A postoperative in-hospital mortality risk model for elderly patients undergoing cardiac valvular surgery based on LASSO-logistic regression / 中国胸心血管外科临床杂志

@#Objective     To evaluate the risk factors for postoperative in-hospital mortality in elderly patients receiving cardiac valvular surgery, and develop a new prediction models using the least absolute shrinkage and selection operator (LASSO)-logistic regression. Methods     The patients≥65 years who underwent cardiac valvular surgery from 2016 to 2018 were collected from the Chinese Cardiac Surgery Registry (CCSR). The patients who received the surgery from January 2016 to June 2018 were allocated to a training set, and the patients who received the surgery from July to December 2018 were allocated to a testing set. The risk factors for postoperative mortality were analyzed and a LASSO-logistic regression prediction model was developed and compared with the EuroSCOREⅡ. Results     A total of 7 163 patients were collected in this study, including 3 939 males and 3 224 females, with a mean age of 69.8±4.5 years. There were 5 774 patients in the training set and 1 389 patients in the testing set. Overall, the in-hospital mortality was 4.0% (290/7 163). The final LASSO-logistic regression model included 7 risk factors: age, preoperative left ventricular ejection fraction, combined coronary artery bypass grafting, creatinine clearance rate, cardiopulmonary bypass time, New York Heart Association cardiac classification. LASSO-logistic regression had a satisfying discrimination and calibration in both training [area under the curve (AUC)=0.785, 0.627] and testing cohorts (AUC=0.739, 0.642), which was superior to EuroSCOREⅡ. Conclusion     The mortality rate for elderly patients undergoing cardiac valvular surgery is relatively high. LASSO-logistic regression model can predict the risk of in-hospital mortality in elderly patients receiving cardiac valvular surgery.

Risk assessment of nosocomial infection in patients with multiple myeloma in the first hospitalization / 公共卫生与预防医学

Objective To assess the risk of nosocomial infection in patients with multiple myeloma during their first hospitalization. Methods Totally 480 patients with multiple myeloma who were hospitalized for the first time in department of hematology of West China Hospital, Sichuan University from August 2021 to August 2022 were included, and the nosocomial infection during treatment was statistically analyzed. The patients were divided into infected group and uninfected group. The independent influencing factors of nosocomial infection were analyzed and a prediction model was established. The reliability of the prediction model was analyzed by receiver operating characteristic curve (ROC). Results The incidence rate of nosocomial infection was 31.2% among 480 patients hospitalized for the first time. There were statistically significant differences in age, ISS staging, controlling nutritional status (CONUT) score, agranulocytosis, hemoglobin, and albumin between the infected group and the uninfected group (P<0.05). Logistic multivariate regression analysis showed that age, ISS staging, CONUT score, agranulocytosis, hemoglobin level, and albumin level were all independent correlated factors of nosocomial infection in patients with multiple myeloma hospitalized for the first time (P<0.05). The area under the ROC curve (AUC), sensitivity and specificity of multivariate logistic regression prediction model were 0.88 (95%CI: 0.840-0.920), 85.00% and 76.36%, respectively. Conclusion The incidence rate of nosocomial infection is high among patients with multiple myeloma in the first hospitalization. The prediction model established according to independent correlated factors of nosocomial infection has high predictive value on the occurrence of nosocomial infection.

DIGITAL SEARCH ADVERTISING – THE ROLE OF POST-CLICK FACTORS IN GENERATING PURCHASE CONVERSIONS

A lot of research is available on the effectiveness of search as an advertising channel. Most of these studies tend to treat a click on a search ad as a binary event. All of them study the events leading to the click. This paper goes beyond this to study the post click actions taken by a user subsequent to clicking on a search ad, and refers to those actions as depth of interaction, and testing the variables that have an effect on the nal outcome. We use a prescriptive research design employing binary logistic regression analysis. Results indicate that the duration of time spent, device used, and recency of visit have a very high positive effect on the nal outcome.

