Checkley W, Martin GS, Brown SM, Chang SY, Dabbagh O, Fremont RD, Girard TD, Rice TW, Howell MD, Johnson SB, et al. Structure, process, and annual ICU mortality across 69 centers: United States Critical Illness and Injury Trials Group Critical Illness Outcomes Study. Crit Care Med. 2014;42(2):344–56.
Wu AW, Pronovost P, Morlock L. ICU incident reporting systems. J Crit Care. 2002;17(2):86–94.
Article
PubMed
Google Scholar
Parker J. California Intensive Care Outcomes Project (CALICO). http://www.oshpd.ca.gov/HID/Products/PatDischargeData/ICUDataCALICO/CALICO_05-07.pdf (2007). Accessed 20 Feb 2015.
Bouch DC, Thompson JP. Severity scoring systems in the critically ill. Contin Educ Anaesth Critical Care Pain. 2008;8(5):181–5.
Article
Google Scholar
Gartman EJ, Casserly BP, Martin D, Ward NS. Using serial severity scores to predict death in ICU patients: a validation study and review of the literature. Curr Opin Crit Care. 2009;15(6):578–82.
Article
PubMed
Google Scholar
Brinkman S, Bakhshi-Raiez F, Abu-Hanna A, de Jonge E, Bosman RJ, Peelen L, de Keizer NF. 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. J Crit Care. 2011;26(1):105.e11–8.
Article
Google Scholar
Zimmerman JE, Kramer AA. Outcome prediction in critical care: the Acute Physiology and Chronic Health Evaluation models. Curr Opin Crit Care. 2008;14(5):491–7.
Article
PubMed
Google Scholar
Beck DH, Smith GB, Pappachan JV, Millar B. External validation of the SAPS II, APACHE II and APACHE III prognostic models in South England: a multicentre study. Intensive Care Med. 2003;29(2):249–56.
PubMed
Google Scholar
Wong DT, Knaus WA. Predicting outcome in critical care: the current status of the APACHE prognostic scoring system. Can J Anaesth. 1991;38(3):374–83.
Article
CAS
PubMed
Google Scholar
Oh TE, Hutchinson R, Short S. BUCKLEY T, LIN E, LEUNG D: Verification of the acute physiology and chronic health evaluation scoring system in a Hong Kong intensive care unit. Crit Care Med. 1993;21(5):698–705.
Article
CAS
PubMed
Google Scholar
Capuzzo M, Valpondi V, Sgarbi A, Bortolazzi S, Pavoni V, Gilli G, Candini G, Gritti G, Alvisi R. Validation of severity scoring systems SAPS II and APACHE II in a single-center population. Intensive Care Med. 2000;26(12):1779–85.
Article
CAS
PubMed
Google Scholar
Knaus WA, Draper EA, Wagner DP, Zimmerman JE, Birnbaum ML, Cullen DJ, Kohles MK, Shin B, Snyder JV. Evaluating outcome from intensive care: a preliminary multihospital comparison. Crit Care Med. 1982;10(8):491–6.
Article
CAS
PubMed
Google Scholar
Knaus WA, Draper EA, Wagner DP, Zimmerman JE. APACHE II: a severity of disease classification system. Crit Care Med. 1985;13(10):818–29.
Article
CAS
PubMed
Google Scholar
Knaus WA, Wagner D, Draper E, Zimmerman J, Bergner M, Bastos PG, Sirio C, Murphy D, Lotring T, Damiano A. The APACHE III prognostic system. Risk prediction of hospital mortality for critically ill hospitalized adults. Chest. 1991;100(6):1619–36.
Article
CAS
PubMed
Google Scholar
Zimmerman JE, Kramer AA, McNair DS, Malila FM. Acute Physiology and Chronic Health Evaluation (APACHE) IV: hospital mortality assessment for today’s critically ill patients*. Crit Care Med. 2006;34(5):1297–310.
Article
PubMed
Google Scholar
Arabi Y, Al Shirawi N, Memish Z, Venkatesh S, Al-Shimemeri A. Assessment of six mortality prediction models in patients admitted with severe sepsis and septic shock to the intensive care unit: a prospective cohort study. Crit Care. 2003;7(5):R116.
Article
PubMed Central
PubMed
Google Scholar
Keegan MT, Gali B, Findlay JY, Heimbach JK, Plevak DJ, Afessa B. APACHE III outcome prediction in patients admitted to the intensive care unit after liver transplantation: a retrospective cohort study. BMC Surg. 2009;9:11.
Article
PubMed Central
PubMed
Google Scholar
Namendys-Silva SA, Baltazar-Torres JA, Rivero-Sigarroa E, Fonseca-Lazcano JA, Montiel-Lopez L, Dominguez-Cherit G. Prognostic factors in patients with systemic lupus erythematosus admitted to the intensive care unit. Lupus. 2009;18(14):1252–8.
Article
CAS
PubMed
Google Scholar
Papachristou GI, Muddana V, Yadav D, O’Connell M, Sanders MK, Slivka A, Whitcomb DC. Comparison of BISAP, Ranson’s, APACHE-II, and CTSI scores in predicting organ failure, complications, and mortality in acute pancreatitis. Am J Gastroenterol. 2010;105(2):435–41.
