Improving the identification of people with dementia in primary care: evaluation of the impact of primary care dementia coding guidance on identified prevalence

New cases of dementia are rising in elderly populations in Wales, UK

Dementia is one of the most common diseases in elderly populations, and older populations are one of the fastest growing groups globally. Consequently, the number of people developing and living with dementia is likely to grow. Using longitudinal medical records from Wales, UK between 1999 and 2018, diagnoses of overall dementia and common subtypes were combined with demographic data to assess numbers of new and existing cases per year. Data extraction resulted in 161,186 diagnoses from 116,645 individuals. Mean age at diagnosis of dementia increased over this period, resulting in fewer younger people with the disease. New cases of dementia have risen, as has the number of people living with dementia. Individuals with dementia are also living longer, even accounting for their older age. This may present a challenge for healthcare systems as the number of elderly people living with dementia is expected to continue to grow.

Understanding how primary care practitioners can be supported to recognise, screen and initially diagnose oropharyngeal dysphagia: protocol for a behavioural science realist review

INTRODUCTION

Oropharyngeal dysphagia (OD) affects around 15% of older people; however, it is often unrecognised and underdiagnosed until patients are hospitalised. Screening is an important process which aims to facilitate proactive assessment, diagnosis and management of health conditions. Healthcare systems do not routinely screen for OD in older people, and healthcare professionals (HCPs) are largely unaware of the need to screen. This realist review aims to identify relevant literature and develop programme theories to understand what works, for whom, under what circumstances and how, to facilitate primary care HCPs to recognise, screen and initially diagnose OD.

METHODS AND ANALYSIS

We will follow five steps for undertaking a realist review: (1) clarify the scope, (2) literature search, (3) appraise and extract data, (4) evidence synthesis and (5) evaluation. Initial programme theories (IPTs) will be constructed after the preliminary literature search, informed by the Theoretical Domains Framework and with input from a stakeholder group. We will search Medline, Google Scholar, PubMed, EMBASE, CINAHL, AMED, Scopus and PsycINFO databases. We will obtain additional evidence through grey literature, snowball sampling, lateral searching and consulting the stakeholder group. Literature will be screened, evaluated and synthesised in Covidence. Evidence will be assessed for quality by evaluating its relevance and rigour. Data will be extracted and synthesised according to their relation to IPTs. We will follow the Realist and Meta-narrative Evidence Syntheses: Evolving Standards quality and publication standards to report study results.

ETHICS AND DISSEMINATION

Formal ethical approval is not required for this review. We will disseminate this research through publication in a peer-reviewed journal, written pieces targeted to diverse groups of HCPs on selected online platforms and public engagement events.

PROSPERO REGISTRATION NUMBER

CRD42022320327.

Inflammatory Diseases, Inflammatory Biomarkers, and Alzheimer Disease: An Observational Analysis and Mendelian Randomization

BACKGROUND AND OBJECTIVES

Whether chronic autoimmune inflammatory diseases causally affect the risk of Alzheimer disease (AD) is controversial. We characterized the relationship between inflammatory diseases and risk of AD and explored the role of circulating inflammatory biomarkers in the relationships between inflammatory diseases and AD.

METHODS

We performed observational analyses for chronic autoimmune inflammatory diseases and risk of AD using data from 2,047,513 participants identified in the UK Clinical Practice Research Datalink (CPRD). Using data of a total of more than 1,100,000 individuals from 15 large-scale genome-wide association study data sets, we performed 2-sample Mendelian randomizations (MRs) to investigate the relationships between chronic autoimmune inflammatory diseases, circulating inflammatory biomarker levels, and risk of AD.

RESULTS

Cox regression models using CPRD data showed that the overall incidence of AD was higher among patients with inflammatory bowel disease (hazard ratio [HR] 1.17; 95% CI 1.15-1.19; p = 2.1 × 10-4), other inflammatory polyarthropathies and systematic connective tissue disorders (HR 1.13; 95% CI 1.12-1.14; p = 8.6 × 10-5), psoriasis (HR 1.13; 95% CI 1.10-1.16; p = 2.6 × 10-4), rheumatoid arthritis (HR 1.08; 95% CI 1.06-1.11; p = 4.0 × 10-4), and multiple sclerosis (HR 1.06; 95% CI 1.04-1.07; p = 2.8 × 10-4) compared with the age (±5 years) and sex-matched comparison groups free from all inflammatory diseases under investigation. Bidirectional MR analysis identified relationships between chronic autoimmune inflammatory diseases and circulating inflammatory biomarkers. Particularly, circulating monokine induced by gamma interferon (MIG) level was suggestively associated with a higher risk of AD (odds ratio from inverse variance weighted [ORIVW] 1.23; 95% CI 1.06-1.42; p IVW = 0.007) and lower risk of Crohn disease (ORIVW 0.73; 95% CI -0.62 to 0.86; p IVW = 1.3 × 10-4). Colocalization supported a common causal single nucleotide polymorphism for MIG and Crohn disease (posterior probability = 0.74), but not AD (posterior probability = 0.03). Using a 2-sample MR approach, genetically predicted risks of inflammatory diseases were not associated with higher AD risk.

