Categorical Parameters Research Articles

Anaemia and Its Correlates in Haart Naïve Patients in Port Harcourt, Nigeria

Introduction: Anemia is one of the complications of HIV infection, a multifactorial marker of bone marrow dysfunction, and an indicator of poor prognosis. Methods: A retrospective assessment of electronic data and case notes of HAART naïve patients in our hospital between January 2016 and December 2018 was done. Data on age, sex, packed cell volume (PCV) and CD4 at diagnosis was collected. Continuous variables were compared with the students’ t-test while categorical parameters were compared with the chi-square. Spearman’s correlation was used to assess the association between anaemia and the CD 4 count. Risk factors for the outcome variable were determined with logistic regression and a p-value of ≤0.05 was considered statistically significant. Results: The records of three hundred and twenty-one (321) new registrants in the Antiretroviral Therapy (ART) Clinic in Rivers State University Teaching Hospital (RSUTH) were evaluated. Their mean age was 40.43 ±10.51 years (range 19 – 76 years). Anemia was prevalent in 280(87.2%) patients. The CD4 count was normal in 102 (32.6%) patients. Female gender (p=0.001) and WHO clinical stage (p<0.001) were found to be the strongest predictors of anemia in this study. Conclusion: The findings from this study shows that a significant proportion of people infected with HIV present with severe immunosuppression and low hemoglobin. There is a need to strengthen the pathways for early diagnosis, prompt treatment by trained physicians and supportive care by hematologists to reduce the severity and impact of anemia in this group of patients.

Моделирование запасов продуктивной влаги в верхних слоях почвы методом нейронных дифференциальных уравнений

The studies on applying the neural ordinary differential equations (ODE) to the problem of modeling soil available water capacity were performed. The modification of the neural ODE for the problem with additional external meteorological (precipitation, wind speed, air temperature, and dew point) and categorical (crop type, soil type, and prevalent land cover type) parameters was proposed. The experiments led to the conclusion that the models based on the neural ODE are promising for modeling such complex unclosed systems as water exchange in the upper 0-10 and 0-20 cm soil layers. The considered nonlinear models perform much better than linear ones: the mean absolute error (MAE) of the 10-day available water capacity forecast is equal to 3.20 and 5.53 mm in the 0-10 and 0-20 cm soil layers, respectively. The proposed approach is promising for modeling processes in the soil and making management decisions in the agro-industrial complex. Keywords: available water capacity, neural differential equations, machine learning, neural networks

Parameters of complete blood count, lipid profile and their ratios in predicting obstructive coronary artery disease in patients with non-ST elevation acute coronary syndrome

Aim. To evaluate the predictive potential of the parameters of complete blood count (CBC), lipid profile and their ratios for predicting obstructive coronary artery disease (oCAD) in patients with non-ST elevation acute coronary syndrome (NSTEACS).Material and methods. The study included 600 patients with NSTE-ACS with a median age of 62 years who underwent invasive coronary angiography (CA). Two groups were formed, the first of which consisted of 360 (60%) patients with oCAD (stenosis ≥50%), and the second — 240 (40%) with coronary stenosis <50%. The clinical and functional status of patients before CAG was assessed by 33 parameters, including parameters of CBC, lipid profile and their ratio. For statistical processing and data analysis, the Mann-Whitney, Fisher, chi-squared tests, univariate logistic regression (LR) were used, while for the creation of predictive models, multivariate LR (MLR) was used. The quality was assessed by 4 metrics: area under the ROC curve (AUC), sensitivity (Se), specificity (Sp), and accuracy (Ac).Results. CBC and lipid profile analysis made it possible to identify factors that are linearly and non-linearly associated with oCAD. Univariate LR revealed their threshold values with the highest predictive potential. The quality metrics of the best prognostic model developed using MLR were as follows: AUC — 0,80, Sp — 0,79, Ac — 0,76, Se — 0,78. Its predictors were 8 following categorical parameters: age >55 years in men and >65 years in women, lymphocyte count (LYM) <19%, hematocrit >49%, immune-inflammation index >1000, high density lipoprotein cholesterol (HDL-C) to low density lipoprotein cholesterol (LDL-C) ratio <0,3, monocyte (MON)-to-HDL-C ratio >0,8, neutrophil (NEUT)-to-HDL-C ratio >5,7 and NEUT/LYM >3. The relative contribution of individual predictors to the development of end point was determined.Conclusion. The predictive algorithm (model 9), developed on the basis of MLR, showed a better quality metrics ratio than other models. The following 3 factors had the dominant influence on the oCAD risk: HDL-C/LDL-C (38%), age of patients (31%), and MON/HDL-C (14%). The influence of other factors on the oCAD risk was less noticeable.

