Derivación y validación de un nuevo puntaje predictivo de mortalidad por covid-19 en la altura / Derivation and Validation of a New covid-19 Predictive Score for Mortality at High Altitude / Derivação e validação de um novo escore preditivo de mortalidade por covid-19 em altitude

Objetivo: desarrollar un puntaje predictivo de mortalidad para pacientes con covid-19. Materiales y méto-dos: estudio retrospectivo, analítico, observacional y transversal, realizado en dos fases. Se revisaron 620 historias clínicas con una cohorte de derivación de 320 pacientes y una de validación de 300 pacientes. Las variables se analizaron con test de Anova, chi cuadrado de Pearson y análisis multivariante con regresión binaria, que determinaron sensibilidad, especificidad y valor predictivo negativo y positivo. Los puntajes se compararon mediante curvas cor con los scoresnews y hews. Resultados: los dos puntajes obtenidos incluyeron valores de edad, conteo de linfocitos, SatO2/FiO2, leucocitos, plaquetas, ausencia de síntomas, hipertensión arterial, epid y dhl. El área bajo la curva (abc) fue de 0.838 para el puntaje con dhl, con una mortalidad del 100 % para 7.75 puntos o más, y un abc de 0.826 para el primer puntaje. En la cohorte de validación, el abc para el primer puntaje fue de 0.831 y para el score con dhl fue 0.855. El puntaje hewsobtuvo un abc de 0.451, y el news, un abc de 0.396. Conclusiones: se desarrollaron dos herramientas para predecir mortalidad en pacientes con covid-19, con alto poder de discriminación, superior a los puntajes británicos hews y news

Objetivo: desarrollar un puntaje predictivo de mortalidad para pacientes con covid-19. Materiales y méto-dos: estudio retrospectivo, analítico, observacional y transversal, realizado en dos fases. Se revisaron 620 historias clínicas con una cohorte de derivación de 320 pacientes y una de validación de 300 pacientes. Las variables se analizaron con test de Anova, chi cuadrado de Pearson y análisis multivariante con regresión binaria, que determinaron sensibilidad, especificidad y valor predictivo negativo y positivo. Los puntajes se compararon mediante curvas cor con los scoresnews y hews. Resultados: los dos puntajes obtenidos incluyeron valores de edad, conteo de linfocitos, SatO2/FiO2, leucocitos, plaquetas, ausencia de síntomas, hipertensión arterial, epid y dhl. El área bajo la curva (abc) fue de 0.838 para el puntaje con dhl, con una mortalidad del 100 % para 7.75 puntos o más, y un abc de 0.826 para el primer puntaje. En la cohorte de validación, el abc para el primer puntaje fue de 0.831 y para el score con dhl fue 0.855. El puntaje hewsobtuvo un abc de 0.451, y el news, un abc de 0.396. Conclusiones: se desarrollaron dos herramientas para predecir mortalidad en pacientes con covid-19, con alto poder de discriminación, superior a los puntajes británicos hews y news

Objetivo: desenvolver um escore preditivo de mortalidade para pacientes com covid-19. Materiais e Métodos: estudo retrospectivo, analítico, observacional e transversal, realizado em duas fases. Foram revisados 620 prontuários, com uma coorte de derivação de 320 pacientes e uma coorte de validação de 300 pacientes. As variáveis foram analisadas com teste anova, qui-quadrado de Pearson e análise multivariada com regressão binária, determinando sensibilidade, especificidade, valor preditivo nega-tivo e positivo. As pontuações foram comparadas por meio de curvas cor com as pontuações news e hews. Resultados: os dois escores obtidos incluíram valores de: idade, contagem de linfócitos, SatO2/FiO2, leucócitos, plaquetas, ausência de sintomas, hipertensão arterial, epid e dhl. A área sob a curva (abc) foi de 0,838 para o escore dhl, com 100 % de mortalidade para 7,75 pontos ou mais, e uma abc de 0,826 para o primeiro escore. Na coorte de validação, a abc para o primeiro escore foi de 0,831 e para o escore com dhl foi de 0,855. A pontuação hews obteve abc de 0,451 e o news uma abc de 0,396. Conclusões: foram desenvolvidas duas ferramentas para prever mortalidade em pacientes com covid-19, com alto poder de discriminação, superior aos escores britânicos hews e news

Effect of early warning score combined with SBAR communication model on early warning of high-risk neonates / 现代临床护理

