ObjectiveTo investigate the establishment of a risk nomogram model for predicting vagus excitatory response in patients with functional epilepsy after radiofrequency thermocoagulation.MethodsA total of 106 patients with epilepsy admitted to the neurosurgery department of our hospital from January 2016 to June 2020 were selected and divided into the Vagus excitatory response (VER) group and the non-VER group according to their occurrence or absence. Logistic regression analysis was used to screen out the risk factors of VER during SEEG-guided Percutaneous radiofrequency thermocoagulation (PRFT) in patients with functional epilepsy, and R software was used to establish a histogram model affecting VER in SEEG-guided PRFT. Bootstrap method was used for internal verification. C-index, correction curve and ROC curve were used to evaluate the prediction ability of the model.ResultsLogistic regression analysis showed that age [OR=0.235, 95%CI (0.564, 3.076)], preoperative fugl-meyer score [OR=4.356, 95%CI (1.537, 6.621)], depression [OR=0.995, 95%CI (1.068, 7.404)], and lesion range [OR=1.512, 95%CI (0.073, 3.453)] were independent risk factors for the occurrence of VER in PRFT under the guidance of SEEG (P<0.05), and were highly correlated with the occurrence of VER in PRFT. Based on the above six indicators, a SEEG-guided colograph model of VER risk in PRFT was established, and the model was validated internally. The results showed that the C-index of the modeling set and validation set were 0.779 [95%CI (0.689, 0.869)] and 0.782 [95%CI (0.692, 0.872)], respectively. The calibration curves of the two groups fit well with the standard curves. The areas under the ROC curve (AUC) of the two groups were 0.779 and 0.782 respectively, which proved that the model had good prediction accuracy.ConclusionFor patients with functional epilepsy requiring seeg-guided PRFT therapy, age, preoperative Fugl-meyer score, depression and lesion range should be taken into full consideration to comprehensively assess the incidence of VER, and early intervention measures should be taken to reduce and reduce the incidence, which has good clinical application value.
ObjectiveTo retrospectively evaluate the risk factors of mortality in postoperative acute kidney injury (AKI) patients undergoing continuous renal replacement therapy (CRRT) after cardiopulmonary bypass (CPB). MethodsWe retrospectively analyzed the clinical data of 66 patients (38 males and 28 females with mean age of 59.11±12.62 years) underwent CRRT after cardiovascular surgery in our hospital between May 2009 and June 2014. The patients were divided into a survival group (18 patients) and a death group (48 patients) according to treatment outcome at discharge. Univariate analysis for risk factors of death was carried out for preoperative characteristics and lab results among study population. Significant univariate factors were then further analyzed by multivariable logistic regression models. ResultsSignificant predictors of death included blood transfusion volume during operation, peak level of blood sugar and lactate during operation, the total bilirubin level and platelet count on the first day after operation, hypotension on the first day after operation, pulmonary infection, multiple organ dysfunction syndrome (MODS) and the interval time of oliguria and CRRT (P<0.05). Logistic regression showed that there were statistical differencs in hypotension on the first day after operation, postoperative platelet count, and interval time of oliguria and CRRT respectively (P<0.05). ConclusionImproving intraoperative management, reducing bleeding and blood transfusion, controlling blood sugar level, dealing with complications such as hypotension, pulmonary infection and MODS more aggressively, starting CRRT when needed may be helpful to reduce mortality. Monitoring of the blood pressure and platelet count on the first day after operation is useful for prognosis estimation.
ObjectiveTo explore the prevalence and risk factors of hypertension in Anyue County from June 2011 to June 2013. MethodsUsing stratfied random cluster sampling method, 5 391 people over 15 years of age were selected from 3 residential areas and 3 natural villages to finish a questionnaire and blood pressure measurement. ResultsThe total prevalence rate of hypertension in Anyue County was 18.77%. The prevalence rates of hypertension in urban areas and rural areas were 21.75% and 16.20%, and the difference was significant (χ2=27.120, P<0.001). In both urban and rural areas, the prevalence rate of hypertension increased with age (χ2=475.634, P<0.001; χ2=394.026, P<0.001). The percentages of awareness, treatment and control in Anyue County were 31.30%, 24.41%, and 9.09%. The percentages of awareness, treatment and control in urban areas were 40.15%, 33.70%, and 11.23% and were 20.68%, 13.65%, and 6.61% in rural areas. There were significant differences in the percentages of awareness, treatment and control between urban and rural areas (χ2=44.475, P<0.001; χ2=54.861, P<0.001; χ2=8.202, P=0.004). The logistic regression analysis showed that age (OR=1.061, P<0.001), diabetes (OR=1.550, P<0.001), hyperlipemia (OR=2.372, P<0.001) and smoking (OR=1.335, P<0.001) were the risk factors for hypertension; and it showed that high level of education was a protective factor for hypertension (OR=0.755, P<0.001). ConclusionBecause of high prevalence and low percentages of awareness, treatment and control in Anyue County, the prevention and control situation of hypertension are grim. We should focus on the control of smoking, blood lipid and blood glucose.
