Forest yield prediction under different climate change scenarios using data intelligent models in Pakistan / Previsão de produção florestal em diferentes cenários de mudanças climáticas usando modelos inteligentes de dados no Paquistão

Abstract This study aimed to develop and evaluate data driven models for prediction of forest yield under different climate change scenarios in the Gallies forest division of district Abbottabad, Pakistan. The Random Forest (RF) and Kernel Ridge Regression (KRR) models were developed and evaluated using yield data of two species (Blue pine and Silver fir) as an objective variable and climate data (temperature, humidity, rainfall and wind speed) as predictive variables. Prediction accuracy of both the models were assessed by means of root mean squared error (RMSE), mean absolute error (MAE), correlation coefficient (r), relative root mean squared error (RRMSE), Legates-McCabe's (LM), Willmott's index (WI) and Nash-Sutcliffe (NSE) metrics. Overall, the RF model outperformed the KRR model due to its higher accuracy in forecasting of forest yield. The study strongly recommends that RF model should be applied in other regions of the country for prediction of forest growth and yield, which may help in the management and future planning of forest productivity in Pakistan.

Resumo Este estudo teve como objetivo desenvolver e avaliar modelos baseados em dados para previsão da produção florestal em diferentes cenários de mudanças climáticas na divisão florestal Gallies do distrito de Abbottabad, Paquistão. Os modelos Random Forest (RF) e Kernel Ridge Regression (KRR) foram desenvolvidos e avaliados usando dados de produção de duas espécies (pinheiro-azul e abeto-prateado) como uma variável objetiva e dados climáticos (temperatura, umidade, precipitação e velocidade do vento) como preditivos variáveis. A precisão da previsão de ambos os modelos foi avaliada por meio de erro quadrático médio (RMSE), erro absoluto médio (MAE), coeficiente de correlação (r), erro quadrático médio relativo (RRMSE), Legates-McCabe's (LM), índice de Willmott (WI) e métricas Nash-Sutcliffe (NSE). No geral, o modelo RF superou o modelo KRR devido à sua maior precisão na previsão do rendimento florestal. O estudo recomenda fortemente que o modelo RF seja aplicado em outras regiões do país para previsão do crescimento e produtividade florestal, o que pode ajudar no manejo e planejamento futuro da produtividade florestal no Paquistão.

Prediction of visceral leishmaniasis incidence using the Seasonal Autoregressive Integrated Moving Average model (SARIMA) in the state of Maranhão, Brazil / Previsão da incidência da leishmaniose visceral usando o modelo de média móvel integrado autorregressivo sazonal (SARIMA) no Maranhão, Brasil

Abstract Visceral leishmaniasis (VL) is an infectious disease predominant in countries located in the tropics. The prediction of occurrence of infectious diseases through epidemiologic modeling has revealed to be an important tool in the understanding of its occurrence dynamic. The objective of this study was to develop a forecasting model for the incidence of VL in Maranhão using the Seasonal Autoregressive Integrated Moving Average model (SARIMA). We collected monthly data regarding VL cases from the National Disease Notification System (SINAN) corresponding to the period between 2001 and 2018. The Box-Jenkins method was applied in order to adjust a SARIMA prediction model for VL general incidence and by sex (male or female) for the period between January 2019 and December 2013. For 216 months of this time series, 10,431 cases of VL were notified in Maranhão, with an average of 579 cases per year. With regard to age range, there was a higher incidence among the pediatric public (0 to 14 years of age). There was a predominance in male cases, 6437 (61.71%). The Box-Pierce test figures for overall, male and female genders supported by the results of the Ljung-Box test suggest that the autocorrelations of residual values act as white noise. Regarding monthly occurrences in general and by gender, the SARIMA models (2,0,0) (2,0,0), (0,1,1) (0,1,1) and (0,1,1) (2, 0, 0) were the ones that mostly adjusted to the data respectively. The model SARIMA has proven to be an adequate tool for predicting and analyzing the trends in VL incidence in Maranhão. The time variation determination and its prediction are decisive in providing guidance in health measure intervention.

Resumo A leishmaniose visceral (LV) é uma doença de natureza infecciosa, predominante em países de zonas tropicais. A predição de ocorrência de doenças infecciosas através da modelagem epidemiológica tem se revelado uma importante ferramenta no entendimento de sua dinâmica de ocorrência. O objetivo deste estudo foi desenvolver um modelo de previsão da incidência da LV no Maranhão usando o modelo de Média Móvel Integrada Autocorrelacionada Sazonal (SARIMA). Foram coletados os dados mensais de casos de LV através do Sistema de Informação de Agravos de Notificação (SINAN) correspondentes ao período de 2001 a 2018. O método de Box-Jenkins foi aplicado para ajustar um modelo de predição SARIMA para incidência geral e por sexo (masculino e feminino) de LV para o período de janeiro de 2019 a dezembro de 2023. Durante o período de 216 meses dessa série temporal, foram registrados 10.431 casos de LV no Maranhão, com uma média de 579 casos por ano. Em relação à faixa etária, houve maior registro no público pediátrico (0 a 14 anos). Houve predominância do sexo masculino, com 6437 casos (61,71%). Os valores do teste de Box-Pierce para incidência geral, sexo masculino e feminino reforçados pelos resultados do teste Ljung-Box sugerem que as autocorrelações de resíduos apresentam um comportamento de ruído branco. Para incidência mensal geral e por sexo masculino e feminino, os modelos SARIMA (2,0,0) (2,0,0), (0,1,1) (0,1,1) e (0,1,1) (2, 0, 0) foram os que mais se ajustaram aos dados, respectivamente. O modelo SARIMA se mostrou uma ferramenta adequada de previsão e análise da tendência de incidência da LV no Maranhão. A determinação da variação temporal e sua predição são determinantes no norteamento de medidas de intervenção em saúde.

A disease predictive model based on epidemiological factors for the management of bacterial leaf blight of rice / Um modelo preditivo de doenças baseado em fatores epidemiológicos para o manejo da queima bacteriana das folhas do arroz

Rice is a widely consumed staple food for a large part of the world's human population. Approximately 90% of the world's rice is grown in Asian continent and constitutes a staple food for 2.7 billion people worldwide. Bacterial leaf blight (BLB) caused by Xanthomonas oryzae pv. oryzae is one of the devastating diseases of rice. A field experiment was conducted during the year 2016 and 2017 to investigate the influence of different meteorological parameters on BLB development as well as the computation of a predictive model to forecast the disease well ahead of its appearance in the field. The seasonal dataset of disease incidence and environmental factors was used to assess five rice varieties/ cultivars (Basmati-2000, KSK-434, KSK-133, Super Basmati, and IRRI-9). The accumulated effect of two year environmental data; maximum and minimum temperature, relative humidity, wind speed, and rainfall, was studied and correlated with disease incidence. Average temperature (maximum & minimum) showed a negative significant correlation with BLB disease and all other variables; relative humidity, rainfall, and wind speed had a positive correlation with BLB disease development on individual varieties. Stepwise regression analysis was performed to indicate potentially useful predictor variables and to rule out incompetent parameters. Environmental data from the growing seasons of July to October 2016 and 2017 revealed that, with the exception of the lowest temperature, all environmental factors contributed to disease development throughout the cropping season. A disease prediction multiple regression model was developed based on two-year data (Y = 214.3-3.691 Max T-0.508 Min T + 0.767 RH + 2.521 RF + 5.740 WS), which explained 95% variability. This disease prediction model will not only help farmers in early detection and timely management of bacterial leaf blight disease of rice but may also help reduce input costs and improve product quality and quantity. The model will be both farmer and environmentally friendly.

