The ALERT scale: An observational study of early prediction of adverse hospital outcome for medical patients

BMJ Open

Volumn 5, Issue 4, 2015, Pages

  Roberts, Daniel ^a   Patrick, Ward ^b   Mojica, Julie ^a   Ostryzniuk, Patricia ^c   Patrick, Margaret ^d   MacKnight, Chris ^b   Kraut, Allen ^a   Shafer, Leigh Anne ^a  

^a UNIVERSITY OF MANITOBA   (Canada)

^b DALHOUSIE UNIVERSITY   (Canada)

^c WINNIPEG REGIONAL HEALTH AUTHORITY   (Canada)

^d Capital District Health Authority   (Canada)

Author keywords

[No Author keywords available]

Indexed keywords

ADVERSE OUTCOME; APACHE; ARTICLE; BREATHING RATE; CANADA; CEREBROVASCULAR ACCIDENT; CHARLSON COMORBIDITY INDEX; CHRONIC DISEASE; COMMUNITY HOSPITAL; DAILY LIFE ACTIVITY; DEATH; GLASGOW COMA SCALE; HEART ARREST; HEART RATE; HIGH RISK PATIENT; HOSPITAL ADMISSION; HOSPITAL PATIENT; HOSPITAL SUBDIVISIONS AND COMPONENTS; HUMAN; INTENSIVE CARE; INTENSIVE CARE UNIT; LEUKOCYTE COUNT; LOW RISK PATIENT; OBSERVATIONAL STUDY; PHYSICAL DISABILITY; PLEURA EFFUSION; PNEUMONIA; PREDICTION; RESUSCITATION; RISK FACTOR; SENSITIVITY AND SPECIFICITY; SIMPLIFIED ACUTE PHYSIOLOGY SCORE; SYSTOLIC BLOOD PRESSURE; TEACHING HOSPITAL; TERTIARY CARE CENTER; ADULT; AGED; FEMALE; HOSPITAL MORTALITY; MALE; MIDDLE AGED; OUTCOME ASSESSMENT; PATIENT TRANSPORT; PROCEDURES; RECEIVER OPERATING CHARACTERISTIC; STATISTICAL MODEL; STATISTICS AND NUMERICAL DATA; UNIVERSITY HOSPITAL;

ADULT; AGED; CANADA; FEMALE; HEART ARREST; HOSPITAL MORTALITY; HOSPITALS, UNIVERSITY; HUMANS; INTENSIVE CARE UNITS; LOGISTIC MODELS; MALE; MIDDLE AGED; OUTCOME ASSESSMENT (HEALTH CARE); PATIENT TRANSFER; ROC CURVE; SENSITIVITY AND SPECIFICITY;

EID: 84929166354     PISSN: None     EISSN: 20446055     Source Type: Journal    
DOI: 10.1136/bmjopen-2014-005501     Document Type: Article

References (18)

1. Bellomo R, Goldsmith D, Uchino S, et al. A prospective before-and-after trial of a medical emergency team. Med J Aust 2003;179:283-7.
2. Morgan R, Williams F, Wright M. An early warning scoring system for detecting developing critical illness. Clin Intensive Care 1997;8:100.
3. Buist MD, Moore GE, Bernard SA, et al. Effects of a medical emergency team on reduction of incidence of and mortality from unexpected cardiac arrests in hospital: preliminary study. BMJ 2002;324:387-90.
4. Parr M, Hadfield J, Flabouris A, et al. The medical emergency team: 12 month analysis of reasons for activation, immediate outcome and not-for-resuscitation orders. Resuscitation 2001;50:39-44.
5. DeVita MA, Bellomo R, Hillman K, et al. Findings of the first consensus conference on medical emergency teams. Crit Care Med 2006;34:2463-78.
6. Ranji SR, Auerbach AD, Hurd CJ, et al. Effects of rapid response systems on clinical outcomes: systematic review and meta-analysis. J Hosp Med 2007;2:422-32.
7. Litvak E, Pronovost PJ. Rethinking rapid response teams. JAMA 2010;304:1375-6.
8. Knaus W, Draper E, Wagner D, et al. APACHE II: a severity of disease classification system. Crit Care Med 1985;13:818-29.
9. Le Gall JR, Lemeshow S, Saulnier F. A new simplified acute physiology score (SAPS II) based on a European/North American multicenter study. JAMA 1993;270:2957-63.
10. Prytherch D, Sirl J, Schmidt P, et al. The use of routine laboratory data to predict in-hospital death in medical admissions. Resuscitation 2005;66:203-7.
11. Olsson T, Terént A, Lind L. Rapid Emergency Medicine Score: a new prognostic tool for in-hospital mortality in nonsurgical emergency department patients. J Intern Med 2004;255:579-87.
12. Olsson T, Terent A, Lind L. Charlson Comorbidity Index can add prognostic information to Rapid Emergency Medicine Score as a predictor of long-term mortality. Eur J Emerg Med 2005;12:220-4.
13. Charlson ME, Pompei P, Ales KL, et al. A new method of classifying prognostic comorbidity in longitudinal studies: development and validation. J Chronic Dis 1987;40:373-83.
14. Katz S, Downs TD, Cash HR, et al. Progress in development of the index of ADL. Gerontologist 1970;10:20-30.
15. Hosmer DW, Lemeshow S. Applied logistic regression (Wiley series in probability and statistics). New York, NY: John Wiley & Sons, 2000.
16. Mallett S, Halligan S, Thompson M, et al. Interpreting diagnostic accuracy studies for patient care. BMJ 2012;345:e3999.
17. Baker SG. Putting risk prediction in perspective: relative utility curves. J Natl Cancer Inst 2009;101:1538-42.
18. Cook NR. Use and misuse of the receiver operating characteristic curve in risk prediction. Circulation 2007;115:928-35.