Socioeconomic disparities in using rehabilitation services among Iranian adults with disabilities: a decomposition analysis.

BACKGROUND: Persons with disabilities (PWD) generally experience various barriers in using health care compared to the general population, and these problems are more worsened for those with disabilities in lower socioeconomic status. The study aimed to estimate socioeconomic inequality in using rehabilitation services (URS) in adults with disabilities in Iran. METHODS: This cross-sectional study was conducted at a national level in Iran. 786 PWD (aged 18 years and older) participated in the study between September and December 2020. Socioeconomic-related inequality in URS was estimated by the Concentration Index (C). The C was decomposed to identify factors explaining the variability within the socioeconomic inequality in URS. RESULTS: In the present study 8.10% (N = 61) of the study population used rehabilitation services during the past three months. In this study, the value of the C was estimated 0.25 (p-value = 0.025) that shows URS was unequally distributed, and concentrated among the higher SES groups. The results of decomposition analysis indicated that the wealth index was the largest contributor (94.22%) to the observed socioeconomic inequalities in URS among PWD. Following the wealth index, Age and marital status were the major contributors to the unequal distribution of URS among the study population. CONCLUSIONS: Our findings revealed that socioeconomic inequality in using rehabilitation services was concentrated among well-off PWD. Accordingly, rehabilitation financing through appropriate mechanisms for individuals with low SES is suggested.

Investigating the effects of post-discharge care services for patients with severe psychiatric illnesses on their caregivers' burnout in Sanandaj.

Family-based caregivers of psychiatric patients are the backbone of the healthcare system and are, in fact, generally considered as patients themselves. Their commitment and obligation to take care of the in-need and disabled patients in the family can lead to their psychological destruction. This paper attempts to investigate the effects of post-discharge care for patients with severe psychiatric illnesses on the burnout of their caregivers in the Qods Hospital of Sanandaj. This before-after study was performed on 72 subjects divided into two groups of 36, all of whom were chosen from the caregivers of the case and control subjects from family members of the psychiatric patients discharged from Qods psychiatric hospital in 2016. The study was effectively conducted with a control group design. The case group included patients who received home-care services after being discharged, and the caregiver group received nothing but regular care. First, using the hospital files, personal characteristics and diagnosis of the patient were recorded, thus the caregivers' characteristics and their burnout and psychological exhaustion severity were collected by caregiver burden inventory. The data were presented using descriptive-analytic indexes. The results represented that most of the caregivers (95.8%) suffered from moderate to severe burdens at the time of discharge. In using the Kolmogorov-Smirnov test, pre-test scores in two groups supported the normal hypotheses of the data (P = 0.55). Also, the level of significance in the covariance test showed the efficacy of intervention after the test (P = 0.000). In this study, most of the patients' caregivers with severe mental illnesses suffered from moderate to a severe burden, which, of course, seems to be more than other similar studies. Differences in social, cultural, and special regional conditions, as well as the type of applied questionnaire, were of significance. However, despite the mentioned difference, as it is true for other similar studies in Iran and other countries, home-care services have a significant effect on reducing the caregivers' burden after one year. Researches could, besides reducing the burnout of caregivers, provide a model which could help patients in the deprived areas without removing cultural and family roots and without diminishing the role of the family.

Factors affecting driver injury severity in fatigue and drowsiness accidents: a data mining framework.

BACKGROUND: Fatigue and drowsiness accidents are more likely to cause serious injuries and fatalities than other accidents. Statistics revealed that 20 to 40 percent of traffic accidents in Iran are due to drivers' fatigue. This study identified the most important factors affecting driver injuries in fatigue and drowsiness accidents. METHODS: The Classification and Regression Tree method (CART) was applied 11,392 drivers were in-volved in fatigue and drowsiness accidents in three provinces of Iran, over the 7 years from 2011-2018. A two-level target variable was used to increase the accuracy of the model. First, dataset in each of three provinces was classified into homogeneous clusters using a two-step clus-tering algorithm. Oversampling method was used for imbalanced accident severity datasets. Then, classification was improved by boosting method. RESULTS: The classification tree reveals that the month, time of day, collision type, and vehicle type were common factors. Also, driver's age was important in female drivers cluster; the geometry of the place and seat belt/helmet usage were important in urban roads cluster; and area type, road type, road direction, and vehicle factor were important in rural roads cluster. Also, the combination of the CART algorithm with oversampling and boosting increased the accuracy of the models. CONCLUSIONS: The analysis results revealed motorcycles, lack of using a helmet or seat belt, curvy roads, roads with two-way undivided and one-way movement direction increased the injury and death of drivers. Collision with fixed object, run-off-road, overturning, falling, and defective vehicles increased the severity of accidents. Female drivers older than 44 years old have a higher probability of fatality. Identifying the factors affecting the severity of driver injuries in such accidents in each province could assist in determining engineering countermeasures and training educational programs to mitigate these crash severities.

Co-administration of GnRH agonists with vaginal progesterone compared to vaginal progesterone in luteal phase support of the frozen-thawed embryo transfer cycle: An RCT.

