Search

The COVID-19 pandemic emphasized the need for pandemic preparedness strategies to mitigate its impacts, particularly in the United States, which experienced multiple waves with varying policies, population response, and vaccination effects. This study explores the relationships between county-level factors and COVID-19 mortality outcomes in the U.S. from 2020 to 2023, focusing on disparities in healthcare access, vaccination coverage, and socioeconomic characteristics. We conduct multi-variable rolling regression analyses to reveal associations between various factors and COVID-19 mortality outcomes, defined as Case Fatality Rate (CFR) and Overall Mortality to Hospitalization Rate (OMHR), at the U.S. county level. Each analysis examines the association between mortality outcomes and one of the three hierarchical levels of the Social Vulnerability Index (SVI), along with other factors such as access to hospital beds, vaccination coverage, and demographic characteristics. Our results reveal persistent and dynamic correlations between various factors and COVID-19 mortality measures. Access to hospital beds and higher vaccination coverage showed persistent protective effects, while higher Social Vulnerability Index was associated with worse outcomes persistently. Socioeconomic status and vulnerable household characteristics within the SVI consistently associated with elevated mortality. Poverty, lower education, unemployment, housing cost burden, single-parent households, and disability population showed significant associations with Case Fatality Rates during different stages of the pandemic. Vulnerable age groups demonstrated varying associations with mortality measures, with worse outcomes predominantly during the Original strain. Rural-Urban Continuum Code exhibited predominantly positive associations with CFR and OMHR, while it starts with a positive OMHR association during the Original strain. This study reveals longitudinal persistent and dynamic factors associated with two mortality rate measures throughout the pandemic, disproportionately affecting marginalized communities. The findings emphasize the urgency of implementing targeted policies and interventions to address disparities in the fight against future pandemics and the pursuit of improved public health outcomes., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2024 Ganjkhanloo et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Abstract: Falls are one of the most common adverse events in hospitals, and patient mobility is a key risk factor. In hospitals, risk assessment tools are used to identify patient-centered fall risk factors and guide care plans, but these tools have limitations. To address these issues, we examined daily patient mobility levels before injurious falls using the Johns Hopkins Highest Level of Mobility, which quantifies key patient mobility milestones from low-level to community distances of walking. We aimed to identify longitudinal characteristics of patient mobility before a fall to help identify fallers before the event. Conducting a retrospective matched case-control analysis, we compared mobility levels in the days leading up to an injurious fall between fallers and nonfallers. We observed that patients who experienced an injurious fall, on average, spent 28% of their time prefall at a low mobility level (Johns Hopkins Highest Level of Mobility levels 1-4), compared with nonfallers who spent 19% of their time at a low mobility level (mean absolute difference, 9%; 95% confidence interval, 1%-16%; P = 0.026; relative difference, 44%). This suggests that assessing a patient's mobility levels over time can help identify those at an increased risk for falls and enable hospitals to manage mobility problems more effectively., Competing Interests: Financial disclosure statements have been obtained, and no conflicts of interest have been reported by the authors or by any individuals in control of the content of this article., (Copyright © 2023 Wolters Kluwer Health, Inc. All rights reserved.)

Background: This study aimed to develop and assess the psychometric features of the Physical Activity at Workplace Questionnaire (PAWPQ) based on the Social Cognitive Theory (SCT) to evaluate employees' physical activity (PA) behaviors at the workplace., Methods: This psychometric cross-sectional study was conducted on 455 employees working in one of the gas refineries in Iran. The participants were selected using the proportional stratified sampling method in 2019. The data collection tools were a demographic information questionnaire, the short form of the International Physical Activity Questionnaire (IPAQ), and a questionnaire developed based on the SCT, whose psychometric features were confirmed in terms of validity and reliability. Data were analyzed using SPSS 22 and AMOS 20 software., Results: The first version of PAWPQ-SCT had 74 items. After evaluating content and face validity, nine items were removed. The results of the content validity index (0.98), content validity ratio (0.86), and impact score (3.62) were acceptable for the whole instrument. In exploratory factor analysis, after removing seven items-58-item final version of the scale-six factors could explain 73.54% of the total variance. The results of structural equation modeling showed the acceptable fit of the model into the data (RMSEA = 0.052, CFI = 0.917, NFI = 0.878, TLI = 0.905, IFI = 0.917, CMIN/DF = 2.818). Cronbach's alpha coefficient and Intraclass Correlation were 0.90 and 0.86, respectively., Conclusion: This study confirmed that the psychometric features of the 58-item final version of PAWPQ-SCT constructs were acceptable in a sample of Iranian employees. This questionnaire can be used as a valid and reliable tool to evaluate Iranian employees' PA behaviors and develop effective educational interventions for workers and managers., Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (© 2023 The Authors.)