O arroz é um alimento básico amplamente consumido por grande parte da população humana mundial. Aproximadamente 90% do arroz do mundo é cultivado no continente asiático e constitui um alimento básico para 2,7 bilhões de pessoas em todo o mundo. O crestamento bacteriano das folhas (BLB) causado por Xanthomonas oryzae pv. oryzae é uma das doenças devastadoras do arroz. Um experimento de campo foi realizado durante os anos de 2016 e 2017 para investigar a influência de diferentes parâmetros meteorológicos no desenvolvimento do BLB, bem como o cálculo de um modelo preditivo para prever a doença bem antes de seu aparecimento em campo. O conjunto de dados sazonais de incidência de doenças e fatores ambientais foi usado para avaliar cinco variedades/cultivares de arroz (Basmati-2000, KSK-434, KSK-133, Super Basmati e IRRI-9). O efeito acumulado de dados ambientais de dois anos; temperatura máxima e mínima, umidade relativa do ar, velocidade do vento e precipitação pluviométrica foram estudados e correlacionados com a incidência da doença. A temperatura média (máxima e mínima) apresentou correlação significativa negativa com a doença BLB e todas as outras variáveis; umidade relativa, precipitação e velocidade do vento tiveram uma correlação positiva com o desenvolvimento da doença BLB em variedades individuais. A análise de regressão stepwise foi realizada para indicar variáveis preditoras potencialmente úteis e para descartar parâmetros incompetentes. Os dados ambientais das safras de julho a outubro de 2016 e 2017 revelaram que, com exceção da temperatura mais baixa, todos os fatores ambientais contribuíram para o desenvolvimento da doença ao longo da safra. Um modelo de regressão múltipla de previsão de doença foi desenvolvido com base em dados de dois anos (Y = 214,3-3,691 Max T-0,508 Min T + 0,767 RH + 2,521 RF + 5,740 WS), que explicou 95% de variabilidade. Este modelo de previsão de doenças não só ajudará os agricultores na detecção precoce e gestão atempada da doença bacteriana das folhas do arroz, mas também pode ajudar a reduzir os custos de insumos e melhorar a qualidade e a quantidade do produto. O modelo será agricultor e ambientalmente amigável.

Drug-induced Sleep Endoscopy: Are there Predictors for Failure of Oral Appliance Treatment?

Abstract Introduction In the literature, evidence is lacking on the predictive value of druginduced sleep endoscopy (DISE) for oral appliance treatment (OAT). Objectives The aim of the present study is to evaluate whether DISE with concomitant mandibular advancement maneuver can predict failure of OAT. Methods An observational retrospective study including patients diagnosed with obstructive sleep apnea (OSA) who previously received OAT. Results of DISE were analyzed in a group with documented OAT failure (apnea-hypopnea index [AHI] >10 events/hour or < 50% reduction) and a group with OAT benefit (AHI <10 events/hour or >50% reduction). The upper airway was assessed using the velum, oropharynx, tongue base, epiglottis (VOTE) classification. Additionally, a mandibular advancement maneuver, manually protruding the mandible by performing a jaw thrust, was performed to mimic the effect of OAT. Results The present study included 50 patients with OAT failure and 20 patients with OAT benefit. A subgroup analysis of patients with OAT failure and an AHI <30events/hour included 26 patients. In the OAT failure group, 74% had a negative jaw thrust maneuver. In the subgroup with an AHI <30 events/hour, 76.9% had a negative jaw thrust maneuver. In the OAT benefit group, 25% had a negative jaw thrust maneuver (p< 0.001). Conclusions A negative jaw thrust maneuver during DISE can be a valuable predictor for OAT failure, independent of AHI. Drug-induced sleep endoscopy should be considered as a diagnostic evaluation tool before starting OAT.

Estado del Arte de la Predicción de Variables en Sistemas de Ingeniería Eléctrica Basada en Inteligencia Artificial

Resumen Existe una gran cantidad de sistemas que se estudian y desarrollan en el campo de la Ingeniería Eléctrica en los que se realizan análisis que tienen como uno de sus fines principales la predicción de sus variables, tanto para procesos de planificación como de toma de decisiones. Con el advenimiento de la Inteligencia Artificial, se ha observado cómo distintas técnicas relacionadas con el aprendizaje automático y la optimización se han incorporado a estas tareas de predicción, con las cuales se obtienen generalmente mejores resultados en los valores estimados que aquellos generados a partir de técnicas más tradicionales. La presente investigación tiene como objetivo realizar una revisión de lo publicado sobre predicciones de variables en sistemas de Ingeniería Eléctrica en las bases de datos EBSCO, SciELO, RedAlyc, Springer Link, IEEE Xplorer, y Google Académico, a partir de una delimitación temporal y de palabras clave del área. A partir del análisis de la literatura se obtuvo la tendencia sobre el tema a partir de los años más productivos, áreas de impacto e idiomas más frecuentes. Se observó que los estudios desarrollados han crecido en años recientes, y que las áreas de mayor impacto, de acuerdo con el número de publicaciones y de citas son la predicción del consumo y producción de energía eléctrica, y las variables relacionadas con energías renovables.

Abstract In many systems that are studied and developed in the field of Electrical Engineering, analyzes are carried out that have as one of their main purposes the prediction of their variables, both for planning and decision-making processes. With the advent of Artificial Intelligence, it has been observed how different techniques related to machine learning and optimization have been incorporated into these prediction tasks. Those new techniques generally obtained better results in the estimation of values ​​than those generated from more traditional techniques. The objective of this research is to review what has been published on predictions of variables in Electrical Engineering systems in the databases EBSCO, SciELO, RedAlyc, Springer Link, IEEE Xplorer, and Google Scholar, given specific temporal and keyworks delimitations for the area. From the analysis of the literature, the trend on the subject was obtained from the most productive years, areas of impact, and most frequent languages. It was observed that the studies developed have grown in recent years and that the areas of greatest impact, according to the number of publications and citations, are the prediction of electricity consumption and production, and the variables related to renewable energy.