DISCUSSION

Our data suggest that the association between inflammatory diseases and risk of AD is unlikely to be causal and may be a result of confounding. In support, although inflammatory biomarkers showed evidence for causal associations with inflammatory diseases, evidence was weak that they affected both inflammatory disease and AD.

Analyses and identification of ICD codes for dementias in the research based on the NHIRD: a scoping review protocol

INTRODUCTION

Studies based on health claims data (HCD) have been increasingly adopted in medical research for their strengths in large sample size and abundant information, and the Taiwan National Health Insurance Research Database (NHIRD) has been widely used in medical research across disciplines, including dementia. How the diagnostic codes are applied to define the diseases/conditions of interest is pivotal in HCD-related research, but the consensus on the issue that diagnostic codes most appropriately define dementias in the NHIRD is lacking. The objectives of this scoping review are (1) to investigate the relevant characteristics in the published reports targeting dementias based on the NHIRD, and (2) to address the diversity by a case study.

METHODS AND ANALYSIS

This scoping review protocol follows the methodological framework of the Joanna Briggs Institute Reviewer's Manual and the guidance of the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for scoping reviews. The review will be performed between 1 March and 31 December 2022 in five stages, including identifying the relevant studies, developing search strategies, individually screening and selecting evidence, collecting and extracting data, and summarising and reporting the results. The electronic databases of MEDLINE, EMBASE, CENTRAL, CINAHL, and PsycINFO, Airiti Library Academic Database, the National Health Insurance Administration's repository, and Taiwan Government Research Bulletin will be searched. We will perform narrative syntheses of the results to address research questions and will analyse the prevalence across the included individual studies as a case study.

ETHICS AND DISSEMINATION

Our scoping review is a review of the published reports and ethical approval is not required. The results will provide a panorama of the dementia studies based on the NHIRD. We will disseminate our findings through peer-reviewed journals and conferences, and share with stakeholders by distributing the summaries in social media and emails.

Clinical judgement by primary care physicians for the diagnosis of all-cause dementia or cognitive impairment in symptomatic people

BACKGROUND

In primary care, general practitioners (GPs) unavoidably reach a clinical judgement about a patient as part of their encounter with patients, and so clinical judgement can be an important part of the diagnostic evaluation. Typically clinical decision making about what to do next for a patient incorporates clinical judgement about the diagnosis with severity of symptoms and patient factors, such as their ideas and expectations for treatment. When evaluating patients for dementia, many GPs report using their own judgement to evaluate cognition, using information that is immediately available at the point of care, to decide whether someone has or does not have dementia, rather than more formal tests.

OBJECTIVES

To determine the diagnostic accuracy of GPs' clinical judgement for diagnosing cognitive impairment and dementia in symptomatic people presenting to primary care. To investigate the heterogeneity of test accuracy in the included studies.

SEARCH METHODS

We searched MEDLINE (Ovid SP), Embase (Ovid SP), PsycINFO (Ovid SP), Web of Science Core Collection (ISI Web of Science), and LILACs (BIREME) on 16 September 2021.

SELECTION CRITERIA

We selected cross-sectional and cohort studies from primary care where clinical judgement was determined by a GP either prospectively (after consulting with a patient who has presented to a specific encounter with the doctor) or retrospectively (based on knowledge of the patient and review of the medical notes, but not relating to a specific encounter with the patient). The target conditions were dementia and cognitive impairment (mild cognitive impairment and dementia) and we included studies with any appropriate reference standard such as the Diagnostic and Statistical Manual of Mental Disorders (DSM), International Classification of Diseases (ICD), aetiological definitions, or expert clinical diagnosis.

DATA COLLECTION AND ANALYSIS

Two review authors screened titles and abstracts for relevant articles and extracted data separately with differences resolved by consensus discussion. We used QUADAS-2 to evaluate the risk of bias and concerns about applicability in each study using anchoring statements. We performed meta-analysis using the bivariate method.

