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RESUMEN La fotocatálisis homogénea foto-Fenton es uno de los procesos de oxidación avanzada más utilizados en el tratamiento de aguas residuales con contenido de pesticidas, donde la optimización de la dosis de catalizador y el agente oxidante, teniendo como respuesta la mineralización en términos de carbón orgánico total (COT) o la eliminación del contaminante específico, son el objetivo de cualquier diseño experimental. El desarrollo experimental en los procesos de tratamiento requiere la ejecución de una cantidad significativa de condiciones experimentales que necesitan el uso de reactivos, energía y tiempo de ejecución, por lo tanto, el modelamiento de este tipo de fenómenos surge como una alternativa a esta limitante en los tratamientos de aguas residuales. En esta investigación, se evaluó la influencia de los factores FeSO4 y H2O2, cada uno en tres niveles, en la mineralización de una solución sintética del insecticida Carbendazim (50 mg.L-1), en términos de COT, mediante un modelo de regresión lineal múltiple y optimizado por una superficie de respuesta. Los principales resultados establecieron que el mejor ajuste del modelo se da teniendo en cuenta la interacción entre el FeSO4 y el H2O2 (X1*X2) y los términos cuadráticos de cada una de ellas con p-values <0,05 y que la validación del modelo, mediante la técnica Leave-One-Out Cross Validation (LOOCV), así como la exactitud y la precisión, mediante el análisis de residuos y el supuesto de mínimos cuadrados ordinarios, establecen que las conclusiones que se deriven de él son válidas.
ABSTRACT Homogeneous photo-Fenton photocatalysis is one of the most widely used advanced oxidation processes in treating wastewater containing pesticides, where optimizing the catalyst dosage and oxidizing agent, with the response being mineralization in terms of total organic carbon (TOC) or removal of the specific contaminant, is the goal of any experimental design. Experimental development in treatment processes necessitates executing a significant number of experimental conditions that require the use of reagents, energy, and execution time. Therefore, modeling such phenomena emerges as an alternative to these limitations in wastewater treatment. In this research, the influence of factors FeSO4 and H2O2, each at three levels, on the mineralization of a synthetic solution of the insecticide Carbendazim (50 mg.L-1) in terms of TOC was evaluated using a multiple linear regression model optimized by response surface methodology. The main results established that the best model fit considers the interaction between FeSO4 and H2O2 (X 1 *X 2 ) and the quadratic terms of each with p-values<0.05. The validation of the model using the Leave-One-Out Cross Validation (LOOCV) technique, as well as accuracy and precision through residual analysis and ordinary least squares assumptions, confirms the validity of the conclusions derived from it.
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OBJECTIVE To provide reference for improving the disease diagnosis related groups （DRG） payment reform， promoting refined hospital operation and management and rational drug use. METHODS Taking the orthopedic department of our hospital （the Third Affiliated Hospital of Anhui Medical University） as the research object， based on evidence-based medicine， a medication clinical pathway （hereinafter referred to as medication pathway） for DRG diseases in this department was constructed and implemented. All patients who met the DRG disease were included in the medication path management， and the patients in the same DRG disease group were treated with the same treatment method. Segmented regression model （SRM） was adopted to analyze the effects of medication pathway on the medical service capacity， efficiency and quality of our hospital. RESULTS During the implementation of medication pathway， significant decreases were observed in average length of hospital stay， cost per hospitalization， the proportion of medication expenses， medication cost per hospitalization and defined daily dose； the proportion of medical service revenue and the qualified rate of medical orders significantly increased （P＜0.05）. After the implementation of medication pathway， the average length of hospital stay and defined daily dose continued to decrease， and the qualified rate of medical orders also continued to significantly increase （P＜0.05）. CONCLUSIONS The implementation of medication pathway enhances the quality of medical services， improves operational efficiency， reduces medical expenses， and contributes to the development of a refined hospital management system.
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Objective @#To analyze the incidence characteristics and trends in pulmonary tuberculosis in the Hotan prefecture , before and after the epidemic , and to provide a reference basis for the formulation and evaluation of tuberculosis prevention and control measures in the Hotan prefecture . @*Methods @#The Hotan prefecture ’s pulmonary tuberculosis incidence data was collected between 2015 and 2021 . Joinpoint regression (JPR) model and Interrupted Time Series (ITS) model were established to explore the incidence trend of pulmonary tuberculosis , as well as the impact of COVID-19 prevention and control measures in Xinjiang on the incidence trend in Hotan , respectively. Furthermore , an analysis of variations in incidence among different age and gender subgroups was carried out. @*Results@#The results of the JPR model showed that from 2015 to 2021 , the reported incidence rate of pulmonary tuberculosis in the Hotan prefecture initially increased and then decreased , with a turning point appearing in December 2018 . The incidence rate in males was slightly higher than that in females , and the turning point and incidence trend were consistent with the overall trend . Among all age subgroups , those ≥60 age group had the highest incidence rate , with the trend also showing an initial increase followed by a decrease . A turning point in the incidence rate for the under 18 age group appeared in June 2021 , yet the trend was not statistically significant (P > 0. 05) .The turning points in the 19 - 59 age group and in those aged ≥60 were consistent with the overall trend . The results of the ITS model showed that the incidence rate of pulmonary tuberculosis in the Hotan prefecture significantly decreased since January 2020 , dropping from 319. 28 per 100 000 in 2019 to 155 . 88 per 100 000 in 2021 , a decrease of 51 . 16% year-on-year , with a monthly average reduction of 0. 049 per 100 000 .@*Conclusion @# In 2018 ,Xinjiang province integrated tuberculosis screening into the universal health checkup for the entire population ,which led to the identification of numerous cases of tuberculosis . In the Hotan prefecture , the reported incidence of pulmonary tuberculosis peaked in December 2018 and then started to decline . Under the impact of COVID-19 isolation measures in Xinjiang , the reported incidence rate showed a notable decrease starting in January 2020 . Reiterating preventive measures and remaining watchful for the possible appearance of latent tuberculosis patients is crucial as the pandemic fades .