Utilidad del modelo 5MPB-Toledo para predecir bacteriemia en el paciente anciano / Usefulness of the 5MPB-Toledo model to predict bacteremia in the elderly patient

Resumen Objetivo: Analizar la utilidad del modelo predictivo de bacteriemia (5MPB-Toledo) en los mayores de 65 años atendidos por infección en el servicio de urgencias (SU). Material y Método: Estudio observacional prospectivo y multicéntrico de los hemocultivos (HC) obtenidos en pacientes mayores de 65 años atendidos por infección en 66 SU españoles desde el 1 de diciembre de 2019 hasta el 30 de abril de 2020. Se analizó la capacidad predictiva del modelo con el área bajo la curva (ABC) de la característica operativa del receptor (COR) y se calculó el rendimiento diagnóstico de los puntos de corte (PC) del modelo elegido con los cálculos de la sensibilidad, la especificidad, el valor predictivo positivo y el valor predictivo negativo. Resultados: Se incluyeron 2.401 episodios de HC extraídos. De ellos, se consideró como bacteriemia verdadera a 579 (24,11%) y como HC negativo a 1.822 (75,89%). Entre los negativos, 138 (5,74%) se consideraron contaminados. Se categorizó a los pacientes en bajo (0-2 puntos), moderado (3-5 puntos) y alto (6-8 puntos) riesgo, con una probabilidad de bacteriemia de 1,2%, 18,1% y 80,7%, respectivamente. El ABC-COR del modelo tras remuestreo fue de 0,908 (IC 95%: 0,897-0,924). El rendimiento diagnóstico del modelo, considerando un PC ≥ 5 puntos, obtiene una sensibilidad de 94% (IC 95%:92-96), especificidad de 77% (IC 95%:76-79) y un valor predictivo negativo de 97% (IC 95%:96-98). Conclusión: El modelo 5MPB-Toledo es de utilidad para predecir bacteriemia en los mayores de 65 años atendidos en el SU por un episodio de infección.

Abstract Objective: To analyse a risk score to predict bacteremia (MPB5-Toledo) in the patients aged older 65 years seen in the emergency departments (ED) due to infections. Patients and Methods: Prospective and multicenter observational cohort study of the blood cultures (BC) ordered in 66 Spanish ED for patients aged older 65 years seen from December 1, 2019, to April 30, 2020. The predictive ability of the model was analyzed with the area under the Receiver Operating Characteristic curve (AUC-ROC). The prognostic performance for true bacteremia was calculated with the cut-off values chosen for getting the sensitivity, specificity, positive predictive value and negative predictive value. Results: A total of 2.401 blood samples wered cultured. True cases of bacteremia were confirmed in 579 (24.11%). The remaining 1.822 cultures (75.89%) wered negative. And, 138 (5.74%) were judged to be contaminated. Low risk for bacteremia was indicated by a score of 0 to 2 points, intermediate risk by 3 to 5 points, and high risk by 6 to 8 points. Bacteremia in these 3 risk groups was predicted for 1.2%, 18.1%, and 80.7%, respectively. The model´s area under the receiver ope rating characteristic curve was 0.908 (95% CI, 0.897-0.924). The prognostic performance with a model´s cut-off value of ≥ 5 points achieved 94% (95% CI: 92-96) sensitivity, 77% (95% CI: 76-79) specificity, and negative predictive value of 97% (95% CI: 96-98). Conclusion: The 5MPB-Toledo score is useful for predicting bacteremia in the patients aged older 65 years seen in the emergency departments due to infections.

The Role of High Concentrations of Homocysteine for the Development of Fetal Growth Restriction / O papel de altas concentrações de homocisteína para o desenvolvimento da restrição de crescimento fetal

Abstract Objective To assess homocysteine (Hcy) levels in the three trimesters of pregnancy in women with fetal growth restriction (FGR) and to evaluate the role of Hcy as a possible predictor of FGR. Methods A total of 315 singleton pregnant women were included in the present prospective cohort study and were monitored since the 1st trimester of pregnancy before delivery. Newborns were monitored for the first 7 days of life. Patients who had risk factors for FGR were excluded. Fetal growth restriction was defined according to uterine fundal height (< 10 percentile), ultrasound fetometry (< 5 percentile), and anthropometry of newborns (<5 percentile). The concentrations of Hcy were detected at between 10 and 14, between 20 and 24, and between 30 and 34 weeks of pregnancy by enzyme-linked immunosorbent assay (ELISA). Receiver operating characteristics (ROC) curve test and diagnostic odds ratio (DOR) were performed to evaluate the results of ELISA. Results The concentration of Hcy in patients with FGR was 19.65 umol/L at between 10 and 14 weeks, compared with 9.28 umol/L in patients with normal fetal growth (p<0.0001). The optimal cut-off level for Hcy in the 1st trimester of pregnancy was>13.9 umol/L with AUC 0.788, sensitivity of 75%, specificity of 83.6%, and DOR of 15.2. Conclusion Assessment of serum Hcy concentration may be used as a predictor of FGR, with the highest diagnostic utility in the 1st trimester of pregnancy.

Resumo Objetivo Avaliar os níveis de homocisteína (Hcy) em três trimestres da gravidez em mulheres com restrição de crescimento fetal (FGR, na sigla em inglês) e avaliar o papel da Hcy como possível preditor de FGR. Métodos Um total de 315 gestantes solteiras foram incluídas no presente estudo de coorte prospectivo e monitoradas desde o 1° trimestre de gravidez antes do parto. Os recém-nascidos foram acompanhados durante os primeiros 7 dias de vida. Pacientes que apresentam fatores de risco para FGR foram excluídos. A FGR foi definida de acordo com a altura do fundo do útero (< percentil 10), ultrassonografia fetometria (< percentil 5) e antropometria dos recém-nascidos (< percentil 5). As concentrações de Hcy foram detectadas entre 10 e 14, entre 20 e 24 e entre 30 e 34 semanas de gravidez por ensaio de imunoabsorção enzimática (ELISA, na sigla em inglês). O teste da curva das características de operação do receptor (ROC, na sigla em inglês) e a razão de chances de diagnóstico (DOR, na sigla em inglês) foram realizados para avaliar os resultados do ELISA. Resultados A concentração de Hcy em pacientes com FGR foi de 19,65 umol/L entre 10 e 14 semanas, em comparação com 9,28 umol/L em pacientes com crescimento fetal normal (p<0,0001). O nível de corte ideal para Hcy no 1° trimestre da gravidez foi>13,9 umol/L com AUC 0,788, sensibilidade de 75%, especificidade de 83,6%, e DOR 15,2. Conclusão A avaliação da concentração sérica de Hcy pode ser usada como um preditor de FGR, com maior utilidade diagnóstica no 1° trimestre de gravidez.

