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The diagnosis, burden and prognosis of dementia: a record-linkage cohort study in England

Authors

Mar Pujades-Rodriguez1

Valentina Assi2

Arturo Gonzalez-Izquierdo4,5

Tim Wilkinson2,3,6

Christian Schnier2,6

Cathie Sudlow2,3,6

Harry Hemingway4,5

William N Whiteley6*

Affiliations

1. Leeds Institute of Health Sciences, University of Leeds, Leeds, UK

2. Usher Institute of Population Health Sciences and Informatics, University of Edinburgh, Edinburgh,

UK

3. Health Data Research UK Scotland, Edinburgh, UK

4. Institute of Health Informatics, University College London, London, UK

5. Health Data Research UK London, London, UK

6. Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK

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*Correspondence to:

[email protected] (WNW)

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mailto:[email protected]

Abstract

Objectives

Electronic health records (EHR) might be a useful resource to study the risk factors and clinical care

of people with dementia. We sought to determine the diagnostic validity of dementia captured in

linked EHR.

Methods and findings

A cohort of adults in linked primary care, hospital, disease registry and mortality records in England,

[CALIBER (CArdiovascular disease research using LInked Bespoke studies and Electronic health

Records)]. The proportion of individuals with dementia, Alzheimer’s disease, vascular and rare

dementia in each data source was determined. A comparison was made of symptoms and care

between people with dementia and age-, sex- and general practice-matched controls, using

conditional logistic regression. The lifetime risk and prevalence of dementia and mortality rates in

people with and without dementia were estimated with random-effects Poisson models.

There were 47,386 people with dementia: 12,633 with Alzheimer’s disease, 9540 with vascular and

1539 with rare dementia. Seventy-four percent of cases had corroborating evidence of dementia.

People with dementia were more likely to live in a deprived area (conditional OR 1.26;95%CI:1.20–

1.31 most vs least deprived), have documented memory impairment (cOR=11.97;95%CI:11.24–

12.75), falls (cOR=2.36;95%CI:2.31–2.41), depression (cOR=2.03; 95%CI:1.98-2.09) or anxiety

(cOR=1.27; 95%CI:1.23-1.32). The lifetime risk of dementia at age 65 was 9.2% (95%CI:9.0%-9.4%), in

men and 14.9% (95%CI:14.7%-15.1%) in women. The population prevalence of recorded dementia

increased from 0.3% in 2000 to 0.7% in 2010. A higher mortality rate was observed in people with

than without dementia (IRR=1.56;95%CI:1.54-1.58).

Conclusions

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Most people with a record of dementia in linked UK EHR had some corroborating evidence for

diagnosis. The estimated 10-year risk of dementia was higher than published population-based

estimations. EHR are therefore a promising source of data for dementia research.

Keywords: cohort, dementia, electronic health records mortality, prevalence, prognosis, risk

assessment

Word count: Abstract = 288; Text= 2,742

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Introduction

Dementia is a common progressive clinical syndrome that develops slowly over years. Many of those

affected are disabled not only by cognitive impairment but also by common co-morbidities of ageing

such as stroke, arthritis, and heart disease. The burden of dementia on patients, carers and the

health system is substantial, and might increase as populations grow older.[1]

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Very long follow-up is needed to study risk factors for dementia, because of the long prodrome

before suspicion of diagnosis, reverse causality, and because it is likely that different factors affect

disease risk at different stages over a lifetime. This means that well conducted prospective studies

with complete follow-up are important, but they are rare and costly.[2,3] More efficient methods to

study dementia, on a large scale and with a low dropout rate, would improve our understanding of

the pathophysiology of this condition. National electronic health records (EHR) linking primary care,

hospital and death records are a potentially important source of data for dementia research. They

include people with the severest manifestations of dementia or disability, who might be under-

represented in bespoke recruited cohorts because they are difficult to recruit or follow-up. They also

capture a wide variety of important health events. However, it is uncertain whether EHRs capture

dementia with sufficient accuracy and completeness.

Studies of the validity of dementia in EHRs reported positive predictive values for a dementia of up to

90% [4,5] (i.e. when a diagnosis is recorded, people usually have dementia). These studies have

relied on hand searching of individual clinical charts, and therefore had modest sample sizes (<500).

EHR might underestimate the proportion of people with dementia (i.e. a low sensitivity) compared

with bespoke cohorts. However, the longitudinal nature of electronic medical records provides

multiple opportunities for capture of a dementia diagnosis, and therefore measurement of the

lifetime risk of dementia could provide a better measure of the sensitivity of EHRs for dementia

diagnosis.

In this study, we sought to determine how dementia is captured in different routinely collected

medical data sources; whether characteristic dementia symptoms might improve dementia

ascertainment; and to determine the lifetime risk of dementia from these records.

