Intercorrelation Coefficients Research Articles

Transvaginal three-dimensional ultrasound assessment of embryonic genital tubercle at 8-10+6weeks of gestation.

To assess embryonic genital tubercle using transvaginal three-dimensional (3D) ultrasound at 8-10+6weeks of gestation. One-hundred and two transvaginal 3D ultrasound scans were performed for first-trimester dating at 8-10+6weeks of gestation. The genital tubercle angle (GTA) and genital tubercle length (GTL) were measured with a mid-sagittal view of the embryo using the 3D ultrasound multiplanar mode. Intra- and inter-observer agreements regarding GTA and GTL were also assessed with Bland-Altman plots and intra- and inter-correlation coefficients. There were no significant differences in GTA between male and female embryos at 8, 9, 10weeks, or 8-10+6weeks of gestation, respectively. There were also no significant differences in GTL between male and female embryos at 8, 9, 10weeks, or 8-10+6weeks of gestation, respectively. However, GTL increased linearly with advancing gestation (r=0.8276, p<0.00001). Mean GTL (SD) values at 8, 9, and 10weeks were 0.833 mm (0.274), 1.623 mm (0.262), and 2.152 mm (0.420), respectively (p<0.001). Intra- and inter-reproducibilities of GTA and GTL were excellent. The intra- and inter-correlation coefficients of GTA and GTL were 0.964 and 0.995, and 0.996 and 0.9933, respectively. The genital tubercle could be identified using transvaginal 3D ultrasound at 8-10+6weeks of gestation. However, sex differentiation could not be performed at this age. The genital tubercle linearly developed with advancing gestation during the mid-first trimester of pregnancy.

Virtual unenhanced images derived from dual-energy computed tomography for assessing bone mineral density and detecting osteoporosis.

The early detection and treatment of osteoporosis can help prevent osteoporosis-related fractures, especially in patients who undergo enhanced computed tomography (CT) scans for disease diagnosis or evaluation of treatment outcomes. Although Hounsfield unit (HU) measurement of the vertebral body has been shown to have a strong positive correlation with bone mineral density (BMD), the contrast media will impact the CT value of the vertebral body and decrease the accuracy. This study is aimed to examine the distinctions in vertebral body CT attenuation measurement on true unenhanced (TUE) and virtual unenhanced (VUE) images generated from triphasic enhanced dual-energy CT (DECT) scans and to determine the feasibility of assessing BMD and detecting osteoporosis on VUE images as compared to quantitative CT (QCT). A total of 235 patients underwent abdominal CT examinations that included unenhanced (with 120 kVp and Smart mA) and triphasic enhanced DECT scans. The BMD and CT attenuation values of the L1-L2 vertebrae were measured on TUE and VUE images reconstructed from the triphasic enhanced CT. The differences and associations between TUE and VUE generated from triphasic enhanced CT were analyzed. The diagnostic performances of HU measurements obtained from TUE and VUE images were evaluated using receiver operating characteristic curve. The BMD and HU measurements of the vertebrae showed good interobserver repeatability on both TUE and VUE images (all intercorrelation coefficients >0.92). The CT attenuation values of L1 and L2 and their average value showed no statistically significant difference among the triphasic VUE images (F=0.121, F=0.061, F=0.090; all P values >0.05) but were significantly lower than those obtained from the TUE images. HU measurements in both the TUE and triphasic VUE images, along with the reference BMD derived from QCT, demonstrated a strong positive correlation (rTUE =0.981, rVUEa =0.966, rVUEv =0.962, rVUEd =0.964; all P values <0.05), with excellent diagnostic performance for the diagnoses of osteoporosis and osteopenia (all areas under curve >0.95). The Bland-Altman scatter plot exhibited good agreement, as the deviations between the reference BMD and the calculated BMD were evenly distributed around 0. Although the attenuation values of the vertebrae on the VUE images were underestimated compared to those on the TUE images, the HU measurement on VUE image was effective in assessing BMD and detecting osteoporosis and osteopenia with good diagnostic performance.

Deep Learning-Based Multiparametric MRI Model for Preoperative T-Stage in Rectal Cancer.

