Rentabilidad de la ratio angiogénica en el seguimiento de gestantes de alto riesgo de preeclampsia precoz tratadas con ácido acetilsalicílico / Profitability of the angiogenic ratio in the follow-up of pregnant women at high risk of early preeclampsia treated with acetylsalicylic acid

Objetivo: Evaluar el valor predictivo negativo de la ratio antigénica y conocer su rentabilidad para descartar preeclampsia precoz en pacientes de alto riesgo de desarrollarla, con profilaxis de ácido acetilsalicílico. Métodos: Se realizó un estudio descriptivo transversal que recogió a las gestantes con cribado de preeclampsia precoz de alto riesgo (384 gestantes) en el Hospital Santa Lucía durante el año 2021, para lo que se usó test Elecsys® tabulado a un riesgo mayor a 1/150 en primer trimestre, y que tomaran ácido acetilsalicílico antes de la semana 16, quedando en 368 gestantes vistas en las semanas 20, 26, 31 y 36. Se realizó biometría, ratio angiogénica y doppler. Resultados: La incidencia de preeclampsia precoz en la población fue 4 casos (incidencia 1,08 %). Son significativos por su alto valor predictivo negativo del 100 % de preeclampsia precoz: la ratio angiogénica mayor a 38 en la semana 26 y el doppler de las uterinas en semana 20 y 26. Conclusión: En gestaciones con cribado de alto riesgo de preeclampsia que tomen ácido acetilsalicílico, una ratio angiogénica menor a 38 en la semana 26, además de un doppler uterino normal en semana 20 y 26 permite reducir el seguimiento gestacional(AU)

Objective: Our main objective was to evaluate the negative predictive value of the angiogenic ratio and to know its profitability to rule out early preeclampsia in patients at high risk of early preeclampsia with acetylsalicylic acid prophylaxis. Methods: A cross-sectional descriptive study was carried out that included pregnant women with high-risk early preeclampsia screening (384 pregnant women) at the Santa Lucía Hospital during the year 2021, for which the Elecsys® test tabulated at a risk >1/ was used. 150 in the first trimester, and who take acetylsalicylic acid before week 16, leaving 368 pregnant women seen in weeks 20, 26, 31 and 36, with biometry, angiogenic ratio and Doppler performed. Results: The incidence of early preeclampsia in the population was 4 cases (incidence 1.08%). They are significant due to their high negative predictive value of 100% of early preeclampsia: Angiogenic ratio > 38 in week 26, uterine Doppler in weeks 20 and 26. Conclusion: Pregnancies with high risk screening for preeclampsia who take acid acetylsalicylic acid, an angiogenic ratio < 38 at week 26 in addition to a normal uterine Doppler at weeks 20 and 26 allows for reduced gestational follow-up(AU)

Behind the Headset: Predictive Accuracy of Patient-Reported Outcome Measures for Voice Symptoms in Call Centers

Objective: This study examines factors predicting self-reported voice symptoms in call center workers. Methods: Multivariate analysis and predictive modeling assess personal, work-related, acoustic, and behavioral factors. Generalized Linear Models (GLMs) and Receiver Operating Characteristic (ROC) curves are employed. Results: Age and sleep patterns impacted voice quality and effort, while workplace factors influenced symptom perception. Unhealthy vocal behaviors related to tense voice and increased effort, while hydration was protective. Voice acoustics showed diagnostic potential, supported by ROC data. These findings emphasize voice symptom complexity in call center professionals, necessitating comprehensive assessment. Limitations: This study recognizes its limitations, including a moderate-sized convenience sample and reliance on PROM metrics. Future research should incorporate more objective measures in addition to self-reports and acoustic analysis. Value: This research provides novel insights into the interplay of personal, occupational, and voice-related factors in developing voice symptoms among call center workers. Predictive modeling enhances risk assessment and understanding of individual susceptibility to voice disorders. Conclusion: Results show associations between various factors and self-reported voice symptoms. Protective factors include sleeping more than six hours and consistent hydration, whereas risk factors include working conditions, such as location and behaviors like smoking. Diagnostic models indicate good accuracy for some voice symptom PROMs, emphasizing the need for comprehensive models considering work factors, vocal behaviors, and acoustic parameters to understand voice issues complexity.

Objetivo: Este estudio examina los factores que predicen los síntomas de voz en los trabajadores de call centers. Métodos: Se utilizan análisis multivariados y modelos predictivos para evaluar factores personales, laborales, acústicos y de comportamiento. Se emplean Modelos Lineales Generalizados (GLM) y curvas ROC. Resultados: La edad y los patrones de sueño afectaron la calidad vocal y el esfuerzo, mientras que los factores laborales influyeron en la percepción de síntomas. Los comportamientos vocales no saludables se relacionaron con voz tensa y mayor esfuerzo, mientras que la hidratación fue protectora. Los parámetros acústicos de voz mostraron potencial diagnóstico respaldado por datos de ROC. Los hallazgos subrayan complejidad de síntomas vocales en profesionales de centros de llamadas, requiriendo una evaluación integral. Limitaciones: Este estudio reconoce sus limitaciones, que incluyen una muestra de conveniencia de tamaño moderado y la dependencia de medidas PROMs. Futuras investigaciones deberían incorporar medidas objetivas, además de los autorreportes y análisis acústico. Importancia: Esta investigación aporta nuevos conocimientos sobre factores personales, laborales y síntomas de voz en trabajadores de call centers. El modelado predictivo mejora la evaluación de riesgos y la comprensión de la susceptibilidad individual a trastornos de la voz. Conclusión: Los resultados muestran asociaciones entre diversos factores y los síntomas vocales reportados. Los factores de protección incluyen dormir más de seis horas y una hidratación constante; los factores de riesgo incluyen las condiciones de trabajo, como la ubicación y comportamientos como fumar. Los modelos de diagnóstico indican una buena precisión para algunas PROMs de síntomas de la voz, lo que subraya la necesidad de modelos integrales que tengan en cuenta los factores laborales, los comportamientos vocales y los parámetros acústicos para comprender la complejidad de los problemas de la voz.

