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Burton JK, Fearon P, Noel-Storr AH, McShane R, Stott DJ, Quinn TJ. Informant Questionnaire on Cognitive Decline in the Elderly (IQCODE) for the detection of dementia within a secondary care setting. Cochrane Database Syst Rev 2021; 7:CD010772. [PMID: 34278561 PMCID: PMC8406705 DOI: 10.1002/14651858.cd010772.pub3] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/07/2022]
Abstract
BACKGROUND The diagnosis of dementia relies on the presence of new-onset cognitive impairment affecting an individual's functioning and activities of daily living. The Informant Questionnaire on Cognitive Decline in the Elderly (IQCODE) is a questionnaire instrument, completed by a suitable 'informant' who knows the patient well, designed to assess change in functional performance secondary to cognitive change; it is used as a tool for identifying those who may have dementia. In secondary care there are two specific instances where patients may be assessed for the presence of dementia. These are in the general acute hospital setting, where opportunistic screening may be undertaken, or in specialist memory services where individuals have been referred due to perceived cognitive problems. To ensure an instrument is suitable for diagnostic use in these settings, its test accuracy must be established. OBJECTIVES To determine the accuracy of the informant-based questionnaire IQCODE for detection of dementia in a secondary care setting. SEARCH METHODS We searched the following sources on the 28th of January 2013: ALOIS (Cochrane Dementia and Cognitive Improvement Group), MEDLINE (Ovid SP), EMBASE (Ovid SP), PsycINFO (Ovid SP), BIOSIS Previews (Thomson Reuters Web of Science), Web of Science Core Collection (includes Conference Proceedings Citation Index) (Thomson Reuters Web of Science), CINAHL (EBSCOhost) and LILACS (BIREME). We also searched sources specific to diagnostic test accuracy: MEDION (Universities of Maastricht and Leuven); DARE (Database of Abstracts of Reviews of Effects - via the Cochrane Library); HTA Database (Health Technology Assessment Database via the Cochrane Library) and ARIF (Birmingham University). We also checked reference lists of relevant studies and reviews, used searches of known relevant studies in PubMed to track related articles, and contacted research groups conducting work on IQCODE for dementia diagnosis to try to find additional studies. We developed a sensitive search strategy; search terms were designed to cover key concepts using several different approaches run in parallel and included terms relating to cognitive tests, cognitive screening and dementia. We used standardised database subject headings such as MeSH terms (in MEDLINE) and other standardised headings (controlled vocabulary) in other databases, as appropriate. SELECTION CRITERIA We selected those studies performed in secondary-care settings, which included (not necessarily exclusively) IQCODE to assess for the presence of dementia and where dementia diagnosis was confirmed with clinical assessment. For the 'secondary care' setting we included all studies which assessed patients in hospital (e.g. acute unscheduled admissions, referrals to specialist geriatric assessment services etc.) and those referred for specialist 'memory' assessment, typically in psychogeriatric services. DATA COLLECTION AND ANALYSIS We screened all titles generated by electronic database searches, and reviewed abstracts of all potentially relevant studies. Two independent assessors checked full papers for eligibility and extracted data. We determined quality assessment (risk of bias and applicability) using the QUADAS-2 tool, and reporting quality using the STARD tool. MAIN RESULTS From 72 papers describing IQCODE test accuracy, we included 13 papers, representing data from 2745 individuals (n = 1413 (51%) with dementia). Pooled analysis of all studies using data presented closest to a cut-off of 3.3 indicated that sensitivity was 0.91 (95% CI 0.86 to 0.94); specificity 0.66 (95% CI 0.56 to 0.75); the positive likelihood ratio was 2.7 (95% CI 2.0 to 3.6) and the negative likelihood ratio was 0.14 (95% CI 0.09 to 0.22). There was a statistically significant difference in test accuracy between the general hospital setting and the specialist memory setting (P = 0.019), suggesting that IQCODE performs better in a 'general' setting. We found no significant differences in the test accuracy of the short (16-item) versus the 26-item IQCODE, or in the language of administration. There was significant heterogeneity in the included studies, including a highly varied prevalence of dementia (10.5% to 87.4%). Across the included papers there was substantial potential for bias, particularly around sampling of included participants and selection criteria, which may limit generalisability. There was also evidence of suboptimal reporting, particularly around disease severity and handling indeterminate results, which are important if considering use in clinical practice. AUTHORS' CONCLUSIONS The IQCODE can be used to identify older adults in the general hospital setting who are at risk of dementia and require specialist assessment; it is useful specifically for ruling out those without evidence of cognitive decline. The language of administration did not affect test accuracy, which supports the cross-cultural use of the tool. These findings are qualified by the significant heterogeneity, the potential for bias and suboptimal reporting found in the included studies.
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Affiliation(s)
- Jennifer K Burton
- Academic Geriatric Medicine, Institute of Cardiovascular and Medical Sciences, University of Glasgow, Glasgow, UK
| | - Patricia Fearon
- Academic Section of Geriatric Medicine, University of Glasgow, Glasgow, UK
| | | | | | - David J Stott
- Institute of Cardiovascular and Medical Sciences, University of Glasgow, Glasgow , UK
| | - Terry J Quinn
- Institute of Cardiovascular and Medical Sciences, University of Glasgow, Glasgow, UK
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Burton JK, Fearon P, Noel-Storr AH, McShane R, Stott DJ, Quinn TJ. Informant Questionnaire on Cognitive Decline in the Elderly (IQCODE) for the detection of dementia within a general practice (primary care) setting. Cochrane Database Syst Rev 2021; 7:CD010771. [PMID: 34278564 PMCID: PMC8406468 DOI: 10.1002/14651858.cd010771.pub3] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/08/2022]
Abstract
BACKGROUND The IQCODE (Informant Questionnaire for Cognitive Decline in the Elderly) is a commonly used questionnaire based tool that uses collateral information to assess for cognitive decline and dementia. Brief tools that can be used for dementia "screening" or "triage" may have particular utility in primary care / general practice healthcare settings but only if they have suitable test accuracy. A synthesis of the available data regarding IQCODE accuracy in a primary care setting should help inform cognitive assessment strategies for clinical practice; research and policy. OBJECTIVES To determine the accuracy of the informant-based questionnaire IQCODE, for detection of dementia in a primary care setting. SEARCH METHODS A search was performed in the following sources on the 28th of January 2013: ALOIS (Cochrane Dementia and Cognitive Improvement Group), MEDLINE (Ovid SP), EMBASE (Ovid SP), PsycINFO (Ovid SP), BIOSIS (Ovid SP), ISI Web of Science and Conference Proceedings (ISI Web of Knowledge), CINHAL (EBSCOhost) and LILACs (BIREME). We also searched sources specific to diagnostic test accuracy: MEDION (Universities of Maastricht and Leuven); DARE (York University); HTA Database (Health Technology Assessments Database via The Cochrane Library) and ARIF (Birmingham University). We developed a sensitive search strategy; search terms were designed to cover key concepts using several different approaches run in parallel and included terms relating to cognitive tests, cognitive screening and dementia. We used standardized database subject headings such as MeSH terms (in MEDLINE) and other standardized headings (controlled vocabulary) in other databases, as appropriate. SELECTION CRITERIA We selected those studies performed in primary care settings, which included (not necessarily exclusively) IQCODE to assess for the presence of dementia and where dementia diagnosis was confirmed with clinical assessment. For the "primary care" setting, we included those healthcare settings where unselected patients, present for initial, non-specialist assessment of memory or non-memory related symptoms; often with a view to onward referral for more definitive assessment. DATA COLLECTION AND ANALYSIS We screened all titles generated by electronic database searches and abstracts of all potentially relevant studies were reviewed. Full papers were assessed for eligibility and data extracted by two independent assessors. Quality assessment (risk of bias and applicability) was determined using the QUADAS-2 tool. Reporting quality was determined using the STARDdem extension to the STARD tool. MAIN RESULTS From 71 papers describing IQCODE test accuracy, we included 1 paper, representing data from 230 individuals (n=16 [7%] with dementia). The paper described those patients consulting a primary care service who self-identified as Japanese-American. Dementia diagnosis was made using Benson & Cummings criteria and the IQCODE was recorded as part of a longer interview with the informant. IQCODE accuracy was assessed at various test thresholds, with a "trade-off" between sensitivity and specificity across these cutpoints. At an IQCODE threshold of 3.2 sensitivity: 100%, specificity: 76%; for IQCODE 3.7 sensitivity: 75%, specificity: 98%. Applying the QUADAS-2 assessments, the study was at high risk of bias in all categories. In particular degree of blinding was unclear and not all participants were included in the final analysis. AUTHORS' CONCLUSIONS It is not possible to give definitive guidance on the test accuracy of IQCODE for the diagnosis of dementia in a primary care setting based on the single study identified. We are surprised by the lack of research using the IQCODE in primary care as this is, arguably, the most appropriate setting for targeted case finding of those with undiagnosed dementia in order to maximise opportunities to intervene and provide support for the individual and their carers.