BACKGROUND: Since progesterone alone does not seem to be enough for luteal phase support (LPS), especially in frozen embryo transfer (FET) cycles, so gonadotropin-releasing hormone agonist (GnRH-a) is suggested as an adjuvant therapy in combination with progesterone for LPS. OBJECTIVE: To evaluate the effects of the administration of GnRH-a with vaginal progesterone compared to vaginal progesterone alone in luteal phase support of the frozen-thawed embryo transfer cycles. MATERIALS AND METHODS: In this randomized controlled clinical trial, 240 infertile women who were candidates for FET were evaluated into two groups (n = 120/each). Group I received 400 mg vaginal progesterone twice a day from the time of transfer. The second group received vaginal progesterone and also 0.1 mg diphereline on days 0, 3, and 6 of FET for LPS. Finally, the clinical and ongoing pregnancy rates, and the implantation, and spontaneous abortion rates were compared in two groups. RESULTS: Results showed that there was no significant difference between the mean age of women and the duration of infertility (p = 0.78, p = 0.58, respectively). There were no significant differences between groups in the terms of implantation and spontaneous abortion rates (p = 0.19, p = 0.31, respectively). However, in terms of clinical and ongoing pregnancy rates, the significant differences were seen between groups (p = 0.008 and p = 0.005, respectively). CONCLUSION: Co-administration of GnRH-a and vaginal progesterone in LPS may be superior to vaginal progesterone alone in women who underwent a frozen-selected embryo transfer cycle.

Tracking leukocytes in intravital time lapse images using 3D cell association learning network.

Leukocytes are key cellular elements of the innate immune system in all vertebrates, which play a crucial role in defending organisms against invading pathogens. Tracking these highly migratory and amorphous cells in in vivo models such as zebrafish embryos is a challenging task in cellular immunology. As temporal and special analysis of these imaging datasets by a human operator is quite laborious, developing an automated cell tracking method is highly in demand. Despite the remarkable advances in cell detection, this field still lacks powerful algorithms to accurately associate the detected cell across time frames. The cell association challenge is mostly related to the amorphous nature of cells, and their complicated motion profile through their migratory paths. To tackle the cell association challenge, we proposed a novel deep-learning-based object linkage method. For this aim, we trained the 3D cell association learning network (3D-CALN) with enough manually labelled paired 3D images of single fluorescent zebrafish's neutrophils from two consecutive frames. Our experiment results prove that deep learning is significantly applicable in cell linkage and particularly for tracking highly mobile and amorphous leukocytes. A comparison of our tracking accuracy with other available tracking algorithms shows that our approach performs well in relation to addressing cell tracking problems.

Tracking Neutrophil Migration in Zebrafish Model Using Multi-Channel Feature Learning.

Tracking cells over time is crucial in the fields of computer vision and biomedical science. Studying neutrophils and their migratory profile is the highly topical fields in inflammation research due to determining role of these cells during immune responses. As neutrophils generally are of various shapes and motion, it remains challenging to track and describe their behaviours from multi-dimensional microscopy datasets. In this study, we propose a robust novel multi-channel feature learning (MCFL) model inspired by deep learning to extract the complex behaviour of neutrophils moved in time lapse images. In this model, the convolutional neural networks along with cell relocation distance and orientation channels learn the robust significant spatial and temporal features of an individual neutrophil. Additionally, we also proposed a new cell tracking framework to detect and track neutrophils in the original time-laps microscopy images, entails sampling, observation, and visualisation functions. Our proposed cell tracking-based-multi channel feature learning method has remarkable performance in rectifying common cell tracking problem compared with state-of the-art methods.

N-acetylcysteine as an adjunct to risperidone for treatment of negative symptoms in patients with chronic schizophrenia: a randomized, double-blind, placebo-controlled study.

OBJECTIVES: Despite the burden of negative symptoms on quality of life in schizophrenic patients, no completely effective treatment has been developed to address such symptoms yet. Abnormalities in oxidative stress pathways have been recently demonstrated to be involved in the pathophysiology of schizophrenia, and a growing interest in antioxidant agents is emerging for targeting negative symptoms of schizophrenia. N-Acetylcysteine (NAC) is a potent antioxidant with neuroprotective properties. This study aimed to evaluate the possible effects of NAC as an adjunct to risperidone in treating negative symptoms of schizophrenia. MATERIALS AND METHODS: In this randomized, double-blind, placebo-controlled, parallel-group study, 42 patients with chronic schizophrenia and a score of 20 or greater on the negative subscale of positive and negative syndrome scale (PANSS) were enrolled in the active phase of their illness. The participants were equally randomized to receive NAC (up to 2 g/d) or placebo, in addition to risperidone (up to 6 mg/d) for 8 weeks. The participants were rated using PANSS every 2 weeks, and the decrease of PANSS negative subscale score was considered as our primary outcome. RESULTS: By the study end point, NAC-treated patients showed significantly greater improvement in the PANSS total (P = 0.006) and negative subscale (P < 0.001) scores than that in the placebo group, but this difference was not significant for positive and general psychopathology subscales. There was no significant difference between the 2 groups in the frequency of adverse effects. CONCLUSIONS: NAC add-on therapy showed to be a safe and effective augmentative strategy for alleviating negative symptoms of schizophrenia.