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.

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.

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 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.

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.

Construction of a prediction model for difficult tracheal intubation in patients with obstructive sleep apnea-hypopnea syndrome / 中华麻醉学杂志

Objective:To construct a prediction model for difficult tracheal intubation in the patients with obstructive sleep apnea-hypopnea syndrome (OSAHS).Methods:A total of 324 patients with OSAHS undergoing surgery with general anesthesia, admitted to our hospital from June 2019 to June 2021, were included in model group, and 175 patients with OSAHS undergoing surgery with general anesthesia, admitted from July 2021 to July 2022, were selected and served as validation group. The patients in model group were divided into occurrence group and non-occurrence group according to whether difficult tracheal intubation occurred. Logistic regression was used to construct the prediction model, and R4.2.1 software was used to draw the risk nomogram and calibration curve. The predictive accuracy of the model was evaluated by the area under the receiver operating characteristic curve.Results:Body mass index (BMI), sagittal minimum cross-sectional area, horizontal minimum cross-sectional area and mandibular distance were risk factors for difficult tracheal intubation in OSAHS patients ( P<0.05). A prediction model was developed using the above factors: Logit P=33.726+ 1.411×BMI score-0.014×sagittal airway minimum cross-sectional area-0.013×airway horizontal minimum cross-sectional area-0.312× mandibular distance. The area under the receiver operating characteristic curve was 0.846, Youden index 0.585, sensitivity 0.831, specificity 0.755, and the accuracy 0.889 (Hosmer-Lemeshow test χ2=9.24, P=0.322) in model group. The area under the external validation curve was 0.802, Youden index 0.545, sensitivity 0.636, specificity 0.908, and the accuracy 0.893 (Hosmer-Lemeshow test χ2=10.24, P=0.287) in validation group. Conclusions:The prediction model based on BMI, sagittal minimum cross-sectional area of airway, horizontal minimum cross-sectional area of airway and mandibular distance has a high value in predicting the risk of difficult tracheal intubation in patients with OSAHS.

Analysis of influencing factors of clinical outcome after surgery and 131I treatment in patients with moderate-risk papillary thyroid cancer / 中华核医学与分子影像杂志

Objective:To investigate the clinical outcome after surgery and first 131I treatment in patients with moderate-risk papillary thyroid cancer (PTC), and analyze the relevant factors that affect the therapeutic effect. Methods:From January 2018 to April 2019, 135 patients (48 males, 87 females; age (42.7±11.1) years) with moderate-risk PTC in the Second Affiliated Hospital of Chongqing Medical University were retrospectively analyzed. According to the 2015 American Thyroid Association (ATA) guidelines, patients were divided into excellent response (ER) group, inderteriminate response (IDR) group, biochemical incomplete response (BIR) group and structural incomplete response (SIR) group, of which IDR, BIR, SIR were collectively referred to as the non-ER group. χ2 test and Mann-Whitney U test were used to compare the general clinical features between the ER and non-ER groups, and then multivariate logistic regression analysis was performed. The predicted value of pre-ablation stimulated thyroglobulin (ps-Tg) to ER was assessed by ROC curve analysis. Results:The treatment responses of 94 patients were ER, and those of 41 were non-ER. The differences in tumor size (0.80(0.50, 1.10) vs 1.00(0.55, 1.50) cm; U=1 491.50, P=0.036), the number of metastatic lymph nodes (3(2, 5) vs 4(2, 12); U=1 422.00, P=0.015), metastatic lymph node size (0.50(0.30, 0.65) vs 0.50(0.30, 1.45) cm; U=1 396.50, P=0.013), metastatic lymph node involvement rate (50%(30%, 70%) vs 60%(50%, 85%); U=1 441.50, P=0.024), metastatic lymph node location (central/lateral: 76/18 vs 24/17; χ2=7.40, P=0.007) and ps-Tg level (2.1(0.8, 5.3) vs 14.0(3.2, 35.2) μg/L; U=680.00, P<0.001) were statistically significant between the ER and non-ER groups. Multivariate logistic regression analysis showed that ps-Tg (odds ratio ( OR)=1.200, 95% CI: 1.107-1.302, P<0.001) was an independent factor influencing ER. The cut-off value of ps-Tg for predicting ER was 7.38 μg/L, with the sensitivity and specificity of 68.3%(28/41) and 87.2%(82/94) respectively. Conclusion:Moderate-risk PTC patients with smaller tumor size, fewer metastatic lymph nodes, lower metastatic lymph node involvement rate, metastatic lymph nodes in central area, smaller metastatic lymph node size, and ps-Tg<7.38 μg/L have better therapeutic effect after initial 131I treatment.