Healthcare Providers’ Compliance with Guidelines for Catheter-Associated Urinary Tract Infections in a Rural Teaching and Referral Hospital

Introduction: Healthcare professionals (HCPs) play a key role in the prevention of catheter-associated urinary tract infections (CAUTI). This study aims to determine the compliance of healthcare personnel with urethral catheterisation standards and the factors affecting it. Materials and Methods: This study is a prospective survey and was conducted between February and March 2021 after ethical approval and patient consent. An internet-based, structured 39-item questionnaire was sent via email to all HCPs at Zonguldak Bulent Ecevit University Hospital, Zonguldak, Turkey. A to evaluate their knowledge and attitudes towards the prevention of CAUTI. The questionnaire was completed by 156 health professionals. For categorical parameters Fisher’s exact test, though for scale parameters student t-test, Mann–Whitney U and Kruskal–Wallis tests were used. All statistical analysis was done using SPSS 17.0. Results: The average years of experience of the HCPs who participated in the survey was 12.5 years. The level of knowledge of the doctors and the nurses about the indication of catheter insertion was similar, whereas the level of knowledge about CAUTI prevention was higher among the doctors. However, none of the participants could fully describe how to prevent CAUTI. Conclusions: The level of knowledge of CAUTI preventive measures among the participants was insufficient. To effectively preventing CAUTI, there is a need to change HCPs’ perspective on this issue, which can be achieved through training, and advantage current technologies.

Comedication with corticosteroids and nonsteroidal antiphlogistics does not affect PD-L1 expression in non-small cell lung cancer.

BackgroundProgrammed death-ligand 1 (PD-L1) expression is a standard predictor in the selection of immunotherapy for locally advanced/advanced non-small cell lung cancer (NSCLC). However, comedication with corticosteroids or non-steroidal anti-inflammatory drugs (NSAIDs) may influence the effectiveness of this treatment as documented in several previous studies. Due to certain molecular linkages between PD-L1 and corticosteroids or NSAIDs, we therefore addressed the question of whether there is a relationship between PD-L1 expression in NSCLC and the use of this comedication.MethodsThis is a retrospective study using the Czech tumor registry LUng CAncer focuS (LUCAS), from which patient data were drawn. Independence of two categorical parameters was tested by Pearson’s chi-square test.ResultsIn our group of 1,148 patients, we observed no significant relationship between PD-L1 expression and the use of corticosteroids or NSAIDs.ConclusionsAccording to our data, treatment with corticosteroids or NSAIDs during biopsy does not affect the expression of PD-L1 and it is therefore not necessary to take this treatment into account in this regard.

Morphological Characteristics and Nutritional Quality of Mutant Benggala Grass (Panicum maximum cv Purple Guinea) Generation M1V3

This study aims to observe morphological characters and genetic parameters of Benggala grass and its nutritional quality. Research on morphological characters was conducted at the Regional Technical Executive Unit (UPTD) of Tenjo dry land, using a randomized block design with 5 replications. The parents of the M1V3 mutant were from Benggala grass cv Purple guinea from the germplasm collection of the Indonesian Research Institute of Animal Production (Balitnak). The M1V3 plants were derived from 2400 M1V1 plants sorted to 250 M1V2 plants, and finally to 29 M1V3 plants. There were 29 plants planted on the experimental field using pols and control plants. Morphological observations and forage harvests were conducted at harvest/cutting ages 2 and 3 months after planting. Each harvest age was analyzed respectively. Forage quality observations were carried out at the RIAP Laboratory. The results showed that at the ages of 2 and 3 months, almost all characters were significantly different (p<0.05) in each genotype and several mutants of Benggala grass were higher than controls. Broad categorical genetic parameters were found in the characters of fresh weight, fresh weight of leaves, and fresh weight of tillers. Nutritional quality shows that irradiated plants have good nutritional quality because the value of crude protein and digestibility increases, while the value of crude fiber decreases compared to the control plant. In conclusion, the characterization of the M1V3 generation showed high-yielding mutants that were higher than the control and this M1V3 generation could be used as candidates for high-yielding varieties of Benggala grass.

