| review article | Q7318358 |
| scholarly article | Q13442814 |
| P2093 | author name string | Gary Globe | |
| Gian Luca Di Tanna | |||
| Karen L Burrows | |||
| Heidi Wirtz | |||
| P2860 | cites work | Understanding the epidemic of heart failure: past, present, and future | Q26996486 |
| Frailty in older adults: evidence for a phenotype | Q28205094 | ||
| Clinical Prediction Models for Cardiovascular Disease: Tufts Predictive Analytics and Comparative Effectiveness Clinical Prediction Model Database | Q28646602 | ||
| Towards better clinical prediction models: seven steps for development and an ABCD for validation | Q39180614 | ||
| Timing and Causes of Readmission After Acute Heart Failure Hospitalization-Insights From the Heart Failure Network Trials | Q39806082 | ||
| Predictors of Long-Term Mortality in Patients With Acute Heart Failure | Q40204730 | ||
| Use and misuse of the receiver operating characteristic curve in risk prediction | Q40241086 | ||
| Plasma biomarkers to predict or rule out early post-discharge events after hospitalization for acute heart failure | Q40311889 | ||
| The Seattle Heart Failure Model: prediction of survival in heart failure | Q40343385 | ||
| Plasma growth hormone is a strong predictor of risk at 1 year in acute heart failure. | Q41048065 | ||
| Optimizing clinical use of biomarkers in high-risk acute heart failure patients | Q41074638 | ||
| The first prognostic model for stroke and death in patients with systolic heart failure | Q41139454 | ||
| Triple head-to-head comparison of fibrotic biomarkers galectin-3, osteopontin and gremlin-1 for long-term prognosis in suspected and proven acute heart failure patients | Q41147879 | ||
| Sudden cardiac death and pump failure death prediction in chronic heart failure by combining ECG and clinical markers in an integrated risk model. | Q42650883 | ||
| Derivation and validation of a 30-day heart failure readmission model | Q43844810 | ||
| Top ten risk factors for morbidity and mortality in patients with chronic systolic heart failure and elevated heart rate: The SHIFT Risk Model | Q43970574 | ||
| Prealbumin improves death risk prediction of BNP-added Seattle Heart Failure Model: results from a pilot study in elderly chronic heart failure patients. | Q44590285 | ||
| Trends and predictors of hospitalization, readmissions and length of stay in ambulatory patients with heart failure | Q44929716 | ||
| Validated, electronic health record deployable prediction models for assessing patient risk of 30-day rehospitalization and mortality in older heart failure patients | Q46906040 | ||
| A prediction model for sudden cardiac death in patients with heart failure and preserved ejection fraction | Q48194474 | ||
| The incremental prognostic and clinical value of multiple novel biomarkers in heart failure | Q48746704 | ||
| Circulating microRNA-132 levels improve risk prediction for heart failure hospitalization in patients with chronic heart failure | Q50062611 | ||
| Evaluating Discrimination of Risk Prediction Models: The C Statistic. | Q50858040 | ||
| Cost-of-illness studies in heart failure: a systematic review 2004-2016. | Q55284753 | ||
| Global Public Health Burden of Heart Failure | Q57095663 | ||
| The ‘Echo Heart Failure Score’: an echocardiographic risk prediction score of mortality in systolic heart failure | Q57551507 | ||
| Performance of Prognostic Risk Scores in Chronic Heart Failure Patients Enrolled in the European Society of Cardiology Heart Failure Long-Term Registry | Q57628379 | ||
| Six-minute walking test but not ejection fraction predicts mortality in elderly patients undergoing cardiac rehabilitation following coronary artery bypass grafting | Q57695786 | ||
| Meta-Analysis Global Group in Chronic (MAGGIC) Heart Failure Risk Score: Validation of a Simple Tool for the Prediction of Morbidity and Mortality in Heart Failure With Preserved Ejection Fraction | Q58121761 | ||
| Incremental value of biomarkers to clinical variables for mortality prediction in acutely decompensated heart failure: The Multinational Observational Cohort on Acute Heart Failure (MOCA) study | Q59684070 | ||
| A systematic review shows no performance benefit of machine learning over logistic regression for clinical prediction models | Q62673862 | ||
| PROBAST: A Tool to Assess Risk of Bias and Applicability of Prediction Model Studies: Explanation and Elaboration | Q63367402 | ||
| PROBAST: A Tool to Assess the Risk of Bias and Applicability of Prediction Model Studies | Q63367404 | ||
| Should we perform a heart failure risk score? | Q64924500 | ||
| Age-related in-hospital mortality among patients with acute myocardial infarction | Q80260676 | ||
| Utility of the SENIORS elderly heart failure risk model applied to the RICA registry of acute heart failure | Q86560382 | ||
| Heart failure mortality according to acute variations in N-terminal pro B-type natriuretic peptide and cystatin C levels | Q87280819 | ||
| Assessment of a multi-marker risk score for predicting cause-specific mortality at three years in older patients with heart failure and reduced ejection fraction | Q87290080 | ||
| Prognostic Modeling in Heart Failure: Time for a Reboot | Q88936096 | ||
| Comparison of Recommendations and Use of Cardiovascular Risk Equations by Health Technology Assessment Agencies and Clinical Guidelines | Q91315838 | ||
| Multidimensional frailty evaluation in elderly outpatients with chronic heart failure: A prospective study | Q91358668 | ||