MAIN RESULTS

We identified 18,202 potentially relevant articles, of which 12,427 remained after de-duplication. We assessed 57 full-text articles and extracted data on 11 studies (17 papers), of which 10 studies had quantitative data. We included eight studies in the meta-analysis for the target condition dementia and four studies for the target condition cognitive impairment. Most studies were at low risk of bias as assessed with the QUADAS-2 tool, except for the flow and timing domain where four studies were at high risk of bias, and the reference standard domain where two studies were at high risk of bias. Most studies had low concern about applicability to the review question in all QUADAS-2 domains. Average age ranged from 73 years to 83 years (weighted average 77 years). The percentage of female participants in studies ranged from 47% to 100%. The percentage of people with a final diagnosis of dementia was between 2% and 56% across studies (a weighted average of 21%). For the target condition dementia, in individual studies sensitivity ranged from 34% to 91% and specificity ranged from 58% to 99%. In the meta-analysis for dementia as the target condition, in eight studies in which a total of 826 of 2790 participants had dementia, the summary diagnostic accuracy of clinical judgement of general practitioners was sensitivity 58% (95% confidence interval (CI) 43% to 72%), specificity 89% (95% CI 79% to 95%), positive likelihood ratio 5.3 (95% CI 2.4 to 8.2), and negative likelihood ratio 0.47 (95% CI 0.33 to 0.61). For the target condition cognitive impairment, in individual studies sensitivity ranged from 58% to 97% and specificity ranged from 40% to 88%. The summary diagnostic accuracy of clinical judgement of general practitioners in four studies in which a total of 594 of 1497 participants had cognitive impairment was sensitivity 84% (95% CI 60% to 95%), specificity 73% (95% CI 50% to 88%), positive likelihood ratio 3.1 (95% CI 1.4 to 4.7), and negative likelihood ratio 0.23 (95% CI 0.06 to 0.40). It was impossible to draw firm conclusions in the analysis of heterogeneity because there were small numbers of studies. For specificity we found the data were compatible with studies that used ICD-10, or applied retrospective judgement, had higher reported specificity compared to studies with DSM definitions or using prospective judgement. In contrast for sensitivity, we found studies that used a prospective index test may have had higher sensitivity than studies that used a retrospective index test.

AUTHORS' CONCLUSIONS

Clinical judgement of GPs is more specific than sensitive for the diagnosis of dementia. It would be necessary to use additional tests to confirm the diagnosis for either target condition, or to confirm the absence of the target conditions, but clinical judgement may inform the choice of further testing. Many people who a GP judges as having dementia will have the condition. People with false negative diagnoses are likely to have less severe disease and some could be identified by using more formal testing in people who GPs judge as not having dementia. Some false positives may require similar practical support to those with dementia, but some - such as some people with depression - may suffer delayed intervention for an alternative treatable pathology.

Evaluation of routinely collected records for dementia outcomes in UK: a prospective cohort study

OBJECTIVES

To evaluate the characteristics of individuals recorded as having a dementia diagnosis in different routinely collected records and to examine the extent of overlap of dementia coding across data sources. Also, to present comparisons of secondary and primary care records providing value for researchers using routinely collected records for dementia outcome capture.

STUDY DESIGN

A prospective cohort study.

SETTING AND PARTICIPANTS

A cohort of 25 639 men and women in Norfolk, aged 40-79 years at recruitment (1993-1997) followed until 2018 linked to routinely collected to identify dementia cases. Data sources include mortality from death certification and National Health Service (NHS) hospital or secondary care records. Primary care records for a subset of the cohort were also reviewed.

PRIMARY OUTCOME MEASURE

Diagnosis of dementia (any-cause).

RESULTS

Over 2000 participants (n=2635 individuals) were found to have a dementia diagnosis recorded in one or more of the data sources examined. Limited concordance was observed across the secondary care data sources. We also observed discrepancies with primary care records for the subset and report on potential linkage-related selection bias.

CONCLUSIONS

Use of different types of record linkage from varying parts of the UK's health system reveals differences in recorded dementia diagnosis, indicating that dementia can be identified to varying extents in different parts of the NHS system. However, there is considerable variation, and limited overlap in those identified. We present potential selection biases that might occur depending on whether cause of death, or primary and secondary care data sources are used. With the expansion of using routinely collected health data, researchers must be aware of these potential biases and inaccuracies, reporting carefully on the likely extent of limitations and challenges of the data sources they use.

Clinical judgment of GPs for the diagnosis of dementia: a diagnostic test accuracy study

BACKGROUND

GPs often report using clinical judgment to diagnose dementia.

AIM

To investigate the accuracy of GPs' clinical judgment for the diagnosis of dementia.

DESIGN & SETTING

Diagnostic test accuracy study, recruiting from 21 practices around Bristol, UK.

METHOD

The clinical judgment of the treating GP (index test) was based on the information immediately available at their initial consultation with a person aged ≥70 years who had cognitive symptoms. The reference standard was an assessment by a specialist clinician, based on a standardised clinical examination and made according to the 10th revision of the International Classification of Diseases (ICD-10) criteria for dementia.