Article
PubMed
Google Scholar
Inal MT, Memis D, Kargi M, Sut N. Prognostic value of indocyanine green elimination assessed with LiMON in septic patients. J Crit Care. 2009;24(3):329–34.
Article
PubMed
Google Scholar
Siontis G, Tzoulaki I, Ioannidis J. Predicting death: an empirical evaluation of predictive tools for mortality. Arch Intern Med. 2011;171(19):1721–6.
Article
PubMed
Google Scholar
Lagu T, Rothberg MB, Nathanson BH, Steingrub JS, Lindenauer PK. Incorporating initial treatments improves performance of a mortality prediction model for patients with sepsis. Pharmacoepidemiol Drug Saf. 2012;21(S2):44–52.
Article
PubMed
Google Scholar
O’Brien JM Jr, Phillips GS, Ali NA, Lucarelli M, Marsh CB, Lemeshow S. Body mass index is independently associated with hospital mortality in mechanically ventilated adults with acute lung injury. Crit Care Med. 2006;34(3):738.
PubMed Central
PubMed
Google Scholar
Pickkers P, de Keizer N, Dusseljee J, Weerheijm D, van der Hoeven JG, Peek N. Body mass index is associated with hospital mortality in critically ill patients: an observational cohort study. Crit Care Med. 2013;41(8):1878–83.
Article
PubMed
Google Scholar
Mahmood K, Eldeirawi K, Wahidi MM. Association of gender with outcomes in critically ill patients. Crit Care. 2012;16(3):R92.
Article
PubMed Central
PubMed
Google Scholar
Combes A, Luyt CE, Trouillet JL, Nieszkowska A, Chastre J. Gender impact on the outcomes of critically ill patients with nosocomial infections. Crit Care Med. 2009;37(9):2506–11.
Article
PubMed
Google Scholar
Nachtigall I, Tafelski S, Rothbart A, Kaufner L, Schmidt M, Tamarkin A, Kartachov M, Zebedies D, Trefzer T, Wernecke KD, et al. Gender-related outcome difference is related to course of sepsis on mixed ICUs: a prospective, observational clinical study. Crit Care. 2011;15(3):R151.
Article
PubMed Central
PubMed
Google Scholar
Moreno RP, Metnitz PG, Almeida E, Jordan B, Bauer P, Campos RA, Iapichino G, Edbrooke D, Capuzzo M, Le Gall JR. 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. Intensive Care Med. 2005;31(10):1345–55.
Article
PubMed Central
PubMed
Google Scholar
Walsh TS, Stanworth SJ, Prescott RJ, Lee RJ, Watson DM, Wyncoll D. Prevalence, management, and outcomes of critically ill patients with prothrombin time prolongation in United Kingdom intensive care units. Crit Care Med. 2010;38(10):1939–46.
PubMed
Google Scholar
Angstwurm MW, Dempfle CE, Spannagl M. 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. Crit Care Med. 2006;34(2):314–20.
Article
PubMed
Google Scholar
Williamson DR, Albert M, Heels-Ansdell D, Arnold DM, Lauzier F, Zarychanski R, Crowther M, Warkentin TE, Dodek P, Cade J, et al. Thrombocytopenia in critically ill patients receiving thromboprophylaxis: frequency, risk factors, and outcomes. Chest. 2013;144(4):1207–15.
Article
PubMed
Google Scholar
Strauss R, Wehler M, Mehler K, Kreutzer D, Koebnick C, Hahn EG. Thrombocytopenia in patients in the medical intensive care unit: bleeding prevalence, transfusion requirements, and outcome. Crit Care Med. 2002;30(8):1765–71.
Article
PubMed
Google Scholar
Collins GS, Reitsma JB, Altman DG, Moons KG. Transparent reporting of a multivariable prediction model for individual prognosis or diagnosis (TRIPOD): the TRIPOD statement. BMJ. 2015;350:g7594.
Article
PubMed
Google Scholar
Cook D, Meade M, Guyatt G, Walter SD, Heels-Ansdell D, Geerts W, Warkentin TE, Cooper DJ, Zytaruk N, Vallance S. PROphylaxis for ThromboEmbolism in Critical Care Trial protocol and analysis plan. J Crit Care. 2011;26(2):e221–3.
Article
Google Scholar
Cook D, Meade M, Guyatt G, Walter S, Heels-Ansdell D, Warkentin TE, Zytaruk N, Crowther M, Geerts W, Cooper DJ, et al. Dalteparin versus unfractionated heparin in critically ill patients. New Engl J Med. 2011;364(14):1305–14.
Article
CAS
PubMed
Google Scholar
Horton NJ, Kleinman KP. Much ado about nothing: a comparison of missing data methods and software to fit incomplete data regression models. Am Stat. 2007;61(1):79–90.