Objective To investigate the effect of early warning score system combined with(situation,background,ssessment,recommendation,SBAR)communication model in early warning of high-risk neonates,therefore to provide an effective communication method for an effective communication method to assess the changes of condition in neonates.Methods A before-after study model was adopted in the study.A total of 270 high-risk neonates admitted to the ward of the Department of Neonatology in a tertiary hospital between August and September 2022 were selected as research subjects.The high-risk neonates admitted in hospital in August were assigned in a control group,and those admitted in September were assigned in an trial group,with 135 neonates per group.Routine care was carried out in the control group,while early warning scoring combined with SBAR communication model were applied in the trial group on top of the cares offered to the control group.The occurrence of early warning events,concordance rate of nurse warning event and doctor handling events,and the satisfaction rate of doctors with the nursing performance were compared between the two groups.Results A total of 63.6%of early warning events were triggered by nurses in the control group,while it was 92.6%in the trial group,with a statistically significant difference between the groups(χ2=16.622,P<0.001).The consistency of handling of early warning events between the nurses and doctors in the trial group(Kappa coefficient=0.926)was higher than that in the control group(Kappa coefficient=0.641).The satisfaction rates of the doctors with the nurses about specialist knowledge,ability in emergency events,mastery of disease,timely observation of disease progress,collaboration between doctors and nurses,working enthusiasm,communication capability and the psychological quality in the trial group were all significantly higher than those in the control group[80.0%-95.0%vs.30.0%-55.0%,all P<0.01].Conclusions The Early Warning Score system combined with SBAR communication model can help nurses to accurately evaluate the changes of disease in neonates,complete the communication with doctors timely and effectively.It improves the observation,communication and handling capability among the nurses as well as the satisfaction rate of doctors with nursing work.

Design and implementation of multi-point trigger system for infectious disease warning / 现代医院

Objective With the focus on emerging infectious diseases and diseases of unknown cause,the study aims to realize multi-point trigger monitoring of infectious diseases through key monitoring sites and key populations.Methods Using ar-tificial intelligence,deep learning,big data and other information technologies to build an intelligent information center for infec-tious diseases with patients'disease files as the core,construct a core capacity of infectious disease surveillance,early warning and situation prediction,and predict and evaluate the importance of infectious disease warning signals.Results The system cov-ered 1 425 primary-level medical institutions,18 hospitals,2 580+schools,4 134 pharmacies,4 laboratories and civil affairs departments,detected 55 kinds of infectious diseases and 6 kinds of syndrome monitoring signals.Since its launch,121 000 ac-tive notification cards have been issued,more than 54 000 new notification cards have been added,35.256 million times of multi-source monitoring and 14.4 million disease files have been recorded.Conclusion By expanding monitoring content and chan-nels,we realized early monitoring,auxiliary investigation and multi-mode visual early warning of infectious diseases,built a multi-point trigger mechanism,and moved forward the infectious disease surveillance.

Establishment of a risk assessment model based early warning system for infectious diseases / 现代医院

Objective To establish a risk assessment model based infectious disease early warning system and promote the improvement of infectious disease management level.Methods By collecting and organizing the latest research results,and referring to the theoretical framework of the relevant infectious disease early warning evaluation index system,a risk assessment model based infectious disease early warning system is constructed.Results A total of 12 experts were included in this study,and three primary indicators were selected,including pre-epidemic indicators,typical symptom period indicators,atypical symp-tom period indicators,and 7 secondary indicators.The average score for necessity of the system was 8.27±0.24 points,and the average score for accessibility was 7.74±0.34 points.Conclusion The establishment of an infectious disease early warning sys-tem based on risk assessment models is conducive to timely following the epidemic trend of infectious diseases in the local area,analyzing the distribution trend of survey indicators,and proposing corresponding early warning plans,which can provide relevant basis for effective prevention of infectious diseases.

Research Progress of the Infectious Disease Prediction Models Based on Internet Data / 医学信息学杂志

Purpose/Significance The paper systematically reviews relevant research on infectious disease prediction models based on internet data,helps to realize the advancement of infectious disease surveillance,and provides references for the construction of intelli-gent three-dimensional prevention and treatment system of infectious diseases.Method/Process The development history and research direction of infectious disease surveillance and early warning based on internet data collected in the core database of Web of Science and CNKI in the past 20 years are reviewed,major existing problems and challenges are analyzed,and common prediction models and their optimization directions are summarized.Result/Conclusion The study on internet infectious disease surveillance shows the trend of diver-sification of monitoring diseases,refinement and specialization of data sources.Due to the complexity and uncertainty of internet data,most of the existing models are only suitable for short-term or real-time prediction.By constructing a combination model,strengthening multi-source data fusion,improving the selection of keywords and influencing factors,the model can be further optimized and the fitting effect and prediction capacity can be strengthened.

Analysis on Basic Medical Insurance Fund Balance Status and Risk Warning in China from 2009 to 2022 / 中国卫生经济

Objective:To analyze the basic medical insurance fund balance status in China and the risk warning since the new medical reform,in order to provide decision-making references for the sustainable development of basic medical insurance fund in China.Methods:Collecting the data on the basic medical insurance fund in China from 2009 to 2022 for descriptive statistical analysis,and conduct fund balance risk warning analysis based on the risk warning interval.Results:During 2009-2021,the percentage of retirees enrolled in UEBMI has continued to increase,and there will still be a certain accumulated balance in the integrated fund.The number of participants in the URBMI has been decreased since 2020,the growth rate of fund expenditures became higher than the growth rate of fund revenues,the fund balance showed a decreasing trend.Conclusion:There are certain risks to the long-term balance of the basic medical insurance fund,which may caused by factors such as aging population,funding mechanisms,and treatment levels.