Conventional MRI staging can be challenging in the preoperative assessment of rectal cancer. Deep learning methods based on MRI have shown promise in cancer diagnosis and prognostication. However, the value of deep learning in rectal cancer T-staging is unclear. To develop a deep learning model based on preoperative multiparametric MRI for evaluation of rectal cancer and to investigate its potential to improve T-staging accuracy. Retrospective. After cross-validation, 260 patients (123 with T-stage T1-2 and 134 with T-stage T3-4) with histopathologically confirmed rectal cancer were randomly divided to the training (N = 208) and test sets (N = 52). 3.0 T/Dynamic contrast enhanced (DCE), T2-weighted imaging (T2W), and diffusion-weighted imaging (DWI). The deep learning (DL) model of multiparametric (DCE, T2W, and DWI) convolutional neural network were constructed for evaluating preoperative diagnosis. The pathological findings served as the reference standard for T-stage. For comparison, the single parameter DL-model, a logistic regression model composed of clinical features and subjective assessment of radiologists were used. The receiver operating characteristic curve (ROC) was used to evaluate the models, the Fleiss' kappa for the intercorrelation coefficients, and DeLong test for compare the diagnostic performance of ROCs. P-values less than 0.05 were considered statistically significant. The Area Under Curve (AUC) of the multiparametric DL-model was 0.854, which was significantly higher than the radiologist's assessment (AUC = 0.678), clinical model (AUC = 0.747), and the single parameter DL-models including T2W-model (AUC = 0.735), DWI-model (AUC = 0.759), and DCE-model (AUC = 0.789). In the evaluation of rectal cancer patients, the proposed multiparametric DL-model outperformed the radiologist's assessment, the clinical model as well as the single parameter models. The multiparametric DL-model has the potential to assist clinicians by providing more reliable and precise preoperative T staging diagnosis. 3 TECHNICAL EFFICACY: Stage 2.

İki Bağımlı Korelasyon Katsayısı Karşılaştırma Testlerinin Performansları için Simülasyon Çalışması ve Akut Apandisit Verileri Üzerinde Bir Uygulama

Objective: Although it is frequently encountered in many studies to examine the relationships between different features of the individuals by using correlation coefficient, it is a situation that can be ignored to statistically test whether there is a difference between the correlation coefficients obtained. In this study, it is aimed to compare the performances of statistical tests proposed for the comparison of dependent overlapping correlation coefficients, in terms of their Type I error rates, within the framework of a wide simulation scenario. Material and Methods: The 6 test procedures were compared with a simulation study, conducted at 5 different intercorrelation magnitudes, with 5 different null correlation coefficient magnitudes, at 6 different sample sizes. Results: Pearson and Filon's z (PF) test performed poorly compared to other 5 procedures in most cases. For small intercorrelation magnitudes Steiger's modification of Dunn and Clark's z (SM) test, Meng, Rosenthal, and Rubin's z (MRR) test, Rosenthal, and Rubin's z test, Hittner, May, and Silver's modification of Dunn and Clark's z (HMS) test and ZOU's approach for overlapping correlations (ZA) procedures outperformed PF test and Hendrickson, Stanley, and Hills' modification of Williams't test (HSHM) especially in small to moderate sample sizes. For larger intercorrelation coefficients, HSHM test gave better results in small to moderate sample sizes and ZA procedure maintained its superiority at the 0.7 intercorrelation level. Conclusion: Tests' performances in terms of Type I error are affected from the magnitude of null correlation, magnitude of intercorrelation and sample size, in different ways. It will be helpful to consider these issues when selecting the appropriate statistical test.

Attention-based Deep Learning for the Preoperative Differentiation of Axillary Lymph Node Metastasis in Breast Cancer on DCE-MRI.