Resting Energy Expenditure, comparison of predictive formulas with bioimpedance: Peruvian population / Gasto Energético en Reposo, comparación de fórmulas predictivas con la bioimpedancia: población peruana

Introduction: In areas with limited access to healthcare systems, Resting Energy Expenditure (REE) estimation is performed using predictive equations to calculate an individual's caloric requirement. One problem is that these equations were validated in populations with different characteristics from those in Latin America, such as race, height, or body mass, leading to potential errors in the prediction of this parameter. Objective: To determine the REE using predictive formulas compared with bioimpedance in Peruvians. Materials and methods: A comparative analytical cross-sectional study with secondary database analysis of the CRONICAS cohort. Results: we worked with a total of 666 subjects. The Mjeor equation was the one with the highest rating of 0.95, a lower mean absolute percentage error (MAPE) of 4.69%, and equivalence was found with the REE values. In the multiple regression, it was observed that the Mjeor equation was the one that least overestimated the REE, increasing 0.77 Kcal/day (95% CI: 0.769-0.814; p<0.001) for each point that increased the REE determined by bioimpedance. The strength of association between Mjeor and bioimpedance was 0.9037. Furthermore, in the regression of the data (weight, height, age) in the Mjeor equation it was observed that the coefficients obtained were the same as those used in the original equation. Conclusions: The Mjeor equation seems to be the most adequate to estimate the REE in the Peruvian population. Future prospective studies should confirm the usefulness of this formula with potential utility in primary health care(AU)

Introducción: En zonas con acceso limitado a sistemas de salud, la estimación del Gasto Energético en Reposo (GER) se realiza utilizando ecuaciones predictivas para calcular el requerimiento calórico de un individuo. Uno de los problemas es que estas ecuaciones fueron validadas en poblaciones con características diferentes a las latinoamericanas, como raza, talla o masa corporal, lo que conlleva a potenciales errores en la predicción de este parámetro. Objetivo: Determinar el GER mediante fórmulas predictivas comparadas con la bioimpedancia en peruanos. Materiales y métodos: Estudio transversal analítico comparativo con análisis secundario de base de datos de la cohorte CRONICAS. Resultados: Se trabajó con un total de 666 sujetos. La ecuación de Mjeor fue la que obtuvo la puntuación más alta de 0,95, un error medio porcentual absoluto (MAPE) inferior de 4,69%, y se encontró equivalencia con los valores del GER. En la regresión múltiple, se observó que la ecuación de Mjeor fue la que menos sobreestimó el GER, aumentando 0,77 Kcal/día (IC 95%: 0,769-0,814; p<0,001) por cada punto que aumentaba el GER determinado por bioimpedancia. La fuerza de asociación entre Mjeor y bioimpedancia fue de 0,9037. Además, en la regresión de los datos (peso, talla, edad) de la ecuación de Mjeor se observó que los coeficientes obtenidos eran los mismos que los utilizados en la ecuación original. Conclusiones: La ecuación de Mjeor parece ser la más adecuada para estimar el GER en la población peruana. Futuros estudios prospectivos deberán confirmar la utilidad de esta fórmula para su potencial utilidad en la atención primaria de salud(AU)

Development and validation of a clinical prediction model for prognostic factors in patients with primary pontine hemorrhage

Abstract We aimed to develop a prognostic model for primary pontine hemorrhage (PPH) patients and validate the predictive value of the model for a good prognosis at 90 days. A total of 254 PPH patients were included for screening of the independent predictors of prognosis, and data were analyzed by univariate and multivariable logistic regression tests. The cases were then divided into training cohort (n=219) and validation cohort (n=35) based on the two centers. A nomogram was developed using independent predictors from the training cohort to predict the 90-day good outcome and was validated from the validation cohort. Glasgow Coma Scale score, normalized pixels (used to describe bleeding volume), and mechanical ventilation were significant predictors of a good outcome of PPH at 90 days in the training cohort (all P<0.05). The U test showed no statistical difference (P=0.892) between the training cohort and the validation cohort, suggesting the model fitted well. The new model showed good discrimination (area under the curve=0.833). The decision curve analysis of the nomogram of the training cohort indicated a great net benefit. The PPH nomogram comprising the Glasgow Coma Scale score, normalized pixels, and mechanical ventilation may facilitate predicting a 90-day good outcome.

Variáveis Clínicas e Laboratoriais na Admissão Hospitalar são Preditores de Fibrilação Atrial Nova em Pacientes Internados com Pneumonia por COVID-19 / Clinical and Laboratory Data Up on Hospital Admission are Predictors of New-Onset Atrial Fibrillation in Patients Hospitalized Due to COVID-19 Pneumonia