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Methods

Study population

We studied a cohort of people registered in the Clinical Practice Research Datalink (CPRD) general

practices between 1st January 1998 and 31st March 2010. At study entry, eligible patients were aged

18 or above at the beginning of the cohort and had at least one year of up-to-standard pre-study

follow-up. We used the CArdiovascular disease research using LInked Bespoke studies and Electronic

health Records (CALIBER) dataset that links individuals in CPRD to national hospital admission and

death records.[6] This linked dataset includes 4% of the English population and is broadly

representative of the UK population in terms of age, sex, ethnicity and overall mortality.[7–9]

Definition of dementia

We identified dementia in the three data sources using the clinical terms (Read version 2) (67 codes),

ICD-9 (12 codes) and ICD-10 (36 codes) classification systems (Figure A and Table A in S1 File). We

defined dementia as the record of one or more diagnostic codes in any of the three data sources at

any time and in any position (i.e. dementia was any of the recorded diagnosis in hospital admission

or death record). We defined people with corroborating evidence of diagnosis if they had dementia

with: (i) more than one record of dementia in the same data source, on different dates; or (ii) a

record of dementia in 2 or 3 data sources; or (iii) a record of falls, confusion, memory problems or

nursing home admission; or (iv) dementia monitoring codes in primary care; or (v) a referral to a

dementia speciality (geriatrics, care of the elderly, psychiatry); or (v) more than one prescription of

rivastigmine, galantamine, donepezil, memantine, which are typically used to treat patients with

Alzheimer’s disease and sometimes patients with dementia in Parkinson’s disease and dementia

with Lewy bodies. We additionally classified people with dementia into four sub-types, Alzheimer’s

disease, vascular, rare and unclassified; using Read and ICD diagnostic codes. Rare dementia

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included fronto-temporal dementia, dementia with Lewy bodies, Parkinson’s, Huntingdon’s, Pick’s or

Creutzfeld-Jakob diseases, and HIV-related dementia.

Selection of comparison group

For each case with dementia identified in primary or hospital care, we randomly selected up to ten

people without dementia (concurrent sampling), who were matched on sex, year of birth and

general practice. Controls had to be alive and actively registered in the general practice at the date

of diagnosis of the matched dementia case, and to have had a contact with the practice within the

year prior or after the matched index date. A total of 47151 people with dementia (99.5% of the

total identified) were matched. They were followed up until death, transfer out of their primary care

practice, or the date of administrative censoring (March 2010).

Statistical analysis

We described the frequency and proportion of people with dementia and its subtypes, in the linked

data and in each data source. We compared symptoms and management characteristics of people

with dementia in cases and matched controls using conditional logistic regression that takes into

account the matched structure of the data and consequently adjusts the results for the matching

factors. We measured deprivation with the index of multiple deprivation, and divided the population

into fifths based on this measure.[10] We calculated the 10-year and lifetime risks of dementia and

Alzheimer’s according to age and gender, using Kaplan-Meier methods corrected for competing risk

of death and using age as the time-scale. For this analysis we included all registered patients who

were alive, registered in the cohort and without any dementia diagnosis, at the beginning of follow-

up (i.e. earliest date of study eligibility), for example at their 65 th, 75th and 85th birthdays. Such

follow-up then ended on the date of first recorded dementia diagnosis (for cases) or the earliest of

date of death, practice deregistration or last data collection date in the practice. We then estimated

the point-prevalence of dementia in the entire cohort on 1st July 2000 and 2005 and on 1st January

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2010. We counted as cases also patients who were diagnosed with dementia only at death, when

this happened within a year from the analysis time points. Finally we compared overall and sex-

specific mortality rates ratios in people with and without dementia in the matched subset. We

performed this analysis using random-effects Poisson models, adjusted for age and sex as

appropriate, with age as the time-scale. Cox proportional hazard models were not used because the

hazard ratio for mortality was not constant over time. For this analysis the observation period began

on the date of first recorded dementia diagnosis of the matched case.

All analyses were performed using Stata 13. The study was registered at www.clinicaltrials.gov

(NCT02549872). Approval was granted by the Independent Scientific Advisory Committee of the

Medicines and Healthcare products regulatory agency (protocol no. 15_138).

Role of the funding source

The funding source had no role in the preparation of the manuscript.

Results

Diagnosis ascertainment and data source overlap

We identified 47,386 people with dementia, of whom 34,925 (74%) had corroborating evidence to

support their diagnosis (Figure B in S1 File). A total of 22,184 (47%) could be classified into a

dementia subtype: 12,633 (27%) had Alzheimer’s disease, 9,540 (20%) had vascular dementia and

1,539 (3%) had a rare dementia (Table B in S1 File). Compared to people with unclassified dementia,

a greater proportion of those with a specific dementia subtype had corroborating evidence for their

diagnosis (82% of Alzheimer’s disease, 71% of vascular, 69% of rare and 62% of unclassified

subtype).

Of the 47,386 cases of dementia, 55% were captured in primary care, 65% in hospital records, and

26% in the national death register only (Table 1). Overall, 44% of dementia cases were captured in

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hospital or in the mortality registry but not in primary care, and 23% were captured in primary care

records only (Fig 1A). In each data source, most people had corroborating evidence of dementia

(88% in primary care, 76% in hospital and 83% in the death registry). Overall, the proportion of

people with dementia who had corroborating evidence was 74%. Compared with other data sources,

a higher proportion dementia cases captured in the primary care were prescribed dementia

medication (18% versus 11% in hospital or 9% in the mortality registry), had recorded symptoms

(27% versus 23% or 25%) and had evidence of dementia monitoring (40% versus 22% or 22%) or of

referral to a relevant speciality (12% versus 10% or 8%).

Overall, a minority of patients with dementia had a primary care record of memory impairment,

confusion or admission to nursing home (23%), a record of dementia monitoring (27%) or had been

referred to a geriatrician or care of the elderly psychiatrist (10%). Drugs typically indicated for

Alzheimer’s dementia, dementia with Lewy bodies or dementia with Parkinson’s disease were more

commonly prescribed to people with Alzheimer’s disease (27%) or rare (26%) dementias than to

people with vascular (6%) or with unclassified dementia subtype (5%). Dementia subtypes were

broadly consistently recorded across data sources, i.e. only 9% of people with Alzheimer’s disease

also had vascular codes, and only 12% of those with vascular dementia also had Alzheimer’s codes;

(Fig 21B, Table B in S1 File).

