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The Framingham 10-year cardiovascular disease risk is measured by laboratory-based and non-laboratory-based models. This study aimed to determine the agreement between these two models in a large population in Southern Iran. In this study, the baseline data of 8138 individuals participated in the Pars cohort study were used. The participants had no history of cardiovascular disease or stroke. For the laboratory-based risk model, scores were determined based on age, sex, current smoking, diabetes, systolic blood pressure (SBP) and treatment status, total cholesterol, and High-Density Lipoprotein. For the non-laboratory-based risk model, scores were determined based on age, sex, current smoking, diabetes, SBP and treatment status, and Body Mass Index. The agreement between these two models was determined by Bland Altman plots for agreement between the scores and kappa statistic for agreement across the risk groups. Bland Altman plots showed that the limits of agreement were reasonable for females < 60 years old (95% CI: -2.27-4.61%), but of concern for those ≥ 60 years old (95% CI: -3.45-9.67%), males < 60 years old (95% CI: -2.05-8.91%), and males ≥ 60 years old (95% CI: -3.01-15.23%). The limits of agreement were wider for males ≥ 60 years old in comparison to other age groups. According to the risk groups, the agreement was better in females than in males, which was moderate for females < 60 years old (kappa = 0.57) and those ≥ 60 years old (kappa = 0.51). The agreement was fair for the males < 60 years old (kappa = 0.39) and slight for those ≥ 60 years old (Kappa = 0.14). The results showed that in overall participants, the agreement between the two risk scores was moderate according to risk grouping. Therefore, our results suggest that the non-laboratory-based risk model can be used in resource-limited settings where individuals cannot afford laboratory tests and extensive laboratories are not available.

Background: Metabolic syndrome (MetS) is a cluster of risk factors and the Framingham risk score (FRS) is a useful metric for measuring the 10-year cardiovascular disease (CVD) risk of the population. The present study aimed to determine the 10-year risk of cardiovascular disease using the Framingham risk score in people with and without MetS in a large Iranian cohort study. Methods: This cross-sectional study was done using the Fasa cohort. Participants aged ≥ 35 years old were recruited to the study from 2015 to 2016. The FRS was calculated using age, sex, current smoking, diabetes, systolic blood pressure (SBP), total cholesterol, and high-density lipoprotein (HDL) cholesterol. MetS was defined as the presence of three or more of the MetS risk factors including triglyceride (TG) level ≥ 150 mg dl− 1, HDL level < 40 mg dl− 1 in men and < 50 mg dl− 1 in women, systolic/diastolic blood pressure ≥ 130/≥85 mmHg or using medicine for hypertension, fasting blood sugar (FBS) level ≥ 100 mg dl− 1 or using diabetes medication and abdominal obesity considered as waist circumference (WC) ≥ 88 cm for women and ≥ 102 cm for men. Multiple logistic regressions were applied to estimate the 10- year CVD risk among people with and without MetS. Results: Of 8949 participants, 1928 people (21.6%) had MetS. The mean age of the participants with and without Mets was 50.4 ± 9.2 years and 46.9 ± 9.1 years respectively. In total 15.3% of participants with MetS and 8.0% of participants without MetS were in the high-risk category of 10-year CVD risk. Among participants with MetS gender, TG, SBP, FBS and in people without MetS gender, TG, SBP, FBS, and HDL showed strong associations with the predicted 10-year CVD risk. Conclusion: Male sex and increased SBP, TG, and FBS parameters were strongly associated with increased 10-year risk of CVD in people with and without MetS. In people without MetS, reduced HDL-cholestrol was strongly associated with increased 10-year risk of CVD. The recognition of participant's TG, blood pressure (BP), FBS and planning appropriate lifestyle interventions related to these characteristics is an important step towards prevention of CVD. [ABSTRACT FROM AUTHOR]