Construction and analysis of early warning and prediction model for risk factors of sepsis-associated encephalopathy / 中华危重病急救医学

Objective:To investigate the epidemiological characteristics of sepsis-associated encephalopathy (SAE) in patients with sepsis, analyze its risk factors and build a prediction model, which provides evidence for early clinical identification of SAE patients and improvement of clinical outcomes.Methods:A retrospective observational study was conducted. Sepsis patients admitted to the critical care medical center of the First Affiliated Hospital of Xinjiang Medical University from February 2022 to February 2023 were enrolled. According to whether SAE occurred, the patients were divided into sepsis group and SAE group. The 24 patients without sepsis in the same period were used as controls (non-sepsis group). Demographic data, relevant scores and laboratory test indicators at admission to intensive care unit (ICU), and prognostic indicators were collected. Univariate and multivariate Logistic regression analysis was used to analyze the risk factors for sepsis and SAE. Receiver operator characteristic curve (ROC curve) was drawn. The predictive value of each risk factor for sepsis and SAE.Results:A total of 130 patients with sepsis were included, of which 52 had SAE, and the incidence of SAE was 40.00%. There were significant differences in the length of ICU stay and total length of stay among all groups, while there were no significant differences in hospitalization cost and mechanical ventilation time. Multivariate Logistic regression analysis showed that pulmonary infection [odds ratio ( OR) = 46.817, 95% confidence interval (95% CI) was 5.624-389.757, P = 0.000], acute physiology and chronic health evaluation Ⅱ (APACHEⅡ: OR = 1.184, 95% CI was 1.032-1.358, P = 0.016), sequential organ failure assessment (SOFA: OR = 9.717, 95% CI was 2.618-36.068, P = 0.001), Charson comorbidity index (CCI: OR = 4.836, 95% CI was 1.860-12.577, P = 0.001), hemoglobin (Hb: OR = 0.893, 95% CI was 0.826-0.966, P = 0.005), glutamyltranspeptidase ( OR = 1.026, 95% CI was 1.008-1.045, P = 0.006) were independent risk factors for sepsis in ICU patients. Pulmonary infection ( OR = 28.795, 95% CI was 3.296-251.553, P = 0.002), APACHEⅡ score ( OR = 1.273, 95% CI was 1.104-1.467, P = 0.001), SOFA score ( OR = 8.670, 95% CI was 2.330-32.261, P = 0.001), CCI ( OR = 5.141, 95% CI was 1.961-13.475, P = 0.001), Hb ( OR = 0.922, 95% CI was 0.857-0.993, P = 0.031), glutamyltranspeptidase ( OR = 1.020, 95% CI was 1.002-1.038, P = 0.030) were independent risk factors for SAE in sepsis patients. ROC curve analysis showed that the area under the curve (AUC) of pulmonary infection, APACHEⅡ score, SOFA score, CCI, Hb, and glutamyltranspeptidase for predicting sepsis were 0.792, 0.728, 0.987, 0.933, 0.720, and 0.699, respectively; the AUC of the combined prediction of the above 6 variables for sepsis was 1.000, with a sensitivity of 100% and a specificity of 100%. The AUC predicted by pulmonary infection, APACHEⅡ score, SOFA score, CCI, and Hb for SAE were 0.776, 0.810, 0.907, 0.917, and 0.758, respectively; the AUC of the combined prediction of the above 5 variables for SAE was 0.975, with a sensitivity of 97.3% and a specificity of 93.1%. Conclusions:Sepsis is more severe when accompanied by encephalopathy. Pulmonary infection, Hb, APACHEⅡ score, SOFA score and CCI were independent risk factors of SAE. The combination of the above five indicators has good predictive value for early screening and prevention of the disease.

Research progress on risk prediction of cardiac arrest / 中华危重病急救医学

Cardiac arrest (CA) is a serious cardiac event, which has a high incidence and low survival rate at home and abroad. In order to predict the risk of CA in advance, a large number of studies have been conducted by relevant researchers. This paper mainly summarizes the characteristics and research status of the existing analysis and prediction of CA from three aspects: the risk prediction factors of CA, the evaluation index of risk prediction of CA and the early warning scoring system of CA. We hope it can help medical staff to understand the current progress in this field, and provide new ways and methods for predicting the risk of CA.

