Maedeh Gholamazad, Jafar Pourmahmoud, Alireza Atashi, Mehdi Farhoudi and Reza Deljavan Anvari
A stroke is a serious, life-threatening condition that occurs when the blood supply to a part of the brain is cut off. The earlier a stroke is treated, the less damage is likely…
Abstract
Purpose
A stroke is a serious, life-threatening condition that occurs when the blood supply to a part of the brain is cut off. The earlier a stroke is treated, the less damage is likely to occur. One of the methods that can lead to faster treatment is timely and accurate prediction and diagnosis. This paper aims to compare the binary integer programming-data envelopment analysis (BIP-DEA) model and the logistic regression (LR) model for diagnosing and predicting the occurrence of stroke in Iran.
Design/methodology/approach
In this study, two algorithms of the BIP-DEA and LR methods were introduced and key risk factors leading to stroke were extracted.
Findings
The study population consisted of 2,100 samples (patients) divided into six subsamples of different sizes. The classification table of each algorithm showed that the BIP-DEA model had more reliable results than the LR for the small data size. After running each algorithm, the BIP-DEA and LR algorithms identified eight and five factors as more effective risk factors and causes of stroke, respectively. Finally, predictive models using the important risk factors were proposed.
Originality/value
The main objective of this study is to provide the integrated BIP-DEA algorithm as a fast, easy and suitable tool for evaluation and prediction. In fact, the BIP-DEA algorithm can be used as an alternative tool to the LR model when the sample size is small. These algorithms can be used in various fields, including the health-care industry, to predict and prevent various diseases before the patient’s condition becomes more dangerous.
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Yalda Sadeghpour, Aliakbar Taheraghdam, Mohammad Khalili, Mazyar Hashemilar, Elyar Sadeghi Hokmabadi, Sheyda Shaafi, Mehdi Farhoudi, Seyed Kazem Shakouri, Nasim Rezaeimanesh and Daryoush Savadi Osgouei
Although the pathogenesis of stroke is not yet completely elucidated, factors such as oxidative stress and inflammation have been shown to play an important role in this regard…
Abstract
Purpose
Although the pathogenesis of stroke is not yet completely elucidated, factors such as oxidative stress and inflammation have been shown to play an important role in this regard. The purpose of this paper is to investigate the effects of whey protein plus lipoic acid on the inflammatory and oxidative stress markers and the prognosis in acute ischemic stroke (AIS) patients.
Design/methodology/approach
A double-blind, randomized controlled clinical trial was conducted among 42 patients with the first episode of AIS at the Imam Reza Hospital of the Tabriz University of Medical Sciences. The blind research staff randomly assigned patients to two groups of receiving usual hospital gavage (control group) and 1,200 mg of lipoic acid plus 20 g of whey protein in addition to usual hospital gavage (intervention group) for midday meal. Levels of albumin, Interleukin-6 (IL-6), tumor necrosis factor (TNF-α), high-sensitivity C-reactive protein (hs-CRP) and clinical outcomes including severity of neurologic damage according to National Institutes of Health Stroke Scale (NIHSS) and functional state based on modified Rankin Scale (mRS) were evaluated initially and three weeks later.
Findings
There were no significant differences in demographic and baseline characteristics between the two groups (p > 0.05). After three weeks, hs-CRP (p <* 0.01), IL-6 (p = 0.02) and TNF-α (p = 0.01) levels significantly reduced in the intervention group, but no significant changes were observed in cases of albumin, malondialdehyde (MDA) and total antioxidant capacity (TAC) in this group (p > 0.05). Instead, only IL-6 decreased significantly in the control group (p <* 0.01). In addition, comparing changes of assessed variables between two groups showed no significant improvement in the whey protein plus lipoic acid supplementation group vs the control group (p > 0.05). While there was significant betterment in clinical prognosis parameters within groups, no significant changes were found between groups.
Originality/value
The investigation implied that whey protein plus lipoic acid supplementation has no significant effects on inflammatory and oxidative stress markers compared to the control group of AIS patients. More studies in this field are needed to approve the result.
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Behnam Farhoudi, SeyedAhmad SeyedAlinaghi, Omid Dadras, Mehrzad Tashakoriyan, Mohammad Nazari Pouya, Mohammad Mehdi Gouya and Kate Dolan
The aim of present study was to integrate vital noncommunicable diseases (coronary artery disease, hypertension, diabetes mellitus and mental health disorders) into Prison-Based…
Abstract
Purpose
The aim of present study was to integrate vital noncommunicable diseases (coronary artery disease, hypertension, diabetes mellitus and mental health disorders) into Prison-Based Active Health Services Provision (PAHSP).
Design/methodology/approach
On Jan 1, 2018, there were 230,000 prisoners in Iran. Timely and systematic detection and diagnosis of chronic health conditions among this population are imperative. The collaboration between healthcare providers in prison and members of the multidisciplinary team of the healthcare community outside prison initiated an active health service provision approach for HIV and tuberculosis (TB). Guidelines for the control of HIV and TB in prison were piloted, and the finalized version was named “Prison-based Active Health Services Provision” (PAHSP), which has been scaled up in 16 of 260 Iranian prisons.