There were 647 people with 2 or more prescriptions for dementia medication who had no dementia

diagnosis in any of the three data sources. The characteristics of this group were similar to people

identified with dementia i.e. 32% had dementia symptoms or nursing home admission, 14% were

monitored for dementia in primary care, and 14% had been referred to a dementia relevant

speciality.

Factors associated with dementia

At diagnosis, most people with dementia were over 80 years old; 3% were <60 years, 6% were 60-69

years, 25% were 70-79 years and 66% were >80 years (Table C in S1 File). Sixty-six percent of them

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were women. Compared with matched controls, people with dementia were more likely to live in a

deprived area (conditional OR 1.26, 95%CI: 1.20-1.31 for most vs least deprived; Table 2). They were

also more likely to have record of memory impairment (conditional OR 11.97, 95%CI:11.24-12.75),

confusion (conditional OR 9.57, 95%CI:9.14-10.02), falls (conditional OR 2.36 95%CI:2.31-2.41),

depression (conditional OR 2.03, 95%CI:1.98-2.09) or anxiety (conditional OR 1.27, 95%CI:1.23-1.32).

Where a diagnosis of depression was recorded, it was prior to dementia diagnosis in 71% of cases

(5993/8449). People with dementia more often had a recorded power of attorney (conditional OR

8.34, 95%CI: 7.24-9.61), or had been admitted to a nursing home (conditional OR 7.09, 6.75-7.44).

However only a minority of people with a diagnosis of dementia had a record of any one of these

factors. The proportion of patients with dementia who had a missed a GP appointment was similar

to patients without dementia (28% vs 27%, OR 1.38, 1.11-1.16), and the annual rate of GP

consultation was similar in the two groups (proportions with >5 appointments per year were 36% vs

56%). However, the annual hospital admission rate was higher in people with than without dementia

(proportions of >2 admissions per year were 3% vs <1%).

Prevalence of dementia

The prevalence of dementia increased markedly with age and over time, in both men and women

(Fig 32). In 2010, in men the prevalence was much higher over 90 (8.7%) than under 50 years (0.2%)

(Table C in S1 File). The estimates were substantially higher in women than in men in the eldest age

group (14.2% vs. 8.7% in 2010). The prevalence of dementia gradually increased over time in men

and women of all ages, for almost all dementia subtypes (Figure C in S1 File) and for diagnosis

captured in primary and hospital records (Figure D in S1 File).

Lifetime risks of dementia

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Estimates of lifetime risk of dementia and Alzheimer’s disease are shown in Table 3. The lifetime risk

of dementia in women increased modestly with age, from 14.9% (95%CI 14.7%-15.1%) at 65 years to

21.8% (95%CI 21.3%-22.3%) at 85 years. Lower estimates were found in men: 9.2% (95%CI 9.0%-

9.4%) at 65 years, and 15.4% (95%CI 14.7%-16.0%) at 85 years.

Mortality associated with dementia

In total, 159,674 deaths were recorded during a median follow-up of 1.7 years (inter-quartile range

0.6 to 3.4), 34,528 amongst people with dementia and 125,146 amongst those without dementia

(Table 4). The incidence rate ratio of mortality for people with dementia compared to individuals

without the disease was 1.56 (95% CI:1.54-1.58). Estimates were similar in men and in women.

Discussion

Using contemporary, nationally-representative linked primary care, hospital records and the death

registry from 2,524,144 people in England and Wales, we identified people with recorded diagnostic

codes of dementia and dementia subtypes. The large majority of people with dementia had

corroborating evidence of diagnosis, including recording of multiple diagnostic records in one or

more data sources, symptoms and care features characteristics of dementia or were prescribed

dementia medication. The lifetime risk of dementia at 65 years was 15% in women and 9% in men,

and mortality was 1.56 higher in people with than without dementia.

Our findings highlight the importance of using multiple linked data sources for defining dementia in

EHRs. No individual data source analysed had complete coverage of coded dementia . Six percent

were only recorded in the death registry, thirty-two percent only in hospital records and twenty-

three percent only in primary care. Because data in CALIBER were anonymised, we could not validate

dementia cases against patient clinical charts.

However, subgroups of dementia codes have been validated in previous EHR-based studies.

[4,5,11,12] In addition, our estimated dementia lifetime risks are similar to figures reported in

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previous population based cohort studies.[13] Our study suggests that Read-coded symptoms on

their own, cannot be used to identify unrecorded patients with dementia, because these are

infrequently recorded and are insufficiently specific, even in combination, to accurately identify

cases. Future work with natural language processing methods of free text collected during the

consultation would be needed to make better use of symptom data in electronic records.

In studies based on the analysis of EHRs, lifetime risk of dementia is likely to be a more suitable

measure of disease risk than absolute incidence rates, given that the time of onset of dementia is

difficult to define in clinical practice. Lifetime risk is probably the most important statistic for an

individual when planning their future needs. The lifetime risk of dementia depends on the duration

of life, and is affected by the competing risks of death from other causes and the incidence of

dementia in a population. We compared the 10 year risk of dementia from the Framingham

study[14] with our estimates (Table E in S1 File). Our lifetime risk estimates were slightly higher than

those reported in the US in 2005. For example, the 10 year risks of all dementia found in the

Framingham study at 75 in men was 7.6%, and in women 7.4%, as compared with 12.8% and 16.6%

in our study.