Analysis on risk factors for prognosis of traumatic brain injury in adults and establishment of the prediction model / 中华创伤杂志

Objective:To analyze risk factors for prognosis of adult patients with traumatic brain injury (TBI), construct the prognostic model of TBI and evaluate its predictive value.Methods:A case-control study was used to analyze the clinical data of 522 patients with TBI admitted to Xijing Hospital of Air Force Medical University from March 2011 to September 2019, including 438 males and 84 females; aged 18-75 years [(44.9±15.0)years]. According to the Glasgow outcome score (GOS) at discharge, the patients were divided into good prognosis group (GOS 4-5 points, n=165) and poor prognosis group (GOS 1-3 points, n=357). The two groups were compared with regards to qualitative data such as sex, underlying diseases, causes of injury, multiple injuries, open injuries, intracranial foreign bodies, cerebral herniation, consciousness status on admission and at discharge, surgery, lung infection on admission, tracheostomy, ventilator-assisted ventilation, hospital-acquired pneumonia/pathogenic bacteria and intracranial infection, and quantitative data such as Glasgow coma score (GCS) on admission and at discharge, age, measurements on admission [systolic blood pressure, diastolic blood pressure, mean arterial pressure, temperature, heart rate, creatinine, urea nitrogen, blood sodium, blood potassium, blood glucose, prothrombin time (PT), activated partial thromboplastin time (APTT), platelets, international normalized ratio (INR), pupil size of both eyes] and length of hospital stay. Univariate analysis and Lasso regression analysis were used to screen the risk factors affecting the prognosis of TBI patients, and the selected influencing factors were included in multivariate Logistic regression analysis to identify independent risk factors and construct regression equations. R was used to draw a visual nomogram based on regression equation for predicting the prognosis of TBI patients. The prognostic predictive value of the nomogram was evaluated by using the receiver operating characteristic (ROC) curve, and the area under the curve (AUC), Youden index, sensitivity, specificity and consistency index (C index) were calculated. Results:Univariate analysis showed that there were significant differences between the two groups in underlying diseases, open injuries, cerebral herniation, consciousness status on admission and at discharge, lung infection on admission, tracheostomy, ventilator-assisted ventilation, hospital-acquired pneumonia/pathogenic bacteria, GCS on admission and at discharge, age, and measurements on admission (systolic blood pressure, mean arterial pressure, body temperature, heart rate, creatinine, urea nitrogen, blood potassium, blood glucose, PT, INR, pupil size of right eye) (all P<0.05 or 0.01). There were no significant differences between the two groups in gender, causes of injury, multiple injuries, intracranial foreign bodies, surgery, intracranial infection, measurements on admission (diastolic blood pressure, blood sodium, APTT, platelets, pupil size of left eye) and length of hospital stay (all P>0.05). After screening by Lasso regression model, the results of multivariate Logistic regression analysis showed that GCS on admission ( OR=0.67, 95% CI 0.62, 0.73, P<0.01), age ( OR=1.03, 95% CI 1.01, 1.04, P<0.01), blood glucose on admission ( OR=1.17, 95% CI 1.06, 1.30, P<0.01) and INR on admission ( OR=17.08, 95% CI 2.12, 137.89, P<0.01) could be used as the main risk factors to construct the prediction model, and the regression equation was constructed: Logit [ P/(1- P)]=-0.398× "GCS on admission"+0.024× "age"+0.158×"blood glucose on admission"+2.838×"INR on admission"-1.693. The AUC for the prognosis prediction in adult patients with TBI using R based on a visual nomogram model was 0.87 (95% CI 0.83, 0.89, P<0.01). The Youden index for the predicted probability was 0.60 (sensitivity of 85.2% and specificity of 75.2%), with the C index of 0.87. Conclusion:Age, GCS on admission, blood glucose on admission and INR on admission are the main risk factors affecting the prognosis of TBI in adults, and the nomogram drawn by these parameters can better predict their clinical outcome.