Factores predictivos de rotura de aneurismas intracraneales

Introducción: Un aneurisma intracraneal roto provoca una hemorragia subaracnoidea. La enfermedad presenta una alta mortalidad y morbilidad. Sin embargo, no todos se rompen. Mejorar la predicción de rotura permitirá un tratamiento quirúrgico preventivo en un grupo de pacientes y evitará una intervención quirúrgica con riesgos en otro grupo de enfermos. Es necesario identificar factores predictivos para mejorar la estratificación del riesgo de rotura y optimizar el tratamiento de los aneurismas intracraneales incidentales. Objetivo: Identificar factores predictivos de rotura de aneurismas intracraneales. Métodos: En una muestra de 152 pacientes espirituanos con aneurismas intracraneales saculares rotos (n = 138) y no rotos (n = 22) y 160 imágenes de angiografía por tomografía computarizada, se realizaron mensuraciones de los índices o factores morfológicos, los cuales se combinaron mediante análisis de regresión logística con variables demográficas y clínicas. Resultados: El grupo de edad con mayor frecuencia de presentación de aneurismas fue el de mayor de 65 años. La muestra estuvo representada, en su gran mayoría, por el sexo femenino. Se identificaron tres factores clínicos y cuatro factores morfológicos estadísticamente significativos, asociados con la rotura. El índice de no esfericidad (p = 0,002 y el sexo femenino (p = 0,02) fueron los de mayor significación estadística. Conclusiones: Se detectaron siete factores predictivos de rotura de aneurismas intracraneales estadísticamente significativos, de los cuales el índice de no esfericidad resultó el de mayor significación.

Introduction: A ruptured intracranial aneurysm causes a subarachnoid hemorrhage. The disease has high mortality and morbidity. However, not all of them break. Improving the rupture prediction will allow preventive surgical treatment in a group of patients and it will avoid risky surgical intervention in another group of patients. It is necessary to identify predictive factors to improve rupture risk stratification and to optimize treatment of incidental intracranial aneurysms. Objective: To identify rupture predictive factors for intracranial aneurysms. Methods: Measurements of the morphological indices or factors were performed in a sample of 152 patients from Sancti Spiritus with ruptured (n = 138) and unruptured (n = 22) saccular intracranial aneurysms and 160 computed tomography angiography images. They were combined using logistic regression analysis with demographic and clinical variables. Results: The age group with the highest frequency of aneurysm presentation was older than 65. The sample was represented, in its vast majority, by the female sex. Three clinical factors and four statistically significant morphological factors associated with rupture were identified. The non-sphericity index (p = 0.002) and the female sex (p = 0.02) were the most statistically significant. Conclusions: Seven statistically significant predictors of intracranial aneurysm rupture were detected, the non-sphericity index being the most significant.

A cross-sectional survey on burden of caregivers of pediatric leukemia patients attending a tertiary care hospital in Kolkata, India

Background: Care giving of children with leukemia involves considerable stress and anxiety on the part of family caregivers. Although caregivers’ burden is a crucial predictor of the health of both the child and the caregiver, it is often overlooked. Aim and Objectives: The present study aimed to assess the burden faced by caregivers of pediatric leukemia patients attending a tertiary care hospital in West Bengal, to elicit their sociodemographic characteristics and patients’ profile, and to find out relationship among these, if any. Materials and Methods: The study was descriptive observational type with cross-sectional design. It was conducted among caregivers of pediatric leukemia patients. Data were collected from 38 caregivers using predesigned, pretested, semi-structured schedule, and patients’ records. Burden was measured using Zarit Burden Interview, which is a 22 item 5-point Likert scale. Data were compiled and analyzed in Microsoft Excel and Statistical Software for the Social Sciences 20.0 for statistical analysis. Sociodemographic and clinical variables were expressed as number, percentages, mean, and standard deviations. To find out the association between different factors and caregiver burden, a logistic regression model was used. P < 0.05 was considered as statistically significant. Results: Majority of the caregivers were the mothers of the patients (68.42%), and most of the families of caregivers belonged to lower middle class according to modified BG Prasad Scale. Half of the caregivers (50%) experienced moderate–to-severe burden according to Zarit Burden Interview. Association was found between burden experienced and duration of disease and treatment. However, socioeconomic status was found to be the most significant determinant of burden as per multiple logistic regression by ENTER method. Conclusions: Majority of the caregivers were having moderate to severe and severe burden, which was significantly more among people coming from lower socioeconomic status. Prolonged disease duration and treatment were also found to be associated with increased burden of the caregivers.