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Affiliation(s)
- Jennifer K Burton
- Academic Geriatric Medicine, Institute of Cardiovascular and Medical Sciences, University of Glasgow, Glasgow, UK
| | - Patricia Fearon
- Academic Section of Geriatric Medicine, University of Glasgow, Glasgow, UK
| | | | - Rupert McShane
- Radcliffe Department of Medicine, University of Oxford, Oxford, UK
| | - David J Stott
- Institute of Cardiovascular and Medical Sciences, University of Glasgow, Glasgow , UK
| | - Terry J Quinn
- Institute of Cardiovascular and Medical Sciences, University of Glasgow, Glasgow, UK
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Quinn TJ, Fearon P, Noel-Storr AH, Young C, McShane R, Stott DJ. Informant Questionnaire on Cognitive Decline in the Elderly (IQCODE) for the detection of dementia within community dwelling populations. Cochrane Database Syst Rev 2021; 7:CD010079. [PMID: 34278562 PMCID: PMC8407460 DOI: 10.1002/14651858.cd010079.pub3] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/07/2022]
Abstract
BACKGROUND Various tools exist for initial assessment of possible dementia with no consensus on the optimal assessment method. Instruments that use collateral sources to assess change in cognitive function over time may have particular utility. The most commonly used informant dementia assessment is the Informant Questionnaire on Cognitive Decline in the Elderly (IQCODE). A synthesis of the available data regarding IQCODE accuracy will help inform cognitive assessment strategies for clinical practice, research and policy. OBJECTIVES Our primary obective was to determine the accuracy of the informant-based questionnaire IQCODE for detection of dementia within community dwelling populations. Our secondary objective was to describe the effect of heterogeneity on the summary estimates. We were particularly interested in the traditional 26-item scale versus the 16-item short form; and language of administration. We explored the effect of varying the threshold IQCODE score used to define 'test positivity'. SEARCH METHODS We searched the following sources on 28 January 2013: ALOIS (Cochrane Dementia and Cognitive Improvement Group), MEDLINE (OvidSP), EMBASE (OvidSP), PsycINFO (OvidSP), BIOSIS Previews (ISI Web of Knowledge), Web of Science with Conference Proceedings (ISI Web of Knowledge), LILACS (BIREME). We also searched sources relevant or specific to diagnostic test accuracy: MEDION (Universities of Maastrict and Leuven); DARE (York University); ARIF (Birmingham University). We used sensitive search terms based on MeSH terms and other controlled vocabulary. SELECTION CRITERIA We selected those studies performed in community settings that used (not necessarily exclusively) the IQCODE to assess for presence of dementia and, where dementia diagnosis was confirmed with clinical assessment. Our intention with limiting the search to a 'community' setting was to include those studies closest to population level assessment. Within our predefined community inclusion criteria, there were relevant papers that fulfilled our definition of community dwelling but represented a selected population, for example stroke survivors. We included these studies but performed sensitivity analyses to assess the effects of these less representative populations on the summary results. DATA COLLECTION AND ANALYSIS We screened all titles generated by the electronic database searches and abstracts of all potentially relevant studies were reviewed. Full papers were assessed for eligibility and data extracted by two independent assessors. For quality assessment (risk of bias and applicability) we used the QUADAS 2 tool. We included test accuracy data on the IQCODE used at predefined diagnostic thresholds. Where data allowed, we performed meta-analyses to calculate summary values of sensitivity and specificity with corresponding 95% confidence intervals (CIs). We pre-specified analyses to describe the effect of IQCODE format (traditional or short form) and language of administration for the IQCODE. MAIN RESULTS From 16,144 citations, 71 papers described IQCODE test accuracy. We included 10 papers (11 independent datasets) representing data from 2644 individuals (n = 379 (14%) with dementia). Using IQCODE cut-offs commonly employed in clinical practice (3.3, 3.4, 3.5, 3.6) the sensitivity and specificity of IQCODE for diagnosis of dementia across the studies were generally above 75%. Taking an IQCODE threshold of 3.3 (or closest available) the sensitivity was 0.80 (95% CI 0.75 to 0.85); specificity was 0.84 (95% CI 0.78 to 0.90); positive likelihood ratio was 5.2 (95% CI 3.7 to 7.5) and the negative likelihood ratio was 0.23 (95% CI 0.19 to 0.29). Comparative analysis suggested no significant difference in the test accuracy of the 16 and 26-item IQCODE tests and no significant difference in test accuracy by language of administration. There was little difference in sensitivity across our predefined diagnostic cut-points. There was substantial heterogeneity in the included studies. Sensitivity analyses removing potentially unrepresentative populations in these studies made little difference to the pooled data estimates. The majority of included papers had potential for bias, particularly around participant selection and sampling. The quality of reporting was suboptimal particularly regarding timing of assessments and descriptors of reproducibility and inter-observer variability. AUTHORS' CONCLUSIONS Published data suggest that if using the IQCODE for community dwelling older adults, the 16 item IQCODE may be preferable to the traditional scale due to lesser test burden and no obvious difference in accuracy. Although IQCODE test accuracy is in a range that many would consider 'reasonable', in the context of community or population settings the use of the IQCODE alone would result in substantial misdiagnosis and false reassurance. Across the included studies there were issues with heterogeneity, several potential biases and suboptimal reporting quality.
