The Effect of Aortic Angulation on Clinical Outcomes of Patients Undergoing Transcatheter Aortic Valve Replacement

ABSTRACT Introduction: The aim of this study was to assess the impact of aortic angulation (AA) on periprocedural and in-hospital complications as well as mortality of patients undergoing Evolut™ R valve implantation. Methods: A retrospective study was conducted on 264 patients who underwent transfemoral-approach transcatheter aortic valve replacement with self-expandable valve at our hospital between August 2015 and August 2022. These patients underwent multislice computer tomography scans to evaluate AA. Transcatheter aortic valve replacement endpoints, device success, and clinical events were assessed according to the definitions provided by the Valve Academic Research Consortium-3. Cumulative events included paravalvular leak, permanent pacemaker implantation, new-onset stroke, and in-hospital mortality. Patients were divided into two groups, AA ≤ 48° and AA > 48°, based on the mean AA measurement (48.3±8.8) on multislice computer tomography. Results: Multivariable logistic regression analysis was performed to identify predictors of cumulative events, utilizing variables with a P-value < 0.2 obtained from univariable logistic regression analysis, including AA, age, hypertension, chronic renal failure, and heart failure. AA (odds ratio [OR]: 1.73, 95% confidence interval [CI]: 0.89-3.38, P=0.104), age (OR: 1.04, 95% CI: 0.99-1.10, P=0.099), hypertension (OR: 1.66, 95% CI: 0.82-3.33, P=0.155), chronic renal failure (OR: 1.82, 95% CI: 0.92-3.61, P=0.084), and heart failure (OR: 0.57, 95% CI: 0.27-1.21, P=0.145) were not found to be significantly associated with cumulative events in the multivariable logistic regression analysis. Conclusion: This study demonstrated that increased AA does not have a significant impact on intraprocedural and periprocedural complications of patients with new generation self-expandable valves implanted.

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.

Prevalência de diabetes mellitus e fatores associados em adultos: inquérito de base populacional / Prevalence of diabetes mellitus and associated factors in adults: population-based survey

Estimar a prevalência de diabetes mellitus e os fatores associados em adultos. Trata-se de um inquérito realizado com 1.637 indivíduos nas zonas urbana e rural do município de Rio Branco, Acre. Diabetes foi definido pela presença de glicemia no plasma em jejum ≥ 126 mg/dl ou utilização de hipoglicemiante oral ou insulina. Medidas de associação foram estimadas por regressão logística hierarquizada. A prevalência de diabetes foi de 6,5% (n = 202). Após análise, a chance de ser diabético esteve independente e positivamente associada a idade ≥ 60 anos (OR: 6,67; IC95%: 1,83-24,30); história familiar de diabetes mellitus (OR: 2,88; IC95%: 1,43-5,81); circunferência da cintura aumentada (OR: 1,83; IC95%:1,01-3,33); dislipidemia (OR: 2,95; IC95%: 1,34-6,49); anemia (OR: 3,15; IC95%: 1,30-7,60); e doença renal crônica (DRC) (OR: 4,00; IC95%: 1,70-9,33). Foi detectada uma prevalência de 6,5%, estando o diabetes associado com idade, história familiar, anemia e DRC. Indica-se a necessidade do adequado rastreio de comorbidades nesses pacientes.

To estimate the prevalence of diabetes mellitus and associated factors in adults.Survey carried out with 1,637 individuals in urban and rural areas of the municipality of Rio Branco, state of Acre. Diabetes was defined by the presence of fasting plasma glucose ≥ 126 mg/dl or the use of oral hypoglycemic agents or insulin. Association measures were estimated by hierarchical logistic regression.The prevalence of diabetes was 6.5% (n = 202). After analysis, the chance of being diabetic was independently and positively associated with age ≥ 60 years (OR: 6.67; 95%CI: 1.83-24.30); family history of diabetes mellitus (OR: 2.88; 95%CI: 1.43-5.81); increased waist circumference (OR: 1.83; 95%CI: 1.01-3.33); dyslipidemia (OR: 2.95; 95%CI: 1.34-6.49); anemia (OR: 3.15; 95%CI: 1.30-7.60); and chronic kidney disease (CKD) (OR: 4.00; 95%CI: 1.70-9.33). A prevalence of 6.5% was detected, with diabetes associated with age, family history, anemia, and CKD. The need for adequate screening of comorbidities in these patients is indicated.