RESULTS

A total of 240 people were recruited, with a median age of 80 years (interquartile range [IQR] 75-84 years), of whom 126 (53%) were men and 132 (55%) had dementia. The median duration of symptoms was 24 months (IQR 12-36 months) and the median Addenbrooke's Cognitive Examination III (ACE-III) score was 75 (IQR 65-87). GP clinical judgment had sensitivity 56% (95% confidence interval [CI] = 47% to 65%) and specificity 89% (95% CI = 81% to 94%). Positive likelihood ratio was higher in people aged 70-79 years (6.5, 95% CI = 2.9 to 15) compared with people aged ≥80 years (3.6, 95% CI = 1.7 to 7.6), and in women (10.4, 95% CI = 3.4 to 31.7) compared with men (3.2, 95% CI = 1.7 to 6.2), whereas the negative likelihood ratio was similar in all groups.

CONCLUSION

A GP clinical judgment of dementia is specific, but confirmatory testing is needed to exclude dementia in symptomatic people whom GPs judge as not having dementia.

The rising tide of dementia deaths: triangulation of data from three routine data sources using the Clinical Practice Research Datalink

BACKGROUND

Dementia is currently the leading certified underlying cause of death in England. We assess how dementia recording on Office for National Statistics death certificates (ONS) corresponded to recording in general practice records (GP) and Hospital Episode Statistics (HES).

METHODS

Retrospective study of deaths (2001-15) in 153 English General Practices contributing to the Clinical Practice Research Datalink, with linked ONS and HES records.

RESULTS

Of 207,068 total deaths from any cause, 19,627 mentioned dementia on the death certificate with 10,253 as underlying cause; steady increases occurred from 2001 to 2015 (any mention 5.3 to 15.4 %, underlying cause 2.7 to 10 %). Including all data sources, recording of any dementia increased from 13.2 to 28.6 %. In 2015, only 53.8 % of people dying with dementia had dementia recorded on their death certificates. Among deaths mentioning dementia on the death certificate, the recording of a prior diagnosis of dementia in GP and HES rose markedly over the same period. In 2001, only 76.3 % had a prior diagnosis in GP and/or HES records; by 2015 this had risen to 95.7 %. However, over the same period the percentage of all deaths with dementia recorded in GP or HES but not mentioned on the death certificate rose from 7.9 to 13.3 %.

CONCLUSIONS

Dementia recording in all data sources increased between 2001 and 2015. By 2015 the vast majority of deaths mentioning dementia had supporting evidence in primary and/or secondary care. However, death certificates were still providing an inadequate picture of the number of people dying with dementia.

Automated detection of patients with dementia whose symptoms have been identified in primary care but have no formal diagnosis: a retrospective case-control study using electronic primary care records

OBJECTIVES

UK statistics suggest only two-thirds of patients with dementia get a diagnosis recorded in primary care. General practitioners (GPs) report barriers to formally diagnosing dementia, so some patients may be known by GPs to have dementia but may be missing a diagnosis in their patient record. We aimed to produce a method to identify these 'known but unlabelled' patients with dementia using data from primary care patient records.

DESIGN

Retrospective case-control study using routinely collected primary care patient records from Clinical Practice Research Datalink.

SETTING

UK general practice.

PARTICIPANTS

English patients aged >65 years, with a coded diagnosis of dementia recorded in 2000-2012 (cases), matched 1:1 with patients with no diagnosis code for dementia (controls).

INTERVENTIONS

Eight coded and nine keyword concepts indicating symptoms, screening tests, referrals and care for dementia recorded in the 5 years before diagnosis. We trialled machine learning classifiers to discriminate between cases and controls (logistic regression, naïve Bayes, random forest).

PRIMARY AND SECONDARY OUTCOMES

The outcome variable was dementia diagnosis code; the accuracy of classifiers was assessed using area under the receiver operating characteristic curve (AUC); the order of features contributing to discrimination was examined.

RESULTS

93 426 patients were included; the median age was 83 years (64.8% women). Three classifiers achieved high discrimination and performed very similarly. AUCs were 0.87-0.90 with coded variables, rising to 0.90-0.94 with keywords added. Feature prioritisation was different for each classifier; commonly prioritised features were Alzheimer's prescription, dementia annual review, memory loss and dementia keywords.

CONCLUSIONS

It is possible to detect patients with dementia who are known to GPs but unlabelled with a diagnostic code, with a high degree of accuracy in electronic primary care record data. Using keywords from clinic notes and letters improves accuracy compared with coded data alone. This approach could improve identification of dementia cases for record-keeping, service planning and delivery of good quality care.

An intervention to improve outcomes of falls in dementia: the DIFRID mixed-methods feasibility study

BACKGROUND

Fall-related injuries are a significant cause of morbidity and mortality in people with dementia. There is presently little evidence to guide the management of such injuries, and yet there are potentially substantial benefits to be gained if the outcomes of these injuries could be improved. This study aimed to design an appropriate new health-care intervention for people with dementia following a fall and to assess the feasibility of its delivery in the UK NHS.