Expression of histone methyltransferase SETD1A and SETD5 in breast cancer and its correlation with clinicopathological characteristics of patients / 中华内分泌外科杂志

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.

Correlation analysis between renin-angiotensin system and bone mineral density in children with glucocorticoid-induced osteoporosis / 中华内分泌外科杂志

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.

Development and evaluation of a mortality risk prediction model for severe bacterial infections in children / 中华急诊医学杂志

Objective:To establish a mortality risk prediction model of severe bacterial infection in children and compare it with the pediatric early warning score (PEWS), pediatric critical illness score (PCIS) and pediatric risk of mortality score Ⅲ (PRISM Ⅲ).Methods:A total of 178 critically ill children were selected from the PICU of the Children's Hospital of Nanjing Medical University from May 2017 to June 2022. After obtaining the informed consent of the parents/guardians, basic information such as sex, age, height and weight, as well as indicators such as heart rate, systolic blood pressure and respiratory rate were collected from all children. A standard questionnaire was used to score the child 24 h after admission to the PICU. The children were divided into the survival and death groups according to their survival status at 28 d after admission. A mortality risk prediction model was constructed and nomogram was drawn. The value of the mortality risk prediction model, PEWS, PCIS and PRISM in predicting the risk of death was assessed and compared using the receiver operating characteristic (ROC) curve and the area under the ROC curve (AUC).Results:Among the 178 critically ill children, 11 cases were excluded due to severe data deficiencies and hospitalization not exceeding 24 h. A total of 167 children were included in the analysis, including 134 in the survival group and 33 in the death group. A mortality risk prediction model for children with severe bacterial infection was constructed using pupillary changes, state of consciousness, skin color, mechanical ventilation, total cholesterol and prothrombin time. ROC curve analysis showed that the AUCs of mortality risk prediction model was 0.888 ( P<0.05). The AUCs of PEWS, PCIS and PRISM Ⅲ in predicting death in children with severe bacterial infection were 0.769 ( P< 0.05), 0.575 ( P< 0.05) and 0.759 ( P< 0.05), respectively. Hosmer-Lemeshow goodness-of-fit test showed the best agreement between risk of death and PEWS predicted morbidity and mortality and actual morbidity and mortality (χ 2 = 5.180, P = 0.738; χ 2 = 4.939, P = 0.764), and the PCIS and PRISM Ⅲ predicted mortality rates fitted reasonably well with actual mortality rates (χ 2= 9.110, P= 0333; χ 2 = 8.943, P= 0.347). Conclusions:The mortality risk prediction model for predicting the death risk has better prognostic value than PEWS, PCIS and PRISM Ⅲ for children with severe bacterial infection.

Death-Related Factors in Patients With Acute Exacerbation of Chronic Obstructive Pulmonary Disease Treated by Sequential Mechanical Ventilation / 中国医学科学院学报

Objective To analyze the death-related factors of elderly patients with acute exacerbation of chronic obstructive pulmonary disease (AECOPD) treated by sequential mechanical ventilation,so as to provide evidence for clinical practice. Methods The clinical data of 1204 elderly patients (≥60 years old) with AECOPD treated by sequential mechanical ventilation from June 2015 to June 2021 were retrospectively analyzed.The probability and influencing factors of death were analyzed. Results Among the 1204 elderly patients with AECOPD treated by sequential mechanical ventilation,167 (13.87%) died.Multivariate analysis showed that plasma procalcitonin ≥0.5 μg/L (OR=2.762, 95%CI=1.920-3.972, P<0.001),daily invasive ventilation time ≥12 h (OR=2.202, 95%CI=1.487-3.262,P<0.001),multi-drug resistant bacterial infection (OR=1.790,95%CI=1.237-2.591,P=0.002),oxygenation index<39.90 kPa (OR=2.447,95%CI=1.625-3.685,P<0.001),glycosylated hemoglobin >6% (OR=2.288,95%CI=1.509-3.470,P<0.001),and acute physiology and chronic health evaluation Ⅱ score ≥25 points (OR=2.126,95%CI=1.432-3.156,P<0.001) were independent risk factors for death in patients with AECOPD treated by sequential mechanical ventilation.Oral care>twice/d (OR=0.676,95%CI=0.457-1.000,P=0.048) and sputum excretion>twice/d (OR=0.492, 95%CI=0.311-0.776, P=0.002) were independent protective factors for death in elderly patients with AECOPD treated by sequential mechanical ventilation. Conclusions The outcomes of sequential mechanical ventilation in the treatment of elderly patients with AECOPD are affected by a variety of factors.To reduce the mortality,we put forward the following measures:attaching great importance to severe patients,restoring oxygenation function,shortening unnecessary invasive ventilation time,controlling blood glucose,preventing multidrug resistant bacterial infection,oral care twice a day,and sputum excretion twice a day.

