Browsing by Subject "risk stratification"

Now showing 1 - 6 of 6
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    Acute Heart Failure Risk Stratification in the Emergency Department: Are We There Yet?
    (Elsevier, 2018) Russell, Frances; Pang, Peter S.; Emergency Medicine, School of Medicine
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    The Combination of Low Skeletal Muscle Mass and High Tumor Interleukin-6 Associates with Decreased Survival in Clear Cell Renal Cell Carcinoma
    (MDPI, 2020-06-17) Kays, Joshua K.; Koniaris, Leonidas G.; Cooper, Caleb A.; Pili, Roberto; Jiang, Guanglong; Liu, Yunlong; Zimmers, Teresa A.; Medical and Molecular Genetics, School of Medicine
    Clear cell renal carcinoma (ccRCC) is frequently associated with cachexia which is itself associated with decreased survival and quality of life. We examined relationships among body phenotype, tumor gene expression, and survival. Demographic, clinical, computed tomography (CT) scans and tumor RNASeq for 217 ccRCC patients were acquired from the Cancer Imaging Archive and The Cancer Genome Atlas (TCGA). Skeletal muscle and fat masses measured from CT scans and tumor cytokine gene expression were compared with survival by univariate and multivariate analysis. Patients in the lowest skeletal muscle mass (SKM) quartile had significantly shorter overall survival versus the top three SKM quartiles. Patients who fell into the lowest quartiles for visceral adipose mass (VAT) and subcutaneous adipose mass (SCAT) also demonstrated significantly shorter overall survival. Multiple tumor cytokines correlated with mortality, most strongly interleukin-6 (IL-6); high IL-6 expression was associated with significantly decreased survival. The combination of low SKM/high IL-6 was associated with significantly lower overall survival compared to high SKM/low IL-6 expression (26.1 months vs. not reached; p < 0.001) and an increased risk of mortality (HR = 5.95; 95% CI = 2.86–12.38). In conclusion, tumor cytokine expression, body composition, and survival are closely related, with low SKM/high IL-6 expression portending worse prognosis in ccRCC.
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    Derivation and validation of a multivariate model to predict mortality from pulmonary embolism with cancer: the POMPE-C tool
    (2012-05) Kline, Jeffrey A.; Roy, Pierre-Marie; Than, Martin P; Hernandez, Jackeline; Courtney, D Mark; Jones, Alan E; Penazola, Andrea; Pollack Jr, Charles V
    Background Clinical guidelines recommend risk stratification of patients with acute pulmonary embolism (PE). Active cancer increases risk of PE and worsens prognosis, but also causes incidental PE that may be discovered during cancer staging. No quantitative decision instrument has been derived specifically for patients with active cancer and PE. Methods Classification and regression technique was used to reduce 25 variables prospectively collected from 408 patients with AC and PE. Selected variables were transformed into a logistic regression model, termed POMPE-C, and compared with the pulmonary embolism severity index (PESI) score to predict the outcome variable of death within 30 days. Validation was performed in an independent sample of 182 patients with active cancer and PE. Results POMPE-C included eight predictors: body mass, heart rate > 100, respiratory rate, SaO2%, respiratory distress, altered mental status, do not resuscitate status, and unilateral limb swelling. In the derivation set, the area under the ROC curve for POMPE-C was 0.84 (95% CI: 0.82-0.87), significantly greater than PESI (0.68, 0.60-0.76). In the validation sample, POMPE-C had an AUC of 0.86 (0.78-0.93). No patient with POMPE-C estimate ≤ 5% died within 30 days (0/50, 0-7%), whereas 10/13 (77%, 46-95%) with POMPE-C estimate > 50% died within 30 days. Conclusion In patients with active cancer and PE, POMPE-C demonstrated good prognostic accuracy for 30 day mortality and better performance than PESI. If validated in a large sample, POMPE-C may provide a quantitative basis to decide treatment options for PE discovered during cancer staging and with advanced cancer.
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    Rectal Optical Markers for In-vivo Risk Stratification of Premalignant Colorectal Lesions.