OBJECTIVES

To determine whether or not it is possible to design an intervention to improve outcomes of falls in dementia, to investigate the feasibility and acceptability of the DIFRID (Developing an Intervention for Fall related Injuries in Dementia) intervention and to investigate the feasibility of a future randomised controlled trial and the data collection tools needed to evaluate both the effectiveness and the cost-effectiveness of the DIFRID intervention.

DESIGN

This was a mixed-methods feasibility study. A systematic review (using Cochrane methodology) and realist review [using Realist And Meta-narrative Evidence Syntheses: Evolving Standards (RAMESES) methodology] explored the existing evidence base and developed programme theories. Searches were carried out in November 2015 (updated in January 2018) for effectiveness studies and in August 2016 for economic studies. A prospective observational study identified service use via participant diary completion. Qualitative methods (semistructured interviews, focus groups and observation) were used to explore current practice, stakeholder perspectives of the health and social care needs of people with dementia following a fall, ideas for intervention and barriers to and facilitators of change. Each of the resulting data sets informed intervention development via Delphi consensus methods. Finally, a single-arm feasibility study with embedded process evaluation was conducted.

SETTING

This study was set in the community.

PARTICIPANTS

The participants were (1) people with dementia presenting with falls necessitating health-care attention in each setting (primary care, the community and secondary care) at three sites and their carers, (2) professionals delivering the intervention, who were responsible for training and supervision and who were members of the intervention team, (3) professionals responsible for approaching and recruiting participants and (4) carers of participants with dementia.

INTERVENTIONS

This was a complex multidisciplinary therapy intervention. Physiotherapists, occupational therapists and support workers delivered up to 22 sessions of tailored activities in the home or local area of the person with dementia over a period of 12 weeks.

MAIN OUTCOME MEASURES

(1) Assessment of feasibility of study procedures; (2) assessment of the acceptability, feasibility and fidelity of intervention components; and (3) assessment of the suitability and acceptability of outcome measures for people with dementia and their carers (number of falls, quality of life, fear of falling, activities of daily living, goal-setting, health-care utilisation and carer burden).

RESULTS

A multidisciplinary intervention delivered in the homes of people with dementia was designed based on qualitative work, realist review and recommendations of the consensus panel. The intervention was delivered to 11 people with dementia. The study suggested that the intervention is both feasible and acceptable to stakeholders. A number of modifications were recommended to address some of the issues arising during feasibility testing. The measurement of outcome measures was successful.

CONCLUSIONS

The study has highlighted the feasibility of delivering a creative, tailored, individual approach to intervention for people with dementia following a fall. Although the intervention required greater investment of time than usual practice, many staff valued the opportunity to work more closely with people with dementia and their carers. We conclude that further research is now needed to refine this intervention in the context of a pilot randomised controlled trial.

TRIAL REGISTRATION

Current Controlled Trials ISRCTN41760734 and PROSPERO CRD42016029565.

FUNDING

This project was funded by the National Institute for Health Research (NIHR) Health Technology Assessment programme and will be published in full in Health Technology Assessment; Vol. 23, No. 59. See the NIHR Journals Library website for further project information.

Could dementia be detected from UK primary care patients' records by simple automated methods earlier than by the treating physician? A retrospective case-control study

Background: Timely diagnosis of dementia is a policy priority in the United Kingdom (UK). Primary care physicians receive incentives to diagnose dementia; however, 33% of patients are still not receiving a diagnosis. We explored automating early detection of dementia using data from patients' electronic health records (EHRs). We investigated: a) how early a machine-learning model could accurately identify dementia before the physician; b) if models could be tuned for dementia subtype; and c) what the best clinical features were for achieving detection. Methods: Using EHRs from Clinical Practice Research Datalink in a case-control design, we selected patients aged >65y with a diagnosis of dementia recorded 2000-2012 (cases) and matched them 1:1 to controls; we also identified subsets of Alzheimer's and vascular dementia patients. Using 77 coded concepts recorded in the 5 years before diagnosis, we trained random forest classifiers, and evaluated models using Area Under the Receiver Operating Characteristic Curve (AUC). We examined models by year prior to diagnosis, subtype, and the most important features contributing to classification. Results: 95,202 patients (median age 83y; 64.8% female) were included (50% dementia cases). Classification of dementia cases and controls was poor 2-5 years prior to physician-recorded diagnosis (AUC range 0.55-0.65) but good in the year before (AUC: 0.84). Features indicating increasing cognitive and physical frailty dominated models 2-5 years before diagnosis; in the final year, initiation of the dementia diagnostic pathway (symptoms, screening and referral) explained the sudden increase in accuracy. No substantial differences were seen between all-cause dementia and subtypes. Conclusions: Automated detection of dementia earlier than the treating physician may be problematic, if using only primary care data. Future work should investigate more complex modelling, benefits of linking multiple sources of healthcare data and monitoring devices, or contextualising the algorithm to those cases that the GP would need to investigate.

