ac.uk). KD is supported by LifeArc STOPCOVID award. This work uses data provided by patients and collected by the NHS as part of their care and support. XW is supported by National Natural Science Foundation of China (grant number:81700006). QL is supported by National Key R&D Program (2018YFC1313700), National Natural Science Foundation of China (grant number: 81870064) and the “Gaoyuan” project of Pudong Health and Family Planning Commission (PWYgy2018-06).Declaration of Interests: The authors declare no competing interests.Ethics Approval Statement: The derivation study was approved by the Research Ethics Committee of Shanghai Dongfang Hospital and Taikang Tongji Hospital. The external validation study operated under London South East Research Ethics Committee (reference 18/LO/2048) approval granted to the King’s Electronic Records Research Interface (KERRI).

Cooper Test Provides Better Half-Marathon Performance Prediction in Recreational Runners Than Laboratory Tests.

This study compared the ability to predict performance in half-marathon races through physiological variables obtained in a laboratory test and performance variables obtained in the Cooper field test. Twenty-three participants (age: 41.6 ± 7.6 years, weight: 70.4 ± 8.1 kg, and height: 172.5 ± 6.3 cm) underwent body composition assessment and performed a maximum incremental graded exercise laboratory test to evaluate maximum aerobic power and associated cardiorespiratory and metabolic variables. Cooper’s original protocol was performed on an athletic track and the variables recorded were covered distance, rating of perceived exertion, and maximum heart rate. The week following the Cooper test, all participants completed a half-marathon race at the maximum possible speed. The associations between the laboratory and field tests and the final time of the test were used to select the predictive variables included in a stepwise multiple regression analysis, which used the race time in the half marathon as the dependent variable and the laboratory variables or field tests as independent variables. Subsequently, a concordance analysis was carried out between the estimated and actual times through the Bland-Altman procedure. Significant correlations were found between the time in the half marathon and the distance in the Cooper test (r = −0.93; p < 0.001), body weight (r = 0.40; p < 0.04), velocity at ventilatory threshold 1, (r = −0.72; p < 0.0001), speed reached at maximum oxygen consumption (vVO2max), (r = −0.84; p < 0.0001), oxygen consumption at ventilatory threshold 2 (VO2VT2) (r = −0.79; p < 0.0001), and VO2max (r = −0.64; p < 0.05). The distance covered in the Cooper test was the best predictor of time in the half-marathon, and might predicted by the equation: Race time (min) = 201.26 – 0.03433 (Cooper test in m) (R2 = 0.873, SEE: 3.78 min). In the laboratory model, vVO2max, and body weight presented an R2 = 0.77, SEE 5.28 min. predicted by equation: Race time (min) = 156.7177 – 4.7194 (vVO2max) – 0.3435 (Weight). Concordance analysis showed no differences between the times predicted in the models the and actual times. The data indicated a high predictive power of half marathon race time both from the distance in the Cooper test and vVO2max in the laboratory. However, the variable associated with the Cooper test had better predictive ability than the treadmill test variables. Finally, it is important to note that these data may only be extrapolated to recreational male runners.

Prospective Diagnosis of VWD in a Large Cohort of Patients with Bleeding Symptoms through the Zimmerman Program

Prospective Diagnosis of VWD in a Large Cohort of Patients with Bleeding Symptoms through the Zimmerman Program

Neuro-Fuzzy Modelling of the Metallic Surface Characterization on Linear Dry Contact between Plastic Material Reinforced with SGF and Alloyed Steel.

This paper presents the modelling of wear data resulting from linear dry contact using artificial neural networks (ANN) and adaptive neuro-fuzzy inference systems (ANFIS) with the aim of constructing predictor models for the depth and volume of the wear scar, with great impact in the characterization of new industrial processes utilizing existing materials. The dataset is the result of laboratory testing, presenting both numerical and categorical variables whose inclusion into the model allows for a number of possibilities. The width of the wear scar was measured on a microscope, and its depth was calculated. A multitude of experimental tests was performed with normal loads and different speeds, which led to some conclusive results, but in some cases, with relatively high variance. Various options for the automatic generation of fuzzy inference systems were also approached (genfis2). The innovative approach was compared with a baseline model featuring multivariate linear regression optimized using gradient descent, drawing on previous experimentation on the same dataset. The models developed can be implemented in future research and in practical applications under similar conditions, aiming to optimize performance by applying Computer Science. The obtained results lead to highly accurate prediction models which are further integrated into various metallic surface characterizations in the wear process for tribological and robotics research in new industrial processes using short glass fiber reinforced polymers.

Early hospital mortality prediction of intensive care unit patients using an ensemble learning approach