Resumo Fundamento Fibrilação atrial nova (FAN) ocorre em pacientes internados por COVID-19. Há controvérsias quanto ao valor preditivo de dados clínicos e laboratoriais à admissão hospitalar para ocorrência de FAN. Objetivos Analisar, à admissão hospitalar, variáveis com potencial preditivo para ocorrência de FAN em pacientes com pneumonia por COVID-19. Método Estudo observacional, retrospectivo, caso-controle. Foram avaliados prontuários eletrônicos de pacientes consecutivos ≥ 60 anos, hospitalizados com pneumonia por COVID-19 entre 1º de março e 15 de julho de 2020. Comparações feitas pelos testes `t' de Student ou qui-quadrado. Foi empregado modelo de risco proporcional de Cox para identificação de preditores de FAN. Considerou-se o valor de p < 0,05 como estatisticamente significativo. Resultados Entre 667 pacientes internados por COVID-19, 201 (30,1%) foram incluídos. FAN foi documentada em 29 pacientes (14,4%) (grupo 1). Grupo 2 foi composto por 162 pacientes que não apresentaram FAN. Dez pacientes excluídos por estarem em FA na admissão hospitalar. Houve diferenças entre os grupos 1 e 2, respectivamente, no tempo de permanência em UTI (11,1±10,5 dias vs. 4,9±7,5 dias; p=0,004), necessidade de ventilação invasiva (82,9% e 32,7%; p<0,001) e mortalidade hospitalar (75,9% vs. 32,1%; p<0,001). No modelo de Cox, idade > 71 anos (hazard ratio [HR]=6,8; p<0,001), leucometria ≤ 7.720 cels.μL-1 (HR=6,6; p<0,001), natremia ≤ 137 mEq.L-1 (HR=5,0; p=0,001), escore SAPS3 > 55 (HR=5,6; p=0,002) e desorientação (HR=2,5; p=0,04) foram preditores independentes de FAN. Conclusões FAN é uma arritmia comum em idosos hospitalizados com pneumonia por COVID-19. Parâmetros clínicos e laboratoriais avaliados na admissão são preditores de FAN durante internação.

Abstract Background New-onset atrial fibrillation (NOAF) occurs in patients hospitalized due to COVID-19. It is still unknown whether clinical and laboratory data assessed upon hospital admission have predictive value for NOAF. Objectives To analyze, upon hospital admission, variables with predictive potential for the occurrence of NOAF in patients with COVID-19 pneumonia. Methods Observational, retrospective, case-control study. Electronic medical reports of consecutive patients, 60 years of age or older, hospitalized due to COVID-19 pneumonia between March 1st and July 15th, 2020, were reviewed. Non-paired Student or chi-squared tests compared variables. A Cox proportional hazard model was employed to identify independent predictors of NOAF. P value < 0.05 was considered statistically significant. Results Among 667 patients hospitalized due to COVID-19, 201 (30.1%) fulfilled the inclusion criteria. NOAF was documented in 29 patients (14.4%), composing group 1. Group 2 was composed of 162 patients without NOAF. Ten patients were excluded due to the AF rhythm upon hospital admission. In groups 1 and 2, there were differences in overall in-hospital survival rate (24.1 % vs. 67.9%; p<0.001), length of stay in ICU (11.1 ± 10.5 days vs. 4.9 ± 7.5 days; p=0.004) and need for mechanical ventilation rate (82.9% vs. 32.7%; p<0.001). In the Cox model, age > 71 y/o (HR=6.8; p<0.001), total leukocyte count ≤ 7,720 cels.μL-¹ (HR=6.6; p<0.001), serum [Na+] ≤ 137 mEq.L-¹ (HR=5.0; p=0.001), SAPS3 score > 55 (HR=5.6; p=0.002), and disorientation (HR=2.5; p=0.04) on admission were independent predictors of NOAF. Conclusion NOAF is a common arrhythmia in elderly hospitalized patients with COVID-19 pneumonia. Clinical and laboratory parameters evaluated on admission have a predictive value for the occurrence of NOAF during hospitalization.

Factors affecting the clinical decision-making expectations of patients undergoing digestive endoscopy / 中国基层医药

Objective:To investigate the influential factors of patients' expectations for clinical decision-making during digestive endoscopy.Methods:A total of 120 patients who underwent digestive endoscopy were admitted to the Endoscopy Center of Zhejiang Provincial People's Hospital from January 2020 to January 2022. Their general information was collected, and their clinical decision-making expectations were evaluated using the Control Preference Scale (CPS). The influential factors of clinical decision-making expectations were determined using multiple linear regression analysis.Results:The total CPS score for 120 patients undergoing digestive endoscopy was (50.72 ± 5.48) points, including (14.12 ± 1.48) points for information needs, (25.17 ± 3.52) points for communication needs, and (11.43 ± 2.04) points for decision-making needs. Univariate analysis showed that the CPS score of patients undergoing digestive endoscopy was related to gender, age, marital status, educational level, number of children, and type of visit ( t = 2.68, 2.61, 2.82, 3.28, 3.61, 2.39, all P < 0.05). Multiple linear regression analysis showed that gender, age, educational level, and type of visit were the influential factors of clinical decision-making expectations for patients undergoing digestive endoscopy ( β = -0.71, 1.07, 0.53, -1.15, all P < 0.05). Conclusion:Gender, age, educational level, and type of visit are influential factors of patients' expectations for clinical decision-making during digestive endoscopy. Patients have a clear need for communication during clinical decision-making, and medical staff can strengthen communication with patients, correctly guiding them to participate in clinical decision-making expectations.