Finding
The PAHSP approach emphasizes the importance of early identification of key symptoms and risk factors. This approach provides an opportunity for improved prevention and treatment, enabling prisoners identified at risk or those who have been diagnosed with a target disease to be followed up and receive the appropriate health care.
Originality/value
Initiatives such as screening for chronic health conditions coupled with treatment will reduce the burden of chronic illness among prisoners and the broader community, thereby saving on healthcare costs and lives.
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Jafar Pourmahmoud and Maedeh Gholam Azad
The purpose of this paper is to propose the data envelopment analysis (DEA) model that can be used as binary-valued data. Often the basic DEA models were developed by assuming…
Abstract
Purpose
The purpose of this paper is to propose the data envelopment analysis (DEA) model that can be used as binary-valued data. Often the basic DEA models were developed by assuming that all of the data are non-negative. However, there are situations where all data are binary. As an example, the information on many diseases in health care is binary data. The existence of binary data in traditional DEA models may change the behavior of the production possibility set (PPS). This study defines a binary summation operator, expresses the modified principles and introduces the extracted PPS of axioms. Furthermore, this study proposes a binary integer programming of DEA (BIP-DEA) for assessing the efficiency scores to use as an alternate tool in prediction.
Design/methodology/approach
In this study, the extracted PPS of modified axioms and the BIP-DEA model for assessing the efficiency score is proposed.
Findings
The binary integer model was proposed to eliminate the challenges of the binary-value data in DEA.
Originality/value
The importance of the proposed model for many fields including the health-care industry is that it can predict the occurrence or non-occurrence of the events, using binary data. This model has been applied to evaluate the most important risk factors for stroke disease and mechanical disorders. The targets set by this model can help to diagnose earlier the disease and increase the patients’ chances of recovery.
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Ghobad Moradi, Amjad Mohamadi-Bolbanabad, Sonia Darvishi, Fatemeh Azimian Zavareh, Bakhtiar Piroozi, Bushra Zareie, Mohammad-Mehdi Gouya and Mehrzad Tashakorian
The purpose of this paper is to determine patterns of sexual behaviors and related factors among prisoners in Iran, 2015.
Abstract
Purpose
The purpose of this paper is to determine patterns of sexual behaviors and related factors among prisoners in Iran, 2015.
Design/methodology/approach
This cross-sectional study was a part of a bio-behavioral surveillance survey conducted on 6,200 prisoners in 26 prisons in Iran. The subjects were selected through multi-stage sampling. Questionnaires and interviews were used to collect data on participant’s demographics and history of sexual behaviors. Using STATA-12 software, the collected data were analyzed through descriptive statistics, and crude and adjusted logistic regression.
Findings
A total of 5,508 prisoners with a response rate of 88.8 percent participated in this study. Of all prisoners, 55 percent (n=3,027) had a history of “unsafe sex in the lifetime” of whom 53.4 percent (n=1,549) never used condoms during unsafe sex in the lifetime. Based on the results of multivariate analysis, risk factors for “unsafe sex in lifetime” were the following: higher level of education (AOR=1.79, CI: 1.41–2.28), being single (AOR=1.32, CI: 1.18–1.47), unemployed before imprisonment (AOR=1.45, CI: 1.06–1.97), having history of previous imprisonment (AOR=1.31, CI: 1.17–1.47) and history of drug use in the lifetime (AOR=1.53, CI: 1.35–1.75).
Originality/value
Prisoners are high-risk groups that are prone to practice unsafe sex. Prisoners who are single, unemployed before imprisonment, a drug user, with a higher level of education and with a history of imprisonment are likely to be sexually active in their lifetime. Thus, they are a priority for receiving suitable interventions.
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Mohammad Mehdi Pouria, Abbas Akbarpour, Hassan Ahmadi, Mohammad Reza Tavassoli and Amir Saedi Daryan
Offshore structures are among the structures exposed to fire more often. Most of these structures are likely to be associated with flammable materials. In this research, some of…
Abstract
Purpose
Offshore structures are among the structures exposed to fire more often. Most of these structures are likely to be associated with flammable materials. In this research, some of the structures constructed on top of marine decks have been studied.
Design/methodology/approach
For this purpose, the upper-bound theory of plastic analysis has been used to investigate its collapse behavior. In this way, genetic algorithm has been used for application of the combination of elementary mechanisms in the classic plastic analysis problem.
Findings
The studied structures are optimized by plastic analysis theory before and after the fire and their failure modes are compared with each other. The comparison of the results indicates significant changes in the load factor value, as well as the critical collapse mode of the structure before and after the fire.
Originality/value
Results indicate that the combination of plastic analysis and a genetic algorithm can predict the collapse mode of the structure before and after the fire accurately.