Objective: We aimed to determine the epidemiological characteristics of asymptomatic AF in elder community population (≥65 years old) to analyze the detection rate of different screening methods. Methods: The study was a prospective cohort study. The elder (≥65 years old) residents who voluntarily participated in free physical examination in Dalian community were selected. The participants were randomly divided into screening group (including intensive screening group and single screening group) and control group. The control group received interrogation, medical history collection and routine 12-lead electrocardiogram (ECG) examination. Screening group received an additional single-lead ambulatory ECG equipment worn for 5-7 days. Intensive screening group received two equal-length wearings in 2020 and 2021 respectively, while one screening group only wore once in 2020. Results: Finally 3 340 residents ((70.7±5.0) years old) which consisted of 1 488 males (44.55%) were enrolled. There were 1 945 residents in screening group, including 859 in intensive screening group and 1 086 in one-time screening group. The control group included 1 395 people. Detection rate of asymptomatic AF was significantly higher in screening group than control group (79(4.06%) vs. 24(1.72%), P<0.001). Higher detection rate was found in screening group than control group in AF risk factors (1 or 2-3) subgroups and CHA₂DS₂-VASc score (2-3 or≥4) subgroups (P<0.05). Additionally, no difference was found between intensive screening group and single screening group (42(4.89%) vs. 37(3.41%), P=0.100). Intensive screening increased detection rate (7(6.93%) vs. 1(0.58%), P=0.009) only in residents those with low thrombosis risk (CHA₂DS₂-VaSc<2). Conclusions: Screening in elderly (≥65 years old) can significantly improve the detection rate of asymptomatic AF by wearing single lead dynamic ECG device. The rate increased significantly with the increase of risk factors associated with AF by single screening. In addition, repeat screening of the same method may only improve detection rates in the group with low risk thrombotic scores and non-combination of AF risk factors.Screening methods that are appropriate for different populations may require further exploration.
Male ; Humans ; Aged ; Atrial Fibrillation/epidemiology* ; Prospective Studies ; Electrocardiography ; Risk Factors ; Stroke ; Risk Assessment ; Mass Screening/methods*

BACKGROUND: Several studies have reported that polygenic risk scores (PRSs) can enhance risk prediction of coronary artery disease (CAD) in European populations. However, research on this topic is far from sufficient in non-European countries, including China. We aimed to evaluate the potential of PRS for predicting CAD for primary prevention in the Chinese population. METHODS: Participants with genome-wide genotypic data from the China Kadoorie Biobank were divided into training ( n = 28,490) and testing sets ( n = 72,150). Ten previously developed PRSs were evaluated, and new ones were developed using clumping and thresholding or LDpred method. The PRS showing the strongest association with CAD in the training set was selected to further evaluate its effects on improving the traditional CAD risk-prediction model in the testing set. Genetic risk was computed by summing the product of the weights and allele dosages across genome-wide single-nucleotide polymorphisms. Prediction of the 10-year first CAD events was assessed using hazard ratios (HRs) and measures of model discrimination, calibration, and net reclassification improvement (NRI). Hard CAD (nonfatal I21-I23 and fatal I20-I25) and soft CAD (all fatal or nonfatal I20-I25) were analyzed separately. RESULTS: In the testing set, 1214 hard and 7201 soft CAD cases were documented during a mean follow-up of 11.2 years. The HR per standard deviation of the optimal PRS was 1.26 (95% CI:1.19-1.33) for hard CAD. Based on a traditional CAD risk prediction model containing only non-laboratory-based information, the addition of PRS for hard CAD increased Harrell's C index by 0.001 (-0.001 to 0.003) in women and 0.003 (0.001 to 0.005) in men. Among the different high-risk thresholds ranging from 1% to 10%, the highest categorical NRI was 3.2% (95% CI: 0.4-6.0%) at a high-risk threshold of 10.0% in women. The association of the PRS with soft CAD was much weaker than with hard CAD, leading to minimal or no improvement in the soft CAD model. CONCLUSIONS In this Chinese population sample, the current PRSs minimally changed risk discrimination and offered little improvement in risk stratification for soft CAD. Therefore, this may not be suitable for promoting genetic screening in the general Chinese population to improve CAD risk prediction.
Male ; Humans ; Female ; Coronary Artery Disease/genetics* ; Biological Specimen Banks ; East Asian People ; Risk Assessment/methods* ; Genetic Predisposition to Disease/genetics* ; Risk Factors ; Genome-Wide Association Study

