Hospital Practices and Research

Abstract Background: In 2023, there were 8.2 million Tuberculosis (TB) cases, primarily in South-East Asia. The World Health Organization (WHO) is advocating for increased funding, enhanced diagnostics, and improved healthcare to eradicate TB by 2035. Wealthy nations exhibit lower relapse rates, while poorer countries face higher risks. The challenges of drug-resistant TB and COVID-19 are complicating treatment efforts.
Objectives: This study aims to examine TB recurrence rates in Iran and neighboring countries using data from the WHO. The objective is to comprehend the rate of disease recurrence and the correlations among the results of the studied countries from 2010 to 2023.
Methods: Data on TB relapse cases from 2010 to 2023 in Iran and neighboring countries were analyzed using SPSS v27. Correlations were assessed using Pearson and Spearman tests.
Results: The study highlights TB relapse trends per 100,000 people in the Middle East and Central Asia from 2010-2023. The UAE and Jordan witnessed significant decreases in cases, while Oman and Egypt reported modest declines. Iran initially showed improvement in rates but later experienced an increase, indicating treatment challenges. Lebanon, Saudi Arabia, and Kuwait also achieved lower rates, but Iraq's rates remain high. Yemen and Qatar saw increases, prompting concerns about control. Turkey and Azerbaijan showed improvement, whereas Afghanistan and Pakistan experienced rising cases, suggesting a need for improved strategies. Accordingly, socioeconomic and healthcare factors play a critical role in effectively managing TB.
Conclusion: Enhancing diagnostic and treatment infrastructure in remote, high-incidence areas is crucial for addressing TB recurrence. Training healthcare workers, implementing Directly Observed Therapy (DOT), monitoring drug resistance, addressing social determinants, and conducting awareness campaigns are essential strategies for enhancing community education and treatment adherence.

Abstract Background: Seeking local evidence on treatment efficacy is necessary if cultural factors are involved, as in psychotherapy for Chronic Pain (CP). Yet, local evidence is known to be prone to bias, making it difficult to reach reliable conclusions.
Objectives: This study aimed to critically evaluate our local evidence on the efficacy of psychotherapy on quality of life and disability in CP. It has been elaborated that, with some requirements, common meta-analytic tools can be utilized to detect and correct local evidence bias.
Methods: The protocol was registered on PROSPERO, Record [deleted for blind review]. Elmnet, Pubmed, and ProQuest were searched for randomized trials. A multilevel meta-analysis was used to capture the hierarchical structure of the data, and robust variance estimation was used for inference. Several moderation analyses were conducted, and publication and other related sources of bias were examined.
Results: Forty-two trials were initially included. Six were excluded before the analysis due to serious reporting problems undermining their validity. The SMD from 185 effect sizes was 1.08 [.87, 1.3]. The funnel plot showed a strong bias. The bias-corrected estimate from a regression-based method was 0.45 [0.04, 0.87], and from the trim-and-fill was 0.75 [0.48, 1.0].
Conclusion: While our original estimate was large, the corrected estimation showed a medium effect, fairly comparable to the international estimates. Current evidence on different sources of bias in our literature suggests low quality and questionable research practice as the first suspects for our local evidence bias.

Abstract Background: Outbreak detection algorithms could play a key role in public health surveillance.
Objectives: This study aimed to compare the performance of three algorithms (EWMA, Cumulative Sum (CUSUM), and Poisson Regression) using the reported COVID-19 data for outbreak detection.
Methods: Three outbreak detection algorithms were applied to the data of COVID-19 daily new cases in Iran between 19/02/2020 and 20/06/2022, and 344 simulated outbreak days were injected into the data sequences. The Area Under the Receiver Operating Characteristics (ROC) Curve (AUC) and its 95% confidence intervals (95% CI) were also computed.
Results: EWMA9 had the lowest AUC (51%). Among the different algorithms, EWMA9 with λ = 0.9 and CUSUM 1 had the highest sensitivity with 100 and 87% (95% CI: 84%-91%), respectively.
Conclusion: According to the results, CUSUM, EWMA, and poison regression showed appropriate performance in detecting the COVID-19 outbreaks. These algorithms can be extremely helpful for health practitioners and policymakers in the detection of infectious disease outbreaks.

Abstract Background: Retraction of articles occurs as a result of scientific misconducts or honest errors.
Objectives: This study aimed to identify the frequency of retracted Iranian publications, compared to those of other countries and adjust them with influential parameters.
Methods: All publications that were indexed on the Scopus database from 2008 to 2017 and then retracted, due to scientific misconduct were extracted through the Retraction Watch database and selected as the research community. To calculate the growth of retraction for each proposed country (or region), first, the rate of an absolute number of retracted papers for the years 2013-2017 was divided by the similar number for years 2008-2012, then this rate was adjusted to the retracted rate which is similarly computed for the total retracted statistics of the world.
Results: Overall, 545 Iranian retracted publications from 2008 to 2017 were identified, of which 240 and 305 retracted articles were related to the first five years and the second five years of the study, respectively. The results showed that less than 1% (0.82) of all scientific articles published by Iranian researchers were retracted. However, the rate of retracted scientific articles in Iran compared to this rate in the world was significantly higher.
Conclusion: Although retracted Iranian publications make up a small percentage of all Iranian publications, the number of retracted publications is increasing. It is important to recognize the reasons for scientific misconducts and to provide researchers with proper education.

Abstract Background: Physicians’ satisfaction is closely related to the effectiveness of health services, including quality of services as well as patient compliance, satisfaction, and outcomes.
Objectives: This study was designed to examine the job satisfaction level of physicians working at a referral hospital in Tehran.
Methods: This research was a descriptive study performed on a population of physicians working at a referral hospital from April to August 2019. The sample size was calculated as 120 subjects. The Physicians’ Job Satisfaction Questionnaire (PJSQ), which is a valid questionnaire, was used as the data collection tool. The collected data was entered into SPSS Statistics 20. Mann-Whitney and t tests were used for data analysis.
Results: The frequency of female and male physicians was 50 (38.2%) and 81 (61.8%), respectively. The total mean of Job satisfaction in physicians was 51±7.05. Overall satisfaction scores were 70.7±15.1, 51.5±11.1, 49.8±13.1, 49.5±11.2, 44.1±9.3, and 40.5±11.9 in domains of income satisfaction, physicians’ satisfaction with management, relationship between physicians and their colleagues, patients, staff, and physicians’ job satisfaction, respectively. 87% of physicians participating in this study were not willing to leave their jobs. The income satisfaction of the female physician group was significantly higher than that of men (P=0.029). The income satisfaction of subspecialists was significantly higher than that of specialists (P=0.022). The job satisfaction of physicians who were not faculty members was significantly higher than that of physicians who were faculty members (P=0.034).
Conclusion: The job satisfaction level of physicians working at a referral hospital in Tehran was moderate. Income satisfaction and job satisfaction were the highest and lowest levels of satisfaction, respectively.