Previous studies have explored the potential on radiomics features of primary breast cancer tumor to identify axillary lymph node (ALN) metastasis. However, the value of deep learning (DL) to identify ALN metastasis remains unclear. To investigate the potential of the proposed attention-based DL model for the preoperative differentiation of ALN metastasis in breast cancer on dynamic contrast-enhanced MRI (DCE-MRI). Retrospective. A total of 941 breast cancer patients who underwent DCE-MRI before surgery were included in the training (742 patients), internal test (83 patients), and external test (116 patients) cohorts. A 3.0 T MR scanner, DCE-MRI sequence. A DL model containing a 3D deep residual network (ResNet) architecture and a convolutional block attention module, named RCNet, was proposed for ALN metastasis identification. Three RCNet models were established based on the tumor, ALN, and combined tumor-ALN regions on the images. The performance of these models was compared with ResNet models, radiomics models, the Memorial Sloan-Kettering Cancer Center (MSKCC) model, and three radiologists (W.L., H.S., and F. L.). Dice similarity coefficient for breast tumor and ALN segmentation. Accuracy, sensitivity, specificity, intercorrelation and intracorrelation coefficients, area under the curve (AUC), and Delong test for ALN classification. The optimal RCNet model, that is, RCNet-tumor+ALN , achieved an AUC of 0.907, an accuracy of 0.831, a sensitivity of 0.824, and a specificity of 0.837 in the internal test cohort, as well as an AUC of 0.852, an accuracy of 0.828, a sensitivity of 0.792, and a specificity of 0.853 in the external test cohort. Additionally, with the assistance of RCNet-tumor+ALN , the radiologists' performance was improved (external test cohort, P< 0.05). DCE-MRI-based RCNet model could provide a noninvasive auxiliary tool to identify ALN metastasis preoperatively in breast cancer, which may assist radiologists in conducting more accurate evaluation of ALN status. 3 TECHNICAL EFFICACY: Stage 2.

Comparison of cine cardiac magnetic resonance and echocardiography derived diameters of the aortic root in a large population-based cohort

Transthoracic echocardiography (TTE) and cine cardiac magnetic resonance imaging (CMR) are established imaging methods of the aortic root. We aimed to evaluate the comparability of measurements in TTE and standard cine CMR sequences of the aortic root. Our study included 741 subjects (mean age 63.5 ± 8 years, 43.7% female) from the Hamburg City Health Study (HCHS). Subjects underwent CMR and TTE. Aortic root measurements were performed at the level of the aortic annulus (AoAn), sinus of Valsalva (SoV), and sinotubular junction (STJ) by standard cine CMR in left ventricular long axis and left ventricular outflow tract view. Measurements were performed applying the leading-edge to leading-edge (LL) convention and inner-edge to inner-edge (II) convention in TTE and the II convention in CMR. Inter correlation coefficients (ICCs) demonstrated high inter- and intraobserver reproducibility for CMR and TTE measurements of SoV and STJ (ICCs 0.9–0.98) and moderate reproducibility for AoAn (ICCs 0.68–0.91). CMR measurements of SoV and STJ showed strong agreement with TTE: while correlations were comparable (r = 0.75–0.85) bias was lower with TTE II (bias − 0.1 to − 0.74) versus TTE LL measurements (mean bias − 1.49 to − 2.58 mm). The agreement for AoAn was fair (r = 0.51–0.57) with variable bias (mean bias 0.39–3.9). Standard cine CMR and TTE derived aortic root measurements are reproducible and comparable with higher agreement for TTE II instead of LL measurements. These results support an interchangeable application of TTE and standard CMR for screening of aortic root diseases thereby possibly reducing redundant multimodality imaging.

Body composition in students physical education and sport: cross-sectional pilot study

Purpose: Young people who study physical education and sport are a priori regarded as having proper body structure and body composition. It is widely presumed that young who study physical education at one of several national universities of physical education (East Sarajevo) could be characterized with proper physique and body composition. Aim of the current study was to assess and analyze the body composition of a male students Physical Education and Sport, University East Sarajevo, by bioelectric impedance analysis and determine the significance of inter correlation coefficients.&#x0D; Material and methods: In study the participants consist 30 male students of Faculty of Physical Education and Sport, University of East Sarajevo, the III year of study (Body Height = 182.20 ± 6.89cm; Body Weight = 80.06 ± 8.80kg; Body Mass Index= 24.03 ± 2.58kg/m²).&#x0D; Results: of the study showed that the body composition is within the healthy (allowed) values recommended for this population of students (Body Fat=10.90kg or 13.62%; Body Muscle= 65.74kg or 82.40%; Body Water = 61.54%; Basal metabolic rate = 2045.07kCal; Daily calorie intake = 8436.56 kCal, etc.). Inter correlation coefficients showed inverse and significantly high correlation (p=0.000) between (inter correlation coefficient Fat-Muscle = -0.945), (inter correlation coefficients Fat-Water = -0.963) while direct correlation was achieved between (inter correlation coefficient Muscle-Water = 0.986).&#x0D; Conclusion: The obtained results of the study defined the appropriate body composition of the students, which is a consequence of their adequate physical activity and well-designed curricula at the home faculty. In the parameters of body composition, students of physical education and sports in East Sarajevo had a higher muscle component and lower values ​​of fat component than other students as a result of their somatotype, way of studying, teaching and extracurricular physical activities.

