20 research outputs found

    Perspectives on reasons of medication nonadherence in psychiatric patients

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    Derya Güliz Mert,1 Nergiz Hacer Turgut,2 Meral Kelleci,3 Murat Semiz4 1Department of Psychiatry, Faculty of Medicine, Cumhuriyet University, 2Department of Pharmacology, Faculty of Pharmacy, Cumhuriyet University, 3Department of Psychiatric Nursing, Faculty of Health Sciences, Cumhuriyet University, Sivas, Turkey; 4Department of Psychiatry, Faculty of Medicine, University of Osmangazi, Tokat, Turkey Purpose: This study was carried out to evaluate factors resulting in medication nonadherence within 6 months before admission to the psychiatric service of our hospital for bipolar disorder, schizophrenia/schizoaffective disorder, depression, and other psychiatric diseases.Patients and methods: Two hundred and three patients admitted to the Psychiatry Service of the Medical Faculty were included in this study. Sociodemographic parameters and clinical findings within 6 months before admission and patients’ views on reasons of medication nonadherence were examined.Results: Patients were classified into four groups according to their diagnosis: bipolar disorder (n=68, 33.5%), schizophrenia/schizoaffective disorder (n=59, 29.1%), depression (n=39, 19.2%), and others (n=37, 18.2%). The ratio of medication nonadherence was higher in the bipolar disorder group when compared to the groups with schizophrenia/schizoaffective disorder, depression, and other disorders (12.1%, 18.2%, and 24.2% vs 45.5%); however, the ratio of medication nonadherence was similar in schizophrenia/schizoaffective disorder, depression, and the others group. In logistic regression analysis, irregular follow-up (odds ratio [OR]: 5.7; 95% confidence interval [CI]: 2.92–11.31) and diagnosis (OR: 1.5; 95% CI: 1.07–1.95) were determined to be important risk factors for medication nonadherence. The leading factors for medication nonadherence were: “not willing to use medication”, “not accepting the disease”, and “being disturbed by side effects” in the bipolar disorder group, “not accepting the disease” in the schizophrenia/schizoaffective disorder group, “feeling well” in the depression group, and “being disturbed by side effects” in the other diseases group.Conclusion: Medication nonadherence is an important problem in psychiatric patients and should be dealt with by taking into account the diagnosis, attendance to follow-up appointments, and the patient’s attitude. Ensuring regular attendance to follow-up appointments, adjusting the management plan according to the diagnosis, and improving their thoughts about resistance to medication can be beneficial in terms of medication adherence. Keywords: bipolar disorder, schizophrenia, schizoaffective disorder, depression, patient’s attitud

    Accuracy/speed analysis of pipe friction factor correlations

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    The Colebrook [1] equation is considered the standard for the calculation of friction factor for turbulent flow in commercial pipes, but it is implicit, and therefore it must be computed by iterative methods. Although such iterative computation quickly converges, the computational time in large pipe system simulations can be reduced using an accurate explicit correlation. A review of the up to date literature identified 30 different explicit correlations. In order to determine which correlation is the best alternative to Colebrook’s, both accuracy and computational burden were compared. The accuracy of each explicit correlation was compared against Colebrook’s correlation using the mean and maximum relative errors and the coefficient of determination. Also, the computational time of each equation was measured using the tic and toc functions in GNU Octave software. It was found that the iterative computation of the Colebrook equation demands about 2.6 times the computational time of the slowest explicit correlation. The correlations with the best balance between accuracy and computational burden are, in decreasing order of accuracy and increasing order of speed, correlations by Serghides [13] (Eqs. (17), (18), (19), and (20)), by Shacham [8] (Eqs. (10) and (11)), by Brkić and Praks [33] (Eqs. (53), (54), (55), and (56)), and by Fang et al. [19] (Eq. (28)).info:eu-repo/semantics/publishedVersio

    Selective Estrogen Receptor Modulation Prevents Scoliotic Curve Progression: Radiologic And Histomorphometric Study On A Bipedal C57Bl6 Mice Model

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    Previous work has suggested that progression of experimental scoliotic curves in pinealectomized chicken and bipedal C57BL6 mice models may be prevented and reversed with Tamoxifen treatment. Raloxifene is another Selective Estrogen Receptor Modulator (SERM) with estrogen agonist effects on bone and increases bone density but with fewer side effects on humans. To investigate whether scoliosis progression in bipedal C57Bl6 mice model could be prevented with SERM treatment and the mechanisms associated with this effect. Eighty C57BL6 mice were rendered bipedal and divided into Tamoxifen (TMX), Raloxifene (RLX) and control groups. TMX and RLX groups received orally administered TMX and RLX for 40 weeks. Anteroposterior X-ray imaging and histomorphometric analysis (at 20th and 40th weeks) were performed. At 20th week, TMX and RLX groups displayed higher rates (p = 0.033, p = 0.029) and larger curve magnitudes (p = 0.018). At 40th week, curve rates were similar between the groups but the curve magnitudes in TMX and RLX groups were smaller (p = 0.001). Histomorphometry revealed that treated animals had higher trabecular density (p = 0.04), lower total intervertebral disc (p = 0.038) and growth plate volumes (p = 0.005) and smaller vertebral bodies (p = 0.016). Treatment with TMX or RLX did not reduce the incidence of scoliosis but decreased the curve magnitudes at 40 weeks. The underlying mechanism associated with the decrease in curve magnitudes may be the early maturation of growth plates, thereby possible deceleration of the growth rate of the vertebral column and increase in bone density. RLX is as effective as TMX in preventing the progression of scoliotic curves in melatonin deficient bipedal mice.Wo
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