Umbral del ciclo de amplificación del gen de la toxina B de Clostridioides difficile como predictor de gravedad / Clostridioides difficile toxin B gen amplification cycle threshold as a predictor of severity

INTRODUCCIÓN: La infección por Clostridioides dfficile (ICD) es la principal causa de diarrea nosocomial, generalmente asociada al consumo de antimicrobianos. Esta infección puede causar desde diarrea no complicada hasta colitis pseudomembranosa o megacolon tóxico. Estudios recientes han intentado relacionar el valor el ciclo umbral (Ct) de la RT-PCR con la mortalidad, como un método rápido, sencillo, objetivo y eficaz. OBJETIVO: Evaluar el Ct como predictor de mala evolución en pacientes con y sin criterio clínico de dicha gravedad. PACIENTES Y MÉTODOS: Realizamos un estudio retrospectivo entre enero 2015 y diciembre 2018, incluyendo todos los pacientes del área de referencia del Hospital Universitario de Canarias en Tenerife (396.483 habitantes) en pacientes con criterios clínicos de gravedad (de acuerdo a la Guía para la Práctica Clínica de la enfermedad por C. dfficile de la Sociedad de Epidemiología del Cuidado de la Salud de América (SHEA) y la Sociedad de Enfermedades Infecciosas de Norteamérica (IDSA) y pacientes sin criterios clínicos de gravedad evaluando el Ct como predictor de mala evolución. RESULTADOS: Se diagnosticó un total de 202 episodios de ICD. El 77,7% (n = 157) presentó criterios clínicos de gravedad. La presencia de colitis ulcerosa (p < 0,001), fiebre (p < 0,001), leucocitosis (p < 0,001), neutrofilia (p < 0,001), creatininemia (p = 0,005) se presentaron como factores de riesgo para el desarrollo de ICD grave. El sexo femenino, la institucionalización, el ingreso previo y el exitus se describieron con mayor frecuencia en el grupo con ICD-G, no encontrando diferencias significativas. No encontramos diferencias respecto a los días de estancia previa, o de estancia post-ICD, aunque en este último, la media fue mayor en el caso de los pacientes con ICD-G. No se encontraron diferencias significativas en cuanto al Ct en ambos grupos; siendo sólo un punto menor en pacientes con criterio de gravedad (Ct = 26,1) que sin criterios de gravedad (Ct = 27,4) (p = 0,326).

BACKGROUND: Clostridioides dfficile infection (CDI) is the main cause of nosocomial diarrhea, generally associated with the use of antibiotics. This infection can cause uncomplicated diarrhea to pseudomembranous colitis or toxic megacolon. Recent studies have attempted to relate the threshold cycle (Ct) value of RT-PCR with mortality, as a fast, simple, objective and efficient method. AIM: To evaluate Ct as a predictor of poor outcome in patients with C. dfficile disease with/without clinical signs of severity. METHODS: We carried out a retrospective study between January 2015 and December 2018, including all patients in the reference area of the Hospital Universitario de Canarias in Tenerife (396,483 inhabitants) in patients with clinical criteria of severity and patients without clinical severity criteria (according to the guide for the clinical practice of CDI of the Society of Healthcare Epidemiology of America (SHEA) and the Infectious Diseases Society of North America (IDSA). RESULTS: A total of 202 CDI episodes were diagnosed. 77.7% (n = 157) presented clinical severity criteria. The presence of ulcerative colitis (p < 0.001), fever (p < 0.001), leukocytosis (p < 0.001), neutrophilia (p < 0.001), creatininemia (p = 0.005) were presented as risk factors for the development of severe CDI (S-CDI). Female sex, institutionalization, previous admission and death were described more frequently in the group with S-CDI, not finding significant differences. We found no differences with respect to the days of previous stay, or of post-CDI stay, although in the latter, the mean was higher in the case of S-CDI patients. No significant differences were found in terms of Ct in both groups; being only one point lower in patients with severity criteria (Ct = 26.1) than without severity criteria (Ct = 27.4) (p = 0.326). CONCLUSION: Based on the results of our study, it has not been possible to systematically implement the Ct value as a predictor of severity to the clinical report, and it is not possible to extrapolate this predictive variable from S-CDI and standardize the Ct value as a predictor of severity. Conclusion: Basándonos en los resultados de nuestro estudio, no ha sido posible la implementación sistemática del valor Ct como predictor de gravedad al informe clínico, no siendo posible extrapolar esta variable predictora de enfermedad por C difficile-G y estandarizar el valor Ct como factor predictor de gravedad.

Nomogram for predicting post-traumatic hydrocephalus after decompressive craniectomy for traumatic brain injury

SUMMARY OBJECTIVE: This study aimed to develop and validate a practical nomogram to predict the occurrence of post-traumatic hydrocephalus in patients who have undergone decompressive craniectomy for traumatic brain injury. METHODS: A total of 516 cases were enrolled and divided into the training (n=364) and validation (n=152) cohorts. Optimal predictors were selected through least absolute shrinkage and selection operator regression analysis of the training cohort then used to develop a nomogram. Receiver operating characteristic, calibration plot, and decision curve analysis, respectively, were used to evaluate the discrimination, fitting performance, and clinical utility of the resulting nomogram in the validation cohort. RESULTS: Preoperative subarachnoid hemorrhage Fisher grade, type of decompressive craniectomy, transcalvarial herniation volume, subdural hygroma, and functional outcome were all identified as predictors and included in the predicting model. The nomogram exhibited good discrimination in the validation cohort and had an area under the receiver operating characteristic curve of 0.80 (95%CI 0.72-0.88). The calibration plot demonstrated goodness-of-fit between the nomogram's prediction and actual observation in the validation cohort. Finally, decision curve analysis indicated significant clinical adaptability. CONCLUSION: The present study developed and validated a model to predict post-traumatic hydrocephalus. The nomogram that had good discrimination, calibration, and clinical practicality can be useful for screening patients at a high risk of post-traumatic hydrocephalus. The nomogram can also be used in clinical practice to develop better therapeutic strategies.

Clinical significance of bispectral index monitoring in patients with acute severe carbon monoxide poisoning / 中华劳动卫生职业病杂志

Objective: To analyze the correlation of bispectral index (BIS) with the prognosis of patients with acute severe carbon monoxide poisoning (ASCMP) and its predictive value of adverse outcomes. Methods: In March 2021, 106 ASCMP patients who were treated in Harrison International Peace Hospital Affiliated to Hebei Medical University from January 2019 to December 2020 were taken as research objects. All patients underwent 24-hour BIS monitoring after admission, and were divided into good prognosis group (n=75) and poor prognosis group (n=31) according to the prognosis of the patients' cranial nerve function after 60 d. The general conditions, Acute Physiology and Chronic Health Evaluation Ⅱ (APACHEⅡ) score, Glasgow Coma Scale (GCS) score at admission and 24-hour BIS mean were compared between the two groups. Pearson correlation analysis was used to analyze the correlations between the 24-hour BIS mean and GCS score at admission, APACHEⅡ score and coma time. The receiver operating characteristic (ROC) curve was drawn to analyze the predictive value of 24-hour BIS mean, GCS score at admission, APACHEⅡ score and coma time on adverse outcome of ASCMP patients. Results: The coma time and APACHEⅡ score of the patients in the poor prognosis group were significantly higher than those in the good prognosis group, the GCS score at admission and 24-hour BIS mean were significantly lower than those in the good prognosis group (P<0.05) . Pearson correlation analysis showed that the 24-hour BIS mean was positively correlated with the GCS score at admission, and negatively correlated with the APACHEⅡ score, coma time (r=0.675, -0.700, -0.565, P<0.001) . The 24-hour BIS mean had the highest predictive value for adverse outcome of ASCMP patients, with a cut-off value of 74, the area under the curve was 0.883 (95%CI: 0.814-0.951, P<0.001) , and the sensitivity and specificity were 73.3% and 87.1%, respectively. Conclusion: The 24-hour BIS mean has a good correlation with the acute brain nerve injury, the severity of the disease and coma time of patients with ASCMP. And it has a high predictive value for the adverse outcome in patients with ASCMP.

