Prínos Bayesovy statistické teorie pro diagnostiku maligních a nemaligních onemocnĕní plic, pleury a mediastina
[The Bayesian statistical theory in the diagnosis of malignant and non-malignant diseases of the lung, pleura and mediastinum]
Language Czech Country Czech Republic Media print
Document type Journal Article
PubMed
8269461
- MeSH
- Bayes Theorem MeSH
- Diagnosis, Computer-Assisted * MeSH
- Diagnosis, Differential MeSH
- Adult MeSH
- Middle Aged MeSH
- Humans MeSH
- Adolescent MeSH
- Mediastinal Neoplasms diagnosis diagnostic imaging MeSH
- Pleural Neoplasms diagnosis diagnostic imaging MeSH
- Lung Neoplasms diagnosis diagnostic imaging MeSH
- Mediastinal Diseases diagnosis diagnostic imaging MeSH
- Pleural Diseases diagnosis diagnostic imaging MeSH
- Lung Diseases diagnosis diagnostic imaging MeSH
- Radiography MeSH
- Aged, 80 and over MeSH
- Aged MeSH
- Sensitivity and Specificity MeSH
- Check Tag
- Adult MeSH
- Middle Aged MeSH
- Humans MeSH
- Adolescent MeSH
- Male MeSH
- Aged, 80 and over MeSH
- Aged MeSH
- Female MeSH
- Publication type
- Journal Article MeSH
The Bayesian algorithm was used to assess the probable diagnosis in 1262 patients with a recently diagnosed finding on X-rays of the chest and the results were compared with the final diagnosis. The patients were with regard to the X-ray picture divided into 9 groups: hilar, solitary, multiple, segmental, non-segmental, cavity, diffuse, pleural and mediastinal lesions. Using the Bayesian algorithm, commonly accessible factors were processed: age, sex, case-history, cigarette smoking, red cell sedimentation rate, number of leucocytes and diameter of solitary parenchymatous lesions and the impact of these factors for assessment of probability of a malignant or non-malignant lesion was evaluated. The reliability in different X-ray lesions was within the range of 84.2% to 92.4%. The authors evaluated also tests of sensitivity, specificity, the reliability of forecast of a positive and negative result, which confirmed the differences in the different groups which showed evaluated. Analysis of the results, provided evidence that the Bayesian algorithm is a promising objective method for the forecast of a malignant or non-malignant diagnosis in patients with a newly diagnosed X-ray finding of the chest.