Objective To analyze the results of the final aviation medical examination of 1281 students recruited into Air Force youth aviation schools in Hunan and Hubei provinces in order to provide reference for establishing the items and standards of medical selection .Methods The data of 1281 students who participated in final aviation medical examination of Air Force youth aviation schools in 2016 were collected , who came from 28 cities in the above two provinces .The disqualification rate and related unqualified medical items were calculated , and the differences of the disqualification rate and medical geographical areas in the 28 cities were analyzed .Results According to the disqualification rate , the top five departments were ophthalmology , otolaryngology, surgery, radiology and ultrasonic departments .The top 10 unqualified items were the lack of distant vision , fundus diseases , nasal anomaly , ametropia and strabismus , spine abnormality , audition abnormality, vestibular function badness , vitreous opacity, and lens abnormalities.There was no significant difference between the 28 cities in the disqualification rate (P >0.05) or between the two provinces (P >0.05). Conclusion The results of the final aviation medical examination reflect the quality and efficiency of the initial aviation medical examination .To improve the quality of medical selection , further research is needed to set a scientific standard for the initial aviation medical examination while strengthening the scientific protection and intervention of distant vision .The efficiency of selection depends on improving the accuracy of initial aviation medical examination in nasal cavity structure, body shape ,and lens opacity .With a better understanding of the disqualification rate and abnormal items in different cities , a scientific arrangement of professional staff and technical force can make the initial aviation medical examination better, thus effectively reducing the rate of false elimination rate and misdiagnosis .

Objective To develop a nomogram based on pulmonary nodules preoperative CT signs and 3D quantitative parameters for predicting mediastinal lymph node metastases in patients with clinical stage ⅠA lung adenocarcinoma.Methods The imaging data of 164 patients who underwent preoperative CT scan and systematic lymph node dissection were analyzed retrospectively.Commercially available AI software was used to extract 3D quantitative parameters of pulmonary nodules automatically,and CT signs of pulmonary nodules were analyzed.Logistic regression was used to explore the role of these parameters in predicting pathological nodal involvement.A nomogram prediction model was established,then discrimination and calibration of the model were evaluated.Results Among 164 enrolled patients,19(11.6％)were tested positive for mediastinal lymph node metastases at pathology review.The nomogram incorporated spiculation,lobulation,the largest cross-sectional area,and carcinoembryonic antigen(CEA).The model showed great discrimination and calibration,with a C-index of 0.942[95％confidence interval(CI)0.923-0.961].The predicted value of the model fitted well with the actual observed value on the calibration curve.Conclusion The nomogram prediction model based on preoperative CT signs,3D quantitative parameters,and CEA can estimate the probability of mediastinal lymph node metastases in clinical stage ⅠA lung adenocarcinoma.This model may help with clinical decision-making and individualized evaluation.