The role of a simple Nomogram model in evaluating the severity of mycoplasma pneumonia pneumonia in adults / 中国基层医药

Objective:To investigate the role of a simple Nomogram model in evaluating the severity of mycoplasma pneumoniae pneumonia (MPP) in adults.Methods:The clinical data of 162 patients with MPP who received treatment in Wenzhou Central Hospital from March 2015 to October 2022 were retrospectively analyzed. These patients were divided into a severe group ( n = 67) and a common group ( n = 95) according to whether they were diagnosed with severe MPP. The clinical data of patients were recorded. Fourteen clinical variables were screened, including age, sex, onset season, fever, heat peak, fever duration, cough duration, white blood cell count, percentage of neutrophils, percentage of lymphocytes, hemoglobin, platelet count, C-reactive protein, and procalcitonin. Multivariate logistic regression analysis of statistically significant variables in univariate analysis was performed. The Nomogram model was constructed with the R language software package (version 3.6.2). The model was verified with a calibration curve and receiver operating characteristic curve. Results:Univariate analysis results showed that in the severe group, the fever peak ( Z = 5.03, P < 0.001) was higher, fever duration ( χ2 = 27.55, P < 0.001), and cough duration ( χ2 = 28.72, P < 0.001) were longer, white cell count ( t = 2.93, P = 0.004), percentage of neutrophils ( t = 9.08, P < 0.001), C-reactive protein ( t = 35.05, P < 0.001), and procalcitonin level ( t = 15.09, P < 0.001) were greater compared with the common group. The percentage of lymphocytes ( t = 1.16, P < 0.001), hemoglobin level ( t = 1.22, P < 0.001), and platelet count ( t = 2.82, P < 0.001) in the severe group were significantly lower than those in the common group. Multivariate logistic regression analysis results showed that heat peak, cough duration, and C-reactive protein were positively correlated with the severity of MPP (all P < 0.05). The percentage of lymphocytes, hemoglobin concentration, and platelet count were negatively correlated with the severity of MPP (all P < 0.05). The establishment and validation results of the Nomogram model showed that the accuracy of the model was good, with a sensitivity of 88.73%, a specificity of 77.61%, and a C-index of 0.904. Conclusion:Heat peak, cough duration, percentage of lymphocytes, platelet count, and C-reactive protein are closely related to the severity of early MPP. A simple Nomogram model can be one of the tools for early assessment of the severity of MPP.

Risk factors of moderate to severe pain in patients with non-small cell lung cancer within 3 days after lobectomy / 中国基层医药

Objective:To investigate the risk factors of moderate to severe pain in patients with non-small cell lung cancer within 3 days after lobectomy.Methods:The clinical data of 297 patients with non-small cell lung cancer who underwent lobectomy in the Department of Thoracic Surgery, Sun Yat-sen University Cancer Center from December 2020 to June 2021 were retrospectively analyzed. A numerical rating scale was used to score the most severe pain within 3 days after surgery. Pain score ≥ 4 was defined as moderate to severe pain. The risk factors for moderate to severe pain were analyzed by binary Logistic regression. General linear model repeated measures and linear mixed models were used to analyze the trend of risk factors influencing postoperative pain with time.Results:The incidence of moderate to severe pain was 34.2% (102/297), 59.8% (178/297), 66.4% (198/297), and 28.2% (84/297) on days 0, 1, 2, and 3 after surgery respectively. The risk for moderate to severe pain was significantly higher in patients undergoing thoracotomy than patients undergoing thoracoscopic surgery on days 1 ( OR = 1.99, P = 0.009), 2 ( OR = 3.08, P < 0.001), and 3 ( OR = 3.88, P < 0.001) after surgery. However, the risk for moderate to severe pain in patients undergoing thoracotomy was slightly, but not significantly, higher than that in patients undergoing thoracoscopic surgery ( OR = 1.53, P = 0.087). The risk for moderate to severe pain was higher in female patients than male patients on day 2 ( OR = 1.62, P = 0.077), and in particular on day 3 after surgery ( OR = 2.39, P = 0.002). Prophylactic use of parecoxib significantly reduced the risk of moderate to severe pain on day 0 ( OR = 0.32, P = 0.004), 1 ( OR = 0.20, P < 0.001), 2 ( OR = 0.36, P < 0.001) and 3 ( OR = 0.56, P = 0.047). Conclusion:The incidence of moderate to severe pain on days 1 and 2 after lobectomy was relatively high in patients with non-small cell lung cancer. Patients undergoing thoracotomy have a higher risk of moderate to severe pain than those who underwent thoracoscopic surgery. Female patients have a higher risk for moderate to severe pain on days 2 and 3 after surgery than male patients. Prophylactic use of parecoxib can decrease the risk for moderate to severe pain in patients with non-small cell lung cancer.