Upregulation of BMI1-suppressor miRNAs (miR-200c, miR-203) during terminal differentiation of colon epithelial cells.

MicroRNAs (miRNAs) are key regulators of stem cell functions, including self-renewal and differentiation. In this study, we aimed to identify miRNAs that are upregulated during terminal differentiation in the human colon epithelium, and elucidate their role in the mechanistic control of stem cell properties. "Bottom-of-the-crypt" (EPCAM+/CD44+/CD66alow) and "top-of-the-crypt" (EPCAM+/CD44neg/CD66ahigh) epithelial cells from 8 primary colon specimens (6 human, 2 murine) were purified by flow cytometry and analyzed for differential expression of 335 miRNAs. The miRNAs displaying the highest upregulation in "top-of-the-crypt" (terminally differentiated) epithelial cells were tested for positive correlation and association with survival outcomes in a colon cancer RNA-seq database (n = 439 patients). The two miRNAs with the strongest "top-of-the-crypt" expression profile were evaluated for capacity to downregulate self-renewal effectors and inhibit in vitro proliferation of colon cancer cells, in vitro organoid formation by normal colon epithelial cells and in vivo tumorigenicity by patient-derived xenografts (PDX). Six miRNAs (miR-200a, miR-200b, miR-200c, miR-203, miR-210, miR-345) were upregulated in "top-of-the-crypt" cells and positively correlated in expression among colon carcinomas. Overexpression of the three miRNAs with the highest inter-correlation coefficients (miR-200a, miR-200b, miR-200c) associated with improved survival. The top two over-expressed miRNAs (miR-200c, miR-203) cooperated synergistically in suppressing expression of BMI1, a key regulator of self-renewal in stem cell populations, and in inhibiting proliferation, organoid-formation and tumorigenicity of colon epithelial cells. In the colon epithelium, terminal differentiation associates with the coordinated upregulation of miR-200c and miR-203, which cooperate to suppress BMI1 and disable the expansion capacity of epithelial cells.

Applications of Mechanical Arm in the Virtual Touch Tissue Imaging Quantification and the Differential Diagnosis of Breast Tumors.

To assess the diagnostic performance of quantitative parameters for virtual touch tissue imaging quantification by the mechanical arm probe, 128 women with 152 breast lesions (90 benign and 62 malignant) were included and maximum elasticity (Vmax), median elasticity (Vmean), maximum elasticity minus minimum (Vmax-min), and minimum elasticity (Vmin) were measured. Intercorrelation coefficients and Bland-Altman plots were used to compare the repeatability and consistency of handheld probe and mechanical arm measurements. Receiver operating characteristic curve was used to evaluate the diagnostic efficiency. The results showed that intercorrelation coefficients were 0.694 to 0.951 by the mechanical arm and 95% limits of agreement were wider than handheld probe. Using 4.36 m/s as cutoff value for Vmax by the mechanical arm, we achieved sensitivity (88.7%) and specificity (90.0%). We concluded that the mechanical arm can reduce the influence of different scanning pressures on the elastic modulus of breast tissue.

Inter-evaluator and Intra-evaluator Reliability of a Software Program Used to Extract Kinematic Variables Obtained by an Extremity-Mounted Inertial Measurement Unit System in Sound Horses at the Trot Under Soft and Hard Ground Conditions and Treadmill Exercise.