Background: This study aimed to describe the trends in incidence, mortality, and burden of tracheal, bronchial and lung (TBL) cancer in Asia from 2010 through 2019 and compare with global and other continental data. Methods: We collected TBL cancer data from the 2019 Global Burden of Disease (GBD) study from 2010 to 2019 in 49 countries and territories in Asia. For all locations, annual case data and age‐standardized rates (ASRs) were used to investigate the incidence, prevalence, mortality, and disability‐adjusted life‐years (DALYs) of TBL from 2010 to 2019. The relative difference (%) between years was used to show comparative variations of ASRs for the indicators studied. Results: In 2019, more than 55% of TBL cancer cases and deaths occurred in Asian countries. A total of 57% of lung cancer patients lived in Asia and almost 60% of the global burden of lung cancer was imposed on Asian countries. From 2010 to 2019, incidences, deaths, prevalence cases, and DALYs number of TBL cancer increased over 1.34‐, 1.31‐, 1.31‐, and 1.26‐fold, in Asia. During this period, the age‐standardized incidence rate (ASIR), the age‐standardized death rate (ASDR), the age‐standardized prevalence rate (ASPR), and the age‐standardized DALYs rate (DALYs ASR) of TBL cancer decreased by 1, 3, 4, and 4%, respectively. While at the same time, the decreasing trend of these rates globally and in America and in Europe happened faster. In 2019, age‐specific incidence, death, prevalence, and DALY cases of TBL cancer were peaking at 65–74, 70–74, 65–69, and 65–69 years, respectively. In 2019, the highest ASIR, ASDR, and DALYs ASR of TBL cancer was observed in East Asia countries and the highest ASPR in high‐income Asia Pacific countries. Central Asia and high‐income Asia Pacific countries experienced a decreasing trend in ASIR and ASDR, and the South Asia countries experienced the highest increasing trend from 2010 to 2019. ASPR only decreased in Central Asia, and DALYs ASR only increased in South Asia. In 2019, among high sociodemographic index (SDI) Asian countries, Brunei Darussalam had the highest ASIR, ASDR, and DALYs ASR and the Republic of Korea had the highest ASPR. Among high‐middle SDIs, Turkey and Georgia; among middle SDIs, China and Armenia; among low‐middle SDIs, Mongolia and the Democratic People's Republic of Korea had the highest ASIR, ASDR, ASPR, and DALY ASR of TBL cancer. Among low SDI Asian countries, Pakistan had the highest ASIR, ASDR, ASPR, and DALY ASR of TBL cancer. Conclusion: Most of the global burden of lung cancer occurs in Asian countries, and the decreasing trend of incidence, death, prevalence, and burden of this cancer in these countries is slower than in other regions. Therefore, the implementation of necessary measures in order to reduce the process of this cancer is considered urgent. [ABSTRACT FROM AUTHOR]

Background: The WHO model has laboratory-based and non-laboratory-based versions for 10-year risk prediction of cardiovascular diseases. Due to the fact that in some settings, there may not be the necessary facilities for risk assessment with a laboratory-based model, the present study aimed to determine the agreement between laboratory-based and non-laboratory-based WHO cardiovascular risk equations. Methods: In this cross-sectional study, we used the baseline data of 6796 individuals without a history of cardiovascular disease and stroke who participated in the Fasa cohort study. The risk factors of the laboratory-based model included age, sex, systolic blood pressure (SBP), diabetes, smoking and total cholesterol, while the non-laboratory-based model included age, sex, SBP, smoking and BMI. Kappa coefficients was used to determine the agreement between the grouped risk and Bland–Altman plots were used to determine the agreement between the scores of the two models. Sensitivity and specificity of non-laboratory-based model were measured at the high-risk threshold. Results: In the whole population, the agreement between the grouped risk of the two models was substantial (percent agreement = 79.0%, kappa = 0.68). The agreement was better in males than in females. A substantial agreement was observed in all males (percent agreement = 79.8%, kappa = 0.70) and males < 60 years old (percent agreement = 79.9%, kappa = 0.67). The agreement in males ≥ 60 years old was moderate (percent agreement = 79.7%, kappa = 0.59). The agreement among females was also substantial (percent agreement = 78.3%, kappa = 0.66). The agreement for females < 60 years old, (percent agreement = 78.8%, kappa = 0.61) was substantial and for females ≥ 60 years old, (percent agreement = 75.8%, kappa = 0.46) was moderate. According to Bland–Altman plots, the limit of agreement was (95%CI: -4.2% to 4.3%) for males and (95%CI: -4.1% to 4.6%) for females. The range of agreement was suitable for both males < 60 years (95%CI: -3.8% to 4.0%) and females < 60 years (95%CI: -3.6% to 3.9%). However, it was not suitable for males ≥ 60 years (95% CI: -5.8% to 5.5%) and females ≥ 60 years (95%CI: -5.7% to 7.4%). At the high-risk threshold of 20% in non-laboratory and laboratory-based models, the sensitivity of the non-laboratory-based model was 25.7%, 70.7%, 35.7%, and 35.4% for males < 60 years, males ≥ 60 years, females < 60 years, and females ≥ 60 years, respectively. At the high-risk threshold of 10% in non-laboratory-based and 20% in laboratory-based models, the non-laboratory model has high sensitivity of 100% for males ≥ 60 years, females < 60 years, females ≥ 60 years, and 91.4% for males < 60 years. Conclusion: A good agreement was observed between laboratory-based and non-laboratory-based versions of the WHO risk model. Also, at the risk threshold of 10% to detect high-risk individuals, the non-laboratory-based model has acceptable sensitivity for practical risk assessment and the screening programs in settings where resources are limited and people do not have access to laboratory tests. [ABSTRACT FROM AUTHOR]