Analysis of risk factors for prolonged postoperative hospital stay in patients after spinal tuberculosis lesion removal and fusion with internal fixation and development of a predictive model / 中国脊柱脊髓杂志

Objectives:To explore the risk factors related to the prolonged postoperative length of hospital stay(LOS)in patients after spinal tuberculosis lesion removal and fusion with internal fixation,and to construct a nomogram prediction model,so as to provide a theoretical basis for the enhanced recovery management of spinal tuberculosis patients.Methods:The clinical data of 142 patients with spinal tuberculosis who underwent lesion removal and fusion with internal fixation in the Department of Orthopedics of the Affiliated Hospital of Zunyi Medical University between December 2018 and June 2023 were retrospectively analyzed.The patients were randomly divided into modeling group(n=96)and validation group(n=46)in a 2∶1 ratio.Setting the postoperative LOS＞21d as the outcome variable for prolonged LOS,and taking age,gender,alcohol history,smoking history,hypertension,coronary heart disease,diabetes,anemia,postoperative hypoproteinemia,spinal cord injury,tuberculosis in other parts,bone destruction,blood transfusion,removal time of drainage,postoperative complications,operative time,blood loss,preoperative American Society of Anesthesiologists(ASA)score,postoperative ASA score,surgical incision length,pus formation,chemotherapy before surgery,and chemotherapy regimens as independent variables to develop univariate logistic regression model.The risk factors screened after univariate analysis were included for multivariate logistic regression model to determine the independent risk factors for LOS＞21d after lesion removal and fusion with internal fixation in patients with spinal tuberculosis and to construct a predictive model for risk factors.The area under the curve(AUC)of receiver operating characteristics(ROC)curve was used to assess the the differentiation of the model;Calibration curve was used to assess the calibration situation of the model;Decision curve analysis(DCA)was used to assess the clinical value and influence of the model on actual decision-making process.Data of validation group was applied to draw ROC curve and calibration curve for external verification.Results:Univariate and multivariate analyses revealed that age(OR=1.040,95%CI:1.011-1.069),tuberculosis at other sites(OR=2.867,95%CI:1.157-7.106),and preoperative ASA score(OR=1.543,95%CI:1.015-2.347)were the independent risk factors for prolonged postoperative hospitalization in patients with spinal tuberculosis after lesion removal and fusion with internal fixation.The AUC of ROC curves of modeling group and validation group were 0.767(95%CI:0.671-0.863)and 0.720(95%CI:0.569-0.871),respectively,suggesting the predictive model had good predictive efficiency.The results of the calibration curve analysis demonstrated that the actual curve roughly resembled the ideal curve,and DCA curve revealed that the nomogram had superior clinical benefits.Conclusions:The spinal tuberculosis patients who are at older age,combined with other sites of tuberculosis,and with high preoperative ASA score are prone to prolonged LOS after lesion removal and fusion with internal fixation,and the risk prediction nomogram model developed accordingly has great predictive efficiency.

Development of a prediction model of surgical site infection after posterior lumbar interbody fusion in patients based on random forest algorithm / 中国脊柱脊髓杂志

Objectives:To analyze the risk factors related to infection after posterior lumbar interbody fusion(PLIF)by random forest algorithm and develop a prediction model,providing a certain reference for clinical prevention of surgical site infection(SSI)after PLIF.Methods:A retrospective study was conducted on the masked data of patients hospitalized for PLIF in the spinal surgery department of some third-level grade A hospitals in Beijing municipality and Hebei Province from June 2019 to June 2021 provided by Beijing Zhongwei Cloud Medical Data Analysis and Application Technology Research Institute through data processing and analysis.The classification data were analyzed and compared between SSI group and non-SSI group to obtain variables that significantly impacted the postoperative infection.SPSS Modeler 20 system was used as the tool for model development,and random forest algorithm was applied to analyze,obtaining the patient characteristics of postoperative infection,namely the infection model.Results:A total of 8,764 patients were included in study,and 373 patients were diagnosed with SSI,with an incidence rate of 4.4％(95％CI:2.2％to 6.5％).After statistical analysis,six variables,including obesity,ASA Ⅲ and above,prolonged operative time,chronic heart disease,diabetes and renal dysfunction,were independently associated with SSI.Classification with a random forest model yielded a high accuracy of 90.6％.The characteristics of patients prone to infection after PLIF(two models of infection)was:[(BMI=1)and(SD=1)and(ASA=1)and(RI=1)]or[(BMI=0)and(SD=1)and(DM=1)and(RI=1)].Conclusions:The random forest algorithm applied in this study could obtain an average accuracy of 90.6％,and two infection models were obtained as:(1)Patients with obesity,renal insufficiency,ASA grade Ⅲ or above,and operative time≥3h;(2)Patients who are not obese,but with diabetes,renal insufficiency,and the operative time ≥3h.

Construction of prediction model of severe acute pancreatitis based on serum soluble T cell immunogloblulin and mucin domain-containing protein 3 / 中华危重病急救医学