Comparison of Diagnostic Ability Between Wide-Field Swept-Source Optical Coherence Tomography Imaging Maps and Heidelberg Retina Tomograph 3 Optic Nerve Head Assessment to Discriminate Glaucomatous and Non-glaucomatous Eyes.

BackgroundIn this study, we aimed to determine the diagnostic performance of optic nerve head (ONH), macular, and circumpapillary retinal nerve fiber layer (cpRNFL) thickness measurements of wide-field maps (12 × 9 mm) using swept-source optical coherence tomography (SS-OCT) compared to measurements of the ONH and RNFL parameters measured by Heidelberg Retina Tomograph (HRT3).MethodologyThis case-control study included 39 eyes of 39 glaucoma patients and 36 eyes of 36 normal subjects (control group). All participants underwent standard automated perimetry (SAP) as well as structural measurements by SS-OCT (DRI-OCT, Triton; Topcon Inc., Tokyo, Japan) and HRT3 (Heidelberg Engineering, Heidelberg, Germany). The abilities of the continuous parameters to discriminate between glaucoma and control groups were assessed using areas under the receiver operating characteristic curves (AUCs). To assess the glaucoma diagnostic abilities of each of the categorical variables, sensitivity, specificity, positive predictive value, and negative predictive value were tested.ResultsThe highest sensitivities were achieved by the DRI-OCT categorical parameters of Superpixel-200 map and cpRNFL (12 sectors) thickness analysis. The best performing HRT3 continuous parameter was rim volume (AUC = 0.829, 95% confidence interval (CI) = 0.735-0.922), and the best continuous parameter for DRI-OCT wide-field was vertical cdr (AUC = 0.883, 95% CI = 0.805-0.951), followed by total cpRNFL thickness (AUC = 0.862, 95% CI = 0.774-0.951). AUCs for disc area, rim area, linear cdr, and RNFL thickness were not significantly different between the two technologies. Using either the most or the least specific criteria, SuperPixel-200 map always showed the highest sensitivity among the categorical parameters of both technologies (82.1% and 89.7%, respectively). The highest sensitivity among HRT3 classification parameters was shown by MRA and GPS classification algorithms.ConclusionsBoth wide-field DRI-OCT maps and HRT3 showed good diagnostic performance in discriminating glaucoma. Although DRI-OCT thickness values and normative diagnostic classification showed the best performance, more studies are required to determine the clinical role of wide-field DRI-OCT scan in glaucoma diagnosis.

Стратегические императивы инвестиционного вектора экономического развития Северо-Кавказского федерального округа

The strategic imperatives of the investment vector of development of the economic space of the North Caucasus Federal District, correlated through the analysis and evaluation of key indicators of the investment attractiveness of regional subsystems carried out in the framework of this study, allowed the authors to clarify some definitions used to establish the categorical parameters and tools that underlie the formation of its investment development paradigm. The investment risks and investment opportunities studied in the framework of the study served to form views on the strategic priorities for developing the investment potential of the North Caucasus Federal District.

Admission and Mortality Patterns in Intensive Care Delivery at Enugu State University of Science and Technology Teaching Hospital: A Three-Year Retrospective Study.

BackgroundThe intensive care unit (ICU) provides critical care to high-risk patients to prevent morbidity and mortality. This requires closer monitoring and better management than the care provided to patients in normal admission wards and non-critical care units. Mortality rates in ICUs in developing countries are remarkably high compared to rates in more developed countries. Evaluating outcomes of treatment is a way to improve the quality of care. Therefore, this study was conducted to review the pattern of admission and outcome in the ICU of Enugu State University of Science and Technology Teaching Hospital (ESUT-TH).MethodologyThis study was a three-year retrospective, descriptive review of all patients admitted to the ICU of ESUT-TH between January 1, 2019, and December 21, 2021. Data were collected from admissions and discharge registers of the ICU ward. Data were analyzed and expressed as frequencies and percentages. Categorical parameters were compared using the chi-squared test, and the significance level was set at p < 0.05.ResultsA total of 179 patients were admitted in the three-year period. Of them, 49.2% were postoperative patients while 21.2% were admitted from the accident and emergency unit. There were a total of 74 (41.3%) medical cases and 81 (45.3%) surgical cases, and the rest were unspecified. Among surgical cases, 19% were from the general surgery department followed by obstetrics and gynecology (18.4%) and neurosurgery (16.8%). Cerebrovascular accidents and traumatic brain injury were the most common specific diagnoses recorded among ICU admitted patients. The most common reason for admission was close monitoring of high-risk patients. The mortality rate during the studied period was 34.1%, and this was significantly associated with patient age and type of illness at presentation (p < 0.05). Stratified by year of admission, the highest rate of mortality was noted in the year 2020 (46.7%).ConclusionThere is a high level of mortality among ICU admissions in our center. This calls for the improvement of intensive care delivery in the healthcare facility, including training and retraining of manpower and provision of essential facilities for high-quality healthcare delivery.

