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Metabolomic Profiles Predict Diabetes Remission after Bariatric Surgery
DC Field | Value | Language |
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dc.contributor.author | Ha, J | - |
dc.contributor.author | Jang, M | - |
dc.contributor.author | Kwon, Y | - |
dc.contributor.author | Park, YS | - |
dc.contributor.author | Park, DJ | - |
dc.contributor.author | Lee, JH | - |
dc.contributor.author | Lee, HJ | - |
dc.contributor.author | Ha, TK | - |
dc.contributor.author | Kim, YJ | - |
dc.contributor.author | Han, SM | - |
dc.contributor.author | Han, SU | - |
dc.contributor.author | Heo, Y | - |
dc.contributor.author | Park, S | - |
dc.date.accessioned | 2022-12-07T05:53:18Z | - |
dc.date.available | 2022-12-07T05:53:18Z | - |
dc.date.issued | 2020 | - |
dc.identifier.uri | http://repository.ajou.ac.kr/handle/201003/23120 | - |
dc.description.abstract | BACKGROUND: Amino acid metabolites (AAMs) have been linked to glucose homeostasis and type 2 diabetes (T2D). We investigated whether (1) baseline AAMs predict T2D remission 12 months after bariatric surgery and (2) whether AAMs are superior for predicting T2D remission postoperatively compared with existing prediction models. METHODS: Among 24 participants undergoing bariatric surgery, 16 diabetes-related AAMs were quantified at baseline and postoperative 3 and 12 months. Existing prediction models included the ABCD, DiaRem, and IMS models. RESULTS: Baseline L-dihydroxyphenylalanine (L-DOPA) (areas under receiver operating characteristic curves (AUROC), 0.92; 95% confidence interval (CI), 0.75 to 1.00) and 3-hydroxyanthranilic acid (3-HAA) (AUROC, 0.85; 95% CI, 0.67 to 1.00) better predicted T2D remission 12 months postoperatively than the ABCD model (AUROC, 0.81; 95% CI, 0.54 to 1.00), which presented the highest AUROC value among the three models. The superior prognostic performance of L-DOPA (AUROC at 3 months, 0.97; 95% CI, 0.91 to 1.00) and 3-HAA (AUROC at 3 months, 0.86; 95% CI, 0.63 to 1.00) continued until 3 months postoperatively. CONCLUSIONS: The AAM profile predicts T2D remission after bariatric surgery more effectively than the existing prediction models. | - |
dc.language.iso | en | - |
dc.title | Metabolomic Profiles Predict Diabetes Remission after Bariatric Surgery | - |
dc.type | Article | - |
dc.identifier.pmid | 33271740 | - |
dc.identifier.url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7760750 | - |
dc.subject.keyword | bariatric surgery | - |
dc.subject.keyword | metabolic surgery | - |
dc.subject.keyword | diabetes | - |
dc.subject.keyword | amino acid | - |
dc.subject.keyword | metabolomics | - |
dc.contributor.affiliatedAuthor | Han, SU | - |
dc.type.local | Journal Papers | - |
dc.identifier.doi | 10.3390/jcm9123897 | - |
dc.citation.title | Journal of clinical medicine | - |
dc.citation.volume | 9 | - |
dc.citation.number | 12 | - |
dc.citation.date | 2020 | - |
dc.citation.startPage | 3897 | - |
dc.citation.endPage | 3897 | - |
dc.identifier.bibliographicCitation | Journal of clinical medicine, 9(12). : 3897-3897, 2020 | - |
dc.identifier.eissn | 2077-0383 | - |
dc.relation.journalid | J020770383 | - |
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