Objective: To assess the inter-evaluator and intra-evaluator reliability of a software program used to extract kinematic variables by a commercially available extremity-mounted inertial measurement unit system in sound horses at the trot under soft and hard ground conditions and treadmill exercise.Animals: Thirty adult, sound and healthy French Montagne stallions.Procedures: Data collection was performed with six IMUs strapped to the distal, metacarpal, metatarsal and tibial regions of every horse. Per surface (treadmill, soft and hard ground) 10 stallions were trotted three times. Prior to the analysis done by six evaluators (three experienced, three inexperienced) the data was blinded and copied three times. For every analysis a minimum of five strides had to be selected. To assess the intra- and inter-evaluator reliability a selection of gait variables was used to calculate intra and inter correlation coefficients (ICCs) as well as variance partitioning coefficients (VPCs).Results: All of the tested gait variables showed high levels of reliability. There was no mentionable difference considering the correlation coefficients between the intra and inter reliability as well as between the three different surfaces. VPCs showed that the factor horse is by far the most responsible for any appearing variance. The experience of the evaluator had no influence on the results.Conclusions and Clinical Relevance: The software program tested in this study has a high inter- and intra-evaluator reliability under the chosen conditions for the selected variables and acts independent of the ground situation and the experience of the evaluator. On the condition of a correct application it has the potential to become a clinically relevant and reliable gait analysis tool.

Planning Results for High Tibial Osteotomies in Degenerative Varus Osteoarthritis Using Standing and Supine Whole Leg Radiographs.

ObjectiveIn this study, we hypothesized that standing and supine X‐rays lead to different preoperative planning results.MethodsThe present study included 168 pictures from 81 patients who were treated surgically with high tibial osteotomy (HTO) for varus deformity between January 2017 and February 2018. Each patient underwent whole leg X‐ray examinations in both standing and supine position. On both images, the following parameters were measured: degree of axis deviation (DAD), mechanical lateral distal femoral angle (mLDFA), mechanical medial proximal tibial angle (mMPTA), width of medial (MJS) and lateral joint space (LJS), and the correction angle (CA). The results were correlated with the patients’ age and body mass index (BMI). To analyze intra‐observer reliability, the same researcher, blinded to the previous measurements, remeasured all X‐rays from 10 patients 8 weeks after the initial measurements were carried out.ResultsWhile mLDFA (P = 0.075), mMPTA (P = 0.435), and MJS (P = 0.119) did not show any differences between the two modalities, LJS (P = 0.016) and DAD (P < 0.001) differed significantly, leading to different correction angles (P < 0.001). The mean difference of the CA was 1.7° ± 2.2° (range, −2.6° to−15.4°). In 14 legs (17%), the standing X‐ray led to a correction angle that was at least 3° larger than the calculation revealed in the supine X‐ray; in 4 legs (5%), it was at least 5° larger. Increased BMI (r = 0.191, P = 0.088) and older age (r = 0.057 , P = 0.605) did not show relevant correlation with DAD differences. However, more severe varus malalignment in the supine radiograph did correlate moderately with differences of correction angles between supine and weight‐bearing radiographs (r = 0.414, P < 0.001). The analysis of the intra‐rater reliability revealed mediocre to excellent intercorrelation coefficients between the measurements of the observer.ConclusionThe use of supine and standing X‐ray images leads to different planning results when performing high tibial osteotomies for varus gonarthrosis. To avoid potential overcorrection, surgeons might consider increased lateral joint spaces on standing radiographs in osteoarthritic knees with varus deviation.

The possibility to applying simulated series for compile scenario forecasting river runoff

The work shows the possibility of jointed simulation of monthly runoff, precipitation and air temperature with the method of canonical expansion. The method allows to save average runoff values, variability indexes and asymmetry coefficients as well as autocorrelation and intercorrelation coefficients. Simulated values of flow-forming factors can be used to compile scenario forecasts of monthly runoff hydrographs based on meteorological factors.

The Swedish Version of the TeamSTEPPS® Teamwork Perceptions Questionnaire (T-TPQ): A Validation Study.