Data assimilation and agent-based modelling: towards the incorporation of categorical agent parameters.

This paper explores the use of a particle filter-a data assimilation method-to incorporate real-time data into an agent-based model. We apply the method to a simulation of real pedestrians moving through the concourse of Grand Central Terminal in New York City (USA). The results show that the particle filter does not perform well due to (i) the unpredictable behaviour of some pedestrians and (ii) because the filter does not optimise the categorical agent parameters that are characteristic of this type of model. This problem only arises because the experiments use real-world pedestrian movement data, rather than simulated, hypothetical data, as is more common. We point to a potential solution that involves resampling some of the variables in a particle, such as the locations of the agents in space, but keeps other variables such as the agents' choice of destination. This research illustrates the importance of including real-world data and provides a proof of concept for the application of an improved particle filter to an agent-based model. The obstacles and solutions discussed have important implications for future work that is focused on building large-scale real-time agent-based models.

Right Ventricular Dysfunction Is Associated With Increased Mortality in Patients Requiring Venovenous Extracorporeal Membrane Oxygenation: Issues With the Method.

To the Editor: We read with interest the article published by Maharaj et al.1 The authors’ aim was to investigate the correlation between echocardiographic parameters and survival in patients supported by venovenous extracorporeal membrane oxygenation (VV-ECMO). The authors retrospectively collected clinical and echocardiographic data from 17 patients over 1 year period. The echocardiograms were a mixture of transthoracic (TTE) and transesophageal (TEE) scans. Visual assessment and right ventricle (RV) fractional area change (FAC) were used as the parameters for RV systolic function as measured by two independent blinded experts, and an average was used for statistical analysis. In patients who did not survive, significant RV dysfunction by visual assessment was more prevalent in nonsurvivors. In addition, median value for FAC in nonsurvivors was significantly lower (11.3% [10.3–15] vs. 30.1% [27.6–31.4], respectively). RV FAC is performed by tracing the endocardial border area of the RV in end systole (ESA) and end diastole (EDA), and it is calculated as EDA − ESA/EDA.2 This method renders FAC open to intra- and interobserver variabilities. A previous study demonstrated FAC to exhibit limited and nonstatistically significant intraobserver (r, 0.56; p = 0.06) and interobserver (r, 0.46; p = 0.16) agreements.2 In addition, mean intra- and interobserver differences were high (mean, 1.86%; 95% CI, −9.25% to −12.96%; and mean, 4.00%; 95% CI, −7.72% to −15.72%, respectively). FAC variability was worst compared with other RV systolic function parameters (e.g., Tricuspid annular plane systolic excursion and velocity). Where FAC is used for RV systolic function assessment, intra- and interobserver variabilities should be assessed and cited providing a guide to results reliability. The authors used a mixture of TEE and TTE to obtain FAC. The two modalities were considered comparable, and thus, values from both modalities were incorporated in the FAC comparison. A recent study compared TTE and TEE in the assessment of RV function using the same parameters in 100 patients undergoing cardiac surgery.3 The TTE and TEE were performed in close temporal proximity under the same loading conditions. The study demonstrated that RV parameters had fair agreement between modalities but not identical. FAC comparison demonstrated correlation concordance coefficient between TTE and TEE of 0.31 (95% CI, 0.12–0.48), suggesting limited agreement and that FAC results are not interchangeable between the two modalities. This result casts a shadow on the feasibility of incorporating FAC from TTE and TEE in the same statistical comparison. Association between a continuous independent parameter (e.g., RV FAC) and categorical dependent parameter (e.g., mortality) requires in-depth statistical analysis. Logistic regression is the most commonly statistical method used to investigate such association.4 A multivariate model is constructed to incorporate all likely and significantly different independent parameters to investigate which parameters predict outcome. Furthermore, receiver operator curve (ROC) analysis is usually performed to establish sensitivity and specificity of the independent parameter in predicting the dependent parameter.5 Without such analysis, association between FAC and mortality could not be convincingly established. Fractional area change is a method of RV systolic function assessment with high observer variability. FAC is not interchangeable between TTE and TEE. Further statistical analysis is required to establish association between RV FAC and outcome.