Objective: To analyze the level of PCDD/Fs exposure of occupational workers in the waste incineration industry and explore the risk of occupational exposure. Methods: In September 2021, literature on environmental PCDD/Fs exposure in waste incineration plants published from the establishment of the database to February 10, 2021 was retrieved from CNKI database. A total of 1365 literatures were retrieved, and 7 met the criteria for inclusion. The US Environmental Protection Agency (EPA) inhalation risk model was used to assess and analyze carcinogenic and non-carcinogenic risks of PCDD/Fs exposure among occupational workers in the waste incineration industry. Results: A total of 86 sampling sites were included in incineration plants in 7 regions. The study of Wuhan area showed that the concentration of working environment near the waste incinerator in the same factory was the highest, followed by the rest and office area in the factory. The concentration of PCDD/Fs in waste incinerators was the highest in Southwest China (4880.00-24880.00 pg TEQ/m(3)), and the lowest in Shenzhen (0.02-0.44 pg TEQ/m(3)). According to the cancer risk assessment, with the increase of exposure years, the risk of cancer increased. The highest risk of cancer was found in the waste incineration plants in Southwest China. When the exposure period was 1 year, the risk was moderate (22.40×10(-6)-114.20×10(-6)). When the exposure time was more than 5 years, the risk of cancer was high. In Jinan, workers working near the incinerator had a moderate risk of cancer after five years of exposure. In Zhejiang, workers were at medium risk of cancer after exposure for more than 20 years. Workers in Wuhan, Shanghai, Zhejiang Province, Shenzhen and the Pearl River Delta were still at low risk of cancer after 40 years of occupational exposure. HQ>1 of workers working near the waste incinerators in Jinan, Zhejiang Province and Southwest China, and the qualitative evaluation results showed that the non-carcinogenic risk was unacceptable. Conclusion: There are great differences in PCDD/Fs of occupational exposure in waste incineration industry, and the occupational exposure exceeding the occupational exposure limit has higher carcinogenic and non carcinogenic risks.
Humans ; Dibenzofurans ; Polychlorinated Dibenzodioxins/analysis* ; Air Pollutants/analysis* ; Incineration ; Dibenzofurans, Polychlorinated/analysis* ; China/epidemiology* ; Benzofurans ; Occupational Exposure/analysis* ; Carcinogens ; Risk Assessment ; Neoplasms ; Environmental Monitoring/methods*

BACKGROUND: Previous cardiovascular risk prediction models in Japan have utilized prospective cohort studies with concise data. As the health information including health check-up records and administrative claims becomes digitalized and publicly available, application of large datasets based on such real-world data can achieve prediction accuracy and support social implementation of cardiovascular disease risk prediction models in preventive and clinical practice. In this study, classical regression and machine learning methods were explored to develop ischemic heart disease (IHD) and stroke prognostic models using real-world data. METHODS: IQVIA Japan Claims Database was searched to include 691,160 individuals (predominantly corporate employees and their families working in secondary and tertiary industries) with at least one annual health check-up record during the identification period (April 2013-December 2018). The primary outcome of the study was the first recorded IHD or stroke event. Predictors were annual health check-up records at the index year-month, comprising demographic characteristics, laboratory tests, and questionnaire features. Four prediction models (Cox, Elnet-Cox, XGBoost, and Ensemble) were assessed in the present study to develop a cardiovascular disease risk prediction model for Japan. RESULTS: The analysis cohort consisted of 572,971 invididuals. All prediction models showed similarly good performance. The Harrell's C-index was close to 0.9 for all IHD models, and above 0.7 for stroke models. In IHD models, age, sex, high-density lipoprotein, low-density lipoprotein, cholesterol, and systolic blood pressure had higher importance, while in stroke models systolic blood pressure and age had higher importance. CONCLUSION Our study analyzed classical regression and machine learning algorithms to develop cardiovascular disease risk prediction models for IHD and stroke in Japan that can be applied to practical use in a large population with predictive accuracy.
Humans ; Cardiovascular Diseases/epidemiology* ; Prognosis ; Prospective Studies ; Japan/epidemiology* ; Stroke/etiology* ; Myocardial Ischemia/epidemiology* ; Risk Assessment/methods*