The prevalence of dementia at different ages in this study in England was lower than estimates

reported in a community prevalence study with participants recruited from Cambridgeshire,

Liverpool and Newcastle. In that study in 2001, prevalences from age 65-69, 70-74, 75-79, 80-84, 85-

90 and over 90 in men were: 1.2, 3.0, 5.2, 10.6, 12.8, 17.1% and in women 1.8, 2.5, 6.2, 9.5, 18.1,

and 35%. Our prevalence estimates were approximately half of this in 2000, but about two-thirds of

this in 2010, perhaps indicating improvement in recording. Community based incidence studies

using formal instruments are likely to ascertain dementia with a lower severity, and it is possible that

those in the EHRs represent only those in a later stage of illness, those with clinically evident

dementia[15] or with more severe symptoms.[12] Given that the benefits of early dementia

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diagnosis have not been shown, and that the impact that such diagnosis has on patients and their

relatives, GPs may hesitate to formally diagnose the disease until symptoms become disabling.

Although we have examined UK linked EHR from 1998 to 2010, our conclusions may not be

transportable to other EHR datasets covering different time periods. With changing UK practice,

diagnostic validity of a dementia record may change, with better ascertainment achieved in recent

years after a significant effort to improve dementia diagnosis in primary care. Our results are not

generalizable to other health systems, and therefore researchers working with data from these

systems should aim to determine the validity of dementia diagnosis, either by linking and/or

comparing information from existing or new disease cohorts to their EHR data sources, though case

review, or conducting a similar analysis to ours.[16]

Although linked EHR are an efficient source of data for dementia research, there are a number of

weakness to be considered. First, there may be variation in case ascertainment and validity of

diagnosis across regions, depending on hospital or primary care diagnostic or management

behaviours. Second, under ascertainment of diagnosis during the early stages of the condition is

likely- hence our recommendation for a lifetime approach. Finally, there is often limited data on

important prognostic factors, such as education and family history or APOE4 allele, although these

might eventually be obtained through linkage to other data sources.

Conclusion

This study provides evidence that the diagnosis of dementia in linked electronic health records has

sufficient validity for large scale epidemiological studies. The major value of current records is found

in coded diagnoses, rather than additional symptoms or other care episodes, which are seldom

recorded. Despite reasonable concerns that that electronic health records underestimate the point

prevalence of dementia compared to research studies, the calculated lifetime risk of dementia from

these electronic health records is similar to population based estimates.

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Declaration of interests

This work uses data provided by patients and collected by the NHS as part of their care and support.

The authors have no competing interests.

Copyright

The Corresponding Author has the right to grant on behalf of all authors and does grant on behalf of

all authors, a worldwide licence to the Publishers and its licensees in perpetuity, in all forms, formats

and media (whether known now or created in the future), to i) publish, reproduce, distribute, display

and store the Contribution, ii) translate the Contribution into other languages, create adaptations,

reprints, include within collections and create summaries, extracts and/or, abstracts of the

Contribution, iii) create any other derivative work(s) based on the Contribution, iv) to exploit all

subsidiary rights in the Contribution, v) the inclusion of electronic links from the Contribution to

third party material where-ever it may be located; and, vi) licence any third party to do any or all of

the above.

Transparency declaration

WNW affirms that the manuscript is an honest, accurate, and transparent account of the study being

reported; that no important aspects of the study have been omitted; and that any discrepancies

from the study as planned (and, if relevant, registered) have been explained.

References

1. Satizabal CL, Beiser AS, Chouraki V, Chêne G, Dufouil C, Seshadri S. Incidence of Dementia

11

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295

296

297

298

299

300

301

302

303

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305

306

307

308

309

310

311

312

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over Three Decades in the Framingham Heart Study. N Engl J Med. Massachusetts Medical

Society; 2016;374: 523–532. doi:10.1056/NEJMoa1504327

2. Chatfield MD, Brayne CE, Matthews FE. A systematic literature review of attrition between

waves in longitudinal studies in the elderly shows a consistent pattern of dropout between

differing studies. J Clin Epidemiol. 2005;58: 13–9. doi:10.1016/j.jclinepi.2004.05.006

3. Matthews FE, Chatfield M, Freeman C, McCracken C, Brayne C, MRC Cognitive Function and

Ageing Study. Attrition and bias in the MRC cognitive function and ageing study: an

epidemiological investigation. BMC Public Health. 2004;4: 12. doi:10.1186/1471-2458-4-12

4. Francesconi P, Gini R, Roti L, Bartolacci S, Corsi A, Buiatti E. The Tuscany experimental registry

for Alzheimer’s disease and other dementias: how many demented people does it capture?

Aging Clin Exp Res. 2007;19: 390–3.

5. van de Vorst IE, Vaartjes I, Sinnecker LF, Beks LJM, Bots ML, Koek HL. The validity of national

hospital discharge register data on dementia: a comparative analysis using clinical data from

a university medical centre. Neth J Med. 2015;73: 69–75.