A generic battery-cycling optimization framework with learned sampling and early stopping strategies

SummaryBattery optimization is challenging due to the huge cost and time required to evaluate different configurations in experiments or simulations. Optimizing the cycling performance is especially costly since battery cycling is extremely time consuming. Here, we introduce an optimization framework building on recent advances in machine learning, which optimizes battery parameters efficiently to significantly reduce the total cycling time. It consists of a pruner and a sampler. The pruner, using the Asynchronous Successive Halving Algorithm and Hyperband, stops unpromising cycling batteries to save the budget for further exploration. The sampler, using Tree of Parzen Estimators, predicts the next promising configurations based on query history. The framework can deal with categorical, discrete, and continuous parameters and can run in an asynchronously parallel way to allow multiple simultaneous cycling cells. We demonstrated the performance by a parameter-fitting problem for calendar aging. Our framework can foster both simulations and experiments in the battery field.

The comparison of postoperative analgesic efficacy of three-in-one-block versus fascia-iliaca blocks following femoral fracture orthopedics surgical procedures under spinal anesthesia, Gondar, Ethiopia, 2021: A prospective cohort study.

IntroductionFemoral bone fracture is the predominant, lower limb orthopedic surgery that is associated with severe acute and persistent chronic pain that needs better postoperative pain management. Untreated postoperative pain results inability to do physiotherapy resulting in stiffens of joints and immobility. This study aimed to compare the postoperative analgesic efficacy of three-in-one-block versus fascia iliaca block in patients who underwent surgically treated femoral fractured patients under spinal anesthesia. MethodsA prospective cohort study was conducted on 110 elective surgically treated femoral fractured orthopedic patients from January to October 2021. Data were entered into epi-data 4.4.2 and imported into a statistical package of social science version 22 for analysis. Shapiro–Wilk normality test was used to check the normality of the data and normally distributed data were analyzed using Student’s independent t-test, whereas non-normally distributed variables were analyzed with Mann–Whitney U-test. The comparisons of categorical parameters were analyzed using the chi-square test and Fisher’s exact test. Finally p-value < 0.05 was declared to be statistically significant.ResultThe median and interquartile range of the postoperative numerical rating scale at rest and on movement was significantly less in three-in-one-block (3IN1B) as compared with fascia-iliaca block (FICB). But at 30 min no significantly different between the two pain management modalities. Moreover, the meantime to seek the first request of analgesia was significantly prolonged in 3IN1B compared with FICB. Regarding the total analgesic consumption, the mean total tramadol consumption was 97. 27 ± 53. 07 and 180 ± 72.96 (p < 0.001) and Diclofenac 53.18 ± 29.28 and 72 ± 43.54 (p < 0. 001) in 3IN1 and FICB, respectively. ConclusionThe present study concludes that three-in-one-block provides more effective analgesia, reduced postoperative analgesic requirements, and prolonged first analgesics requests compared with fascia iliaca block, and Landmark technique fascia-iliaca block (FICB) is an alternative pain management modality in a resource-limited setting.

Frequency-Based Representation of Massive Alerts and Combination of Indicators by Heterogeneous Intrusion Detection Systems for Anomaly Detection.

Although the application of a wide range of sensors has been generalized through the development of technology, the processing of massive alerts generated through data analysis and monitoring remains a challenge. This problem is also found in cyber security because the intrusion detection system (IDS) produces a tremendous number of alerts. Massive alerts not only significantly increase resources for analysis, but also make it difficult to analyze the overall situation of the system. In order to handle massive alerts, we propose using an indicator as a frequency-based representation. The proposed indicator is generated from categorical parameters of alerts that occur within a unit time utilizing frequency and is used for situational awareness with machine learning to detect whether there is a threat or not. The advantage of using indicators is that they can determine the situation for a period without analyzing individual alerts, which helps security experts to recognize the situation in the system and focus on targets that require in-depth analysis. In addition, the conversion from the categorical parameters which is highly related to analysis to numeric parameter allows for applying machine learning. For performance evaluation, we collect data from an HAI testbed similar to real critical infrastructure and conduct experiments using indicators and XGBoost, a classification machine learning algorithm against five famous vulnerability attacks. Consequently, we show that the proposed method can detect attacks with more than 90 percent accuracy, and the performance is enhanced using heterogeneous intrusion detection systems.