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Affiliation(s)
- Terry J Quinn
- Institute of Cardiovascular and Medical Sciences, University of Glasgow, Glasgow, UK
| | - Patricia Fearon
- Academic Section of Geriatric Medicine, University of Glasgow, Glasgow, UK
| | | | - Camilla Young
- Institute of Cardiovascular and Medical Sciences, University of Glasgow, Glasgow, UK
| | | | - David J Stott
- Institute of Cardiovascular and Medical Sciences, University of Glasgow, Glasgow , UK
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Burton JK, Stott DJ, McShane R, Noel-Storr AH, Swann-Price RS, Quinn TJ. Informant Questionnaire on Cognitive Decline in the Elderly (IQCODE) for the early detection of dementia across a variety of healthcare settings. Cochrane Database Syst Rev 2021; 7:CD011333. [PMID: 34275145 PMCID: PMC8406787 DOI: 10.1002/14651858.cd011333.pub3] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Abstract
BACKGROUND The Informant Questionnaire for Cognitive Decline in the Elderly (IQCODE) is a structured interview based on informant responses that is used to assess for possible dementia. IQCODE has been used for retrospective or contemporaneous assessment of cognitive decline. There is considerable interest in tests that may identify those at future risk of developing dementia. Assessing a population free of dementia for the prospective development of dementia is an approach often used in studies of dementia biomarkers. In theory, questionnaire-based assessments, such as IQCODE, could be used in a similar way, assessing for dementia that is diagnosed on a later (delayed) assessment. OBJECTIVES To determine the accuracy of the informant-based questionnaire IQCODE for the early detection of dementia across a variety of health care settings. SEARCH METHODS We searched these sources on 16 January 2016: ALOIS (Cochrane Dementia and Cognitive Improvement Group), MEDLINE Ovid SP, Embase Ovid SP, PsycINFO Ovid SP, BIOSIS Previews on Thomson Reuters Web of Science, Web of Science Core Collection (includes Conference Proceedings Citation Index) on Thomson Reuters Web of Science, CINAHL EBSCOhost, and LILACS BIREME. We also searched sources specific to diagnostic test accuracy: MEDION (Universities of Maastricht and Leuven); DARE (Database of Abstracts of Reviews of Effects, in the Cochrane Library); HTA Database (Health Technology Assessment Database, in the Cochrane Library), and ARIF (Birmingham University). We checked reference lists of included studies and reviews, used searches of included studies in PubMed to track related articles, and contacted research groups conducting work on IQCODE for dementia diagnosis to try to find additional studies. We developed a sensitive search strategy; search terms were designed to cover key concepts using several different approaches run in parallel, and included terms relating to cognitive tests, cognitive screening, and dementia. We used standardised database subject headings, such as MeSH terms (in MEDLINE) and other standardised headings (controlled vocabulary) in other databases, as appropriate. SELECTION CRITERIA We selected studies that included a population free from dementia at baseline, who were assessed with the IQCODE and subsequently assessed for the development of dementia over time. The implication was that at the time of testing, the individual had a cognitive problem sufficient to result in an abnormal IQCODE score (defined by the study authors), but not yet meeting dementia diagnostic criteria. DATA COLLECTION AND ANALYSIS We screened all titles generated by the electronic database searches, and reviewed abstracts of all potentially relevant studies. Two assessors independently checked the full papers for eligibility and extracted data. We determined quality assessment (risk of bias and applicability) using the QUADAS-2 tool, and reported quality using the STARDdem tool. MAIN RESULTS From 85 papers describing IQCODE, we included three papers, representing data from 626 individuals. Of this total, 22% (N = 135/626) were excluded because of prevalent dementia. There was substantial attrition; 47% (N = 295) of the study population received reference standard assessment at first follow-up (three to six months) and 28% (N = 174) received reference standard assessment at final follow-up (one to three years). Prevalence of dementia ranged from 12% to 26% at first follow-up and 16% to 35% at final follow-up. The three studies were considered to be too heterogenous to combine, so we did not perform meta-analyses to describe summary estimates of interest. Included patients were poststroke (two papers) and hip fracture (one paper). The IQCODE was used at three thresholds of positivity (higher than 3.0, higher than 3.12 and higher than 3.3) to predict those at risk of a future diagnosis of dementia. Using a cut-off of 3.0, IQCODE had a sensitivity of 0.75 (95%CI 0.51 to 0.91) and a specificity of 0.46 (95%CI 0.34 to 0.59) at one year following stroke. Using a cut-off of 3.12, the IQCODE had a sensitivity of 0.80 (95%CI 0.44 to 0.97) and specificity of 0.53 (95C%CI 0.41 to 0.65) for the clinical diagnosis of dementia at six months after hip fracture. Using a cut-off of 3.3, the IQCODE had a sensitivity of 0.84 (95%CI 0.68 to 0.94) and a specificity of 0.87 (95%CI 0.76 to 0.94) for the clinical diagnosis of dementia at one year after stroke. In generaI, the IQCODE was sensitive for identification of those who would develop dementia, but lacked specificity. Methods for both excluding prevalent dementia at baseline and assessing for the development of dementia were varied, and had the potential to introduce bias. AUTHORS' CONCLUSIONS Included studies were heterogenous, recruited from specialist settings, and had potential biases. The studies identified did not allow us to make specific recommendations on the use of the IQCODE for the future detection of dementia in clinical practice. The included studies highlighted the challenges of delayed verification dementia research, with issues around prevalent dementia assessment, loss to follow-up over time, and test non-completion potentially limiting the studies. Future research should recognise these issues and have explicit protocols for dealing with them.
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Affiliation(s)
- Jennifer K Burton
- Academic Geriatric Medicine, Institute of Cardiovascular and Medical Sciences, University of Glasgow, Glasgow, UK
| | - David J Stott
- Institute of Cardiovascular and Medical Sciences, University of Glasgow, Glasgow , UK
| | | | | | | | - Terry J Quinn
- Institute of Cardiovascular and Medical Sciences, University of Glasgow, Glasgow, UK
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Huang HC, Tseng YM, Chen YC, Chen PY, Chiu HY. Diagnostic accuracy of the Clinical Dementia Rating Scale for detecting mild cognitive impairment and dementia: A bivariate meta-analysis. Int J Geriatr Psychiatry 2021; 36:239-251. [PMID: 32955146 DOI: 10.1002/gps.5436] [Citation(s) in RCA: 46] [Impact Index Per Article: 15.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/14/2020] [Accepted: 09/16/2020] [Indexed: 12/29/2022]
Abstract
OBJECTIVE The Clinical Dementia Rating (CDR) Scale comprising global score (CDR-GS) and sum of boxes scores (CDR-SB) is commonly used in staging cognitive impairment; however, its diagnostic accuracy is not well clarified. The meta-analysis aimed to investigate the diagnostic accuracy of the CDR for mild cognitive impairment (MCI) and dementia in older populations. METHODS Studies examining the diagnostic accuracy of the CDR for MCI or dementia against reference standards were included from seven electronic databases. The bivariate analysis with a random-effects model was adopted to calculate the pooled sensitivity and specificity of the CDR for MCI and dementia. RESULTS Fifteen studies investigating the diagnostic accuracy of the CDR-GS (n = 13) or CDR-SB (n = 5) for MCI or dementia were included. The pooled sensitivity and specificity of the CDR-GS for MCI were 93% and 97%, respectively. With respect to dementia, the CDR-GS had superior pooled specificity compared to the CDR-SB (99% vs. 94%), while similar sensitivities were found between the CDR-GS and CDR-SB (both 87%). Significant moderators of an old age, a high educational level, a high prevalence of MCI or dementia, being in a developing country, and a lack of informants' observations may affect the estimation of the sensitivity or specificity of the CDR. CONCLUSIONS Evidence supports the CDR being useful for detecting MCI and dementia; applying the CDR for staging cognitive impairment in at risk populations should be considered. Furthermore, including objective observations from relevant informants or proxies to increase the accuracy of the CDR for dementia is suggested.
