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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.
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Humans , Male , Female , Adult , Middle Aged , Aged , Aged, 80 and over , Leukemia, Lymphocytic, Chronic, B-Cell , Flow Cytometry , Algorithms , Linear Models , Immunophenotyping , Diagnosis, DifferentialABSTRACT
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.
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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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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 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 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.
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Objective:To analyze the influencing factors on initial testing qualified rate of condition monitoring of digital radiography (DR) devices in China and provide the scientific basis for key points of national medical radiation protection monitoring work.Methods:The data of quality control detection of DR devices, reported by 31 provinces in 2020, were collected from National Radiation Health Information Platform-National Medical Radiation Protection Monitoring System. Logistic regression was used to analyze the related influencing factors of initial testing qualified rate of condition monitoring of DR devices.Results:The result of logistic regression analysis showed that the nature of radiological health technical service institutions, the level of medical and health institution and the regions where they are located in China were the independent influencing factors of initial testing qualified rate of condition monitoring of DR devices ( χ2=15.41-21.18, P < 0.05). Private institution group ( OR=1.714, 95% CI: 1.310-2.243), tertiary hospital group ( OR=1.710, 95% CI: 1.310-2.232) and secondary hospital group ( OR=1.540, 95% CI: 1.203-1.971) had a higher qualified probability of DR devices, while western region group ( OR=0.670, 95% CI: 0.526-0.852) had a lower qualified probability of DR devices. Conclusions:Supervision on quality control of DR devices should be strengthened, such as strengthening the random inspection and double-check to the devices. And great attention should be paid to the quality control testing of DR devices in the western China and in the primary and ungraded hospitals.
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The purpose of the paper was to introduce how to reasonably carry out multiple Logistic regression analysis combined with the average treatment effect analysis. Firstly， it introduced 4 basic concepts related to the average treatment effect analysis. Secondly， it presented the core contents in the average treatment effect analysis， that was， six estimation methods. Thirdly， through a hypothetical drug clinical trial example， it gave the whole process of how to use SAS software for the analysis. The contests were as follows： ① the traditional multiple Logistic regression model was used for the analysis； ② the propensity score model was used to calculate the inverse probability weights； ③ six estimation methods were used to estimate the potential outcome mean and the average treatment effect.
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The purpose of this paper was to introduce how to combine the propensity score analysis to reasonably carry out multiple linear regression analysis. Firstly， it introduced 3 basic concepts related to the propensity score analysis. Secondly， it presented the core contents of the propensity score analysis， that was， three matching methods. Thirdly， through an epidemiological survey example， it gave the whole process of how to use SAS software for the analysis. The contents were as follows： ① for the original data set， test whether the difference of covariates between the treatment group and the control group was statistically significant； ② directly implement the multiple linear regression analysis for the original data set； ③ the propensity score analysis was used to generate the matched data set； ④ for the matched data set， test whether the difference of covariates between the treatment group and the control group was statistically significant； ⑤ a reasonable multiple linear regression analysis was used for the matched data set.
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OBJECTIVE：To investigate the influ ential factors of traditional Chinese medicine （TCM）service utilized by outpatients in Jiangsu province ，and to provide reference for scientific utilization of TCM service. METHODS ：Based on the data of Jiangsu province in National Sixth Health Service Survey in 2018，descriptive analysis was performed for the general situation and population characteristics of 1 617 outpatients in Jiangsu province. Single factor analysis and multivariate binary Logistic regression model analysis were used to analyze the influential factors of TCM service utilized by outpatients. RESULTS ：Of the 1 617 respondents，145 patients（9.0％）applied TCM services at outpatient visits. Results of single factor analysis showed that age ， education degree ，annual income ，whether to participate in basic medical insurance ，self-perceived illness severity ，hypertension， diabetes，other chronic diseases ，and the first diagnose institutions were significant influential factors for TCM service utilized by outpatients in Jiangsu province （P＜0.05）. Results of binary Logistic regression showed that the elderly aged 65 years and over ， the patients who participated in the basic medical insurance for urban workers ，the patients with hypertension ，primary medical institutions as first diagnosis institutions ，the middle-income population ，and other chronic diseases were significant influential factors for TCM service utilized by outpatients in Jiangsu province （P＜0.05）. CONCLUSIONS ：Age，annual income ，whether to participate in basic medical insurance ，hypertension and other chronic diseases ，and first diagnosis institutions are significant infleutial factors for TCM service utilized by outpatients in Jiangsu province. The utilization of TCM health services for outpatients in Jiangsu province is in relatively low level ，and middle-aged and elderly patients and patients with chronic diseases show high acceptance for TCM services. Outpatients first diagnosed in primary medical institutions are more willing to accept TCM services.