Construction of a nomogram prediction model for pathological complete response (pCR) of ipsilateral supraclavicular lymph node after neoadjuvant chemotherapy for breast cancer with first diagnosis of ipsilateral supraclavicular lymph node metastasis / 中华肿瘤杂志

Objective: To develop a predictive model for pathologic complete response (pCR) of ipsilateral supraclavicular lymph nodes (ISLN) after neoadjuvant chemotherapy for breast cancer and guide the local treatment. Methods: Two hundred and eleven consecutive breast cancer patients with first diagnosis of ipsilateral supraclavicular lymph node metastasis who underwent ipsilateral supraclavicular lymph node dissection and treated in the Breast Department of Henan Cancer Hospital from September 2012 to May 2019 were included. One hundred and forty two cases were divided into the training set while other 69 cases into the validation set. The factors affecting ipsilateral supraclavicular lymph node pCR (ispCR)of breast cancer after neoadjuvant chemotherapy were analyzed by univariate and multivariate logistic regression analyses, and a nomogram prediction model of ispCR was established. Internal and external validation evaluation of the nomogram prediction model were conducted by receiver operating characteristic (ROC) curve analysis and plotting calibration curves. Results: Univariate logistic regression analysis showed that Ki-67 index, number of axillary lymph node metastases, breast pCR, axillary pCR, and ISLN size after neoadjuvant chemotherapy were associated with ispCR of breast cancerafter neoadjuvant chemotherapy (P<0.05). Multivariate logistic regression analysis showed that the number of axillary lymph node metastases (OR=5.035, 95%CI: 1.722-14.721, P=0.003), breast pCR (OR=4.662, 95%CI: 1.456-14.922, P=0.010) and ISLN size after neoadjuvant chemotherapy (OR=4.231, 95%CI: 1.194-14.985, P=0.025) were independent predictors of ispCR of breast cancer after neoadjuvant chemotherapy. A nomogram prediction model of ispCR of breast cancer after neoadjuvant chemotherapy was constructed using five factors: number of axillary lymph node metastases, Ki-67 index, breast pCR, axillary pCR and size of ISLN after neoadjuvant chemotherapy. The areas under the ROC curve for the nomogram prediction model in the training and validation sets were 0.855 and 0.838, respectively, and the difference was not statistically significant (P=0.755). The 3-year disease-free survival rates of patients in the ispCR and non-ispCR groups after neoadjuvant chemotherapy were 64.3% and 54.8%, respectively, with statistically significant differences (P=0.024), the 3-year overall survival rates were 83.8% and 70.2%, respectively, without statistically significant difference (P=0.087). Conclusions: Disease free survival is significantly improved in breast cancer patients with ispCR after neoadjuvant chemotherapy. The constructed nomogram prediction model of ispCR of breast cancer patients after neoadjuvant chemotherapy is well fitted. Application of this prediction model can assist the development of local management strategies for the ipsilateral supraclavicular region after neoadjuvant chemotherapy and predict the long-term prognosis of breast cancer patients.

Performance of memory task indicators for assessment of the risk of depressive disorders / 预防医学

Objective@#To evaluate the risk of depressive disorders using memory task indicators, so as to provide insights into clinical assessment of depressive disorders.@*Methods@#A total of 68 patients with depressive disorders undergoing treatments in the departments of psychiatrics and clinical psychology in a tertiary hospital during the period from January to September, 2021 were enrolled as the case group, while a total of 31 hospital employees, social volunteers and university students served as controls. The error rate and response time of classical memory task experiments were compared between the two groups, including implicit memory, short-term memory and working memory tasks. In addition, the predictive indicators of depressive disorders were identified using multivariable logistic regression analysis and receiver operative characteristics (ROC) curve.@*Results@#The case group included 29 men and 39 women and had a mean age of (24.12±7.40) years, including 46 subjects with an educational level higher than diploma. The control group included 15 men and 16 women and had a mean age of (26.45±6.65) years, including 23 subjects with an educational level higher than diploma. Multivariable logistic regression analysis showed significant associations of age of >18 years (OR=3.431, 95%CI: 1.259-9.350), error rate of 2-back task (OR=1.056, 95%CI: 1.016-1.097) and error rate of short-term memory tasks (OR=1.078, 95%CI: 1.009-1.152) with the development of depressive disorders. ROC curve analysis showed that the error rate of 2-back tasks showed an area under the ROC curve (AUC) of 0.730 (95%CI: 0.630-0.831), cutoff of 22.5%, sensitivity of 42.6% and specificity of 93.5% for prediction of the risk of depressive disorders, and the error rate of short-term memory tasks showed an AUC of 0.717 (95%CI: 0.605-0.829), cutoff of 23.5%, sensitivity of 67.6% and specificity of 71.0% for prediction of the risk of depressive disorders. In addition, the combination of the error rate of 2-back tasks and the error rate of short-term memory tasks showed an AUC of 0.829 (95%CI: 0.734-0.923), sensitivity of 75.0% and specificity of 80.6% for prediction of the risk of depressive disorders.@*Conclusion@#Short-term and working memory task indicators are feasible for assessment of the risk of depressive disorders.

Predictive value of nomogram model based on PNI, SII and CAR for abdominal infection after liver transplantation / 器官移植

Objective To investigate the risk factors of abdominal infection after orthotopic liver transplantation. Methods Clinical data of 284 recipients undergoing orthotopic liver transplantation were retrospectively analyzed. All recipients were divided into the infection group (n=51) and non-infection group (n=233) according to the incidence of postoperative abdominal infection. Univariate and multivariate logistic regression analyses were used to identify the risk factors of abdominal infection. Nomogram prediction models were constructed and the prediction efficiency of these models was evaluated. The predictive value of continuous variables for abdominal infection was assessed. Results Among 284 recipients, 51 developed abdominal infection with an incidence of 18.0%. Diabetes mellitus before surgery[odds ratio (OR) 2.66, 95% confidence interval (CI) 1.13-6.14, P=0.013], long operation time (OR 1.98, 95%CI 1.03-3.57, P=0.038), low prognostic nutritional index (PNI) (OR 2.18, 95%CI 1.06-4.44, P=0.023), high systemic immune-inflammation index (SII) (OR 2.21, 95%CI 1.06-4.78, P=0.012) and high C-reactive protein/albumin ratio (CAR) (OR 1.90, 95%CI 1.05-3.49, P=0.029) were independent risk factors for abdominal infection after liver transplantation. The area under curve (AUC) of nomogram model for predicting abdominal infection after liver transplantation was 0.761. The standard model yielded high consistency. CAR, PNI and SII were all predictors of abdominal infection after liver transplantation (all P < 0.05), with AUC of 0.648, 0.611 and 0.648, and cut-off values of 2.75, 43.15 and 564.50, respectively. Conclusions CAR, SII and PNI are predictors of abdominal infection after liver transplantation. The nomogram model based on PNI, SII and CAR may effectively predict the incidence of abdominal infection after liver transplantation.