Objective: The X-ray repair cross complementing group 1 ( XRCC1 ) gene is involved in DNA repair. Defects in DNA repair may lead to head and neck squamous cell carcinomas (HNSCCs). Several researches have focused on relationship between XRCC1 Arg 399Gln genetic polymorphism with HNSCC's prognosis with conflicting results. So, the aim of the present meta-analysis was evaluation of relationship between XRCC1 Arg 399Gln polymorphism with HNSCC's prognosis., Methods: Published articles up to July 2022 were systematically searched through international databases like PubMed, Web of Science, Scopus, etc. I 2 test was applied to assess the heterogeneity. Data were analyzed using random effects model. Funnel plots and Egger test were applied for assessing publication biases. The hazard ratios (HRs) and 95 % confidence intervals (CIs) were calculated for evaluation of relationship between the polymorphism with HNSCC's prognosis., Results: Fifteen articles were included for the systematic review. Six of those articles were considered for inclusion in meta-analysis. The different forms of XRCC1 Arg 399Gln polymorphism had not significant association with overall survival (OS) under varied genetic models (heterozygous: Ln (HR) = 0.02, 95 % CI= (-0.33,0.37), p-value = 0.90; homozygous: Ln (HR) = 0.33, 95 % CI= (-0.03,0.69), p-value = 0.07 and dominant: Ln (HR) = 0.06, 95 % CI = (-0.17,0.28), p-value = 0.62). Analysis showed that variants of the polymorphism had no significant relationship with OS in Asian and Caucasian ethnicity under dominant model (Ln (HR) = 0.14, 95 % CI= (-0.13,0.40), p-value = 0.31; Ln (HR) = -0.01, 95 % CI= (-0.41,0.38), p-value = 0.96)., Conclusion: Different forms of XRCC1 Arg 399Gln polymorphism had no significant relationship with HNSCC's prognosis under varied genetic models and based on different ethnicity., Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (© 2023 The Authors. Published by Elsevier Ltd.)

Early detection of breast cancer (BC) is important to increase the likelihood of treatment and improve the quality of life and survival. The study explored why symptomatic women linger to seek early screening for BC diagnosis based on the health belief model (HBM). In this qualitative study, 20 participants were selected using the purposive sampling method (9 health professionals and 11 female patients BC). Data were collected using in-depth, semi-structured interviews in 2019. Transcribed interview data were analyzed using the directed content analysis informed by HBM. According to the participants' experiences, although most patients comprehended the extent of the disease, they did not see themselves at risk of BC. Some were not adequately aware of the benefits of early diagnosis and did not have the self-efficacy required for early presentation. The main barriers to the early presentation included lack of awareness, financial problems, embarrassment over the clinical examination, and inadequate access to specialized centers. According to HBM, while designing and implementing educational programs, it is recommended to focus on reinforcing perceived susceptibility, perceived benefits, and perceived self-efficacy, providing access to facilities, and removing possible barriers and cultural issues to encourage women for timely referral for BC screening., (© 2023. The Author(s) under exclusive licence to American Association for Cancer Education.)

