New insight in the relationship between regional patterns of knee cartilage thickness, osteoarthritis disease severity, and gait mechanics.

To test if the relationship between knee kinetics during walking and regional patterns of cartilage thickness is influenced by disease severity we tested the following hypotheses in a cross-sectional study of medial compartment osteoarthritis (OA) subjects: (1) the peak knee flexion (KFM) and adduction moments (KAM) during walking are associated with regional cartilage thickness and medial-to-lateral cartilage thickness ratios, and (2) the associations between knee moments and cartilage thickness data are dependent on disease severity. Seventy individuals with medial compartment knee OA were studied. Gait analysis was used to determine the knee moments and cartilage thickness was measured from magnetic resonance imaging. Multiple linear regression analyses tested for associations between cartilage thickness and knee kinetics. Medial cartilage thickness and medial-to-lateral cartilage thickness ratios were lower in subjects with greater KAM for specific regions of the femoral condyle and tibial plateau with no associations for KFM in patients of all disease severities. When separated by severity, the association between KAM and cartilage thickness was found only in patients with more severe OA, and KFM was significantly associated with cartilage thickness only for the less severe OA subjects for specific tibial plateau regions. The results support the idea that the KAM is larger in patients with more severe disease and the KFM has greater influence early in the disease process, which may lessen as pain increases with disease severity. Each component influences different regions of cartilage. Thus the relative contributions of both KAM and KFM should be considered when evaluating gait mechanics and the influence of any intervention for knee OA.

A short screener is valid for assessing mediterranean diet adherence among older spanish men and women

Ensuring the accuracy of dietary assessment instruments is paramount for interpreting diet-disease relationships. The present study assessed the relative and construct validity of the 14-point Mediterranean Diet Adherence Screener (MEDAS) used in the Prevencio´n con Dieta Mediterra´nea (PREDIMED) study, a primary prevention nutrition-intervention trial. A validated FFQ and the MEDAS were administered to 7146 participants of the PREDIMED study. The MEDASderived PREDIMED score correlated significantly with the corresponding FFQ PREDIMED score (r = 0.52; intraclass correlation coefficient = 0.51) and in the anticipated directions with the dietary intakes reported on the FFQ. Using Bland Altman"s analysis, the average MEDAS Mediterranean diet score estimate was 105% of the FFQ PREDIMED score estimate. Limits of agreement ranged between 57 and 153%. Multiple linear regression analyses revealed that a higher PREDIMED score related directly (P , 0.001) to HDL-cholesterol (HDL-C) and inversely (P , 0.038) to BMI, waist circumference, TG, the TG:HDL-C ratio, fasting glucose, and the cholesterol:HDL-C ratio. The 10-y estimated coronary artery disease risk decreased as the PREDIMED score increased (P , 0.001). The MEDAS is a valid instrument for rapid estimation of adherence to the Mediterranean diet and may be useful in clinical practice.

A short screener is valid for assessing mediterranean diet adherence among older spanish men and women

Ensuring the accuracy of dietary assessment instruments is paramount for interpreting diet-disease relationships. The present study assessed the relative and construct validity of the 14-point Mediterranean Diet Adherence Screener (MEDAS) used in the Prevencio´n con Dieta Mediterra´nea (PREDIMED) study, a primary prevention nutrition-intervention trial. A validated FFQ and the MEDAS were administered to 7146 participants of the PREDIMED study. The MEDASderived PREDIMED score correlated significantly with the corresponding FFQ PREDIMED score (r = 0.52; intraclass correlation coefficient = 0.51) and in the anticipated directions with the dietary intakes reported on the FFQ. Using Bland Altman"s analysis, the average MEDAS Mediterranean diet score estimate was 105% of the FFQ PREDIMED score estimate. Limits of agreement ranged between 57 and 153%. Multiple linear regression analyses revealed that a higher PREDIMED score related directly (P , 0.001) to HDL-cholesterol (HDL-C) and inversely (P , 0.038) to BMI, waist circumference, TG, the TG:HDL-C ratio, fasting glucose, and the cholesterol:HDL-C ratio. The 10-y estimated coronary artery disease risk decreased as the PREDIMED score increased (P , 0.001). The MEDAS is a valid instrument for rapid estimation of adherence to the Mediterranean diet and may be useful in clinical practice.

Screening of mental health and substance users in frequent users of a general Swiss emergency department.