Objective To explore the impact of hospital staff’s risk perception on their emergency responses, and provide reference for future responses to public health emergencies. Methods Based on participatory observation and in-depth interviews, the staff of the First Affiliated Hospital of Guangzhou Medical University who participated in the prevention and control of the coronavirus disease 2019 from April to September 2020 were selected. The information on risk perception and emergency responses of hospital staff was collected. Results A total of 61 hospital staff were included. The positions of hospital staff were involved including hospital leading group, hospital office, medical department, logistics support department and outpatient isolation area. The interview results showed that both individual and organizational factors of hospital staff would affect the risk perception of hospital staff, thus affecting the emergency responses of hospital staff, mainly reflected in the psychological and behavioral aspects. Among them, their psychological reactions were manifested as more confidence, sensitivity, and sense of responsibility and mission; The behavior aspects was mainly reflected in the initiation time, execution ability, and standardization level of emergency responses actions. Conclusion Therefore, relevant departments should pay attention to the risk perception of hospital staff, improve the risk perception and emergency responses of hospital staff by influencing the individual and organizational factors of hospital staff, so as to respond more effectively to future public health emergencies and reduce the adverse impact of public health emergencies on the work of hospital staff.
Objective To systematically review risk prediction models of in-hospital cardiac arrest in patients with cardiovascular disease, and to provide references for related clinical practice and scientific research for medical professionals in China. Methods Databases including CBM, CNKI, WanFang Data, PubMed, ScienceDirect, Web of Science, The Cochrane Library, Wiley Online Journals and Scopus were searched to collect studies on risk prediction models for in-hospital cardiac arrest in patients with cardiovascular disease from January 2010 to July 2022. Two researchers independently screened the literature, extracted data, and evaluated the risk of bias of the included studies. Results A total of 5 studies (4 of which were retrospective studies) were included. Study populations encompassed mainly patients with acute coronary syndrome. Two models were modeled using decision trees. The area under the receiver operating characteristic curve or C statistic of the five models ranged from 0.720 to 0.896, and only one model was verified externally and for time. The most common risk factors and immediate onset factors of in-hospital cardiac arrest in patients with cardiovascular disease included in the prediction model were age, diabetes, Killip class, and cardiac troponin. There were many problems in analysis fields, such as insufficient sample size (n=4), improper handling of variables (n=4), no methodology for dealing with missing data (n=3), and incomplete evaluation of model performance (n=5). Conclusion The prediction efficiency of risk prediction models for in-hospital cardiac arrest in patients with cardiovascular disease was good; however, the model quality could be improved. Additionally, the methodology needs to be improved in terms of data sources, selection and measurement of predictors, handling of missing data, and model evaluations. External validation of existing models is required to better guide clinical practice.
The pathogenesis of diabetic retinopathy (DR) is complex and there are many related risk factors. It is related to the course of diabetes, blood glucose, blood pressure, and blood lipids, among which the course of disease and hyperglycemia are recognized main risk factors. In addition, other factors which include heredity, gender, age, obesity, pregnancy, insulin use, can also affect the occurrence and development of DR, but there is no unified conclusion about its correlation. A comprehensive understanding of the risk factors that affect DR can provide new ideas for the prevention, diagnosis, treatment, and intervention of DR.
Objective To analyze the risk factors for duration of mechanical ventilation in critically ill patients. Methods Ninety-six patients who received mechanical ventilation from January 2011 to December 2011 in intensive care unit were recruited in the study. The clinical data were collected retrospectively including the general condition, underlying diseases, vital signs before ventilation, laboratory examination, and APACHEⅡ score of the patients, etc. According to ventilation time, the patients were divided into a long-term group ( n = 41) and a short-term group ( n = 55) . Risk factors were screened by univariate analysis, then analyzed by logistic regression method.Results Univariate analysis revealed that the differences of temperature, respiratory index, PaCO2 , white blood cell count ( WBC) , plasma albumin ( ALB) , blood urea nitrogen ( BUN) , pulmonary artery wedge pressure ( PAWP) , APACHEⅡ, sex, lung infection in X-ray, abdominal distention, and complications between two groups were significant.With logistic multiple regression analysis, the lower level of ALB, higher level of PAWP, lung infection in X-ray, APACHE Ⅱ score, abdominal distention, and complications were independent predictors of long-term mechanical ventilation ( P lt;0. 05) . Conclusion Early improving the nutritional status and cardiac function, control infection effectively, keep stool patency, and avoid complications may shorten the duration of mechanical ventilation in critically ill patients.
