Papers by parvin sarbakhsh
Frontiers in Cardiovascular Medicine
Background: Coronary heart disease (CHD) is the major cause of mortality in the world with a sign... more Background: Coronary heart disease (CHD) is the major cause of mortality in the world with a significant impact on the younger population. The aim of this study was to identify prematurity among patients with coronary artery bypass graft surgery (CABG) based on the clustering of CHD risk factors.Methods: Patients were recruited from an existing cohort of candidates for CABG surgery named Tehran Heart Center Coronary Outcome Measurement (THC-COM). A latent class analysis (LCA) model was formed using 11 potential risk factors as binary variables: cigarette smoking, obesity, diabetes, family history of CHD, alcohol use, opium addiction, hypertension, history of stroke, history of myocardial infarction (MI), peripheral vascular disease (PVD), and hyperlipidemia (HLP). We analyzed our data to figure out how the patients are going to be clustered based on their risk factors.Results: For 566 patients who were studied, the mean age (SD) and BMI of patients were 59.1 (8.9) and 27.3 (4.1), re...
Crescent Journal of Medical and Biological Sciences, Jul 29, 2022
Introduction Chronic kidney disease jeopardizes various aspects of a patient's health (1). In end... more Introduction Chronic kidney disease jeopardizes various aspects of a patient's health (1). In end-stage renal disease, alternative treatment methods such as hemodialysis should be used to replace the kidney functions and keep the patient alive (2). Patients undergoing hemodialysis experience many symptoms such as nausea, vomiting, decreased appetite, hypotension, muscle contractions, chest pain, headache, and fatigue, all of which adversely affect their daily functioning and quality of life (3). Fatigue is a prevalent and frustrating symptom among these patients (3-5). About one-third of patients experience fatigue an hour after starting a hemodialysis session and one-fourth of them feel tired at the end of each session (6). The chronic and debilitating nature of fatigue can restrict the patients' ability to perform their roles and daily activities and may even lead to job loss and increased dependence on health care. Given the high prevalence of fatigue in patients receiving hemodialysis (3-5) and the related adverse effects (7), special efforts should be made to reduce fatigue in these patients. Pharmacotherapy is often used as the first step to reduce the complications in hemodialysis patients (8). Despite the benefits of medicines, they are often prescribed and used for long periods and may cause several side effects (9). Therefore, some non-pharmacological complementary therapies have been tested to reduce these side effects (10). Aromatherapy is a holistic treatment approach used as a complementary therapy (11). In aromatherapy, volatile oils derived from some plants are used for the improvement of health. These herbal oils can be used through inhalation, aromatic compresses, baths, and massages (12). Damask rose (Rosa damascena), is one of the most widely used aromatic, therapeutic, and decorative plants. It is the main variety of Rosa planted to make rose water and rose oil, and is mainly used in the perfume and food industries (13). R. damascena, known as "Gol-e Mohammadi" in Iran (14), grows in a variety of climatic conditions (15). There are a variety of carotenoids, flavonoids, and vitamins in R. damascena (16), and its oil has sedative, hypnotic, calming, and antispasmodic effects (16-18). It also has beneficial effects on sleep quality, blood pressure, and even in relieving mild to moderate postoperative pain (19-21). Inhalation of some essential oils has been reported to Abstract Objectives: The prevalence of fatigue in patients receiving hemodialysis is high. This study aimed to investigate the effect of Rosa damascena oil on fatigue severity in patients receiving hemodialysis. Materials and Methods: This randomized controlled trial was performed on 74 patients receiving hemodialysis in Tabriz, Iran from January 21 to February 21, 2019. The patients were conveniently recruited and assigned into two groups of intervention and control using a block randomization method with block sizes of four and six and a sequence of 1:1. Patients in the intervention group were trained to inhale three drops of R. damascena oil each night for one month. We used the Fatigue Severity Scale (FSS) for data collection and analyzed the data using the independent samples and paired t tests. Results: No significant difference was found between the two groups respecting the mean baseline fatigue scores (P=0.12). However, at the end of the study, the mean fatigue score was significantly lower in the intervention group compared to the control group (P=0.001). Conclusions: We witnessed that R. damascena oil aromatherapy significantly reduced the severity of fatigue in patients receiving hemodialysis. This useful and inexpensive technique can be utilized as a complementary method to relieve fatigue in patients receiving hemodialysis.
