Aspectos psicossociais associados à percepção da dor pós-operatória em indivíduos submetidos a cirurgia coronária

Objectivo: Identificar os factores psicossociais que influenciam a percepção da dor pós-operatória em doentes submetidos a cirurgia de revascularização do miocárdio (CRM). Material e Métodos: Estudo exploratório correlacional de 91 doentes (71 homens e 20 mulheres) submetidos a CRM (pontagem aortocoronária) por esternotomia). A idade média era de 63,8 ± 9,6 anos (entre 39 e 84). Foram utilizados os seguintes instrumentos: Escala Analógica Visual às 24, 48 e 96 horas do pós-operatório; Questionário de Caracterização Demográfica; Mental Health Inventory de 5 itens; Percepção de Saúde Geral (SF-36); Escala de Expectativas de Dor; Escala de Percepção de Apoio; Escala de Expectativas de Auto-eficácia; Satisfação com o tratamento, médicos e enfermeiros (American Pain Society Questionnaire) aplicados às 96 horas após a cirurgia. Resultados: Os doentes que apresentaram expectativas elevadas de dor, percepcionaram maior apoio, apresentaram níveis elevados de auto-eficácia para lidar com a dor ou, se pertenciam ao sexo masculino, sentiram menos dor. De igual modo, os doentes que apresentaram melhor saúde mental, percepcionaram a sua saúde como boa e os doentes que expressaram maior satisfação com o tratamento sentiram menos dor. A dor não foi influenciada pela idade, grau de escolaridade ou pela satisfação com a conduta de médicos e enfermeiros. Conclusão: Após as primeiras 48 horas do pós-operatório, a experiência de dor é influenciada por factores psicossociais, em oarticular pela expectativa de dor, expectativa de auto-eficácia, apoio percebido, percepção da saúde geral, percepção de saúde mental e satisfação com o tratamento para a dor. Perante os resultados, evidencia-se a necessidade de conjugar conhecimentos no sentido de dar respostas mais alargadas e de carácter multidisciplinar no tratamento da dor pós-operatória em CRM devendo, a par de outros aspectos, focar-se na gestão das expectativas dos doentes. ABSTRACT - Objective: To identify the psychological factors that influence post-surgery pain perception in patients undergoing coronary artery bypass graft surgery (CABG). Methods: This was an exploratory correlational study of 91 patients (71 men and 20 women) who underwent CABG (aortocoronary anastomosis) by sternotomy. Mean age was 63.8 ± 9.6 years (between 39 and 84). The following instruments were used: visual analogical scales at 24, 48 and 96 hours of post-surgery; demographic characteristics survey; pain expectations scale; perceived support scale; self-efficacy scale, Mental Inventory (5 items); health perception scale; and satisfaction with treatment, doctors and nurses (American Pain Society questionnaire) at 96 hours after surgery. Results: Patients who had presented high expectations of pain, perceived more support, presented high levels of self-efficacy to deal with pain or were male, felt less pain. Furthermore, patients who presented better mental health, perceived their general health as being good, or expressed greater satisfaction with treatment, felt less pain. Pain was not influenced by age, level of education or satisfaction with doctors and nurses. Conclusion: After the first 48 hours following surgery, the pain experience is influenced by psychosocial factors, in particular by expectation of pain and of self-efficacy, perceived support, perception of general and mental health, and satisfaction with pain treatment. The results confirm the need to bring together different kinds of knowledge for a broad, multidisciplinary approach to postoperative CABG pain treatment, focusing, along with other aspects, on management of patients’ expectations.

Automatic assignment of absolute configuration from 1D NMR data

Opposite enantiomers exhibit different NMR properties in the presence of an external common chiral element, and a chiral molecule exhibits different NMR properties in the presence of external enantiomeric chiral elements. Automatic prediction of such differences, and comparison with experimental values, leads to the assignment of the absolute configuration. Here two cases are reported, one using a dataset of 80 chiral secondary alcohols esterified with (R)-MTPA and the corresponding 1H NMR chemical shifts and the other with 94 13C NMR chemical shifts of chiral secondary alcohols in two enantiomeric chiral solvents. For the first application, counterpropagation neural networks were trained to predict the sign of the difference between chemical shifts of opposite stereoisomers. The neural networks were trained to process the chirality code of the alcohol as the input, and to give the NMR property as the output. In the second application, similar neural networks were employed, but the property to predict was the difference of chemical shifts in the two enantiomeric solvents. For independent test sets of 20 objects, 100% correct predictions were obtained in both applications concerning the sign of the chemical shifts differences. Additionally, with the second dataset, the difference of chemical shifts in the two enantiomeric solvents was quantitatively predicted, yielding r2 0.936 for the test set between the predicted and experimental values.

Longitudinal versus polar wrinkling of core-shell fibers with anisotropic size mismatches

We consider a fiber made of a soft elastic material, encased in a stiff elastic shell (core-shell geometry). If the core and shell dimensions are mismatched, e.g., because the core shrinks while the shell does not, but the two remain attached, then an elastic instability is triggered whereby wrinkles may appear on the shell. The wrinkle orientation may be longitudinal (along the fiber axis), polar (along the fiber perimeter), or a mixture of both, depending on the fiber's geometrical and material parameters. Here we investigate under what conditions longitudinal or polar wrinkling will occur.

Neural-network approach to modeling liquid crystals in complex confinement

Finding the structure of a confined liquid crystal is a difficult task since both the density and order parameter profiles are nonuniform. Starting from a microscopic model and density-functional theory, one has to either (i) solve a nonlinear, integral Euler-Lagrange equation, or (ii) perform a direct multidimensional free energy minimization. The traditional implementations of both approaches are computationally expensive and plagued with convergence problems. Here, as an alternative, we introduce an unsupervised variant of the multilayer perceptron (MLP) artificial neural network for minimizing the free energy of a fluid of hard nonspherical particles confined between planar substrates of variable penetrability. We then test our algorithm by comparing its results for the structure (density-orientation profiles) and equilibrium free energy with those obtained by standard iterative solution of the Euler-Lagrange equations and with Monte Carlo simulation results. Very good agreement is found and the MLP method proves competitively fast, flexible, and refinable. Furthermore, it can be readily generalized to the richer experimental patterned-substrate geometries that are now experimentally realizable but very problematic to conventional theoretical treatments.