AIM To study the association between vitamin D level and hospitalization rate in Crohn's disease(CD) patients.METHODS We designed a retrospective cohort study using adult patients(> 19 years) with CD followed f...AIM To study the association between vitamin D level and hospitalization rate in Crohn's disease(CD) patients.METHODS We designed a retrospective cohort study using adult patients(> 19 years) with CD followed for at least one year at our inflammatory bowel disease center. Vitamin D levels were divided into: low mean vitamin D level(< 30 ng/m L) vs appropriate mean vitamin D level(30-100 ng/m L). Generalized Poisson Regression Models(GPR) for Rate Data were used to estimate partially adjusted and fully adjusted incidence rate ratios(IRR) of hospitalization among CD patients. We also examined IRRs for vitamin D level as a continuous variable.RESULTS Of the 880 CD patients, 196 patients with vitamin D level during the observation period were included. Partially adjusted model demonstrated that CD patients with a low mean vitamin D level were almost twice more likely to be admitted(IRR = 1.76, 95%CI: 1.38-2.24) compared to those with an appropriate vitamin D level. The fully adjusted model confirmed this association(IRR = 1.44, 95%CI: 1.11-1.87). Partially adjusted model with vitamin D level as a continuous variable demonstrated,higher mean vitamin D level was associated with a 3% lower likelihood of admission with every unit(ng/m L) rise in mean vitamin D level(IRR = 0.97, 95%CI: 0.96-0.98). The fully adjusted model confirmed this association(IRR = 0.98, 95%CI: 0.97-0.99). CONCLUSION Normal or adequate vitamin D stores may be protective in the clinical course of CD. However, this role needs to be further characterized and understood.展开更多
INTRODUCTIONCancer treatment situation in tumor hospitals inChina has its own unique characteristics which arenot found in other parts of the world. Because ofthe huge population and high incidence rates ofesophageal ...INTRODUCTIONCancer treatment situation in tumor hospitals inChina has its own unique characteristics which arenot found in other parts of the world. Because ofthe huge population and high incidence rates ofesophageal and stomach cancer[1-5], the number ofcancer patients waiting for admission isinconceivably large.展开更多
We have proposed a new mathematical method,the SEIHCRD model,which has an excellent potential to predict the incidence of COVID-19 diseases.Our proposed SEIHCRD model is an extension of the SEIR model.Three-compartmen...We have proposed a new mathematical method,the SEIHCRD model,which has an excellent potential to predict the incidence of COVID-19 diseases.Our proposed SEIHCRD model is an extension of the SEIR model.Three-compartments have added death,hospitalized,and critical,which improves the basic understanding of disease spread and results.We have studiedCOVID-19 cases of six countries,where the impact of this disease in the highest are Brazil,India,Italy,Spain,the United Kingdom,and the United States.After estimating model parameters based on available clinical data,the modelwill propagate and forecast dynamic evolution.Themodel calculates the Basic reproduction number over time using logistic regression and the Case fatality rate based on the selected countries’age-category scenario.Themodel calculates two types of Case fatality rate one is CFR daily,and the other is total CFR.The proposed model estimates the approximate time when the disease is at its peak and the approximate time when death cases rarely occur and calculate how much hospital beds and ICU beds will be needed in the peak days of infection.The SEIHCRD model outperforms the classic ARXmodel and the ARIMA model.RMSE,MAPE,andRsquaredmatrices are used to evaluate results and are graphically represented using Taylor and Target diagrams.The result shows RMSE has improved by 56%–74%,and MAPE has a 53%–89%improvement in prediction accuracy.展开更多