Background: Precise causes of musculoskeletal complaints among nurses are not known well, but many studies have pointed to manual patient handling tasks. Subjective judgment and decision-making process for patient lifting is crucial for gathering data regards patient handling. The aim of this study was to consider reliability and validity and re-structure of two special tools for patient handling's tasks., Methods: In this cross- sectional study 249 nurses were fully participated. As recommended by literature for cultural adaptation of instruments, forward/backward translation method was applied. Reliability of the translated version was assessed by Cronbach's alpha coefficient. Validity testing for the two scales was based on content validity index/ratio analysis and also Exploratory Factor Analysis was run to extract latent factors., Results: Reliability estimated by internal consistency reached a Cronbach's Alpha of above 0.7 for all subscales of two questionnaires. After testing the validity, the final version of questionnaires was remained by 14 and 15 questions respectively., Conclusions: These instruments evaluated for manual handling of normal and obese patients had acceptable validity and reliability in Iranian Nursing context. So, these tools can be used in further studies with the same cultures., (© 2023. The Author(s).)

Background: Tuberculosis (TB) and human immunodeficiency virus (HIV) are major public health challenges globally, and the number of TB infections and death caused by HIV are high because of HIV/ TB co-infection. On the other hand, CD4 count plays a significant role in TB/HIV co-infections. We used a joint model of longitudinal outcomes and competing risks to identify the potential risk factors and the effect of CD4 cells on TB infection and death caused by HIV in HIV-infected patients., Study Design: This was a retrospective cohort study., Methods: The current study was performed on 1436 HIV+patients referred to Behavioral Diseases Counseling Centers in Kermanshah Province during 1998-2019. In this study, joint modeling was used to identify the effect of potential risk factors and CD4 cells on TB and death caused by HIV., Results: The results demonstrated that the decreasing CD4 cell count was significantly associated with an increased risk of death, while it had no significant relation with the risk of TB. In addition, patients with TB were at a higher risk of death. Based on the results, a significant relationship was found between CD4 count and sex, marital status, education level, antiretroviral therapy (ART), time, and the interaction between time and ART. Further, people infected with HIV through sexual relationships were at higher risk of TB, while those with a history of imprisonment who received ART or were infected with HIV through drug injection had a lower risk of TB., Conclusion: The findings revealed that the decreasing CD4 count had a significant association with an increased risk of death caused by HIV. However, it was not significantly related to the risk of TB. Finally, patients with TB were at higher risk of death caused by HIV., (© 2023 The Author(s); Published by Hamadan University of Medical Sciences. This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.)

Background: The X-ray repair cross complementing group 1 (XRCC1) is a DNA repair gene. Various studies have examined the association between XRCC1 Arg194Trp polymorphism and head and neck squamous cell carcinoma (HNSCC) susceptibility with contradictory results. So, this systematic review and meta-analysis aimed to assess whether variants of this polymorphism increase the HNSCC risk or not., Recent Findings: Thirty three studies consisting of 14282 subjects (6012 cases and 8270 controls) were included in this meta-analysis. Variants of XRCC1 Arg194Trp polymorphism were associated with increased HNSCC risk and the associations were significant based on heterozygous and dominant models (heterozygous model: OR = 1.182, 95%CI = 1.015-1.377, P = 0.032; homozygous model: OR = 1.274, 95%CI = 0.940-1.727, P = 0.119; dominant model: OR = 1.194, 95%CI = 1.027-1.388, P = 0.021; recessive model: OR = 1.181, 95%CI = 0.885-1.576, P = 0.119). There were significant associations between variants of this polymorphism and HNSCC risk based on Asian ethnicity under dominant model, hospital control source under different genetic models, PCR-RFLP genotyping method under dominant model and oral cavity tumor site under heterozygous and dominant models., Objective: The X-ray repair cross complementing group 1 (XRCC1) is a DNA repair gene. Various studies have examined the association between XRCC1 Arg194Trp polymorphism and head and neck squamous cell carcinoma (HNSCC) susceptibility with contradictory results. So, this systematic review and meta-analysis aimed to assess whether variants of this polymorphism increase the HNSCC risk or not., Methods: A systematic search of the literatures published till April 2022 was conducted using Google Scholar, Scopus, PubMed, Web of Science, Cochrane Library and Embase databases. The heterogeneity was assessed with the I-Square statistic. A random effects model or fixed effects model was used to analyze the data. Data were reported by odds ratio (OR) and 95% confidence interval (CI). The p value was considered significant if p < .05., Results: Thirty three studies consisting of 14 282 subjects (6012 cases and 8270 controls) were included in this meta-analysis. Variants of XRCC1 Arg194Trp polymorphism were associated with increased HNSCC risk and the associations were significant based on heterozygous and dominant models (heterozygous model: OR = 1.182, 95%CI = 1.015-1.377, p = .032; homozygous model: OR = 1.274, 95%CI = 0.940-1.727, p = .119; dominant model: OR = 1.194, 95%CI = 1.027-1.388, p = .021; recessive model: OR = 1.181, 95%CI = 0.885-1.576, p = .119). There were significant associations between variants of this polymorphism and HNSCC risk based on Asian ethnicity under dominant model, hospital control source under different genetic models, PCR-RFLP genotyping method under dominant model and oral cavity tumor site under heterozygous and dominant models., Conclusion: Variants of XRCC1 Arg194Trp polymorphism were significantly associated with increased risk of HNSCC development based on heterozygous and dominant genetic models., (© 2022 The Authors. Cancer Reports published by Wiley Periodicals LLC.)

