Validation of clinical classification schemes for predicting stroke: results from the National Registry of Atrial Fibrillation.

By B. Gage, A. Waterman, William D. Shannon, M. Boechler, M. Rich, M. Radford. 2001

2,478 citations recorded by the source corpus.

Subfields: Cardiology and Cardiovascular Medicine, Epidemiology, Pulmonary and Respiratory Medicine, Medical & Health AI

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Citations in the corpus

Learning Optimized Risk Scores (2016, methodology): “…development involves having a panel experts build a model by hand, and using data to validate the model after it is built (e.g., for the CHADS2 score for stroke prediction of Gage et al. 2001, and the National Early Warning Score to assess acute illness in the ICU of McGinley and Pearse 2012).”
Supersparse linear integer models for optimized medical scoring systems (2015, methodology): “This appears to have been the case for CHADS2 as suggested by Gage et al. (2001): “To create CHADS2, we assigned 2 points to a history of prior cerebral ischemia and 1 point for the presence of other risk factors because a history of prior cerebral ischemia increases the relative risk (RR) of…”
Supersparse Linear Integer Models for Predictive Scoring Systems (2013, methodology): “See, for instance, these commonly used scoring systems: (Gage et al. 2001; Le Gall et al. 1984; Le Gall, Lemeshow, and Saulnier 1993; Knaus et al. 1985).”
Learning Classification Models of Cognitive Conditions from Subtle Behaviors in the Digital Clock Drawing Test (2015, methodology): “For example, a novel decision list construction algorithm [22] was used to generate a new scoring criterion to predict stroke in patients with atrial fibrillation, significantly outperforming the CHADS2 [15] scoring system currently in use by doctors, while remaining equally interpretable; another w”
A Provable Algorithm for Learning Interpretable Scoring Systems (2018, methodology): “Some other widely used medical scores are SAPS I, II, and III [10, 21] and APACHE I, II, III to assess intensive care units mortality risks [14], CHADS2 to assess the risk of stroke [9]; TIMI to estimate the risk of death of ischemic events [2].”
2014 AHA/ACC/HRS guideline for the management of patients with atrial fibrillation: executive summary: a report of the American College of Cardiology/American Heart Association Task Force on practice guidelines and the Heart Rhythm Society. (2014, neutral): “TIA or Thromboembolism (doubled) (CHADS2) (89), or the Congestive heart failure, Hypertension, Age ≥75”
A risk score for predicting stroke or death in individuals with new-onset atrial fibrillation in the community: the Framingham Heart Study. (2003, background): “These clinical risk factors also have been incorporated into subsequent AF risk stratification schemes.(7,8) The results of the current study are similar to those of prior studies with respect to risk factors such as advanced age, diabetes, and elevated blood pressure.”
Anticoagulation therapy for stroke prevention in atrial fibrillation: how well do randomized trials translate into clinical practice? (2003, methodology): “The CHADS2 index measures stroke risk by assigning 1 point each for congestive heart failure, hypertension, age 75 years or older, and diabetes mellitus, with 2 points added for patients who have a history of stroke or transient ischemic attack.(27) To evaluate the effectiveness of warfarin compared”
Guidelines for the Primary Prevention of Stroke (2011, neutral): “The widely used CHADS 2 scheme (Table 3) yields a score of 0 to 6, with 1 point each given for congestive heart failure, hypertension, age ≥75 years, and diabetes mellitus and with 2 points given for prior stroke or transient ischemic attack (TIA).(378) This scheme has been tested in multiple indepe”
ACC/AHA/ESC 2006 guidelines for the management of patients with atrial fibrillation--executive summary: a report of the American College of Cardiology/American Heart Association Task Force on Practice Guidelines and the European Society of Cardiology Committee for Practice Guidelines (Writing Commit (2006, neutral): “JAMA 2001;285:2864–70.(152) AF indicates atrial fibrillation; CHADS2, Cardiac Failure, Hypertension, Age, Diabetes, and Stroke (Doubled); CI, confidence interval; and TIA,”