İlgi alanları
Yayınları
2 →- MakaleAçık Erişim2026Scopus SJRQ2The COPD-augmented R2CHA2DS2-VA score: development and internal assessment for predicting one-year outcomes after transcatheter aortic valve implantation
Boyaci, Faruk; Sahin, Mustafa Kursat; Akcay, Murat; Yanik, Ahmet; Yenercag, Mustafa; Seker, Onur Osman; Ucar, Melisa; Kokcu, Halil Ibrahim; Ozturk, Berkant; Kaya, Enes
Background Existing CHA(2)DS(2)-VASc-based scores incompletely capture the prognostic impact of chronic obstructive pulmonary disease (COPD) and of graded renal dysfunction in patients undergoing transcatheter aortic valve implantation (TAVI). We acknowledge that the score's development in a high-risk, high-comorbidity cohort may produce optimistic performance estimates that require attenuation through external validation. We aimed to develop a novel COPD-augmented R(2)CHA(2)DS(2)-VA (COPD-R(2)CHA(2)DS(2)-VA) score that systematically integrates quantitative renal function and COPD, and to internally assess its discriminative performance for one-year all-cause mortality and major adverse cardiovascular events (MACE). Methods In this single-center, retrospective cohort study, 622 consecutive patients undergoing TAVI for severe aortic stenosis (2018-2024) were analyzed. The COPD-R(2)CHA(2)DS(2)-VA score was constructed as a prespecified clinical tool by augmenting the R(2)CHA(2)DS(2)-VA framework with COPD (1 point) and refining renal dysfunction into two graded estimated glomerular filtration rate strata (eGFR 30-59 mL/min/1.73 m & sup2;: 1 point; eGFR < 30: 2 points). Discriminative performance was evaluated using receiver operating characteristic curve analysis with bootstrap internal validation (2,000 resamples) and compared with established CHA(2)DS(2)-VASc-based scores. Multivariable logistic regression assessed the independent prognostic value of the score treated as a continuous variable. Results The COPD-R(2)CHA(2)DS(2)-VA score demonstrated encouraging discriminative ability for one-year all-cause mortality (apparent area under the curve [AUC] 0.946, 95% CI 0.926-0.971). As a prespecified tool with fixed component weights, bootstrap internal validation confirmed negligible optimism (mean optimism - 0.00014), with bias-corrected AUC identical to the apparent value. The addition of COPD significantly improved mortality discrimination over the R(2)CHA(2)DS(2)-VA score (Delta AUC + 0.033, p = 0.0001). For one-year MACE, the apparent AUC was 0.806 (95% CI 0.765-0.852); the addition of COPD did not significantly enhance MACE discrimination (Delta AUC + 0.001, p = 0.853). In multivariable analysis, each one-point increase in the COPD-R(2)CHA(2)DS(2)-VA score was independently associated with 3.52-fold higher odds of one-year mortality (95% CI 2.45-5.06, p < 0.001) and 2.02-fold higher odds of MACE (95% CI 1.67-2.46, p < 0.001). The bias-corrected AUC of the full multivariable model was 0.973 (95% CI 0.962-0.984) for mortality and 0.795 (95% CI 0.752-0.841) for MACE. Conclusions The COPD-R(2)CHA(2)DS(2)-VA score demonstrated encouraging discriminative ability for one-year all-cause mortality after TAVI in this single-center development cohort (apparent AUC 0.946). However, this high discriminative performance is likely influenced by the elevated comorbidity burden in our cohort and the single-center design, and should be interpreted as an upper-bound estimate. The addition of COPD provides a statistically significant but clinically modest incremental improvement for mortality (Delta AUC + 0.033, p = 0.0001), with no significant enhancement for MACE (Delta AUC + 0.001, p = 0.853). These findings are preliminary and hypothesis-generating; urgent external validation in diverse, prospective cohorts is essential before any clinical application can be considered. At present, this score should be regarded as a development-phase, hypothesis-generating tool that complements rather than replaces guideline-recommended instruments such as STS-PROM and EuroSCORE II. The score's clinical utility remains unproven.
- MakaleAçık Erişim2013Scopus SJRQ4Evaluation of protein tyrosine phosphatase activity in patients with acute leukemia
Akdogan, Elif; Cengiz, Sevil; YIlmaz, Mustafa; Sönmez, Mehmet; Durmus, Ahmet; Oval, Ercüment; Omay, Serdar Bedii
Protein tyrosine phosphatases regulate physiological processes including growth, differentiation, metabolism and the cell cycle. Together with tyrosine kinases, they control the phosphorylation state of tyrosine residues of signaling proteins. An increased level of protein phosphorylation results in abnormal proliferation and many cancer types show a mutation or deletion of a protein tyrosine phosphatase gene. In this study we evaluated the protein tyrosine phosphatase activity in acute leukemia patients. Tyrosine phosphatase activity in bone marrow mononuclear cells of acute leukemia patients was measured using a tyrosine phosphatase assay system kit and compared with a control group. We found that tyrosine phosphatase activity in acute leukemia patients was high compared to the controls. According to subgroups of acute leukemia, tyrosine phosphatase activity in the AML-M2 subgroup was high compared to the controls. The effect of increased level of protein tyrosine phosphatase activity on leukemogenesis needs further evaluation. Studies in a large group of patients are needed to emphasize the importance of tyrosine phosphatase activity in acute leukemia patients.
AtıfScopus1WoS1OpenAlex1İncele
Tam Kayıt
| Alan | Değer | Dil |
|---|---|---|
| dc.date.accessioned | 2026-10-22T09:25:38.767101785Z | |
| dc.date.available | 2026-10-22T09:25:38.767101785Z | |
| dc.identifier.uri | https://rdlopen.rawdatalibrary.net/r/gumushane/10939 | |
| dc.rights | info:eu-repo/semantics/openAccess | |
| dc.title | Yılmaz, Mustafa | |
| person.affiliation.name | Kelkit Aydın Doğan Meslek Yüksekokulu, Bilgisayar Teknolojileri Bölümü | |
| person.familyName | Yılmaz | |
| person.givenName | Mustafa | |
| person.identifier.orcid | 0009-0004-1207-1663 | |
| person.identifier.wos | QPB-1664-2026 | |
| person.identifier.yok | 2636B3E58DAF0B36 | |
| person.interest | Bilgisayar Bilimleri Ve Mühendisliği | |
| person.interest | Yapay Zeka | |
| person.interest | Makine Öğrenmesi | |
| person.interest | Görüntü İşleme | |
| person.jobTitle | Öğr. Gör. | |
| person.status | verified | |
| person.url | https://rdlsis.gumushane.edu.tr/tr/researcher/mustafa-yilmaz |