Infectious disease modelling can serve as a powerful tool for situational awareness and decision support for policy makers. However, COVID-19 modelling efforts faced many challenges, from poor data quality to changing policy and human behaviour. To extract practical insight from the large body of COVID-19 modelling literature available, we provide a narrative review with a systematic approach that quantitatively assessed prospective, data-driven modelling studies of COVID-19 in the USA. We analysed 136 papers, and focused on the aspects of models that are essential for decision makers. We have documented the forecasting window, methodology, prediction target, datasets used, and geographical resolution for each study. We also found that a large fraction of papers did not evaluate performance (25%), express uncertainty (50%), or state limitations (36%). To remedy some of these identified gaps, we recommend the adoption of the EPIFORGE 2020 model reporting guidelines and creating an information-sharing system that is suitable for fast-paced infectious disease outbreak science., Competing Interests: Declaration of interests ECL declares payment for expert testimony from Cohen Ziffer Frenchman & McKenna for a report related to COVID-19 epidemiology. KN, SJ, and LG submitted a model to the US COVID-19 Forecast Hub. NGR is a coauthor on EPIFORGE 2020 model reporting guidelines, is a codirector of the Forecast Hub, has submitted individual models to the Forecast Hub, and served in an advisory role for the US Scenario Modeling Hub. ST is a cofounder and member of the leadership team for the US Scenario Modeling Hub, and has submitted individual models to both the Scenario and Forecast Hubs. ECL has submitted models to both the Forecast and Scenario Hubs. FP and KG declare no competing interests., (Copyright © 2022 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license. Published by Elsevier Ltd.. All rights reserved.)

Competing Interests: ECL received payment for expert testimony from Cohen Ziffer Frenchman & McKenna for a report related to COVID-19 epidemiology. KN, SJ, and LG submitted a model to the COVID-19 Forecast Hub. NGR is a coauthor on EPIFORGE 2020 model reporting guidelines, a codirector of the Forecast Hub, has submitted individual models to the Forecast Hub, and served in an advisory role for the US Scenario Modeling Hub. ST is a cofounder and member of leadership team for the US Scenario Modeling Hub and has submitted individual models to both the Scenario and Forecast Hub. ECL has submitted models to both the Forecast and Scenario Hub. KN, SJ, MM, and LG were funded by the National Science Foundation (NSF) Rapid Response Research grants (2108526 and 2028604) and the Centers for Disease Control and Prevention (CDC) SHEPheRD Project (200-2016-91781). NGR has been supported by the CDC (1U01IP001122) and the National Institutes of General Medical Sciences (NIGMS; R35GM119582). The content is solely the responsibility of the authors and does not necessarily represent the official views of the NIGMS or the National Institutes of Health. KG and FP were funded by the Society for Medical Decision Making Covid Modeling Accelerator and the CDC (U01CK000589). ST has been supported by the NSF (2127976) and the CDC SHEPheRD Project (200-2016-91781). The funders of the study had no role in the conceptualisation or writing of the Comment.