Research on the application of evaluation and warning system based on Shewhart control chart in medical device related pressure injury / 中国医学装备

Objective:To explore the effectiveness of the Shewhart control chart-based assessment and early warning system in prevention of medical device-related pressure injury(MDRPI).Methods:152 critically ill patients admitted to Hebei Central Hospital from January 2020 to December 2021 were selected and divided into a control group and an observation group based on different methods of assessing MDRPI risk,with 76 cases in each group.The control group adopted the Braden scale to assess the risk of MDRPI.The observation group adopted a safety early warning system based on Shewhart control charts to assess the risk of MDRPI in patients.Nursing measures were undertaken according to MDRPI risk grade in both groups.The occurrence of adverse events of MDRPI,nursing safety quality and nursing comprehensive quality were compared between the two groups.Results:The incidence rate of head,neck and face adverse events of MDRPI and the total incidence of adverse events of MDRPI of the patients in the observation group were lower than those in the control group(x2=4.802,5.758,P<0.05).The safety quality and comprehensive quality of nursing of 20 nurses in the observation group were higher than those in the control group(t=6.654,7.172,P<0.05).Conclusion:The application of assessment and early warning system based on Shewhart control chart in clinical nursing management can effectively reduce the incidence of MDRPI adverse events and improve the quality of nursing safety and comprehensive nursing.

A synthetic minority oversampling technique-based early warning model of postoperative biliary leakage after resection for hepatocellular carcinoma / 中华肝胆外科杂志

Objective:To analyze the influencing factors of postoperative bile leakage in laparoscopic liver lobectomy for hepatocellular carcinoma (HCC), and to create and validate an early warning model of postoperative bile leakage based on the synthetic minority oversampling technique (SMOTE).Methods:Clinical data of 120 patients with HCC undergoing laparoscopic lobectomy in Xiaolan People's Hospital of Zhongshan City from January 2016 to January 2022 were retrospectively analyzed, including 72 males and 48 females, aged (58.6±6.7) years old. The patients were divided into two groups according to the occurrence of bile leakage within 30 days after surgery: bile leakage group ( n=32) and non-bile leakage group ( n=88). Clinical data such as lesion size, remnant liver volume, intraoperative blood loss, and serum levels of alanine aminotransferase (ALT) and aspartate aminotransferase (AST) were collected. The positive sample size in the original dataset was expanded according to the SMOTE algorithm, and the SMOTE risk warning model (P 2) was established based on the new dataset. The predictive efficacy of the model was accessed using the receiver operating characteristic (ROC) curve and the area under the curve (AUC). Results:The incidence of postoperative bile leakage was 26.67%(32/120) in the patients. Lesion size, preoperative cholangitis, remnant liver volume, intraoperative blood loss, serum level of ALT and AST differs between the groups (all P<0.05). The sample size of the bile leakage group was expanded to 96 cases by the SMOTE algorithm, and then the sample size ratio of the two groups would be close to 1. Subsequent re-fitting of the expanded data based on the SMOTE algorithm showed that a lesion size of ≥5 cm, preoperative cholangitis, increased intraoperative hemorrhage, elevated ALT and AST were independent risk factors for postoperative bile leakage in patients with HCC (all P<0.05), while a larger remnant liver volume was a protective factor for postoperative bile leakage ( P<0.05). An early warning model P 2 was established based on the above factors. The Hosmer-Lemeshow test showed that the model fitting was good ( P=0.842, coefficient of determination R2=0.647). The sensitivity and specificity of the model for predicting postopera-tive bile leakage was 93.75% and 82.95%, respectively, with an AUC of 0.955 (95% CI: 0.901-0.985). Conclusion:Lesion size, preoperative cholangitis, remnant liver volume, intraoperative blood loss, serum levels of ALT and AST were associated with postoperative bile leakage after surgery for HCC. The early warning model of postoperative bile leakage based on the SMOTE algorithm has a high predictive efficacy.

Progress of early warning indicators on infectious diseases / 上海预防医学

In recent years， with frequent outbreaks of infectious diseases around the world， the global public health is faced with many threats and challenges. An infectious diseases early warning system is an important means for prevention and control of infectious diseases. As an important part of the early warning system， the warning indicators is crucial for understanding the occurrence and development trend of infectious diseases， detecting abnormal situations timely and effectively， and issuing early warning and initiating emergency response. Based on the occurrence and development process of infectious diseases， this paper summarizes the research status of early warning indicators on infectious diseases， in order to provide reference for the development and improvement of the infectious diseases early warning system.

COVID-19: Asociación entre la clasificación de riesgo y el Modified Early Warning Score y los resultados hospitalarios / COVID-19: Association of risk classification with the Modified Early Warning Score and hospital outcomes / COVID-19: Associação da classificação de risco com o Modified Early Warning Score e os desfechos hospitalares