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Background Arsenic, cobalt, barium, and other individual metal exposure have been confirmed to be associated with the incidence of kidney stones. However, there are few studies on the association between mixed metal exposure and kidney stones, especially in occupational groups. Objective To investigate the association between mixed metal exposure and kidney stones in an occupational population from a metal smelting plant. Methods A questionnaire survey was conducted to collect sociodemographic characteristics, medical history, and lifestyle information of 1158 mixed metal-exposed workers in a metal smelting plant in Guangdong Province from July 2021 to January 2022. Midstream morning urine samples were collected from the workers, the concentrations of 18 metals including lithium, vanadium, chromium, manganese, cobalt, nickel, copper, zinc, arsenic, selenium, strontium, molybdenum, cadmium, cesium, barium, tungsten, titanium, and lead were measured by inductively coupled plasma mass spectrometry, and the urinary mercury levels were measured by cold atomic absorption spectroscopy. Based on predetermined inclusion criteria, a total of 919 mixed metal-exposed workers were included in the study, including 117 workers in the kidney stone group and 802 workers in the non-kidney stone group. With a detection rate of urinary metals greater than 80% as entry criterion, 16 eligible metals were finally included for further analysis. Parametric or non-parametric methods were used to compare the differences between continuous or categorical variables of the non-kidney stone group and the kidney stone group. Logistic regression models were constructed to explore the association between individual metal exposures and kidney stones. Weighted quantile sum (WQS) regression models were used to evaluate the association between mixed metal exposure and kidney stones, as well as the weights of each metal on kidney stones. Then Bayesian kernel machine regression (BKMR) models were used to explore the overall effect of mixed metal exposure on renal calculi and the potential interactions between metals. Results We found that there were significant differences in sex, age, length of service, and body mass Index (BMI) between the non-kidney stone group and the kidney stone group (P<0.05). The urinary concentrations of molybdenum and barium in the kidney stone group were higher than those in the non-kidney stone group, and the differences were statistically significant (P<0.05). The logistic regression models demonstrated that urinary cobalt, arsenic, molybdenum, and barium were positively correlated with the risk of kidney stones (Ptrend<0.05). The WQS regression models showed that the mixed exposure to vanadium, cobalt, arsenic, molybdenum, and barium was positively associated with the risk of kidney stones (P<0.05). Among them, molybdenum, arsenic, and barium accounted for 0.391, 0.337, and 0.154, respectively. The BKMR results revealed a positive association between metal mixture exposure and the risk of kidney stones (P<0.05). When other metals were fixed at the 25th, 50th, or 75th percentile, arsenic, molybdenum, cobalt, and barium exhibited significant positive effects on the risk of kidney stones (P<0.05), while vanadium showed a significant negative effect (P<0.05). The interaction analysis demonstrated interactions between barium and cobalt, as well as between vanadium and cobalt (P<0.05). Conclusion In the occupational population of this smelter, occupational mixed metal exposure could increase the risk of kidney stones, and the main metals are molybdenum, arsenic, barium, and cobalt.
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Objective To analyze the trends in Oncomelania hupensis distribution in Wuhan City, Hubei Province from 2003 to 2022, so as to provide insights into precision schistosomiasis control. Methods Data pertaining to O. hupensis snail survey in Wuhan City from 2003 to 2022 were collected. The trends in the proportion of areas with snail habitats, actual area with snail habitats, mean density of living snails and prevalence of Schistosoma japonicum infection in snails were evaluated in schistosomiasis-endemic areas of Wuhan City from 2003 to 2022 with the slope of trend curve (β), annual percent change (APC) and average annual percent change (AAPC) using a Joinpoint regression model. Results During the period from 2003 through 2022, there were two turning points for the proportion of areas with snail habitats in Wuhan City in 2005 and 2015, with a rise during the period from 2003 to 2005 (β1 = 5.93, t = 1.280, P > 0.05), a decline from 2005 to 2015 (β2 = −0.88, t = −2.074, P > 0.05) and a rise from 2015 to 2022 (β3 = 1.46, t = −2.356, P < 0.05). During the period from 2003 through 2022, there were two turning points for the proportion of areas with snail habitats in islet endemic areas of Wuhan City in 2006 and 2015, with no significant differences in the trends from 2003 to 2006 (β1 = 4.64, t = 1.888, P > 0.05) or from 2006 to 2015 (β2 = −1.45, t = −2.143, P > 0.05), and with a tendency towards a rise from 2015 to 2022 (β3 = 2.04, t = −3.100, P < 0.05). During the period from 2003 through 2022, there were two turning points for the proportion of areas with snail habitats in inner embankment endemic areas of Wuhan City in 2012 and 2020, with a tendency towards a decline from 2003 to 2012 (β1 = −0.39, t = −4.608, P < 0.05) and with no significant differences in the trends from 2012 to 2020 (β2 = 0.03, t = 0.245, P > 0.05) and from 2020 to 2022 (β3 = 1.38, t = 1.479, P > 0.05). During the period from 2003 to 2022, the actual area with snail habitats all appeared a tendency towards a decline in Wuhan City, and in islet and inner embankment endemic areas of Wuhan City from 2003 to 2022 (AAPC = −2.39%, −5.75% and −2.35%, all P values < 0.05). The mean density of living snails reduced from 0.087 snails/0.1 m2 in 2003 to 0.027 snails/0.1 m2 in 2022 in Wuhan City, with a significant difference in the tendency towards the decline (APC = AAPC = −11.47%, P < 0.05). The annual mean decline rate of the mean density of living snails was 17.36% in outside embankment endemic areas of Wuhan City from 2003 to 2022 (APC = AAPC = −17.36%, P < 0.05), and there was no significant difference in the trends in the mean density of living snails in islet endemic areas of Wuhan City from 2003 to 2022 (APC = AAPC = −0.97%, P > 0.05). In addition, the prevalence of S. japonicum infection in snails appeared a tendency towards a decline in Wuhan City from 2003 to 2022 (APC = AAPC = −12.45%, P < 0.05). Conclusions The proportion of areas with snail habitats, actual area with snail habitats, mean density of living snails and prevalence of S. japonicum infection in snails all appeared a tendency towards a decline in Wuhan City from 2003 to 2022. Intensified snail control, modification of snail habitats, shrinking of areas with snails and implementation of grazing prohibition in snail-infested settings are required, in order to facilitate the progress towards schistosomiasis elimination in Wuhan City.