6. Denaxas SC, George J, Herrett E, Shah AD, Kalra D, Hingorani AD, et al. Data Resource Profile:

Cardiovascular disease research using linked bespoke studies and electronic health records

(CALIBER). Int J Epidemiol. Oxford University Press; 2012;41: 1625–1638.

doi:10.1093/ije/dys188

7. Mathur R, Bhaskaran K, Chaturvedi N, Leon DA, van Staa T, Grundy E SL. Completeness and

usability of ethnicity data in UK-based primary care and hospital databases. Public Heal.

2014;36: 684–92.

8. Gallagher A, Puri S, van Staa T. Linkage of the General Practice Research Database (GPRD)

with other data sources. Pharmacoepidemiol Drug Saf 2011;20(Supplement 1). 2011;20:

S230–S231.

12

314

315

316

317

318

319

320

321

322

323

324

325

326

327

328

329

330

331

332

333

334

335

336

337

9. Herrett E, Gallagher AM, Bhaskaran K, Forbes H, Mathur R, van Staa T, et al. Data Resource

Profile: Clinical Practice Research Datalink (CPRD). Int J Epidemiol. Oxford University Press;

2015;44: 827–36. doi:10.1093/ije/dyv098

10. Noble M, Mclennan D, Wilkinson K WA. Indices of Deprivation 2007. 2007.

11. Romero JP, Benito-León J, Mitchell AJ, Trincado R, Bermejo-Pareja F. Under reporting of

dementia deaths on death certificates using data from a population-based study (NEDICES). J

Alzheimers Dis. 2014;39: 741–8. doi:10.3233/JAD-131622

12. Matthews FE, Stephan BCM, Robinson L, Jagger C, Barnes LE, Arthur A, et al. A two decade

dementia incidence comparison from the Cognitive Function and Ageing Studies I and II. Nat

Commun. Nature Publishing Group; 2016;7: 11398. doi:10.1038/ncomms11398

13. Seshadri S, Wolf PA, Beiser A, Au R, McNulty K, White R, et al. Lifetime risk of dementia and

Alzheimer’s disease. The impact of mortality on risk estimates in the Framingham Study.

Neurology. 1997;49: 1498–504.

14. Seshadri S, Beiser A, Kelly-Hayes M, Kase CS, Au R, Kannel WB, et al. The Lifetime Risk of

Stroke. Stroke. 2006;37.

15. Eefsting JA, Boersma F, Van den Brink W, Van Tilburg W. Differences in prevalence of

dementia based on community survey and general practitioner recognition. Psychol Med.

1996;26: 1223–30. doi:10.1017/S0033291700035947

16. Perera G, Pedersen L, Ansel D, Alexander M, Arrighi HM, Avillach P, et al. Dementia

prevalence and incidence in a federation of European Electronic Health Record databases—

The European Medical Informatics Framework resource. Alzheimer’s Dement. 2017;

doi:10.1016/j.jalz.2017.06.2270

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Supporting information

S1 File. Supplementary data

Table A. Dementia diagnostic codes used to identify people with dementia in hospital (ICD-10),

mortality registry (ICD-9 and ICD-10) and primary care (Read codes)

Table B. Capture of diagnosis of dementia and its subtypes and overlap between data sources

Table C. Time trends in prevalence of dementia according to age group and sex

Table D. Median residual life expectancy in years

Table E. Comparison of 10-year lifetime risks of dementia in our study and in the Framingham study

Figure A. Defining cases of dementia and non-dementia in national samples of structured electronic

health records: phenotype algorithm using multiple ontologies (ICD-10, Read-2, BNF)

Figure B. Study flow chart

Figure C. Time trends in prevalence of dementia subtypes according to age group

Figure D. Time trends in prevalence of dementia diagnosis according to data source capture

Figure legends

Fig. 1. Capture of dementia in EHRs across the entire registration period in primary care,

hospital episode statistics, and death records

A) Capture of diagnosis across three data sources; B)Figure 2. Capture of dementia by

subtypesvascular dementia, Alzheimer’s dementia, rare dementia and dementia without

specific diagnosis

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Fig. 32. Time trends in prevalence of dementia according to age group and sex

Point prevalence estimated on 1st July 2000 and 2005 and 1st January 2010

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Table 1. Capture of diagnosis of dementia and overlap between data sources

Dementia diagnosis All Primary care Hospital Mortality registry

No of people 47,386 26,269 31,034 12,232

No. of people with corroborating evidence 34,925 (74%) 23,225 (88%) 23,658 (76%) 10,191 (83%)

In multiple data sources 18,288 (39%) 15,348 (58%) 15,913 (51%) 9,176 (75%)

Multiple records in same data source 19,465 (41%) 8,770 (33%) 13,805 (44%) NA

Prescribed dementia medication 5,264 (12%) 4,438 (18%) 3,087 (11%) 1,001 (9%)

Dementia symptoms 11,066 (23%) 7,096 (27%) 7,008 (23%) 3,075 (25%)

Dementia monitoring in primary care 12,590 (27%) 10,537 (40%) 6,977 (22%) 2,664 (22%)

Referral to relevant speciality 4,509 (10%) 3,038 (12%) 3,031 (10%) 963 (8%)

Note: NA, non-applicable

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Table 2. Characteristics of people with dementia compared with age-, practice- and sex-matched

controls

People with dementia

People without dementia

Adjusted conditional OR (95%CI)