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Objective:To evaluate the prognostic value of transthoracic lung ultrasound comet-tail and extravascular lung water index (EVLWI) in septic patients.Methods:A prospective cohort study was conducted. Sixty septic patients admitted to department of intensive care unit (ICU) of Sichuan Provincial People's Hospital from November 2016 to October 2019 were enrolled. The EVLWI and pulmonary vascular permeability index (PVPI) were determined by pulse-indicated continuous cardiac output (PiCCO) system at 0, 24, 48 and 72 hours. At the same time, the numbers of comet tail signs in both lungs (parasternal, midclavicular, axillary to midaxillary) were collected by chest ultrasound. Moreover, arterial blood gas analysis, such as pH value, central venous-to-arterial carbon dioxide difference (Pcv-aCO 2), central venous oxygen saturation (ScvO 2), blood lactic acid (Lac), PaO 2/FiO 2 were measured. Pearson correlation analysis was performed between the number of comet-tail sign and EVLWI. Multivariate Logistic regression model was used to analyze the relationship between the number of comet-tail sign, EVLWI and prognosis. Receiver operator characteristic curve (ROC curve) was drawn to predict the prognosis. Results:There were 43 males and 17 females in 60 septic patients. The average age was (64.3±15.5) years old (range: 31-83 years old). There were 35 cases with pulmonary infection, 10 cases with abdominal infection, 6 cases with urinary tract infection, 3 cases with skin and soft tissue infection, 3 cases with intestinal infection, 1 case with meningitis, 1 case with cellulitis and 1 case with multiple injury. Acute respiratory distress syndrome (ARDS) occurred with 8 patients; 40 patients (66.7%) survived and 20 patients (33.3%) died on day 28. Pearson correlation analysis showed that the number of comet-tail sign was positively correlated with EVLWI ( r = 0.944, P < 0.001). There was significant difference in the number of comet-tail signs among sepsis patients with different primary infection sites ( H = 17.714, P < 0.001). The number of comet-tail signs in sepsis patients with pulmonary infection [19 (13, 27)] was significantly higher than that with other infections. The number of comet-tail sign in patients with ARDS was significantly higher than that in patients without ARDS [27 (19, 30) vs. 15 (9, 24), H = 25.387, P < 0.001]. Multivariate Logistic regression analysis showed that EVLWI, the number of comet-tail signs and PVPI were independent risk factors for death in septic patients [odds ratio ( OR) and 95% confidence interval (95% CI) were 10.772 (1.161-99.851), 2.360 (1.070-5.202), 2.042 (1.152-3.622), all P < 0.05]. The accuracy, sensitivity, specificity, positive predictive value, negative predictive value of Logistic regression model based on comet-tail sign and EVLWI were 90.0%, 90.0%, 90.0%, 81.8%, 94.7%, respectively, and area under curve (AUC) were 0.926±0.018, 95% CI was 0.912-0.975, P < 0.001. Conclusions:The transthoracic lung ultrasound comet-tail in septic patients is significantly correlated with EVLWI monitored by PiCCO. The transthoracic lung ultrasound comet-tail combined with EVLWI can better improve the sensitivity, specificity and accuracy of 28-day prognosis in septic patients.