Electrocardiographic, echocardiographic and lipid parameters in predicting obstructive coronary artery disease in patients with non-ST elevation acute coronary syndrome

Aim. To assess the predictive potential of electrocardiographic (ECG), echocardiographic, and lipid parameters for predicting obstructive coronary artery disease (oCAD) in patients with non-ST-elevation acute coronary syndrome (NSTE-ACS) prior to invasive coronary angiography (CA).Material and methods. This prospective observational cohort study included 525 patients with NSTE-ACS with a median age of 62 years who underwent invasive coronary angiography. Two groups were distinguished, the first of which consisted of 351 (67%) patients with oCAD (stenosis 50%), and the second — 174 (33%) without oCAD (&lt;50%). Clinical and functional status of patients before CAG was assessed by 40 indicators. Mann-Whitney, Fisher, chi-squared, univariate logistic regression (LR) methods were used for data processing and analysis, while miltivariate LR (MLR), gradient boosting (XGBoost) and artificial neural networks (ANN) were used to develop predictive models. The quality of the models was assessed using 4 following metrics: area under the ROC curve (AUC), sensitivity (Se), specificity (Sp), and accuracy (Ac).Results. A comprehensive analysis of ECG, echocardiography and lipid profile parameters made it possible to identify factors that had linear and non-linear association with oCAD. LR were used to determine their weight coefficients and threshold values with the highest predictive potential. The quality metrics of the best predictive algorithm based on MLR were 0,81 for AUC, 0,74 for Sp and Ac, and 0,75 for Se. The predictors of this model were 4 categorical parameters (left ventricular (LV) ejection fraction of 42-60%, global LV longitudinal systolic strain &lt;19%, low-density lipoprotein cholesterol &gt;3,5 mmol/l, age &gt;55 years in men and &gt;65 years for women).Conclusion. The prognostic model developed on the basis of MLR made it possible to verify oCAD with high accuracy in patients with NSTE-ACS before invasive CA. Models based on XGBoost and ANN had less predictive value.

Are facial, maxillary arch and incisor dimensions related in patients with a unilaterally impacted palatal canine? A prospective investigation

Abstract Objective To identify and determine the relationship between facial, maxillary arch and incisor dimensions of patients presenting with a unilaterally impacted palatal canine. Methods Prospective referrals over one calendar year of patients identified with a unilaterally impacted palatal canine were compared with prospectively recruited control subjects. Canine location was determined radiographically and re-confirmed two weeks later. Facial, maxillary arch and incisor dimensions were assessed. Intra-examiner reproducibility was re-assessed using randomly selected images (20%, n = 40). General linear models were applied for inter-group comparisons incorporating Bonferroni adjustment with categorical parameters assessed using Fisher’s exact test (SAS®, Version 9.4, SAS.com). Inter-class correlation coefficients were calculated for relationships between the variables. Results Fifty-four patients (37 females; 17 males) presenting with a unilaterally impacted palatal canine [mean age 14.5 (SD 1.7) years] and 54 control subjects (37 females, 17 males) [mean age 14.3 (SD 2.2) years] were recruited. Measurement error was small for landmark data (0.58 mm), palatal depth (0.09 mm), palatal area (0.42 mm²) and Bolton ratio (0.14%). For facial, maxillary arch and tooth shape assessments, landmark error was 0.05 mm with complete agreement for classification. The mean nasal basal width was smaller in the unilaterally impacted palatal canine group compared with the control group (P &lt; 0.0001) but face shape distribution and face ratio were similar (both P &gt; 0.05). The mean anterior Bolton ratio was larger in the impacted canine group (P &lt; 0.01). No differences were recorded between groups for other parameters (all P &gt; 0.05). No positive correlations were identified between the variables. Conclusions Patients with a unilaterally impacted palatal canine had a narrower mean nasal basal width and a larger mean anterior Bolton ratio compared to a control group but the clinical significance of the differences was considered minor. Facial, maxillary arch and incisor dimensions were neither individually nor collectively correlated with a palatal canine which may lend support to a genetic aetiology.

Laboratory Parameters Associated With Inflammation Do Not Affect PD-L1 Expression in Non-small Cell Lung Cancer.