Journal of Caring Sciences, 2021
Introduction:Developing new training methods for improving the health of diabetic patients has al... more Introduction:Developing new training methods for improving the health of diabetic patients has always been a concern for nurses. The present study aims to investigate the effects of empowerment-based interventions with or without telenursing on self-efficacy and HbA1c level in diabetic patients. Methods:In this randomized clinical trial, 156 patients with type-2 diabetes were randomly assigned into two intervention groups (empowerment with/without telenursing) and one control group. All subjects in the intervention groups participated in two sessions of the empowerment program. However, only the group of empowerment with telenursing received telephone counseling for 12 weeks. The patients in the control group did not receive any intervention programs. Self-efficacy was measured by diabetes-specific self-efficacy scale. The HbA1c level was measured using Bionic kit. Data were analyzed using SPSS Statistics for Windows, version 13.0 (SPSS Inc., Chicago, Ill., USA). Results:After 14 we...
Introduction Self-concept refers to an individual’s description of his/ her own characteristics (... more Introduction Self-concept refers to an individual’s description of his/ her own characteristics (1). According to Shavelson, it is a hierarchical phenomenon. At the first level, there is a general self-concept. The general self-concept is a set of beliefs that a person has about himself/herself, which is relatively difficult to change. The second level is divided into academic and non-academic levels (2). The occupational or professional self-concept can replace academic self-concept with a person’s maturity (3). Professional self-concept is regarded as a person’s perception of himself/herself as a professional, which influences his/her thinking, role development, behavior, and professional performance (4). It seems that a number of the academic disciplines and professions require a higher self-concept, among which nursing is of greater importance in this regard. Due to the nature of clinical environments, nursing students’ mental and psychological health is affected by stress which...
Schizophrenia Research, 2010
مجله دانشگاه علوم پزشکی رفسنجان, 2020
Neurological Sciences, 2022
Stroke is a global public health challenge. Frailty models can detect and consider the effects of... more Stroke is a global public health challenge. Frailty models can detect and consider the effects of the unknown factors influencing survival along with other known factors. This study aims to evaluate health care providers’ effect, along with the demographic and clinical factors, on the stroke patients’ survival by using the shared frailty survival models. In the 2-year follow-up, a total of 1036 patients with first-ever stroke were recruited from 2013 up to 2015 with census sampling method from two hospitals of Iran, as the health care providers. For model selection, we fitted parametric and semiparametric survival models with parametric shared frailty and used the goodness of fit criteria to compare the models. The median follow-up was 730 days. The rate of mortality was 38% during the follow-up period. The Weibull model with gamma frailty had a better fit than the other survival models. The significant variables from the Weibull model were NIHSS score as the stroke severity (score < 5: reference category; scores 5–19: HR = 2.99, p value < 0.001; score ≥ 20: HR = 5.66, p value < 0.001) and age (HR = 1.03, p value < 0.001). Even with the incorporation of the demographic and clinical factors in the survival model, the effect of health care providers as the shared frailty effect was significant (p < 0.001). Despite considering the known demographic and clinical prognostic factors, health care providers’ effect on the patients’ survival after stroke was still significant. This may be due to the existing difference between two hospitals in facilities, management, coordination, and efficiency of treatment.