Objectives: Breast cancer (BC) is the most common cause of cancer death in Iranian women. Sometimes death from other causes precludes the event of interest and makes the analysis complicated. The purpose of this study was to identify important prognostic factors associated with survival duration among patients with BC using random survival forests (RSF) model in presence of competing risks. Also, its performance was compared with cause-specific hazard model., Methods: This retrospective cohort study assessed 222 patients with BC who were admitted to Ayatollah Khansari hospital in Arak, a major industrial city and the capital of Markazi province in Iran. The cause-specific Cox proportional hazards and RSF models were employed to determine the important risk factors for survival of the patients., Results: The mean and median survival duration of the patients were 90.71 (95%CI: 83.8-97.6) and 100.73 (95%CI: 89.2-121.5) months, respectively. The cause-specific model indicated that type of surgery and HER2 had statistically significant effects on the risk of death of BC. Moreover, the RSF model identified that HER2 was the most important variable for the event of interest., Conclusion: According to the results of this study, the performance of the RSF model was better than the cause-specific hazard model. Moreover, HER2 was the most important variable for death of BC in both of the models., Competing Interests: Conflict of interest statement The authors declare that they have no conflicts of interest., (©2022 Pacini Editore SRL, Pisa, Italy.)

As different types of hazards, including natural and man-made, can occur simultaneously, to implement an integrated and holistic risk management, a multi-hazard perspective on disaster risk management, including preparedness and planning, must be taken for a safer and more resilient society. Considering the emerging challenges that the COVID-19 pandemic has been introducing to regular hospital operations, there is a need to adapt emergency plans with the changing conditions, as well. Evacuation of patients with different mobility disabilities is a complicated process that needs planning, training, and efficient decision-making. These protocols need to be revisited for multi-hazard scenarios such as an ongoing disease outbreak during which additional infection control protocols might be in place to prevent transmission. Computational models can provide insights on optimal emergency evacuation strategies, such as the location of isolation units or alternative evacuation prioritization strategies. This study introduces a non-ICU patient classification framework developed based on available patient mobility data. An agent-based model was developed to simulate the evacuation of the emergency department at the Johns Hopkins Hospital during the COVID-19 pandemic due to a fire emergency. The results show a larger nursing team can reduce the median and upper bound of the 95% confidence interval of the evacuation time by 36% and 33%, respectively. A dedicated exit door for COVID-19 patients is relatively less effective in reducing the median time, while it can reduce the upper bound by more than 50%., Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (© 2021 Elsevier Ltd. All rights reserved.)

Background: Burn is a tragic event for an individual, the family, and community. It can cause irreparable physical, mental, economic, and social injury. Researches well documented that a quick visit to a healthcare center can greatly reduce burn injuries. Therefore, the aim of this study is to identify the effective factors in the interval between a burn and start of treatment in burn patients by comparing three classification data mining methods and logistic regression., Methods: This cross-sectional study conducted on 389 hospitalized patients in Imam Khomeini Hospital of Kermanshah city since 2012 to 2015. The data collection instrument was a three-part questionnaire, including demographic information, geographical information, and burn information. Four classification methods (decision tree (DT), random forest (RF), support vector machine (SVM) and logistic regression (LR)) were used to identify the effective factors in the interval between burn and start of treatment (less than two hours and equal or more than two hours)., Results: The mean total accuracy of all models is higher than 0.8. The DT model has the highest mean total accuracy (0.87), sensitivity (0.44), positive likelihood ratio (14.58), negative predictive value (0.89) and positive predictive value (0.71). However, the specificity of the SVM model and RF model (0.99) was higher than other models, and the mean negative likelihood ratio (0.98) of the SVM model are higher than other models., Conclusions: The results of this study shows that DT model performed better that data mining models in terms of total accuracy, sensitivity, positive likelihood ratio, negative predictive value and positive predictive value. Therefore, this method is a promising classifier for investigating the factors affecting the interval between a burn and the start of treatment in burn patients. Also, key factors based on DT model were location of transfer to hospital, place of occurrence, time of accident, religion, history and degree of burn, income, province of residence, burnt limbs and education.

As the scope and scale of the COVID-19 pandemic became clear in early March of 2020, the faculty of the Malone Center engaged in several projects aimed at addressing both immediate and long-term implications of COVID-19. In this article, we briefly outline the processes that we engaged in to identify areas of need, the projects that emerged, and the results of those projects. As we write, some of these projects have reached a natural termination point, whereas others continue. We identify some of the factors that led to projects that moved to implementation, as well as factors that led projects to fail to progress or to be abandoned.