Factores asociados a casos de malaria y plantas medicinales empleadas para su tratamiento en habitantes de Corozal, Colombia / Factors associated with cases of malaria and medicinal plants used for its treatment in inhabitants of Corozal, Colombia

Introducción: La malaria es una de las enfermedades infecciosas más importantes y para tratarla además de medicamentos, la población emplea plantas medicinales. El objetivo fue establecer los factores asociados a malaria y las plantas empleadas para su tratamiento en habitantes de Corozal. Método: Se aplicó una encuesta con preguntas sociodemográficas, de la vivienda, de conocimiento y de actitudes y las plantas medicinales empleadas para tratarla. Resultados: El 48% emplean plantas medicinales solas o con medicamentos, siendo el Gliricidia sepium (matarratón) y el Acmella oppositifolia (yuyo) las plantas más empleadas. En el 48% de las casas ha habido malaria. Por regresión logística se estableció que la malaria se asoció con conocer cómo se adquiere, consultar al médico tradicional y tener más de 15 años en Corozal. Conclusiones: Las plantas que la población de este estudio reportan no muestran evidencia científica como antimalaricos. Es importante una mayor presencia de las autoridades de salud y su trabajo conjunto con el médico tradicional para lograr estrategias más efectivas(AU)

Introduction: Malaria is one of the most important infectious disease and to treat it in addition to medicines the population uses medicinal plants. The objective was to establish the factors associated with malaria and the plants used for its treatment in inhabitants of Corozal. Method: A survey was applied with sociodemographic questions about housing, knowledge and attitudes, in addition to the medicinal plants used to treat it. Results: 48% use medicinal plants alone or with medicines, Gliricidia sepium (rat poisson) and Acmella oppositifolia (Opposite-leaf Spotflower) are the most used. In 48% of the homes there has been malaria. By logistic regression it was established that malaria was associated with knowing how it is acquired, consulting the traditional doctor and living in Corozal for more than 15 years. Conclusions: The plants that the population of this study report usimg do not show scientific evidence antimalarials. A greater presence of health authorities and their joint work with the traditional doctor for more effective strategies is important(AU)

Modeling of covariates predicting renal allograft failure within six months after transplantation / Modelagem das covariáveis preditivas para falência do enxerto renal até seis meses do transplante

INTRODUCTION: Kidney transplantation (KT) is the renal replacement therapy (RRT) of choice for patients with chronic kidney disease (CKD). However, not every KT is successful and some patients persist on RRT. OBJECTIVE: To model a logistic regression with pre- and post-KT risk covariates capable of predicting secondary allograft dysfunction in need of RRT or reaching stage V of CKD until the first six months post-KT. METHODS: Cohort with KT recipients from Northeastern Brazil. Medical records of KT performed between 2011-2018 were analyzed. KT-recipients with insufficient data or who abandoned follow-up were excluded. The covariables analyzed were: demographic; infectious; pre- and post-KT comorbidities; panel reactive-antibodies; number of HLA mismatches; acute rejection episodes mediated by T-cell (ACR) or antibodies (AAR) six months after KT; and laboratory tests six months after KT. RESULTS: Covariates with higher risk for the analyzed outcomes six months after KT were: elderly KT recipients (OR:1.41; CI95%:1.01-1.99), time between onset of RRT and KT (ΔT-RRT&KT)>10years (OR:3.54; CI95%:1.27-9.87), diabetes mellitus (DM) pre-KT (OR:3.35; CI95%:1.51-7.46), pyelonephritis (OR:2.45; CI95%:1.24-4.84), polyomavirus nephropathy (OR:4.99; CI95%:1.87-13.3), AAS (OR:4.82; CI95%:1.35-17.2), 24h-proteinuria ≥300mg/24h (OR:5.05; CI95%:2.00-12.7) and serum calcium (Ca) <8.5mg/dL (OR:4.72; CI95%:2.00-11.1). The multivariate model presented an accuracy of 88.1% and the mean variance inflation factor is 1.81. CONCLUSION: Elderly-recipients, ΔT-RRT&KT>10 years, pre-KT DM, and post-KT aggressions until six months (pyelonephritis, polyomavirus nephropathy, ABMR, 24h-proteinuria≥300mg/24h, and Ca<8.5mg/dL) are associated with high predictive power for secondary allograft dysfunction in need of RRT or reaching CKD stage V until the first six months post-KT.