Due to some interconnectedness at the molecular level, this study assessed the possible influence of laboratory parameters associated with systemic inflammatory environment on programmed death-ligand 1 (PD-L1) expression in non-small cell lung carcinoma (NSCLC). We assessed effects of c-reactive protein (CRP), albumin, haemoglobin, neutrophil, and lymphocyte levels on PD-L1 expression in NSCLC. Patient data were obtained retrospectively from LUCAS, the Czech registry of patients with lung carcinomas. Correlations of two continuous parameters (PD-L1 expression and laboratory parameters) were analysed by correlation coefficient. Differences in continuous parameters between two or more groups were tested by Mann-Whitney or Kruskal-Wallis tests. Independence of two categorical parameters was tested by chi-square test. We demonstrated no influence of the investigated laboratory parameters on PD-L1 expression in NSCLC, either in continuous or categorical division of variables. Inflammatory laboratory parameters at time of NSCLC diagnosis are unlikely to affect the determination of PD-L1 expression.

A novel methodology for perception-based portfolio management.

Selecting and investing in stock market with right proportions is one of the major challenges. Majority of the investors end up losing their invested equity capital due to uncertainty in the market. The present study provides a novel framework for novice investors to construct portfolio based on multicriteria decision making techniques under fuzzy environment. The scores obtained from these techniques were used to introduce two non-dimensional parameters for categorization of risky and non-risky assets. Three perceptions portfolios were constructed based on the proposed non-dimensional parameters along with fractional lion clustering algorithm. In order to demonstrate the proposed framework, an illustrative application is included in equity portfolio selection. The returns and risks of these perception based portfolios are compared to major Index funds for validating the efficiency and are found to overpower the Index funds with significant margins by maintaining the risk comparable to Index funds. Further, Markowitz based efficient frontier is plotted for better understanding of optimal returns and risk for perception based investment.

Reliability of preoperative MRI findings in patients with lumbar spinal stenosis

BackgroundMagnetic Resonance Imaging (MRI) is an important tool in preoperative evaluation of patients with lumbar spinal stenosis (LSS). Reported reliability of various MRI findings in LSS varies from fair to excellent. There are inconsistencies in the evaluated parameters and the methodology of the studies. The purpose of this study was to evaluate the reliability of the preoperative MRI findings in patients with LSS between musculoskeletal radiologists and orthopaedic spine surgeons, using established evaluation methods and imaging data from a prospective trial.MethodsConsecutive lumbar MRI examinations of candidates for surgical treatment of LSS from the Norwegian Spinal Stenosis and Degenerative Spondylolisthesis (NORDSTEN) study were independently evaluated by two musculoskeletal radiologists and two orthopaedic spine surgeons. The observers had a range of experience between six and 13 years and rated five categorical parameters (foraminal and central canal stenosis, facet joint osteoarthritis, redundant nerve roots and intraspinal synovial cysts) and one continuous parameter (dural sac cross-sectional area). All parameters were re-rated after 6 weeks by all the observers. Inter- and intraobserver agreement was assessed by Gwet’s agreement coefficient (AC1) for categorical parameters and Intraclass Correlation Coefficient (ICC) for the dural sac cross-sectional area.ResultsMRI examinations of 102 patients (mean age 66 ± 8 years, 53 men) were evaluated. The overall interobserver agreement was substantial or almost perfect for all categorical parameters (AC1 range 0.67 to 0.98), except for facet joint osteoarthritis, where the agreement was moderate (AC1 0.39). For the dural sac cross-sectional area, the overall interobserver agreement was good or excellent (ICC range 0.86 to 0.96). The intraobserver agreement was substantial or almost perfect/ excellent for all parameters (AC1 range 0.63 to 1.0 and ICC range 0.93 to 1.0).ConclusionsThere is high inter- and intraobserver agreement between radiologists and spine surgeons for preoperative MRI findings of LSS. However, the interobserver agreement is not optimal for evaluation of facet joint osteoarthritis.Trial registrationwww.ClinicalTrials.gov identifier: NCT02007083, registered December 2013.

Stable Neural Population Dynamics in the Regression Subspace for Continuous and Categorical Parameters in the Monkey Orbitofrontal Cortex and Hippocampus

Stable Neural Population Dynamics in the Regression Subspace for Continuous and Categorical Parameters in the Monkey Orbitofrontal Cortex and Hippocampus