Objective:To investigate the predictive value of the model based on soluble T cell immunogloblulin and mucin domain-containing protein 3 (sTIM3) for the progression of severe acute pancreatitis (SAP) in patients with acute pancreatitis (AP).Methods:A retrospective cohort study was conducted. The AP patients admitted to Changzhou First People's Hospital and Changzhou Second People's Hospital from June 1, 2020 to June 30, 2022 were enrolled. Mild AP (MAP) and moderately severe AP (MSAP) patients were classified as non-SAP group, and SAP patients were classified as SAP group according to the progression of AP patients during hospitalization. The basic data, blood biological indicators, serum sTIM3 level, bedside index for severity in acute pancreatitis (BISAP), acute physiology and chronic health evaluation Ⅱ (APACHE Ⅱ) score, modified computed tomography severity index (MCTSI) score within 48 hours of admission, and prognosis indicators were collected. Multivariate Logistic regression analysis was conducted to analyze the risk factors of the progression of SAP in patients with AP during hospitalization. Based on the results of multivariate analysis and the best parameters selected based on the minimal Akaike information criterion (AIC), the SAP prediction model based on sTIM3 was constructed. The receive operator characteristic curve (ROC curve) was plotted to analyze the predictive efficacy of the model.Results:A total of 99 AP patients were enrolled, 80 patients in the non-SAP group and 19 patients in the SAP group. Compared with the non-SAP group, body mass index (BMI), drinking history ratio, heart rate (HR), respiration rate (RR), white blood cell count (WBC), red blood cell count (RBC), C-reactive protein (CRP), alanine aminotransferase (ALT), serum creatinine (SCr), procalcitonin (PCT), interleukin-6 (IL-6), sTIM3, BISAP score, APACHEⅡ score and MCTSI score were significantly increased, and pulse oxygen saturation (SpO 2), direct bilirubin (DBil) and IL-10 were significantly decreased. The length of intensive care unit (ICU) stay and total length of hospital stay of patients in the SAP group were significantly longer than those in the non-SAP group [length of ICU stay (days): 1.0 (0, 1.5) vs. 0 (0, 0), total length of hospital stay (days): 17.11±9.39 vs. 8.40±3.08, both P < 0.01]. Multivariate Logistic regression analysis showed that HR [odds ratio ( OR) = 1.059, 95% confidence interval (95% CI) was 1.010-1.110, P = 0.017], DBil ( OR = 0.981, 95% CI was 0.950-0.997, P = 0.043), and sTIM3 ( OR = 1.002, 95% CI was 1.001-1.003, P = 0.027) were independent risk factors for predicting the progression of SAP in patients with AP, and the SAP prediction model based on sTIM3 was constructed: Logit( P) = -14.602+0.187×BMI+0.057×HR+0.006×CRP-0.020×DBil+0.002×sTIM3. ROC curve analysis showed that among the aforementioned single factor quantitative indicators, IL-6 was the most effective in predicting the progression of AP patients to SAP during hospitalization, but the predictive performance of prediction model based on the sTIM3 was significantly better than IL-6 [area under the ROC curve (AUC) and 95% CI: 0.957 (0.913-1.000) vs. 0.902 (0.845-0.958), P < 0.05]. Conclusion:The model based on serum sTIM3 demonstrated good predictive value for the progression of SAP in patients with AP.

Predictive value of von Willebrand factor for venous thromboembolism in critically ill patients based on propensity score matching / 中华危重病急救医学

Objective:To analyze the predictive value of von Willebrand factor (vWF) for venous thromboembolism (VTE) of patients in intensive care unit (ICU) by using propensity score matching (PSM).Methods:Patients admitted to ICU of the Second Affiliated Hospital of Kunming Medical University from December 2020 to June 2022 who stayed in ICU for ≥72 hours and underwent daily bedside vascular ultrasound screening were included. Baseline data such as age, gender, primary disease, and chronic comorbidities were collected. Coagulation indexes before admission to ICU and 24 hours and 48 hours after ICU admission were collected, including prothrombin time (PT), activated partial thromboplastin time (APTT), thrombin time (TT), international normalized ratio (INR), fibrinogen (Fib), fibrin monomer (FM), vWF, D-dimer, antithrombin Ⅲ (ATⅢ), etc. Patients were divided into VTE group and non-VTE group according to whether they had VTE or not [diagnosis of VTE: patients underwent daily ultrasound screening of bedside blood vessels (both upper and lower limbs, visceral veins), and those suspected of having thrombosis were confirmed by ultrasonographer or pulmonary angiography]. Using PSM analysis method, the VTE group was used as the benchmark to conduct 1 : 1 matching of age, whether there was malignant tumor, whether there was infection, whether there was diabetes, and coagulation indicators before admission to ICU. Finally, the cases with balanced covariates between the two groups were obtained. The risk factors of VTE were analyzed by multivariate Logistic regression analysis. Receiver operator characteristic curve (ROC curve) was drawn to evaluate the predictive value of vWF in the occurrence of VTE in critically ill patients.Results:A total of 120 patients were enrolled, of which 18 (15.0%) were diagnosed with VTE within 72 hours after admission to ICU, and 102 (85.0%) were not found to have thrombus in ICU. Before PSM, there were significant differences in age, gender, proportion of malignant tumor and infection, and coagulation indexes between VTE group and non-VTE group. After PSM, 14 pairs were successfully matched, and the unbalanced covariables between the two groups reached equilibrium. Multivariate Logistic regression analysis showed that vWF was an independent risk factor for VTE at 48 hours after ICU admission in critically ill patients [odds ratio ( OR) = 1.165, 95% confidence interval (95% CI) was 1.000-1.025, P = 0.004]. ROC curve analysis showed that the area under the ROC curve (AUC) of vWF at 48 hours after ICU admission for predicting VTE was 0.782, 95% CI was 0.618-0.945, P = 0.007. When the optimal cut-off value was 312.12%, the sensitivity was 67.7% and the specificity was 93.0%. Conclusion:Dynamic monitoring of vWF is helpful to predict the occurrence of VTE in ICU patients, and vWF at 48 hours after ICU admission has certain value in predicting the occurrence of VTE.