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Objective:To investigate the relationship between preoperative serum thyroglobulin (Tg) and clinical data with the risk of cervical lymph node metastasis in patients with papillary thyroid carcinoma (PTC) .Methods:Data of 395 PTC patients who underwent surgery from Feb. 2016 to Jun. 2019 at the Second Affiliated Hospital of Soochow University were retrospectively analyzed. Based on whether cervical lymph nodes had metastasis, patients were classified into central lymph node metastasis positive group ( n=195 cases) , central lymph node metastasis negative group ( n=200 cases) , lateral lymph node metastasis positive group ( n=72 cases) , and lateral lymph node metastasis negative group ( n=323 cases) .Then the relationship between age, sex, multifocality, tumor diameter, capsular invasion, preoperative TSH and preoperative Tg with lymph node metastasis were analyzed by SPSS. Comparisons between groups were performed by χ2 test and rank sum test. Prediction efficiency of the preoperative Tg and Logistic regression model was estimated by receiver operating characteristic (ROC) curve. A total of 100 PTC patients confirmed by pathological results in the Second Affiliated Hospital of Soochow University from Jul. 2019 to Apr. 2020 were selected as the validation data. Results:Multi-factor Logistic regression showed that age, tumor diameter, capsular invasion and preoperative Tg were independent risk factors of central cervical lymphatic metastasis ( P<0.05) ; Tumor diameter, capsular invasion, central cervical lymphatic metastasis and preoperative Tg were independent risk factors of lateral cervical lymphatic metastasis ( P<0.05) . The area under the ROC curve (AUC) for diagnosing central lymph node metastasis by preoperative Tg was 0.710, with a sensitivity of 49.2%, and specificity of 88.5%. The AUC for diagnosing lateral lymph node metastasis by preoperative Tg was 0.728, with a sensitivity of 59.7%, and specificity of 89.5%. The AUC for diagnosing central lymph node metastasis by the prediction model was 0.773, with a sensitivity of 78.5%, and specificity of 64.5%.The AUC for diagnosing lateral lymph node metastasis by the prediction model was 0.869, with a sensitivity of 84.7%, and specificity of 70.3%. Conclusions:The preoperative serum Tg level is correlated with cervical lymph node metastasis in PTC patients. But the Logistic regression model based on preoperative Tg and other independent risk factors shows a better predictive value.
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Objective In order to strengthen health supervision and management of public places and prevent occurrence of sudden public health events, we explored the effect of quantified and graded management of public places health supervision in Pudong New Area, Shanghai, and drew relevant research results, improving the efficiency of supervision and management in public places. Methods In 2018 from Zhuqiao Town of Pudong New Area Zhuqiao, 200 public places were randomly selected for quantified and graded management of health supervision and quantitative grading including public regulations, tobacco control and appliances, cleaning and disinfection procedures, and according to the score of evaluation results, public health levels A, B, C were rated for those public places.Single factor and multi factor conditional logistic regression model were used for comprehensive analysis to identify related factors affecting the quantitative and graded effect of public health supervision. Results With regard to quantitative and graded health supervision, the relevant knowledge in the 200 public places was updated.By univariate and multivariate conditional logistic regression analysis of multiple factors were ultimately selected 3 factors for public health supervision and quantitative grading management:with or without a health certificate valid (OR=1.121, P=0.026), with or without ashtrays placed in public places (OR=1.012, P=0.032), with or without health inspection report (OR=1.412, P=0.012). Conclusion The influencing factors of quantifying hygienic supervision in public places are mainly effective health certificates, ashtrays in public places and health inspection reports.In future, health supervision of public places should be enhanced in this regard.
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Background: Unmet need for family planning, which refers to the condition in which there is the desire to avoid or post-pone child bearing, without the use of any means of contraception, has been a core concept in the field of international population. This study aimed to determine the factors affecting for unmet need for family planning among married women in the age group of 15-49 years of rural areas of Kalaburagi. By multiple logistic regression model and stepwise forward logistic regression model to estimate the parameters of the model, odds ratios and log likelihood values are computed. Testing of hypothesis of goodness of fit of the model is carried out by Hosmer and Lemeshow test.Methods: 600 married women in the age group of 15-49 years were the study participants who were selected randomly from the 7 taluks of rural areas by using multistage sampling techniques.Results: Total of 26 explanatory variables are included in the model, in which only 5 explanatory variables (19.00%) are found to be significant regression coefficients i.e., education of married women, abortion, physical deformities baby, ideal gap between children, contraceptive used in past normal level of significance (p<0.05).Conclusions: The test statistic of all five models, only model 4 and model 5 fit well with response variable for the rural sample data.