PurposeThe delivery of effective and safe healthcare to patients is highly dependent on careful collaboration between healthcare professionals. Although teamwork is an important component for patient safety, effective teamwork is not always carried out in hospital wards, leading to negative consequences for the patients. Teamwork measurements can be used to evaluate and provide feedback to healthcare professionals to support team performance and to identify areas for improvement. The TeamSTEPPS® Teamwork Perceptions Questionnaire (T-TPQ) evaluates Team Structure and four core competences of teamwork (Leadership, Situation Monitoring, Mutual Support, and Communication) among healthcare professionals in various healthcare settings. The questionnaire was judged to be relevant in a Swedish healthcare context and was translated into Swedish. This study aimed to test the reliability and construct validity of the Swedish version of the T-TPQ.MethodsA total of 450 (of 1176) frontline healthcare professionals working at four hospitals responded to the questionnaire. A confirmatory factor analysis was carried out to test the factor structure. Cronbach’s alpha was used to measure internal consistency.ResultsThe hypothesized five-factor model of the five dimensions showed acceptable goodness-of-fit indexes. Cronbach’s alpha coefficient for the total T-TPQ was 0.94, and the Cronbach’s alpha coefficients for the dimensions ranged from 0.79 to 0.92. The intercorrelation coefficients ranged from 0.27 to 0.74.ConclusionThe Swedish version of the T-TPQ showed acceptable reliability and validity for measuring healthcare professionals’ individual perceptions of teamwork at the group level. Due to the low response rate, further studies are required to test the validity of the Swedish T-TPQ.

Deep learning-based analysis of macaque corneal sub-basal nerve fibers in confocal microscopy images

BackgroundTo develop and validate a deep learning-based approach to the fully-automated analysis of macaque corneal sub-basal nerves using in vivo confocal microscopy (IVCM).MethodsIVCM was used to collect 108 images from 35 macaques. 58 of the images from 22 macaques were used to evaluate different deep convolutional neural network (CNN) architectures for the automatic analysis of sub-basal nerves relative to manual tracings. The remaining images were used to independently assess correlations and inter-observer performance relative to three readers.ResultsCorrelation scores using the coefficient of determination between readers and the best CNN averaged 0.80. For inter-observer comparison, inter-correlation coefficients (ICCs) between the three expert readers and the automated approach were 0.75, 0.85 and 0.92. The ICC between all four observers was 0.84, the same as the average between the CNN and individual readers.ConclusionsDeep learning-based segmentation of sub-basal nerves in IVCM images shows high to very high correlation to manual segmentations in macaque data and is indistinguishable across readers. As quantitative measurements of corneal sub-basal nerves are important biomarkers for disease screening and management, the reported work offers utility to a variety of research and clinical studies using IVCM.

Development and validation of an instrument to measure patient engagement in Hong Kong Special Administrative Region, China.

ObjectiveThe objective of this study was to develop, pilot test, and psychometrically validate a patient engagement questionnaire, called Patient Engagement Index (PEI), in Hong Kong, China.MethodThe method employed was based on a patient engagement framework and literature review and expert panel discussion. A new measure named PEI with 20 items divided into five factors was developed. A pilot study of 40 patients was used to confirm the clarity of PEI. Explored factor analysis was used to confirm the construct validity. Cronbach’s alpha, intercorrelation coefficients (ICCs), and weighted kappa were used to assess the internal consistency reliability and test–retest reliability separately. Rasch model and differential item functioning were also used to further confirm the fit of the instrument.ResultsIn all, 324 participants successfully completed the survey. Based on the evaluation of exploratory factor analysis and theoretically considerations, a four-factor structure comprising 20 items was identified. Rasch analysis also confirmed that the model has a good fit (ranging from 0.662 to 1.294). All domains were considered internally consistent (alpha >0.7). Test–retest showed both ICC (>0.6) and weighted kappa (>0.4) meeting the minimum recommended standard. No ceiling or floor effect was found. Furthermore, Spearman’s correlation coefficient confirmed that PEI had good internal validity.ConclusionPEI was shown to have good reliability and validity. This is a short, quick, and appropriate tool to assess the extent of patient engagement in both clinical and research settings.