OBJECTIVE: We aimed to assess the feasibility and superiority of machine learning (ML) methods to predict the risk of Major Adverse Cardiovascular Events (MACEs) in chest pain patients with NSTE-ACS. METHODS: Enrolled chest pain patients were from two centers, Beijing Anzhen Emergency Chest Pain Center Beijing Bo'ai Hospital, China Rehabilitation Research Center. Five classifiers were used to develop ML models. Accuracy, Precision, Recall, F-Measure and AUC were used to assess the model performance and prediction effect compared with HEART risk scoring system. Ultimately, ML model constructed by Naïve Bayes was employed to predict the occurrence of MACEs. RESULTS: According to learning metrics, ML models constructed by different classifiers were superior over HEART (History, ECG, Age, Risk factors, & Troponin) scoring system when predicting acute myocardial infarction (AMI) and all-cause death. However, according to ROC curves and AUC, ML model constructed by different classifiers performed better than HEART scoring system only in prediction for AMI. Among the five ML algorithms, Linear support vector machine (SVC), Naïve Bayes and Logistic regression classifiers stood out with all Accuracy, Precision, Recall and F-Measure from 0.8 to 1.0 for predicting any event, AMI, revascularization and all-cause death ( vs. HEART ≤ 0.78), with AUC from 0.88 to 0.98 for predicting any event, AMI and revascularization ( vs. HEART ≤ 0.85). ML model developed by Naïve Bayes predicted that suspected acute coronary syndrome (ACS), abnormal electrocardiogram (ECG), elevated hs-cTn I, sex and smoking were risk factors of MACEs. CONCLUSION Compared with HEART risk scoring system, the superiority of ML method was demonstrated when employing Linear SVC classifier, Naïve Bayes and Logistic. ML method could be a promising method to predict MACEs in chest pain patients with NSTE-ACS.
Humans ; Acute Coronary Syndrome/epidemiology* ; Bayes Theorem ; Feasibility Studies ; Risk Assessment/methods* ; Chest Pain/etiology* ; Myocardial Infarction/diagnosis*

Objective: We aimed to determine the epidemiological characteristics of asymptomatic AF in elder community population (≥65 years old) to analyze the detection rate of different screening methods. Methods: The study was a prospective cohort study. The elder (≥65 years old) residents who voluntarily participated in free physical examination in Dalian community were selected. The participants were randomly divided into screening group (including intensive screening group and single screening group) and control group. The control group received interrogation, medical history collection and routine 12-lead electrocardiogram (ECG) examination. Screening group received an additional single-lead ambulatory ECG equipment worn for 5-7 days. Intensive screening group received two equal-length wearings in 2020 and 2021 respectively, while one screening group only wore once in 2020. Results: Finally 3 340 residents ((70.7±5.0) years old) which consisted of 1 488 males (44.55%) were enrolled. There were 1 945 residents in screening group, including 859 in intensive screening group and 1 086 in one-time screening group. The control group included 1 395 people. Detection rate of asymptomatic AF was significantly higher in screening group than control group (79(4.06%) vs. 24(1.72%), P<0.001). Higher detection rate was found in screening group than control group in AF risk factors (1 or 2-3) subgroups and CHA₂DS₂-VASc score (2-3 or≥4) subgroups (P<0.05). Additionally, no difference was found between intensive screening group and single screening group (42(4.89%) vs. 37(3.41%), P=0.100). Intensive screening increased detection rate (7(6.93%) vs. 1(0.58%), P=0.009) only in residents those with low thrombosis risk (CHA₂DS₂-VaSc<2). Conclusions: Screening in elderly (≥65 years old) can significantly improve the detection rate of asymptomatic AF by wearing single lead dynamic ECG device. The rate increased significantly with the increase of risk factors associated with AF by single screening. In addition, repeat screening of the same method may only improve detection rates in the group with low risk thrombotic scores and non-combination of AF risk factors.Screening methods that are appropriate for different populations may require further exploration.
Male ; Humans ; Aged ; Atrial Fibrillation/epidemiology* ; Prospective Studies ; Electrocardiography ; Risk Factors ; Stroke ; Risk Assessment ; Mass Screening/methods*

To compare different illness severity scores in predicting mortality risk of extremely low birth weight infants (ELBWI). From January 1st, 2019 to January 1st, 2020, all ELBWI admitted in the Children's Hospital of Nanjing Medical University, Nanjing Maternity and Child Health Care Hospital and the First Affiliated Hospital of Nanjing Medical University were included in the study. ELBWI with admission age ≥1 h, gestational age ≥37 weeks and incomplete data required for scoring were excluded. The clinical data were collected, neonatal critical illness score (NCIS), score for neonatal acute physiology version Ⅱ (SNAP-Ⅱ), simplified version of the score for neonatal acute physiology perinatal extension (SNAPPE-Ⅱ), clinical risk index for babies (CRIB) and CRIB-Ⅱ were calculated. The scores of the fatal group and the survival group were compared, and the receiver operating characteristic (ROC) curve was used to evaluate the predictive value of the above illness severity scores for the mortality risk of ELBWI. Pearson correlation analysis was used to analyze the correlation between illness scores and birth weight, illness scores and gestational age. A total of 192 ELBWI were finally included, of whom 114 cases survived (survival group) and 78 cases died (fatal group). There were significant differences in birth weight, gestational age and Apgar scores between fatal group and survival group (all <0.01). There were significant differences in NCIS, SNAP-Ⅱ, SNAPPE-Ⅱ, CRIB and CRIB-Ⅱ between fatal group and survival group (all <0.01). The CRIB had a relatively higher predictive value for the mortality risk. Its area under the ROC curve (AUC) was 0.787, the sensitivity was 0.678, the specificity was 0.804, and the Youden index was 0.482. The scores of NCIS, SNAP-Ⅱ, SNAPPE-Ⅱ, CRIB and CRIB-Ⅱ were significantly correlated with birth weight and gestational age (all <0.05). The correlation coefficients of CRIB-Ⅱ and CRIB with birth weight and gestational age were relatively large, and the correlations coefficients of NCIS with birth weight and gestational age were the smallest (0.191 and 0.244, respectively). Among these five illness severity scores, CRIB has better predictive value for the mortality risk in ELBWI. NCIS, which is widely used in China, has relatively lower sensitivity and specificity, and needs to be further revised.
Birth Weight ; Gestational Age ; Humans ; Infant ; Infant, Extremely Low Birth Weight ; Infant, Newborn ; Infant, Newborn, Diseases/mortality* ; Predictive Value of Tests ; Risk Assessment/methods* ; Severity of Illness Index