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Objective To understand the epidemiological characteristics of scrub typhus disease and to provide a scientific basis for the prevention and control of scrub typhus disease. Methods Descriptive epidemiological methods were used to analyze the population and regional distribution of scrub typhus. Seasonal characteristics were analyzed using concentration method and circular distribution method, and incidence trend was analyzed using joinpoint regression model. Results The annual incidence rate of scrub typhus was 0.95/100 000 from 2010 to 2022. The incidence rate of male was 0.77/100 000, lower than that of female 1.12/100 000 (χ2=18.89, P-=-62.3728, S=20.8960. The circular distribution results indicated that the peak day was October 19th, and the peak period was between October 7 to December 19. The average annual percentage change (AAPC) of the incidence rate from 2010 to 2022 was 13.70%, 95% CI (-8.62%~41.48%), and the incidence rate showed an upward trend (t=1.15, P=0.249). Conclusion The incidence of scrub typhus disease is strictly seasonal, and the incidence rate over the years shows an upward trend. It is necessary to strengthen monitoring and take various intervention measures to reduce the risk of scrub typhus disease.
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Objective To investigate the relationship between vitamin K2,insulin-like growth factor bind-ing protein 3(IGFBP-3),Omentin-1 and the therapeutic effect on children with idiopathic short stature(ISS),and to build a prediction model.Methods A total of 242 ISS children in Jinan Second Maternal and Child Health Hospital from 2019 to 2021 were selected.All of them received recombinant human growth hormone(rhGH)treatment and were divided into effective group and ineffective group according to the therapeutic effect after 12 months of treatment.The general data,vitamin K2,IGFBP-3 and Omentin-1 in the two groups were analyzed.The influencing factors of ISS children's therapeutic effect were analyzed by Logistic regression model and decision tree model.The predictive performance of two models was analyzed by using receiver oper-ating characteristic(ROC)curve.Results There were statistically significant differences in 25-hydroxy vita-min D[25(OH)D],parathyroid hormone(PTH),thyroid stimulating hormone(TSH),vitamin K2,IGFBP-3,Omentin-1,rhGH dosage and weekly outdoor exercise time between the two groups(P＜0.05).Logistic re-gression showed that PTH(OR=7.011,95％CI:2.456-20.014),vitamin K2(OR=0.605,95％CI:.0.465-0.788),IGFBP-3(OR=0.458,95％CI:0.321-0.654),Omentin-1(OR=0.514,95％CI:0.389-0.679)and rhGH dose(OR=0.563,95％CI:0.445-0.712)]were the influential factors for treatment ineffectiveness in ISS children(P＜0.05).The decision tree model showed that vitamin K2,IGFBP-3 and Omentin-1 were the factors influencing the therapeutic effect of ISS,and IGFBP-3 had the most significant impact.ROC curve re-sults showed that the area under the curve of decision tree model and Logistic regression model were 0.922 and 0.908,respectively,with good classification effect.Conclusion The therapeutic effect of ISS children is in-fluenced by factors such as vitamin K2,IGFBP-3,Omentin-1,and so on,and IGFBP-3 has the most significant impact.Logistic regression model and decision tree model could complement each other so as to provide refer-ence for improving the therapeutic effect of ISS children from different aspects.
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Abstract Introduction: Plant functional traits are widely used to predict community productivity. However, they are rarely used to predict the performance (in terms of growth diameter, growth height, survival, and integral response index) of woody species planted in degraded soils. Objective: To evaluate the relationship between the functional traits and the performance of 25 woody species planted in disturbed soils affected by oil extraction activities in Ecuadorian Amazon. Methods: Eighteen permanent sampling plots were established and five 6-month-old seedlings of each 25 species were randomly planted in each plot (125 individuals per plot), at a distance of 4×4 m. Eight quantitative functional traits (leaf size, specific leaf area, leaf nitrogen concentration, leaf phosphorus concentration, leaf minimum unit, leaf dry matter content, stem specific density and leaf tensile strength) were determined for each species. Results: The woody species with high performance shows greater leaf size, specific leaf area and Stem Specific Density than those showing low performance. Leaf nitrogen concentration and stem specific density had a direct relationship with the integral response index. The leaf size, leaf phosphorus concentration, leaf dry matter content and leaf tensile strength showed a negative relationship with the integral response index. Conclusions: Our study demonstrated that the performance of woody species o disturbed soils can be predicted satisfyingly by leaf and stem functional traits, presumably because these traits capture most of environmental and neighborhood conditions.
Resumen Introducción: Los rasgos funcionales de las plantas han sido ampliamente utilizados para predecir la productividad (en términos de crecimiento en diámetro, crecimiento en altura, sobrevivencia e índice de respuesta integral) de las comunidades vegetales. Sin embargo, rara vez han sido utilizados para predecir el desempeño de las especies leñosas plantadas en suelos degradados. Objetivo: Evaluar la relación entre el desempeño y los rasgos funcionales de 25 especies leñosas plantadas en suelos afectados por actividades de extracción de petróleo en la Amazonía ecuatoriana. Métodos: Se establecieron 18 parcelas permanentes de muestreo y en cada parcela se sembraron aleatoriamente cinco plántulas de 6 meses de las 25 especies (125 individuos por parcela), a una distancia de 4×4 m. Se determinaron ocho rasgos funcionales (área foliar, área foliar específica, concentración de nitrógeno foliar, concentración de fósforo foliar, unidad mínima foliar, contenido foliar de materia seca, densidad específica del fuste y fuerza tensil foliar) de cada especie. Resultados: Las especies leñosas con alto desempeño presentaron mayor área foliar, área foliar específica y densidad específica del fuste que las especies de bajo desempeño. La concentración de nitrógeno foliar y la densidad específica del fuste mostraron una relación directa. El área foliar, la concentración de fósforo foliar, el contenido de materia seca foliar y la fuerza tensil foliar presentaron una relación inversa con el Índice de Respuesta Integral. Conclusión: Se demostró que el desempeño de las especies leñosas plantadas en suelos alterados puede predecirse satisfactoriamente por rasgos funcionales de hoja y de tallo, debido posiblemente a que los rasgos influyen en el crecimiento y supervivencia de las especies, y reflejan la mayoría de las condiciones ambientales.