Background: Artificial intelligence (AI) has potential to streamline interpretation of pH-impedance studies. In this exploratory observational cohort study, we determined feasibility of automated AI extraction of baseline impedance (AIBI) and evaluated clinical value of novel AI metrics., Methods: pH-impedance data from a convenience sample of symptomatic patients studied off (n = 117, 53.1 ± 1.2 years, 66% F) and on (n = 93, 53.8 ± 1.3 years, 74% F) anti-secretory therapy and from asymptomatic volunteers (n = 115, 29.3 ± 0.8 years, 47% F) were uploaded into dedicated prototypical AI software designed to automatically extract AIBI. Acid exposure time (AET) and manually extracted mean nocturnal baseline impedance (MNBI) were compared to corresponding total, upright, and recumbent AIBI and upright:recumbent AIBI ratio. AI metrics were compared to AET and MNBI in predicting  ≥ 50% symptom improvement in GERD patients., Results: Recumbent, but not upright AIBI, correlated with MNBI. Upright:recumbent AIBI ratio was higher when AET  > 6% (median 1.18, IQR 1.0-1.5), compared to  < 4% (0.95, IQR 0.84-1.1), 4-6% (0.89, IQR 0.72-0.98), and controls (0.93, IQR 0.80-1.09, p ≤ 0.04). While MNBI, total AIBI, and the AIBI ratio off PPI were significantly different between those with and without symptom improvement (p < 0.05 for each comparison), only AIBI ratio segregated management responders from other cohorts. On ROC analysis, off therapy AIBI ratio outperformed AET in predicting GERD symptom improvement when AET was  > 6% (AUC 0.766 vs. 0.606) and 4-6% (AUC 0.563 vs. 0.516) and outperformed MNBI overall (AUC 0.661 vs. 0.313)., Conclusions: BI calculation can be automated using AI. Novel AI metrics show potential in predicting GERD treatment outcome.

The COVID-19 crisis has brought about new clinical questions, new workflows, and accelerated distributed healthcare needs. Although artificial intelligence (AI)-based clinical decision support seemed to have matured, the application of AI-based tools for COVID-19 has been limited to date. In this perspective piece, the opportunities and requirements for AI-based clinical decision support systems are identified and challenges that impact "AI readiness" for rapidly emergent healthcare challenges are highlighted., Competing Interests: The authors declare no conflict of interest., (© 2020 The Authors. Published by WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim.)

Background: Drug injection has been increasing over the past decades all over the world. Hepatitis B and C viruses (HBV and HCV) are two common infections among people who inject drugs (PWID) and more than 60% of new human immunodeficiency virus (HIV) cases are PWID. Thus, investigating risk factors associated with drug use transition to injection is essential and was the aim of this research., Methods: We used a database from drug use treatment centers in Kermanshah Province (Iran) in 2013 that included 2098 records of people who use drugs (PWUD). The information of 29 potential risk factors that are commonly used in the literature on drug use was selected. We employed four classification methods (decision tree, neural network, support vector machine, and logistic regression) to determine factors affecting the decision of PWUD to transition to injection., Results: The average specificity of all models was over 84%. Support vector machine produced the highest specificity (0.9). Also, this model showed the highest total accuracy (0.91), sensitivity (0.94), positive likelihood ratio [1] and Kappa (0.94) and the smallest negative likelihood ratio (0). Therefore, important factors according to the support vector machine model were used for further interpretation., Conclusions: Based on the support vector machine model, the use of heroin, cocaine, and hallucinogens were identified as the three most important factors associated with drug use transition injection. The results further indicated that PWUD with the history of prison or using drug due to curiosity and unemployment are at higher risks. Unemployment and unreliable sources of income were other suggested factors of transition in this research.

