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1.
Chinese Journal of Traumatology ; (6): 356-359, 2021.
Article in English | WPRIM | ID: wpr-922709

ABSTRACT

PURPOSE@#The median time from the event leading to the spinal cord injury (SCI) to the time of decompressive surgery is estimated to be 6.9 days in Iran, which is much longer than the proposed ideal time (less than 24 h) in published guidelines. The current qualitative study aimed to determine the reasons for the observed decompression surgery delay in Iran from the perspective of neurosurgeons.@*METHODS@#This qualitative study is designed to perform content analysis on the gathered data from face-to-face semi-structured interviews with 12 Iranian neurosurgeons.@*RESULTS@#The findings of the current study suggest that patient-related factors constitute more than half of the codes extracted from the interviews. Overall, the type of injury, presence of polytrauma, and surgeons' wrong attitude are the main factors causing delayed spinal cord decompression in Iranian patients from the perspective of neurosurgeons. Other notable factors include delay in transferring patients to the trauma center, delay in availability of necessary equipment, and scarce medical personnel.@*CONCLUSION@#In the perspective of neurosurgeons, the type of injury, presence of polytrauma, and surgeons' wrong attitude are the leading reasons for delayed decompressive surgery of individuals with SCI in Iran.


Subject(s)
Humans , Decompression , Iran , Neurosurgeons , Spinal Cord Injuries/surgery
2.
Asian Pacific Journal of Tropical Medicine ; (12): 448-455, 2020.
Article in Chinese | WPRIM | ID: wpr-951136