Objetivo: evaluar la asociación entre las categorías de clasificación de riesgo y el Modified Early Warning Score y los resultados de los pacientes con COVID-19 en el servicio de emergencia Método: estudio transversal, realizado con 372 pacientes hospitalizados con diagnóstico de COVID-19 atendidos en la Recepción con Clasificación de Riesgo en Urgencias. En este estudio, el Modified Early Warning Score de los pacientes se clasificó como sin y con deterioro clínico, de 0 a 4 y de 5 a 9, respectivamente. Se consideró que había deterioro clínico cuando presentaban insuficiencia respiratoria aguda, shock y paro cardiorrespiratorio. Resultados: el Modified Early Warning Score promedio fue de 3,34. En cuanto al deterioro clínico de los pacientes, se observó que en el 43% de los casos el tiempo de deterioro fue menor a 24 horas y que el 65,9% ocurrió en urgencias. El deterioro más frecuente fue la insuficiencia respiratoria aguda (69,9%) y el resultado fue alta hospitalaria (70,3%). Conclusión: los pacientes con COVID-19 que presentaban Modified Early Warning Score 4 se asociaron a las categorías de clasificación de riesgo urgente, muy urgente y emergente y tuvieron más deterioro clínico, como insuficiencia respiratoria y shock, y murieron, lo que demuestra que el Protocolo de Clasificación de Riesgo priorizó correctamente a los pacientes con riesgo vital.

Objective: to evaluate the association of the risk classification categories with the Modified Early Warning Score and the outcomes of COVID-19 patients in the emergency service Method: a crosssectional study carried out with 372 patients hospitalized with a COVID-19 diagnosis and treated at the Risk Classification Welcoming area from the Emergency Room. In this study, the patients' Modified Early Warning Score was categorized into without and with clinical deterioration, from 0 to 4 and from 5 to 9, respectively. Clinical deterioration was considered to be acute respiratory failure, shock and cardiopulmonary arrest Results: the mean Modified Early Warning Score was 3.34. In relation to the patients' clinical deterioration, it was observed that, in 43%, the time for deterioration was less than 24 hours and that 65.9% occurred in the Emergency Room. The most frequent deterioration was acute respiratory failure (69.9%) and the outcome was hospital discharge (70.3%). Conclusion: COVID-19 patients who had a Modified Early Warning Scores > 4 were associated with the urgent, very urgent and emergency risk classification categories, had more clinical deterioration, such as respiratory failure and shock, and evolved more to death, which shows that the Risk Classification Protocol correctly prioritized patients at risk of life.

Objetivo: avaliar a associação das categorias de classificação de risco com o Modified Early Warning Score e os desfechos dos pacientes com COVID-19 no serviço de emergência Método: estudo transversal, realizado com 372 pacientes internados com diagnóstico de COVID-19 atendidos no Acolhimento com Classificação de Risco no Pronto-Atendimento. Neste estudo, o Modified Early Warning Score dos pacientes foi categorizado em sem e com deterioração clínica, de 0 a 4 e de 5 a 9, respectivamente. Foram consideradas deteriorações clínicas a insuficiência respiratória aguda, choque e parada cardiorrespiratória. Resultados: o Modified Early Warning Score médio foi de 3,34. Em relação à deterioração clínica dos pacientes, observou-se que em 43% o tempo para deterioração foi menor de 24 horas e que 65,9% delas ocorreu no pronto-socorro. A deterioração mais frequente foi a insuficiência respiratória aguda (69,9%) e o desfecho foi o de alta hospitalar (70,3%). Conclusão: pacientes com COVID-19 que tiveram Modified Early Warning Score 4 foram associados às categorias da classificação de risco urgente, muito urgente e emergente e tiveram mais deterioração clínica, como a insuficiência respiratória e o choque, e evoluíram mais a óbito, o que demonstra que o Protocolo de Classificação de Risco priorizou corretamente os pacientes com risco de vida.

A retrospective and comparative study between quick sequential organ failure assessment, CURB-65, and early warning scorings in COVID-19 patients to predict the disease severity and outcome

Background: Predicting the severity of COVID-19 infection in advance is the key to success of its treatment outcome. Various scoring systems are used to detect the severity of this disease but this study targets three simple scoring systems based on the vital parameters and basic routine laboratory tests. Aims and Objectives: The aim of the study was to assess the predictability of three scoring systems (Quick sequential organ failure assessment [q SOFA], CURB-65, and Early Warning scoring system) for disease severity at presentation in a rural-based tertiary care center. Materials and Methods: An observational, descriptive, retrospective, and cross-sectional study was conducted at Diamond Harbour Government Medical College Covid Hospital from January 2021 to January 2022 to assess the predictability of q SOFA, CURB-65, and Early Warning scoring system for disease severity at presentation. Results: The total number of participants was 561 among total admitted 1367 patients. A short descriptive analysis obtained from the variables to analyze the scorings howed among total sample collected, 57% were male and 43% were female. In this study, 87% of patients were survived and the rest 13% succumbed (death). There is no statistically significant difference in mortality between both genders. Age, pulse rate, and respiratory rate have a significant correlation with the outcome and altered sensorium is also highly associated with mortality. The accuracy was also found to be little higher for National Early Warning score (NEWS) score than CURB-65 scoring and q SOFA scoring (0.919, 0.914 and 0.907). Although all the scoring systems have high sensitivity (>90%) (CURB 65: Most sensitive [0.99]), the specificities of all three scoring systems are below 50%. Among these three-scoring systems, NEWS showed the highest specificity (0.492) than q SOFA (0.423) and CURB 65 (0.394). Conclusion: We suggest NEWS score and CURB-65 as a better predictor for in-hospital mortality in COVID-19 patients as it is significantly sensitive and reasonably specific. It can be recommended in less equipped hospitals where only basic laboratory facilities are available. qSOFA can be utilized where no laboratory facility is available like in safe home and isolation centers.