INTRODUÇÃO: Transplante renal (TR) é a terapia renal substitutiva (TRS) de escolha para pacientes com doença renal crônica (DRC). Entretanto, nem todo TR é bem-sucedido e alguns pacientes persistem em TRS. OBJETIVO: Modelar uma regressão logística com covariáveis de risco pré e pós-TR preditora da disfunção secundária do aloenxerto com necessidade de TRS ou alcance ao estágio V da DRC até os primeiros seis meses pós-TR. MÉTODOS: Coorte com receptores transplantados realizado em hospital no Nordeste brasileiro. Analisou-se registros médicos dos TR realizados entre 2011-2018. Receptores com dados insuficientes ou que abandonaram seguimento foram excluídos. Foram analisadas covariáveis: demográficas; infecciosas; comorbidades pré e pós-TR; painel de reatividade; incompatibilidades de HLA; episódios de rejeições agudas mediadas por células-T ou por anticorpos; exames laboratoriais seis meses pós-TR. RESULTADOS: Receptores idosos (OR:1,41; IC95%:1,01-1,99), tempo entre início da TRS e TR (∆T-TRS&TR)>10 anos (OR:3,54; IC95%:1,27-9,87), diabetes mellitus (DM) pré-TR (OR:3,35; IC95%:1,51-7,46), pielonefrite (OR:2,45; IC95%:1,24-4,84), nefropatia por poliomavírus (OR:4,99; IC95%:1,87-13,3), RAMA (OR:4,82; IC95%:1,35-17,2), proteinúria de 24h (Pt24h) ≥300mg/24h (OR:5,05; IC95%:2,00-12,7) e cálcio sérico (Ca)<8,5mg/dL (OR:4,72; IC95%:2,00-11,1) foram identificadas como covariáveis de maior risco para os desfechos analisados até seis meses pós-TR. O modelo multivariado apresentou acurácia de 88,1% e fator de inflação da variância médio de 1,81. CONCLUSÃO: Receptores idosos, ∆T-TRS&TR>10anos, DM pré-TR e agressões até seis meses pós-TR (pielonefrite, nefropatia por poliomavírus, RAMA, Pt24h≥300mg/24h e Ca<8,5mg/dL), apresentam alto poder preditivo para disfunção secundária do aloenxerto com necessidade de TRS ou alcance ao estágio V da DRC até os primeiros seis meses pós-TR.

Factores de adherencia al tratamiento de hipertensión arterial en servicios de primer nivel de atención / Adherence factors to hypertension treatment in primary care services

Introducción: La enfermedad arterial hipertensiva no controlada (EAHNC), se asoció en 2008 con alta mortalidad por enfermedad cardiovascular que genera 9,4 millones de fallecimientos y 7% de la carga de enfermedad expresada en Años de Vida Ajustados por Discapacidad (AVAD). Un 50% de los pacientes no se adhieren al tratamiento EAH y se desconoce sobre las causas en el nivel básico de atención en Colombia. Objetivo: Identificar factores asociados con la adherencia al tratamiento de EAH en una Empresa Social del Estado (E.S.E), pública de un municipio colombiano. Materiales y métodos: Estudio de casos y controles, 75 casos y 75 controles seleccionados aleatoriamente a partir de una base de pacientes del programa de control de hipertensión arterial. Resultados: La edad mayor a 50 años fue el único factor asociado con falta de adherencia al tratamiento, sujetos entre 50-59 años con un OR=3,18 (Intervalo al 95% de confianza) IC95% 1,01-10,00; y entre 60-69 años OR=3,70 IC95% 1,17-11,60 tienen mayor probabilidad de no adherirse al tratamiento. Conclusiones: Los mayores de 50 a 69 años de edad presentaron la más alta probabilidad de no adherencia al tratamiento de la EAH. Se requieren reforzar medidas de seguimiento para mejorar su adherencia al tratamiento.