Analysis of latent classes and predictive factors of health behavior among stroke patients / 中华行为医学与脑科学杂志

Objective:To explore the latent classes of health behavior and explore the predictive factors among stroke patients.Methods:A total of 1 250 participants were recruited using cluster random sampling in September 2022. The general information, the modified Rankin scale(mRS), stroke prevention knowledge questionnaire(SPKQ), health behavior scale for stroke patients (HBS-SP), and short form-health belief model scale (SF-HBMS) were administered in the cross-sectional survey. Mplus 8.3 software was used to conduct a latent class analysis (LCA) on the health behavior of stroke patients, and SPSS 27.0 software was used to carry out multinomial Logistic regression to analyze the predictive factors of different latent classes of health behavior of stroke patients.Results:The health behavior of stroke patients obtained three latent classes: low health behaviors-lack of health responsibility group (66.9%, n=794), moderate health behaviors-poor compliance group (11.9%, n=141), and good health behaviors-insufficient exercise group (21.2%, n=251). Compared with good health behaviors-insufficient exercise group, stroke patients with shorter duration education time ( B=-0.589, OR=0.555, P=0.036), hemorrhagic stroke ( B=0.082, OR=1.086, P<0.001), fewer comorbidities ( B=-0.022, OR=0.978, P=0.026), higher mRS score ( B=-0.046, OR=1.047, P=0.004), lower SPKQ score ( B=-0.055, OR=0.947, P=0.016), and lower SF-HBMS score ( B=-0.085, OR=0.919, P<0.001) were more likely to be included in moderate health behaviors-poor compliance group. However, stroke patients with shorter duration education time ( B=-0.026, OR=0.974, P=0.003), rural areas dwelling ( B=0.800, OR=2.225, P=0.004), fewer comorbidities ( B=-0.056, OR=0.945, P<0.001), lower SPKQ score ( B=-0.101, OR=0.904, P<0.001), and lower SF-HBMS score ( B=-0.071, OR=0.931, P<0.001) were more likely to be included in low health behaviors-lack of health responsibility group. Conclusion:The health behavior of stroke patients has three latent classes. A targeted intervention should be carried out according to the characteristics of different classes to improve their health behavior levels.

Analysis of influencing factors and prediction models of vancomycin AUC0-24h in postoperative orthopedic patients / 中国药师

Objective To investigate the influencing factors of vancomycin in the area under curve for 24 h(AUC0-24h)in patients after orthopedic surgery,and to predictive and analyze a good pharmacokinetic model for AUC0-24h Methods Patients who underwent orthopedic surgery and used vancomycin in The Sixth Affiliated Hospital of Xinjiang Medical University from January 2018 to December 2022 were included,and the basic information,the medication,the blood and biochemical indexes of the patients were collected to analyze the factors affecting postoperative vancomycin AUC0-24h in orthopedic surgery.The AUC0-24h was calculated using the first-level pharmacokinetic formula,the JavaPK? for Desktop(JPKD)and the vancomycin daily dose elimination rate formula.Results 91 patients were finally included,and the cystatin C(OR=189.168,P=0.005)and the single dose(OR=19.160,P＜0.001)were independent protective factors for vancomycin AUC0 24 h in postoperative orthopedic patients,and the retinol binding protein was an independent risk factor for vancomycin AUC0-24h(OR=0.910,P＜0.05).By predicting and analyzing the model of vancomycin AUC0 24h in postoperative orthopedic patients,the absolute percentage error of both JPKD software and vancomycin daily dose elimination rate formula were lower than 30％.The intraclass correlation efficient between the AUC0 24h of the JPKD software and vancomycin daily dose elimination rate formula,and the AUC0 24h of the first-level pharmacokinetic formula were 0.781 and 0.524,respectively.Conclusion Cystatin C is an important factor influencing vancomycin AUC0-24h in postoperative orthopedic patients,and JPKD software is more suitable for predicting vancomycin AUC0-24h after orthopedic surgery than the vancomycin daily dose elimination rate formula method.

Establishment of machine learning-based risk prediction model for acute kidney injury in acute myocardial infarction patients and compared with traditional model / 中华肾脏病杂志

Objective:To establish a predictive risk model for acute kidney injury (AKI) in acute myocardial infarction (AMI) patients based on machine learning algorithm and compare with a traditional logistic regression model.Methods:It was a retrospective study. The demographic data, laboratory examination, treatment regimen and medication of AMI patients from July 2011 to December 2016 in Beijing Anzhen Hospital, Capital Medical University were collected. The diagnostic criteria of AKI were based on the AKI diagnosis and treatment guidelines published by Kidney Diseases: Improving Global Outcomes in 2012. The selected AMI patients were randomly divided into training set (70%) and internal test set (30%) by simple random sampling. SelectFromModel and Lasso regression models were used to extract clinical parameters as predictors of AKI in AMI patients. Logistic regression model (model A) and machine learning algorithm (model B) were used to establish the risk prediction model of AKI in AMI patients. DeLong method was used to compare the area under the receiver-operating characteristic (ROC) curve ( AUC) between model A and model B for selecting the best model. Results:A total of 6 014 AMI patients were included in the study, with age of (58.4±11.7) years old and 3 414 males (80.5%). There were 674 patients (11.2%) with AKI. There were 4 252 patients (70.7%) in the training set and 1 762 patients (29.3%) in the test set. The selected twelve clinical parameters by the SelectFromModel and Lasso regression models included the number of myocardial infarctions, ST-segment elevation myocardial infarction, ventricular tachycardia, third degree atrioventricular block, decompensated heart failure at admission, admission serum creatinine, admission blood urea nitrogen, admission peak creatine kinase isoenzyme, diuretics, maximum daily dose of diuretics, days of diuretic use and statins. Logistic regression prediction model showed that AUC for the test set was 0.80 (95% CI 0.76-0.84). The machine learning algorithm model obtained AUC in the test set with 0.82 (95% CI 0.78-0.85).There was no significant difference in AUC between the two models ( Z=0.858, P=0.363), and AUC of the machine learning algorithm predictive model was slightly higher than that of the traditional logistic regression model. Conclusions:The prediction effect of AKI risk in AMI patients based on machine learning algorithm is similar to that of traditional logistic regression model, and the prediction accuracy of machine learning algorithm is better. The introduction of machine learning algorithm model may improve the ability to predict AKI risk.