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Trees/growth & development , Petroleum Pollution/analysis , Amazonian Ecosystem , EcuadorABSTRACT
OBJECTIVE@#To evaluate the trend of notified incidence of pulmonary tuberculosis (PTB) in China at different periods by population and region and to explore the effect of TB prevention and control in recent years.@*METHODS@#Using pooled data on TB cases reported by the TB Information Management Reporting System (TBIMS) from 2005 to 2020, we calculated the annual percentage change (APC) using the Joinpoint regression model.@*RESULTS@#From 2005 to 2020, a total of 16.2 million cases of PTB were reported in China, with an average notified incidence of 75.5 per 100,000 population. The age standardization rate (ASR) continued to decline from 116.9 (/100,000) in 2005 to 47.6 (/100,000) in 2020, with an average annual decrease of 5.6% [APC = -5.6, 95% confidence interval ( CI): -7.0 to -4.2]. The smallest decline occurred in 2011-2018 (APC = -3.4, 95% CI: -4.6 to -2.3) and the largest decrease in 2018-2020 (APC = -9.2, 95% CI: -16.4 to -1.3). From 2005 to 2020, the ASR in males (159.8 per 100,000 in 2005, 72.0 per 100,000 in 2020) was higher than that in females (62.2 per 100,000 in 2005, 32.3 per 100,000 in 2020), with an average annual decline of 6.0% for male and 4.9% for female. The average notified incidence was the highest among older adults (65 years and over) (182.3/100,000), with an average annual decline of 6.4%; children (0-14 years) were the lowest (4.8/100,000), with an average annual decline of 7.3%, but a significant increase of 3.3% between 2014 and 2020 (APC = 3.3, 95% CI: 1.4 to 5.2); middle-aged (35-64 years) decreased by 5.8%; and youth (15-34 years) decreased by an average annual rate of 4.2%. The average ASR in rural areas (81.3/100,000) is higher than that in urban areas (76.1/100,000). The average annual decline in rural areas was 4.5% and 6.3% in urban areas. South China had the highest average ASR (103.2/100,000), with an average annual decline of 5.9%, while North China had the lowest (56.5/100,000), with an average annual decline of 5.9%. The average ASR in the southwest was 95.3 (/100,000), with the smallest annual decline (APC = -4.5, 95% CI: -5.5 to -3.5); the average ASR in the Northwest China was 100.1 (/100,000), with the largest annual decline (APC = -6.4, 95% CI: -10.0 to -2.7); Central, Northeastern, and Eastern China declined by an average of 5.2%, 6.2%, and 6.1% per year, respectively.@*CONCLUSIONS@#From 2005 to 2020, the notified incidence of PTB in China continued to decline, falling by 55%. For high-risk groups such as males, older adults, high-burden areas in South, Southwest, and Northwest China, and rural regions, proactive screening should be strengthened to provide timely and effective anti-TB treatment and patient management services for confirmed cases. There is also a necessity to be vigilant about the upward trend of children in recent years, the specific reasons for which need to be further studied.
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Child , Middle Aged , Adolescent , Humans , Female , Male , Aged , Incidence , Tuberculosis, Pulmonary/epidemiology , China/epidemiology , Population GroupsABSTRACT
Objective:Multidrug-resistant tuberculosis(MDR-TB)has a high mortality and is always one of the major challenges in global TB prevention and control.Analyzing the factors that may impact the adverse outcomes of MDR-TB patients is helpful for improving the systematic management and optimizing the treatment strategies for MDR-TB patients.For follow-up data,the Cox proportional hazards regression model is an important multifactor analysis method.However,the method has significant limitations in its application,such as the fact that it is difficult to deal with the impacts of small sample sizes and other practical issues on the model.Therefore,Bayesian and conventional Cox regression models were both used in this study to analyze the influencing factors of death in MDR-TB patients during the anti-TB therapy,and compare the differences between these 2 methods in their application. Methods:Data were obtained from 388 MDR-TB patients treated at Lanzhou Pulmonary Hospital from November 1,2017 to March 31,2021.Survival analysis was employed to analyze the death of MDR-TB patients during the therapy and its influencing factors.Conventional and Bayesian Cox regression models were established to estimate the hazard ratios(HR)and their 95% confidence interval(95% CI)for the factors affecting the death of MDR-TB patients.The reliability of parameter estimation in these 2 models was assessed by comparing the parameter standard deviation and 95% CI of each variable.The smaller parameter standard deviation and narrower 95% CI range indicated the more reliable parameter estimation. Results:The median survival time(1st quartile,3rd quartile)of the 388 MDR-TB patients included in the study was 10.18(4.26,18.13)months,with the longest survival time of 31.90 months.Among these patients,a total of 12 individuals died of MDR-TB and the mortality was 3.1%.The median survival time(1st quartile,3rd quartile)for the deceased patients was 4.78(2.63,6.93)months.The majority of deceased patients,accounting for 50%,experienced death within the first 5 months of anti-TB therapy,with the last mortality case occurring within the 13th month of therapy.The results of the conventional Cox regression model showed that the risk of death in MDR-TB patients with comorbidities was approximately 6.96 times higher than that of patients without complications(HR=6.96,95% CI 2.00 to 24.24,P=0.002)and patients who received regular follow-up had a decrease in the risk of death by approximately 81% compared to those who did not receive regular follow-up(HR=0.19,95% CI 0.05 to 0.77,P=0.020).In the results of Bayesian Cox regression model,the iterative history plot and Blue/Green/Red(BGR)plot for each parameter showed the good model convergence,and parameter estimation indicated that the risk of death in patients with a positive first sputum culture was lower than that of patients with a negative first sputum culture(HR=0.33,95% CI 0.08 to 0.87).Additionally,compared to patients without complications,those with comorbidities had an approximately 6.80-fold increase in the risk of death(HR=7.80,95% CI 1.90 to 21.91).Patients who received regular follow-up had a 90% reduction in the risk of death compared to those who did not receive regular follow-up(HR=0.10,95% CI 0.01 to 0.30).The comparison between these 2 models showed that the parameter standard deviations and corresponding 95% CI ranges of other variables in the Bayesian Cox model were significantly smaller than those in the conventional model,except for parameter standard deviations of receiving regular follow-up(Bayesian model was 0.77;conventional model was 0.72)and pulmonary cavities(Bayesian model was 0.73;conventional model was 0.73). Conclusion:The first year of anti-TB therapy is a high-risk period for mortality in MDR-TB patients.Complications are the main risk factors of death in MDR-TB patients,while patients who received regular follow-up and had positive first sputum culture presented a lower risk of death.For data with a small sample size and low incidence of outcome,the Bayesian Cox regression model provides more reliable parameter estimation than the conventional Cox model.