Introduction: In 2008, uncontrolled hypertensive arterial disease (UHAD) was associated with a high cardiovascular mortality that caused 9.4 million deaths and 7% of the disease burden expressed as Disability-Adjusted Life Years (DALYs). The reasons why 50% of the patients treated in primary care facilities in Colombia do not adhere to UHAD treatment are unknown. Objective: To identify factors associated with UHAD treatment adherence in a Public Health Care institution from a Colombian city. Materials and methods: A case-control study with 75 cases and 75 controls randomly selected from a patient database of the arterial hypertension control program. Results: Being older than 50 years was the only factor associated with lack of adherence to treatment. Participants who were 50-59 (OR=3.18; IC95% 1.01-10.00) and 60-69 (OR=3.70; IC95% 1.17-11.60) are less likely to adhere to treatment. Conclusions: Patients who are 50-69 years old had the highest probability of non-adherence to UHAD treatment. Follow-up measures are necessary to improve this figure.

Development and validation of predictive model for long-term hospitalization, readmission, and in-hospital death of patients over 60 years old

ABSTRACT Objective To develop and validate a high-risk predictive model that identifies, at least, one common adverse event in older population: early readmission (up to 30 days after discharge), long hospital stays (10 days or more) or in-hospital deaths. Methods This was a retrospective cohort study including patients aged 60 years or older (n=340) admitted at a 630-beds tertiary hospital, located in the city of São Paulo, Brazil. A predictive model of high-risk indication was developed by analyzing logistical regression models. This model prognostic capacity was assessed by measuring accuracy, sensitivity, specificity, and positive and negative predictive values. Areas under the receiver operating characteristic curve with 95% confidence intervals were also obtained to assess the discriminatory power of the model. Internal validation of the prognostic model was performed in a separate sample (n=168). Results Statistically significant predictors were identified, such as current Barthel Index, number of medications in use, presence of diabetes mellitus, difficulty chewing or swallowing, extensive surgery, and dementia. The study observed discrimination model acceptance in the construction sample 0.77 (95% confidence interval: 0.71-0.83) and good calibration. The characteristics of the validation samples were similar, and the receiver operating characteristic curve area was 0.687 (95% confidence interval: 0.598-0.776). We could assess an older patient's adverse health events during hospitalization after admission. Conclusion A predictive model with acceptable discrimination was obtained, with satisfactory results for early readmission (30 days), long hospital stays (10 days), or in-hospital death.

Inteligência artificial e previsão de óbito por Covid-19 no Brasil: uma análise comparativa entre os algoritmos Logistic Regression, Decision Tree e Random Forest / Artificial intelligence and forecasting of death by COVID-19 in Brazil: A comparative analysis of the algorithms Logistic Regression, Decision Tree, and Random Forest

RESUMO Este trabalho fez uso da inteligência artificial para contribuir com evidências empíricas que auxiliem na previsão de morte por Covid-19, possibilitando a melhoria de protocolos de saúde utilizados em sistemas de saúde no Brasil e dotando a sociedade com mais ferramentas de combate a essa doença. Utilizaram-se dados de janeiro a setembro de 2021 para o Brasil com o objetivo de prever morte por Covid-19, tomando por base o quadro clínico de pacientes que utilizaram o Sistema Único de Saúde no período estudado. Três algoritmos de classificação foram experimentados: Logistic Regression (LR), Decision Tree (DT) e Random Forest (RF). Os modelos LR, DT e RF tiveram uma acurácia média de, respectivamente, 76%, 76% e 77% na previsão de morte. Além disso, foi possível inferir que, quando o paciente chega a um ponto que necessita do uso de suporte ventilatório e de Unidade de Terapia Intensiva, somado à idade, sua chance de ir a óbito por Covid-19 é maior.