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Affiliation(s)
- Hui-Chuan Huang
- School of Nursing, College of Nursing, Taipei Medical University, Taipei, Taiwan, ROC
| | - Yu-Min Tseng
- School of Nursing, College of Nursing, Taipei Medical University, Taipei, Taiwan, ROC
| | - Yi-Chun Chen
- Department of Neurology, Chang Gung Memorial Hospital at Linkou, Chang Gung University College of Medicine, Taoyuan, Taiwan, ROC
| | - Pin-Yuan Chen
- Department of Neurosurgery, Chang Gung Memorial Hospital, Keelung, Taiwan, ROC.,School of Medicine, College of Medicine, Chang Gung University, Taoyuan, Taiwan, ROC
| | - Hsiao-Yean Chiu
- School of Nursing, College of Nursing, Taipei Medical University, Taipei, Taiwan, ROC.,Research Center of Sleep Medicine, College of Medicine, Taipei Medical University, Taipei, Taiwan, ROC
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Hale K, Østbye T, Perera B, Bradley R, Maselko J. A Novel Adaptation of the HOME Inventory for Elders: The Importance of the Home Environment Across the Life Course. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2019; 16:E2826. [PMID: 31398802 PMCID: PMC6719999 DOI: 10.3390/ijerph16162826] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Received: 07/09/2019] [Revised: 07/27/2019] [Accepted: 07/28/2019] [Indexed: 12/14/2022]
Abstract
The context in which dependents, regardless of age, receive care affects their health. This study adapted the Home Observation for Measurement of the Environment (HOME) Inventory, originally designed for child development research, to assess the quality of stimulation and support available to elders in their habitual households in Sri Lanka. Whether the adapted domains correlated with indicators of health and well-being in ways consistent with the child development literature was then examined. Through mixed-methods research based on 248 household surveys, four focus groups, and 15 interviews, three domains emerged: Physical Environment, Variety of Stimulation, and Emotional and Verbal Responsiveness. Regression modeling revealed that a higher quality physical home environment correlated with two measures of cognitive function after adjusting for covariates, but no consistent association with two psychological well-being scales. In contrast, higher Variety of Stimulation scores correlated with better cognitive function and lower psychological distress. There was no consistent correlation between Responsiveness and selected health outcomes. Qualitative data indicate that elders are active household contributors who strive to achieve harmonious relations with coresident kin. These findings reveal notable synergies between early and late life efforts to improve cognitive and psychological health, and highlight household considerations for future healthy aging research.
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Affiliation(s)
- Kathryn Hale
- Cecil G. Sheps Center for Health Services Research, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA.
| | - Truls Østbye
- Department of Family Medicine and Community Health, Duke University School of Medicine, Durham, NC 27710, USA
- Center for Aging Research and Education, Duke-NUS Medical School, Singapore 169857, Singapore
| | - Bilesha Perera
- Department of Community Medicine, Faculty of Medicine, University of Ruhuna, Galle 80000, Sri Lanka
| | - Robert Bradley
- Department of Psychology, Arizona State University, Tempe, AZ 85287, USA
| | - Joanna Maselko
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
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Harrison JK, Stott DJ, McShane R, Noel‐Storr AH, Swann‐Price RS, Quinn TJ. Informant Questionnaire on Cognitive Decline in the Elderly (IQCODE) for the early diagnosis of dementia across a variety of healthcare settings. Cochrane Database Syst Rev 2016; 11:CD011333. [PMID: 27869298 PMCID: PMC6477966 DOI: 10.1002/14651858.cd011333.pub2] [Citation(s) in RCA: 27] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/23/2022]
Abstract
BACKGROUND The Informant Questionnaire for Cognitive Decline in the Elderly (IQCODE) is a structured interview based on informant responses that is used to assess for possible dementia. IQCODE has been used for retrospective or contemporaneous assessment of cognitive decline. There is considerable interest in tests that may identify those at future risk of developing dementia. Assessing a population free of dementia for the prospective development of dementia is an approach often used in studies of dementia biomarkers. In theory, questionnaire-based assessments, such as IQCODE, could be used in a similar way, assessing for dementia that is diagnosed on a later (delayed) assessment. OBJECTIVES To determine the diagnostic accuracy of IQCODE in a population free from dementia for the delayed diagnosis of dementia (test accuracy with delayed verification study design). SEARCH METHODS We searched these sources on 16 January 2016: ALOIS (Cochrane Dementia and Cognitive Improvement Group), MEDLINE Ovid SP, Embase Ovid SP, PsycINFO Ovid SP, BIOSIS Previews on Thomson Reuters Web of Science, Web of Science Core Collection (includes Conference Proceedings Citation Index) on Thomson Reuters Web of Science, CINAHL EBSCOhost, and LILACS BIREME. We also searched sources specific to diagnostic test accuracy: MEDION (Universities of Maastricht and Leuven); DARE (Database of Abstracts of Reviews of Effects, in the Cochrane Library); HTA Database (Health Technology Assessment Database, in the Cochrane Library), and ARIF (Birmingham University). We checked reference lists of included studies and reviews, used searches of included studies in PubMed to track related articles, and contacted research groups conducting work on IQCODE for dementia diagnosis to try to find additional studies. We developed a sensitive search strategy; search terms were designed to cover key concepts using several different approaches run in parallel, and included terms relating to cognitive tests, cognitive screening, and dementia. We used standardised database subject headings, such as MeSH terms (in MEDLINE) and other standardised headings (controlled vocabulary) in other databases, as appropriate. SELECTION CRITERIA We selected studies that included a population free from dementia at baseline, who were assessed with the IQCODE and subsequently assessed for the development of dementia over time. The implication was that at the time of testing, the individual had a cognitive problem sufficient to result in an abnormal IQCODE score (defined by the study authors), but not yet meeting dementia diagnostic criteria. DATA COLLECTION AND ANALYSIS We screened all titles generated by the electronic database searches, and reviewed abstracts of all potentially relevant studies. Two assessors independently checked the full papers for eligibility and extracted data. We determined quality assessment (risk of bias and applicability) using the QUADAS-2 tool, and reported quality using the STARDdem tool. MAIN RESULTS From 85 papers describing IQCODE, we included three papers, representing data from 626 individuals. Of this total, 22% (N = 135/626) were excluded because of prevalent dementia. There was substantial attrition; 47% (N = 295) of the study population received reference standard assessment at first follow-up (three to six months) and 28% (N = 174) received reference standard assessment at final follow-up (one to three years). Prevalence of dementia ranged from 12% to 26% at first follow-up and 16% to 35% at final follow-up.The three studies were considered to be too heterogenous to combine, so we did not perform meta-analyses to describe summary estimates of interest. Included patients were poststroke (two papers) and hip fracture (one paper). The IQCODE was used at three thresholds of positivity (higher than 3.0, higher than 3.12 and higher than 3.3) to predict those at risk of a future diagnosis of dementia. Using a cut-off of 3.0, IQCODE had a sensitivity of 0.75 (95%CI 0.51 to 0.91) and a specificity of 0.46 (95%CI 0.34 to 0.59) at one year following stroke. Using a cut-off of 3.12, the IQCODE had a sensitivity of 0.80 (95%CI 0.44 to 0.97) and specificity of 0.53 (95C%CI 0.41 to 0.65) for the clinical diagnosis of dementia at six months after hip fracture. Using a cut-off of 3.3, the IQCODE had a sensitivity of 0.84 (95%CI 0.68 to 0.94) and a specificity of 0.87 (95%CI 0.76 to 0.94) for the clinical diagnosis of dementia at one year after stroke.In generaI, the IQCODE was sensitive for identification of those who would develop dementia, but lacked specificity. Methods for both excluding prevalent dementia at baseline and assessing for the development of dementia were varied, and had the potential to introduce bias. AUTHORS' CONCLUSIONS Included studies were heterogenous, recruited from specialist settings, and had potential biases. The studies identified did not allow us to make specific recommendations on the use of the IQCODE for the future diagnosis of dementia in clinical practice. The included studies highlighted the challenges of delayed verification dementia research, with issues around prevalent dementia assessment, loss to follow-up over time, and test non-completion potentially limiting the studies. Future research should recognise these issues and have explicit protocols for dealing with them.