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Objective To analyze the clinical,laboratory and brain MRI features of patients with neurosyphilis(NS).Methods Eighty-five NS patients admitted to the Department of Neurology in Nanjing Second Hospital from November 2018 to November 2022 were retrospectively analyzed.According to the results of brain MRI,the patients were divided into two groups:normal brain MRI + unilateral lesions group and bilateral lesions group(more severe group).ROC were plotted and the areas under the curves(AUC)were calculated to evaluate the diagnostic value of clinical indicators for severe NS on MRI.Results Compared with normal brain MRI + unilateral lesions group,the mean age(P = 0.000),the rate of male(P = 0.008)and the rate of symptomatic NS(P = 0.006)were significantly higher in bilateral lesions group.Moreover,hypersensitive C-reactive protein(P = 0.028),basophil(P = 0.003),fibrinogen(P = 0.011),CSF tolulized red unheated serum test titer(P = 0.004),CSF protein concentration(P =0.000),CSF adenosine deaminase(P =0.003),and CSF white blood cell count(P =0.049)were significantly increased in patients with NS in bilateral brain lesions group.Multivariate regression analysis suggested that age(OR =1.085,P =0.019)and CSF protein concentration(OR =1.004,P =0.023)were risk factors for NS patients with bilateral brain lesions on MRI.The clinical model was established by age,CSF protein concentration,and basophil,the AUC for predicting NS patients with bilateral brain lesions could reach 0.83(95%CI:0.73-0.91,P＜0.01).Conclusions Clinical,laboratory and brain MRI examination should be integrated during the diagnosis and treatment of NS.Elderly patients and patients with high CSF protein concentration suggest severe disease,and reduction of CSF protein concentration is expected to improve the condition of NS patients.
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Objective:To investigate the value of common clinical symptoms and signs of knee joint, elbow joint and lumbar spine in clinical diagnosis of endemic skeletal fluorosis.Methods:From August to October 2020, a cross-sectional survey of skeletal fluorosis was conducted in 8 administrative villages in Gaotai County and 5 administrative villages in Gaolan County, which were serious areas of drinking-water-borne endemic fluorosis in Gansu Province. Individuals aged ≥25 years old, residing for more than 1 year, and exhibiting symptoms and signs of the motor system in the affected villages were selected as the survey subjects. According to the X-ray diagnostic criteria in the "Diagnostic Standard for Endemic Skeletal Fluorosis" (WS/T 192-2021), they were divided into skeletal fluorosis group and non skeletal fluorosis group. The basic information of the two groups was collected, and orthopedic examination and digital radiography (DR) were performed. Multivariate logistic regression model was used to fit the effects of knee joint, elbow joint and lumbar spine related symptoms and signs on the diagnosis of skeletal fluorosis. Receiver operating characteristic (ROC) curve was drawn to evaluate the predictive effectiveness of the model for skeletal fluorosis, and Kappa test was used to evaluate the consistency between the model and X-ray diagnosis (the gold standard for diagnosis of skeletal fluorosis). Results:A total of 970 subjects were included in the investigation, including 501 in the skeletal fluorosis group and 469 in the non skeletal fluorosis group. Multivariate logistic regression analysis showed that elbow joint flexion and extension range of motion (ROM) decreased by ≥45° [odds ratio ( OR) = 2.73, 95% confidence interval ( CI): 2.00 - 3.72], elbow joint rotation ROM decreased by ≥30° ( OR = 3.34, 95% CI: 1.96 - 5.68), ulnar nerve injury symptoms ( OR = 3.77, 95% CI: 3.21 - 4.42), intermittent claudication ( OR = 2.72, 95% CI: 1.48 - 4.99), and positive straight leg elevation test ( OR = 1.69, 95% CI: 1.09 - 2.61) had certain impact on the diagnosis of skeletal fluorosis. The area under the ROC curve was 0.88, and the model had a good predictive ability for the diagnosis of skeletal fluorosis. After Kappa test, the Kappa value was 0.61, which suggested that the prediction of skeletal fluorosis by this model was in good agreement with X-ray diagnosis. Conclusions:Elbow joint flexion and extension limitation, elbow joint rotation limitation, ulnar nerve injury, intermittent claudication, and positive straight leg elevation test have certain diagnostic value for skeletal fluorosis. The combined diagnosis of these signs has good predictive ability for skeletal fluorosis.
