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Objective To analyze the comparison of viral meningitis / the encephalitis (disease brain) and the other three common intracranial infection (tuberculous meningoencephalitis, suppurative meningoencephalitis and cryptococcal meningoencephalitis) in the clinical features, laboratory data and differences on the imaging data were established disease brain has practical value differential diagnosis evaluation model. Methods A retrospective survey method to collect Xiangya Hospital from January 2004 to December 2010, the Second Xiangya Hospital, Hunan Provincial People's Hospital, Changsha Central Hospital the God of Internal four common intracranial infection in patients with clinical data , laboratory test results and imaging data, and according to the diagnosis of the corresponding disease brain is divided into groups, group tuberculous meningitis, cryptococcal meningitis group of brain group tuberculous meningitis group, cryptococcal meningitis group and brain group combined into non-disease brain group . The disease brain group and the four groups, respectively, for comparative analysis. Univariate analysis using X2 test, t test method. In univariate analysis, P values ??less than or equal to 0.05 variable multivariate analysis, the Logistic regression methods, screening potential differential diagnosis factor gradually establish the prediction model of the clinical differential diagnosis between disease brain and intracranial infection and score based on the p-value assignment model. Assignment weighted scoring model to evaluate the receiver operating characteristic curve (ROC) analysis. The results of the study, a total of 910 cases of intracranial infection patients met the inclusion criteria, including 481 cases of viral meningitis, 349 cases of tuberculous meningitis, cryptococcal meningitis, 31 cases, 49 cases of the brain. Respectively, and the comparison of different control group in disease brain group univariate analysis, the presence of multiple indicators statistically significant. Age, onset days and epilepsy, cerebrospinal fluid pressure, cerebrospinal fluid white blood cell count, cerebrospinal fluid neutrophil ratio, cerebrospinal fluid monocytes ratios, cerebrospinal fluid protein content, cerebrospinal fluid chloride content in the group of viral meningitis and tuberculous meningitis group, disease brain group meningitis group, disease the brain group with cryptococcal meningitis group and disease brain group analysis with the single factor of the group of non-disease brain, there is a statistically significant difference (P ≤ 0.05). Finally, multivariate analyzes were successfully established disease brain with tuberculous meningitis disease brain of brain disease brain and non-disease brain differential diagnosis scoring model. The The three scoring model back cases of differential diagnosis, the sensitivity and specificity were 87.4% and 94.3%, 96.4% and 79.2% and 90.2% and 84.4%. Conclusion of the Institute were established disease brain and meningitis, viral meningitis and tuberculous meningitis disease brain and non-disease brain differential diagnosis scoring model has a high diagnostic predictive performance expected for disease brain and the other three common cranial within the differential diagnosis of infection.
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