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.

Construction of Logistic prediction model and countermeasures for type 2 diabetic nephropathy based on clinical data / 中国医师进修杂志

Objective:To explore the construction of a Logistic prediction model and countermeasures for type 2 diabetic nephropathy based on clinical data.Methods:The patients with type 2 diabetic nephropathy admitted to Shijiazhuang Second Hospital from September 2019 to September 2021 (study group) were selected and the patients were selected according to a 1∶1 ratio using individual matching (control group), each group with 200 patients. Single and multiple factors analysis were used to analyze the factors influencing type 2 diabetic nephropathy, and Logistic regression equation models were developed to verify their predictive value.Results:Logistic regression equation model showed that the course of type 2 diabetes, glycosylated hemoglobin (HbA 1c), fasting plasma glucose (FPG), homocysteine (Hcy), urinary microalbumin, and serum creatinine (Scr) were high risk factors for type 2 diabetic nephropathy ( P<0.05). The results of Logistic regression model evaluation showed that the model was established with statistical significance, and the coefficients of the regression equations had statistically significant differences. The Hosmer-Lemeshow goodness-of-fit test showed that the model fitting effect was good. Logistic regression model was used to statistically analyzed the data set, and the receiver operating characteristic (ROC) curve of type 2 diabetic nephropathy was drawn, the area under the curve was 0.949(95% CI 0.922 - 0.968), the prediction sensitivity was 81.50%, the specificity was 95.50%, the calibration curve showed that the predicted results was in good agreement with the observed results. Conclusions:The independent predictors of type 2 diabetic nephropathy involve HbA 1c, FPG, Hcy, urinary microalbumin. The Logistic prediction model based on these predictors has reliable predictive value and can help guide clinical diagnosis and treatment.

Analysis of influencing factors of delayed nausea and vomiting in patients with primary liver cancer after transarterial chemoembolization based on two models / 中国实用护理杂志

Objective:To analyze the influencing factors of delayed nausea and vomiting in patients with primary liver cancer after transarterial chemoembolization based on Logistic regression model and decision tree model.Methods:This was a cross-sectional study. A total of 236 patients with primary liver cancer after transarterial chemoembolization in The Second Affiliated Hospital of Air Force Military Medical University from March 2021 to June 2022 were conveniently selected as the research subjects. The factors related to delayed nausea and vomiting were collected, and Logistic regression and decision tree models were established, respectively, and the differences between the two models were compared.Results:The incidence of delayed nausea and vomiting of patients with primary liver cancer after transarterial chemoembolization was 45.34% (107/236). Logistic regression model showed that age, anxiety, sleep disorder, emetic risk level of chemotherapeutic drugs, embolic agent type, and pain 24 hours after surgery were the influencing factors of delayed nausea and vomiting in patients with primary liver cancer after transarterial chemoembolization(all P<0.05). Decision tree model showed that age, sleep disorder, emetic risk level of chemotherapeutic drugs, embolic agent type, and pain 24 hours after surgery were the influencing factors of delayed nausea and vomiting in patients with primary liver cancer after transarterial chemoembolization (all P<0.05). The classification accuracy rates of Logistic regression, decision tree model and combined diagnosis of two models were 72.9%, 71.2% and 72.0% respectively; the areas under the ROC curve were 0.778, 0.781 and 0.806 respectively, with no significant difference (all P>0.05). Conclusions:The analysis results of Logistic regression and decision tree model on the influencing factors of delayed nausea and vomiting in patients with primary liver cancer after transarterial chemoembolization are highly consistent, which can be combined to provide a more comprehensive reference for the evaluation and intervention of medical staff.