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Objective:To investigate the risk factors of non-valvular paroxysmal atrial fibrillation (NVPAF) with cerebral ischemic stroke(CIS) and analyze NVPAF by using left atrial automatic imaging (AFILA). Logistic regression model was established for left atrial(LA) function parameters.Methods:A total of 205 patients with NVPAF were included in the study and divided into the NVPAF group without ischemic stroke (154 patients) and the CIS group (51 patients). The clinical baseline data, blood biochemical results and AFILA ultrasound data of all patients were collected. Univariate analysis was performed to compare the above data between the two groups of patients. The independent risk factors were obtained by multivariate logistic regression analysis. Logistic regression model was compared with CHA2DS2-VASc scoring system in terms of area under ROC curve, sensitivity and specificity.Results:There were significant differences in age, CHA2DS2-VASc score, taking anticoagulant drugs, history of hypertension, diabetes and coronary heart disease, LAEF, S_R, S_CT, WBC, NEUT, HCY, UREA, NDD, NT-proBNP, Fibrinogen(Fib), Cardiac troponin I(cTnI) and NLR between the two groups (all P<0.05). The results of multifactor analysis showed that: age, hypertension, S_ CT, UREA, NLR, Fib and cTnI were independent risk factors associated with CIS in patients with paroxysmal atrial fibrillation[ OR value: 1.608 ( P=0.003), 3.821 ( P=0.019), 1.259 ( P=0.001), 1.326( P=0.001), 1.352 ( P=0.011), 1.502 ( P=0.042), 7.651( P=0.001)]. After adjusting for the age, sex and history of hypertension included in CHA2DS2-VASc score, S_CT significantly led to NVPAF complicated with stroke[ OR value 1.259 (1.095-1.447), P=0.001]. The diagnostic efficacy of Logistic regression model is better than that of CHA2DS2-VASc scoring (AUC of 0.931 vs 0.717, 95% CI: 0.896-0.967 vs 0.634-0.799, sensitivity of 0.883 vs 0.755, specificity of 0.849 vs 0.713, all P<0.001). Conclusions:Age, hypertension, S_CT, UREA, NLR, fibrinogen, cTnI are independently associated risk factors for patients with combined CIS; The diagnostic efficacy of Logistic regression model is better than that of CHA2DS2-VASc scoring model.And the sensitivity and specificity are high.
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Background Pesticide poisoning is not only a common acute poisoning, but also an indispensable public health problem. It is important to describe and analyze the epidemic characteristics and trends of pesticide poisoning for its prevention and control. Objective To understand the epidemiological characteristics and trends of pesticide poisoning in Jiaxing from 2008 to 2020, and provide a basis for making effective intervention measures. Methods The relevant information of pesticide poisoning cases in Jiaxing from 2008 to 2020 was collected through the Occupational Disease and Occupational Health Information Monitoring System of the China Disease Prevention and Control Information System, and the demographic information was obtained from the statistical yearbook of Jiaxing. Joinpoint regression models were used to analyze trends in overall, gender, age, season, type of poisoning, and type of pesticide among poisoned individuals. Results A total of 3109 cases of pesticide poisoning were reported in Jiaxing City from 2008 to 2020. The overall pesticide poisoning incidence trended downward from 2008 to 2014, with an annual percent change (APC) of −9.0% (95%CI: −16.6%-−0.7%). The female pesticide poisoning incidence trended downward from 2008 to 2015, with an APC of −8.6% (95%CI: −13.9%-−2.9%). The 18-34 age group showed a decreasing trend of pesticide poisoning incidence from 2008 to 2015, with an APC of −11.0% (95%Cl: −17.4%-4.3%), and an increasing trend from 2015 to 2020, with an APC of 18.5% (95%Cl: 4.7%-34.0%). The >60 age group showed a decreasing trend of pesticide poisoning incidence from 2008 to 2014, with an APC of -12.9% (95%Cl: −20.4%-−4.7%). The second quarter showed an increasing trend of pesticide poisoning incidence from 2010 to 2020, with an APC of 4.4% (95%CI: 0.3%-8.5%); the third quarter showed a decreasing trend, with an APC of −4.9% (95%CI: −8.6%-−1.1%); the fourth quarter showed an increasing trend from 2015 to 2020, with an APC of 17.8% (95%CI: 4.4%-33.0%). Productive poisoning showed a decreasing trend, with an APC of −11.1% (95%CI: −16.2%-−5.7%); self-poisoning showed a decreasing trend from 2008 to 2014, with an APC of -9.5% (95%CI: −17.4%-−0.7%), and an increasing trend from 2014 to 2020, with an APC of 10.2% (95%CI: 0.5%-20.8%). The incidences of poisoning by herbicides, fungicides, and mixed formulations all showed an increasing trend from 2008 through 2020, with an APC of 8.6% (95%CI: 5.8%-11.5%), 9.1% (95%CI: 0.3%-18.7%), and 193.3% (95%CI: 11.6%-671.0%), respectively; the incidence of poisoning by other types of pesticides showed a decreasing trend from 2008 to 2020, with an APC of −14.1% (95%CI: −23.7%-−3.2%). Conclusion The overall reported pesticide poisoning incidents in Jiaxing City present a decline then a rise in 2008 to 2020. Relevant departments should take timely measures to prevent and reduce the occurrence of pesticide poisoning according to the changing characteristics and occurrence trends of local pesticide poisonings.
