[Point system in diagnostics of the gallbladder cholesterosis].
OBJECTIVE
Development of scoring systems of diagnostics of gallbladder cholesterolosis (GBC) on the grounds of clinical and laboratory-instrumental parameters determined in the general clinical practice.


METHODS
For development of the scoring systems, the methods of the logistic regression (LR) and artificial neuron networks (ANN) were used. The results of specially carried clinical observations of 124 patients, who had cholelithiasis with morphological confirmation of presence of GBC or chronic cholecystitis after planned cholecystectomy, were analysed.


RESULTS
The scoring systems of diagnostics of GBC have been created: the detailed scring system, subjected to 24 parameters (12 quantitative ones; 12 qualitative ones) and the diminished scring system subjected to 6 the most informative parameters (3 clinical ones, 3 ultrasonic signs). Using the detailed scoring system of diagnostics of GBC allowed to set a correct diagnosis in 83,8% cases, specificity of the method was 91.80%, sensitiveness--92.11%. Diminished scoring system provides the correct diagnostics of GBC in 68% cases, the model specificity--63.41%, sensitiveness--63.77%.


CONCLUSIONS
Using LR and ANN allowed to evaluate the influence of individual clinical and laboratory-instrumental parameters on probability of the GBC diagnosis. Developed scoring systems open new possibilities of the early diagnosing of this disease that enables to conduct the identical medication treatment in proper time, cut off clinical presentations and prevent the development of cholelithiasis.
Shcherbinina
M B
MB
Zakrevskaia
E V
EV
Baĭbuz
O G
OG
Emel'ianenko
T G
TG
D042101:Acalculous Cholecystitis / Q000150:complications / Q000175:diagnosis* / Q000000981:diagnostic imaging / Q000188:drug therapy; D000328:Adult; D000368:Aged; D002769:Cholelithiasis / Q000209:etiology / Q000517:prevention & control; D003938:Diagnostic Techniques, Digestive System / Q000706:statistics & numerical data; D042241:Early Diagnosis; D005260:Female; D006801:Humans; D016015:Logistic Models; D008297:Male; D008875:Middle Aged; D016571:Neural Networks, Computer; D012680:Sensitivity and Specificity; D014463:Ultrasonography