ABSTRACT

Objective: To determine the significance of temperature, rainfall and humidity in the seasonal abundance of Anopheles stephensi in southern Iran. Methods: Data on the monthly abundance of Anopheles stephensi larvae and adults were gathered from earlier studies conducted between 2002 and 2019 in malaria prone areas of southeastern Iran. Climatic data for the studied counties were obtained from climatology stations. Generalized estimating equations method was used for cluster correlation of data for each study site in different years. Results: A significant relationship was found between monthly density of adult and larvae of Anopheles stephensi and precipitation, max temperature and mean temperature, both with simple and multiple generalized estimating equations analysis (P<0.05). But when analysis was done with one month lag, only relationship between monthly density of adults and larvae of Anopheles stephensi and max temperature was significant (P<0.05). Conclusions: This study provides a basis for developing multivariate time series models, which can be used to develop improved appropriate epidemic prediction systems for these areas. Long-term entomological study in the studied sites by expert teams is recommended to compare the abundance of malaria vectors in the different areas and their association with climatic variables. Abbasi Madineh 1 Deparment of Medical Entomology & Vector Control, School of Public Health, Tehran University of Medical Sciences, Tehran; Infectious and Tropical Diseases Research Center,Tabriz University of Medical Sciences, Tabriz Rahimi Foroushani Abbas 2 Department of Epidemiology and Biostatistics, School of Public Health, Tehran University of Medical Sciences, Tehran Jafari-Koshki Tohid 3 Molecular Medicine Research Center; Department of Statistics and Epidemiology, Faculty of Health, Tabriz University of Medical Sciences, Tabriz Pakdad Kamran 4 Department of Parasitology & Mycology, Paramedical School, Shahid Beheshti University of Medical Sciences, Tehran Vatandoost Hassan 5 Deparment of Medical Entomology & Vector Control, School of Public Health, Tehran University of Medical Sciences, Tehran Hanafi-Bojd Ahmad 6 Deparment of Medical Entomology & Vector Control, School of Public Health, Tehran University of Medical Sciences, Tehran WHO. Malaria report 2019. Geneva: WHO; 2019. Vatandoost H, Raeisi A, Saghafipour A, Nikpour F, Nejati J. Malaria situation in Iran: 2002-2017. Malar J 2019; 18: 200. Hanafi-Bojd AA, Azari-Hamidian S, Vatandoost H, Charrahy Z. Spatio-temporal distribution of malaria vectors (Diptera: Culicidae) across different climatic zones of Iran. Asian Pac J Trop Med 2011; 6: 498-504. Vatandoost H, Oshaghi MA, Abaie MR, Shahi M, Yaghoobi F, Baghaii M, et al. Bionomics of Anopheles stephensi Liston in the malarious area of Hormozgan Province, southern Iran. Acta Trop 2006; 97(2): 196-203. Faulde MK, Rueda LM, Khaireh BA. First record of the Asian malaria vector Anopheles stephensi and its possible role in the resurgence of malaria in Djibouti, Horn of Africa. Acta Trop 2014; 139: 39-43. Gayan Dharmasiri G, Yashan Perera A, Harishchandra J, Herath H, Aravindan K, Jayasooriya HTR, et al. First record of Anopheles stephensi in Sri Lanka: A potential challenge for prevention of malaria reintroduction. Malar J 2017; 16: 326. Carter TE, Yared S, Gebresilassie A, Bonnell V, Damodaran L, Lopez K, et al. First detection of Anopheles stephensi Liston, 1901 (Diptera: Culicidae) in Ethiopia using molecular and morphological approaches. Acta Trop 2018; 188: 180-186. Zhou G, Munga S, Minakawa N. Spatial relationship between adult malaria vector abundance and environmental factors in western Kenya highlands. Am J Trop Med Hyg 2007; 77(1): 29-35. Bashar K, Tuno N. Seasonal abundance of Anopheles mosquitoes and their association with meteorological factors and malaria incidence in Bangladesh. Parasites Vectors 2014; 7: 442. Gardiner LS. Climate change and vector-borne disease. University Corporation for Atmospheric Research. 2018. [Online]. Available from: https://scied.ucar.edu/longcontent/climate-change-and-vector-borne- disease [Accessed on 9 June 2019]. Patz JA, Lindsay SW. New challenges, new tools: The impact of climate change on infectious diseases. Curr Opin Microbiol 1999; 2(4): 445-451. Khormi HM, Kumar L. Future malaria spatial pattern based on the potential global warming impact in South and Southeast Asia. Geospat Health 2016; 11(3). doi: 10.4081/gh.2016.416. Ren Z, Wang D, Ma A, Hwang J, Bennett A, Sturrock HJW, et al. Predicting malaria vector distribution under climate change scenarios in China: Challenges for malaria elimination. Sci Rep 2016; 6: 20604. Campbell-lendrum D, Woodruff R. Climate change: Quantifying the health impact at national and local levels. Geneva: World Health Organization; 2007. Hanafi-Bojd AA. Using of remote sensing and geographical information system for estabiling a malaria monitoring system in the Bashadgard endemic focus, Hormozgan Province, Iran. Ph.D. Thesis. Tehran University of Medical Sciences; 2010. No. 4526. Mohammadkhani M, Khanjani N, Bakhtiari B, Sheikhzadeh K. The relation between climatic factors and malaria incidence in Kerman, South East of Iran. Parasite Epidemiol Control 2016; 1: 205-210. Statistical Center of Iran. Country statistical yearbook. 1st ed. Iran: Management & Planning Organization; 2018, p.100-120. Basseri HR, Moosakazemi SH, Yosafi S. Mohebali M, Hajaran H, Jedari M. Anthropophily of malaria vectors in Kahnouj district, south of Kerman, Iran. Iran J Public Health 2005; 34(2): 27-35. Fathian M, Vatandoost H, Moosa-Kazemi H, Raeisi A, Yaghoobi-Ershadi MR, Oshaghi MA, et al. Susceptibility of Culicidae mosquitoes to some insecticides recommended by WHO in a malaria endemic area of Southeastern Iran. J Arthropod-Borne Dis 2015; 9(1): 22-34. Mojahedi A, Basseri HR, Raeisi A, Pakari A. Bioecological characteristics of malaria vectors in different geographical areas of Bandar Abbas County, 2014. J Prev Med 2016; 3(1): 18-25. Nedjati J. The study on some bioecological characteristics of malaria vectors and monitoring of their suseptibility levels to some insecticides in Sarbaz county, Sistan va Baluchestan province. MSc. Thesis. Tehran University of Medical Sciences; 2011. No. 5046. Poudat A. Epidemiological survey of malaria in Bandar Abbas County, 1998-2002. MSc. Thesis. Tehran University of Medical Sciences; 2003. No. 3375. Yeryan M, Basseri HR, Hanafi-Bojd AA, Raeisi A, Edalat H, Safari R. Bio-ecology of malaria vectors in an endemic area, Southeast of Iran. Asian Pac J Trop Med 2016; 9(1): 32-38. Iran Meteorological Organization. Specialized products and services weather. 2019. [Online]. Available from: https://data.irimo.ir/ [Accessed on 10 April 2019]. Cui J. QIC program and model selection in GEE analyses. Stata J 2007; 7(2): 209-220. Aytekin S, Aytekin AM, Alten B. Effect of different larval rearing temperatures on the productivity (R0) and morphology of the malaria vector Anopheles superpictus Grassi (Diptera: Culicidae) using geometric morphometrics. J Vec Ecol 2009; 34: 32-42. Lardeux FJ, Tejerina RH, Quispe V, Chavez TK. A physiological time analysis of the duration of the gonotrophic cycle of Anopheles pseudopunctipennis and its implications for malaria transmission in Bolivia. Malar J 2008; 7: 141. Simon-Oke IA, Olofintoye LK. The effect of climatic factors on the distribution and abundance of mosquito vectors in Ekiti State. J Biol Agri Healthcare 2015; 5(9): 142-146. Jemal Y, Al-Thukair AA. Combining GIS application and climatic factors for mosquito control in Eastern Province, Saudi Arabia. Saudi J Biol Sci 2016; 25(8):1593-1602. Msugh-Ter MM, Aondowase DA, Terese AE. Association of meteorological factors with two principal malaria vector complexes in the University of Agriculture Makurdi community, Central Nigeria. Am J Entomol 2017; 1(2): 31-38. [31 ]Kabbale FG, Akol AM, Kaddu JB, Ambrose W. Biting patterns and seasonality of Anopheles gambiae sensu lato and Anopheles funestus mosquitoes in Kamuli District, Uganda Onapa. Parasit Vectors 2013; 6: 340. Paaijmans KP, Wandago OM, Githeko AK, Takken W. Unexpected high losses of Anopheles gambiae larvae due to rainfall. PLoS One 2007; 2(11): e1146. Gillooly JF, Brown JH, West GB, Savage VM, Charnov EL. Effects of size and temperature on metabolic rate. Science 2001; 293: 2248-2251. Koenraadt CJ, Paaijmans KP, Schneider P, Githeko AK, Takken W. Low level vector survival explains unstable malaria in the western Kenya highlands. Trop Med Int Health 2006; 11(8): 1195-1205. Munga S, Minakawa N, Zhou G, Githeko AK, Yan G. Survivorship of immature stages of Anopheles gambiae s.l. (Diptera: Culicidae) in natural habitats in western Kenya highlands. J Med Entomol 2007; 44: 758-764. Afrane YA, Zhou G, Lawson BW, Githeko AK, Yan G. Effects of microclimatic changes due to deforestation on the survivorship and reproductive fitness of Anopheles gambiae in Western Kenya Highlands. Am J Trop Med Hyg 2006; 74: 772-778. Afrane YA, Githeko AK, Yan G. The Ecology of Anopheles mosquitoes under climate change: Case studies from the effects of environmental changes in East Africa highlands. Ann Acad Sci 2012; 1249: 204-210. Abbasi F, Babaeian I, Malboosi SH, Asmari M, Mokhtari LG. Climate change assessment over Iran during future decades, using statistical downscaling of ECHO-G model. J Geogr Res 2012; 104: 205-230 (In Persian).

