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Objective:To provide a scientific basis for reducing the rate of invalid ambulance attendance and the establishment of grades dispatch system through a retrospective analysis of the invalid ambulance attendance in prehospital emergency care.Methods:The data of the invalid ambulance attendance was collected in Huazhong University of Science and Technology Union Shenzhen Hospital (the only tertiary hospital of in Nanshan District) from 2014 to 2018, and the reasons of the invalid ambulance attendance, the time period during the invalid ambulance attendance occurred (every 3 hours was divided into one time period), and the reasons of ambulance calling were statistically analyzed.Results:① The invalid ambulance attendance rates showed a fluctuating decrease trend year by year from 2014 to 2018, the rates were 31.22% (2 515/8 055), 26.94% (2 147/7 970), 29.80% (2 398/8 046), 25.69% (1 844/7 177) and 21.89% (1 686/7 703), respectively. The total invalid ambulance attendance rate was 27.19% (10 590/38 951) in the five years. ② The top three reasons for the invalid ambulance attendance were cancelled calls, departure before the ambulance arrived, and going to hospital by themselves, accounting for 36.87%, 25.08%, and 17.03%, respectively. The constituent ratios of the causes of invalid ambulance attendance in each year were different with statistical significance (χ 2 = 217.626, P < 0.001). ③ The top three time period of invalid ambulance attendance occurred at 21:00-23:59, 18:00-20:59 and 09:00-11:59, accounting for 16.86%, 14.95% and 13.54%, respectively. There was no statistical significance in the distribution of time period in each year (χ 2 = 32.571, P = 0.252). ④ The top five reasons for ambulance calling of invalid ambulance attendance were fainting/syncope, trauma, alcoholism, traffic accident injuries, and brawls, accounting for 20.13%, 15.67%, 9.97%, 8.64%, and 6.45%, respectively, and there was statistically significant difference in the distribution of the reason for ambulance calls in each year (χ 2 = 194.213, P < 0.001). Conclusion:The invalid ambulance attendance rate is high in Nanshan District of Shenzhen. Improving the professional level and triage ability of the dispatchers, improving the system construction of prehospital emergency care system and increasing social education are conducive to reduce invalid ambulance attendance rate.
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The paper takes heart disease dataset of UCI as experimental data,carries out disease diagnosis and calssification based on the deep learning technology of machine learning,compares with Random Forest (RF),Support Vector Machine (SVM) and Neural Network (NN) classification,and indicates that the Deep Learning (DL) technology is of great potential and important value for exploration of medical big data.
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Controlled attenuation parameter (CAP)is a noninvasive,quantitative,fast,and reliable novel tool for the assessment of fatty liver disease (FLD),and it has been a hotspot in the noninvasive diagnosis of FLD.This paper introduces factors associated with CAP asses-sing FLD,the cut -off value for the diagnosis of liver steatosis,and the causes of the failure of CAP measurement and unreliable CAP meas-urement.The paper believes that even though the noninvasive and quantitative diagnosis of FLD by CAP has been confirmed by many stud-ies,most of the results were obtained with a limited sample size.Therefore,the factors associated with the cut -off value for CAP diagnosing liver steatosis and factors influencing the measurement results still need validation with larger samples and multi -centered research reports.