Avaliação da relação entre a qualidade da anotação dos parâmetros fisiológicos, o Escore para Alerta Precoce e a adoção do Plano de Ação em enfermaria de um Hospital Universitário / Assessment of the relationship between the quality of the recording of physiological parameters, the Early Warning Score, and the adoption of the Action Plan in the ward of a University Hospital

Introdução: Em pacientes em enfermarias, eventos adversos evitáveis podem decorrer de deterioração clínica despercebida, frequentemente antecedida por alterações nos sinais vitais, fornecendo oportunidade para intervenção precoce. A adoção de Equipe de Resposta Rápida (ERR) pode melhorar esse desfecho, porém é altamente dependente do monitoramento dos parâmetros fisiológicos e da notificação da ERR. Objetivo: Avaliar a qualidade das informações em prontuários e da resposta assistencial a pacientes em enfermarias com agravamento do estado clínico, resultando em óbito ou transferência para UTI em um Hospital Universitário e fornecer dados para comparação de resultados após implantação da ERR. Material e Métodos: Estudo documental retrospectivo, entre junho de 2013 e julho de 2014, em 128 prontuários de pacientes com piora clínica que resultou em óbito ou admissão em UTI ("evento"). Foram coletados os parâmetros fisiológicos, a pontuação no Escore para Alerta Precoce e o Plano de Ação registrado em 11 momentos que antecederam o "evento", resultando em 11 escores. A relação entre a pontuação do Escore de Alerta Precoce e a execução do Plano de Ação foi classificada como "adequada", "inadequada" ou "ausente". Resultados: Quanto mais se afastava momento de ocorrência do "evento", maior foi o número de dados faltantes, ocasionando Escores de Alerta Precoce não calculáveis. O número de casos adequados foi menor quanto mais distante estava o "evento" do momento da aferição dos parâmetros fisiológicos. Conclusão: Os tempos de resposta foram inadequados ao Plano de Ação. A falha em socorrer pacientes em deterioração clínica é complexa e multifatorial, mas acredita-se que no presente relato isto se deveu, pelo menos em parte, à anotação inadequada dos parâmetros fisiológicos. Esforços devem ser envidados no sentido de reforçar a importância do registro dos parâmetros fisiológicos, de reconhecer, de intervir e de comunicar agravos, essenciais para o correto funcionamento das alças aferente e eferentes das ERR.

Introduction: Preventable adverse events may result from unnoticed clinical deterioration in inpatients, which are often preceded by changes in warning signs, providing an opportunity for early intervention. The adoption of the Rapid Response Team (ERR) can improve the outcome; however, it is highly dependent on monitoring of the physiological parameters and on notification of the ERR. Objective: To evaluate the quality of information in medical records and the care response to patients in wards with worsening of the clinical status, which resulting in death or transfer to the ICU in a University Hospital and provide data for future comparison of results after ERR deployment. Material and Methods: Documentary retrospective study, between June 2013 and July 2014, of 128 medical records of patients with clinical worsening who died in death or admission to the ICU ("event"). The physiological parameters, the score on the Early Warning Score and the Action Plan recorded in 11 moments that preceded the "event" were collected, resulting in 11 scores. The relationship between the Early Warning Score and Action Plan execution was classified as "adequate", "inadequate" or "absent". Results: The further away from the moment of occurrence of the "event", greater the number of missing data, causing non- calculable Early Warning Scores. The number of adequate cases was smaller the further away the "event" was from the moment of measurement of the physiological parameters. Conclusion: Response times were inadequate to the Action Plan. Failure to rescue patients in the clinic is a complex and multifactorial, but it is believed that in the present report this was due, at least in part, to inadequate recording of physiological parameters. Efforts should be made to reinforce the importance of recording physiological parameters, recognizing, intervening, and communicating injuries, which are essential for the correct functioning of the afferent and efferent loops of the ERR.

Visual atlas analysis of research hot spots and trends of infectious disease early warning in China / 公共卫生与预防医学

Objective To sort out the scientific research achievements in the direction of early warning of infectious diseases in China from 2001 to 2022, and analyze the research hotspots and trends in the direction of early warning of infectious diseases in China in recent 20 years, so as to provide reference for relevant policies and exploration directions. Methods Relevant literature retrieved from CNKI Chinese database was used as the data source, and Excel 2019 and Citespace 6.1.R2 software were used for visual analysis of research hotspots and frontier literature. Results A total of 1276 papers meeting requirements were obtained, and most of the research groups were relatively small and had little cooperation with others. The types of research institutions were relatively single, and most of them were domestic universities. “Infectious diseases”, “early warning” and “prediction” were the most frequently used keywords. Research on big data and COVID-19 epidemic prevention and control is the current research frontier. Conclusion There is little cooperation among authors and between institutions in the field of early warning of infectious diseases in China. Using big data to early warning of infectious diseases and improving the ability of early warning of COVID-19 are the main research directions and trends at present.