A novel differential diagnosis algorithm for chronic lymphocytic leukemia using immunophenotyping with flow cytometry

Abstract Introduction The availability of a clinical decision algorithm for diagnosis of chronic lymphocytic leukemia (CLL) may greatly contribute to the diagnosis of CLL, particularly in cases with ambiguous immunophenotypes. Herein we propose a novel differential diagnosis algorithm for the CLL diagnosis using immunophenotyping with flow cytometry. Methods The hierarchical logistic regression model (Backward LR) was used to build a predictive algorithm for the diagnosis of CLL, differentiated from other lymphoproliferative disorders (LPDs). Results A total of 302 patients, of whom 220 (72.8%) had CLL and 82 (27.2%), B-cell lymphoproliferative disorders other than CLL, were included in the study. The Backward LR model comprised the variables CD5, CD43, CD81, ROR1, CD23, CD79b, FMC7, sIg and CD200 in the model development process. The weak expression of CD81 and increased intensity of expression in markers CD5, CD23 and CD200 increased the probability of CLL diagnosis, (p < 0.05). The odd ratio for CD5, C23, CD200 and CD81 was 1.088 (1.050 - 1.126), 1.044 (1.012 - 1.077), 1.039 (1.007 - 1.072) and 0.946 (0.921 - 0.970) [95% C.I.], respectively. Our model provided a novel diagnostic algorithm with 95.27% of sensitivity and 91.46% of specificity. The model prediction for 97.3% (214) of 220 patients diagnosed with CLL, was CLL and for 91.5% (75) of 82 patients diagnosed with an LPD other than CLL, was others. The cases were correctly classified as CLL and others with a 95.7% correctness rate. Conclusions Our model highlighting 4 markers (CD81, CD5, CD23 and CD200) provided high sensitivity and specificity in the CLL diagnosis and in distinguishing of CLL among other LPDs.

Risk predictive models of healthcare-seeking delay among imported malaria patients in Jiangsu Province based on the machine learning / 中国血吸虫病防治杂志

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.

Factors influencing the levels of occupational exposure in medical radiation workers in China, 2021 / 中国辐射卫生

Objective To analyze the factors influencing the levels of occupational exposure in medical radiation workers in China, and to provide a scientific basis for determining the key points of radiation protection in the medical sector. Methods The individual monitoring data on occupational external exposure in medical radiation workers in 2021 were collected from the “National Individual Dose Registry”. The Chi-squared test and logistic regression were used to analyze the factors influencing the levels of occupational exposure in medical radiation workers. Results The Chi-squared test showed that gender, occupational category, medical institution category, region, number of radiation workers per thousand population, and regional per capita GDP were significantly associated with occupational exposure in medical radiation workers exceeding the annual effective dose of 5 mSv and an annual effective dose limit of 20 mSv (χ2 = 21.456−262.329, 7.601−78.650, P < 0.05). The logistic regression analysis further showed that gender, occupational category, region, and number of radiation workers per thousand population were factors influencing the occupational exposure in medical radiation workers exceeding the annual effective dose of 5 mSv (χ2 = 14.621−170.857, P < 0.05); gender, occupational category, region, and regional per capita GDP were factors influencing the occupational exposure in medical radiation workers exceeding the annual effective dose of 20 mSv (χ2 = 5.401−48.709, P < 0.05). Conclusion Male radiation workers in interventional radiology and in central China have high risks of exceeding annual effective doses of 5 and 20 mSv. Moreover, high number of radiation workers per thousand population and regional per capita GDP are associated with low risks. Medical institutions should maintain a sufficient number of radiation workers and strengthen training on radiation protection knowledge for male and interventional radiology workers to enhance their radiation protection awareness. Investigation of the factors contributing to the high occupational exposure in central China should be intensified, and targeted effective measures should be conducted to reduce the occupational exposure in medical radiation workers.