ABSTRACT This work makes use of artificial intelligence to contribute with empirical evidence that help predict death by COVID-19, enabling the improvement of health protocols used in health systems in Brazil and providing society with more tools to combat COVID-19. Data from January to September 2021 for Brazil are used in order to predict death by COVID-19 based on the clinical status of patients who used the Unified Health System in the studied period, in which three classification algorithms were tried: Logistic Regression (LR), Decision Tree (DT), and Random Forest (RF). The LR, DT, and RF models had a mean accuracy of 76%, 76%, and 77% in predicting death, respectively. In addition, it was possible to infer that when patients reach a point that require the use of ventilatory support and ICU, added to age, their chance of dying of COVID-19 is greater.

Adverse outcomes of hypertensive disorders of pregnancy: development and validation of a predictive model / 中华围产医学杂志

Objective:To develop and validate a predictive model for adverse outcomes in women with hypertensive disorders of pregnancy (HDP).Methods:We retrospectively analyzed the clinical data of patients diagnosed with HDP and delivered at the First Affiliated Hospital of Soochow University or Sichuan Provincial Maternity and Child Health Care Hospital between May 1, 2011, and April 30, 2019. These patients were categorized as the adverse outcome group or the control group with adverse outcomes within 48 h after admission. Univariate analysis, least absolute shrinkage, selection operator (LASSO), and multivariable logistic regression were employed to analyze factors influencing the adverse outcomes and develop a predictive model. The receiver operating characteristic (ROC) curve and calibration plot was used to assess the predictive performance. Bootstrapping was used for the internal validation and the retrospective dataset of patients with HDP from the First Affiliated Hospital of Soochow University from May 1, 2019, to April 30, 2020, for the external validation. A graphic nomogram was created through R software based on the model.Results:(1) Of the 2 978 HDP patients who were included in the development set, 356 were in the adverse outcome group, accounting for 12.0%; of the 233 patients who were included in the external validation set, 40 presented with adverse outcomes within 48 h after admission, accounting for 17.2%. (2) Nine optimal predictors were identified based on the LASSO regression analysis and multivariable logistic regression, consisting of gestational age on admission, routine prenatal care, number of symptoms, mean arterial pressure, platelet count, fibrinogen, albumin, serum urea, and serum creatinine, based on which the logistic predictive model was established. (3) The ROC curve for this predictive model achieved an area under the curve (AUC) of 0.878 (95% CI: 0.858-0.897), and the ideal cut-off value for predicted probability was 0.136, with a sensitivity of 0.778 (95% CI: 0.731-0.820) and specificity of 0.848(95% CI: 0.834-0.862). The model was well-calibrated as the Hosmer-Lemeshow test showed that P>0.05. The calibration plot of the model had a slope of 1 and an intercept of 0. (4) The model showed good consistency in the internal validation and had an AUC of 0.872 (95% CI: 0.807-0.937) in the external validation. The Hosmer-Lemeshow test showed that the P value was >0.05, and the calibration slope was 1.001. (5) A nomogram was constructed for convenient clinical use. Conclusion:A relatively accurate prediction model for adverse outcomes in HDP patients was established, which could be used as a valuable quantitative tool for assessing HDP-related complications.

Prognosis prediction of neonatal early-onset sepsis by constructing predictors based on logistic regression model / 中国医师杂志