Enhancing the Effectiveness of Surveillance Systems in Pacific Island Countries as Early Warning Systems for Detecting and Responding to COVID-19 Outbreaks: Key Strategies and Recommendations

@#The coronavirus disease 2019 (COVID-19) pandemic has uncovered the need for health systems to be strengthened in order to be able to respond quickly to any potential future outbreaks. In response, the Pacific Syndromic Surveillance System (PSSS) is currently being used by many countries within the Pacific Islands for tracking and addressing infectious disease outbreaks, including COVID-19. To maximise its usefulness as an early warning system, investments must be made in strengthening data quality, data sharing, health facility capacity, technology, and ongoing evaluation of surveillance systems. Doing so will ensure that the PSSS and other surveillance systems can remain effective tools for monitoring and respond to infectious disease outbreaks in the Pacific Islands

Emergency response of infectious snails detected after interruption of schistosomiasis transmission in Hannan District, Wuhan / 中国热带医学

@#Abstract: Objective　To analyze the emergency response and long-term intervention effects after the detection of infectious snails epidemic by loop-mediated isothermal amplification (LAMP) assays in Hannan District, Wuhan City, and to explore the application of LAMP in early surveillance and early-warning of schistosomiasis transmission. Methods Snails picked up by the risk monitoring system in Hannan District were examined by anatomical microscopy and LAMP technology to identify the schistosomiasis infection. Emergency response and intensive intervention were initiated in the environment where positive snails appeared, and the long-term effects were evaluated. Results In May 2018, the infectious snails were detected by LAMP technology in Hannan District, and the positive snails were located in Zhujiacha, Dongzhuang Village, Obstacles and weeds were removed and buried by machine in Zhujiacha. 12 700 m2 of snails were killed by drugs, and the mortality rate of snails was more than 80%; no new seropositive persons were found in the emergency examination within 500 m of the positive snail sites. 506 people were examined in Dong Zhuang Village at the end of the year, and 30 positive IHA cases were detected with a blood positive rate of 5.93%, no positive fecal test was found, and all positive blood test patients took preventive medication. The monitoring results of sentinel rats and wild feces were all negative. Health education was carried out, 7 warning signs were deployed and refreshed, and 500 publicity brochures were distributed. After nearly three years of intensified intervention and monitoring in the villages where the positive environment is located, and the density of snails on the stubborn snail has dropped from 0.094/frame to 0.027/frame, and the positive rate of blood test in Dongzhuang Village has steadily dropped from 5.93% to 3.74%. Conclusions The infected snails missed by microscopy were detected by LAMP in Hannan District, which created conditions for the rapid emergency treatment of environment and elimination of positive snail and improved the sensitivity of the surveillance and early warning system in transmission-interrupted areas.

Analysis of clinical characteristics and warning factors in SARS-CoV-2 variants infection / 中国热带医学

@#Abstract: Objective To investigate the influence of the variation of SARS-CoV-2 on the clinical feature, and to provide early warning signs for the variation of SARS-CoV-2 in clinical work. Methods From Jan 2, 2021 to Jun 30, 2021, a total of 105 COVID-19 patients were included in the study using a case-control method. Nasal swab samples were collected from the study subjects, the viral genes were sequenced, and patients were divided into Delta variant group and non-Delta variant group according to their gene sequences. Clinically relevant data were collected from the two groups, and indicators such as days of hospitalization, age distribution, lymphocytes, neutrophils, B lymphocytes, NK cells, IL-4, and IL-10 were compared; subgroup analysis was performed based on the number of days of viral negativity in the study subjects as the basis for grouping, and differences in immunological characteristics were compared, including lymphocytes, neutrophils, B lymphocytes, NK cells, IL-4, IL-10, etc. Results The theoretical hospitalization days of Delta variant group were (22.2±8.33) d, which were significantly longer than (17.6±10.50) d of non-Delta variant group (t=2.396, P<0.05). The total lymphocyte count and IL-4 of Delta variant group were (1.22±0.86) ×109/L and (0.80±0.23) ng/mL, which were significantly lower than corresponding (1.91±0.70) ×109/L and (1.59±0.59) ng/mL of non-Delta variant group (t=4.329, 9.072, P<0.05), while IL-10 was (7.16±7.77) ng/mL, which was significantly higher than (4.26±3.91) ng/mL of non-Delta mutation group (t=1.980, P<0.05). Subgroup analysis showed that the total lymphocyte count and IL-4 concentration in Delta variant group were (1.04±0.60) ×109/L and (0.74±0.25) ng/ml, which were significantly lower than corresponding (1.62±0.56) ×109/L and (1.56±0.52) ng/mL in non-Delta variant group, in patients with delayed discharge (P<0.05). Conclutions SARS-CoV-2 variant has an impact on clinical manifestations. The patient's B cell count and IL-10 concentration increased or IL-2 and IL-4 concentration decreased within 12 hours of admission indicated variant virus infection. The decrease of total lymphocyte count, especially T lymphocyte reduction, strongly suggests discharge delay due to viral clearance disorder.

