Professional Ethics Relationship with Patient’s Rights Charter Observance among Nurses and Midwives

Introduction: Respect for patients’ rights and observance of professional ethics standards improves medical services that will have an essential role in promoting patients’ health. Objective: This study aimed to determine the relationship between awareness of patient’s rights charter and professional ethics with patient’s rights charter observance. Materials and Methods: This analytical correlational study was performed on 285 staff members (196 nurses and 85 midwives) working in 2 hospitals affiliated to Alborz University of Medical Sciences, Iran, and 2 social security hospitals. They were selected using a stratified random sampling method. The study data were collected using the sociodemographic characteristics questionnaire, awareness and observance of the patient’s rights, and professional ethics charter questionnaires. Descriptive statistics and inferential statistics, including the independent t-test, Pearson correlation, Chi-square tests, and multivariate linear regression, were used for data analysis. Results: The Mean±SD ages of nurses and midwives were 36.2±8.3 and 37.5±7.9 years, respectively. The results also showed an association of professional ethics and awareness of patient’s rights charter with patient’s rights charter observance in both nurses (P=0.0001) and midwives (P=0.0001). Based on multivariate linear regression analysis, there were relationships between gender (B=-0.3; 95%CI; -2.0, 2.0; P=0.000), work experience (B=-0.6; 95%CI; -4.0, 3.0; P=0.000), marital and employment status (B=-3.2; 95%CI; -6.0, -0.0; P=0.045), in nurses and between job position (B=9.5; 95%CI; 5.4, 13.5; P=0.000), interest to work (B=-7.9; 95%CI; -11.5, -4.3; P=0.000), and income status (B=6.3; 95%CI; 3.3, 9.2; P=0.000), in midwives with Observance of the Charter of Patient Rights. Conclusion: It is possible to improve compliance with the charter of patient’s rights and its dimensions by strengthening the knowledge of nurses and midwives in this area and their professional ethics, which results in patient satisfaction in this area.

Correlation between FA and ADC, number and length of the periprostatic neurovascular fibers

Purpose: Our aim was to explore the relation between FA and ADC, number and length of the periprostatic neurovascular fibers (PNF) by means of 1.5 T Diffusion Tensor Imaging (DTI) imaging through a multivariate linear regression analysis model. Methods: For this retrospective study, 56 patients (mean age 63.5 years), who underwent 1.5-T prostate MRI, including DTI, were enrolled between October 2014 and December 2018. Multivariate regression analysis was performed to evaluate the statistically significant correlation between FA values (dependent variable) and ADC, the number and the length of PNF (independent variables), if p-value <0.05. A value of 0.5 indicated poor agreement; 0.5–0.75, moderate agreement; 0.75–0.9, good agreement; 0.61–0.80, good agreement; and 0.9–1.00, excellent agreement. Results: The overall fit of the multivariate regression model was excellent, with R2 value of 0.9445 ( R2 adjusted 0.9412; p < 0.0001). Multivariate linear regression analysis showed a statistically significant correlation ( p < 0.05) for all the three independent variables. The r partial value was −0.9612 for ADC values ( p < 0.0001), suggesting a strong negative correlation, 0.4317 for the number of fiber tracts ( p < 0.001), suggesting a moderate positive correlation, and −0.306 for the length of the fiber tracts ( p < 0.05), suggesting a weak negative correlation. Conclusions: Our multivariate linear regression model has demonstrated a statistically significant correlation between FA values of PNF with other DTI parameters, in particular with ADC.

The Health Determinants of Accessibility to Clubfoot Treatment in LMICs: A Global Exploration of Barriers and Solutions

Background: Clubfoot or Congenital Talipes Equinovarus (CTEV) treatment in newborn infants involves simple, non-invasive manipulation and is primarily managed non-surgically if identified early. In low- and middle-income countries (LMICs), less than 15% of patients with CTEV access treatment. This cross-sectional questionnaire study conducted descriptive and regression analysis of institutional reasons for CTEV management in LMICs. Methods: A cross-sectional study was undertaken of 1,489 medical institutions in 62 LMICs. Data were evaluated from the “World Health Organization Situation Analysis tool” database. We analyzed characteristics of institutions that manage and did not manage CTEV. With the use of a multivariate linear regression model, we identified a set of factors linked to referral for non-management of CTEV. Results: A total of 72.7% (1,083/1,395) of institutions surveyed did not manage CTEV. The most common reason cited for not managing CTEV was a lack of sufficient skills, 92.1% (668/725, P<0.001). A total of 39.4% (286/725) of institutions also cited a lack of functioning equipment as a reason. Multivariate linear regression analysis showed lack of training, lack of supplies, and lack of functioning equipment were most closely related to non-management of CTEV. Conclusion and Global Health Implications: We identified that failure to manage CTEV may result from a lack of skills and medical equipment. Increasing the capacity of sustainable training programs may reduce the presently available skill deficit in treating CTEV in LMICs and provide improved health outcomes for those with CTEV. While considerable progress has been made in building capacity for the treatment and management of CTEV in LMICs, structured training programs that support conservative manipulative methods to manage CTEV should be initiated globally. Copyright © 2021 Sheik-Ali et al. Published by Global Health and Education Projects, Inc. This is an open-access article distributed under the terms of the Creative Commons Attribution License CC BY 4.0.

