Risk factors for and prediction of mortality in critically ill medical–surgical patients receiving heparin thromboprophylaxis

[1]  G. Collins,et al.  Transparent reporting of a multivariable prediction model for individual prognosis or diagnosis (TRIPOD): The TRIPOD statement , 2015, British Journal of Cancer.

[2]  S. Lasocki.  The true obesity paradox: obese and malnourished?. , 2015, Critical care medicine.

[3]  L. Polonski,et al.  The obesity paradox in acute coronary syndrome: a meta-analysis , 2014, European Journal of Epidemiology.

[4]  C. Bollen,et al.  Outcome of invasive mechanical ventilation after pediatric allogeneic hematopoietic SCT: results from a prospective, multicenter registry , 2014, Bone Marrow Transplantation.

[5]  Samuel M. Brown,et al.  Structure, Process, and Annual ICU Mortality Across 69 Centers: United States Critical Illness and Injury Trials Group Critical Illness Outcomes Study* , 2014, Critical care medicine.

[6]  D. Cook,et al.  Thrombocytopenia in critically ill patients receiving thromboprophylaxis: frequency, risk factors, and outcomes. , 2013, Chest.

[7]  Niels Peek,et al.  Body Mass Index Is Associated With Hospital Mortality in Critically Ill Patients: An Observational Cohort Study , 2013, Critical care medicine.

[8]  Matthew Thompson,et al.  Clinical prediction model to aid emergency doctors managing febrile children at risk of serious bacterial infections: diagnostic study , 2013, BMJ : British Medical Journal.

[9]  P. Royston,et al.  External validation of a Cox prognostic model: principles and methods , 2013, BMC Medical Research Methodology.

[10]  M. Gould,et al.  Predicting in-hospital mortality among critically ill patients with end-stage liver disease. , 2012, Journal of critical care.

[11]  J. Bonastre,et al.  Ventilatory support in critically ill hematology patients with respiratory failure , 2012, Critical Care.

[12]  M. Wahidi,et al.  Association of gender with outcomes in critically ill patients , 2012, Critical Care.

[13]  Peter K Lindenauer,et al.  Incorporating initial treatments improves performance of a mortality prediction model for patients with sepsis , 2012, Pharmacoepidemiology and drug safety.

[14]  John P A Ioannidis,et al.  Predicting death: an empirical evaluation of predictive tools for mortality. , 2011, Archives of internal medicine.

[15]  K. Reinhart,et al.  The obesity paradox in surgical intensive care unit patients , 2011, Intensive Care Medicine.

[16]  K. Wernecke,et al.  Gender-related outcome difference is related to course of sepsis on mixed ICUs: a prospective, observational clinical study , 2011, Critical care.

[17]  G. Guyatt,et al.  Dalteparin versus unfractionated heparin in critically ill patients. , 2011, The New England journal of medicine.

[18]  G. Guyatt,et al.  PROphylaxis for ThromboEmbolism in Critical Care Trial protocol and analysis plan. , 2011, Journal of critical care.

[19]  N. D. de Keizer,et al.  External validation of Acute Physiology and Chronic Health Evaluation IV in Dutch intensive care units and comparison with Acute Physiology and Chronic Health Evaluation II and Simplified Acute Physiology Score II. , 2011, Journal of critical care.

[20]  R. Prescott,et al.  Prevalence, management, and outcomes of critically ill patients with prothrombin time prolongation in United Kingdom intensive care units* , 2010, Critical care medicine.

[21]  Michael R. O'Connell,et al.  Comparison of BISAP, Ranson's, APACHE-II, and CTSI Scores in Predicting Organ Failure, Complications, and Mortality in Acute Pancreatitis , 2010, The American Journal of Gastroenterology.

[22]  Nicholas S Ward,et al.  Using serial severity scores to predict death in ICU patients: a validation study and review of the literature , 2009, Current opinion in critical care.

[23]  E. Rivero-Sigarroa,et al.  Prognostic factors in patients with systemic lupus erythematosus admitted to the intensive care unit , 2009, Lupus.

[24]  A. Combes,et al.  Gender impact on the outcomes of critically ill patients with nosocomial infections* , 2009, Critical care medicine.

[25]  M. Inal,et al.  Prognostic value of indocyanine green elimination assessed with LiMON in septic patients. , 2009, Journal of critical care.

[26]  Bekele Afessa,et al.  APACHE III outcome prediction in patients admitted to the intensive care unit after liver transplantation: a retrospective cohort study , 2009, BMC surgery.

[27]  Yvonne Vergouwe,et al.  Prognosis and prognostic research: validating a prognostic model , 2009, BMJ : British Medical Journal.

[28]  Yvonne Vergouwe,et al.  Prognosis and prognostic research: Developing a prognostic model , 2009, BMJ : British Medical Journal.