Objective: To explore the independent risk factors of internal mammary lymph nodes (IMN) metastasis and the risk assessment method of IMN metastasis preoperatively in breast cancer patients with negative IMN in imaging examination, and guide the radiotherapy of IMN in patients with different risk stratification of IMN metastasis. Methods: The clinical and pathological data of 301 breast cancer patients who underwent internal mammary sentinel node biopsy(IM-SLNB) and/or IMN dissection in Shandong Cancer Hospital with negative IMN on CT and/or MRI from January 2010 to October 2019 were analyzed retrospectively. The independent risk factors were analyzed by univariate and multivariate logistic regression, and the independent risk factors of IMN metastasis were used to risk stratification. Results: Among the 301 patients, 43 patients had IMN metastasis, and the rate of IMN metastasis was 14.3%. Univariate analysis showed that vascular tumor thrombus, progesterone receptor (PR) expression, T stage and N stage were associated with IMN metastasis. Multivariate logistic regression analysis showed that tumor located in medial quadrant, positive PR and axillary lymph node metastasis were independent risk factors for IMN metastasis. The risk of IMN metastasis was assessed according to the independent risk factors of the patients: low-risk group is including 0 risk factor, medium-risk group is including 1 risk factor, and high-risk group is including 2-3 risk factors. According to this evaluation criteria, 301 patients with breast cancer were divided into low-risk group (with 0 risk factors), medium-risk group (with 1 risk factor) and high-risk group (with 2-3 risk factors). The IMN metastasis rates were 0 (0/34), 4.3% (6/140) and 29.1% (37/127), respectively. Conclusions: The risk stratification of IMN metastasis according to three independent risk factors of IMN metastasis including tumor located in medial quadrant, positive PR and axillary lymph node metastasis in breast cancer patients can guide the radiotherapy of IMN in newly diagnosed breast cancer patients. For N1 patients, radiotherapy of IMN is strongly recommended when the primary tumor is located in the medial quadrant and/or PR positive.
Breast Neoplasms/pathology* ; Female ; Humans ; Lymph Nodes/pathology* ; Lymphatic Metastasis/pathology* ; Neoplasms, Second Primary/pathology* ; Retrospective Studies ; Risk Assessment ; Sentinel Lymph Node Biopsy/methods*

Food safety in China has been significantly improved since the melamine crisis in 2008 and the promulgation of the first Food Safety Law in 2009. However, food safety is a long standing issue in China due to the backward productive structure of agriculture and food business. In order to further improve the food safety in China, it is critical to reach a consensus on the leading edge concept of food safety and the identification of priority areas based on the concept. The leading edge concept of food safety aims to prevent potential issues and deal with current issues based on the risk, i.e. risk-based approach, as opposed to the concept based on the hazard, i.e. hazard-based approach. Practice is to determine the key problems that need to be solved first according to the concept. This paper expounds the different food safety management strategies and measures caused by the two concepts, and lists several key food safety problems (importance and solutions) determined according to the concept of "risk-based". These examples include foodborne diseases caused by pathogenic microorganisms, antimicrobial resistance, food allergen control, risk assessment of multiple chemical hazards exposure and alternative methods in food toxicology.
China ; Food ; Food Safety/methods* ; Foodborne Diseases ; Humans ; Risk Assessment

Risks exist in medicine related fields, which cannot be defined and quantified precisely. It is necessary to adopt a method for the risk assessment of uncertain and fuzzy phenomenon. This paper summarizes the thinking, procedure, advantage and application of fuzzy analytic hierarchy process in the risk assessment in medicine related fields for the purpose of providing reference for its further application.
Analytic Hierarchy Process ; Fuzzy Logic ; Humans ; Risk Assessment/methods*