How good are we at determining risk? Quantifying the accuracy of clinician determined risk for VTE prophylaxis

Objectives: Create and validate a simple tool for concurrent audits of risk stratification, compliance and documentation Evaluate accuracy of clinician risk stratification and prophylatic ordering practice compared with a standardized Caprini RAM across different assigned risk categories Provide recommendations for EPIC VTE Prophylaxis CDS Developmenthttps://jdc.jefferson.edu/patientsafetyposters/1050/thumbnail.jp

Development and validation of the Surgical Outcome Risk Tool (SORT).

Existing risk stratification tools have limitations and clinical experience suggests they are not used routinely. The aim of this study was to develop and validate a preoperative risk stratification tool to predict 30-day mortality after non-cardiac surgery in adults by analysis of data from the observational National Confidential Enquiry into Patient Outcome and Death (NCEPOD) Knowing the Risk study

Risk stratification in non-ST elevation acute coronary syndromes: risk scores, biomarkers and clinical judgment

Undifferentiated chest pain is one of the most common reasons for emergency department attendance and admission to hospitals. Non-ST elevation acute coronary syndrome (NSTE-ACS) is an important cause of chest pain, and accurate diagnosis and risk stratification in the emergency department must be a clinical priority. In the future, the incidence of NSTE-ACS will rise further as higher sensitivity troponin assays are implemented in clinical practice. In this article, we review contemporary approaches for the diagnosis and risk stratification of NSTE-ACS during emergency care. We consider the limitations of current practices and potential improvements. Clinical guidelines recommend an early invasive strategy in higher risk NSTE-ACS. The Global Registry of Acute Coronary Events (GRACE) risk score is a validated risk stratification tool which has incremental prognostic value for risk stratification compared with clinical assessment or troponin testing alone. In emergency medicine, there has been a limited adoption of the GRACE score in some countries (e.g. United Kingdom), in part related to a delay in obtaining timely blood biochemistry results. Age makes an exponential contribution to the GRACE score, and on an individual patient basis, the risk of younger patients with a flow-limiting culprit coronary artery lesion may be underestimated. The future incorporation of novel cardiac biomarkers into this diagnostic pathway may allow for earlier treatment stratification. The cost-effectiveness of the new diagnostic pathways based on high-sensitivity troponin and copeptin must also be established. Finally, diagnostic tests and risk scores may optimize patient care but they cannot replace patient-focused good clinical judgment

A Statistical Model for Risk Stratification on the Basis of Left Ventricular Ejection Fraction and Heart-Rate Turbulence

The MPIP data set was used to obtain a model for mortality risk stratification of acute myocardial infarction patients. The predictors heart rate turbulence (HRT) and left-ventricular ejection fraction (LVEF) were employed. HRT was a categorical variable of three levels; LVEF was continuous and its influence on the relative risk was explained by the natural logarithm function (found using fractional polynomials). Cox - PH model with HRT and lnLVEF was constructed and used for risk stratification. The model can be used to divide the patients into two or more groups according to mortality risk. It also describes the relationship between risk and predictors by a (continuous) function, which allows the calculation of individual mortality risk

Non-Linear Heart Rate Variability and Risk Stratification in Cardiovascular Disease

Traditional time and frequency domain heart rate variability (HRV) have cardiac patients at risk of mortality post-myocardial infarction. More recently, non linear HRV has been applied to risk stratification of cardiac patients. In this review we describe studies of non linear HRV and outcome in cardiac patients. We have included studies that used the three most common non-linear indices: power law slope, the short term fractal scaling exponent and measures based on Poincaré plots. We suggest that a combination of traditional and non-linear HRV may be optimal for risk stratification. Considerations in using non linear HRV in a clinical setting are described