Identifying undetected dementia in UK primary care patients: a retrospective case-control study comparing machine-learning and standard epidemiological approaches

BACKGROUND

Identifying dementia early in time, using real world data, is a public health challenge. As only two-thirds of people with dementia now ultimately receive a formal diagnosis in United Kingdom health systems and many receive it late in the disease process, there is ample room for improvement. The policy of the UK government and National Health Service (NHS) is to increase rates of timely dementia diagnosis. We used data from general practice (GP) patient records to create a machine-learning model to identify patients who have or who are developing dementia, but are currently undetected as having the condition by the GP.

METHODS

We used electronic patient records from Clinical Practice Research Datalink (CPRD). Using a case-control design, we selected patients aged >65y with a diagnosis of dementia (cases) and matched them 1:1 by sex and age to patients with no evidence of dementia (controls). We developed a list of 70 clinical entities related to the onset of dementia and recorded in the 5 years before diagnosis. After creating binary features, we trialled machine learning classifiers to discriminate between cases and controls (logistic regression, naïve Bayes, support vector machines, random forest and neural networks). We examined the most important features contributing to discrimination.

RESULTS

The final analysis included data on 93,120 patients, with a median age of 82.6 years; 64.8% were female. The naïve Bayes model performed least well. The logistic regression, support vector machine, neural network and random forest performed very similarly with an AUROC of 0.74. The top features retained in the logistic regression model were disorientation and wandering, behaviour change, schizophrenia, self-neglect, and difficulty managing.

CONCLUSIONS

Our model could aid GPs or health service planners with the early detection of dementia. Future work could improve the model by exploring the longitudinal nature of patient data and modelling decline in function over time.

The Cretan Aging Cohort: Cohort Description and Burden of Dementia and Mild Cognitive Impairment

Our aim was to explore the burden of dementia in the Cretan Aging Cohort, comprised of 3140 persons aged ≥60 years (56.8% women, 5.8 ± 3.3 years formal education, 86.2% living in rural areas) who attended selected primary health-care facilities on the island of Crete, Greece. In the first study phase, a formal diagnosis of dementia had been reached in 4.0% of the participants. However, when selected 505 participants underwent thorough neuropsychiatric evaluation in the second phase of this study (344 with Mini-Mental State Examination [MMSE] <24 and 161 with MMSE ≥24), and results were extrapolated to the entire cohort, the prevalence of dementia and mild cognitive impairment was estimated at 10.8% (9.7%-11.9%) and 32.4% (30.8%-34.0%), respectively. Using both the field diagnostic data and the extrapolated data, the highest dementia prevalence (27.2%) was found in the 80- to 84-year-old group, who also showed the lowest educational level, apparently due to lack of schooling during World War II.

Are noise and air pollution related to the incidence of dementia? A cohort study in London, England

OBJECTIVE

To investigate whether the incidence of dementia is related to residential levels of air and noise pollution in London.

DESIGN

Retrospective cohort study using primary care data.

SETTING

75 Greater London practices.

PARTICIPANTS

130 978 adults aged 50-79 years registered with their general practices on 1 January 2005, with no recorded history of dementia or care home residence.

PRIMARY AND SECONDARY OUTCOME MEASURES

A first recorded diagnosis of dementia and, where specified, subgroups of Alzheimer's disease and vascular dementia during 2005-2013. The average annual concentrations during 2004 of nitrogen dioxide (NO₂), particulate matter with a median aerodynamic diameter ≤2.5 µm (PM_2.5) and ozone (O₃) were estimated at 20×20 m resolution from dispersion models. Traffic intensity, distance from major road and night-time noise levels (L_night) were estimated at the postcode level. All exposure measures were linked anonymously to clinical data via residential postcode. HRs from Cox models were adjusted for age, sex, ethnicity, smoking and body mass index, with further adjustments explored for area deprivation and comorbidity.

RESULTS

2181 subjects (1.7%) received an incident diagnosis of dementia (39% mentioning Alzheimer's disease, 29% vascular dementia). There was a positive exposure response relationship between dementia and all measures of air pollution except O₃, which was not readily explained by further adjustment. Adults living in areas with the highest fifth of NO₂ concentration (>41.5 µg/m³) versus the lowest fifth (<31.9 µg/m³) were at a higher risk of dementia (HR=1.40, 95% CI 1.12 to 1.74). Increases in dementia risk were also observed with PM_2.5, PM_2.5 specifically from primary traffic sources only and L_night, but only NO₂ and PM_2.5 remained statistically significant in multipollutant models. Associations were more consistent for Alzheimer's disease than vascular dementia.