Establishment and evaluation of predictive models of platelet transfusion effect in multi-center tumor patients / 中国输血杂志

【Objective】 To study the platelet transfusion predictive models in tumor patients and evaluate its application effect. 【Methods】 A retrospective study was conducted on 944 tumor patients, including 533 males and 411 females who received platelet transfusion in the Affiliated Hospital of Traditional Chinese Medicine of Xinjiang Medical University, the Affiliated Cancer Hospital of Xinjiang Medical University and Kailuan General Hospital from August 2022 to January 2023. Multivariate Logistic regression analysis was used to establish the platelet transfusion predictive models, and Medcalc15.8 software was used to draw the receiver operating curve (ROC) to evaluate the application effect of the prediction model. The actual application effect of models was verified through 162 female clinical cases and 172 male clinical cases. 【Results】 The incidence of platelet transfusion refractoriness in tumor patients was 28.9% (273/944), with 33.2% (177/533) in males, significantly higher than that in females [23.4% (96/411)] (P<0.05). Platelet transfusion predictive models: Y1 (female) =-8.546+ (0.581×number of pregnancies) + (0.964×number of inpatient transfusion bags) + number of previous platelet transfusion bags (5-9 bags: 1.259, ≥20 bags: 1.959) + clinical diagnosis (lymphoma: 2.562, leukemia: 3.214); Y2 (male) =-7.600+ (1.150×inpatient transfusion bags) + previous platelet transfusion bags (10-19 bags: 1.015, ≥20 bags: 0.979) + clinical diagnosis (lymphoma: 1.81, leukemia: 3.208, liver cancer: 1.714). Application effect evaluation: The AUC (area under the curve), cut-off point, corresponding sensitivity and specificity of female and male platelet transfusion effect prediction models were 0.868, -0.354, 68.75%, 89.84% and 0.854, -0.942, 81.36%, 77.53%, respectively. Actual application results showed that the sensitivity, specificity, and accuracy of female and male model were 89.47%, 92.74%, 91.98% and 83.72%, 91.47%, 89.53%, respectively. 【Conclusion】 There is high incidence of platelet transfusion refractoriness in tumor patients, and the predictive model has good prediction effect on platelet transfusion refractoriness in tumor patients, which can provide reliable basis for accurate platelet transfusion in tumor patients.

Analysis of risk factors in blood donors with confirmed positive syphilis / 中国输血杂志

【Objective】 To study the risk factors of blood donors confirmed to be positive for syphilis, so as to avoid highrisk groups, guide the recruitment of blood donors and improve blood safety. 【Methods】 From September 2021 to August 2022, 44 514 blood samples were screened using two enzyme-linked immunosorbent reagents for syphilis, and the reactive samples were confirmed by TPPA. Blood collection time, blood collection location, blood donation numbers, gender, age, marital status and educational level of blood donors were taken as the prediction risk factors, and factors with statistically significant differences by univariate Logistic regression analysis were further analyzed using multivariate factor Logistic regression analysis to determine the final independent risk factors. 【Results】 A total of 121 syphilis antibody reactive samples were detected by enzyme-linked immunosorbent assay, and 64 were confirmed positive by TPPA. Excluding those with incomplete information, a total of 44 505 blood donors were included in the analysis. Logistic regression analysis showed that there were statistically significant differences in blood collection location, blood donation numbers, age and education level. 【Conclusion】 Based on the analysis results of risk factors of syphilis positive blood donors in Wuhu, it is necessary to strengthen the consultation of blood donors in blood donation sites. The high-risk groups are first-time blood donors over 50 years old, with education level of junior high school or below.