| 2013 ACCF/AHA guideline for the management of heart failure: a report of the American College of Cardiology Foundation/American Heart Association Task Force on Practice Guidelines | Q29620107 | ||
| A simple validated method for predicting the risk of hospitalization for worsening of heart failure in ambulatory patients: the Redin-SCORE. | Q30374980 | ||
| Probabilistic sensitivity analysis in health economics | Q30407247 | ||
| Risk-adjustment models for heart failure patients' 30-day mortality and readmission rates: the incremental value of clinical data abstracted from medical charts beyond hospital discharge record | Q31127047 | ||
| Prospective development and validation of a model to predict heart failure hospitalisation | Q33659469 | ||
| Do Non-Clinical Factors Improve Prediction of Readmission Risk?: Results From the Tele-HF Study | Q33764535 | ||
| A global clinical measure of fitness and frailty in elderly people | Q33920591 | ||
| Predicting survival in heart failure: a risk score based on 39 372 patients from 30 studies | Q34308075 | ||
| Biomarkers of myocardial stress and fibrosis as predictors of mode of death in patients with chronic heart failure | Q34472413 | ||
| 2016 ESC Guidelines for the diagnosis and treatment of acute and chronic heart failure: The Task Force for the diagnosis and treatment of acute and chronic heart failure of the European Society of Cardiology (ESC)Developed with the special contribut | Q34527664 | ||
| 2017 ACC/AHA/HFSA Focused Update of the 2013 ACCF/AHA Guideline for the Management of Heart Failure: A Report of the American College of Cardiology/American Heart Association Task Force on Clinical Practice Guidelines and the Heart Failure Society o | Q34556019 | ||
| Hospital readmissions reduction program | Q35631600 | ||
| Biomarkers and low risk in heart failure. Data from COACH and TRIUMPH. | Q35807149 | ||
| Can machine-learning improve cardiovascular risk prediction using routine clinical data? | Q36334041 | ||
| Variables Measured During Cardiopulmonary Exercise Testing as Predictors of Mortality in Chronic Systolic Heart Failure | Q36599696 | ||
| Assessing the performance of prediction models: a framework for traditional and novel measures | Q36617895 | ||
| Assessing hospital readmission risk factors in heart failure patients enrolled in a telemonitoring program | Q36848576 | ||
| Risk stratification for death and all-cause hospitalization in heart failure clinic outpatients | Q37495565 | ||
| Forecasting the impact of heart failure in the United States: a policy statement from the American Heart Association | Q37538031 | ||
| PREDICTIVE MODELING OF HOSPITAL READMISSION RATES USING ELECTRONIC MEDICAL RECORD-WIDE MACHINE LEARNING: A CASE-STUDY USING MOUNT SINAI HEART FAILURE COHORT. | Q37716068 | ||
| Risk prediction models: I. Development, internal validation, and assessing the incremental value of a new (bio)marker | Q37991423 | ||
| Risk prediction models for mortality in ambulatory patients with heart failure: a systematic review | Q38124253 | ||
| Risk prediction in patients with heart failure: a systematic review and analysis | Q38246491 | ||
| Factors influencing the predictive power of models for predicting mortality and/or heart failure hospitalization in patients with heart failure | Q38246494 | ||
| Effect of Natriuretic Peptide-Guided Therapy on Hospitalization or Cardiovascular Mortality in High-Risk Patients With Heart Failure and Reduced Ejection Fraction: A Randomized Clinical Trial | Q38371833 | ||
| Multistate Model to Predict Heart Failure Hospitalizations and All-Cause Mortality in Outpatients With Heart Failure With Reduced Ejection Fraction: Model Derivation and External Validation | Q38388968 | ||
| Predictors of mortality in 6975 patients with chronic heart failure in the Gruppo Italiano per lo Studio della Streptochinasi nell'Infarto Miocardico-Heart Failure trial: proposal for a nomogram | Q38461247 | ||
| Validation of the Readmission Risk Score in Heart Failure Patients at a Tertiary Hospital | Q38553754 | ||
| Applicability of the heart failure Readmission Risk score: A first European study | Q38730648 | ||
| Limited Added Value of Circulating Inflammatory Biomarkers in Chronic Heart Failure | Q38737583 | ||
| Risk Stratification Model for 30-Day Heart Failure Readmission in a Multiethnic South East Asian Community | Q38902785 | ||
| An Absolute Risk Prediction Model to Determine Unplanned Cardiovascular Readmissions for Adults with Chronic Heart Failure | Q38998756 | ||
| Predicting hospitalization and mortality in patients with heart failure: The BARDICHE-index | Q39133150 | ||
| Mild cognitive impairment predicts death and readmission within 30days of discharge for heart failure | Q39138246 | ||
| P275 | copyright license | Creative Commons Attribution 4.0 International | Q20007257 |
| P6216 | copyright status | copyrighted | Q50423863 |
| P433 | issue | 1 | |
| P921 | main subject | systematic review | Q1504425 |
| literature review | Q2412849 | ||
| P304 | page(s) | e0224135 | |
| P577 | publication date | 2020-01-15 | |
| P1433 | published in | PLOS One | Q564954 |
| P1476 | title | Evaluating risk prediction models for adults with heart failure: A systematic literature review | |
| P478 | volume | 15 |
| Q102145709 | Machine learning vs. conventional statistical models for predicting heart failure readmission and mortality |
| Q99631124 | UMBRELLA protocol: systematic reviews of multivariable biomarker prognostic models developed to predict clinical outcomes in patients with heart failure |
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