Simple model construction of arteriovenous fistula classification in maintenance hemodialysis patients / 中国实用护理杂志

Objective:To construct a simple model of arteriovenous fistula classification,and to achieve the classification of arteriovenous fistula in hemodialysis patients.Methods:The study was a retrospective analysis, a total of 304 hemodialysis patients with internal fistula in People′s Hospital of Deyang City from January 2016 to January 2021 were selected by convenience sampling method,depending on whether the internal fistula was dysfunctional, patients were divided into 64 in the internal fistula failure group and 240 in the internal fistula patency group. Independent influence factors and their regression coefficient were obtained by single-factor analysis and logistic regression analysis, The risk score formula was established based on the regression coefficient to form a simple model of internal fistula classification.The model was evaluated by receiver operating characteristic curve and the scoring criteria for internal fistula classification was determined.Results:Logistic regression analysis showed that diabetes mellitus, hypotension, age≥60 years old, compression time≥30 min, blood phosphorus>1.78 mmol/L, triglyceride>1.71 mmol/L and fibrinogen>4 g/L were independent influencing factors of internal fistula failure (all P<0.05).The area under the receiver operating characteristic curve was 0.858(95% CI 0.789-0.928, P<0.01), and the best critical value of the internal fistula classification was 7.5, the sensitivity was 80.4% and the specificity was 84.8%. Conclusions:By obtaining the predictors of internal fistula failure, conducted the risk score, and constructed a simple model of internal fistula classification, which can effectively predicted the risk of internal fistula failure. It is conducive to the implementation of internal fistula classification management and the puncture of corresponding grade, to ensure the pathway safety of patients.

Factors associated with poor short-term pharmacotherapy response in self-limited epilepsy with centrotemporal spikes / 中华实用儿科临床杂志

Objective:To explore risk factors for clinical onset in children with uncontrolled self-limited epilepsy with centrotemporal spikes (SeLECTS) managed by 2 anti-seizure medications (ASMs).Methods:A total of 112 children with SeLECTS who were diagnosed at the Department of Pediatric Neurology of the Third Affiliated Hospital of Zhengzhou University from January 2018 to May 2021 were retrospectively reviewed.All of them were treated with conventional ASMs, and regularly followed up for 1-2 years.Types of therapeutic drugs, clinical seizure control status, presence of new seizure forms, electroencephalogram (EEG) were reviewed at follow-up visits.According to whether the seizures were controlled after the use of no more than 2 ASMs, patients were divided into poor response group (43 cases) and good response group (69 cases), and their clinical data and EEG characteristics were compared.Multivariate Logistic regression analysis was used to explore the risk factors for seizures that were uncontrolled by 2 ASMs. Results:There were significant differences in the age of onset ( χ2=8.919, P=0.003), seizure form ( χ2=4.218, P=0.040), seizure frequency ( Z=-7.664, P<0.001), EEG background slowing ( χ2=10.284, P=0.001), emergence of electrical status epilepticus during slow-wave sleep (ESES)( χ2=11.921, P=0.001), discharge generalization ( χ2=25.377, P<0.001), and presence of epileptic encephalopathy with spike-and-wave activation in sleep (EE-SWAS)( χ2=54.334, P<0.001) between groups.Multivariate Logistic regression analysis showed that seizure frequency ( P<0.001, OR=0.086, 95% CI: 0.022-0.329), discharge generalization ( P=0.006, OR=9.942, 95% CI: 1.918-51.527) and EEG background slowing ( P=0.041, OR=6.648, 95% CI: 1.077-41.038) were the 3 main risk factors associated with poor response to short-term medications of ASMs. Conclusions:Seizures are easily controlled in most SeLECTS patients medicated with ASMs with a favorable prognosis.Seizure frequency, discharge generalization and EEG background slowing are risk factors for the poor response to short-term pharmacotherapy in children with SeLECTS.