Verification of the risk score of hepatocellular carcinoma in patients with hepatitis B virus-associated liver cirrhosis / 中华消化杂志

Objective:To evaluate the accuracy and practicability of hepatocellular carcinoma prediction score (PAGE-B) and modified hepatocellular carcinoma prediction score (mPAGE-B) in predicting the development of hepatocellular carcinoma in patients with hepatitis B virus (HBV)-associated liver cirrhosis and received nucleos(t)ide analogue (NA) treatment.Methods:From June 2009 to December 2014, at Department of Hepatology, the First Affiliated Hospital of Fujian Medical University, the clinical data of 707 patients with HBV-associated liver cirrhosis and received NA treatment were retrospectively collected, and the patients were followed up. The risk factors of development of hepatocellular carcinoma were analyzed. PAGE-B (including platelet count, age, gender), mPAGE-B (including platelet count, age, gender and albumin), Child-Turcotte-Pugh (CTP) score and aspartate aminotransferase to platelet ratio index (APRI) were compared in area under receiver operator characteristic curve (AUROC) for predicting the occurrence of hepatocellular carcinoma within 5 years. Risk stratification analysis was carried out for mPAGE-B and PAGE-B. Multivariate Cox regression analysis, receiver operator characteristic curve, Mann-Whitney U test and Kaplan-Meier method were used for statistical analysis. Results:The age of 707 patients was (46.7±12.2) years old, including 567 males (80.2%) and 140 females (19.8%). The positive rate of hepatitis B e antigen was 56.4% (399/707). The scores of PAGE-B, mPAGE-B, CTP and APRI were 15.90±4.24, 12.39±3.58, 6.88±2.15 and 1.80 (0.85, 3.79), respectively. The overall follow up time was (38.14±20.97) months and the incidence of hepatocellular carcinoma was 8.1% (57/707). The results of multivariate Cox regression analysis showed that advanced age, low platelet count and quantitative reduction of HBV DNA were independent risk factors of development of hepatocellular carcinoma (Wald=20.44, 5.64 and 9.25; HR(95% confidence interval (95% CI) 1.056(1.031 to 1.081), 0.994(0.989 to 0.999) and 0.769(0.649 to 0.911); P<0.001, =0.018 and 0.002). The AUROCs (95% CI) of PAGE-B, mPAGE-B, CTP score and APRI for predicting the occurrence of hepatocellular carcinoma within 5 years were 0.708 (0.639 to 0.778), 0.724 (0.657 to 0.778), 0.576 (0.500 to 0.652) and 0.516 (0.443 to 0.589), respectively. There were no statistically significant differences in AUROCs for predicting the occurrence of hepatocellular carcinoma within 5 years between mPAGE-B and PAGE-B, between APRI and CTP score (both P>0.05). The AUROC for predicting the occurrence of hepatocellular carcinoma within 5 years of CTP score was less than those of PAGE-B and mPAGE-B, and the differences were statistically significant ( Z=3.00 and 3.79; P=0.003, <0.001). The AUROC for predicting the occurrence of hepatocellular carcinoma within 5 years of APRI was less than those of PAGE-B and mPAGE-B, and the differences were statistically significant ( Z=4.75 and 5.46, both P<0.001). There were 51 cases (7.2%), 394 cases (55.7%) and 262 cases (37.1%) in the low-risk (<10) group, medium-risk (10 to 17) group and high-risk (>17) group as assessed by PAGE-B. The incidence of hepatocellular carcinoma was 0(0/51), 4.8% (19/394) and 14.5% (38/262), respectively the annual average incidence of hepatocellular carcinoma was 0, 1.6% and 5.5%, respectively, the 5-year cumulative incidence of hepatocellular carcinoma was 0, 7.3% and 31.3%, respectively. The 5-year cumulative incidence of hepatocellular carcinoma of high-risk group was higher than those of medium-risk group and low-risk group (log-rank test=19.27, P<0.001). There were 97 cases (13.7%), 246 cases (34.8%) and 364 cases (51.5%) in the low-risk group (<9), medium-risk group (9 to 12) and high-risk group (>12) as assessed by mPAGE-B. The incidence of hepatocellular carcinoma was 2.1% (2/97), 3.7% (9/246) and 12.6%(46/364), the annual average incidence of hepatocellular carcinoma was 0.6%, 1.1% and 4.7%, respectively, the 5-year cumulative incidence of hepatocellular carcinoma was 2.4%, 5.1% and 26.7%, respectively. The 5-year cumulative incidence of hepatocellular carcinoma of high-risk group was higher than those of medium-risk group and low-risk group (log-rank test value=18.64, P<0.001). Conclusions:Both PAGE-B and mPAGE-B can predict the occurrence of hepatocellular carcinoma within 5 years in patients with HBV-associated liver cirrhosis treated with antiviral therapy, identify liver cirrhotic patients at high risk of development of hepatocellular carcinoma and guide clinicans to use more efficient screening strategies.

The role of serum pyrrole-protein adduct in evaluating the severity and predicting the anticoagulant efficacy in patients with pyrroidine alkaloid-related hepatic sinusoidal obstruction syndrome / 中华消化杂志