Analysis of factors influencing the complication of dry eye after corneal transplantation and construction of nomogram predictive model / 国际眼科杂志(Guoji Yanke Zazhi)

AIM: To analyze the influencing factors of postoperative dry eye complication after corneal transplantation and to build a nomogram prediction model.METHODS: Clinical data were collected on 117 patients who underwent corneal transplantation at our hospital from March 2021 to February 2023. They were divided into dry eye group(n=96)and non-dry eye group(n=21)according to whether there was a postoperative dry eye. The risk factors of postoperative complication of dry eye after corneal transplantation were analyzed, the nomogram prediction model for predicting postoperative complication of dry eye after corneal transplantation was constructed, and the internal validation of the model and the prediction efficacy were assessed by calibration curves and decision curves, respectively.RESULTS: Comorbid diabetes mellitus, comorbid sleep disorders, comorbid meibomian gland dysfunction, chronic eye drop abuse, chronic corneal contact lens wear, interleukin-6(IL-6), and tumor necrosis factor-α(TNF-α)were the risk factors for the complication of dry eye after corneal transplantation(P&#x003C;0.05). The nomogram model predicted a C-index of 0.890(95% CI 0.877-0.903). The nomogram model had a threshold &#x003E;0.07, and the nomogram model provided higher net clinical benefit than the single index in all cases.CONCLUSION: The nomogram model built in this study based on the factors affecting the complication of dry eye after corneal transplantation has a good predictive value for the complication of dry eye after corneal transplantation.

Advances in the predictive application of abnormal early motor development in infants and toddlers / 中国儿童保健杂志

Despite a more significant improvement in survival rates of premature and high-risk infants, surviving infants face a high risk of developing neurodevelopmental disorders such as cerebral palsy.Infant development is characterized by a dynamic continum, which makes it difficult to classify a child′s level of motor development as normal or abnormal on the basis of a single examination.This article provides a review of advances in the application of the predictive validity of General Movement Assessment (GMA) and the Alberta Infant Motor Scale (AIMS) in the early assessment and follow-up of infants and toddlers, in order to intervene in a timely manner with young children at potential motor risk.

The application value and predictors of 18F-PSMA PET/CT on the metastatic lesions of prostate cancer with tPSA≤20 ng/mL / 现代泌尿外科杂志

【Objective】 To explore the application value of 18F-PSMA PET/CT on the detection of metastatic lesions of prostate cancer with serum total prostate specific antigen (tPSA) ≤20 ng/mL and the predictive variables affecting the imaging results, and to establish a predictive nomogram for the metastasis of prostate cancer. 【Methods】 The imaging, pathological, serum and clinical data of 175 pathologically confirmed prostate cancer patients who underwent 18F-PSMA PET/CT examination during Jan.2020 and Oct.2021 were retrospectively collected.The patients were divided into metastatic group and non-metastatic group according to PET/CT imaging results, and the positive detection rate of metastatic lesions was calculated.The independent influencing factors of 18F-PSMA PET/CT in the positive detection of metastatic lesions were determined with univariate and multivariate logistic regression analyses.The predictive nomogram was established. 【Results】 Of the 175 patients, metastatic lesions were detected in 78 cases and not detected in 97 cases, with a detection rate of 44.6% (78/175).There were statistically significant differences between the metastatic group and the non-metastatic group in urinary tract symptoms, androgen deprivation treatment (ADT) at the time of PET/CT examination and the risk level of Gleason score (GS) (P<0.05).Univariate logistic regression showed that urinary tract symptoms(OR=3.64, P<0.001), GS risk (OR=3.96, P<0.001) and concurrent ADT treatment (OR=3.71, P<0.001) were associated with the positive detection rate of metastatic lesions.Multivariate Logistic regression showed that urinary tract symptoms (OR=3.19, P=0.002), GS high-risk group (OR=2.95, P=0.005) and concurrent ADT treatment (OR=3.27, P=0.001) were independent predictors of positive detection rate. 【Conclusion】 The probability of metastasis in newly diagnosed prostate cancer patients with tPSA≤20 ng/mL is high.18F-PSMA PET/CT is of high value for the early detection of metastasis.Urinary tract symptoms, GS high-risk group and concurrent ADT treatment are independent predictors of metastatic lesions.The predictive nomogram can help assist clinical optimization of imaging examination path.

Construction and evaluation of predictive model for risk of postoperative fecal soiling in children with Hirschsprung's disease / 重庆医学

Objective To investigate the risk factors of postoperative fecal contamination in children pa-tients with Hirschsprung's disease(HSCR),and to construct and evaluate the risk predictive model.Methods The clinical data in 377 children patients with HSCR in 3 class 3A hospitals in Guangxi from Janu-ary 2016 to June 2021were retrospectively analyzed by adopting the convenience sampling method.The pa-tients were divided into the modeling group(n=264)and testing model group(n=113)with a ratio of 7∶3.The risk factors of postoperative fecal soiling were analyzed by the single factor and multiple factors,and the risk predictive model was constructed.The receiver operating characteristic(ROC)curve was used to detect the discriminative ability of the model and the H-L test was used to determine the goodness of fit of the mod-el.The model was prospectively validated in 21 children patients with HSCR from August to December 2021.Results Among 377 children patients with HSCR,the fecal soiling occurred in 131 cases with a incidence rate of 34.75％.The constructed predictive model of fecal contamination risk after HSCR operation:logit(P)=-2.385+1.697 × special type of megacolon+0.929 × Soave+0.105 × length of bowel resection+2.065 × il-literate caregivers+0.808 × caregivers'implementation of postoperative diet+0.867 × postoperative defecation training by caregivers.The area under the curve(AUC)in the modeling group was 0.849,the Yoden index was 0.53,the optimal critical value of the model was 0.32,the sensitivity was 76.00％,and the specificity was 77.00％.The H-L test,X2=6.649,P=0.575.AUC of the testing model group was 0.736,the sensitivity was 81.25％,and the specificity was 78.46％.The prospective validation results showed that the sensitivity and specificity of the model were 66.67％and 100％respectively.Conclusion The constructed model has good i-dentification and predictive ability.

