ABSTRACT
Background@#Since the emergence of coronavirus disease 2019 (COVID-19), various clinical manifestations ranging from asymptomatic to severe, life-threatening courses have been presented. It is well known that COVID-19 patients are at an increased risk of pulmonary thromboembolism (PTE) development; however, the associated demographic, medical, and clinical factors for developing PTE remain unknown. The current study aimed to assess the characteristics of patients with PTE. @*Methods@#This case-control study was derived from an ongoing population-based investigation of hospitalized patients with COVID-19 pneumonia. The case group included 99 patients with PTE confirmed by computed tomography pulmonary angiography (CTPA), and the controls (N=132) were age-matched patients selected from the PTE-suspected patients with a negative CTPA. The demographic, medical, and clinical characteristics of the study population were entered into the study checklist and compared. A logistic regression test was used to determine the factors associated with PTE development. @*Results@#Among the 13,099 admitted patients, 690 (5.26%) were suspected of having PTE according to their clinical manifestations. CTPA was performed for suspected cases, and PTE was confirmed in 132 patients (19.13%). Logistic regression assessments revealed that male gender (OR, 2.39; 95%CI, 1.38‒4.13), decreased oxygen saturation (OR, 2.33; 95%CI, 1.27‒4.26), and lower hemoglobin (OR, 0.83, 0.95), and albumin (OR, 0.31; 95%CI, 0.18‒0.53) levels were associated with PTE development. @*Conclusion@#PTE was confirmed in one-fifth of suspected patients who underwent CTPA imaging. Male sex, decreased oxygen saturation, and lower levels of hemoglobin and albumin were independent predictors of PTE in patients with COVID-19 pneumonia.
ABSTRACT
Background: Routine reporting of sexually transmitted infections [STIs] in Iran is one of the main information sources on STIs, endures some diminution under influence of several factors. We aimed to adjust registered STI data with a model-based approach and estimate the incidence and prevalence of STIs in Iran
Methods: In this cross-sectional study, we developed a stochastic compartmental model considering effects of influential factors on STI reporting process to adjust registered STI data. We reviewed literature and used Delphi method to collect data and estimate model parameters. We calibrated the model using Monte Carol simulation with 95% confidence interval [CI]. Finally, we validated the models by comparing their output with investigational data
Results: The estimated prevalence of male urethral discharge was 0.40% [95% CI: 0.26%, 0.65%]; the prevalence of genital ulcers was 3.68% [95% CI: 2.31%, 6.43%] in women and 0.16% [95% CI: 0.10%, 0.27%] in men. The estimated incidence for Neisseria gonorrhoeae, Chlamydia trachoma and syphilis per 1000 women was 2.44 [95% CI: 1.17, 6.65], 5.02 [95% CI: 2.78, 10.16] and 0.04 [95% CI: 0.02, 0.05] respectively; the corresponding figures per 1000 men were 0.43 [95% CI: 0.26, 0.80], 0.82 [95% CI: 0.42, 1.92] and 0.005 [95% CI: 0.003, 0.008]
Conclusions: Various factors are responsible for the obvious underestimation in the number of STIs registered in Iran. Notwithstanding this underestimation, our models offer an indirect method of estimating the prevalence of STIs in the country. Providing policymakers and STI experts with more realistic estimates might prompt policymakers and STI experts to recognize the importance of STIs in Iran and help them to develop appropriate prevention and control programs
Subject(s)
Humans , Male , Female , Adolescent , Adult , Middle Aged , Prevalence , Incidence , Cross-Sectional Studies , Syphilis , Neisseria gonorrhoeae , Chlamydia trachomatisABSTRACT
Main technique to control acquired immunodeficiency syndrome [HIV] infection is the effective preventive programs among high-risk groups. Modeling is one of the effective methods where there is inadequate data. We used the modes of transmission [MOT] model to predict the transmission of HIV infection in Iran. We systematically searched published and grey literature to find values for the input parameters of MOT in 2010. The data were discussed by experts before being fed into the model. Using the Monte Carlo simulation, we computed the 95% confidence interval [CI] for the outputs of the MOT. The MOT estimates that 9136 new HIV infections would have occurred in Iran in 2010 [95% CI: 6831, 11757]. About 56% [95% CI: 47.7%, 61.6%] of new infections were among intravenous drug users [IDUs] and 12% [95% CI: 9.5%, 15%] among their sexual partners. The major routes of direct and indirect HIV transmission in Iran are unsafe injection [68%] and unprotected sexual contact [34% unprotected heterosexual and 10% homosexual] respectively. If current coverage for safe injection among IDUs increases from 80% to 95%, new HIV infections in this group would decrease around 75%. IDUs remain at highest risk of HIV infection in Iran, so the preventive program coverage for IDUs and their spouses needs to be increased. As the sexual transmission of HIV contributes increasingly to the pool of new infections, serious measures such as harm reduction program are required to reduce sexual transmission of HIV among the relevant key populations.
ABSTRACT
To address research questions, measuring variables are neccessary. However, every measurement is prone to different types of measurement errors. Therefore, understanding about the different types of measurement errors are a great of importance. This paper presents four types of measurement errors 1] Disagreement, which is discrepancies between the results of two or more than two measuring tools or observers 2] Random error which is a none-directional gap between the true and measured values 3] Systematic error or bias which is a directional gap between the true and measured values, and finally 4] Confounding error which changes the strength of association between dependent and independent variables in analytical studies