Risk factors of endometrial lesions after breast cancer surgery and construction of a graph model / 中华内分泌外科杂志

Objective:To explore the risk factors affecting endometrial lesions after breast cancer surgery, and build a nomogram prediction model.Methods:From Oct. 2019 to Nov. 2021, 103 patients with abnormal bleeding after breast cancer surgery were selected, the clinical data of the patients were collected, and they were divided into the non-lesion group and the lesion group according to whether the endometrial lesion occurred. A Logistic risk regression model was established to analyze the risk factors affecting endometrial lesions in postoperative patients with breast cancer, a nomogram prediction model was constructed and verified, and receiver operating characteristic curve (ROC) analysis was performed to analyze the nomogram model for predicting sensitivityof endometrial lesions.Results:Childbirth history ( OR=37.100, 95% CI: 3.777-527.7, P=0.004), endometrial thickness ( OR=2.489, 95% CI: 1.699-4.007, P<0.001), menopause ( OR=0.099, 95% CI: 0.015-0.499, P=0.009), abnormal bleeding time ( OR=6.922, 95% CI: 2.221-24.800, P=0.002), and types of treatment drugs ( OR=3.738, 95% CI: 1.187-13.200, P=0.030) had statistical significance in predicting endometrial lesions in postoperative patients with breast cancer. Using the above five variables to construct a nomogram model, the consistency of the nomogram in predicting endometrial lesions in postoperative patients with breast cancer was 0.739, and the discrimination was good. The calibration curve showed that the average absolute error between the predicted probability and the actual probability was 0.041,and ROC curve showed that the AUC value of the nomogram model for predicting endometrial lesions was 0.800. Conclusion:Establishing a nomogram model for predicting the risk of endometrial lesions in postoperative patients with breast cancer has good accuracy and high clinical value.

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.

Factors associated with loss to follow-up in tuberculosis treatment in Brazil: a retrospective cohort study / Factores asociados a la pérdida de seguimiento del tratamiento para la tuberculosis en Brasil: cohorte retrospectiva / Fatores associados à perda de seguimento do tratamento para tuberculose no Brasil: coorte retrospectiva

ABSTRACT Objective: To analyze the factors associated with loss to follow-up in tuberculosis cases among adults in Brazil in 2020 and 2021. Method: Retrospective cohort with secondary data from the Brazilian Notifiable Diseases Information System. A total of 24,344 people diagnosed with tuberculosis whose information was complete in the database were included. Adjusted odds ratios and confidence intervals were estimated by binary logistic regression. Results: Higher odds of loss to follow-up were observed for males, non-white ethnicity/color, with lower education level, homeless or deprived of liberty, who used drugs, alcohol and/or tobacco, with admission due to recurrence or re-entry after abandonment, and with unknown or positive serology for HIV. On the other hand, older age, extrapulmonary tuberculosis, deprivation of libertyand supervised treatment were associated with lower odds of loss to follow-up. Conclusion: Demographic, socioeconomic and clinical-epidemiological factors were associated with the loss to follow-up in tuberculosis cases, which reiterates the various vulnerabilities intertwined with the illness and treatment of this disease. Therefore, there is a need to promote strategies aimed at adherence and linkage to the care for groups most vulnerable to loss to follow-up in tuberculosis treatment in Brazil.