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Affiliation(s)
- Jennifer K Harrison
- University of EdinburghCentre for Cognitive Ageing and Cognitive Epidemiology and the Alzheimer Scotland Dementia Research CentreDepartment of Geriatric Medicine, The Royal Infirmary of Edinburgh, Room S164251 Little France CrescentEdinburghUKEH16 4SB
| | - David J Stott
- University of GlasgowInstitute of Cardiovascular and Medical SciencesNew Lister BuildingGlasgow Royal InfirmaryGlasgowStrathclydeUKG4 0SFR
| | - Rupert McShane
- University of OxfordRadcliffe Department of MedicineJohn Radcliffe HospitalLevel 4, Main Hospital, Room 4401COxfordOxfordshireUKOX3 9DU
| | - Anna H Noel‐Storr
- University of OxfordRadcliffe Department of MedicineJohn Radcliffe HospitalLevel 4, Main Hospital, Room 4401COxfordOxfordshireUKOX3 9DU
| | | | - Terry J Quinn
- University of GlasgowInstitute of Cardiovascular and Medical SciencesNew Lister BuildingGlasgow Royal InfirmaryGlasgowStrathclydeUKG4 0SFR
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Creavin ST, Wisniewski S, Noel‐Storr AH, Trevelyan CM, Hampton T, Rayment D, Thom VM, Nash KJE, Elhamoui H, Milligan R, Patel AS, Tsivos DV, Wing T, Phillips E, Kellman SM, Shackleton HL, Singleton GF, Neale BE, Watton ME, Cullum S. Mini-Mental State Examination (MMSE) for the detection of dementia in clinically unevaluated people aged 65 and over in community and primary care populations. Cochrane Database Syst Rev 2016; 2016:CD011145. [PMID: 26760674 PMCID: PMC8812342 DOI: 10.1002/14651858.cd011145.pub2] [Citation(s) in RCA: 311] [Impact Index Per Article: 38.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/20/2022]
Abstract
BACKGROUND The Mini Mental State Examination (MMSE) is a cognitive test that is commonly used as part of the evaluation for possible dementia. OBJECTIVES To determine the diagnostic accuracy of the Mini-Mental State Examination (MMSE) at various cut points for dementia in people aged 65 years and over in community and primary care settings who had not undergone prior testing for dementia. SEARCH METHODS We searched the specialised register of the Cochrane Dementia and Cognitive Improvement Group, MEDLINE (OvidSP), EMBASE (OvidSP), PsycINFO (OvidSP), LILACS (BIREME), ALOIS, BIOSIS previews (Thomson Reuters Web of Science), and Web of Science Core Collection, including the Science Citation Index and the Conference Proceedings Citation Index (Thomson Reuters Web of Science). We also searched specialised sources of diagnostic test accuracy studies and reviews: MEDION (Universities of Maastricht and Leuven, www.mediondatabase.nl), DARE (Database of Abstracts of Reviews of Effects, via the Cochrane Library), HTA Database (Health Technology Assessment Database, via the Cochrane Library), and ARIF (University of Birmingham, UK, www.arif.bham.ac.uk). We attempted to locate possibly relevant but unpublished data by contacting researchers in this field. We first performed the searches in November 2012 and then fully updated them in May 2014. We did not apply any language or date restrictions to the electronic searches, and we did not use any methodological filters as a method to restrict the search overall. SELECTION CRITERIA We included studies that compared the 11-item (maximum score 30) MMSE test (at any cut point) in people who had not undergone prior testing versus a commonly accepted clinical reference standard for all-cause dementia and subtypes (Alzheimer disease dementia, Lewy body dementia, vascular dementia, frontotemporal dementia). Clinical diagnosis included all-cause (unspecified) dementia, as defined by any version of the Diagnostic and Statistical Manual of Mental Disorders (DSM); International Classification of Diseases (ICD) and the Clinical Dementia Rating. DATA COLLECTION AND ANALYSIS At least three authors screened all citations.Two authors handled data extraction and quality assessment. We performed meta-analysis using the hierarchical summary receiver-operator curves (HSROC) method and the bivariate method. MAIN RESULTS We retrieved 24,310 citations after removal of duplicates. We reviewed the full text of 317 full-text articles and finally included 70 records, referring to 48 studies, in our synthesis. We were able to perform meta-analysis on 28 studies in the community setting (44 articles) and on 6 studies in primary care (8 articles), but we could not extract usable 2 x 2 data for the remaining 14 community studies, which we did not include in the meta-analysis. All of the studies in the community were in asymptomatic people, whereas two of the six studies in primary care were conducted in people who had symptoms of possible dementia. We judged two studies to be at high risk of bias in the patient selection domain, three studies to be at high risk of bias in the index test domain and nine studies to be at high risk of bias regarding flow and timing. We assessed most studies as being applicable to the review question though we had concerns about selection of participants in six studies and target condition in one study.The accuracy of the MMSE for diagnosing dementia was reported at 18 cut points in the community (MMSE score 10, 14-30 inclusive) and 10 cut points in primary care (MMSE score 17-26 inclusive). The total number of participants in studies included in the meta-analyses ranged from 37 to 2727, median 314 (interquartile range (IQR) 160 to 647). In the community, the pooled accuracy at a cut point of 24 (15 studies) was sensitivity 0.85 (95% confidence interval (CI) 0.74 to 0.92), specificity 0.90 (95% CI 0.82 to 0.95); at a cut point of 25 (10 studies), sensitivity 0.87 (95% CI 0.78 to 0.93), specificity 0.82 (95% CI 0.65 to 0.92); and in seven studies that adjusted accuracy estimates for level of education, sensitivity 0.97 (95% CI 0.83 to 1.00), specificity 0.70 (95% CI 0.50 to 0.85). There was insufficient data to evaluate the accuracy of the MMSE for diagnosing dementia subtypes.We could not estimate summary diagnostic accuracy in primary care due to insufficient data. AUTHORS' CONCLUSIONS The MMSE contributes to a diagnosis of dementia in low prevalence settings, but should not be used in isolation to confirm or exclude disease. We recommend that future work evaluates the diagnostic accuracy of tests in the context of the diagnostic pathway experienced by the patient and that investigators report how undergoing the MMSE changes patient-relevant outcomes.
