Developing and validating a risk prediction model for acute care based on frailty syndromes

BMJ Open

Volumn 5, Issue 10, 2015, Pages

  Soong, J ^a,b   Poots, A J ^a   Scott, S ^c   Donald, K ^c   Bell, D ^a  

^a IMPERIAL COLLEGE LONDON   (United Kingdom)

^b ROYAL COLLEGE OF PHYSICIANS   (United Kingdom)

^c Mercer Oliver Wyman   (United Kingdom)

Author keywords

[No Author keywords available]

Indexed keywords

AGED; ANXIETY; ARTICLE; CHARLSON COMORBIDITY INDEX; COGNITIVE DEFECT; CONSTRUCT VALIDITY; CONTROLLED STUDY; DECUBITUS; DEPENDENT PERSONALITY DISORDER; DEPRESSION; EMERGENCY CARE; FALLING; FEMALE; FRAILTY SYNDROME; GERIATRIC DISORDER; HOSPITAL READMISSION; HUMAN; ICD-10; INCONTINENCE; LENGTH OF STAY; MAJOR CLINICAL STUDY; MALE; MORTALITY; PREDICTION; RISK FACTOR; SYNDROME; WALKING DIFFICULTY; AGING; CODING; COMORBIDITY; ENGLAND; EPIDEMIOLOGY; FACTUAL DATABASE; FRAIL ELDERLY; GERIATRIC ASSESSMENT; HOSPITAL MORTALITY; INTENSIVE CARE; INTERNATIONAL CLASSIFICATION OF DISEASES; MULTIVARIATE ANALYSIS; QUALITY OF LIFE; RECEIVER OPERATING CHARACTERISTIC; STANDARDS; STATISTICAL MODEL; STATISTICS AND NUMERICAL DATA; TRENDS; VALIDATION STUDY; VERY ELDERLY;

AGED; AGED, 80 AND OVER; AGING; CLINICAL CODING; COMORBIDITY; CRITICAL CARE; DATABASES, FACTUAL; ENGLAND; FEMALE; FRAIL ELDERLY; GERIATRIC ASSESSMENT; HOSPITAL MORTALITY; HUMANS; INTERNATIONAL CLASSIFICATION OF DISEASES; LOGISTIC MODELS; MALE; MULTIVARIATE ANALYSIS; PATIENT READMISSION; QUALITY OF LIFE; RISK FACTORS; ROC CURVE;

EID: 84945952528     PISSN: None     EISSN: 20446055     Source Type: Journal    
DOI: 10.1136/bmjopen-2015-008457     Document Type: Article

References (50)