Background: Cervical ripening is one of the main stages of initiation labor. Acupressure in Chinese medicine is considered as an invasive technique, which through reliving oxytocin ripens the cervix. Acupoint Sanyinjiao (SP6) was selected in this study because it is the acupoint selected in gynecology and it is easy for women to locate and apply pressure without medical assistance., Objectives: The aim of this study was to determine the effect of acupressure on cervical ripening., Patients and Methods: In this randomized clinical trial, 150 primigravida with term pregnancy who had referred to Deziani hospital in Gorgan were chosen and divided to three groups: in the first group acupressure was done by the researcher while in the second groups this was performed by the mother her self, and the third group served as a control and only received routine care. For both intervention groups the pressure was applied on Sp6 for about 20 minutes during one to five days. Elements were checked from cervical ripening at 48 and 96 hours after intervention and at the time of hospitalization. The tools for gathering information included demographic characteristics and midwifery history questionnaire, daily records and follow up forms. Content validity was used for validity of tools. Reliability of the observation check-list and physical examination was confirmed by inter-rater scores (inter observer), and daily records by test-re-test. Data was analyzed by analysis of variance (ANOVA), Kruskal-Wallis and Chi-squared tests (P ≤ 0.05)., Results: There was a significant difference between mothers' educations in the three groups. Most of the mothers (59.5%) in the researcher-performed acupressure group had secondary education. Cervical ripening was significantly different between the three groups after 48 hours (P ≤ 0.05), yet there was no significant difference after 96 hours and at the time of admission. Mean Bishop score was enhanced after 48 hours in the researcher-performed acupressure group (P ≤ 0.021) and the self-performed acupressure group (P ≤ 0.007) in comparison to the control group., Conclusions: The results showed that acupressure is a safe technique and leads to cervical ripening. Thus, regarding the desired results that were achieved when mothers applied acupressure themselves, it could be suggested that it is beneficial for mothers to be trained to apply this method at home.

Background: Meta-analysis is a statistical technique in which the results of two or more independent studies, with similar objectives, are mathematically combined in order to improve the reliability of the results. The outliers, which may exist even in random models, can affect the validity and strength of meta-analysis results., Objectives: The current study uses "random effects variance shift model" to evaluate and correct the outliers in performing a meta-analysis study of the effect of albendazole in treating patients with Ascaris lumbricoides infection., Patients and Methods: The study used data from 14 clinical trials; each article was composed of two groups, a treatment group and a placebo group. These articles compared the effect of single dose intakes of 400 mg albendazole in treating two groups of patients with Ascaris lumbricoides infection. The articles were published in a number of internationally indexed journals between 1983 to 2013. For both groups in each article, the total number of participants, the number of those with Ascaris lumbricoides infection, and the number of those recovered following the intake of albendazole were identified and recorded. The relative risk (RR) and variance were computed for each article individually. Then, using meta-analysis, the RR was computed for all the articles together. In order to detect outliers the "random effects variance shift model" and "likelihood ratio test" (LRT) were used. Adopting the bootstrap method, the accuracy rates for sampling distribution of the tests, which were used for multiple testing, were obtained and the relevant graphs were depicted. For data analysis, STATA and R software were used., Results: According to meta-analysis results, the estimate for RR was 2.91, with a 95% confidence interval of 2.6 to 3.25. According to the method used in this study, three articles (articles number 4, 7, and 12) were outliers and, as such, they were detected in the graphs., Conclusions: We can detect and accommodate outliers in meta-analysis by using random effects variance shift model and likelihood ratio test.

Purpose: The purpose of this work is to advance the two-step approach for Gamma Knife(®) Perfexion™ (PFX) optimization to account for dose homogeneity and overlap between the planning target volume (PTV) and organs-at-risk (OARs)., Methods: In the first step, a geometry-based algorithm is used to quickly select isocentre locations while explicitly accounting for PTV-OARs overlaps. In this approach, the PTV is divided into subvolumes based on the PTV-OARs overlaps and the distance of voxels to the overlaps. Only a few isocentres are selected in the overlap volume, and a higher number of isocentres are carefully selected among voxels that are immediately close to the overlap volume. In the second step, a convex optimization is solved to find the optimal combination of collimator sizes and their radiation duration for each isocentre location., Results: This two-step approach is tested on seven clinical cases (comprising 11 targets) for which the authors assess coverage, OARs dose, and homogeneity index and relate these parameters to the overlap fraction for each case. In terms of coverage, the mean V99 for the gross target volume (GTV) was 99.8% while the V95 for the PTV averaged at 94.6%, thus satisfying the clinical objectives of 99% for GTV and 95% for PTV, respectively. The mean relative dose to the brainstem was 87.7% of the prescription dose (with maximum 108%), while on average, 11.3% of the PTV overlapped with the brainstem. The mean beam-on time per fraction per dose was 8.6 min with calibration dose rate of 3.5 Gy/min, and the computational time averaged at 205 min. Compared with previous work involving single-fraction radiosurgery, the resulting plans were more homogeneous with average homogeneity index of 1.18 compared to 1.47., Conclusions: PFX treatment plans with homogeneous dose distribution can be achieved by inverse planning using geometric isocentre selection and mathematical modeling and optimization techniques. The quality of the obtained treatment plans are clinically satisfactory while the homogeneity index is improved compared to conventional PFX plans.