CONCLUSIONS

We have found evidence of a positive association between residential levels of air pollution across London and being diagnosed with dementia, which is unexplained by known confounding factors.

Trends in diagnosis and treatment for people with dementia in the UK from 2005 to 2015: a longitudinal retrospective cohort study

BACKGROUND

The objectives of this study were to describe changes in the proportion of people diagnosed with dementia and the pharmacological treatments prescribed to them over a 10 year period from 2005 to 2015 at a time of UK policy strategies and prioritisation of dementia. We aimed to explore the potential impact of policy on dementia care.

METHODS

In this longitudinal retrospective cohort study, we included all patients registered at a Clinical Practice Research Datalink (CPRD) practice between July 1, 2005, and June 30, 2015, with a diagnosis of dementia defined using Read codes. The main outcomes were the number and proportion of acceptable patients, who met the CPRD threshold for data quality, in a GP practice defined by the CPRD as contributing up-to-standard data with a diagnosis of dementia and the number and proportion of these with a prescription for an antidementia or antipsychotic medication. We examined the prevalence of dementia diagnosis and prescribing by calendar quarter, and stratified by age, sex, and UK country (England, Scotland, Wales, or Northern Ireland). We investigated the use of antidementia drugs, alone and in combination, antipsychotics, antidepressants, anxiolytics, and hypnotics. The trend in the proportion of patients with a diagnosis of dementia, before and after the introduction of the UK National Dementia Strategy, was estimated using an interrupted time-series analysis.

FINDINGS

8 966 224 patients were identified in the CPRD whose most recent registration period overlapped the study period. Of these, 128 249 (1·4%) had a diagnosis of dementia before the end of the study period. The proportion of people diagnosed with dementia in the UK doubled from 0·42% (19 635 of 4 640 290 participants) in 2005 to 0·82% (25 925 of 3 159 754 participants) in 2015 (χ² test for trend, p<0·0001), and the proportion of those who received antidementia medication increased from 15·0% (2942 of 19 635) to 36·3% (9406 of 25 925). The interrupted time-series analysis showed a significant acceleration in the rate of diagnosis of dementia after the introduction of the UK National Dementia Strategy (p<0·0001). There was a large reduction in antipsychotic drug prescription in dementia from 22·1% (4347 of 19 635) in 2005 to 11·4% (2943 of 25 925) by 2015.

INTERPRETATION

Over the 10 years studied, there is evidence of a sustained positive change in diagnosis rates of dementia and in the quality of drug treatment provided to those diagnosed. The prescription of antidementia drugs more than doubled and the prescription of potentially hazardous antipsychotics halved after the introduction of national dementia strategies. These data support the formulation and delivery of national policy to improve the quality of care for people with dementia.

FUNDING

None.

Diagnosing dementia: Ethnography, interactional ethics and everyday moral reasoning

This article highlights the contribution of ethnography and qualitative sociology to the ethical challenges that frame the diagnosis of dementia. To illustrate this contribution, the paper draws on an ethnographic study of UK memory clinics carried out between 2012 and 2014. The ethnographic data, set alongside other studies and sociological theory, contest the promotion of a traditional view of autonomy; the limiting of the point of ethical interest to a distinct moment of diagnosis disclosure; and the failure to recognise risk and uncertainty in the building of clinical 'facts' and their communication. In addressing these specific concerns, this article contributes to the wider debate over the relationship between sociology and bioethics (medical ethics). At the heart of these debates lies more fundamental questions: how can we best understand and shape moral decision-making and ethics that guide behaviour in medical practice, and what should be the guiding ideas, concepts and methods to inform ethics in the clinic? Using the case of dementia diagnosis, this article illustrates the benefits of an ethnographic approach, not just for understanding this ethical problem but also for exploring if and how a more empirically informed ethics can help shape healthcare practices for the better.

Comparison of dementia recorded in routinely collected hospital admission data in England with dementia recorded in primary care

BACKGROUND

Electronic linkage of UK cohorts to routinely collected National Health Service (NHS) records provides virtually complete follow-up for cause-specific hospital admissions and deaths. The reliability of dementia diagnoses recorded in NHS hospital data is not well documented.

METHODS

For a sample of Million Women Study participants in England we compared dementia recorded in routinely collected NHS hospital data (Hospital Episode Statistics: HES) with dementia recorded in two separate sources of primary care information: a primary care database [Clinical Practice Research Datalink (CPRD), n = 340] and a survey of study participants' General Practitioners (GPs, n = 244).