1. Department for Environment, Food and Rural Affairs (Defra) Survey of public attitudes and behaviours towards the environment. 2011.
2. Marengoni A, Angleman S, Melis R, et al. Aging with multimorbidity: a systematic review of the literature. Ageing Res Rev 2011;10:430-9.
3. Wolff JL, Boult C, Boyd C, et al. Newly reported chronic conditions and onset of functional dependency. J Am Geriatr Soc 2005;53:851-5.
4. Department of Health. Improving care and saving money: learning the lessons on prevention and early intervention for older people. 2010.
5. Inouye SK, Studenski S, Tinetti ME, et al Geriatric syndromes: clinical, research, and policy implications of a core geriatric concept. J Am Geriatr Soc 2007;55:780-91.
6. Heppenstall CP, Wilkinson TJ, Hanger HC, et al. Frailty: dominos or deliberation? N Z Med J 2009;122:42-53.
7. Ellis G, Whitehead MA, Robinson D, et al. Comprehensive geriatric assessment for older adults admitted to hospital: meta-analysis of randomised controlled trials. BMJ 2011;343:d6553.
8. Edmans J, Bradshaw L, Gladman JR, et al. The Identification of Seniors at Risk (ISAR) score to predict clinical outcomes and health service costs in older people discharged from UK acute medical units. Age Ageing 2013;42:747-53.
9. Wou F, Gladman JR, Bradshaw L, et al. The predictive properties of frailty-rating scales in the acute medical unit. Age Ageing 2013;42:776-81.
10. Conroy S, Dowsing T. The ability of frailty to predict outcomes in older people attending an acute medical unit. Acute Med2013;12: 74-6.
11. Banerjee J, Conroy S, Cooke MW. Quality care for older people with urgent and emergency care needs in UK emergency departments. Emerg Med J 2013;30:699-700.
12. Acute Care Toolkit 3. Acute medical care for frail older people. London: Royal College of Physicians, 2012.
13. Edmans J, Bradshaw L, Franklin M, et al. Specialist geriatric medical assessment for patients discharged from hospital acute assessment units: randomised controlled trial. BMJ 2013;347:f5874.
14. Rockwood K, Song X, MacKnight C, et al. A global clinical measure of fitness and frailty in elderly people. CMAJ2005;173:489.
15. Rodriguez-Mañas L, Féart C, Mann G, et al. Searching for an operational definition of frailty: a Delphi method based consensus statement: the frailty operative definition-consensus conference project. J Gerontol A Biol Sci Med Sci 2013;68:62-7.
16. Morley JE, Vellas B, van Kan GA, et al. Frailty consensus: a call to action. J Am Med Dir Assoc 2013;14:392-7.
17. Fried LP, Tangen CM, Walston J, et al. Frailty in older adults: evidence for a phenotype. J Gerontol A Biol Sci Med Sci 2001;56: M146-56.
18. Wou F, Conroy S. The frailty syndrome. Medicine 2013;41:13-15.
19. Blodgett J, Theou O, Kirkland S, et al. Frailty in NHANES: comparing the frailty index and phenotype. Arch Gerontol Geriatr 2015;60:464-70.
20. Cesari M, Gambassi G, van Kan GA, et al. The frailty phenotype and the frailty index: different instruments for different purposes. Age Ageing 2014;43:10-12.
21. Isaacs B. The challenge of geriatric medicine. USA: Oxford University Press, 1992.
22. Rockwood K, Mitnitski A, Song X, et al. Long-term risks of death and institutionalization of elderly people in relation to deficit accumulation at age 70. J Am Geriatr Soc 2006;54:975-9.
23. Anpalahan M, Gibson SJ. Geriatric syndromes as predictors of adverse outcomes of hospitalization. Intern Med J 2008;38:16-23.
24. HES Online: Hospital Episode Statistics. 2013. http://www.hscic. gov.uk/hes (accessed Nov 2014).
25. Rockwood K. What would make a definition of frailty successful? Age Ageing 2005;34:432-4.
26. 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.
27. Health and social care information centre. Methodology to create provider and CIP spells from HES APC data: 1-9, 2014. http://www.hscic.gov.uk/media/11859/Provider-Spells-Methodology/pdf/Spells-Methodology.pdf (accessed Nov 2014).
28. Bottle A, Aylin P. Comorbidity scores for administrative data benefited from adaptation to local coding and diagnostic practices. J Clin Epidemiol2011;64:1426-33.
29. Pedregosa F, Varoquaux G, Granfort A, et al. Scikit-learn: machine learning in python. J Mach Learn Res 2011;12:2825-30.
30. Lalkhen AG, McCluskey A. Clinical tests: sensitivity and specificity. Contin Educ Anaesth Crit Care Pain 2008;8:221-3.
31. Hosmer David W Jr, Lemeshow S, Sturdivant RX. Applied logistic regression (Wiley series in probability and statistics). Wiley-Blackwell, 2013:528. 2013-04-26.
32. Wou F, Gladman JRF, Bradshaw L, et al. The predictive properties of frailty-rating scales in the acute medical unit. Age Ageing 2013;42:776-81.
33. Romero-Ortuno R, O'Dwyer C, Byrne D, et al A Risk Index for Geriatric Acute Medical Admissions (RIGAMA). Acute Med2014;13:6-11.
34. Billings J, Blunt I, Steventon A, et al Development of a predictive model to identify inpatients at risk of re-admission within 30 days of discharge (PARR-30). BMJ Open 2012;2:e001667.
35. Kellett J, Clifford M, Ridley A, et al A four item scale based on gait for the immediate global assessment of acutely ill medical patients-one look is more than 1000 words. Eur GeriatrMed 2014;5:92-6.
36. McCusker J, Bellavance F, Cardin S, et al. Detection of older people at increased risk of adverse health outcomes after an emergency visit: the ISAR screening tool. J Am Geriatr Soc 1999;47:1229-37.
37. Smith GB, Prytherch DR, Meredith P, et al The ability of the National Early Warning Score (NEWS) to discriminate patients at risk of early cardiac arrest, unanticipated intensive care unit admission, and death. Resuscitation 2013;84:465-70.
38. Yim VW, Rainer TH, Graham CA, et al. Emergency department intervention for high-risk elders: identification strategy and randomised controlled trial to reduce hospitalisation and institutionalisation. Hong Kong Med J 2011;17(3 Suppl 3):4-7.
39. Braes T, Flamaing J, Sterckx W, et al. Predicting the risk of functional decline in older patients admitted to the hospital: a comparison of three screening instruments. Age Ageing 2009;38:600-3.
40. Dendukuri N, McCusker J, Belzile E. The identification of seniors at risk screening tool: further evidence of concurrent and predictive validity. J Am Geriatr Soc 2004;52:290-6.
41. McCusker J, Bellavance F, Cardin S, et al. Prediction of hospital utilization among elderly patients during the 6 months after an emergency department visit. Ann Emerg Med 2000;36:438-45.
42. Cornette P, Swine C, Malhomme B, et al. Early evaluation of the risk of functional decline following hospitalization of older patients: development of a predictive tool. Eur J Public Health 2006;16: 203-8.
43. Sager MA, Rudberg MA, Jalaluddin M, et al. Hospital admission risk profile (HARP): identifying older patients at risk for functional decline following acute medical illness and hospitalization. J Am Geriatr Soc 1996;44:251-7.
44. Dent E, Chapman I, Piantadosi C, et al. Frailty determinants and discharge outcomes in hospitalised older persons. Australas J Ageing 2012;31:71.
45. Bagshaw SM, Stelfox HT, McDermid RC, et al. Association between frailty and short-and long-term outcomes among critically ill patients: a multicentre prospective cohort study. CMAJ 2014;186: E95-102.
46. Krishnan M, Beck S, Havelock W, et al. Predicting outcome after hip fracture: using a frailty index to integrate comprehensive geriatric assessment results. Age Ageing 2014;43:122-6.
47. Pilotto A, Rengo F, Marchionni N, et al. Comparing the prognostic accuracy for all-cause mortality of frailty instruments: a multicentre 1-year follow-up in hospitalized older patients. PLoS ONE 2012;7: e29090.
48. Wu AW, Yasui Y, Alzola C, et al. Predicting functional status outcomes in hospitalized patients aged 80 years and older. J Am Geriatr Soc 2000;48(5 Suppl):S6-15.
49. Evans SJ, Sayers M, Mitnitski A, et al. The risk of adverse outcomes in hospitalized older patients in relation to a frailty index based on a comprehensive geriatric assessment. Age Ageing 2014;43:127-32.
50. Hosmer DW, Hosmer T, Le Cessie S, et al. A comparison of goodness-of-fit tests for the logistic regression model. Stat Med 1997;16:965-80.