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Objective To identify the main risk factors of human cystic echinococcosis in Shiqu County, Sichuan Province, so as to provide the reference for the formulation of echinococcosis control strategies in Shiqu County. Methods During the period from November 2015 through June 2017, the patients with cystic echinococcosis (case group) and healthy controls (control group) were randomly sampled from Shiqu County as the study subjects. A questionnaire survey was conducted to capture the study subjects’age, gender, ethnicity, occupation, religion, lifestyle, education level, number of household dogs, bovine and sheep, and density of dog feces in the courtyard. The major risk factors of human cystic echinococcosis were identified using a logistic regression model. Results Univariate logistic regression analysis showed 7 risk factors with statistical significance between the case and control groups, and age, lifestyle, number of household bovine, number of household sheep, number of house-hold dogs, and the density of dog feces in the courtyard were included in the multivariate logistic regression model (OR = 1.026, 4.792, 1.067, 1.022, 1.709 and 1.095, respectively). Conclusion High age, pastoral nomadic lifestyle, high number of house-hold bovine, high number of household sheep, high number of household dogs and high density of dog feces in the courtyard are strongly associated with the riks of human cystic echinococcosis in Shiqu County.
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Objective To identify the main risk factors of human cystic echinococcosis in Shiqu County, Sichuan Province, so as to provide the reference for the formulation of echinococcosis control strategies in Shiqu County. Methods During the period from November 2015 through June 2017, the patients with cystic echinococcosis (case group) and healthy controls (control group) were randomly sampled from Shiqu County as the study subjects. A questionnaire survey was conducted to capture the study subjects’age, gender, ethnicity, occupation, religion, lifestyle, education level, number of household dogs, bovine and sheep, and density of dog feces in the courtyard. The major risk factors of human cystic echinococcosis were identified using a logistic regression model. Results Univariate logistic regression analysis showed 7 risk factors with statistical significance between the case and control groups, and age, lifestyle, number of household bovine, number of household sheep, number of house-hold dogs, and the density of dog feces in the courtyard were included in the multivariate logistic regression model (OR = 1.026, 4.792, 1.067, 1.022, 1.709 and 1.095, respectively). Conclusion High age, pastoral nomadic lifestyle, high number of house-hold bovine, high number of household sheep, high number of household dogs and high density of dog feces in the courtyard are strongly associated with the riks of human cystic echinococcosis in Shiqu County.
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Objective To analyze the clinical characteristics and short-term prognostic factors in acute cerebral infarction patients who underwent recanalization. Methods This retrospective study enrolled 94 cases of acute cerebral ischemic patients in the First Affiliated Hospital of Nanjing Medical University between October 2014 and August 2016. Based on the clinical characteristics of the enrolled patients, a multivariate Logistic regression model was established to analyze the risk factors of unfavorable prognosis. Besides, patients were further divided into good collateral circulation group (1-2) and poor collateral circulation group (3-5) according to the Pial Collateral score, and the prognosis improvement rates between patients recanalized within 4 h and over 4 h were analyzed in each group. Chi-square test or Fisher's exact test was used to analyze statistical difference as indicated. Results By multivariate Logistic regression analysis, age older than 70 years old (OR=2.651, 95％CI: 1.013-6.937)and poor collateral circulation (OR=3.160, 95％CI: 1.113-8.977) were independent risk factors of short-term poor prognosis. In the poor collateral circulation subgroup, patients recanalized within 4 h exerted a relatively better prognosis than patients recanalized over 4 h (42.9％ vs.10.5％, P=0.047). However, the effect of recanalization duration on the prognosis in the good collateral circulation subgroups was not statistically significant (42.9％ vs. 10.5％, P=0.047), however, the effect of recanalization duration on prognosis in patients with good collateral circulation was not statistically significant (58.3％ vs. 37.8％, P=0.117). Conclusions For patients with acute cerebral infarction, age and collateral circulation status may influence the prognosis of recanalization therapy. The treatment time had a significant influence on the prognosis in patients with poor collateral, while it had minimal significance on patients with good collateral.