Summary:Throughout the duration of the New Cooperative Medical Scheme(NCMS),it was found that an increasing number of rural patients were seeking out-of^county medical treatment,which posed a great burden on the NCMS ...Summary:Throughout the duration of the New Cooperative Medical Scheme(NCMS),it was found that an increasing number of rural patients were seeking out-of^county medical treatment,which posed a great burden on the NCMS fund.Our study was conducted to examine the prevalence of out-of^county hospitalizations and its related factors,and to provide a scientific basis for follow?up health insurance policies.A total of 215 counties in central and western China from 2008 to 2016 were selected.The total out-of-county hospitalization rate in nine years was 16.95%,which increased from 12.37%in 2008 to 19.21%in 2016 with an average annual growth rate of 5.66%.Its related expenses and compensations were shown to increase each year,with those in the central region being higher than those in the western region.Stepwise logistic regression reveals that the increase in out-of-county hospitalization rate was associated with region(XI),rural population(X2),per capita per year net income(X3),per capita gross domestic product(GDP)(X4),per capita funding amount of NCMS(X5),compensation ratio of out-of^county hospitalization cost(X6),per time average in-county(X7)and out-of-county hospitalization cost(X8).According to Bayesian network(BN),the marginal probability of high out-of^county hospitalization rate was as high as 81.7%.Out-of^county hospitalizations were directly related to X8,X3,X4 and X6.The probability of high out-of-county hospitalization obtained based on hospitalization expenses factors,economy factors,regional characteristics and NCMS policy factors was 95.7%,91.1%,93.0% and 88.8%,respectively.And how these factors affect out-of-county hospitalization and their interrelationships were found out.Our findings suggest that more attention should be paid to the influence mechanism of these factors on out-of-county hospitalizations,and the increase of hospitalizations outside the county should be reasonably supervised and controlled and our results will be used to help guide the formulation of proper intervention policies.展开更多
Objective To investigate the infection rate of hepatitis C virus among the ambulatory patients and in-patients of a tertiary teaching hospital,and study the demographic factors related to the prevalence of hepatitis C...Objective To investigate the infection rate of hepatitis C virus among the ambulatory patients and in-patients of a tertiary teaching hospital,and study the demographic factors related to the prevalence of hepatitis C virus infection.Methods All patients tested for hepatitis C virus antibody from July 2008 to July 2009 in Peking Union Medical College Hospital were enrolled in this cross-sectional analysis.The prevalence of hepatitis C virus infection was compared according to age,gender,and departments,respectively.Among patients with positive serology hepatitis C virus marker,the positivity of hepatitis C virus RNA was analysed.Results Among 29 896 subjects included,the hepatitis C virus antibody of 494 patients were positive(1.7%).When patients were divided into 9 age groups,the age specific prevalence of hepatitis C virus antibody were0.2%,1.7%,1.2%,1.1%,1.5%,1.9%,2.6%,2.4%and 2%,respectively.The prevalence of hepatitis C virus antibody in non-surgical department and surgical department was 3%and 1%,respectively.The prevalence of hepatitis C virus antibody of males was higher than that of the females.Total of 194 patients with positive hepatitis C virus antibody were tested for hepatitis C virus RNA,the RNA level of 113 patients(58.2%)were higher than the low detection limit.Conclusions The prevalence of hepatitis C virus antibody was relatively high among patients of general tertiary hospital.Age group of 60-69,males and patients in non-surgical departments were factors associated with high rate of hepatitis C virus infection.展开更多
Introduction: On March 11, 2020, the World Health Organization (WHO) declared that the entire World was overrun by a pandemic. Science has managed, in a short time, to characterize a new disease, sequence a new viral ...Introduction: On March 11, 2020, the World Health Organization (WHO) declared that the entire World was overrun by a pandemic. Science has managed, in a short time, to characterize a new disease, sequence a new viral genome, develop diagnostics, produce treatment protocols and establish the efficacy of drugs and vaccines in randomized controlled trials. In this paper we have dealt with different topics regarding the pandemic linked to COVID-19. Objectives: Aim of this paper is to compare the number of deaths attributable to COVID-19, that occurred in the different Italian macro-areas, in the different pandemic waves;we studied the trend of the curves relating to the proportion of deaths to the number of infected in the Italian macro-areas for the pandemic waves and analysed the mortality data, focusing on the Italian context and comparing it with other foreign countries. We examined the data regarding swabs, hospitalizations, home isolation, admissions to