ObjectiveTo investigate risk factors of anastomotic fistula after total mesorectum excision (TME) in middle and low rectal cancer. MethodsThe clinical data of 446 patients with middle and low rectal cancer received TME surgery from June 2004 to June 2014 were retrospectively analyzed.Single-factor analysis of risk factors was used by χ2 test,multiple-factor analysis was used by logistic regression analysis. ResultsThere were 36 patients with anastomotic fistula in these 446 patients,which of 22 patients were recovered after conservative treatment,of 14 patients were recovered after colostomy.The results of single-factor analysis showed that the age>60 years,preoperative hemoglobin<110 g/L,preoperative albumin<35 g/L,accompanied with diabetes mellitus,neoadjuvant chemoradiation,distance from anasto-mosis to anus<5 cm,non-strengthen suture by hand were the risk factors of anastomotic fistula after TME in the middle and low rectal cancer (P<0.05).The results of multiple-factor analysis showed that the preoperative hemoglobin<110 g/L,preoperative albumin<35 g/L,accompanied with diabetes mellitus,neoadjuvant chemoradiation,and distance from anastomosis to anus<5 cm were the independent risk factors of anastomotic fistula after TME in the middle and low rectal cancer (P<0.05). ConclusionsRisk of anastomotic fistula after TME in middle and low rectal cancer is higher.Basic complications of patient and local conditions of anastomosis,and intraoperative factors could affect incidence of anastomotic fistula,it should be paid enough attention.In general,most of anastomotic fistula could be cured with conservative treatment,in case of conservative treatment is invalid,colostomy is feasible.
ObjectiveConstructing a prediction model for seizures after stroke, and exploring the risk factors that lead to seizures after stroke. MethodsA retrospective analysis was conducted on 1 741 patients with stroke admitted to People's Hospital of Zhongjiang from July 2020 to September 2022 who met the inclusion and exclusion criteria. These patients were followed up for one year after the occurrence of stroke to observe whether they experienced seizures. Patient data such as gender, age, diagnosis, National Institute of Health Stroke Scale (NIHSS) score, Activity of daily living (ADL) score, laboratory tests, and imaging examination data were recorded. Taking the occurrence of seizures as the outcome, an analysis was conducted on the above data. The Least absolute shrinkage and selection operator (LASSO) regression analysis was used to screen predictive variables, and multivariate Logistic regression analysis was performed. Subsequently, the data were randomly divided into a training set and a validation set in a 7:3 ratio. Construct prediction model, calculate the C-index, draw nomogram, calibration plot, receiver operating characteristic (ROC) curve, and decision curve analysis (DCA) to evaluate the model's performance and clinical application value. ResultsThrough LASSO regression, nine non-zero coefficient predictive variables were identified: NIHSS score, homocysteine (Hcy), aspartate aminotransferase (AST), platelet count, hyperuricemia, hyponatremia, frontal lobe lesions, temporal lobe lesions, and pons lesions. Multivariate logistic regression analysis revealed that NIHSS score, Hcy, hyperuricemia, hyponatremia, and pons lesions were positively correlated with seizures after stroke, while AST and platelet count were negatively correlated with seizures after stroke. A nomogram for predicting seizures after stroke was established. The C-index of the training set and validation set were 0.854 [95%CI (0.841, 0.947)] and 0.838 [95%CI (0.800, 0.988)], respectively. The areas under the ROC curves were 0.842 [95%CI (0.777, 0.899)] and 0.829 [95%CI (0.694, 0.936)] respectively. Conclusion These nine variables can be used to predict seizures after stroke, and they provide new insights into its risk factors.
Nonrandomized studies are an important method for evaluating the effects of exposures (including environmental, occupational, and behavioral exposures) on human health. Risk of bias in nonrandomized studies of exposures (ROBINS-E) is used to evaluate the risk of bias in natural or occupational exposure observational studies. This paper introduces the main contents of ROBINS-E 2022, including backgrounds, seven domains, signal questions and the operation process.