Background: In patients with acute pulmonary embolism (PE), rapid and accurate risk assessment is paramount in selecting the appropriate treatment strategy. Right ventricular (RV) enlargement on chest CT has previously been shown to correlate with an unstable hospital course, but its role as a predictor of death is unknown.
Methods And Results: We evaluated 431 consecutive patients (mean age, 59+/-16 years; 55% women) with acute PE confirmed by multidetector-row chest CT. With the use of multiplanar reformats of axial CT data, CT 4-chamber (4-CH) views were reconstructed and right and left ventricular dimensions (RV(D), LV(D)) were measured. RV enlargement, defined as RV(D)/LV(D) >0.9, was present in 276 (64.0%; 95% CI, 59.5% to 68.6%) patients. Thirty-day mortality rate was 15.6% (95% CI, 11.3% to 19.9%) in patients with and 7.7% (95% CI, 3.5% to 12.0%) without RV enlargement (log rank, P=0.018). The hazard ratio of RV(D)/LV(D) >0.9 for predicting 30-day death was 3.36 (95% CI, 1.13 to 9.97; P=0.029). On multivariable analysis, RV enlargement predicted 30-day death (hazard ratio, 5.17; 95% CI, 1.63 to 16.35; P=0.005) after adjusting for pneumonia (hazard ratio, 2.95; 95% CI, 1.19 to 3.83; P=0.002), cancer (hazard ratio, 2.13; 95% CI, 1.19 to 3.83; P=0.011), chronic lung disease (hazard ratio, 2.00; 95% CI, 1.04 to 3.86; P=0.039), and age (hazard ratio, 1.03; 95% CI, 1.01 to 1.05; P=0.005).
Conclusions: In patients with acute PE, RV enlargement on reconstructed CT 4-CH view helps predict early death.
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http://dx.doi.org/10.1161/01.CIR.0000147612.59751.4C | DOI Listing |
Cancer Med
January 2025
The Huntsman Cancer Institute at the University of Utah, Salt Lake City, Utah, USA.
Introduction: The purpose of this study was to evaluate the association between body composition, overall survival, odds of receiving treatment, and patient-reported outcomes (PROs) in individuals living with metastatic non-small-cell lung cancer (mNSCLC).
Methods: This retrospective analysis was conducted in newly diagnosed patients with mNSCLC who had computed-tomography (CT) scans and completed PRO questionnaires close to metastatic diagnosis date. Cox proportional hazard models and logistic regression evaluated overall survival and odds of receiving treatment, respectively.
Front Nutr
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Hubei Cancer Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
Background: The Prognostic Nutritional Index (PNI), which reflects both nutritional and immune status, has emerged as a potential predictor of survival outcomes in cancer patients. However, its role in forecasting the prognosis of hepatocellular carcinoma (HCC) following curative hepatectomy remains unclear. To further investigate the association between PNI and survival outcomes in HCC patients, we conducted a systematic review and meta-analysis.
View Article and Find Full Text PDFFront Cardiovasc Med
December 2024
Department of Hypertension, Henan Provincial People's Hospital, Zhengzhou, China.
Background: Previous studies suggest that frailty increases the risk of mortality, but the risk of cardiovascular disease (CVD) and all-cause mortality in Chinese community-dwelling older adults remains understudied. Our aim was to explore the effect of frailty on cardiovascular and all-cause mortality in older adults based on a large-scale prospective survey of community-dwelling older adults in China.
Methods: We utilized the 2014-2018 cohort of the Chinese Longitudinal Healthy Longevity Survey and constructed a frailty index (FI) to assess frailty status.
Front Cardiovasc Med
December 2024
Department of Cardiovascular Medicine, Fengxian District Central Hospital, Shanghai, China.
Background: Although a few studies have examined the correlation between low-density lipoprotein cholesterol (LDL-C) and mortality, no study has explored these associations in hypertensive populations. This study aims to investigate the relationship between low-density lipoprotein cholesterol and cardiovascular and all-cause mortality in adults with hypertension.
Methods: Hypertensive participants aged ≥18 years from the National Health and Nutrition Examination Survey 1999-2018 with blood lipid testing data and complete follow-up data until 31 December 2019 were enrolled in the analysis.
EClinicalMedicine
August 2024
Department of Psychology, University of Cambridge, Cambridge, CB2 3EB, United Kingdom.
Background: Predicting dementia early has major implications for clinical management and patient outcomes. Yet, we still lack sensitive tools for stratifying patients early, resulting in patients being undiagnosed or wrongly diagnosed. Despite rapid expansion in machine learning models for dementia prediction, limited model interpretability and generalizability impede translation to the clinic.
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