OBJECTIVETo observe the prevention effects of patients with lung exudation and pulmonary fibrosis induced by paraquat poisoning in sodium bicarbonate (SB) with gastric lavage, atomization inhalation and intravenous injection.

METHODSTo collect 38 patients with paraquat poisoning in hospital, after poison immediately with gastric lavage of 1.5% SB, and atomization inhalation of 5% SB 10~15 ml twice daily and intravenous injection of 5% SB twice a day, continuous application of 5~7 days. and the HRCT score and liver and kidney function was performed on patients with lung after treatment. And the extraction of 38 SB patients with previously untreated with SB for comparison.

RESULTSLung HRCT average score in 72 h, 7 d, 30 d on patients with paraquat poisoning untreated with SB reached 2.87, 3.12, 2.13, HRCT display shows that the appearance of the wear glass shadow, grid shadow, honeycomb shadow, and other signs of fibrosis. Average HRCT reached 1.95, 2.20, 1.67 on patients treated with SB,signs of lung exudation and fibrosis was significantly reduced,compare two groups,there was statistically significance (P<0.01). And compared to the control group, activity of serum alanine aminotransferase (ALT) and aspartic acid transaminase (AST) decreased significantly in group of paraquat poisoning with triple application of SB, the level of serum urea nitrogen (BUN) and creatinine (Cr) significantly decreased, the difference is statistically significant (P<0.01).

CONCLUSIONThe triple application of SB can reduced the pulmonary fibrosis and effusion induced by paraquat poisoning,and protective effect on the function of liver and kidney is obvious, suggesting that the method for treatment of paraquat poisoning, prevention of paraquat lung and improve survival rate has the exact effect.

Blood Urea Nitrogen ; Creatinine ; blood ; Gastric Lavage ; Humans ; Injections, Intravenous ; Lung ; pathology ; Paraquat ; poisoning ; Pulmonary Fibrosis ; chemically induced ; therapy ; Sodium Bicarbonate ; therapeutic use ; Survival Rate

Objective To develop a mammogram microcalcification detection model(DL model)based on Attention U-Net for realizing the efficient detection of microcalcifications,and to investigate the effects of breast density and microcalcification type on the microcalcification detection performance of the DL model.Methods A retrospective analysis was performed on 694 images from 347 patients undergoing mammography.Through the independent image diagnosis by junior physicians and review by senior physicians,the reference standard for microcalcification detection was established.Neural network training was performed to establish a DL model.The performance of the model for microcalcification detection was evaluated using precision rate,recall rate,intersection over union(IoU)and F1-score which were calculated based on calcification area or quantity;and the effects of microcalcification type(benignvsmalignant)and breast density(a+bvsc+d)on the model performance were also analyzed.Results For detecting microcalcifications by the DL model,the precision rate,recall rate,IoU and F1-score were 85.12%±18.39%,78.18%±19.25%,68.29%±21.39%and 78.96%±17.70%when the calculation was based on calcification area,and those were 76.72%±19.85%,85.12%±18.39%,67.13%±23.84%and 77.65%±9.37%when the calculation was based on calcification quantity.The differences in precision rate,recall rate,IoU,F1-score of DL model in different microcalcification types(benignvsmalignant)and breast densities(a+bvsc+d)were insignificant.Conclusion The developed mammogram microcalcification detection model based on Attention U-Net can effectively detect breast microcalcifications and is conducive to the quantitative research on breast microcalcifications.Meanwhile,the model exhibits high stability,and the breast density and microcalcification type have trivial effects on the microcalcification detection performance of the model.