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Affiliation(s)
- Sam T Creavin
- University of BristolSchool of Social and Community MedicineCarynge Hall39 Whatley RoadBristolUKBS8 2PS
| | - Susanna Wisniewski
- Cochrane Dementia and Cognitive Improvement Group, Oxford UniversityOxfordUK
| | - Anna H Noel‐Storr
- University of OxfordRadcliffe Department of MedicineRoom 4401c (4th Floor)John Radcliffe Hospital, HeadingtonOxfordUKOX3 9DU
| | - Clare M Trevelyan
- Avon and Wiltshire Mental Health Partnership NHS TrustMedical EducationWoodland View, Brentry LaneBristolUKBS10 6NB
| | - Thomas Hampton
- Frimley Health NHS Foundation TrustENTFrimley Park HospitalPortsmouth RoadFrimley, CamberleySurreyUKGU16 7UJ
| | - Dane Rayment
- Avon and Wiltshire Partnership NHS TrustOlder Adult PsychiatryJenner House, Langley ParkChippenhamWiltshireUKSN15 1GG
| | - Victoria M Thom
- Avon & Wiltshire Mental Health Partnership NHS TrustForensic PsychiatryFromeside, Blackberry Hill HospitalBristolUKBS16 1EG
| | | | - Hosam Elhamoui
- Somerset Partnership NHS TrustPsychiatry91 Comeytrowe LaneTauntonSomersetUKTA1 5QG
| | - Rowena Milligan
- Mansion House SurgeryGeneral PracticeAbbey StreetStoneStaffordshireUKST15 0WA
| | - Anish S Patel
- Avon and Wiltshire Mental Health Partnership NHS TrustNBT Acute Mental Health Liaison TeamDonal Early HouseSouthmead HospitalBristolUKBS10 5NB
| | - Demitra V Tsivos
- North Bristol NHS TrustNeuropsychologySouthmead HospitalBristolUKBS10 5NB
| | - Tracey Wing
- Taunton and Somerset NHS trustCare of Elderly/ITU/A+EBristolUKBS1 3DH
| | - Emma Phillips
- 2gether NHS Foundation TrustCharlton Lane HospitalCheltenhamGloucestershireUKGL53 9DZ
| | - Sophie M Kellman
- Avon and Wiltshire Mental Health Partnership NHS TrustJenner House, Langley ParkChippenhamWiltshireUKSN15 1GG
| | - Hannah L Shackleton
- NHS ScotlandNHS Forth ValleyFalkirk Community Hospital, Majors LoanFalkirkUK
| | | | - Bethany E Neale
- RCGP Severn FacultyGeneral PracticeDeanery HouseBristolUKBA16 1GW
| | | | - Sarah Cullum
- University of BristolSchool of Social and Community MedicineCarynge Hall39 Whatley RoadBristolUKBS8 2PS
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Awan S, Shahbaz N, Akhtar SW, Ahmad A, Iqbal S, Ahmed S, Naqvi H, Wasay M. Validation Study of the Mini-Mental State Examination in Urdu Language for Pakistani Population. Open Neurol J 2015; 9:53-8. [PMID: 26191094 PMCID: PMC4503826 DOI: 10.2174/1874205x01509010053] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2014] [Revised: 12/01/2014] [Accepted: 12/11/2014] [Indexed: 11/22/2022] Open
Abstract
Validation study of the Mini-Mental State Examination in Urdu language for Pakistani population
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Affiliation(s)
- Safia Awan
- Department of Medicine, Neurology, Psychiatry, Aga Khan University, Karachi
| | - Naila Shahbaz
- Department of Medicine, Neurology, Psychiatry, Aga Khan University, Karachi
| | - Syed Wasim Akhtar
- Neurology Section, Department of Medicine, Karachi Medical & Dental College and Abbasi Shaheed Hospital, Karachi
| | - Arsalan Ahmad
- Department of Neurology, Shifa International Medical College and Hospital, Islamabad
| | - Sadaf Iqbal
- Department of Neurology and Geriatrics, Liaquat National Hospital, Karachi
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Harrison JK, Fearon P, Noel-Storr AH, McShane R, Stott DJ, Quinn TJ. Informant Questionnaire on Cognitive Decline in the Elderly (IQCODE) for the diagnosis of dementia within a secondary care setting. Cochrane Database Syst Rev 2015:CD010772. [PMID: 25754745 DOI: 10.1002/14651858.cd010772.pub2] [Citation(s) in RCA: 61] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
Abstract
BACKGROUND The diagnosis of dementia relies on the presence of new-onset cognitive impairment affecting an individual's functioning and activities of daily living. The Informant Questionnaire on Cognitive Decline in the Elderly (IQCODE) is a questionnaire instrument, completed by a suitable 'informant' who knows the patient well, designed to assess change in functional performance secondary to cognitive change; it is used as a tool to identifying those who may have dementia.In secondary care there are two specific instances where patients may be assessed for the presence of dementia. These are in the general acute hospital setting, where opportunistic screening may be undertaken, or in specialist memory services where individuals have been referred due to perceived cognitive problems. To ensure an instrument is suitable for diagnostic use in these settings, its test accuracy must be established. OBJECTIVES To determine the diagnostic accuracy of the informant-based questionnaire IQCODE, for detection of all-cause (undifferentiated) dementia in adults presenting to secondary-care services. SEARCH METHODS We searched the following sources on the 28th of January 2013: ALOIS (Cochrane Dementia and Cognitive Improvement Group), MEDLINE (Ovid SP), EMBASE (Ovid SP), PsycINFO (Ovid SP), BIOSIS Previews (Thomson Reuters Web of Science), Web of Science Core Collection (includes Conference Proceedings Citation Index) (Thomson Reuters Web of Science), CINAHL (EBSCOhost) and LILACS (BIREME). We also searched sources specific to diagnostic test accuracy: MEDION (Universities of Maastricht and Leuven); DARE (Database of Abstracts of Reviews of Effects - via the Cochrane Library); HTA Database (Health Technology Assessment Database via the Cochrane Library) and ARIF (Birmingham University). We also checked reference lists of relevant studies and reviews, used searches of known relevant studies in PubMed to track related articles, and contacted research groups conducting work on IQCODE for dementia diagnosis to try to find additional studies. We developed a sensitive search strategy; search terms were designed to cover key concepts using several different approaches run in parallel and included terms relating to cognitive tests, cognitive screening and dementia. We used standardised database subject headings such as MeSH terms (in MEDLINE) and other standardised headings (controlled vocabulary) in other databases, as appropriate. SELECTION CRITERIA We selected those studies performed in secondary-care settings, which included (not necessarily exclusively) IQCODE to assess for the presence of dementia and where dementia diagnosis was confirmed with clinical assessment. For the 'secondary care' setting we included all studies which assessed patients in hospital (e.g. acute unscheduled admissions, referrals to specialist geriatric assessment services etc.) and those referred for specialist 'memory' assessment, typically in psychogeriatric services. DATA COLLECTION AND ANALYSIS We screened all titles generated by electronic database