Validation of a consensus method for identifying delirium from hospital records

Elvira Kuhn, Xinyi Du, Keith McGrath, Sarah Coveney, Niamh O'Regan, Sarah Richardson, Andrew Teodorczuk, Louise Allan, Dan Wilson, Sharon K Inouye, Alasdair M J MacLullich, David Meagher, Carol Brayne, Suzanne Timmons, Daniel Davis, Elvira Kuhn, Xinyi Du, Keith McGrath, Sarah Coveney, Niamh O'Regan, Sarah Richardson, Andrew Teodorczuk, Louise Allan, Dan Wilson, Sharon K Inouye, Alasdair M J MacLullich, David Meagher, Carol Brayne, Suzanne Timmons, Daniel Davis

Abstract

Background: Delirium is increasingly considered to be an important determinant of trajectories of cognitive decline. Therefore, analyses of existing cohort studies measuring cognitive outcomes could benefit from methods to ascertain a retrospective delirium diagnosis. This study aimed to develop and validate such a method for delirium detection using routine medical records in UK and Ireland.

Methods: A point prevalence study of delirium provided the reference-standard ratings for delirium diagnosis. Blinded to study results, clinical vignettes were compiled from participants' medical records in a standardised manner, describing any relevant delirium symptoms recorded in the whole case record for the period leading up to case-ascertainment. An expert panel rated each vignette as unlikely, possible, or probable delirium and disagreements were resolved by consensus.

Results: From 95 case records, 424 vignettes were abstracted by 5 trained clinicians. There were 29 delirium cases according to the reference standard. Median age of subjects was 76.6 years (interquartile range 54.6 to 82.5). Against the original study DSM-IV diagnosis, the chart abstraction method gave a positive likelihood ratio (LR) of 7.8 (95% CI 5.7-12.0) and the negative LR of 0.45 (95% CI 0.40-0.47) for probable delirium (sensitivity 0.58 (95% CI 0.53-0.62); specificity 0.93 (95% CI 0.90-0.95); AUC 0.86 (95% CI 0.82-0.89)). The method diagnosed possible delirium with positive LR 3.5 (95% CI 2.9-4.3) and negative LR 0.15 (95% CI 0.11-0.21) (sensitivity 0.89 (95% CI 0.85-0.91); specificity 0.75 (95% CI 0.71-0.79); AUC 0.86 (95% CI 0.80-0.89)).

Conclusions: This chart abstraction method can retrospectively diagnose delirium in hospitalised patients with good accuracy. This has potential for retrospectively identifying delirium in cohort studies where routine medical records are available. This example of record linkage between hospitalisations and epidemiological data may lead to further insights into the inter-relationship between acute illness, as an exposure, for a range of chronic health outcomes.

Conflict of interest statement

Competing Interests: The authors have declared that no competing interests exist.

Figures

Figure 1. STARD flow diagram showing the…
Figure 1. STARD flow diagram showing the numbers receiving the index test and reference standard.
TP true positive; TN true negative; FP false positive; FN false negative.