Background: Methodology of Failure Mode and Effects Analysis (FMEA) is known as an important risk assessment tool and accreditation requirement by many organizations. For prioritizing failures, the index of "risk priority number (RPN)" is used, especially for its ease and subjective evaluations of occurrence, the severity and the detectability of each failure. In this study, we have tried to apply FMEA model more compatible with health-care systems by redefining RPN index to be closer to reality. Methods: We used a quantitative and qualitative approach in this research. In the qualitative domain, focused groups discussion was used to collect data. A quantitative approach was used to calculate RPN score. Results: We have studied patient's journey in surgery ward from holding area to the operating room. The highest priority failures determined based on (1) defining inclusion criteria as severity of incident (clinical effect, claim consequence, waste of time and financial loss), occurrence of incident (time - unit occurrence and degree of exposure to risk) and preventability (degree of preventability and defensive barriers) then, (2) risks priority criteria quantified by using RPN index (361 for the highest rate failure). The ability of improved RPN scores reassessed by root cause analysis showed some variations. Conclusions: We concluded that standard criteria should be developed inconsistent with clinical linguistic and special scientific fields. Therefore, cooperation and partnership of technical and clinical groups are necessary to modify these models. [ABSTRACT FROM AUTHOR]

BACKGROUND: Ensuring about the patient's safety is the first vital step in improving the quality of care and the emergency ward is known as a high-risk area in treatment health care. The present study was conducted to evaluate the selected risk processes of emergency surgery department of a treatment-educational Qaem center in Mashhad by using analysis method of the conditions and failure effects in health care. METHODS: In this study, in combination (qualitative action research and quantitative crosssectional), failure modes and effects of 5 high-risk procedures of the emergency surgery department were identified and analyzed according to Healthcare Failure Mode and Effects Analysis (HFMEA). To classify the failure modes from the "nursing errors in clinical management model (NECM)", the classification of the effective causes of error from "Eindhoven model" and determination of the strategies to improve from the "theory of solving problem by an inventive method" were used. To analyze the quantitative data of descriptive statistics (total points) and to analyze the qualitative data, content analysis and agreement of comments of the members were used. RESULTS: In 5 selected processes by "voting method using rating", 23 steps, 61 sub-processes and 217 potential failure modes were identified by HFMEA. 25 (11.5%) failure modes as the high risk errors were detected and transferred to the decision tree. The most and the least failure modes were placed in the categories of care errors (54.7%) and knowledge and skill (9.5%), respectively. Also, 29.4% of preventive measures were in the category of human resource management strategy. CONCLUSION: "Revision and re-engineering of processes", "continuous monitoring of the works", "preparation and revision of operating procedures and policies", "developing the criteria for evaluating the performance of the personnel", "designing a suitable educational content for needs of employee", "training patients", "reducing the workload and power shortage", "improving team communication" and "preventive management of equipment's" were on the agenda as the guidelines. [ABSTRACT FROM AUTHOR]