3.
IJFS-International Journal of Fertility and Sterility. 2017; 11 (2): 117-122
in English | IMEMR | ID: emr-186839

ABSTRACT

Background: The most common chromosomal abnormality due to non-obstructive azoospermia [NOA] is Klinefelter syndrome [KS] which occurs in 1-1.72 out of 500-1000 male infants. The probability of retrieving sperm as the outcome could be asymmetrically different between patients with and without KS, therefore logistic regression analysis is not a well-qualified test for this type of data. This study has been designed to evaluate skewed regression model analysis for data collected from microsurgical testicular sperm extraction [micro-TESE] among azoospermic patients with and without non-mosaic KS syndrome


Materials and Methods: This cohort study compared the micro-TESE outcome between 134 men with classic KS and 537 men with NOA and normal karyotype who were referred to Royan Institute between 2009 and 2011. In addition to our main outcome, which was sperm retrieval, we also used logistic and skewed regression analyses to compare the following demographic and hormonal factors: age, level of follicle stimulating hormone [FSH], luteinizing hormone [LH], and testosterone between the two groups


Results: A comparison of the micro-TESE between the KS and control groups showed a success rate of 28.4% [38/134] for the KS group and 22.2% [119/537] for the control group. In the KS group, a significantly difference [P<0.001] existed between testosterone levels for the successful sperm retrieval group [3.4 +/- 0.48 mg/mL] compared to the unsuccessful sperm retrieval group [2.33 +/- 0.23 mg/mL]. The index for quasi Akaike information criterion [QAIC] had a goodness of fit of 74 for the skewed model which was lower than logistic regression [QAIC=85]


Conclusion: According to the results, skewed regression is more efficient in estimating sperm retrieval success when the data from patients with KS are analyzed. This finding should be investigated by conducting additional studies with different data structures

4.
Iranian Journal of Public Health. 2013; 42 (6): 602-609
in English | IMEMR | ID: emr-148145

ABSTRACT

This study was conducted to investigate the effects of Brewer's yeast supplementation on serum lipoproteins and blood pressure in patients with Type 2 diabetes mellitus. In a randomized double blind clinical trial, 90 adults with type 2 diabetes mellitus were recruited, and divided randomly into 2 groups, trial group received brewer's yeast [1800 mg/day] and control group received placebo for 12 weeks. Weight, BMI, food consumption [based on 24 hour food recall], fasting serum lipoproteins [Cholesterol, Triglyceride, LDL-c, HDL-c], systolic and diastolic blood pressures were measured before and after the intervention. Data analyses were performed by Statistical Package for Social Sciences ver. 18.0, and the statistical tests included Independent t-test, Paired t-test, Kolmogorov-Smirnov and analysis of covariance. This trial was registered in Iranian Registry of Clinical Trials [IRCT], No.IRCT138807062513N1. Eighty-four subjects [21 men and 63 women] aged 46.3 +/- 6.1 years completed the study. After 12 weeks supplementation, systolic and diastolic blood pressures were decreased in the group receiving brewer's yeast [4.1 +/- 1.5, P = 0.007 and 5.7 +/- 0.6, P = 0.001 respectively]. No-significant changes in LDL-c, HDL-c, Triglyceride and Cholesterol were shown. Supplementation with Brewer's yeast besides the usual treatment of type 2 diabetes mellitus can reduce systolic and diastolic blood pressures in diabetic patients

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