Analysis of fertility intention to have a third child among childbearing age women in Wanzhou District of Chongqing Municipality and its influencing factors / 重庆医学

Objective To survey the current situation of fertility intention to have a third child among childbearing age women in Wanzhou District of Chongqing Municipality under the background of the new fer-tility policy,and to analyze its influencing factors.Methods The convenience sampling method was adopted to conduct the survey on the third child fertility intention by the self-designed questionnaire and the Question-naire Star platform among the childbearing women with one child or two children in Wanzhou District of Chongqing Municipality from September to October 2022.The multiple linear regression analysis and two-step cluster analysis were used to explore the influencing factors.Results A total of 632 questionnaires were re-ceived,32 invalid questionnaires were excluded,and the effective recovery rate was 94.9％.The score of fertili-ty intention to have a third child in the respondents was(12.81±2.83)points.The multiple linear regression analysis showed that the age,marital status,place of residence,spouse cultural degree,family rearing child model,whether the family can provide support and previous vaginal delivery history were the influencing fac-tors of fertility intention to have a third child among the childbearing age women in this place(P＜0.05).The two step cluster analysis showed that"obstetrician/midwife's help"was the most important predictive factor for the childbearing age women to choose to have a third child.Conclusion The current situation of childbear-ing age women's fertility intention to have a third child in Wanzhou District of Chongqing Municipality is not optimistic.It is necessary to create the positive factors that encourage childbearing age women to make deci-sion about having a third child.

Risk factors and predictive model of complicating urosepsis after percutaneous nephrolithotripsy / 重庆医学

Objective To explore the risk factors of complicating urogenic sepsis after percutaneous nephrolithotripsy(PCNL)and construct a nomogram prediction model.Methods The data of 291 patients with stage 1 PCNL in 940 Hospital of Joint Logistics Support Force from October 2016 to October 2021 were retrospectively analyzed.The patients were divided into the sepsis group and non-sepsis group according to whether complicating urogenic sepsis after operation.The general data,stone-related data,operation-related data and laboratory detection related data were included.The independent risk factors were screened by the univariate and multivariate logistic regression analysis,and the nomogram prediction model was constructed.Results The results of univariate and multivariate logistic regression analysis showed that age≥60 years old(OR=6.438,95％CI:1.548-26.769),urinary leukocyte 3+(OR=5.651,95％CI:1.614-31.766),urinary nitrite positive(OR=7.117,95％CI:1.190-42.561),operation time≥90 min(OR=4.626,95％CI:1.137-18.817)and perfusion volume 30 L(OR=3.312,95％CI:1.090-10.061)were the independent risk factors of postoperative complicating urogenic sepsis.C-index of the constructed nomogram prediction model in the modeling samples was 0.937,the calibrated C-index was 0.914,and the model predictive efficien-cy was good.Conclusion Age ≥60 years old,urinary leukocyte 3+,urinary nitrite positive,operation time 90 min and perfusion volume ≥30 L are the independent risk factors for complicating urogenic sepsis after PCNL;the constructed nomogram prediction model has a good predictive efficiency for the occurrence of post-operative urogenic sepsis.

Prediction and evaluation of nomogram model on risk of hyperuricemia in overweight and obese children and adolescents / 重庆医学

Objective To establish a nomogram prediction model of hyperuricemia(HUA)onset risk in overweight and obese children and adolescents in order to provide reference for the prevention and treatment of HUA in this population.Methods The clinical data of 1 410 overweight and obese children and adolescents aged 6-17 years old visiting in this hospital from September 2021 to August 2022 were retrospectively analyzed.A total of 987 overweight and obese children and adolescents were randomly extracted according to a ratio of 7:3 to establish the model,and the remaining 423 cases were validated internally.Referring to the definition of high uric acid in"Zhu-futang Practical Pediatrics",the subjects were divided into high uric acid group and non-high uric acid group.The logis-tic regression analysis was used to analyze the influencing factors of HUA in overweight and obese children and adoles-cents.The nomogram model was constructed by using the R language.The area under the receiver operating character-istic(ROC)curve(AUC),decision analysis curve(DIC),clinical impact curve(CIC)and C-index were used to evalu-ate the predictive ability of the model,and the Bootstrap repeated sampling method(taking samples for 1000 times)was used for internal validation of the model.Results The results of multivariate analysis showed that the age(OR=2.324,95％CI:1.155-4.672,P=0.018),gender(OR=0.456,95％CI:0.256-0.810,P=0.007),triglycerides(OR=3.775,95％CI:2.321-6.138,P＜0.001),blood calcium(OR=26.986,95％CI:3.186-228.589,P=0.003)and blood creatinine(OR=1.047,95％CI:1.026-1.070,P＜0.001)were the influen-cing factors of HUA in overweight and obese children and adolescents.AUC of the ROC curve of the model was 0.840,the sensitivity was 0.786,the specificity was 0.762,the Youden index was 0.548,and the C-index was 0.840.The risk probability of DC A was 0.1-0.8,the net benefit rate of both models was＞0,AUC of ROC curve in the internal verification was 0.871.Conclusion The constructed nomogram in this study has a good predictive efficiency for the onset risk of HUA in overweight and obese children and adolescents,and may provide reference for the early diagnosis and treatment of this population.