[29]  P. Pronovost,et al.  The impact of obesity on outcomes after critical illness: a meta-analysis , 2009, Intensive Care Medicine.

[30]  D. Bouch,et al.  Severity scoring systems in the critically ill , 2008 .

[31]  J. Zimmerman,et al.  Outcome prediction in critical care: the Acute Physiology and Chronic Health Evaluation models , 2008, Current opinion in critical care.

[32]  E. Villamor,et al.  Obesity and Mortality in Critically Ill Adults: A Systematic Review and Meta‐analysis , 2008, Obesity.

[33]  Ken P Kleinman,et al.  Much Ado About Nothing , 2007, The American statistician.

[34]  J. Zimmerman,et al.  Acute Physiology and Chronic Health Evaluation (APACHE) IV: Hospital mortality assessment for today’s critically ill patients* , 2006, Critical care medicine.

[35]  S. Lemeshow,et al.  Body mass index is independently associated with hospital mortality in mechanically ventilated adults with acute lung injury* , 2006, Critical Care Medicine.

[36]  Michael Spannagl,et al.  New disseminated intravascular coagulation score: A useful tool to predict mortality in comparison with Acute Physiology and Chronic Health Evaluation II and Logistic Organ Dysfunction scores , 2006, Critical care medicine.

[37]  S. Lemeshow,et al.  BODY MASS INDEX (BMI) IS INDEPENDENTLY ASSOCIATED WITH MORTALITY IN ADULTS WITH ACUTE LUNG INJURY (ALI) IN AN OBSERVATIONAL DATABASE.: 120-M , 2005 .

[38]  Peter Bauer,et al.  SAPS 3—From evaluation of the patient to evaluation of the intensive care unit. Part 2: Development of a prognostic model for hospital mortality at ICU admission , 2005, Intensive Care Medicine.

[39]  Kamyar Kalantar-Zadeh,et al.  Reverse epidemiology of conventional cardiovascular risk factors in patients with chronic heart failure. , 2004, Journal of the American College of Cardiology.

[40]  Yaseen Arabi,et al.  Assessment of six mortality prediction models in patients admitted with severe sepsis and septic shock to the intensive care unit: a prospective cohort study , 2003, Critical care.

[41]  Gary B. Smith,et al.  External validation of the SAPS II, APACHE II and APACHE III prognostic models in South England: a multicentre study , 2003, Intensive Care Medicine.

[42]  C. Koebnick,et al.  Thrombocytopenia in patients in the medical intensive care unit: Bleeding prevalence, transfusion requirements, and outcome* , 2002, Critical care medicine.

[43]  Albert W Wu,et al.  ICU incident reporting systems. , 2002, Journal of critical care.

[44]  J. Miles,et al.  Applying regression & correlation : a guide for students and researchers , 2001 .

[45]  M. Capuzzo,et al.  Validation of severity scoring systems SAPS II and APACHE II in a single-center population , 2000, Intensive Care Medicine.

[46]  D. Goldhill,et al.  Outcome of intensive care patients in a group of British intensive care units. , 1998, Critical care medicine.

[47]  F. Harrell,et al.  Prognostic/Clinical Prediction Models: Multivariable Prognostic Models: Issues in Developing Models, Evaluating Assumptions and Adequacy, and Measuring and Reducing Errors , 2005 .

[48]  Ørnulf Borgan,et al.  A method for checking regression models in survival analysis based on the risk score , 1996, Lifetime data analysis.

[49]  P. Grambsch,et al.  Proportional hazards tests and diagnostics based on weighted residuals , 1994 .

[50]  Edward J. Lin,et al.  Verification of the Acute Physiology and Chronic Health Evaluation scoring system in a Hong Kong intensive care unit , 1993, Critical care medicine.

[51]  W. Knaus,et al.  The APACHE III prognostic system. Risk prediction of hospital mortality for critically ill hospitalized adults. , 1991, Chest.

[52]  W. Knaus,et al.  Predicting outcome in critical care: the current status of the APACHE prognostic scoring system , 1991, Canadian journal of anaesthesia = Journal canadien d'anesthesie.

[53]  G. Guyatt,et al.  Clinical Prediction Rules , 2004 .

[54]  E. Draper,et al.  APACHE II: A severity of disease classification system , 1985, Critical care medicine.

[55]  H. Sox,et al.  Clinical prediction rules. Applications and methodological standards. , 1985, The New England journal of medicine.

[56]  E. Draper,et al.  Evaluating outcome from Intensive care: A preliminary multihospital comparison , 1982, Critical care medicine.

[57]  H. Akaike.  A new look at the statistical model identification , 1974 .

[58]  L. Cancio,et al.  PIRO score for community-acquired pneumonia : A new prediction rule for assessment of severity in intensive care unit patients with community-acquired pneumonia To the , 2022 .