Prediction of inflammation in hemodialysis patients using neural network analysis
Background. Numerous hemodialysis patients (HD) suffer from severe, life-threatening inflammation that must be treated to prevent further complications. Early diagnosis of inflammation in HD is highly needed. The present study used matrix metalloproteinase-1 (MMP3) and tissue inhibitor of metallopro...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | Russian |
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Sankt-Peterburg : NIIÈM imeni Pastera
2023-11-01
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| Series: | Инфекция и иммунитет |
| Subjects: | |
| Online Access: | https://iimmun.ru/iimm/article/viewFile/15622/1786 |
| _version_ | 1827582507677122560 |
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| author | Hadi H. Hadi Hawraa H. Al-Mayali Habiba K. Abdalsada Shatha R. Moustafa Abbas F. Almulla Hussein K. Al-Hakeim |
| author_facet | Hadi H. Hadi Hawraa H. Al-Mayali Habiba K. Abdalsada Shatha R. Moustafa Abbas F. Almulla Hussein K. Al-Hakeim |
| author_sort | Hadi H. Hadi |
| collection | DOAJ |
| description | Background. Numerous hemodialysis patients (HD) suffer from severe, life-threatening inflammation that must be treated to prevent further complications. Early diagnosis of inflammation in HD is highly needed. The present study used matrix metalloproteinase-1 (MMP3) and tissue inhibitor of metalloproteinases-1 (TIMP1) to differentiate between patients with/without inflammation using the neural network analysis (NN).
Methods. The positive results of C-reactive protein were used as a criterion for the presence of inflammation in the patients (HD+CRP) versus the negative group (HD-CRP). The NN analysis was used to discriminate between groups using the measured biomarkers.
Results. HD+CRP patients have a higher duration of disease, MMP3 and lower calcium than the HD-CRP level is significantly higher, while vitamin D is significantly lower in the HD+CRP group compared with both other groups (all p0.05). TIMP1 is significantly correlated with inorganic phosphate and CRP. In NN#1, the model for the prediction of HD+CRP from HD-CRP has an area under the curve (AUC) of the receiver operating characteristic (ROC) of 0.907 with a sensitivity and specificity 89.2% and a specificity of 100.0%. The top predicting variable for the prediction of HD+CRP is MMP3 (100%), followed by creatinine (87.1%). MMP3 is linked to the pathophysiology of HD, at least through their correlation with the inflammation in HD. In NN#2, the AUC of the ROC for predicting the kidney disease and subsequent HD was 98.9%, with a sensitivity of 100.0% and a specificity of 97.1%. The top four predicting variables for the prediction of high risk of inflammation in HD patients are urea (100%), creatinine (100%), MMP3 (59.7%), and vitamin D (57.1%).
Conclusion. The NN analysis may differentiate between HD patients with inflammation from the HD without inflammation. Also, the measured parameters, especially MMP3, TIMP1, and vitamin D are useful as a diagnostic tools for the kidney diseases and inflammation linked with the disease. |
| first_indexed | 2024-03-08T22:52:50Z |
| format | Article |
| id | doaj.art-bb67bc13fb874262bcf73b51a64447fc |
| institution | Directory Open Access Journal |
| issn | 2220-7619 2313-7398 |
| language | Russian |
| last_indexed | 2024-03-08T22:52:50Z |
| publishDate | 2023-11-01 |
| publisher | Sankt-Peterburg : NIIÈM imeni Pastera |
| record_format | Article |
| series | Инфекция и иммунитет |
| spelling | doaj.art-bb67bc13fb874262bcf73b51a64447fc2023-12-16T10:50:05ZrusSankt-Peterburg : NIIÈM imeni PasteraИнфекция и иммунитет2220-76192313-73982023-11-0113595796610.15789/2220-7619-POI-156221338Prediction of inflammation in hemodialysis patients using neural network analysisHadi H. Hadi0Hawraa H. Al-Mayali1Habiba K. Abdalsada2Shatha R. Moustafa3Abbas F. Almulla4Hussein K. Al-Hakeim5https://orcid.org/0000-0001-6143-5196University of KufaAl-Furat Al-Awsat Technical UniversityAl-Muthanna UniversityHawler Medical UniversityThe Islamic UniversityUniversity of KufaBackground. Numerous hemodialysis patients (HD) suffer from severe, life-threatening inflammation that must be treated to prevent further complications. Early diagnosis of inflammation in HD is highly needed. The present study used matrix metalloproteinase-1 (MMP3) and tissue inhibitor of metalloproteinases-1 (TIMP1) to differentiate between patients with/without inflammation using the neural network analysis (NN). Methods. The positive results of C-reactive protein were used as a criterion for the presence of inflammation in the patients (HD+CRP) versus the negative group (HD-CRP). The NN analysis was used to discriminate between groups using the measured biomarkers. Results. HD+CRP patients have a higher duration of disease, MMP3 and lower calcium than the HD-CRP level is significantly higher, while vitamin D is significantly lower in the HD+CRP group compared with both other groups (all p0.05). TIMP1 is significantly correlated with inorganic phosphate and CRP. In NN#1, the model for the prediction of HD+CRP from HD-CRP has an area under the curve (AUC) of the receiver operating characteristic (ROC) of 0.907 with a sensitivity and specificity 89.2% and a specificity of 100.0%. The top predicting variable for the prediction of HD+CRP is MMP3 (100%), followed by creatinine (87.1%). MMP3 is linked to the pathophysiology of HD, at least through their correlation with the inflammation in HD. In NN#2, the AUC of the ROC for predicting the kidney disease and subsequent HD was 98.9%, with a sensitivity of 100.0% and a specificity of 97.1%. The top four predicting variables for the prediction of high risk of inflammation in HD patients are urea (100%), creatinine (100%), MMP3 (59.7%), and vitamin D (57.1%). Conclusion. The NN analysis may differentiate between HD patients with inflammation from the HD without inflammation. Also, the measured parameters, especially MMP3, TIMP1, and vitamin D are useful as a diagnostic tools for the kidney diseases and inflammation linked with the disease.https://iimmun.ru/iimm/article/viewFile/15622/1786hemodialysis patients (hd)tissue inhibitor of metalloproteinases-1 (timp1)matrix metalloproteinase-1 (mmp3)vitamin dneural networkinflammation |
| spellingShingle | Hadi H. Hadi Hawraa H. Al-Mayali Habiba K. Abdalsada Shatha R. Moustafa Abbas F. Almulla Hussein K. Al-Hakeim Prediction of inflammation in hemodialysis patients using neural network analysis Инфекция и иммунитет hemodialysis patients (hd) tissue inhibitor of metalloproteinases-1 (timp1) matrix metalloproteinase-1 (mmp3) vitamin d neural network inflammation |
| title | Prediction of inflammation in hemodialysis patients using neural network analysis |
| title_full | Prediction of inflammation in hemodialysis patients using neural network analysis |
| title_fullStr | Prediction of inflammation in hemodialysis patients using neural network analysis |
| title_full_unstemmed | Prediction of inflammation in hemodialysis patients using neural network analysis |
| title_short | Prediction of inflammation in hemodialysis patients using neural network analysis |
| title_sort | prediction of inflammation in hemodialysis patients using neural network analysis |
| topic | hemodialysis patients (hd) tissue inhibitor of metalloproteinases-1 (timp1) matrix metalloproteinase-1 (mmp3) vitamin d neural network inflammation |
| url | https://iimmun.ru/iimm/article/viewFile/15622/1786 |
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