BACKGROUND: The objectives of this study were to determine the proportions of psychiatric and substance use disorders suffered by emergency departments' (EDs') frequent users compared to the mainstream ED population, to evaluate how effectively these disorders were diagnosed in both groups of patients by ED physicians, and to determine if these disorders were predictive of a frequent use of ED services. METHODS: This study is a cross-sectional study with concurrent and retrospective data collection. Between November 2009 and June 2010, patients' mental health and substance use disorders were identified prospectively in face-to-face research interviews using a screening questionnaire (i.e. researcher screening). These data were compared to the data obtained from a retrospective medical chart review performed in August 2011, searching for mental health and substance use disorders diagnosed by ED physicians and recorded in the patients' ED medical files (i.e. ED physician diagnosis). The sample consisted of 399 eligible adult patients (≥18 years old) admitted to the urban, general ED of a University Hospital. Among them, 389 patients completed the researcher screening. Two hundred and twenty frequent users defined by >4 ED visits in the previous twelve months were included and compared to 169 patients with ≤4 ED visits in the same period (control group). RESULTS: Researcher screening showed that ED frequent users were more likely than members of the control group to have an anxiety, depressive disorder, post-traumatic stress disorder (PTSD), or suffer from alcohol, illicit drug abuse/addiction. Reviewing the ED physician diagnosis, we found that the proportions of mental health and substance use disorders diagnosed by ED physicians were low both among ED frequent users and in the control group. Using multiple logistic regression analyses to predict frequent ED use, we found that ED patients who screened positive for psychiatric disorders only and those who screened positive for both psychiatric and substance use disorders were more likely to be ED frequent users compared to ED patients with no disorder. CONCLUSIONS: This study found high proportions of screened mental health and/or substance use disorders in ED frequent users, but it showed low rates of detection of such disorders in day-to-day ED activities which can be a cause for concern. Active screening for these disorders in this population, followed by an intervention and/or a referral for treatment by a case-management team may constitute a relevant intervention for integration into a general ED setting.

Classification models for neurocognitive impairment in HIV infection based on demographic and clinical variables

Objective: We used demographic and clinical data to design practical classification models for prediction of neurocognitive impairment (NCI) in people with HIV infection. Methods: The study population comprised 331 HIV-infected patients with available demographic, clinical, and neurocognitive data collected using a comprehensive battery of neuropsychological tests. Classification and regression trees (CART) were developed to btain detailed and reliable models to predict NCI. Following a practical clinical approach, NCI was considered the main variable for study outcomes, and analyses were performed separately in treatment-naïve and treatment-experienced patients. Results: The study sample comprised 52 treatment-naïve and 279 experienced patients. In the first group, the variables identified as better predictors of NCI were CD4 cell count and age (correct classification [CC]: 79.6%, 3 final nodes). In treatment-experienced patients, the variables most closely related to NCI were years of education, nadir CD4 cell count, central nervous system penetration-effectiveness score, age, employment status, and confounding comorbidities (CC: 82.1%, 7 final nodes). In patients with an undetectable viral load and no comorbidities, we obtained a fairly accurate model in which the main variables were nadir CD4 cell count, current CD4 cell count, time on current treatment, and past highest viral load (CC: 88%, 6 final nodes). Conclusion: Practical classification models to predict NCI in HIV infection can be obtained using demographic and clinical variables. An approach based on CART analyses may facilitate screening for HIV-associated neurocognitive disorders and complement clinical information about risk and protective factors for NCI in HIV-infected patients.

Image guided critical screw placement precision in the cervical spine : important or incidental? : results of a series of 91 consecutive cases using OVEM

Study design: A retrospective study of image guided cervical implant placement precision. Objective: To describe a simple and precise classification of cervical critical screw placement. Summary of Background Data: "Critical" screw placement is defined as implant insertion into a bone corridor which is surrounded circumferentially by neurovascular structures. While the use of image guidance has improved accuracy, there is currently no classification which provides sufficient precision to assess the navigation success of critical cervical screw placement. Methods: Based on postoperative clinical evaluation and CT imaging, the orthogonal view evaluation method (OVEM) is used to classify screw accuracy into grade I (no cortical breach), grade la (screw thread cortical breach), grade II (internal diameter cortical breach) and grade III (major cortical breach causing neural or vascular injury). Grades II and III are considered to be navigation failures, after accounting for bone corridor / screw mismatch (minimal diameter of targeted bone corridor being smaller than an outer screw diameter). Results: A total of 276 screws from 91 patients were classified into grade I (64.9%), grade la (18.1%), and grade II (17.0%). No grade III screw was observed. The overall rate of navigation failure was 13%. Multiple logistic regression indicated that navigational failure was significantly associated with the level of instrumentation and the navigation system used. Navigational failure was rare (1.6%) when the margin around the screw in the bone corridor was larger than 1.5 mm. Conclusions: OVEM evaluation appears to be a useful tool to assess the precision of critical screw placement in the cervical spine. The OVEM validity and reliability need to be addressed. Further correlation with clinical outcomes will be addressed in future studies.