N=47,151 N=324,627Index of multiple deprivation (fifths)1 (least) 10,741 (23%) 77,516 (24%) 12 10,860 (23%) 76,460 (24%) 1.05 (1.0 –1.09)3 9,986 (21%) 66,982 (21%) 1.12 (1.08–1.16)4 8,440 (18%) 58,978 (18%) 1.12 (1.08–1.16)5 (most) 7,124 (15%) 44,691 (14%) 1.26 (1.20–1.31)Memory impairmentYes 2,769 (6%) 1,842 (1%) 11.97 (11.24–12.75)No 47,382 (94%) 322,785 (99%) 1Confusion Yes 4,829 (10%) 3,844 (1%) 9.57 (9.14–10.02)No 42,322 (90%) 320,783 (99%) 1FallsYes 18,673 (40%) 67,268 (21%) 2.36 (2.31–2.41)No 28,478 (60%) 257,359 (79%) 1DepressionYes 8,449 (18%) 31,946 (10%) 2.03 (1.98–2.09)No 38,702 (82%) 292,681 (90%) 1AnxietyYes 4,262 (9%) 24,046 (7%) 1.27 (1.23–1.32)No 42,889 (91%) 300,581 (93%) 1Admission to nursing homeYes 4,447 (9%) 4,868 (1%) 7.09 (6.75–7.44)No 42,704 (91%) 319,759 (99%) 1Power of attorneyYes 459 (1%) 362 (<1%) 8.34 (7.24–9.61)No 46,692 (99%) 324,265 (>99%) 1Missed appointmentsYes 13,095 (28%) 87,548 (27%) 1.38 (1.11–1.16)No 34,056 (72%) 237,079 (73%) 1Median (IQR)1 1 (1-3) 1 (1 – 2)GP consultation rate2

Missing 526 (1%) 0 (0%)0 23,993 (51%) 19,637 (6%) 10-5 5,564 (12%) 123,302 (38%) 0.04 (0.04-0.04)>5 17,068 (36%) 181,688 (56%) 0.07 (0.07-0 .07)Hospital admission rate2 Missing0 526 (1%) 0 (0%)0-1 16,828 (36%) 161,866 (50%) 11-2 28,412 (60%) 161,934 (50%) 1.67 (1.63–1.71)>2 1,385 (3%) 827 (<1%) 15.15 (13.83–16.59)

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1Amongst people with at least one missed appointment; 2Annual rate in the 5 years prior to entry

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Table 3. Lifetime risk of dementia in men and women estimated in linked primary care, hospital episode and death records

All dementia Alzheimer’s disease

No. of people at risk

10-year risk in % Lifetime risk in %* No. of people at risk 10-year risk in % Lifetime risk in %*

Women

65 years 321,851 2.8 (2.7-2.9) 14.9 (14.7 -15.1) 321,851 1.0 (0.9 -1.1) 4.9 (4.7-5.0)

75 years 197,918 16.6 (16.3-16.8) 21.7 (21.4-21.9) 197,918 5.0 (4.8-5.1) 6.2 (6.0-6.3)

85 years 83,694 23.8 (23.3-24.3) 21.8 (21.3-22.3) 83,694 4.5 (4.2-4.7) 4.1 (3.9-4.4)

Men

65 years 253,203 2.7 (2.6–2.8) 9.2 (9.0-9.4) 253,203 0.7 (0.7-0.8) 2.5 (2.4-2.6)

75 years 128,957 12.8 (12.6-13.1) 14.5 (14.2-14.7) 128,957 3.4 (3.2-3.5) 3.7 (3.5- 3.8)

85 years 38,822 17.4 (16.7-18.2) 15.4 (14.7-16.0) 38,822 3.5 (3.1-3.8) 3.2 (2.9-3.5)

Note: (*) Lifetime risk calculated on the median residual life from the UK National Lifetable. For women aged 65, 75 and 85 the median years of residual life expectancy were 21.04, 13.11 and 6.81 years respectively, whereas for men aged 65, 75 and 85 they were 18.61, 11.35 and 5.85 years respectively.

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Table 4. Association between dementia and mortality

No. of people No. of deaths IRR (95% CI)

Overall

People without dementia 324,627 125,146 1

People with dementia 47,151 34,528 1.56 (1.54–1.58)

Men



Women



Note: IRR, incidence rate ratios adjusted for age and sex (as appropriate) from random-effects Poisson models

comparing people with dementia and randomly selected people without dementia matched for age, sex and

general practice

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SUPPLEMENTARY MATERIAL

TABLES






Table E. Comparison of 10-year lifetime risks of dementia in our study and in the Framingham study

FIGURES

Figure A. Defining cases of dementia and non-dementia in national samples of structured electronic

health records: phenotype algorithm using multiple ontologies (ICD-10, Read-2, BNF)