    (AACR, 2015-10-01) Radosevich, Andrew J.; Mutyal, Nikhil N.; Eshein, Adam; Nguyen, The-Quyen; Gould, Bradley; Rogers, Jeremy D.; Goldberg, Michael J.; Bianchi, Laura K.; Yen, Eugene F.; Konda, Vani; Rex, Douglas K.; Van Dam, Jacques; Backman, Vadim; Roy, Hemant K.; Department of Medicine, IU School of Medicine
    Purpose: Colorectal cancer remains the second leading cause of cancer deaths in the U.S. despite being eminently preventable by colonoscopy via removal of premalignant adenomas. In order to more effectively reduce colorectal cancer mortality, improved screening paradigms are needed. Our group pioneered the use of low coherence enhanced backscattering (LEBS) spectroscopy to detect the presence of adenomas throughout the colon via optical interrogation of the rectal mucosa. In a previous ex-vivo biopsy study of 219 patients, LEBS demonstrated excellent diagnostic potential with 89.5% accuracy for advanced adenomas. The objective of the current cross-sectional study is to assess the viability of rectal LEBS in-vivo. Experimental Design: Measurements from 619 patients were taken using a minimally invasive 3.4 mm diameter LEBS probe introduced into the rectum via anoscope or direct insertion, requiring ~1 minute from probe insertion to withdrawal. The diagnostic LEBS marker was formed as a logistic regression of the optical reduced scattering coefficient μs∗ and mass density distribution factor D. Results: The rectal LEBS marker was significantly altered in patients harboring advanced adenomas and multiple non-advanced adenomas throughout the colon. Blinded and cross-validated test performance characteristics showed 88% sensitivity to advanced adenomas, 71% sensitivity to multiple non-advanced adenomas, and 72% specificity in the validation set. Conclusions: We demonstrate the viability of in-vivo LEBS measurement of histologically normal rectal mucosa to predict the presence of clinically relevant adenomas throughout the colon. The current work represents the next step in the development of rectal LEBS as a tool for colorectal cancer risk stratification.
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    Risk Stratification Strategies for Colorectal Cancer Screening: From Logistic Regression to Artificial Intelligence
    (Elsevier, 2020-07) Imperiale, Thomas F.; Monahan, Patrick O.; Medicine, School of Medicine
    Risk stratification is a system or process by which clinically-meaningful separation of risk is achieved in a group of otherwise similar persons. While parametric logistic regression dominates risk prediction, use of nonparametric methods such as classification and regression trees, artificial neural networks, and other machine-learning methods are increasing. Collectively, these learning methods are referred to as “artificial intelligence” (AI). The persuasive nature of AI requires knowledge of study validity, an understanding of model metrics, and determination of whether and to what extent the model can and should be applied to the patient or population under consideration. Further investigation is needed, especially in model validation and impact assessment.
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    Use of High-Sensitivity Troponin T to Identify Patients With Acute Heart Failure at Lower Risk for Adverse Outcomes
    (Elsevier, 2016-07) Pang, Peter S.; Teerlink, John R.; Voors, Adriaan A.; Ponikowski, Piotr; Greenberg, Barry H.; Filippatos, Gerasimos; Felker, G. Michael; Davison, Beth A.; Cotter, Gad; Kriger, Joshua; Prescott, Margaret F.; Hua, Tsushung A.; Severin, Thomas; Metra, Marco; Department of Emergency Medicine, IU School of Medicine
    Objectives The aim of this study was to determine if a baseline high-sensitivity troponin T (hsTnT) value ≤99th percentile upper reference limit (0.014 μg/l [“low hsTnT”]) identifies patients at low risk for adverse outcomes. Background Approximately 85% of patients who present to emergency departments with acute heart failure are admitted. Identification of patients at low risk might decrease unnecessary admissions. Methods A post-hoc analysis was conducted from the RELAX-AHF (Serelaxin, Recombinant Human Relaxin-2, for Treatment of Acute Heart Failure) trial, which randomized patients within 16 h of presentation who had systolic blood pressure >125 mm Hg, mild to moderate renal impairment, and N-terminal pro–brain natriuretic peptide ≥1,600 ng/l to serelaxin versus placebo. Linear regression models for continuous endpoints and Cox models for time-to-event endpoints were used. Results Of the 1,076 patients with available baseline hsTnT values, 107 (9.9%) had low hsTnT. No cardiovascular (CV) deaths through day 180 were observed in the low-hsTnT group compared with 79 CV deaths (7.3%) in patients with higher hsTnT. By univariate analyses, low hsTnT was associated with lower risk for all 5 primary outcomes: 1) days alive and out of the hospital by day 60; 2) CV death or rehospitalization for heart failure or renal failure by day 60; 3) length of stay; 4) worsening heart failure through day 5; and 5) CV death through day 180. After multivariate adjustment, only 180-day CV mortality remained significant (hazard ratio: 0.0; 95% confidence interval: 0.0 to 0.736; p = 0.0234; C-index = 0.838 [95% confidence interval: 0.798 to 0.878]). Conclusions No CV deaths through day 180 were observed in patients with hsTnT levels ≤0.014 μg/l despite high N-terminal pro–brain natriuretic peptide levels. Low baseline hsTnT may identify patients with acute heart failure at very low risk for CV mortality.