intensive care and deaths registered in pandemic period. Results: Geographically, Italy was differently affected by the pandemic. Northern Italy was the most affected area. In comparison with some foreign countries, Italy is one of the nations that paid the most in terms of deaths, due to: delays in understanding the seriousness of the emergency;the slow management in the tracking systems of contagions;the high number of hospitalizations;a corporate organizational system poorly planned. Conclusion: The years 2020 and 2021 have been dramatic and unprecedented. The year 2021 was the year of redemption, where, despite social, economic and health difficulties, thanks to mass vaccination, we were able to give a real strong response to the pandemic. Trust in science has led to a drastic decrease in mortality throughout the world.展开更多
文摘AIM To study the association between vitamin D level and hospitalization rate in Crohn's disease(CD) patients.METHODS We designed a retrospective cohort study using adult patients(> 19 years) with CD followed for at least one year at our inflammatory bowel disease center. Vitamin D levels were divided into: low mean vitamin D level(< 30 ng/m L) vs appropriate mean vitamin D level(30-100 ng/m L). Generalized Poisson Regression Models(GPR) for Rate Data were used to estimate partially adjusted and fully adjusted incidence rate ratios(IRR) of hospitalization among CD patients. We also examined IRRs for vitamin D level as a continuous variable.RESULTS Of the 880 CD patients, 196 patients with vitamin D level during the observation period were included. Partially adjusted model demonstrated that CD patients with a low mean vitamin D level were almost twice more likely to be admitted(IRR = 1.76, 95%CI: 1.38-2.24) compared to those with an appropriate vitamin D level. The fully adjusted model confirmed this association(IRR = 1.44, 95%CI: 1.11-1.87). Partially adjusted model with vitamin D level as a continuous variable demonstrated,higher mean vitamin D level was associated with a 3% lower likelihood of admission with every unit(ng/m L) rise in mean vitamin D level(IRR = 0.97, 95%CI: 0.96-0.98). The fully adjusted model confirmed this association(IRR = 0.98, 95%CI: 0.97-0.99). CONCLUSION Normal or adequate vitamin D stores may be protective in the clinical course of CD. However, this role needs to be further characterized and understood.
基金Supported by the Hebei Provincial Scientific Commission, No. 97276162D
文摘INTRODUCTIONCancer treatment situation in tumor hospitals inChina has its own unique characteristics which arenot found in other parts of the world. Because ofthe huge population and high incidence rates ofesophageal and stomach cancer[1-5], the number ofcancer patients waiting for admission isinconceivably large.
基金The work has been supported by a grant received from the Ministry of Education,Government of India under the Scheme for the Promotion of Academic and Research Collaboration(SPARC)(ID:SPARC/2019/1396).
文摘We have proposed a new mathematical method,the SEIHCRD model,which has an excellent potential to predict the incidence of COVID-19 diseases.Our proposed SEIHCRD model is an extension of the SEIR model.Three-compartments have added death,hospitalized,and critical,which improves the basic understanding of disease spread and results.We have studiedCOVID-19 cases of six countries,where the impact of this disease in the highest are Brazil,India,Italy,Spain,the United Kingdom,and the United States.After estimating model parameters based on available clinical data,the modelwill propagate and forecast dynamic evolution.Themodel calculates the Basic reproduction number over time using logistic regression and the Case fatality rate based on the selected countries’age-category scenario.Themodel calculates two types of Case fatality rate one is CFR daily,and the other is total CFR.The proposed model estimates the approximate time when the disease is at its peak and the approximate time when death cases rarely occur and calculate how much hospital beds and ICU beds will be needed in the peak days of infection.The SEIHCRD model outperforms the classic ARXmodel and the ARIMA model.RMSE,MAPE,andRsquaredmatrices are used to evaluate results and are graphically represented using Taylor and Target diagrams.The result shows RMSE has improved by 56%–74%,and MAPE has a 53%–89%improvement in prediction accuracy.
基金This work was supported by the National Natural Science Foundation of China(No.71573192 and No.81573262)the Fundamental Research Funds for the Central Universities,HUST(No.2016YXZD042).