Frontiers in Genetics, 2021
Ovarian cancer is the second most dangerous gynecologic cancer with a high mortality rate. The cl... more Ovarian cancer is the second most dangerous gynecologic cancer with a high mortality rate. The classification of gene expression data from high-dimensional and small-sample gene expression data is a challenging task. The discovery of miRNAs, a small non-coding RNA with 18–25 nucleotides in length that regulates gene expression, has revealed the existence of a new array for regulation of genes and has been reported as playing a serious role in cancer. By using LASSO and Elastic Net as embedded algorithms of feature selection techniques, the present study identified 10 miRNAs that were regulated in ovarian serum cancer samples compared to non-cancer samples in public available dataset GSE106817: hsa-miR-5100, hsa-miR-6800-5p, hsa-miR-1233-5p, hsa-miR-4532, hsa-miR-4783-3p, hsa-miR-4787-3p, hsa-miR-1228-5p, hsa-miR-1290, hsa-miR-3184-5p, and hsa-miR-320b. Further, we implemented state-of-the-art machine learning classifiers, such as logistic regression, random forest, artificial neural...
Journal of Education and Health Promotion, 2020
BACKGROUND AND OBJECTIVE: Data on the factors affecting long-term mortality following a stroke in... more BACKGROUND AND OBJECTIVE: Data on the factors affecting long-term mortality following a stroke in Iran are scarce. The current research aimed at investigating the extent of 2-year mortality following a stroke and the factors affecting it in the northwest of Iran. MATERIALS AND METHODS: This prospective cohort study was conducted in Tabriz, Northwest of Iran. Patients with computed tomography/magnetic resonance imaging confirmed the first-ever stroke were included in this study and followed up to 2 years. Clinical examinations, including the severity of the stroke using the modified National Institutes of Health Stroke Scale (mNIHSS), were conducted by a neurologist. The general characteristics, lifestyle factors, and laboratory tests were also completed. To estimate the survival, Kaplan–Meier analysis was used; and for group comparison, the log-rank method was applied. To identify the factors predicting 2-year mortality, semiparametric Cox regression analysis was used. RESULTS: A to...
Introduction: Detection of population at risk of type II diabetes, as a multi-factorial disease, ... more Introduction: Detection of population at risk of type II diabetes, as a multi-factorial disease, is an important issue because of its individual and social impacts. To date, several studies have been conducted to predict the incidence of diabetes, using different statistical methods. However, despite its clinical importance, it is highly difficult to consider all interactions among risk factors, in ordinary statistical models. This study aimed to extract appropriate logic combination of type 2 diabetes risk factors employing the recently introduced method, Logic regression. Materials and Methods: The study population was selected from a cohort of the Tehran Lipid and Glucose Study (TLGS). Data for 3523 participants, aged 20 years and over (57.8% female and 42.2% male) were entered into analysis, for which logistic logic regression method was used. The model parameters were estimated using the Annealing algorithm. To avoid overestimation, the optimal number of logic combinations was determined by the cross-validation method. Deviance, sensitivity and specificity measures were computed to evaluate the logic model and its comparison to ordinary logistic regression; the latter accommodated only the main effects. The prediction power of the two models was compared by Area under ROC curve. R software version 2.8.1 was employed for analyses. Results: Logistic logic regression with the 4 Boolean combination including 5 variables was fitted using the Annealing algorithm and resulted in in deviance of 1203.30. This model had better fit compared to other logic models and also ordinary logistic regression with forward procedure (deviance=1206.88). The Boolean combination of the above model included impaired fasting glucose (OR=5.53, 95%CI: 4.03-7.59), IGT (OR=5.54, 95%CI: 3.96-7.49), family history of diabetes (OR=1.89, 95%CI: 1.38-2.63), and interaction of high triglycerides or abnormal waist circumference (OR=2.4, 95%CI: 1.73-3.32); all p-values <0.001. The area under ROC curve for the model was 0.843 (95%CI: 0.813-0.874). Conclusion: This study showed that the logic regression as a newly introduced method has the ability of recognizing and modelling the interactions between different risk factors. Therefore, it is recommended as an appropriate tool for screening of the multi-factorial diseases such as diabetes.
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Papers by parvin sarbakhsh