Figure B. Study flow chart



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ICD-10

Alzheimer’s disease

F00 Dementia in Alzheimer's disease

F000A Dementia in Alzheimer's disease with early onset

F001A Dementia in Alzheimer's disease with late onset

F002A Dementia in Alzheimer's disease, atypical or mixed type

F009A Dementia in Alzheimer's disease, unspecified

G30 Alzheimer’s disease

G30.0 Alzheimer’s disease with early onset

G30.1 Alzheimer’s disease with late onset

G30.8 Other Alzheimer disease, unspecified

G30.9 Alzheimer's disease unspecified

Vascular dementia

F01 Vascular dementia

F010 Vascular dementia of acute onset

F011 Multi-infarct dementia

F012 Subcortical vascular dementia

F013 Mixed cortical and subcortical vascular dementia

F018 Other vascular dementia

F019 Vascular dementia, unspecified

I67.3 Binswanger's disease

Rare dementia

F020A Dementia in Pick's disease

F021A Dementia in Creutzfeldt-Jakob disease

F022A Dementia in Huntington's disease

F023A Dementia in Parkinson's disease

F024A Dementia in human immunodef virus [HIV] disease

F028A Dementia in other specified diseases classified elsewhere

Unspecified dementia type

F02 Dementia in other diseases classified elsewhere

F03X Unspecified dementia

F051 Delirium superimposed on dementia

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Possible dementia

F050 Delirium not superimposed on dementia, so described

G31.0 Circumscribed brain atrophy

G31.1 Senile degeneration of brain, not otherwise classified

G31.2 Degeneration of nervous system due to alcohol

G31.8 Other specified degenerative diseases of nervous system

G31.9 Degenerative disease of nervous system, unspecified

ICD-9


331.0 Alzheimer's disease

Vascular dementia

290.4 Vascular dementia

Rare dementia

046.19 Creutzfeld Jacob

333.4 Huntingdon's

331.1 Frontotemporal dementia


290.0 Senile dementia, uncomplicated

290.1x Presenile dementia

290.2 Senile dementia with delusional features

290.3 Senile dementia with delirium

Possible dementia

294.9 unspecified persistent mental disorders

331.2 Senile degeneration

331.9 Cerebral degeneration unspecified

Read code


Eu00012 [X]Primary degen dementia, Alzheimer's type, presenile onset

Eu00013 [X]Alzheimer's disease type 2

Fyu3000 [X]Other Alzheimer's disease

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Eu00111 [X]Alzheimer's disease type 1

Eu01111 [X]Predominantly cortical dementia

Eu00113 [X]Primary degen dementia of Alzheimer's type, senile onset

Eu00011 [X]Presenile dementia,Alzheimer's type

Eu00000 [X]Dementia in Alzheimer's disease with early onset

Eu00z00 [X]Dementia in Alzheimer's disease, unspecified

Eu00100 [X]Dementia in Alzheimer's disease with late onset

F110100 Alzheimer's disease with late onset

F110000 Alzheimer's disease with early onset

Eu00200 [X]Dementia in Alzheimer's dis, atypical or mixed type

Eu00112 [X]Senile dementia,Alzheimer's type

Eu00z11 [X]Alzheimer's dementia unspec

Eu00.00 [X]Dementia in Alzheimer's disease

F110.00 Alzheimer's disease

Vascular dementia

E004100 Arteriosclerotic dementia with delirium

Eu01000 [X]Vascular dementia of acute onset

E004200 Arteriosclerotic dementia with paranoia

Eu01y00 [X]Other vascular dementia

E004300 Arteriosclerotic dementia with depression

Eu01200 [X]Subcortical vascular dementia

E004000 Uncomplicated arteriosclerotic dementia

Eu01300 [X]Mixed cortical and subcortical vascular dementia

Eu01z00 [X]Vascular dementia, unspecified

E004z00 Arteriosclerotic dementia NOS

Eu01.11 [X]Arteriosclerotic dementia

Eu01100 [X]Multi-infarct dementia

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E004.00 Arteriosclerotic dementia

E004.11 Multi infarct dementia

Eu01.00 [X]Vascular dementia

Rare dementia

Eu02400 [X]Dementia in human immunodef virus [HIV] disease

Eu02100 [X]Dementia in Creutzfeldt-Jakob disease

Eu02200 [X]Dementia in Huntington's disease

Eu02000 [X]Dementia in Pick's disease

F111.00 Pick's disease

Eu02300 [X]Dementia in Parkinson's disease

Eu02500 [X]Lewy body dementia

F116.00 Lewy body disease


E002z00 Senile dementia with depressive or paranoid features NOS

Eu02z11 [X] Presenile dementia NOS

Eu02y00 [X]Dementia in other specified diseases classif elsewhere

E001000 Uncomplicated presenile dementia

E001100 Presenile dementia with delirium

E012.00 Other alcoholic dementia

Eu04100 [X]Delirium superimposed on dementia

Eu02z13 [X] Primary degenerative dementia NOS

E001300 Presenile dementia with depression

E001200 Presenile dementia with paranoia

Eu02z16 [X] Senile dementia, depressed or paranoid type

E001z00 Presenile dementia NOS

E002.00 Senile dementia with depressive or paranoid features

E003.00 Senile dementia with delirium

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Eu10711 [X]Alcoholic dementia NOS

E012.11 Alcoholic dementia NOS

E041.00 Dementia in conditions EC

E002000 Senile dementia with paranoia

Eu02.00 [X]Dementia in other diseases classified elsewhere

E002100 Senile dementia with depression

E001.00 Presenile dementia

9hD0.00 Excepted from dementia quality indicators: Patient unsuitabl

Eu02z14 [X] Senile dementia NOS

E000.00 Uncomplicated senile dementia

Eu02z00 [X] Unspecified dementia

E00..11 Senile dementia

E00..12 Senile/presenile dementia

E02y100 Drug-induced dementia

Possible dementia

Eu04000 [X]Delirium not superimposed on dementia, so described

Note: Possible dementia codes were used for exclusion from the potentially eligible individuals for

the random selection of people without dementia (matched sample)

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All Unclassified Alzheimer’s Vascular Rare