Objective:To explore the role of serum pyrrole-protein-adduct (PPA) in evaluating the severity and predicting the anticoagulant efficacy in patients with pyrrolidine alkaloid-related hepatic sinusoidal obstruction syndrome (PA-HSOS).Methods:From April 2018 to December 2019, the data of 48 patients with PA-HSOS admitted and treated at Drum Tower Hospital, Affiliated Medical College of Nangjing University were collected, which included PPA level, portal vein velocity (PVV), ascites grading, PA-HSOS severity grading (according to the new severity grading criteria for suspected hepatic sinusoidal obstruction syndrome in adults by the European Society of Blood and Bone Marrow Transplantation and adjusted) and the outcome of anticoagulation. Patients with acute onset (onset of symptoms within 1 month after consuming pyrrolizidine alkaloid-containing plants) were taken as research subjects. The combination of PPA with PVV or with ascites classification of PA-HSOS severity assessment model was fitted by logistic regression, and the logit values of 2 combination models were calculated, the formula was logit 1=0.034×PPA(nmol/L)+ 0.055×PVV(cm/s)-3.287, logit 2=0.039×PPA(nmol/L)-2.712×ascites grade 2 (Yes=1, No=0)-0.388×ascites grade 3 (Yes=1, No=0)-0.899. The patients received initial anticoagulation therapy at Drum Tower Hospital, Affiliated Medical College of Nanjing University were selected as research subjects. The anticoagulant efficacy prediction model of combination of PPA with serum creatinine (SCR) and with hepatic venous pressure gradient (HVPG) was fitted by logistic regression, and the logit value was calculated, the formula was logit 3=0.013×PPA(nmol/L)+ 0.064×SCR (mol/L)+ 0.542×HVPG (mmHg, 1 mmHg=0.133 kPa)-16.005. The predictive value of PPA in evaluating the severity of PA-HSOS and anticoagulant efficacy was evaluated. Receiver operating characteristic curve analysis was performed for statistical analysis. Results:The serum PPA level of 48 patients was 10.81 nmol/L (3.91 nmol/L, 32.04 nmol/L). Among them, 33 cases (68.8%) were mild PA-HSOS, 3 cases (6.2%) were moderate PA-HSOS, no severe PA-HSOS case and 12 cases (25.0%) were very severe PA-HSOS. Among 23 patients received initial anticoagulant therapy at Drum Tower Hospital, Affiliated Medical College of Nanjing University and with complete data, 8 patients responded and survived, and 15 patients did not respond (5 patients died, 1 patient relieved after continue anticoagulant therapy, and 9 patients survived after switching to anticoagulant therapy and transjugular intrahepatic portosystemic shunt (TIPS) treatment). One patient without initial anticoagulant therapy, survived after TIPS treatment because of the progress of the disease. Area under the curve (AUC) of PPA to assess the severity of acute onset PA-HSOS was 0.75, 95% confidence interval ( CI) was 0.52 to 0.98 ( P=0.047). When PPA≥45.519 nmol/L, the specificity and sensitivity in evaluating severe and very severe PA-HSOS was 100.0% and 57.1%, respectively. AUC of combination of PPA and PVV to assess the severity of PA-HSOS was 0.77, 95% CI was 0.55 to 1.00 ( P=0.032). When the logit of combination model≥0.180, the specificity and sensitivity in evaluating severe and very severe PA-HSOS was 71.4% and 81.8%, respectively. AUC of combination of PPA and ascites grade (grade 1, 2 or 3) to assess the severity of PA-HSOS was 0.85, 95% CI was 0.63 to 1.00 ( P=0.005). When the logit of combination model≥0.347, the specificity and sensitivity in evaluating severe and very severe PA-HSOS was 85.7% and 92.0%, respectively. AUC of combination of PPA, SCR and HVPG to predict anticoagulation efficacy was 0.85, 95% CI was 0.69 to 1.00 ( P=0.009). When the logit≥0.393, the specificity and sensitivity in predicting anticoagulation efficacy was 62.5% and 91.7%, respectively. Conclusions:PPA can be used to assess the severity of acute onset PA-HSOS patients, and combined with ascites grading can significantly improve its efficiency. PPA combined with SCR and HVPG can better predict anticoagulant efficacy.

The accuracy of mpMRI combined with clinical scales in predicting invasion of capsule and seminal vesicle in prostate cancer / 中华泌尿外科杂志

Objective:To explore the accuracy of mpMRI combined with Partin table, MSKCC nomogram and CAPRA score in predicting extracapsular extension and seminal vesicle invasion of prostate cancer.Methods:From January 2016 to June 2021, a total of 178 patients who underwent laparoscopic radical prostatectomy were selected. The average age of patients was (68.3±3.5) years, the average preoperative PSA level was (24.5±7.1)ng/ml, and the average percentage of positive cores in biopsy was 44.3%. The clinical T 1c stage was determined in 67 cases (37.6%), T 2a in 69 cases (38.8%) and T 2b-2c in 42 cases(23.6%). Biopsy Gleason score of 3+ 3=6 was found in 45 cases(25.3%), 3+ 4=7 in 41 cases(23.0%), 4+ 3=7 in 26 cases(14.6%), 8 with different combinations in 36 cases(20.2%), and 9 or 10 in 30 cases(16.9%). According to preoperative PSA level, biopsy Gleason score, clinical stage, age, total biopsy cores and positive cores, the posibility of extracapsular extension and seminal vesicle invasion were predicted using 2012-version Partin table and MSKCC nomogram. CAPRA score of each patient was calculated. The prediction schemes were built as follows: ①mpMRI alone, ②mpMRI combined with Partin scale, ③mpMRI combined with MSKCC nomogram, ④mpMRI combined with CAPRA score. The results of each prediction scheme were compared with postoperative pathological reports. Logistic regression analysis was used to evaluate the relationship between predictive results and postoperative pathological outcomes. The receiver operating characteristic curve of each prediction scheme was drawn. The area under curve was used to compare the predictive accuracy of each combination scheme for the pathological results of prostate cancer. The decision analysis curve of each prediction scheme was drawn. The clinical benefits of each scheme were analyzed by comparing the net return under different risk thresholds. Results:mpMRI predicted extracapsular extension in 21 cases(11.8%) and seminal vesicle invasion in 16 cases(9.0%). The postoperative pathological results reported extracapsular extension in 27 cases(15.2%) and seminal vesicle invasion in 39 cases(21.9%). Logistic regression analysis showed that mpMRI and clinical scales were predictors related to the pathological results of prostate cancer( P<0.05). The receiver operating characteristic curve of each scheme showed that the area under curve for predicting extracapsular extension by using mpMRI, mpMRI combined with Partin table, mpMRI combined with MSKCC nomogram and mpMRI combined with CAPRA score were 0.599, 0.652, 0.763 and 0.780, respectively, and the area under curve for predicting seminal vesicle invasion were 0.607, 0.817, 0.826 and 0.820, respectively. Compared with simple application of mpMRI, except that the scheme of mpMRI combined with Partin table had no obvious advantage in predicting extracapsular extension( P=0.117), any other combined scheme had higher prediction accuracy( P<0.01). mpMRI combined with MSKCC nomogram or CAPRA score was better than mpMRI combined with Partin table in predicting extracapsular invasion ( P<0.01). There was no significant difference in predicting seminal vesicle invasion among these three combination schemes ( P>0.05). The net income of the combined prediction scheme was higher than that of using mpMRI alone under any risk threshold. The scheme of using mpMRI combined with MSKCC nomogram had the highest net income. Conclusions:mpMRI combined with clinical scales has good accuracy in predicting pathological characteristics of prostate cancer in Chinese population. Compared with other schemes in this study, the combination scheme of mpMRI combined with MSKCC nomogram has the highest prediction accuracy.