References

    1. Siddiqi N, House AO, Holmes JD (2006) Occurrence and outcome of delirium in medical in-patients: A systematic literature review. Age and ageing 35: 350–364.
    1. Witlox J, Eurelings LSM, De Jonghe JFM, Kalisvaart KJ, Eikelenboom P, et al. (2010) Delirium in elderly patients and the risk of postdischarge mortality, institutionalization, and dementia: A meta-analysis. JAMA 304: 443–451.
    1. Young J, Murthy L, Westby M, Akunne A, O'Mahony R (2010) Diagnosis, prevention, and management of delirium: summary of NICE guidance. BMJ 341: c3704.
    1. Partridge JS, Martin FC, Harari D, Dhesi JK (2013) The delirium experience: what is the effect on patients, relatives and staff and what can be done to modify this? International journal of geriatric psychiatry 28: 804–812.
    1. Akunne A, Murthy L, Young J (2012) Cost-effectiveness of multi-component interventions to prevent delirium in older people admitted to medical wards. Age and ageing 41: 285–291.
    1. Inouye SK, Bogardus ST Jr, Charpentier PA, Leo-Summers L, Acampora D, et al. (1999) A multicomponent intervention to prevent delirium in hospitalized older patients. N Engl J Med 340: 669–676.
    1. Marcantonio ER, Flacker JM, Wright RJ, Resnick NM (2001) Reducing delirium after hip fracture: a randomized trial. Journal of the American Geriatrics Society 49: 516–522.
    1. Maclullich AM, Anand A, Davis DH, Jackson T, Barugh AJ, et al. (2013) New horizons in the pathogenesis, assessment and management of delirium. Age and Ageing 42: 667–674.
    1. Inouye SK, Westendorp RG, Saczynski JS (2013) Delirium in elderly people. Lancet
    1. Sampson EL, Blanchard MR, Jones L, Tookman A, King M (2009) Dementia in the acute hospital: prospective cohort study of prevalence and mortality. Br J Psychiatry 195: 61–66.
    1. Davis DH, Muniz Terrera G, Keage H, Rahkonen T, Oinas M, et al. (2012) Delirium is a strong risk factor for dementia in the oldest-old: a population-based cohort study. Brain 135: 2809–2816.
    1. Davis DHJ, Kreisel SH, Muniz Terrera G, Hall AJ, Morandi A, et al. (2013) The epidemiology of delirium: challenges and opportunities for population studies. Am J Geriatr Psychiatry
    1. Johnson JC, Kerse NM, Gottlieb G, Wanich C, Sullivan E, et al. (1992) Prospective versus retrospective methods of identifying patients with delirium. J Am Geriatr Soc 40: 316–319.
    1. Inouye SK, Leo-Summers L, Zhang Y, Bogardus ST Jr, Leslie DL, et al. (2005) A chart-based method for identification of delirium: Validation compared with interviewer ratings using the confusion assessment method. J Am Geriatr Soc 53: 312–318.
    1. Inouye SK, van Dyck CH, Alessi CA, Balkin S, Siegal AP, et al. (1990) Clarifying confusion: the confusion assessment method. A new method for detection of delirium. Annals of Internal Medicine 113: 941–948.
    1. Fong TG, Jones RN, Shi P, Marcantonio ER, Yap L, et al. (2009) Delirium accelerates cognitive decline in Alzheimer disease. Neurology 72: 1570–1575.
    1. Gross A, Jones RN, Habtemariam DA, Fong TG, Tommet D, et al. (2012) Delirium and long-term cognitive trajectory among persons with dementia. Archives of Internal Medicine 172: 1324–1331.
    1. Ryan DJ, O'Regan NA, Caoimh RO, Clare J, O'Connor M, et al. (2013) Delirium in an adult acute hospital population: predictors, prevalence and detection. BMJ Open 3: e001772.
    1. American Psychiatric Association (1987) Diagnostic and Statistical Manual of Mental Disorders, ed 3, revised (DSM-III-R). Washington: American Psychiatric Association.
    1. Bossuyt PM, Reitsma JB, Bruns DE, Gatsonis CA, Glasziou PP, et al. (2003) Towards complete and accurate reporting of studies of diagnostic accuracy: the STARD initiative. BMJ 326: 41–44.
    1. Trzepacz PT, Mittal D, Torres R, Kanary K, Norton J, et al. (2001) Validation of the Delirium Rating Scale-revised-98: comparison with the delirium rating scale and the cognitive test for delirium. J Neuropsychiatry Clin Neurosci 13: 229–242.
    1. Jorm AF (1994) A short form of the Informant Questionnaire on Cognitive Decline in the Elderly (IQCODE): development and cross-validation. Psychological medicine 24: 145–153.
    1. Charlson ME, Pompei P, Ales KL, MacKenzie CR (1987) A new method of classifying prognostic comorbidity in longitudinal studies: development and validation. Journal of chronic diseases 40: 373–383.
    1. Blessed G, Tomlinson BE, Roth M (1968) The association between quantitative measures of dementia and of senile change in the cerebral grey matter of elderly subjects. British Journal of Psychiatry 114: 797–811.

Source: PubMed

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