BackgroundMortality prediction of hospitalized patients is an important problem. Over the past few decades, several severity scoring systems and machine learning mortality prediction models have been developed for predicting hospital mortality. By contrast, early mortality prediction for intensive care unit patients remains an open challenge. Most research has focused on severity of illness scoring systems or data mining (DM) models designed for risk estimation at least 24 or 48h after ICU admission. ObjectivesThis study highlights the main data challenges in early mortality prediction in ICU patients and introduces a new machine learning based framework for Early Mortality Prediction for Intensive Care Unit patients (EMPICU). Materials and methodsThe proposed method is evaluated on the Multiparameter Intelligent Monitoring in Intensive Care II (MIMIC-II) database. Mortality prediction models are developed for patients at the age of 16 or above in Medical ICU (MICU), Surgical ICU (SICU) or Cardiac Surgery Recovery Unit (CSRU). We employ the ensemble learning Random Forest (RF), the predictive Decision Trees (DT), the probabilistic Naive Bayes (NB) and the rule-based Projective Adaptive Resonance Theory (PART) models. The primary outcome was hospital mortality. The explanatory variables included demographic, physiological, vital signs and laboratory test variables. Performance measures were calculated using cross-validated area under the receiver operating characteristic curve (AUROC) to minimize bias. 11,722 patients with single ICU stays are considered. Only patients at the age of 16 years old and above in Medical ICU (MICU), Surgical ICU (SICU) or Cardiac Surgery Recovery Unit (CSRU) are considered in this study. ResultsThe proposed EMPICU framework outperformed standard scoring systems (SOFA, SAPS-I, APACHE-II, NEWS and qSOFA) in terms of AUROC and time (i.e. at 6h compared to 48h or more after admission). Discussion and conclusionThe results show that although there are many values missing in the first few hour of ICU admission, there is enough signal to effectively predict mortality during the first 6h of admission. The proposed framework, in particular the one that uses the ensemble learning approach – EMPICU Random Forest (EMPICU-RF) offers a base to construct an effective and novel mortality prediction model in the early hours of an ICU patient admission, with an improved performance profile.

Comparison of acute cholangitis with or without common bile duct dilatation.

To improve the management of patients with acute cholangitis, the present study compared laboratory test variables between acute cholangitis patients with or without common bile duct (CBD) dilatation [CBDdil(+) and CBDdil(-), respectively]. The medical records of patients diagnosed with acute cholangitis and subjected to endoscopic retrograde cholangiopancreatography between February 2008 and May 2015 were retrospectively analyzed. The present study consisted of 40 men (aged 69.4±8.8 years) and 37 women (aged 68.8±11.6 years). It was observed that CBDdil(-) patients were slightly younger than CBDdil(+) patients (P=0.0976), and levels of C-reactive protein (CRP) were significantly higher in CBDdil(-) patients than in CBDdil(+) patients (P=0.0392). In addition, logistic regression analysis indicated that CRP levels were associated with the presence of CBD dilatation (P=0.0392). These data indicate that patients with acute cholangitis without CBD dilatation tend to be younger and have higher levels of CRP. Thus, in acute cholangitis patients without CBD dilatation, diagnosis should be determined using clinical symptoms and laboratory data.

Prevalence of vitamin D deficiency in Thai patients receiving various modalities of renal replacement therapy

Background: Vitamin D status of Thai patients receiving renal replacement therapy (RRT) is incompletely known. Objectives: To determine the prevalence of vitamin D deficiency or insufficiency in adult Thai patients receiving various RRT modalities, and factors associated with low vitamin D levels. Methods: In this retrospective, observational, single-center, cross-sectional study, we evaluated dialysis-related laboratory test variables from 111 patients receiving RRT. Serum 25-hydroxyvitamin D concentration [25(OH)D] Results: Low vitamin D levels were identified in 100% patients receiving peritoneal dialysis (PD; 81% deficient, 19% insufficient), 94% patients receiving online-hemodiafiltration (OL-HDF; 50% deficient, 44% insufficient), and 100% patients with kidney transplants (KT; 55% deficient, 45% insufficient). PD patients showed significantly lower serum [25(OH)D] than OL-HDF or KT patients (10.5 ± 5.9 vs 17.7 ± 8.5 vs 15.4 ± 6.1 ng/mL respectively, P Conclusions: Nearly 100% patients receiving RRT had vitamin D deficiency or insufficiency, and RRT modalities might be related. Keywords: prevalence, renal replacement therapy, vitamin D deficiency, 25 hydroxyvitamin D

A Population-Based Acute Meningitis and Encephalitis Syndromes Surveillance in Guangxi, China, May 2007-June 2012.

ObjectivesAcute meningitis and encephalitis (AME) are common diseases with the main pathogens being viruses and bacteria. As specific treatments are different, it is important to develop clinical prediction rules to distinguish aseptic from bacterial or fungal infection. In this study we evaluated the incidence rates, seasonal variety and the main etiologic agents of AME, and identified factors that could be used to predict the etiologic agents.MethodsA population-based AME syndrome surveillance system was set up in Guigang City, Guangxi, involving 12 hospitals serving the study communities. All patients meeting the case definition were investigated. Blood and/or cerebrospinal fluid were tested for bacterial pathogens using culture or RT-PCR and serological tests for viruses using enzyme-linked immunosorbent assays. Laboratory testing variables were grouped using factor analysis. Multinomial logistic regression was used to predict the etiology of AME.ResultsFrom May 2007 to June 2012, the annual incidence rate of AME syndrome, and disease specifically caused by Japanese encephalitis (JE), other viruses, bacteria and fungi were 12.55, 0.58, 4.57, 0.45 and 0.14 per 100,000 population, respectively. The top three identified viral etiologic agents were enterovirus, mumps virus, and JE virus, and for bacteria/fungi were Streptococcus sp., Cryptococcus neoformans and Staphylococcus sp. The incidence of JE and other viruses affected younger populations and peaked from April to August. Alteration of consciousness and leukocytosis were more likely to be caused by JE, bacteria and fungi whereas CSF inflammation was associated with bacterial/fungal infection.ConclusionsWith limited predictive validity of symptoms and signs and routine laboratory tests, specific tests for JE virus, mumps virus and enteroviruses are required to evaluate the immunization impact and plan for further intervention. CSF bacterial culture cannot be omitted in guiding clinical decisions regarding patient treatment.