Objective:A clinical prediction model was constructed based on the related factors affecting neonatal early-onset sepsis (EOS).Methods:A retrospective study was conducted. The patients with EOS amditted to the neonatal intensive care unit of Children′s Hospital Affiliated to Xi′an Jiaotong University from April 2015 to April 2020 were enrolled. The demographic data and the clinical indicators within 8 hours after admission were collected. The death 7 days after admission was taken as the end event. The differences of various indexes between the survival group and the death group were compared. After univariate analysis of the indexes that may have an impact on the prognosis, binary logistic regression analysis was performed; The predictive model was established for the factors that may affect the prognosis; the predictive value of the relevant models was analyzed by recevier operating characteristic (ROC) curve, and the model was verified by independent clinical medical records.Results:A total of 139 children were enrolled, and 41 died within 7 days, with a fatality rate of 29.50%. Compared with the survival group, the dead group had higher white blood cells (WBC), serum procalcitonin (PCT), lactic acid (Lac), creatinine (Scr), D-dimer and Paediatric Risk of Mortality (PRISM) score {WBC(×10 9/L): 24.15[4.36, 29.36] vs 21.21[19.14, 28.36], PCT: (67.32±40.36)ng/L vs (37.76±25.11)ng/L, Lac: (8.69±6.17)mmol/L vs (2.34±1.11)mmol/L, Scr: (239.99±68.46)μmol/L vs (65.31±34.34)μmol/L, D-dimer(mg/L): 5.21[2.06, 21.49] vs 0.34[0.26, 0.45], PRISM Ⅲ: (19.52±6.25)s vs (10.63±2.05)s, all P<0.05}, and lower fibrinogen (Fib), platelet count (PLT) and hemoglobin concentration (Hb) [Fib: (1.48±1.19)g/L vs (2.44±0.83)g/L, PLT: (154±58)×10 9/L vs (189±29)×10 9/L, Hb: (169±49)g/L vs (182±52)g/L, all P<0.05]. The incidence of placental/umbilical cord lesions, amniotic fluid pollution, asphyxia, premature delivery, premature rupture of membranes, positive etiology and maternal infection in the death group were higher than those in the survival group, while the gestational age and weight were lower than those in the survival group (all P<0.05); Binary logistic regression analysis showed that Lac, PCT and premature rupture of membranes were independent risk factors for the prognosis of EOS [odds ratio ( OR) and 95% confidence interval (95% CI): Lac was 1.23(1.00-2.05), PCT was 1.05(1.03-1.85), premature rupture of membranes was 2.59(1.89-3.32), all P<0.05]; ROC curve analysis showed that the area under the curve (AUC) of the prediction model was 0.967; the predicted sensitivity was 88.70%; and the specificity was 78.20% respectively. Conclusions:PCT, Lac and premature rupture of membranes are independent risk factors affecting the prognosis of EOS. The clinical prognosis prediction model constructed by combining PLT, gestational age and weight has good prediction efficiency.

Clinical value of common laboratory indexes in evaluating infarct size of ischemic stroke / 中国医师杂志

Objective:To explore the level changes of common laboratory indexes in patients with ischemic stroke (IS) with different infarct sizes and their clinical application value.Methods:The baseline data of 237 patients hospitalized in Lanzhou University Second Hospital from June 2019 to December 2020 and their laboratory indicators within 24 hours of admission were collected. The patients were divided into lacunar group ( n=80) and infarct group ( n=157) according to the infarct area. The experimental indexes and clinical data of the two groups were compared. Binary logistic regression was used to screen the independent influencing factors of infarct size and establish a joint diagnostic model. The receiver operating characteristic (ROC) curve and model calibration chart were used to verify the clinical application value of each index. Results:The levels of cholesterol (CHO)/high density lipoprotein (HDL), low density lipoprotein (LDL)/HDL, neutrophil count, Cystatin C (Cys C), phosphorus (PHOS), indirect bilirubin (IBIL), LDL, apolipoprotein (ApoB), homocysteine (HCY), D-dimer, smoking, drinking, overweight and arterial stenosis in the infarct group were higher than those in the lacunar group (all P<0.05), and the levels of apolipoprotein A Ⅰ (ApoAⅠ)/ApoB, ApoAⅠ and carbon dioxide (CO 2) in the infarct group were lower than those in the lacunar group (all P<0.05). ApoA Ⅰ/ApoB and CO 2 were independent protective factors of infarct size (all P<0.05); Cys C, PHOS and IBIL were independent risk factors of infarct size (all P<0.05). The combined prediction model of CO 2, PHOS, IBIL, ApoA Ⅰ/ApoB and Cys C has good prediction efficiency for infarct area, and the area under the curve (AUC) of combined diagnosis was 0.739. Conclusions:Laboratory indicators are closely related to the infarct size of IS. The model developed in this study have good clinical value, which provides a new basis for IS evaluation and early warning.