1.Research progress of immunoscore
Xinru ZHAO ; Yuye ZHAO ; Guohong LI ; Xuan KAN ; Zuoxing NIU
Journal of International Oncology 2016;43(10):772-774
A methodology named immunoscorehas been proposed in recent years.It has been demonstrated to be a prognostic factor superior to the Union for International Cancer Control-American Joint Committee on Cancer (UICC-AJCC)TNMclassification.Over the past few years,it has gained a forefront posi-tion in colorectal cancer.It has the advantages of simple operation,low cost and high accuracy,and it is nee-ded for individual therapy.However,it still has its limitations.
2.Statistics and Analysis of 136 Cases of Adverse Events of International Medical Devices.
Fei ZHAO ; Mingxian GAO ; Pu LIU ; Yang WANG ; Hangyao ZHANG ; Yuye ZHANG ; Qin ZHAN ; Shouli WANG
Chinese Journal of Medical Instrumentation 2020;44(2):166-171
To explore the law and characteristics of adverse events of medical devices and to provide research methods and basis for reducing the recurrence of similar adverse events, we collect medical devices safety information from five representative countries in the world, and make statistics and analysis on the types of events, the types of management and the causes of events. The results show that among 136 serious adverse events, the top three causes of recall are product design factors, software factors, and component defects. In order to reduce the application risk of medical devices, it is suggested that product designers, operating users and medical institutions should correctly implement the monitoring and evaluation system of medical devices.
Equipment Safety
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Equipment and Supplies/adverse effects*
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Product Surveillance, Postmarketing
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Software
3.Establishment of risk prediction nomograph model for sepsis related acute respiratory distress syndrome.
Chunling ZHAO ; Yuye LI ; Qiuyi WANG ; Guowei YU ; Peng HU ; Lei ZHANG ; Meirong LIU ; Hongyan YUAN ; Peicong YOU
Chinese Critical Care Medicine 2023;35(7):714-718
OBJECTIVE:
To explore the risk factors of acute respiratory distress syndrome (ARDS) in patients with sepsis and to construct a risk nomogram model.
METHODS:
The clinical data of 234 sepsis patients admitted to the intensive care unit (ICU) of Tianjin Hospital from January 2019 to May 2022 were retrospectively analyzed. The patients were divided into non-ARDS group (156 cases) and ARDS group (78 cases) according to the presence or absence of ARDS. The gender, age, hypertension, diabetes, coronary heart disease, smoking history, history of alcoholism, temperature, respiratory rate (RR), mean arterial pressure (MAP), pulmonary infection, white blood cell count (WBC), hemoglobin (Hb), platelet count (PLT), prothrombin time (PT), activated partial thromboplastin time (APTT), fibrinogen (FIB), D-dimer, oxygenation index (PaO2/FiO2), lactic acid (Lac), procalcitonin (PCT), brain natriuretic peptide (BNP), albumin (ALB), blood urea nitrogen (BUN), serum creatinine (SCr), acute physiology and chronic health evaluation II (APACHE II), sequential organ failure assessment (SOFA) were compared between the two groups. Univariate and multivariate Logistic regression were used to analyze the risk factors of sepsis related ARDS. Based on the screened independent risk factors, a nomogram prediction model was constructed, and Bootstrap method was used for internal verification. The receiver operator characteristic curve (ROC curve) was drawn, and the area under the ROC curve (AUC) was calculated to verify the prediction and accuracy of the model.
RESULTS:
There were no significant differences in gender, age, hypertension, diabetes, coronary heart disease, smoking history, alcoholism history, temperature, WBC, Hb, PLT, PT, APTT, FIB, PCT, BNP and SCr between the two groups. There were significant differences in RR, MAP, pulmonary infection, D-dimer, PaO2/FiO2, Lac, ALB, BUN, APACHE II score and SOFA score (all P < 0.05). Multivariate Logistic regression analysis showed that increased RR, low MAP, pulmonary infection, high Lac and high APACHE II score were independent risk factors for sepsis related ARDS [RR: odds ratio (OR) = 1.167, 95% confidence interval (95%CI) was 1.019-1.336; MAP: OR = 0.962, 95%CI was 0.932-0.994; pulmonary infection: OR = 0.428, 95%CI was 0.189-0.966; Lac: OR = 1.684, 95%CI was 1.036-2.735; APACHE II score: OR = 1.577, 95%CI was 1.202-2.067; all P < 0.05]. Based on the above independent risk factors, a risk nomograph model was established to predict sepsis related ARDS (accuracy was 81.62%, sensitivity was 66.67%, specificity was 89.10%). The predicted values were basically consistent with the measured values, and the AUC was 0.866 (95%CI was 0.819-0.914).
CONCLUSIONS
Increased RR, low MAP, pulmonary infection, high Lac and high APACHE II score are independent risk factors for sepsis related ARDS. Establishment of a risk nomograph model based on these factors may guide to predict the risk of ARDS in sepsis patients.
Humans
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Retrospective Studies
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Alcoholism
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Prognosis
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Respiratory Distress Syndrome
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Pneumonia
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Sepsis
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Intensive Care Units
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Procalcitonin
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Fibrinogen
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ROC Curve