Construction of a rapid depression screening model for blood donors in Guangzhou based on decision tree / 中国输血杂志

【Objective】 To investigate the prevalence of depression in blood donors and analyze the related factors, so as to develop a rapid depression screening model for blood donors. 【Methods】 A total of 13 015 street whole blood donors in Guangzhou Blood Center during May to August, 2020 filled in an anonymous e-questionnaire, including social demography information and the Patient Health Questionnaire-9 before donation. The cut-off value for detecting depression was 10. Logistic regression by SPSS 26.0 was used to analyze depression related factors. 2-level decision tree with 30/10 as the minimum number of cases in parent/child node, 10-fold cross validation was used to cut items of PHQ-9 to form the depression screening model. 【Results】 364 out of 13 015 (2.80%) street whole blood donors reported a score ≥ 10. Donors with 18-29 years old (P <0.05), unmarried (P<0.05), less than 50 000 RMB household income per year (P< 0.05) were more prone to depression. 81.96% donors in "<10 scores" group, while 3.85%donors in "≥ 10 scores" group were in two terminal nodes formed by Item-6, 2 and 4 of PHQ-9. After verification by the 10 fold crossover method, the estimated misclassification risk of the model was 1.7%. 【Conclusion】 The screening prevalence of depression based on PHQ-9 in Guangzhou blood donors was 2.8%(95% CI: 2.52%-3.09%) . Donation frequency was not related to depression. A rapid and efficient depression screening model for blood donors based on item-6, 2 and 4 of PHQ-9 was developed.

Construction of blood transfusion prediction model for patients with severe traumatic brain injury / 中国输血杂志

【Objective】 To construct a blood transfusion prediction model for patients with severe traumatic brain injury (TBI), in order to predict the risk of blood transfusion and guide blood transfusion decision-making. 【Methods】 The clinical data of 756 patients with severe TBI admitted to the hospital from January 1, 2015 to June 30, 2021 were retrospectively analyzed. According to whether the patients were transfused with red blood cells after admission, the patients were divided into blood transfusion group (n=354) and non-blood transfusion group (n=402). The basic clinical data and prognostic indicators of the two groups were compared. Logistic regression algorithm was used to screen the risk factors related to blood transfusion in hospital to establish a nomogram prediction model, and the performance of the model was evaluated. 【Results】 No significant differences were noticed in gender, age, body temperature, cause of injury, ABO blood group, Rh blood group, serum Na and K concentrations between the two groups (P>0.05). Significant differences were found in Glasgow coma score (GCS), heart rate (HR), systolic blood pressure (SP), diastolic blood pressure (DP), shock index (SI), respiratory rate (RR), clinical diagnosis, treatment, hemoglobin concentration (Hb), hematocrit (Hct), platelet count (Plt) and coagulation function between the two groups (P0.05). Multivariate logistic regression analysis showed that surgical treatment, skull fracture, hemorrhagic shock, decreased Plt, decreased Hct and increased INR were independent risk factors for blood transfusion. A nomogram prediction model was constructed and the area under the ROC curve of the training set and the test set was 0.819(95% CI: 0.784-0.854) and 0.866(95% CI: 0.818-0.910), respectively, which had good predictive performance. 【Conclusion】 Surgical treatment, skull fracture, hemorrhagic shock, decreased Plt, decreased Hct and increased INR are independent risk factors for blood transfusion in adult patients with severe traumatic brain injury. The nomogram prediction model can better predict the blood transfusion demand of TBI patients and has high application value.