Construction of intelligent fall warning model for the elderly based on plantar pressure / 中国实用护理杂志

Objective:To realize the accurate prediction of the fall risk of the elderly by a convolutional neural network prediction model.Methods:Stratified random cluster sampling was used from June 2019 to February 2020, Python′s Matlabplot library and Opencv library were used to perform data preprocessing on the plantar pressure data of 1 093 subjects who had come from medical institutionsand community or elderly care institutions of Chongqing and Nanjing, such as data visualization, compression and clipping, grayscale, Gaussian blur, etc., and then the data were divided into training set (983 cases) and verification set (110 cases), the training set data were used to train the convolutional neural network model, the verification set was used to verify the model, and the ReLU function was used to suppress overfitting to obtain the final prediction model.Results:The sensitivity of the fall warning model to the validation set for predicting falls was 91.2%, the specificity was 81.4%, the accuracy was 91.5%, and the AUC was 0.865.Conclusions:The fall prediction model can predict the fall risk of the elderly in a specific scenario. In the subsequent improvement, the software and hardware construction should be comprehensively improved to further improve the prediction accuracy.

Design of early warning system for mental health problems based on data mining and database / Projeto de sistema de alerta precoce para problemas de saúde mental com base na mineração de dados e banco de dados / Diseño de un sistema de alerta temprana de problemas de salud mental basado en la minería de datos y en la base de datos

ABSTRACT Introduction: Data mining technology is mainly employed in the era of big data to evaluate the acquired information. Subsequently, reasoning about the data inductively is fully automated to discover possible patterns. Objective: Recently, data mining technology in the national mental health database has deepened and can be effectively used to solve various mental health early warning problems. Methods: For example, it can be applied to mine psychological data and extract the most important features and information. Results: This paper presents the design of an early warning system for mental health problems based on data mining techniques to offer some thoughts on early warning of mental health problems, including data preparation, data mining, results in analysis, and decision tree algorithm. Conclusion: The experimental results indicate that the results of the early warning system in this paper can achieve an accuracy rate of more than 96% with a high accuracy rate. Level of evidence II; Therapeutic studies - investigating treatment outcomes.

RESUMO Introdução: A tecnologia de mineração de dados é empregada principalmente na era da big data para avaliar as informações adquiridas. Posteriormente, raciocinar indutivamente sobre os dados de forma totalmente automatizada para descobrir possíveis padrões. Objetivo: Recentemente, a tecnologia de mineração de dados no banco de dados nacional de saúde mental tem se aprofundado e pode ser efetivamente utilizada para resolver vários problemas de alerta precoce da saúde mental. Métodos: Por exemplo, ela pode ser aplicada para a mineração de dados psicológicos e extrair as características e informações mais importantes. Resultados: Este documento apresenta o projeto de um sistema de alerta precoce para problemas de saúde mental baseado em técnicas de mineração de dados, com o objetivo de oferecer algumas reflexões sobre alerta precoce de problemas de saúde mental, incluindo preparação de dados, mineração de dados, análise de resultados e algoritmo de árvore de decisão. Conclusão: Os resultados experimentais indicam que os resultados do sistema de alerta precoce neste trabalho podem alcançar uma taxa de precisão de mais de 96% com uma alta taxa de precisão. Nível de evidência II; Estudos terapêuticos - investigação dos resultados do tratamento.

Resumen Introducción: La tecnología de minería de datos se emplea principalmente en la era de la big data para evaluar la información adquirida. Posteriormente, razonar inductivamente sobre los datos de forma totalmente automatizada para descubrir posibles patrones. Objetivo: Recientemente, la tecnología de minería de datos en la base de datos nacional de salud mental se ha profundizado y puede ser utilizada eficazmente para resolver varios problemas de alerta temprana de salud mental. Métodos: Por ejemplo, puede aplicarse para minar datos psicológicos y extraer las características e información más importantes. Resultados: Este trabajo presenta el diseño de un sistema de alerta temprana de problemas de salud mental basado en técnicas de minería de datos, con el objetivo de ofrecer algunas reflexiones sobre la alerta temprana de problemas de salud mental, incluyendo la preparación de los datos, la minería de datos, el análisis de los resultados y el algoritmo de árbol de decisión. Conclusión: Los resultados experimentales indican que los resultados del sistema de alerta temprana de este documento pueden alcanzar un índice de precisión superior al 96% con un alto índice de precisión. Nivel de evidencia II; Estudios terapéuticos - investigación de los resultados del tratamiento.