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Objective To explore the risk factors and predict the risk of delirium in patients with mechanical ventilation in intensive care unit(ICU).Methods Data were collected from ICU patients hospitalized from June 2016 to June 2017.Logistic regression model was used to analyze the risk factors of delirium in ICU patients with mechanical ventilation,and the ROC curve was used to calculate the area and optimal cut-off value of the curve.Results This study included 398 patients with 163 cases of delirium,and the incidence of delirium was 41.0％.Logistic regression model showed that using physical restraint (OR=3.084),receiving sedation (OR=2.255),duration of mechanical ventilation(OR=1.146) and ICU length of stay(OR=1.111) were independent predictors of delirium.ROC curve showed that the area under the curve was 0.580,0.566,0.787,and 0.774,respectively,and the cut-off value for mechanical ventilation duration and ICU length was 7 days and 8 days,respectively.Conclusion The incidence of delirium in ICU patients with mechanical ventilation is still high.Physical restraint,sedation,mechanical ventilation time of duration more than 7 days and ICU length of stay greater than 8 days can cause ICU delirium.
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Objective To analyze the prevalence of fatty liver in male patients and to explore the risk factors of the disease,so as to provide theoretical basis for the prevention and treatment of fatty liver in male patients.Methods A total of one thousand seven hundred and eight male patients with physical examination in 2016 in Tangshan Third Hospital were selected, and 488 cases of fatty liver were diagnosed by ultrasonography.The prevalence of fatty liver in male patients with different characteristics was analyzed,the difference of blood biochemical indexes between fatty liver and non fatty liver groups was compared,and the non-conditional logistic regression model was used to explore the risk factors affecting the prevalence of fatty liver in males.Results The prevalence rate of fatty liver in males was 28.6%(488/1708).The results of multivariate logistic regression analysis showed that the individual characteristics(age,BMI,smoking,drinking)and biochemical indexes(FPG,TC,TG,HDL-C,LDL-C)had significant effects on the prevalence of fatty liver in male patients(P<0.05).The prevalence rate of fatty liver increased with age(χ2=77.321,P<0.05),the prevalence rates of<40 years old,≥40 years-<50 years,≥50 years-<60 years,above 60 years were 14.9%(68/488),25.0%(80/488),32.7%(132/488),39.4%(208/488)respectively.Overweight,obesity,smoking and drinking increased the risk of fatty liver disease,and the OR values were 3.173,4.175,2.401 and 3.249 respectively.The biochemical indexes FPG,TC,TG,LDL-C in the fatty liver group((7.61 ± 2.85)mmol/L, (6.55±1.52)mmol/L,(1.97±0.68)mmol/L,(3.18±0.93)mmol/L)were higher than those in the non fatty liver group((5.17 ±1.37)mmol/L,(5.49 ± 1.46)mmol/L,(1.47 ± 0.71)mmol/L,(2.86 ± 0.81)mmol/L),the differences were statistically significant(t=580.648,220.727,176.356,33.596,P<0.05),HDL-C was lower than that in non fatty liver group((1.18 ± 0.38)mmol/L vs.(1.29 ± 0.41)mmol/L,t =42.261,P<0.05).Conclusion The prevalence of male fatty liver was higher.Age,obesity,smoking,alcohol consumption, glucose metabolism and lipid metabolism disorder were closely related to the occurrence of fatty liver in male.
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OBJECTIVE: To analyze the risk factors for stroke in patients with type 2 diabetes in China by using CHIRA database and control the expenditure of medicine for stroke patients and reducing the economic burden of medical insurance funds. METHODS: The data of T2DM patients in the 2015 CHIRA database were collected. The new stroke patients were used as a baseline group. The stroke-free patients who have the similar baseline were selected as the control group by using the PSM. At last, Logistic regression model was used to analyze the relationship between chronic complications of type 2 diabetes and stroke in T2DM patients. RESULTS: Four thousand four hundred and fifty patients were included after using the PSM. Two thousand one hunderd and forty-five(48.20%) patients were diagnosed with chronic complications and 1 138 patients were diagnosed with stroke (53.05%), higher than patietnts who have no chronic complications (47.16%, P<0.0001). Logistic regression model showed that cardiovascular complication(OR=1.19,95%CI:1.05-1.34) and peripheral neuropathy (OR=1.34,95%CI:1.11-1.62) are independent risk factors for stroke. CONCLUSION: Cardiovascular complication and peripheral neuropathy of patients with type 2 diabetes are independent risk factors for stroke.