Proposição, validação e análise dos modelos que correlacionam estrutura química e atividade biológica

The present paper aims to bring under discussion some theoretical and practical aspects about the proposition, validation and analysis of QSAR models based on multiple linear regression. A comprehensive approach for the derivation of extrathermodynamic equations is reviewed. Some examples of QSAR models published in the literature are analyzed and criticized.

Aplicação de algoritmos genéticos na seleção de variáveis em espectroscopia no infravermelho médio: determinação simultânea de glicose, maltose e frutose

Genetic algorithm was used for variable selection in simultaneous determination of mixtures of glucose, maltose and fructose by mid infrared spectroscopy. Different models, using partial least squares (PLS) and multiple linear regression (MLR) with and without data pre-processing, were used. Based on the results obtained, it was verified that a simpler model (multiple linear regression with variable selection by genetic algorithm) produces results comparable to more complex methods (partial least squares). The relative errors obtained for the best model was around 3% for the sugar determination, which is acceptable for this kind of determination.

Quantitative structure-retention relationships analysis of retention index of essential oils

Genetic algorithm and multiple linear regression (GA-MLR), partial least square (GA-PLS), kernel PLS (GA-KPLS) and Levenberg-Marquardt artificial neural network (L-M ANN) techniques were used to investigate the correlation between retention index (RI) and descriptors for 116 diverse compounds in essential oils of six Stachys species. The correlation coefficient LGO-CV (Q²) between experimental and predicted RI for test set by GA-MLR, GA-PLS, GA-KPLS and L-M ANN was 0.886, 0.912, 0.937 and 0.964, respectively. This is the first research on the QSRR of the essential oil compounds against the RI using the GA-KPLS and L-M ANN.

Problems and potentialities of e-Learning for regular undergraduate courses in emergency medicine

BACKGROUND: E-learning techniques are spreading at great speed in medicine, raising concerns about the impact of adopting them. Websites especially designed to host courses are becoming more common. There is a lack of evidence that these systems could enhance student knowledge acquisition. GOAL: To evaluate the impact of using dedicated-website tools over cognition of medical students exposed to a first-aid course. METHODS: Prospective study of 184 medical students exposed to a twenty-hour first-aid course. We generated a dedicated-website with several sections (lectures, additional reading material, video and multiple choice exercises). We constructed variables expressing the student's access to each section. The evaluation was composed of fifty multiple-choice tests, based on clinical problems. We used multiple linear regression to adjust for potential confounders. RESULTS: There was no association of website intensity of exposure and the outcome - beta-coeficient 0.27 (95%CI - 0.454 - 1.004). These findings were not altered after adjustment for potential confounders - 0.165 (95%CI -0.628 - 0.960). CONCLUSION: A dedicated website with passive and active capabilities for aiding in person learning had not shown association with a better outcome.

Spatio-temporal modelling of the duration of the cotton cycle in the State Of Goiás, Brazil

The objective of this work was to develop and validate a mathematical model to estimate the duration of cotton (Gossypium hirsutum L. r. latifolium hutch) cycle in the State of Goiás, Brazil, by applying the method of growing degree-days (GD), and considering, simultaneously, its time-space variation. The model was developed as a linear combination of elevation, latitude, longitude, and Fourier series of time variation. The model parameters were adjusted by using multiple-linear regression to the observed GD accumulated with air temperature in the range of 15°C to 40°C. The minimum and maximum temperature records used to calculate the GD were obtained from 21 meteorological stations, considering data varying from 8 to 20 years of observation. The coefficient of determination, resulting from the comparison between the estimated and calculated GD along the year was 0.84. Model validation was done by comparing estimated and measured crop cycle in the period from cotton germination to the stage when 90 percent of bolls were opened in commercial crop fields. Comparative results showed that the model performed very well, as indicated by the Pearson correlation coefficient of 0.90 and Willmott agreement index of 0.94, resulting in a performance index of 0.85.

