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OBJECTIVE@#To investigate the value of optic disc retinal nerve fiber layer (RNFL) thickness in the diagnosis of diabetic peripheral neuropathy (DPN).@*METHODS@#Ninety patients with type 2 diabetes, including 60 patients without DPN (NDPN group) and 30 patients with DPN (DPN group), and 30 healthy participants (normal group) were enrolled. Optical coherence tomography (OCT) was used to measure the four quadrants and the overall average RNFL thickness of the optic disc. The receiver operator characteristic curve was drawn and the area under the curve (AUC) was calculated to evaluate the diagnostic value of RNFL thickness in the optic disc area for DPN.@*RESULTS@#The RNFL thickness of the DPN group was thinner than those of the normal and NDPN groups in the overall average ((101.07± 12.40) µm vs. (111.07±6.99) µm and (109.25±6.90) µm), superior quadrant ((123.00±19.04) µm vs. (138.93±14.16) µm and (134.47±14.34) µm), and inferior quadrant ((129.37±17.50) µm vs. (143.60±12.22) µm and (144.48±14.10) µm), and the differences were statistically significant. The diagnostic efficiencies of the overall average, superior quadrant, and inferior quadrant RNFL thicknesses, and a combined index of superior and inferior quadrant RNFL thicknesses were similar, and the AUCs were 0.739 (95% confidence interval (CI) 0.635-0.826), 0.683 (95% CI 0.576-0.778), 0.755 (95% CI 0.652-0.840), and 0.773 (95% CI 0.672-0.854), respectively. The diagnostic sensitivity of RNFL thickness in the superior quadrant reached 93.33%.@*CONCLUSIONS@#The thickness of the RNFL in the optic disc can be used as a diagnostic method for DPN.
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Objective To explore the value of determination of combined tumor markers based on artificial neural network (ANN) discrimination model in facilitating the diagnosis of hepatic carcinoma. Methods Serum samples were collected from three groups of subjects, including 50 cases of liver cancer, 40 cases of benign liver disease, and 50 normal controls. The levels of serum alpha fetoprotein (AFP), carbohydrate antigen 125 (CA125) and carcino-embryonic antigen (CEA) were determined by chemiluminescence immunoassay. The level of serum sialic acid (SA) was determined by spectrophotometry, the content of calcium in serum was measured by calcium assay kit (Azo-end method of arsenic HI). Based on the five tumor markers mentioned above as discrimination variables, Fisher discrimination and ANN were applied to set up the intelligent auxiliary diagnostic model. Results By applying the Fisher discrimination model established in present work, the diagnostic sensitivity of liver cancer was 46.1%, the specificity was 98.9%, the accurate rate was 79.3%, the positive predictive value was 95.8%, and the negative predictive value was 76.7% for the three groups. With the application of ANN discrimination model, the diagnostic sensitivity of liver cancer was raised to 96.0%, the specificity 98.9%, the accuracy 94.3%, the positive predictive value 98.0%, and the negative predictive value was 97.8%. Conclusion The diagnostic model based on ANN combined with 5 tumor markers is superior in diagnostic acuity to traditional Fisher discrimination analysis, thus more suitable for clinical data analysis.
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Objective To find a way to measure and count plane distribution of cells distributed on single layer and compare differences of undifferentiated mesenchymal cells of periosteum germinal layer from different parts of the body.Methods After counting the number of undifferentiated mesenchymal cells of periosteum germinal layer from different parts of the body microscopically and figuring out the number of cells per area unit in each periosteum specimen,the obtained data were statistically analyzed and the stratum structure of periosteum observed microscopically.Results The homogeneity of variance test showed homoscedasticity,with no statistical significance(P＞0.05).The analysis of variance found homoscedasticity but showed no statistical significance(F=0.253,P＞0.05).The periosteum of patel- la,tibial plateau and costa had two layers,while the periosteum of costal cartilage had three layers. Conclusions There is no conspicuous difference upon proliferation and evoluting activities of periosteum from different parts of body.Therefore,it is unnecessary to choose specific parts for drawing the periote- um in clinical situation.In the meantime,the structure of periosteum from different parts diversifies.