The Predictive Factors on Extended Hospital Length of Stay in Patients with AMI: Laboratory and Administrative Data
暂无分享,去创建一个
Teresa Magalhães | João Gomes | Sílvia Lopes | Filipe Seixo | S. Lopes | F. Seixo | João Gomes | T. Magalhães
[1] C. Mathers,et al. Projections of Global Mortality and Burden of Disease from 2002 to 2030 , 2006, PLoS medicine.
[2] Tom Stargardt,et al. Measuring the relationship between costs and outcomes: the example of acute myocardial infarction in German hospitals. , 2014, Health economics.
[3] David García-Dorado,et al. In-hospital mortality due to acute myocardial infarction. relevance of type of hospital and care provided. RECALCAR study. , 2013, Revista espanola de cardiologia.
[4] Haiyan Gao,et al. Length of stay as a performance indicator: robust statistical methodology , 2005 .
[5] G. Stone,et al. Safety and cost-effectiveness of early discharge after primary angioplasty in low risk patients with acute myocardial infarction. PAMI-II Investigators. Primary Angioplasty in Myocardial Infarction. , 1998, Journal of the American College of Cardiology.
[6] Jean-Claude Tardif,et al. Women and men with stable coronary artery disease have similar clinical outcomes: insights from the international prospective CLARIFY registry , 2012, European heart journal.
[7] Dinesh U Acharya,et al. Comparison of Different Data Mining Techniques to Predict Hospital Length of Stay , 2011 .
[8] Carl van Walraven,et al. The Kaiser Permanente inpatient risk adjustment methodology was valid in an external patient population. , 2010, Journal of clinical epidemiology.
[9] Ming Zhong,et al. A medical costs study of older patients with acute myocardial infarction and metabolic syndrome in hospital , 2015, Clinical interventions in aging.
[10] David W. Hosmer,et al. Applied Logistic Regression , 1991 .
[11] Jean-Marie Aerts,et al. Computerized prediction of intensive care unit discharge after cardiac surgery: development and validation of a Gaussian processes model , 2011, BMC Medical Informatics Decis. Mak..
[12] Alexander Geissler,et al. Do diagnosis-related groups appropriately explain variations in costs and length of stay of hip replacement? A comparative assessment of DRG systems across 10 European countries. , 2012, Health economics.
[13] Julian J. Faraway,et al. Does data splitting improve prediction? , 2013, Stat. Comput..
[14] K. Swedberg,et al. Factors influencing the length of hospital stay of patients with heart failure , 2003, European journal of heart failure.
[15] L. Neyses,et al. Kardiologische Aspekte der präoperativen Risikostratifizierung , 2011 .
[16] L. Sinoway,et al. Revisiting the role of oxygen therapy in cardiac patients. , 2010, Journal of the American College of Cardiology.
[17] S-J Yoon,et al. Comparison of risk‐adjustment models using administrative or clinical data for outcome prediction in patients after myocardial infarction or coronary bypass surgery in Korea , 2007, International journal of clinical practice.
[18] Paolo Barbini,et al. A straightforward approach to designing a scoring system for predicting length-of-stay of cardiac surgery patients , 2014, BMC Medical Informatics and Decision Making.
[19] Jeroen J. Bax,et al. ESC Guidelines for the management of acute coronary syndromes in patients presenting without persistent ST-segment elevation , 2012 .
[20] Jeroen J. Bax,et al. 2015 ESC Guidelines for the management of acute coronary syndromes in patients presenting without persistent ST-segment elevation: Task Force for the Management of Acute Coronary Syndromes in Patients Presenting without Persistent ST-Segment Elevation of the European Society of Cardiology (ESC). , 2011, European heart journal.
[21] Nilay D. Shah,et al. All Else Being Equal, Men and Women Are Still Not the Same: Using Risk Models to Understand Gender Disparities in Care , 2015, Circulation. Cardiovascular quality and outcomes.
[22] H. Khan,et al. Alterations in prothrombin time and activated partial thromboplastin time in patients with acute myocardial infarction. , 2013, International journal of clinical and experimental medicine.
[23] Ewout W Steyerberg,et al. Applicability of clinical prediction models in acute myocardial infarction: a comparison of traditional and empirical Bayes adjustment methods. , 2005, American heart journal.
[24] D. Atar,et al. ESC Guidelines for the Management of Acute Myocardial Infarction in Patients Presenting With ST-Segment Elevation , 2013 .
[25] Ian M Hastings,et al. Prediction of hospital mortality from admission laboratory data and patient age: A simple model , 2011, Emergency medicine Australasia : EMA.
[26] Sungchul Park,et al. Quality of care and in-hospital resource use in acute myocardial infarction: evidence from Japan. , 2013, Health policy.
[27] Peter Cameron,et al. Air Versus Oxygen in ST-Segment–Elevation Myocardial Infarction , 2015, Circulation.
[28] Ryuji Ohtani,et al. Relation between neutrophil counts on admission, microvascular injury, and left ventricular functional recovery in patients with an anterior wall first acute myocardial infarction treated with primary coronary angioplasty. , 2007, The American journal of cardiology.
[29] L. Iezzoni. Risk Adjustment for Measuring Healthcare Outcomes , 1994 .
[30] D. Hosmer,et al. Applied Logistic Regression , 1991 .
[31] Rodney X. Sturdivant,et al. Applied Logistic Regression: Hosmer/Applied Logistic Regression , 2005 .
[32] Jorge Yarzebski,et al. Declining length of stay for patients hospitalized with AMI: impact on mortality and readmissions. , 2010, The American journal of medicine.
[33] Rizwan Afzal,et al. Can we improve length of hospitalization in ST elevation myocardial infarction patients treated with primary percutaneous coronary intervention? , 2009, The Canadian journal of cardiology.
[34] R. Kaplan,et al. Balancing influence between actors in healthcare decision making , 2011, BMC health services research.
[35] Walter Sermeus,et al. Assessing the causes inducing lengthening of hospital stays by means of the Appropriateness Evaluation Protocol. , 2011, Health policy.
[36] Pamela Banning,et al. Challenges and Benefits of Adding Laboratory Data to a Mortality Risk Adjustment Method , 2011, Quality management in health care.
[37] David Brieger,et al. Inflammation and coronary artery disease. , 2005, American heart journal.
[38] Marie Schmidt,et al. HEAL TH AT A GLANCE , 2007 .
[39] Manuel Anguita,et al. Mortalidad intrahospitalaria por infarto agudo de miocardio. Relevancia del tipo de hospital y la atención dispensada. Estudio RECALCAR , 2013 .
[40] J V Tu,et al. Development and validation of the Ontario acute myocardial infarction mortality prediction rules. , 2001, Journal of the American College of Cardiology.
[41] Isabelle Durand-Zaleski,et al. Does lay media ranking of hospitals reflect lower mortality in treating acute myocardial infarction? , 2012, Archives of cardiovascular diseases.