What is the reliability of clinical measurement tests for humeral head position? A systematic review

Study DesignSystematic review. IntroductionPhysiotherapists routinely assess the position of the humeral head (HH) in patients with shoulder pain. Purpose of the StudyTo conduct a systematic review to determine the quality and content of studies that evaluated the reliability of clinical measurement methods for assessing the HH position. MethodsFive databases and gray literature were searched for studies fitting the eligibility criteria. After abstract and full-text review, the included studies were appraised using the Quality Appraisal of Reliability Studies checklist. Articles were considered of high quality if 8 was achieved on the checklist, and the overall quality of evidence was classified using prespecified criteria. Multiple raters extracted and performed quality ratings; a consensus process was used to finalize the reliability data that were synthesized and presented in a narrative synthesis. Reliability was classified as excellent if the intracorrelation coefficients or intercorrelation coefficients (ICCs) reported exceeded 0.75. ResultsFifteen studies on the reliability of ultrasound (US) and 3 studies on palpation were included. The methodologic quality was moderate in 17 of 18 studies. The intrarater reliability for all studies was excellent (ICC, 0.76-0.99) with the exception of the 90° abduction in internal rotation position (ICC, 0.48) for palpation. The inter-rater reliability tended to be lower (ICC, 0.48-0.68) for palpation and higher (ICC, 0.66-0.99) for US. Physiotherapists demonstrated excellent intrarater reliability across different levels of training in ultrasonography. DiscussionOur study found a moderate overall level of evidence to support the use of US for assessing HH position in symptomatic or asymptomatic subjects. ConclusionA moderate overall level of evidence exists for the use of US to reliably assess the HH position. Limited research supports the methods used for palpation within a clinical setting. Level of Evidence2a.

Into the cognitive constructs related to adherence to treatment in CHD outpatients: the importance of accepting the disease limitations

Background and aims: Poor adherence to clinical prescriptions has been recognized as a major problem in management of chronic diseases. Only few studies tried to identify which factors could be considered predictive of low adherence to pharmacological and non pharmacological prescriptions in Coronary Heart Disease (CHD) patients. The aims of our observational-longitudinal study were to assess in CHD outpatients admitted to a Cardiological Day Hospital (DH): self-reported knowledge and acceptance about illness, perceived self-efficacy in disease management and emotional status, and the possible relationships among these variables. Methods: Patients were assessed at baseline during the first days of DH and few days before discharge (follow-up) by the Adherence Schedule in Ischemic Heart Disease (ASIHD) and by the Anxiety and Depression Scale (AD). The ASIHD is a tool specifically aimed at evaluating the cognitive, relational and behavioural antecedents of adherence to treatment of patients suffering CHD. The rehabilitation programme comprised: individualized physical training, nutrition monitoring, psychological assessment and psychoeducational interventions, when indicated. Baseline and follow- up clinical data, ASHID and AD scores were analysed both considering the whole sample (n=117) and the subgroup which met the clinical criteria for psychological counselling (n=35, psychologically treated group). Intracorrelation and intercorrelation coefficients of the whole sample baseline data were calculated among ASIHD, AD scores and socio-demographic data. Results: Our CHD outpatients (62.6±9.3 years) were mainly male, married and retired. They had 5,2 years of illness on the average, and only 9% of them were still smokers, whereas 62% had smoked in the past. Total and LDL cholesterol levels showed a significant reduction at follow up evaluation. Among ASIHD baseline item scores, many statistically significant intracorrelations emerged, in particular: disease limitations acceptance showed significant positive correlations with disease knowledge (r=.34, p=.0001), family/friend support (r=.27, p=.003), following dietary prescriptions (r=.38, p=.0001), exercise (r=.35, p=.0001), taking medicines punctually (r=.35, p=.0001), identifying physical/ psychological fatigue (r=.45, p=.0001), monitoring clinical parameters (r=.42, p=.0001), management of stressful situations (r=.26, p=.006), and reducing stress sources (r=.34, p=.0001). Concerning the significant intercorrelations between AD and ASIHD scores, disease acceptance showed negative correlations with anxiety and depression (r=-.27, p=.004; r=-.26, p=.004 respectively). Conclusions: The pathway stemmed from our data enlights that in the area of cognitive and relational antecedents of adeherence, accepting the disease limitations can be considered a central issue in CHD patient’s illness adjustment and prescriptions adherence. Moreover, the ASHID resulted a useful synthetic schedule of psychological/behavioural variables regarding perceived self-efficacy in disease management. This may facilitate a synergic team work on common priorities that respect the point of view of the patient and the clinical-rehabilitation purposes.

Effects of socioeconomic disadvantage on renal failure hospital admissions in Victoria.