RESULTS

Dementia recorded in HES fully agreed both with CPRD and with GP survey data for 85% of women; it did not agree for 1 and 4%, respectively. Agreement was uncertain for the remaining 14 and 11%, respectively; and among those classified as having uncertain agreement in CPRD, non-specific terms compatible with dementia, such as 'memory loss', were recorded in the CPRD database for 79% of the women. Agreement was significantly better (p < 0.05 for all comparisons) for women with HES diagnoses for Alzheimer's disease (95 and 94% agreement with any dementia for CPRD and GP survey, respectively) and for vascular dementia (88 and 88%, respectively) than for women with a record only of dementia not otherwise specified (70 and 72%, respectively). Dementia in the same woman was first mentioned an average 1.6 (SD 2.6) years earlier in primary care (CPRD) than in hospital (HES) data. Age-specific rates for dementia based on the hospital admission data were lower than the rates based on the primary care data, but were similar if the delay in recording in HES was taken into account.

CONCLUSIONS

Dementia recorded in routinely collected NHS hospital admission data for women in England agrees well with primary care records of dementia assessed separately from two different sources, and is sufficiently reliable for epidemiological research.

Blood Pressure and Risk of Vascular Dementia: Evidence From a Primary Care Registry and a Cohort Study of Transient Ischemic Attack and Stroke

BACKGROUND AND PURPOSE

Vascular dementia is the second most common form of dementia but reliable evidence on age-specific associations between blood pressure (BP) and risk of vascular dementia is limited and some studies have reported negative associations at older ages.

METHODS

In a cohort of 4.28 million individuals, free of known vascular disease and dementia and identified from linked electronic primary care health records in the United Kingdom (Clinical Practice Research Datalink), we related BP to time to physician-diagnosed vascular dementia. We further determined associations between BP and dementia in a prospective population-based cohort of incident transient ischemic attack and stroke (Oxford Vascular Study).

RESULTS

For a median follow-up of 7.0 years, 11 114 initial presentations of vascular dementia were observed in the primary care cohort after exclusion of the first 4 years of follow-up. The association between usual systolic BP and risk of vascular dementia decreased with age (hazard ratio per 20 mm Hg higher systolic BP, 1.62; 95% confidence interval, 1.13-2.35 at 30-50 years; 1.26, 1.18-1.35 at 51-70 years; 0.97, 0.92-1.03 at 71-90 years; P trend=0.006). Usual systolic BP remained predictive of vascular dementia after accounting for effect mediation by stroke and transient ischemic attack. In the population-based cohort, prior systolic BP was predictive of 5-year risk of dementia with no evidence of negative association at older ages.

CONCLUSIONS

BP is positively associated with risk of vascular dementia, irrespective of preceding transient ischemic attack or stroke. Previous reports of inverse associations in old age could not be confirmed.

Targeted case finding for dementia in primary care: Surrey Downs dementia diagnosis project

Currently less than half of the estimated number of people with dementia in England receive a formal diagnosis of dementia or have contact with specialist dementia services. Case finding focused on high risk groups may be an effective way to identify the undiagnosed. This joint Surrey Downs Clinical Commissioning Group and Surrey and Borders NHS Foundation Trust quality improvement project aimed to increase the rate of dementia diagnosis across Surrey Downs using specialist link nurses (SLNs).

Thirty three GP surgeries covering the entire Surrey Downs area took part in the project. Individuals at high risk of developing dementia were identified from GP electronic disease registers, and were offered screening at their GP practices by SLNs, using a combination of mini cognitive test (Mini-Cog) and functional assessment questionnaire (FAQ). Suitable individuals who screened positive were seen by their GP and where appropriate referred to secondary care services for further evaluation.

Based on the presence of risk factors, 6657 (11.9%) people were identified from a total population of 55 845 over 65s, and 1980 (29.7%) completed the screening assessment. Three hundred and fifty eight (18.1%) individuals screened positive and were referred to their GP, who referred 205 (57.2%) of them to the memory services for further assessment. Of those referred, 164 (80%) had a comprehensive specialist assessment. Forty one (20%) declined further assessment, and their GPs were informed.

The mean age of the cohort who completed the comprehensive assessment was 82.3 years (SD=4.26), and were predominantly white and male. Fifty four (32.9%) had mild cognitive disorder (MCD), and 101 (61.6%) patients were diagnosed with dementia. The most common dementia was mixed type (43; 42.6%), followed by Alzheimer's dementia (32; 31.7%). The most common risk factor among patients with cognitive impairment (MCD or dementia) was hypertension (69; 44.5 %), followed by ischemic heart disease (64, 41.3%).

Nurse led case finding for cognitive impairment in a high risk population identifies people with dementia who are not yet formally diagnosed. The combined use of brief instruments to assess cognitive functioning and functional capabilities is helpful in identifying individuals with possible dementia.