文摘Summary:Throughout the duration of the New Cooperative Medical Scheme(NCMS),it was found that an increasing number of rural patients were seeking out-of^county medical treatment,which posed a great burden on the NCMS fund.Our study was conducted to examine the prevalence of out-of^county hospitalizations and its related factors,and to provide a scientific basis for follow?up health insurance policies.A total of 215 counties in central and western China from 2008 to 2016 were selected.The total out-of-county hospitalization rate in nine years was 16.95%,which increased from 12.37%in 2008 to 19.21%in 2016 with an average annual growth rate of 5.66%.Its related expenses and compensations were shown to increase each year,with those in the central region being higher than those in the western region.Stepwise logistic regression reveals that the increase in out-of-county hospitalization rate was associated with region(XI),rural population(X2),per capita per year net income(X3),per capita gross domestic product(GDP)(X4),per capita funding amount of NCMS(X5),compensation ratio of out-of^county hospitalization cost(X6),per time average in-county(X7)and out-of-county hospitalization cost(X8).According to Bayesian network(BN),the marginal probability of high out-of^county hospitalization rate was as high as 81.7%.Out-of^county hospitalizations were directly related to X8,X3,X4 and X6.The probability of high out-of-county hospitalization obtained based on hospitalization expenses factors,economy factors,regional characteristics and NCMS policy factors was 95.7%,91.1%,93.0% and 88.8%,respectively.And how these factors affect out-of-county hospitalization and their interrelationships were found out.Our findings suggest that more attention should be paid to the influence mechanism of these factors on out-of-county hospitalizations,and the increase of hospitalizations outside the county should be reasonably supervised and controlled and our results will be used to help guide the formulation of proper intervention policies.
文摘Objective To investigate the infection rate of hepatitis C virus among the ambulatory patients and in-patients of a tertiary teaching hospital,and study the demographic factors related to the prevalence of hepatitis C virus infection.Methods All patients tested for hepatitis C virus antibody from July 2008 to July 2009 in Peking Union Medical College Hospital were enrolled in this cross-sectional analysis.The prevalence of hepatitis C virus infection was compared according to age,gender,and departments,respectively.Among patients with positive serology hepatitis C virus marker,the positivity of hepatitis C virus RNA was analysed.Results Among 29 896 subjects included,the hepatitis C virus antibody of 494 patients were positive(1.7%).When patients were divided into 9 age groups,the age specific prevalence of hepatitis C virus antibody were0.2%,1.7%,1.2%,1.1%,1.5%,1.9%,2.6%,2.4%and 2%,respectively.The prevalence of hepatitis C virus antibody in non-surgical department and surgical department was 3%and 1%,respectively.The prevalence of hepatitis C virus antibody of males was higher than that of the females.Total of 194 patients with positive hepatitis C virus antibody were tested for hepatitis C virus RNA,the RNA level of 113 patients(58.2%)were higher than the low detection limit.Conclusions The prevalence of hepatitis C virus antibody was relatively high among patients of general tertiary hospital.Age group of 60-69,males and patients in non-surgical departments were factors associated with high rate of hepatitis C virus infection.
文摘Introduction: On March 11, 2020, the World Health Organization (WHO) declared that the entire World was overrun by a pandemic. Science has managed, in a short time, to characterize a new disease, sequence a new viral genome, develop diagnostics, produce treatment protocols and establish the efficacy of drugs and vaccines in randomized controlled trials. In this paper we have dealt with different topics regarding the pandemic linked to COVID-19. Objectives: Aim of this paper is to compare the number of deaths attributable to COVID-19, that occurred in the different Italian macro-areas, in the different pandemic waves;we studied the trend of the curves relating to the proportion of deaths to the number of infected in the Italian macro-areas for the pandemic waves and analysed the mortality data, focusing on the Italian context and comparing it with other foreign countries. We examined the data regarding swabs, hospitalizations, home isolation, admissions to intensive care and deaths registered in pandemic period. Results: Geographically, Italy was differently affected by the pandemic. Northern Italy was the most affected area. In comparison with some foreign countries, Italy is one of the nations that paid the most in terms of deaths, due to: delays in understanding the seriousness of the emergency;the slow management in the tracking systems of contagions;the high number of hospitalizations;a corporate organizational system poorly planned. Conclusion: The years 2020 and 2021 have been dramatic and unprecedented. The year 2021 was the year of redemption, where, despite social, economic and health difficulties, thanks to mass vaccination, we were able to give a real strong response to the pandemic. Trust in science has led to a drastic decrease in mortality throughout the world.