5 years of age. RFAs had the sixth highest 30-day readmission (15%). One-tenth of the patients died in hospital. The RFA rates varied inversely with SED (r=–0.51, P <0.01).Thecoefficientofvariationwas0.44and0.16forRFA andalladmissions,respectively,indicatingthatRFAshadgreater variability by LGA than all admissions. The mean RFA rate for the top percentile LGAs was 2.4-fold greater than that of the bottom percentile LGA (13.21 (95% CI 11.44–14.93) vs 5.62 (95% CI 4.43–6.95), respectively). The top percentile group was the most disadvantaged, including Central Goldfields, Loddon and Mildura. The bottom percentile group include Bayside, Boroondara and Nillumbik. LGAs with high RFA rates also had high hospital admission ratesforotherconditions,suchasheartfailure(r=0.58,P <0.01) and chronic obstructive pulmonary disease (r=0.49, P <0.01), and prevalence of hypertension (r=0.32, P <0.01) and obesity (r=0.26,P <0.05). Residents of disadvantaged communities are significantly more likely (r=0.45, P <0.01) to be on a Disability Support Pension (Table 1). Inconclusion,thevariationsinRFAratesmayreflectmultiple factors, particularly access to adequate care, delayed referral to Table 1. Inter-correlation coefficients for age-standardised renal failure hospitalisation rates and key variables *P <0.05, **P <0.01 (two-tailed). SED, socioeconomic disadvantage; REN, age-adjusted renal failure admissions per 10 000 population; HRF, age-adjusted heartfailureadmissionsper10 000population;COP,age-adjustedchronicobstructivepulmonarydiseaseadmissionsper10 000population;OCA,proportionof thepopulationundertakingmostlyheavylabourorphysicallydemandingactivity;HYP,prevalence(%)ofhypertension;OBE,prevalence(%)ofoverweightand obesity;HLS,prevalence(%)offairorpoorself-reportedhealthstatus;CAN,prevalence(%)ofcancer;DSP,proportionofthepopulationonDisabilitySupport

Assessing correlation of clustered mixed outcomes from a multivariate generalized linear mixed model.

The classic concordance correlation coefficient measures the agreement between two variables. In recent studies, concordance correlation coefficients have been generalized to deal with responses from a distribution from the exponential family using the univariate generalized linear mixed model. Multivariate data arise when responses on the same unit are measured repeatedly by several methods. The relationship among these responses is often of interest. In clustered mixed data, the correlation could be present between repeated measurements either within the same observer or between different methods on the same subjects. Indices for measuring such association are needed. This study proposes a series of indices, namely, intra-correlation, inter-correlation, and total correlation coefficients to measure the correlation under various circumstances in a multivariate generalized linear model, especially for joint modeling of clustered count and continuous outcomes. The proposed indices are natural extensions of the concordance correlation coefficient. We demonstrate the methodology with simulation studies. A case example of osteoarthritis study is provided to illustrate the use of these proposed indices.

Multilevel Analysis of Factors Predicting Self Efficacy in Computer Programming

This study used multilevel analysis to determine the predictive value of selected intrinsic factors (gender, computer ownership, mathematics background and computer experience) and institutional type (an extrinsic factor) on undergraduates’ Self Efficacy in Java Computer Programming (SEiJCP) in South – West, Nigeria. The study adopted a correlational design. Purposive Sampling was used to select 254 computer science undergraduates from four universities (three federal-owned and one state-owned) in south-west, Nigeria. Three research questions were answered. Two research instruments namely, Computer experience scale (r = 0.84) and Java Programming Self Efficacy Scale (JPSES, r = 0.96) were used to collect data. Data were analysed using descriptive statistics, and null and linear growth model (LGM) procedures. The intercorrelation coefficients among the extrinsic factor, intrinsic factors and SEiJCP were moderate. Null model shows that the variations in SEiJCP accounted for by insitutional level differences was 99.0%. The fixed part of the LGM of intrinsic factors showed that only mathematical backgroung contributed significantly (p < 0.05) to the prediction of SEiJCP. The random part of the LGM showed no significant contributions of the interactions of the intrinsic factors, to the prediction of SEiJCP. About 60.0% of the student level variation in SEiJCP is explained by the differences in intrinsic factors. The institution – level variable had large predictive value on programming self efficacy. Computer science departments should increase the number of mathematics courses in their curriculum.