Determination of the influence of the variation of reducing and non-reducing sugars on coffee quality with use of artificial neural network

The present study aimed at evaluating the use of Artificial Neural Network to correlate the values resulting from chemical analyses of samples of coffee with the values of their sensory analyses. The coffee samples used were from the Coffea arabica L., cultivars Acaiá do Cerrado, Topázio, Acaiá 474-19 and Bourbon, collected in the southern region of the state of Minas Gerais. The chemical analyses were carried out for reducing and non-reducing sugars. The quality of the beverage was evaluated by sensory analysis. The Artificial Neural Network method used values from chemical analyses as input variables and values from sensory analysis as output values. The multiple linear regression of sensory analysis values, according to the values from chemical analyses, presented a determination coefficient of 0.3106, while the Artificial Neural Network achieved a level of 80.00% of success in the classification of values from the sensory analysis.

The use of ALOS/PALSAR data for estimating sugarcane productivity

Some models have been developed using agrometeorological and remote sensing data to estimate agriculture production. However, it is expected that the use of SAR images can improve their performance. The main objective of this study was to estimate the sugarcane production using a multiple linear regression model which considers agronomic data and ALOS/PALSAR images obtained from 2007/08, 2008/09 and 2009/10 cropping seasons. The performance of models was evaluated by coefficient of determination, t-test, Willmott agreement index (d), random error and standard error. The model was able to explain 79%, 12% and 74% of the variation in the observed productions of the 2007/08, 2008/09 and 2009/10 cropping seasons, respectively. Performance of the model for the 2008/09 cropping season was poor because of the occurrence of a long period of drought in that season. When the three seasons were considered all together, the model explained 66% of the variation. Results showed that SAR-based yield prediction models can contribute and assist sugar mill technicians to improve such estimates.

The effect of dynamic capabilities on operational-level innovation – Empirical study in magazine publishing industry

This master’s thesis aims to examine the relationship between dynamic capabilities and operational-level innovations. In addition, measures for the concept of dynamic capabilities are developed. The study was executed in the magazine publishing industry which is considered favourable for examining dynamic capabilities, since the sector is characterized by rapid change. As a basis for the study and the measure development, a literary review was conducted. Data for the empirical section was gathered by a survey targeted to chief-editors of Finnish consumer magazines. The relationship between dynamic capabilities and innovation was examined by multiple linear regression. The results indicate that dynamic capabilities have effect on the emergence of radical innovations. Environmental dynamism’s effect on radical innovations was not detected. Also, dynamic capabilities’ effect on innovation was not greater in turbulent operating environment.

Is liver transplantation associated with decreased bone mass in climacteric women?

PURPOSE: To evaluate whether climacteric women undergoing liver transplantation had higher prevalence of decreased bone mass than those without any liver disease. METHODS: A cross-sectional study with 48 women receiving follow-up care at a university hospital in Southeastern Brazil, from February 4th 2009 to January 5th 2011, was conducted. Of these women, 24 were 35 years or older and had undergone liver transplantation at least one year before study entry. The remaining 24 women had no liver disease and their ages and menstrual patterns were similar to those of transplanted patients. Laboratorial tests (follicle-stimulating hormone and estradiol) and bone density measurements of the lumbar spine and femur (equipment Hologic, Discovery WI) were performed. Statistical analysis was carried out by Fisher's exact test, simple Odds Ratio (OR), and multiple logistic regression. RESULTS: Mean age of the women included in the study was 52.8 (±10.7) years-old, 27.1% were premenopausal and 72.9% were peri/postmenopausal. Approximately 14.6% of these women exhibited osteoporosis and 35.4% had low bone mass. The following items were associated with decreased bone mass: being postmenopausal (OR=71.4; 95%CI 3.8 - 1,339.7; p<0.0001), current age over 49 years-old (OR=11.4; 95%CI 2.9 - 44.0; p=0.0002), and serum estradiol levels lower than 44.5 pg/mL (OR=18.3; 95%CI 3.4 - 97.0; p<0.0001). Having a history of liver transplantation was not associated with decreased bone mass (OR=1.4; 95%CI 0.4 - 4.3; p=0.56). CONCLUSION: Liver transplantation was not associated with decreased bone mass in this group of climacteric women.