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OBJECTIVE@#To compare the performance of machine learning models and traditional Cox regression model in predicting postoperative outcomes of patients with esophagogastric junction adenocarcinoma (AEG).@*METHODS@#This study was conducted among 203 AEG patients with complete clinical and follow-up data, who were treated in our hospital between September, 2015 and October, 2020. The clinicopathological data of the patients were processed for analysis using R language package and divided into training and validation datasets at the ratio of 3:1. The Cox proportional hazards regression model and 4 machine learning models were constructed for analyzing the datasets. ROC curves, calibration curves and clinical decision curves (DCA) were plotted. Internal validation of the machine learning models was performed to assess their predictive efficacy. The predictive performance of each model was evaluated by calculating the area under the curve (AUC), and the model fitting was assessed using the calibration curve.@*RESULTS@#For predicting 3-year survival based on the validation dataset, the AUC was 0.870 for Cox proportional hazard regression model, 0.901 for eXtreme Gradient Boosting (XGBoost), 0.791 for random forest, 0.832 for support vector machine, and 0.725 for multilayer perceptron; For predicting 5-year survival, the AUCs of these models were 0.915, 0.916, 0.758, 0.905, and 0.737, respectively. For internal validation, the AUCs of the 4 machine learning models decreased in the order of XGBoost (0.818), random forest (0.758), support vector machine (0.0.804), and multilayer perceptron (0.745).@*CONCLUSION@#The machine learning models show better predictive efficacy for survival outcomes of patients with AEG than Cox proportional hazard regression model, especially when proportional odds assumption or linear regression models are not applicable. XGBoost models have better performance than the other machine learning models, and the multi-layer perception model may have poor fitting results for a limited data volume.
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Humans , Adenocarcinoma , Prognosis , Machine Learning , Esophagogastric JunctionABSTRACT
ObjectiveTo analyze the epidemic trends and current status in the prevalence of schistosomiasis in Jiangxi Province from 2002 to 2021， and to provide evidence for formulating and optimizing schistosomiasis control strategies in the province. MethodsEpidemiological data of schistosomiasis in Jiangxi Province from 2002 to 2021 were collected. The Joinpoint regression model was used to investigate the epidemic trends of schistosomiasis， and the annual average percent change （AAPC） was used to assess the changing trend of schistosomiasis infection in humans and bovines. SPSS 25.0 software was used to analyze the target achievement status， infection rate of schistosomiasis in humans and the areas with snails in 2021 to evaluate the differences among various districts and epidemic regions. ResultsBy 2021， 24 counties （61.50%） in the province had achieved the elimination goal， with hilly and marsh counties reaching 82.60% and 31.30%， respectively. The seropositive rate of schistosomiasis in human was 3.51% across the province. However， the seropositive rate in marshland areas （4.77%） was significantly higher than that in hilly areas （1.23 %） （χ2=3 827.51， P<0.001）. The total area with snails in the province was 84 938.32 hm2， including 82 196.86 hm2 in marshland areas and 2 741.46 hm2 in hilly areas. From 2002 to 2021， the infection rate of schistosomiasis in the humans and bovines exhibited a declining trend， with AAPC values of -48.70 and -39.70， respectively. The decline rate in the hilly areas was higher than that in marshland areas. However， the area with snail showed an upward trend （AAPC=0.50）， with a growth rate of 5.80% in hilly areas， which was greater than that in marshland areas （0.40%）. ConclusionFrom 2002 to 2021， the infection rate of schistosomiasis in humans and bovines in Jiangxi Province continued to decline， while the areas with snails increased. The prevention focus should still be on the marshland endemic areas， and attention should also be given to the risk of schistosomiasis in hilly endemic areas. Therefore， it is necessary to continue implementing a comprehensive prevention and control strategy that emphasizes controlling the sources of infection and adopts tailored measures based on local conditions and precise policies.
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Objective:To investigate the relationship between renin-angiotensin system (RAS) and bone mineral density in children with glucocorticoids-induced osteoporosis (GIOP) .Methods:From Apr. 2020 to May. 2021, 53 children with GIOP were recruited in the Children’s Hospital of Taiyuan Maternal and Child Health Hospital and included in the observation group, and 47 children who received glucocorticoid therapy but did not suffer from GIOP were included in the control group. The levels of serum RAS components and bone mineral density of the two groups of pediatric patients were detected and compared, and the risk clinical indicators affecting bone mineral density and GIOP were analyzed.Results:There were no significant differences between the observation group and the control group in terms of gender, age, BMI, disease type, type of glucocorticoid use, use of anti-osteoporosis (OP) drugs, expression levels of Angiotensin converting enzyme 2 (ACE2) or angiotensin II (Ang Ⅱ) (all P>0.05) . The bone density value of the observation group was lower than those of the control group, and the levels of angiotensin converting enzyme (ACE) (1.19±0.23) , angiotensin receptor 1 (AT1R) (1.24±0.24) , angiotensin receptor 2 (AT2R) (1.14±0.17) , and Mas receptor (MasR) (1.11±0.28) were significantly higher than those of the control group (1.00±0.23, 1.00±0.25, 1.00±0.21, 1.00±0.20) , and the differences were statistically significant (all P<0.05) . Pearson analysis showed that bone mineral density was negatively correlated with the levels of ACE ( r=-0.34, P=0.013) , AT1R ( r=-0.41, P=0.002) and AT2R ( r=-0.34, P=0.014) , and stepwise regression model showed that ACE ( t=-2.21, P=0.032) and AT1R ( t=-2.92, P=0.005) were the main factors affecting bone mineral density. Logistic regression model analysis showed that bone mineral density ( OR=0.85, P<0.001) , Ang Ⅱ ( OR=0.53, P=0.041) and AT2R ( OR=2.00, P=0.024) were independent clinical risk factors affecting GIOP (all P<0.05) . Conclusion:RAS components ACE and AT1R are independent risk factors affecting bone mineral density in children with GIOP, and are significantly correlated with bone mineral density in children.
