scholarly journals Bayesian Recognition Procedures with Independent Signs of Inflammatory Processes in Gliomas, Metastases and Meningiomas by Indicators of Erythrocyte Sedimentation Rate

Author(s):  
Andrii Tarasov

Introduction. The article discusses the application of Bayesian recognition procedures with independent signs in relation to the data of the modified erythrocyte sedimentation rate, which were taken from patients with gliomas, metastases, meningiomas, craniocerebral concussion and from a group of healthy people. Purpose of the article. Improving the efficiency of recognition of inflammatory processes in gliomas, metastases and meningiomas by indicators of erythrocyte sedimentation rate using optimal recognition procedures with independent signs. Results. In previous articles by the authors, an attempt was made to recognize inflammatory processes by indicators of the modified erythrocyte sedimentation rate caused by brain cancer using Bayesian recognition procedures based on a single substance. In this work, a new model was built using several independent signs (different substances) at once. The results obtained on the basis of the new model significantly increased their efficiency in relation to the models that were used earlier. Such an increase in all comparisons ranged from 3 to 12 %, and up to almost 94 %. If earlier it was possible to recognize only combinations of diagnoses in which there were no more than two diagnoses, then in this work for the first time it was possible to recognize three diagnoses at once. At the same time, the recognition efficiency became slightly more than 70 %. An attempt was also made to recognize more than three diagnoses, but the new model did not give significant results, slightly exceeding 50 % when recognizing four diagnoses at once. Conclusions. Thanks to the use of Bayesian recognition procedures with independent signs, it was possible to significantly increase the recognition of inflammatory processes caused by brain cancer. The modified erythrocyte sedimentation rate, which is an auxiliary tool in the diagnosis of gliomas, allows one or another pathology to be determined in the preoperative period, since the pathology is finally determined only when studying a surgically removed tumor. In the postoperative period, such a modification is an indicator of repeated recurrence of gliomas. It was also possible to significantly increase the recognition of inflammatory processes caused by non-oncological disease (traumatic brain injury) in relation to oncological processes in gliomas, metastases and meningiomas. Keywords: Bayesian recognition procedure, independent signs, gliomas, metastases, meningiomas, modified erythrocyte sedimentation rate, complex parameter.

Author(s):  
A.L. Tarasov ◽  
A.M. Gupal ◽  
N.Ya. Gridina

Introduction. The article discusses the application of Bayesian recognition procedures with one independent feature in relation to the erythrocyte sedimentation rate data taken from patients with gliomas, metastases, meningiomas, traumatic brain injury and from a group of healthy people. Purpose of the article. Analysis of erythrocyte sedimentation rate indicators using optimal recognition procedures. Results. In earlier articles by the authors, a similar work was described, however, due to the fact that the erythrocyte sedimentation rate was measured in different concentrations of pharmaceuticals and due to the receipt of new data structures, it was possible to increase the efficiency of the recognition procedures by 3-4%. The maximum recognition efficiency of almost 90% was achieved in the differential diagnosis of gliomas in relation to traumatic brain injury and the use of a substance supplemented with chlorpromazine. When recognizing inflammatory processes in patients with metatsases in relation to a group of healthy people, the efficiency of the recognition procedure was 88% using NaATF with a dilution of 1:10. We also note a 4% increase in the recognition efficiency of conditionally benign grade II gliomas, i.e. the efficiency of recognition of the development of gliomas in the early stages increased. Also in this work, it was possible to identify inflammatory processes in benign extracerebral tumors - meningiomas. The effectiveness of this recognition in relation to a group of healthy people was 83%. Conclusions. New results of recognition of inflammatory processes in brain gliomas have been obtained, on the basis of which an auxiliary diagnostic tool has been improved in gliomas, metastases and meningiomas. This diagnostic method becomes especially valuable in cases where modern imaging diagnostic methods are not able to determine the presence of a tumor in a patient, as well as in the postoperative period with indulgent tumor growth. Keywords: Bayesian recognition procedure, gliomas, metastases, meningiomas, erythrocyte sedimentation rate, complex parameter.


2008 ◽  
Vol 24 (5) ◽  
pp. 351
Author(s):  
Young Ki Kim ◽  
Seong Woo Hong ◽  
Jung Woo Chun ◽  
Yeo Goo Chang ◽  
In Wook Paik ◽  
...  

2021 ◽  
pp. 1-7
Author(s):  
Zahra Soleimani ◽  
Fatemeh Amighi ◽  
Zarichehr Vakili ◽  
Mansooreh Momen-Heravi ◽  
Seyyed Alireza Moravveji

BACKGROUND: The diagnosis of osteomyelitis is a key step of diabetic foot management. Procalcitonin (PCT) is a novel infection marker. This study aimed to investigate the diagnostic value of procalcitonin and other conventional infection markers and clinical findings in diagnosis of osteomyelitis in diabetic foot patients. METHODS AND MATERIALS: This diagnostic value study was carried out on ninety patients with diabetic infected foot ulcers admitted in Kashan Beheshti Hospital, 2016. After obtaining consent, 10 cc blood sample was taken for measuring serum PCT, CBC, ESR, CRP and FBS. Clinical characteristics of the wounds were noted. Magnetic resonance imaging of the foot was performed in all patients to diagnose osteomyelitis. All statistical analyses were done with the use of SPSS-16. RESULTS: PCT levels were 0.13 ± 0.02 ng/mili patients with osteomyelitis (n= 45) and 0.04 ± 0.02 ng/ml in patients without osteomyelitis (n= 45). PCT, Erythrocyte sedimentation rate and C-reactive protein was found significantly higher in patients with osteomyelitis (p< 0.001). The ROC curve was calculated for PCT. The area under the ROC curve for infection identification was 1 (p< 0.001). The best cut-off value for PCT was 0.085 ng/ml. Sensitivity, specificity, and positive and negative predictive values were 100%, 97.8%,97.8% and 100%, respectively. CONCLUSION: In this group of patients, PCT was useful to discriminate patients with bone infection. Also, Erythrocyte sedimentation rate and C-reactive protein can be used as a marker of osteomyelitis in diabetic patients.


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