Article
PubMed Central
PubMed
Google Scholar
Royston P, Moons KG, Altman DG, Vergouwe Y. Prognosis and prognostic research: developing a prognostic model. BMJ. 2009;338:b604. doi:10.1136/bmj.b604.
Miles J, Shevlin M. Appling regression and correlation: a guide for students. London: Sage; 2001.
Google Scholar
Grambsch PM, Therneau TM. Proportional hazards tests and diagnostics based on weighted residuals. Biometrika. 1994;81(3):515–26.
Article
Google Scholar
Goldhill DR, Sumner A. Outcome of intensive care patients in a group of British intensive care units. Crit Care Med. 1998;26(8):1337–45.
Article
CAS
PubMed
Google Scholar
Nijman RG, Vergouwe Y, Thompson M, van Veen M, van Meurs AH, van der Lei J, Steyerberg EW, Moll HA, Oostenbrink R: Clinical prediction model to aid emergency doctors managing febrile children at risk of serious bacterial infections: diagnostic study. BMJ. 2013;346:f1706.
Gronnesby JK, Borgan O. A method for checking regression models in survival analysis based on the risk score. Lifetime Data Anal. 1996;2(4):315–28.
Article
CAS
PubMed
Google Scholar
Akaike H. A new look at the statistical model identification. Autom Control IEEE Trans. 1974;19(6):716–23.
Article
Google Scholar
Harrell F, Lee KL, Mark DB. Tutorial in biostatistics multivariable prognostic models: issues in developing models, evaluating assumptions and adequacy, and measuring and reducing errors. Stat Med. 1996;15:361–87.
Article
PubMed
Google Scholar
Altman DG, Vergouwe Y, Royston P, Moons KG. Prognosis and prognostic research: validating a prognostic model. BMJ. 2009;338:b605.
Royston P, Altman DG. External validation of a Cox prognostic model: principles and methods. BMC Med Res Methodol. 2013;13(1):33.
Article
PubMed Central
PubMed
Google Scholar
Pickkers P, de Keizer N, Dusseljee J, Weerheijm D, van der Hoeven JG, Peek N. Body mass index is associated with hospital mortality in critically ill patients: an observational cohort study. Crit Care Med. 2013;41(8):1878–83.
Article
PubMed
Google Scholar
Hogue CW Jr, Stearns JD, Colantuoni E, Robinson KA, Stierer T, Mitter N, Pronovost PJ, Needham DM. The impact of obesity on outcomes after critical illness: a meta-analysis. Intensive Care Med. 2009;35(7):1152–70.
Article
PubMed
Google Scholar
Hutagalung R, Marques J, Kobylka K, Zeidan M, Kabisch B, Brunkhorst F, Reinhart K, Sakr Y. The obesity paradox in surgical intensive care unit patients. Intensive Care Med. 2011;37(11):1793–9.
Article
PubMed
Google Scholar
Kalantar-Zadeh K, Block G, Horwich T, Fonarow GC. Reverse epidemiology of conventional cardiovascular risk factors in patients with chronic heart failure. J Am Coll Cardiol. 2004;43(8):1439–44.
Article
PubMed
Google Scholar
Niedziela J, Hudzik B, Niedziela N, Gasior M, Gierlotka M, Wasilewski J, Myrda K, Lekston A, Polonski L, Rozentryt P. The obesity paradox in acute coronary syndrome: a meta-analysis. Eur J Epidemiol. 2014;29(11):801–12.
Article
PubMed Central
CAS
PubMed
Google Scholar
Lasocki S. The true obesity paradox: obese and malnourished? Crit Care Med. 2015;43(1):240–1.
Article
PubMed
Google Scholar
Oliveros H, Villamor E. Obesity and mortality in critically ill adults: a systematic review and meta-analysis. Obesity. 2008;16(3):515–21.
Article
PubMed
Google Scholar
Molina R, Bernal T, Borges M, Zaragoza R, Bonastre J, Granada RM, Rodriguez-Borregán JC, Núñez K, Seijas I, Ayestaran I. Ventilatory support in critically ill hematology patients with respiratory failure. Crit Care. 2012;16(4):R133.
Article
PubMed Central
PubMed
Google Scholar
van Gestel J, Bierings M, Dauger S, Dalle J, Pavlíček P, Sedláček P, Monteiro L, Lankester A, Bollen C. Outcome of invasive mechanical ventilation after pediatric allogeneic hematopoietic SCT: results from a prospective, multicenter registry. Bone Marrow Transplant. 2014;49(10):1287–92.
Article
PubMed
Google Scholar
Adams ST, Leveson SH: Clinical prediction rules. BMJ. 2012;344:d8312.
Balekian AA, Gould MK. Predicting in-hospital mortality among critically ill patients with end-stage liver disease. J Crit Care. 2012;27(6):e741–7.
Article
Google Scholar
Rello J, Rodriguez A, Lisboa T, Gallego M, Lujan M, Wunderink R. PIRO score for community-acquired pneumonia: a new prediction rule for assessment of severity in intensive care unit patients with community-acquired pneumonia*. Crit Care Med. 2009;37(2):456–62.
Article
PubMed
Google Scholar