searches, and reviewed abstracts of all potentially relevant studies. Two independent assessors checked full papers for eligibility and extracted data. We determined quality assessment (risk of bias and applicability) using the QUADAS-2 tool, and reporting quality using the STARD tool. MAIN RESULTS From 72 papers describing IQCODE test accuracy, we included 13 papers, representing data from 2745 individuals (n = 1413 (51%) with dementia). Pooled analysis of all studies using data presented closest to a cut-off of 3.3 indicated that sensitivity was 0.91 (95% CI 0.86 to 0.94); specificity 0.66 (95% CI 0.56 to 0.75); the positive likelihood ratio was 2.7 (95% CI 2.0 to 3.6) and the negative likelihood ratio was 0.14 (95% CI 0.09 to 0.22).There was a statistically significant difference in test accuracy between the general hospital setting and the specialist memory setting (P = 0.019), suggesting that IQCODE performs better in a 'general' setting.We found no significant differences in the test accuracy of the short (16-item) versus the 26-item IQCODE, or in the language of administration.There was significant heterogeneity in the included studies, including a highly varied prevalence of dementia (10.5% to 87.4%). Across the included papers there was substantial potential for bias, particularly around sampling of included participants and selection criteria, which may limit generalisability. There was also evidence of suboptimal reporting, particularly around disease severity and handling indeterminate results, which are important if considering use in clinical practice. AUTHORS' CONCLUSIONS The IQCODE can be used to identify older adults in the general hospital setting who are at risk of dementia and require specialist assessment; it is useful specifically for ruling out those without evidence of cognitive decline. The language of administration did not affect test accuracy, which supports the cross-cultural use of the tool. These findings are qualified by the significant heterogeneity, the potential for bias and suboptimal reporting found in the included studies.
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Affiliation(s)
- Jennifer K Harrison
- Department of Cardiovascular Sciences, University of Leicester, Leicester Royal Infirmary, Leicester, UK, LE1 5WW
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Harrison JK, Fearon P, Noel-Storr AH, McShane R, Stott DJ, Quinn TJ. Informant Questionnaire on Cognitive Decline in the Elderly (IQCODE) for the diagnosis of dementia within a general practice (primary care) setting. Cochrane Database Syst Rev 2014:CD010771. [PMID: 24990271 DOI: 10.1002/14651858.cd010771.pub2] [Citation(s) in RCA: 33] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/02/2023]
Abstract
BACKGROUND The IQCODE (Informant Questionnaire for Cognitive Decline in the Elderly) is a commonly used questionnaire based tool that uses collateral information to assess for cognitive decline and dementia. Brief tools that can be used for dementia "screening" or "triage" may have particular utility in primary care / general practice healthcare settings but only if they have suitable test accuracy.A synthesis of the available data regarding IQCODE accuracy in a primary care setting should help inform cognitive assessment strategies for clinical practice; research and policy. OBJECTIVES We sought to describe the accuracy of IQCODE (the index test) against a clinical diagnosis of dementia (the reference standard). In this review we focus on those studies conducted in a primary care (general practice) setting. SEARCH METHODS A search was performed in the following sources on the 28th of January 2013: ALOIS (Cochrane Dementia and Cognitive Improvement Group), MEDLINE (Ovid SP), EMBASE (Ovid SP), PsycINFO (Ovid SP), BIOSIS (Ovid SP), ISI Web of Science and Conference Proceedings (ISI Web of Knowledge), CINHAL (EBSCOhost) and LILACs (BIREME). We also searched sources specific to diagnostic test accuracy: MEDION (Universities of Maastricht and Leuven); DARE (York University); HTA Database (Health Technology Assessments Database via The Cochrane Library) and ARIF (Birmingham University). We developed a sensitive search strategy; search terms were designed to cover key concepts using several different approaches run in parallel and included terms relating to cognitive tests, cognitive screening and dementia. We used standardized database subject headings such as MeSH terms (in MEDLINE) and other standardized headings (controlled vocabulary) in other databases, as appropriate. SELECTION CRITERIA We selected those studies performed in primary care settings, which included (not necessarily exclusively) IQCODE to assess for the presence of dementia and where dementia diagnosis was confirmed with clinical assessment. For the "primary care" setting, we included those healthcare settings where unselected patients, present for initial, non-specialist assessment of memory or non-memory related symptoms; often with a view to onward referral for more definitive assessment. DATA COLLECTION AND ANALYSIS We screened all titles generated by electronic database searches and abstracts of all potentially relevant studies were reviewed. Full papers were assessed for eligibility and data extracted by two independent assessors. Quality assessment (risk of bias and applicability) was determined using the QUADAS-2 tool. Reporting quality was determined using the STARDdem extension to the STARD tool. MAIN RESULTS From 71 papers describing IQCODE test accuracy, we included 1 paper, representing data from 230 individuals (n=16 [7%] with dementia). The paper described those patients consulting a primary care service who self-identified as Japanese-American. Dementia diagnosis was made using Benson & Cummings criteria and the IQCODE was recorded as part of a longer interview with the informant.IQCODE accuracy was assessed at various test thresholds, with a "trade-off" between sensitivity and specificity across these cutpoints. At an IQCODE threshold of 3.2 sensitivity: 100%, specificity: 76%; for IQCODE 3.7 sensitivity: 75%, specificity: 98%.Applying the QUADAS-2 assessments, the study was at high risk of bias in all categories. In particular degree of blinding was unclear and not all participants were included in the final analysis. AUTHORS' CONCLUSIONS It is not possible to give definitive guidance on the test accuracy of IQCODE for the diagnosis of dementia in a primary care setting based on the single study identified. We are surprised by the lack of research using the IQCODE in primary care as this is, arguably, the most appropriate setting for targeted case finding of those with undiagnosed dementia in order to maximise opportunities to intervene and provide support for the individual and their carers.