RESUMEN Objetivo: Analizar los factores asociados a la pérdida de seguimiento de los casos de tuberculosis entre adultos en Brasil en 2020 y 2021. Método: Cohorte retrospectiva con datos secundarios del Sistema de Información de Enfermedades de Declaración Obligatoria de Brasil. Se incluyeron un total de 24.344 personas diagnosticadas con tuberculosis cuya información estaba completa en la base de datos. Las razones de probabilidad ajustadas y los intervalos de confianza se estimaron mediante regresión logística binaria. Resultados: Se observaron mayores posibilidades de perder el seguimiento para el sexo masculino, de etnia/color no blanco, con baja escolaridad, sin hogar, que usaban drogas, alcohol y/o tabaco, con ingreso por recidiva o reingreso tras abandono, y con serología desconocida o positiva para VIH. Por otro lado, la edad avanzada, la forma extrapulmonar de tuberculosis, la privación de libertad y el tratamiento supervisado se asociaron con menores probabilidades. Conclusión: Factores demográficos, socioeconómicos y clínico-epidemiológicos se asociaron a la pérdida del seguimiento de los casos de tuberculosis, lo que reitera las diversas vulnerabilidades entrelazadas con la enfermedad y el tratamiento de esta enfermedad. Por lo tanto, existe la necesidad de promover estrategias dirigidas a la adherencia y la vinculación a la atención de los grupos más vulnerables a la pérdida del tratamiento de seguimiento de la tuberculosis en Brasil.

RESUMO Objetivo: Analisar os fatores associados à perda de seguimento dos casos de tuberculose entre adultos no Brasil em 2020 e 2021. Método: Coorte retrospectiva com dados secundários provenientes do Sistema de Informação de Agravos de Notificação do Brasil. Foram incluídas 24.344 pessoas diagnosticadas com tuberculose cujas informações estavam completas no banco de dados. Razões de chances ajustadas eintervalos de confiança foram estimados por regressão logística binária. Resultados: Observaram-se maiores chances de perda de seguimento para pessoas do sexo masculino, deetnia/cor não branca, combaixa escolaridade, em situação de rua, que faziamuso de drogas, álcool e/outabaco, com entrada porrecorrênciaou reingressoapós abandono, e com sorologia desconhecida oupositiva para HIV. Por outro lado, a idade mais avançada, a forma extrapulmonar da tuberculose, a privação de liberdade eo tratamento supervisionado associaram-se a menores chances. Conclusão: Fatores demográficos, socioeconômicos e clínico-epidemiológicos estiveram associadosà perda de seguimento dos casos de tuberculose, o que reitera as diversas vulnerabilidades imbricadas ao adoecimento e ao tratamento dessa doença. Portanto, constata-se a necessidade depromoção de estratégias que visem à adesão e à vinculação ao cuidado dos grupos mais vulneráveis à perda de seguimento do tratamento para tuberculoseno Brasil.

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.

Association between multimorbidity, intensive care unit admission, and death in patients with COVID-19 in Brazil: a cross-section study, 2020

ABSTRACT BACKGROUND: Multimorbidity can influence intensive care unit (ICU) admissions and deaths due to coronavirus disease (COVID-19). OBJECTIVE: To analyze the association between multimorbidity, ICU admissions, and deaths due to COVID-19 in Brazil. DESIGN AND SETTING: This cross-sectional study was conducted using data from patients with severe acute respiratory syndrome (SARS) due to COVID-19 recorded in the Influenza Epidemiological Surveillance Information System (SIVEP-Gripe) in 2020. METHODS: Descriptive and stratified analyses of multimorbidity were performed based on sociodemographic, ventilatory support, and diagnostic variables. Poisson regression was used to estimate the prevalence ratios. RESULTS: We identified 671,593 cases of SARS caused by COVID-19, of which 62.4% had at least one morbidity. Multimorbidity was associated with male sex, age 60-70 and ≥ 80 years, brown and black skin color, elementary education and high school, ventilatory support, and altered radiologic exams. Moreover, all regions of the country and altered computed tomography due to COVID-19 or other diseases were associated with death; only the northeast region and higher education were associated with ICU admission. CONCLUSION: Our results showed an association between multimorbidity, ICU admission, and death in COVID-19 patients in Brazil.

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.