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  • 1. Lim, Eric
    et al.
    Ali, Ayyaz
    Theodorou, Panagiotis
    Sousa, Ines
    Ashrafian, Hutan
    Chamageorgakis, Themis
    Duncan, Alison
    Henein, Michael
    Diggle, Peter
    Pepper, John
    Longitudinal study of the profile and predictors of left ventricular mass regression after stentless aortic valve replacement2008In: Annals of Thoracic Surgery, ISSN 0003-4975, E-ISSN 1552-6259, Vol. 85, no 6, p. 2026-2029Article in journal (Refereed)
    Abstract [en]

    BACKGROUND: The aim of this study was to evaluate the long-term profile and determine the factors that would influence the effect and rate of ventricular mass regression with time after aortic valve replacement with a stentless or a homograft valve.

    METHODS: We studied 300 patients during a 10-year period with at least a year of follow-up with a total of 1,273 serial echocardiographic measurements. Left ventricular mass was calculated from M-mode recordings and indexed to body surface area. Longitudinal data analysis was performed using a linear mixed effects model.

    RESULTS: The mean age (+/- standard deviation) was 65 (+/-14) years, consisting of 216 (72%) males. A stentless valve was implanted in 156 (52%), and a homograft in 144 (48%). The median time (interquartile range) to follow-up was 4.7 (2.8 to 6.6) years. The greatest rate of left ventricular mass regression occurred in the first year after surgery. On multivariable modeling, independent predictors of left ventricular mass were valve size (p = 0.011), left ventricular function (moderate impairment, p = 0.418; severe impairment, p = 0.011), and baseline left ventricular mass (middle tercile, p < 0.001; highest tercile, p < 0.001). Only baseline ventricular mass influenced the rate of subsequent left ventricular mass regression; the greatest rate of regression occurred in patients with the highest baseline values of ventricular mass (p < 0.001).

    CONCLUSIONS: The greatest rate of left ventricular mass regression occurs in the first year with baseline left ventricular mass as the strongest predictor and the only identified variable that influenced the rate of left ventricular mass regression.

  • 2.
    Mariscalco, Giovanni
    et al.
    Umeå University, Faculty of Medicine, Department of Surgical and Perioperative Sciences, Surgery.
    Engström, Karl Gunnar
    Umeå University, Faculty of Medicine, Department of Surgical and Perioperative Sciences, Surgery.
    Postoperative atrial fibrillation is associated with late mortality after coronary surgery, but not after valvular surgery2009In: Annals of Thoracic Surgery, ISSN 0003-4975, E-ISSN 1552-6259, Vol. 88, no 6, p. 1871-1876Article in journal (Refereed)
    Abstract [en]

    Postoperative AF increases late mortality after isolated CABG surgery only. This finding was not statistically confirmed after isolated or combined valvular procedures. Our results draw the attention to possible AF recurrence after hospital discharge, indicating a strict postoperative surveillance.

  • 3. Zhang, Xiangwei
    et al.
    Wang, Yang
    Qu, Pengfei
    Liu-Helmersson, Jing
    Umeå University, Faculty of Medicine, Department of Public Health and Clinical Medicine, Epidemiology and Global Health.
    Zhao, Linping
    Zhang, Lin
    Sang, Shaowei
    The Prognostic Value of Tumor Length for Cause-Specific Mortality in Resectable Esophageal Cancer.2018In: Annals of Thoracic Surgery, ISSN 0003-4975, E-ISSN 1552-6259, Vol. 106, no 4, p. 1038-1046Article in journal (Refereed)
    Abstract [en]

    BACKGROUND: The current esophageal cancer AJCC-TNM staging system may not capture the full prognostic implications of the primary tumor. A study is needed to explore the prognostic value of tumor size on esophageal cancer-specific mortality.

    METHODS: Patients who underwent surgical resection for non-metastatic esophageal cancer were selected from the Surveillance, Epidemiology and End Results Program database (United States, 1988 - 2014). Using statistics methods - maximally selected rank and two hazard models (Cox model and Fine-Gray model) - the optimum cutoff point for tumor length in each T classification was estimated and the prognostic value of tumor size on esophageal cancer-specific mortality was analyzed.

    RESULTS: 4,447 patients were identified. The median tumor size was significantly correlated with T classification, with the correlation coefficient of 0.43 (p < 0.001). Patients in the T1-T3 classifications who had larger tumor size showed a larger probability of cancer-specific mortality. The multivariate Cox model showed that tumor size was significantly associated with an increase in cancer-specific mortality in T1 (2.15, 95% CI [1.72, 2.69]) and T2 (1.31, 95% CI [1.06, 1.62]), but marginally significantly in T3 (1.12, 95% CI [1.00, 1.27]) and insignificantly in T4 classification (p > 0.1). Similar results were found using the multivariate Fine-Gray model.

    CONCLUSIONS: We have found that combining T classification with tumor size can increase the precision in identifying the high-risk groups in T1-T2 classification. Based on esophageal cancer-specific mortality our study is the first to explore the prognostic cutoff point of tumor size by T classification.

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