Association between e-cigarette use and subjective cognitive decline among adults aged 45 and above / 上海预防医学

ObjectiveTo investigate the relationship between e-cigarette use and subjective cognitive decline. MethodsThis study included survey participants aged ≥45 years from the US Behavioral Risk Factor Surveillance System. The prevalence of subjective cognitive decline in people with different tobacco use conditions was estimated. Multivariate logistic regression was employed to determine the relationship between e-cigarette use and subjective cognitive decline， as well as the relationship between co-use of e-cigarette and combustible tobacco and subjective cognitive decline. ResultsA total of 204 032 participants were included in the study. The total prevalence of subjective cognitive decline was 11.46%， whereas among current e-cigarette users， the prevalence was 19.92%. After accounting for confounding factors， current e-cigarette use was identified as a risk factor for subjective cognitive decline compared to individuals who had never used e-cigarettes， with an OR of 1.46 （95%CI： 1.20‒1.77）. Meanwhile， occasional e-cigarette use showed a higher risk， with an OR of 1.54 （95%CI： 1.22‒1.95）. The highest risk was observed with the co-use of e-cigarette and combustible tobacco， with an OR of 1.69 （95%CI： 1.32‒2.16）， followed by current e-cigarette use and former combustible tobacco use， with an OR value of 1.38 （95%CI： 1.08‒1.78）. ConclusionThe use of e-cigarettes increases the risk of subjective cognitive decline， with occasional use demonstrating a more pronounced negative impact. In general， the risk of cognitive decline is greater among e-cigarette users compared to combustible tobacco users. Controlling the use of combustible tobacco， especially e-cigarette， will help reduce the incidence of subjective cognitive decline. Individuals currently using combustible tobacco are advised to explore smoking cessation methods other than transitioning to e-cigarettes.

Current situation of health checkup and the management willingness of post-test abnormal values among residents of mega communities / 中华健康管理学杂志

Objective:To investigate the current status of health checkups and the management willingness of post-test abnormal values in residents of mega communities, and to explore the factors affecting the demand for health management of abnormal values after examination.Methods:A cross-sectional study. The residents of Huaguoyuan Community in Guiyang City were enrolled as the objects of this surveywith stratified systematic sampling method and questionnaire survey. The binary logistic regression was used to analyze the influencing factors of health management demand for abnormal values after examination.Results:There were 404 residents participating in this survey, and 182 cases were male (45.05%) and 222 cases were female (54.95%); the mean age was (39.64±15.03) years. There were 179 (44.31%) urban residents and 225 (55.69%) rural residents. There were 162 (40.10%) floating population and 242 (59.90%) non-floating population. Of the residents, 34.2% participated in the physical examination independently due to physical reasons. The age ( χ 2=16.227), household registration ( χ 2=16.117) and occupation ( χ 2=36.454) had statistically significant differences in residents′ participation in physical examination; the household registration ( χ 2=18.726, P<0.001) and occupation ( χ 2=18.094, P=0.034) had significant differences in the handling methods of abnormal values of physical examination. The age ( OR=7.00, P=0.032) and income ( OR=0.33, P=0.047) were the influencing factors of health management needs of abnormal values after health checkup. Conclusion:The awareness of active physical examination of residents in mega community is weak, and it is recommended to strengthen health education and health promotion; residents have a high willingness to the management of abnormal values after health checkup, it can be an important supplement to improve the service quality of physical examination related institutions.

Correlation analysis between uranium exposure and renal injury / 中华放射医学与防护杂志

Objective:To analyze the relationship between plasma uranium concentration and renal injury.Methods:A case-control study was conducted in Hunan province, involving 102 renal injury cases and 102 matched controls. The association between plasma uranium concentration and renal injury was analyzed using conditional logistic regression models, and the dose-response relationship was analyzed through restricted cubic spline regression. The linear regression model and Spearman correlation were used to analyze the association between plasma uranium concentration and renal injury indicators.Results:The median of plasma uranium concentration was 8.94 ng/L in all subjects and 10.19 ng/L in the case group. The plasma uranium may be a risk factor for renal injury, with a dose-response relationship between the both representing nonlinear association ( χ2=5.15, P<0.05). The risk of renal injury was 4.21 times higher in the group exposed to highest uranium concentration than that in the group exposed to lowest uranium concentration. Plasma uranium concentration was closely related to glomerular filtration rate, serum creatinine and β 2-microglobulin ( r=0.211, -0.142, 0.195, P<0.05). Conclusions:The plasma uranium concentration is significantly associated with the renal injury, which may provide epidemiology evidence for the prevention of renal injury.

Left atrial automated functional myocardial imaging to identify patients with paroxysmal atrial fibrillation at high risk of stroke / 中华超声影像学杂志

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.