External validation of the intensive care national audit & research centre (ICNARC) risk prediction model in critical care units in Scotland

BMC Anesthesiology

Volumn 14, Issue 1, 2014, Pages

  Harrison, David A ^a   Lone, Nazir I ^b,c,d   Haddow, Catriona ^b   MacGillivray, Moranne ^b   Khan, Angela ^b   Cook, Brian ^b,c   Rowan, Kathryn M ^a  

^a and London School of Hygiene Tropical Medicine   (United Kingdom)

^b INFORMATION SERVICES DIVISION   (United Kingdom)

^c ROYAL INFIRMARY OF EDINBURGH   (United Kingdom)

^d UNIVERSITY OF EDINBURGH   (United Kingdom)

Author keywords

Critical care; Intensive care units; Models; Prognosis; Risk adjustment; Severity of illness index; Statistical; Validation studies

Indexed keywords

ADULT; APACHE; ARTERIAL PH; ARTICLE; CLINICAL DECISION MAKING; FEMALE; HOSPITALIZATION; HUMAN; INTENSIVE CARE; INTENSIVE CARE UNIT; MAJOR CLINICAL STUDY; MALE; MENTAL HEALTH; MIDDLE AGED; MORTALITY; PREDICTION; QUALITY CONTROL; RISK FACTOR; STRATIFICATION; SYSTOLIC BLOOD PRESSURE; UNITED KINGDOM; AGED; ALGORITHM; COMPARATIVE STUDY; FACTUAL DATABASE; RISK; RISK ASSESSMENT; STATISTICAL MODEL; STATISTICS AND NUMERICAL DATA; VALIDATION STUDY;

AGED; ALGORITHMS; APACHE; CRITICAL CARE; DATABASES, FACTUAL; FEMALE; HOSPITALIZATION; HUMANS; INTENSIVE CARE UNITS; MALE; MIDDLE AGED; MODELS, STATISTICAL; RISK; RISK ADJUSTMENT; RISK ASSESSMENT; SCOTLAND;

EID: 84924041681     PISSN: None     EISSN: 14712253     Source Type: Journal    
DOI: 10.1186/1471-2253-14-116     Document Type: Article

References (22)

1. Higgins TL: Quantifying risk and benchmarking performance in the adult intensive care unit. J Intensive Care Med 2007, 22:141-156. 10.1177/0885066607299520
2. Turner EL, Perel P, Clayton T, Edwards P, Hernández AV, Roberts I, Shakur H, Steyerberg EW, CRASH Trial Collaborators: Covariate adjustment increased power in randomized controlled trials: an example in traumatic brain injury. J Clin Epidemiol 2012, 65:474-481. 10.1016/j.jclinepi.2011.08.012
3. Wunsch H, Linde-Zwirble WT, Angus DC: Methods to adjust for bias and confounding in critical care health services research involving observational data. J Crit Care 2006, 21:1-7. 10.1016/j.jcrc.2006.01.004
4. Altman DG, Royston P: What do we mean by validating a prognostic model? Stat Med 2000, 19:453-473. 10.1002/(SICI)1097-0258(20000229)19:4<453::AID-SIM350>3.0.CO;2-5
5. Altman DG, Vergouwe Y, Royston P, Moons KGM: Prognosis and prognostic research: validating a prognostic model. BMJ 2009, 338:b605. 10.1136/bmj.b605
6. Harrison DA, Brady AR, Parry GJ, Carpenter JR, Rowan K: Recalibration of risk prediction models in a large multicenter cohort of admissions to adult, general critical care units in the United Kingdom. Crit Care Med 2006, 34:1378-1388. 10.1097/01.CCM.0000216702.94014.75
7. Harrison DA, Parry GJ, Carpenter JR, Short A, Rowan K: A new risk prediction model for critical care: The Intensive Care National Audit & Research Centre (ICNARC) model. Crit Care Med 2007, 35:1091-1098. 10.1097/01.CCM.0000259468.24532.44
8. Harrison DA, Rowan KM: Outcome prediction in critical care: the ICNARC model. Curr Opin Crit Care 2008, 14:506-512. 10.1097/MCC.0b013e328310165a
9. Young JD, Goldfrad C, Rowan K: Development and testing of a hierarchical method to code the reason for admission to intensive care units: the ICNARC Coding Method. Br J Anaesth 2001, 87:543-548. 10.1093/bja/87.4.543
10. Knaus WA, Draper EA, Wagner DP, Zimmerman JE: APACHE II: a severity of disease classification system. Crit Care Med 1985, 13:818-829. 10.1097/00003246-198510000-00009
11. Rowan KM, Kerr JH, Major E, McPherson K, Short A, Vessey MP: Intensive Care Society's APACHE II study in Britain and Ireland-II: outcome comparisons of intensive care units after adjustment for case mix by the American APACHE II method. BMJ 1993, 307:977-981. 10.1136/bmj.307.6910.977
12. Harrell FE Jr, Califf RM, Pryor DB, Lee KL, Rosati RA: Evaluating the yield of medical tests. JAMA 1982, 247:2543-2546. 10.1001/jama.1982.03320430047030
13. Hanley JA, McNeil BJ: The meaning and use of the area under a receiver operating characteristic (ROC) curve. Radiology 1982, 143:29-36. 10.1148/radiology.143.1.7063747
14. Hosmer DW Jr, Lemeshow S: Goodness-of-fit tests for the multiple logistic regression model. Commun Stat 1980, A9:1043-1069.
15. Kramer AA, Zimmerman JE: Assessing the calibration of mortality benchmarks in critical care: The Hosmer-Lemeshow test revisited. Crit Care Med 2007, 35:2052-2056. 10.1097/01.CCM.0000275267.64078.B0
16. Cox DR: Two further applications of a model for binary regression. Biometrika 1958, 45:562-565. 10.1093/biomet/45.3-4.562
17. Brier GW: Verification of forecasts expressed in terms of probability. Mon Weather Rev 1950, 75:1-3.
18. Shapiro AR: The evaluation of clinical predictions. A method and initial application. N Engl J Med 1977, 296:1509-1514. 10.1056/NEJM197706302962607
19. Mittlböck M, Schemper M: Explained variation for logistic regression. Stat Med 1996, 15:1987-1997. 10.1002/(SICI)1097-0258(19961015)15:19<1987::AID-SIM318>3.0.CO;2-9
20. DeLong ER, DeLong DM, Clarke-Pearson DL: Comparing the areas under two or more correlated receiver operating characteristic curves: a nonparametric approach. Biometrics 1988, 44:837-845. 10.2307/2531595
21. Wilson EB: Probable inference, the law of succession, and statistical inference. J Am Stat Assoc 1927, 22:209-212. 10.1080/01621459.1927.10502953
22. Minne L, Eslami S, de Keizer N, de Jonge E, de Rooij SE, Abu-Hanna A: Effect of changes over time in the performance of a customized SAPS-II model on the quality of care assessment. Intensive Care Med 2012, 38:40-46. 10.1007/s00134-011-2390-2