• 제목/요약/키워드: Chonnam

검색결과 17,863건 처리시간 0.043초

Prediction of 6-Month Mortality Using Pre-Extracorporeal Membrane Oxygenation Lactate in Patients with Acute Coronary Syndrome Undergoing Veno-Arterial-Extracorporeal Membrane Oxygenation

  • Kim, Eunchong;Sodirzhon-Ugli, Nodirbek Yuldashev;Kim, Do Wan;Lee, Kyo Seon;Lim, Yonghwan;Kim, Min-Chul;Cho, Yong Soo;Jung, Yong Hun;Jeung, Kyung Woon;Cho, Hwa Jin;Jeong, In Seok
    • Journal of Chest Surgery
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    • 제55권2호
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    • pp.143-150
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    • 2022

  • Background: The effectiveness of extracorporeal membrane oxygenation (ECMO) for patients with refractory cardiogenic shock or cardiac arrest is being established, and serum lactate is well known as a biomarker of end-organ perfusion. We evaluated the efficacy of pre-ECMO lactate for predicting 6-month survival in patients with acute coronary syndrome (ACS) undergoing ECMO. Methods: We reviewed the medical records of 148 patients who underwent veno-arterial (VA) ECMO for ACS between January 2015 and June 2020. These patients were divided into survivors and non-survivors based on 6-month survival. All clinical data before and during ECMO were compared between the 2 groups. Results: Patients' mean age was 66.0±10.5 years, and 116 (78.4%) were men. The total survival rate was 45.9% (n=68). Cox regression analysis showed that the pre-ECMO lactate level was an independent predictor of 6-month mortality (hazard ratio, 1.210; 95% confidence interval [CI], 1.064-1.376; p=0.004). The area under the receiver operating characteristic curve of pre-ECMO lactate was 0.64 (95% CI, 0.56-0.72; p=0.002; cut-off value=9.8 mmol/L). Kaplan-Meier survival analysis showed that the cumulative survival rate at 6 months was significantly higher among patients with a pre-ECMO lactate level of 9.8 mmol/L or less than among those with a level exceeding 9.8 mmol/L (57.3% vs. 31.8%, p=0.0008). Conclusion: A pre-ECMO lactate of 9.8 mmol/L or less may predict a favorable outcome at 6 months in ACS patients undergoing VA-ECMO. Further research aiming to improve the accuracy of predictions of reversibility in patients with high pre-ECMO lactate levels is essential.

  • https://doi.org/10.5090/jcs.21.127 인용 PDF KSCI

Prediction of Residual Axillary Nodal Metastasis Following Neoadjuvant Chemotherapy for Breast Cancer: Radiomics Analysis Based on Chest Computed Tomography

  • Hyo-jae Lee;Anh-Tien Nguyen;Myung Won Song;Jong Eun Lee;Seol Bin Park;Won Gi Jeong;Min Ho Park;Ji Shin Lee;Ilwoo Park;Hyo Soon Lim
    • Korean Journal of Radiology
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    • 제24권6호
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    • pp.498-511
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    • 2023

  • Objective: To evaluate the diagnostic performance of chest computed tomography (CT)-based qualitative and radiomics models for predicting residual axillary nodal metastasis after neoadjuvant chemotherapy (NAC) for patients with clinically node-positive breast cancer. Materials and Methods: This retrospective study included 226 women (mean age, 51.4 years) with clinically node-positive breast cancer treated with NAC followed by surgery between January 2015 and July 2021. Patients were randomly divided into the training and test sets (4:1 ratio). The following predictive models were built: a qualitative CT feature model using logistic regression based on qualitative imaging features of axillary nodes from the pooled data obtained using the visual interpretations of three radiologists; three radiomics models using radiomics features from three (intranodal, perinodal, and combined) different regions of interest (ROIs) delineated on pre-NAC CT and post-NAC CT using a gradient-boosting classifier; and fusion models integrating clinicopathologic factors with the qualitative CT feature model (referred to as clinical-qualitative CT feature models) or with the combined ROI radiomics model (referred to as clinical-radiomics models). The area under the curve (AUC) was used to assess and compare the model performance. Results: Clinical N stage, biological subtype, and primary tumor response indicated by imaging were associated with residual nodal metastasis during the multivariable analysis (all P < 0.05). The AUCs of the qualitative CT feature model and radiomics models (intranodal, perinodal, and combined ROI models) according to post-NAC CT were 0.642, 0.812, 0.762, and 0.832, respectively. The AUCs of the clinical-qualitative CT feature model and clinical-radiomics model according to post-NAC CT were 0.740 and 0.866, respectively. Conclusion: CT-based predictive models showed good diagnostic performance for predicting residual nodal metastasis after NAC. Quantitative radiomics analysis may provide a higher level of performance than qualitative CT features models. Larger multicenter studies should be conducted to confirm their performance.

  • https://doi.org/10.3348/kjr.2022.0731 인용 PDF