Preoperative Nomogram prediction model for lymph node metastasis in patients with renal cell carcinoma / 中华泌尿外科杂志

Objective:To identify preoperative clinical predictors of positive lymph nodes in patients with renal cell carcinoma (RCC)and provide a preoperative predictive model.Methods:The data of 173 RCC patients who underwent either retroperitoneal lymph node dissection or biopsy at a single institution from January 2016 to December 2020 were retrospectively analyzed. There were 109 males and 64 females, with an average age of (53.29±13.58) years, median tumor diameter of 70 (23-150) mm, 68 patients with local symptoms, 24 patients with systemic symptoms, and 56 patients with ECOG score ≥1. There were 96 patients with tumor pseudocapsule, 23 patients with renal vein or inferior vena cava tumor thrombus, 114 patients in stage T 1-2, 59 patients in stage T 3-4, 22 patients with distant metastasis and 88 patients with lymph node metastasis by preoperative imaging examination. Univariate analysis was performed by Mann-Whitney U test or Chi-square test, and multivariate logistic regression analysis was used to determine preoperative predictors of pathologic lymph node positivity. The significant variables were then included in a novel Nomogram to predict the probability of lymph node invasion.C-index and Bootstrap self-sampling methods were used to evaluate the discrimination and consistency of the model. Results:Of the 173 patients, 49(28.32%)and 124(71.68%)had pN 1 and pN 0 disease, respectively. Among 88 patients with suspected lymph node involvement (cN 1) assessed by preoperative imaging, only 47.73%(42/88) were confirmed to be pathologically positive. However, 8.24% (7/85) of the 85 patients with negative lymph nodes (cN 0) assessed by preoperative imaging were pathologically positive. Age, ECOG score, symptoms at presentation, tumor pseudocapsule, metastasis at diagnosis, clinical tumor stage, clinical nodal status, clinical nodal size, D-dimer, lactate dehydrogenase, microscopic hematuria were significant in the univariate analysis ( P<0.05). On multivariable analyses, the most informative independent predictors were age, clinical tumor stage, clinical nodal status, clinical nodal size and microscopic hematuria ( P<0.05). A Nomogram with good performance was developed to predict the probability of lymph node metastasis. The C-index of the model was 0.954, the calibration curve of forecasting curve with the ideal curve fit was good, indicating that the model has a good consistency. Conclusions:Younger age, microscopic hematuria, suspected lymph node involvement in imaging, larger lymph node diameter and higher T stage were independent risk factors for renal cell carcinoma with lymph node metastasis. The Nomogram based on the above factors has good identification and calibration ability, which can help predict the probability of lymph node metastasis of renal cell carcinoma before surgery.

Analysis of risk factors and construction of a prediction model for mild cognitive impairment in elderly inpatients in sub-plateau areas / 中华老年医学杂志

Objective:To investigate the prevalence of mild cognitive impairment(MCI)in elderly inpatients in high altitude areas, analyze the influencing factors, and then construct a risk factor model.Methods:A cross-sectional random sampling method was used to conduct a questionnaire survey among elderly patients over 65 years old hospitalized at Qinghai Provincial People's Hospital from October 2018 to February 2019.The survey contents included demographic data, lifestyles, physical activities and cognitive function.The occurrence of MCI was analyzed with descriptive epidemiological measures, a predictive model of influencing factors was established using Logistic regression analysis, and influencing factors were ranked.Results:There were a total of 1412 elderly people aged 65 and above, with 760 males, accounting for 53.8%.The ages of respondents ranged between 65-82 years, with an average age of(72.8±5.8)years.Of the subjects, 600 had MCI, with a prevalence of 42.4%.Male( OR=1.318, P=0.02), junior high school education or above( OR=0.521, P<0.001), bedriddenness( OR=2.658, P=0.002), lifestyle( OR=0.702, P=0.011), abnormal defecation( OR=1.625, P=0.005)and frailty( OR=1.536, P=0.002)were included into the predictive model of influencing factors.The area under the ROC curve in this study was 0.676(95% CI: 0.648-0.704), with sensitivity=0.553, specificity=0.741, and Youden index=0.274.When ordered by importance, the independent risk factors were frailty, male, abnormal defecation, bedriddenness, lifestyle, and education level. Conclusions:Male, frailty, abnormal defecation and long-term bedriddenness are risk factors for cognitive impairment in elderly people, whereas living with a partner and education above junior high school are protective factors.

Study of three-dimensional dose distribution prediction in cervical cancer brachytherapy based on U-Net fully convolutional network / 中华放射肿瘤学杂志

Objective:Topredict the three-dimensional dose distribution of regions of interest (ROI) with brachytherapy for cervical cancer based on U-Net fully convolutional network, and evaluate the accuracy of prediction model.Methods:First, 100 cases of cervical cancer intracavity combined with interstitial implantation were selected as the entire research data set, and divided into the training set ( n=72), validation set ( n=8), and test set ( n=20). Then the U-Net was used to construct two models based on whether the uterine tandem and the implantation needles were included as the distinguishing factors. Finally, dose distribution of 20 cases in the test set were predicted using the trained model, and comparative analysis was performed. The performance of the model was jointly evaluated by , and the mean absolute deviation (MAD). Results:Compared with the model without the uterine tandem and the implantation needles, the of the rectum was increased by (16.83±1.82) cGy ( P<0.05), and the or of the other ROI were not different significantly (all P>0.05). The MAD of the high-risk clinical target volume, rectum, sigmoid, small bowel, and bladder was increased by (11.96±3.78) cGy, (11.43±0.54) cGy, (24.08±1.65) cGy, (17.04±7.17) cGy and (9.52±4.35) cGy, respectively (all P<0.05). The MAD of the intermediate-risk clinical target volume was decreased by (120.85±29.78) cGy ( P<0.05). The mean value of MAD for all ROI was decreased by (7.8±53) cGy ( P<0.05), which was closer to the actual plan. Conclusions:U-Net fully convolutional network can be used to predict three-dimensional dose distribution of patients with cervical cancer undergoing brachytherapy. Combining the uterine tube with the implantation needles as the input parameters yields more accurate predictions than a single use of the ROI structure as the input.

Personalized quantitative evaluation of the quality of radiotherapy plans based on dose prediction / 中华放射医学与防护杂志

Objective:To develop a dose prediction-based quantitative evaluation method of the quality of radiotherapy plans, and to verify the clinical feasibility and clinical value of the method .Methods:The 3D U-Netwas trained using the radiotherapy plans of 45 rectal cancer cases that were formulated by physicists with more than five years of radiotherapy experience. After obtaining 3D dose distribution using 3D U-Net prediction, this study established the plan quality metrics of intensity modulated radiotherapy(IMRT) rectal cancer radiotherapy plans using dose-volume histogram(DVH) indexes of dose prediction. Then, the initial scores of rectal cancer radiotherapy plans were determined.Taking the predicted dose as the optimization goal, the radiotherapy plans were optimized and scored again. The clinical significance of this scoring method was verified by comparing the scores and dosimetric parameters of the 15 rectal cancer cases before and after optimization.Results:The radiotherapy plans before and after optimization all met the clinical dose requirements. The total scores were(77.21±9.74) before optimization, and (88.78±4.92) after optimization. Therefore, the optimized radiotherapy planswon increased scores with a statistically significant difference( t=-4.105, P<0.05). Compared to the plans before optimization, the optimized plans show decreased Dmax of all organs at risk to different extents. Moreover, the Dmax, V107%, and HI of PTV and the Dmax of the bladder decreased in the optimized plans, with statistically significant differences ( t=2.346-5.771, P<0.05). There was no statistically significant difference in other indexes before and after optimization ( P>0.05).The quality of the optimized plans were improved to a certain extent. Conclusions:This study proposed a dose prediction-based quantitative evaluation method of the quality of radiotherapy plans. It can be used for the effective personalized elevation of the quality of radiotherapy plans, which is beneficial to effectively compare and review the quality of clinical plans determined by different physicists and provide personalized dose indicators. Moreover, it can provide great guidance for the formulation of clinical therapy plans.