Predicting COD and BOD Parameters of Greywater Using Multivariate Linear Regression

Greywater reuse furthermore, reusing can be an incredible method to get non-consumable water. Since it contains broke down pollutions, greywater can’t be utilized straightforwardly. As an outcome, it is critical to decide the nature of water prior to utilizing it. Body estimations require five days to finish, while COD estimations require only a couple of hours. Not exclusively improve models for evaluating water quality are required; however, a more coordinated methodology is additionally getting more normal. Most of these models require a wide scope of information that isn’t in every case promptly available, making it a costly and tedious activity. Because of different issues in the enlistment with estimation included in water quality boundaries like BOD as well as COD, the principal objective of this investigation is to track down the best multivariate direct relapse models for foreseeing complex water quality outcomes. The code was written in Python for multi-variable information sources, and a Linear Regression Model was created. The projected COD versus estimated COD chart shows that the noticed and expected qualities are practically the same. The R-squared worth was 0.9973. A plot of extended BOD as an element of COD is likewise remembered for the outcome.

498 Oxidative stress and left ventricular performance in patients according to different glycometabolic phenotypes

Recent studies demonstrated that in normoglucose-tolerant subjects (NGT), 1-h post load plasma glucose value ≥155 mg/dL, during OGTT, identifies a worse cardio-metabolic risk profile with increased risk for Type 2 Diabetes Mellitus (T2DM). T2DM patients present increased oxidative stress, due to high blood glucose levels, which plays a central role in the development of CV events. The aim of our study was to evaluate the correlation between oxidative stress and subclinical myocardial damage, assessed with speckle tracking echocardiography, in NGT patients with 1-h post load ≥155 mg/dL vs. NGT &lt; 155 subjects, impaired glucose tolerance (IGT) and T2DM patients. We enrolled 100 Caucasian patients (61 M, 39 W, mean age 61.4 ± 10.7) afferent to CATAMERI study. Main exclusion criteria were CV complications, history of malignant or chronic respiratory disease, alcohol, drug influencing glucose metabolism or smoking abuse. All subjects underwent clinical and laboratory evaluation, OGTT and HOMA-IR. The serum values of the markers of oxidative stress (8-isoprostane and NOX-2) were assessed with ELISA sandwich. Statistical analysis was performed with ANOVA test, linear correlation analysis and stepwise multivariate linear regression model. According to OGTT results, subjects were divided into 4 groups: NGT &lt; 155 (n = 30), NGT ≥ 155 (n = 24), IGT (n = 28), T2DM (n = 18). Serum levels of 8-isoprostane and NOX-2 were significantly increased (P &lt; 0.0001) in NGT ≥ 155 compared to NGT &lt; 155 group, but similar with IGT, indicating an increase in oxidative stress with the worsening of the metabolic status. The left global systolic function, evaluated as myocardial deformation and global longitudinal strain (GLS), appeared progressively lower proceeding from the NGT &lt; 155 group to the T2DM group (P &lt; 0.0001). Moreover, for similar values of ejection fraction (EF), NGT ≥ 155 subjects presented reduced GLS compared to NGT &lt; 155 (P = 0.001), but similar to IGT patients. The linear correlation analysis showed that endo/epi ratio was significantly and inversely correlated with 1 h post load glycaemia (r = −0.632, P &lt; 0.0001), NOX-2 (r = −0.638, P &lt; 0.0001), 8-isoprostane (r = −0.508, P &lt; 0.0001); GLS was inversely correlated with 1 h post load glycaemia (r = −0.734, P &lt; 0.0001) and directly and significantly correlated with 8-isoprostane (r = 0.564, P &lt; 0.0001), NOX-2 (r = 0.625, P &lt; 0.0001). From stepwise multivariate linear regression model, NOX-2 resulted the major predictor of endo/epi ratio, justifying 40.7% of its variation. 1-h post load glycaemia was the second predictor of endo/epi ratio justifying another 9.2% of its variation. Similarly 1-h post load glycaemia was the strongest predictor of the GLS, explaining 53.9% of its variation. Our study demonstrated that NGT ≥ 155 subjects present functional alterations of myocardial contractile fibres, compared to NGT &lt; 155 subjects, but similar to IGT, and these alterations are correlated with oxidative stress. Moreover, GLS is able to identify early alterations in the contractility of subendocardial longitudinal fibres long before the alteration of EF. This data have a central role in ongoing research on the association between hyperglycaemia at 1-h post load and CV risk.

Mapping Computations in Heterogeneous Multicore Systems with Statistical Regression on Program Inputs

A hardware configuration is a set of processors and their frequency levels in a multicore heterogeneous system. This article presents a compiler-based technique to match functions with hardware configurations. Such a technique consists of using multivariate linear regression to associate function arguments with particular hardware configurations. By showing that this classification space tends to be convex in practice, this article demonstrates that linear regression is not only an efficient tool to map computations to heterogeneous hardware, but also an effective one. To demonstrate the viability of multivariate linear regression as a way to perform adaptive compilation for heterogeneous architectures, we have implemented our ideas onto the Soot Java bytecode analyzer. Code that we produce can predict the best configuration for a large class of Java and Scala benchmarks running on an Odroid XU4 big.LITTLE board; hence, outperforming prior techniques such as ARM’s GTS and CHOAMP, a recently released static program scheduler.