No. of people with dementia

diagnosis

47386 25208 12633 9540 1539

No. of people with dementia

diagnosis and corroborating evidence

34925 (74%) 15523 (62%) 10296 (82%) 6735 (71%) 1065 (70%)

Recorded in multiple data sources* 18288 (39%) 6437 (26%) 3634 (29%) 1919 (20%) 208 (14%)

Multiple records in same data source* 19465 (41%) 6735 (27%) 5388 (43%) 2507 (26%) 395 (26%)

Prescribed dementia medication 5264 (12%) 1284 (5%) 3360 (27%) 603 (6%) 396 (26%)

Dementia symptoms 11066 (23%) 5203 (21%) 3456 (27%) 2515 (26%) 380 (25%)

Dementia monitoring in primary

care

12590 (27%) 4546 (18%) 5001 (40%) 3225 (34%) 490 (32%)

Referral to relevant speciality 4509 (10%) 1883 (7%) 1483 (12%) 1185 (12%) 184 (12%)

Dementia subtype

Alzheimer’s 12633 (27%) NA - 1182 (12%) 222 (14%)

Vascular 9540 (20%) NA 1182 (9%) - 146 (9%)

Rare 1539 (3%) NA 222 (2%) 146 (2%) -

*For columns related to each of the dementia subtypes, this refers to the number of people who had a

diagnosis of the dementia subtype in more than one data source (e.g. in primary care and hospital) or in the

same data source, as appropriate.

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Men Women

Age group

No. of people

with dementia

Total population Prevalence (%)

No. of people

with dementia

Total population Prevalence (%)

2000

18-49 11 342191 <.01 16 330915 <.04

50-59 40 107298 0.04 29 104566 0.03

60-69 130 74982 0.17 130 77244 0.17

70-79 381 54212 0.70 593 69091 0.86

80-89 501 21516 2.33 1171 39672 2.95

90+ 105 2893 3.63 445 9318 4.78

2005

18-49 51 407168 0.01 36 392112 0.01

50-59 70 123416 0.06 83 121483 0.07

60-69 238 92079 0.26 234 93421 0.25

70-79 826 60834 1.36 1084 73490 1.48

80-89 1146 27274 4.20 2699 46995 5.74

90+ 280 3816 7.34 1200 11408 10.52

2010

18-49 72 383801 0.02 61 372857 0.02

50-59 141 123930 0.11 109 120695 0.09

60-69 369 108741 0.34 313 110851 0.28

70-79 957 66187 1.45 1145 75422 1.52

80-89 1638 32406 5.05 3314 49468 6.70

90+ 443 5087 8.71 1893 13295 14.24

Figure note: Point prevalence estimated on 1st July 2000 and 2005 and 1st January 2010

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At age Women Men

65 21.0 18.6

75 13.1 11.4

85 6.8 5.9

Note: Lifetime risk calculated on the median residual life from the UK National Lifetable. For women aged 65,

75 and 85 the median years of residual life expectancy were 21.04, 13.11 and 6.81 years respectively, whereas

for men aged 65, 75 and 85 they were 18.61, 11.35 and 5.85 years respectively.

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Table E. Comparison of 10-year lifetime risks of dementia in our study and in the Framingham

study

10-year risk of dementia in our

study in % (95% CI)

10-year risk of dementia in the

Framingham study in % (95% CI)*

Women

65 2.8 (2.7–2.9) 1.0 (0.4-1.5)

75 16.6 (16.3–16.8) 7.4 (6.0-8.8)

85 23.8 (23.3–24.3) 20.3 (17.2-23.5)

Men

65 2.7 (2.6–2.8) 1.6 (0.8-2.4)

75 12.8 (12.6–13.1) 7.6 (5.8-9.3)

85 17.4 (16.7-18.2) 13.8 (9.9-17.7)

*Reported by Seshadri S, Beiser A, Kelly-Hayes M, et al. (2006) The Lifetime Risk of Stroke. Stroke;

37(2): 345-50.

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Figure A. Defining cases of dementia and non dementia in national samples of structured

electronic health records: phenotype algorithm using multiple ontologies (ICD-10, Read-2, BNF)

Note: CID, corroborating information for dementia diagnosis; dx, diagnostic. The phenotype algorithm uses

multiple ontologies: the International Classification of Disease version 10 (ICD-10), version 2 of the Read

classification system and the British National Formulary (BNF). CID includes multiple diagnostic codes

recorded on different dates in the same data source, recorded diagnostic codes in 2 or 3 different data sources

(e.g. primary care and hospital admissions), record of dementia symptoms (falls, confusion, cognitive deficiency

or nursing home admission), record of dementia monitoring or referral to a dementia specialist (geriatrics, care

of the elderly, psychiatry), or more than one prescription of dementia medication (rivastigmine, galantamine,

donepezil, memantine) during the study period. The group of people with ‘possible dementia’ included those

without diagnostic codes for dementia and with recorded unspecific codes listed in Table S1.

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Figure B. Study flowchart

*Some people had more than one subtype of dementia

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No. of CALIBER people eligible

(N=2,524,144)

No. of people with dementia (N=47,386)*

Alzheimer’s: 12,633 Vascular: 9,540 Rare: 1,539 Unclassified: 25,202

No. of people with corroborating diagnosis evidence (N=34,925)*

Alzheimer’s: 10,296 (82%) Vascular: 6,735 (71%) Rare: 1,065 (69%) Unclassified: 15,519 (62%)

No. of matched cases

(N=47,151)

No. of matched controls

(N=324,627)

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