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Objective:To analyze the expression of histone methyltransferase SETD1A and SETD5 in breast cancer and its correlation with the clinicopathological characteristics of patients.Methods:A total of 80 breast cancer patients were included in the study. GSCA website screened SET domain family members, predicted their expression in breast cancer tissues, and verified them with immunohistochemical SP method. Chi-square test and Logistic regression model were used to analyze the correlation between SETD1A, SETD5 and clinicopathological characteristics of patients.Results:The GSCA website showed that the expressions of SETD1A and SETD5 of the SET domain family were up-regulated in breast cancer tissues compared with normal tissues (all P<0.05). Immunohistochemical SP method showed that the positive expression rates of SETD1A and SETD5 in breast cancer tissues were 73.8% and 68.8% respectively, which were significantly higher than the positive expression rates of SETD1A and SETD5 in paracancerous tissues 38.8% ( χ2=19.91, P<0.001) and 32.5% ( χ2=21.03, P<0.001). Chi-square test results showed that the expression of SETD1A was significantly correlated with lymph node metastasis and vascular invasion, and the expression of SETD5 was significantly correlated with nerve invasion (all P<0.05). Logistic regression model showed that SETD1A expression was correlated with lymph node metastasis ( OR=0.07, 95% CI: 0.01-0.25, P<0.001) and molecular type ( OR=0.04, 95% CI: 0.00-0.48, P=0.022), SETD5 expression was correlated with neural invasion ( OR=6.41, 95% CI: 1.45-46.65, P=0.029) . Conclusion:The expressions of histone methyltransferases SETD1A and SETD5 are up-regulated in breast cancer tissues, and they are correlated with pathological features such as lymph node metastasis, vascular invasion, and neural invasion.
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Objective:To explore the risk factors affecting endometrial lesions after breast cancer surgery, and build a nomogram prediction model.Methods:From Oct. 2019 to Nov. 2021, 103 patients with abnormal bleeding after breast cancer surgery were selected, the clinical data of the patients were collected, and they were divided into the non-lesion group and the lesion group according to whether the endometrial lesion occurred. A Logistic risk regression model was established to analyze the risk factors affecting endometrial lesions in postoperative patients with breast cancer, a nomogram prediction model was constructed and verified, and receiver operating characteristic curve (ROC) analysis was performed to analyze the nomogram model for predicting sensitivityof endometrial lesions.Results:Childbirth history ( OR=37.100, 95% CI: 3.777-527.7, P=0.004), endometrial thickness ( OR=2.489, 95% CI: 1.699-4.007, P<0.001), menopause ( OR=0.099, 95% CI: 0.015-0.499, P=0.009), abnormal bleeding time ( OR=6.922, 95% CI: 2.221-24.800, P=0.002), and types of treatment drugs ( OR=3.738, 95% CI: 1.187-13.200, P=0.030) had statistical significance in predicting endometrial lesions in postoperative patients with breast cancer. Using the above five variables to construct a nomogram model, the consistency of the nomogram in predicting endometrial lesions in postoperative patients with breast cancer was 0.739, and the discrimination was good. The calibration curve showed that the average absolute error between the predicted probability and the actual probability was 0.041,and ROC curve showed that the AUC value of the nomogram model for predicting endometrial lesions was 0.800. Conclusion:Establishing a nomogram model for predicting the risk of endometrial lesions in postoperative patients with breast cancer has good accuracy and high clinical value.
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Objective To create risk predictive models of healthcare-seeking delay among imported malaria patients in Jiangsu Province based on machine learning algorithms, so as to provide insights into early identification of imported malaria cases in Jiangsu Province. Methods Case investigation, first symptoms and time of initial diagnosis of imported malaria patients in Jiangsu Province in 2019 were captured from Infectious Disease Report Information Management System and Parasitic Disease Prevention and Control Information Management System of Chinese Center for Disease Control and Prevention. The risk predictive models of healthcare-seeking delay among imported malaria patients were created with the back propagation (BP) neural network model, logistic regression model, random forest model and Bayesian model using thirteen factors as independent variables, including occupation, species of malaria parasite, main clinical manifestations, presence of complications, severity of disease, age, duration of residing abroad, frequency of malaria parasite infections abroad, incubation period, level of institution at initial diagnosis, country of origin, number of individuals travelling with patients and way to go abroad, and time of healthcare-seeking delay as a dependent variable. Logistic regression model was visualized using a nomogram, and the nomogram was evaluated using calibration curves. In addition, the efficiency of the four models for prediction of risk of healthcare-seeking delay among imported malaria patients was evaluated using the area under curve (AUC) of receiver operating characteristic curve (ROC). The importance of each characteristic was quantified and attributed by using SHAP to examine the positive and negative effects of the value of each characteristic on the predictive efficiency. Results A total of 244 imported malaria patients were enrolled, including 100 cases (40.98%) with the duration from onset of first symptoms to time of initial diagnosis that exceeded 24 hours. Logistic regression analysis identified a history of malaria parasite infection [odds ratio (OR) = 3.075, 95% confidential interval (CI): (1.597, 5.923)], long incubation period [OR = 1.010, 95% CI: (1.001, 1.018)] and seeking healthcare in provincial or municipal medical facilities [OR = 12.550, 95% CI: (1.158, 135.963)] as risk factors for delay in seeking healthcare among imported malaria cases. BP neural network modeling showed that duration of residing abroad, incubation period and age posed great impacts on delay in healthcare-seek among imported malaria patients. Random forest modeling showed that the top five factors with the greatest impact on healthcare-seeking delay included main clinical manifestations, the way to go abroad, incubation period, duration of residing abroad and age among imported malaria patients, and Bayesian modeling revealed that the top five factors affecting healthcare-seeking delay among imported malaria patients included level of institutions at initial diagnosis, age, country of origin, history of malaria parasite infection and individuals travelling with imported malaria patients. ROC curve analysis showed higher overall performance of the BP neural network model and the logistic regression model for prediction of the risk of healthcare-seeking delay among imported malaria patients (Z = 2.700 to 4.641, all P values < 0.01), with no statistically significant difference in the AUC among four models (Z = 1.209, P > 0.05). The sensitivity (71.00%) and Youden index (43.92%) of the logistic regression model was higher than those of the BP neural network (63.00% and 36.61%, respectively), and the specificity of the BP neural network model (73.61%) was higher than that of the logistic regression model (72.92%). Conclusions Imported malaria cases with long duration of residing abroad, a history of malaria parasite infection, long incubation period, advanced age and seeking healthcare in provincial or municipal medical institutions have a high likelihood of delay in healthcare-seeking in Jiangsu Province. The models created based on the logistic regression and BP neural network show a high efficiency for prediction of the risk of healthcare-seeking among imported malaria patients in Jiangsu Province, which may provide insights into health management of imported malaria patients.