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Affiliation(s)
- Jennifer K Harrison
- Department of Cardiovascular Sciences, University of Leicester, Leicester Royal Infirmary, Leicester, UK, LE1 5WW
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Quinn TJ, Fearon P, Noel-Storr AH, Young C, McShane R, Stott DJ. Informant Questionnaire on Cognitive Decline in the Elderly (IQCODE) for the diagnosis of dementia within community dwelling populations. Cochrane Database Syst Rev 2014:CD010079. [PMID: 24719028 DOI: 10.1002/14651858.cd010079.pub2] [Citation(s) in RCA: 64] [Impact Index Per Article: 6.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/20/2022]
Abstract
BACKGROUND Various tools exist for initial assessment of possible dementia with no consensus on the optimal assessment method. Instruments that use collateral sources to assess change in cognitive function over time may have particular utility. The most commonly used informant dementia assessment is the Informant Questionnaire on Cognitive Decline in the Elderly (IQCODE).A synthesis of the available data regarding IQCODE accuracy will help inform cognitive assessment strategies for clinical practice, research and policy. OBJECTIVES Our primary objective was to determine the diagnostic accuracy of the informant based questionnaire IQCODE, for detection of all cause (undifferentiated) dementia in community-dwelling adults with no previous cognitive assessment. We sought to describe the accuracy of IQCODE (the index test) against a clinical diagnosis of dementia (the reference standard). Our secondary objective was to describe the effect of heterogeneity on the summary estimates. We were particularly interested in the traditional 26-item scale versus the 16-item short form; and language of administration. We explored the effect of varying the threshold IQCODE score used to define 'test positivity'. SEARCH METHODS We searched the following sources on 28 January 2013: ALOIS (Cochrane Dementia and Cognitive Improvement Group), MEDLINE (OvidSP), EMBASE (OvidSP), PsycINFO (OvidSP), BIOSIS Previews (ISI Web of Knowledge), Web of Science with Conference Proceedings (ISI Web of Knowledge), LILACS (BIREME). We also searched sources relevant or specific to diagnostic test accuracy: MEDION (Universities of Maastrict and Leuven); DARE (York University); ARIF (Birmingham University). We used sensitive search terms based on MeSH terms and other controlled vocabulary. SELECTION CRITERIA We selected those studies performed in community settings that used (not necessarily exclusively) the IQCODE to assess for presence of dementia and, where dementia diagnosis was confirmed, with clinical assessment. Our intention with limiting the search to a 'community' setting was to include those studies closest to population level assessment. Within our predefined community inclusion criteria, there were relevant papers that fulfilled our definition of community dwelling but represented a selected population, for example stroke survivors. We included these studies but performed sensitivity analyses to assess the effects of these less representative populations on the summary results. DATA COLLECTION AND ANALYSIS We screened all titles generated by the electronic database searches and abstracts of all potentially relevant studies were reviewed. Full papers were assessed for eligibility and data extracted by two independent assessors. For quality assessment (risk of bias and applicability) we used the QUADAS 2 tool. We included test accuracy data on the IQCODE used at predefined diagnostic thresholds. Where data allowed, we performed meta-analyses to calculate summary values of sensitivity and specificity with corresponding 95% confidence intervals (CIs). We pre-specified analyses to describe the effect of IQCODE format (traditional or short form) and language of administration for the IQCODE. MAIN RESULTS From 16,144 citations, 71 papers described IQCODE test accuracy. We included 10 papers (11 independent datasets) representing data from 2644 individuals (n = 379 (14%) with dementia). Using IQCODE cut-offs commonly employed in clinical practice (3.3, 3.4, 3.5, 3.6) the sensitivity and specificity of IQCODE for diagnosis of dementia across the studies were generally above 75%.Taking an IQCODE threshold of 3.3 (or closest available) the sensitivity was 0.80 (95% CI 0.75 to 0.85); specificity was 0.84 (95% CI 0.78 to 0.90); positive likelihood ratio was 5.2 (95% CI 3.7 to 7.5) and the negative likelihood ratio was 0.23 (95% CI 0.19 to 0.29).Comparative analysis suggested no significant difference in the test accuracy of the 16 and 26-item IQCODE tests and no significant difference in test accuracy by language of administration. There was little difference in sensitivity across our predefined diagnostic cut-points.There was substantial heterogeneity in the included studies. Sensitivity analyses removing potentially unrepresentative populations in these studies made little difference to the pooled data estimates.The majority of included papers had potential for bias, particularly around participant selection and sampling. The quality of reporting was suboptimal particularly regarding timing of assessments and descriptors of reproducibility and inter-observer variability. AUTHORS' CONCLUSIONS Published data suggest that if using the IQCODE for community dwelling older adults, the 16 item IQCODE may be preferable to the traditional scale due to lesser test burden and no obvious difference in accuracy. Although IQCODE test accuracy is in a range that many would consider 'reasonable', in the context of community or population settings the use of the IQCODE alone would result in substantial misdiagnosis and false reassurance. Across the included studies there were issues with heterogeneity, several potential biases and suboptimal reporting quality.
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Affiliation(s)
- Terry J Quinn
- Cardiovascular and Medical Sciences, University of Glasgow, Walton Building, Glasgow Royal Infirmary, Glasgow, UK, G4 0SF
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Umayal S, Kulathunga M, Somaratne S, Srikanth S, Kathriarachchi S, De Silva R. Validation of a functional screening instrument for dementia in an elderly sri lankan population: comparison of modified bristol and blessed activities of daily living scales. BMC Res Notes 2010; 3:268. [PMID: 20974013 PMCID: PMC2987868 DOI: 10.1186/1756-0500-3-268] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/12/2010] [Accepted: 10/26/2010] [Indexed: 11/30/2022] Open
Abstract
Background Cognitive tests have been used in population surveys as first stage screens for dementia but are biased by education. However functional ability scales are less biased by education than the cognitive scale and thus can be used in screening for dementia. Objective To validate Activities of Daily Living (ADL) scale appropriate for use in assessing the presence of dementia in an elderly population living in care homes in Sri Lanka. Method Sinhalese version of the modified Bristol and Blessed scale was administered to subjects aged 55 years and above residing in 14 randomly selected elders' homes. Receiver Operating Characteristic (ROC) was used to determine the cut-off scores of both the scales. Results Based on the ROC analysis, optimal cut off score of the modified Bristol scale was 20 with a sensitivity of 100%, specificity of 74.2% and the area under the curve 0.933(95% CI: 0.871-0.995) while the optimal cut off score of the modified Blessed scale was 10.5 with a sensitivity of 100%, specificity of 71% and the area under the curve 0.892 (95% CI: 0.816-0.967). Conclusion The findings confirm that both the scales can be used in screening for dementia in the elderly living in care homes in Sri Lanka.
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Affiliation(s)
- S Umayal
- Dept of Anatomy, Faculty of Medical Sciences, University of Sri Jayewardenepura, Nugegoda, Sri Lanka.
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Abstract
All the articles published in the Indian Journal of Psychiatry (IJP) from 1958 to 2009 on aging, dementia and other mental health issues of late life were systematically reviewed. There were only a limited number of research articles on dementia in the IJP. Most of the Indian studies on dementia were published elsewhere. People above the age of 60 years constitute about 5% of patients seen in tertiary care settings. High prevalence of psychiatric morbidity was reported among community resident older people. Depression was the commonest mental health problem in late life. We need to develop community-based interventions for management of common conditions like depression in late life. The effectiveness of these interventions needs to be established. It is important to identify risk factors for depression and dementia in our population. We could then try and modify these factors to reduce the prevalence of these conditions.
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Affiliation(s)
- K. S. Shaji
- Department of Psychiatry, Medical College, Thrissur - 680 596, Kerala, India
| | - V. P. Jithu
- Department of Psychiatry, Medical College, Thrissur - 680 596, Kerala, India
| | - K. S. Jyothi
- Department of Psychiatry, Medical College, Thrissur - 680 596, Kerala, India
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