BACKGROUND/AIMS: There are controversial data about renal function following off-pump coronary artery bypass grafting (CABG). The present study aimed to evaluate renal function changes 24 h after on- and off-pump CABG, as well as renal function correlated with high-sensitivity C-reactive protein (hs-CRP) and tumor necrosis factor-α (TNF-α). METHODS: Ninety patients with coronary artery disease referred to our center for CABG from July 2006 to November 2007 were enrolled in the study. Patients were equally and randomly divided in two groups, on- and off-pump. Serum levels of creatinine (Cr), blood urea nitrogen, creatinine clearance (CrCl), hs-CRP, and TNF-α were determined immediately before and 24 h after surgery. RESULTS: Cr and CrCl changes after surgery were not significantly different between the two groups; however, blood urea nitrogen levels after surgery were significantly higher in the on-pump group (p = 0.035). No statistically significant difference was noted between the two groups in terms of changes in levels of hs-CRP and TNF-α (p = 0.350 and 0.805, respectively). The changes in CrCl levels had no significant correlation with hs-CRP and TNF-α. CONCLUSIONS: The early Cr and CrCl levels after surgery are not significantly different in on- and off-pump groups. The early renal function after on- or off-pump CABG is not correlated with the levels of inflammatory markers including hs-CRP and TNF-α.

Purpose: The purpose of this work is to develop a framework to the inverse problem for radiosurgery treatment planning on the Gamma Knife(®) Perfexion™ (PFX) for intracranial targets., Methods: The approach taken in the present study consists of two parts. First, a hybrid grassfire and sphere-packing algorithm is used to obtain shot positions (isocenters) based on the geometry of the target to be treated. For the selected isocenters, a sector duration optimization (SDO) model is used to optimize the duration of radiation delivery from each collimator size from each individual source bank. The SDO model is solved using a projected gradient algorithm. This approach has been retrospectively tested on seven manually planned clinical cases (comprising 11 lesions) including acoustic neuromas and brain metastases., Results: In terms of conformity and organ-at-risk (OAR) sparing, the quality of plans achieved with the inverse planning approach were, on average, improved compared to the manually generated plans. The mean difference in conformity index between inverse and forward plans was -0.12 (range: -0.27 to +0.03) and +0.08 (range: 0.00-0.17) for classic and Paddick definitions, respectively, favoring the inverse plans. The mean difference in volume receiving the prescribed dose (V(100)) between forward and inverse plans was 0.2% (range: -2.4% to +2.0%). After plan renormalization for equivalent coverage (i.e., V(100)), the mean difference in dose to 1 mm(3) of brainstem between forward and inverse plans was -0.24 Gy (range: -2.40 to +2.02 Gy) favoring the inverse plans. Beam-on time varied with the number of isocenters but for the most optimal plans was on average 33 min longer than manual plans (range: -17 to +91 min) when normalized to a calibration dose rate of 3.5 Gy/min. In terms of algorithm performance, the isocenter selection for all the presented plans was performed in less than 3 s, while the SDO was performed in an average of 215 min., Conclusions: PFX inverse planning can be performed using geometric isocenter selection and mathematical modeling and optimization techniques. The obtained treatment plans all meet or exceed clinical guidelines while displaying high conformity., (© 2012 American Association of Physicists in Medicine.)