Search

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., (Copyright © 2021 The Cochrane Collaboration. Published by John Wiley & Sons, Ltd.)

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., (Copyright © 2021 The Cochrane Collaboration. Published by John Wiley & Sons, Ltd.)

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., (Copyright © 2021 The Cochrane Collaboration. Published by John Wiley & Sons, Ltd.)

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., (Copyright © 2021 The Cochrane Collaboration. Published by John Wiley & Sons, Ltd.)

Background: Dementia assessment often involves initial screening, using a brief tool, followed by more detailed assessment where required. The AD-8 is a short questionnaire, completed by a suitable 'informant' who knows the person well. AD-8 is designed to assess change in functional performance secondary to cognitive change., Objectives: To determine the diagnostic accuracy of the informant-based AD-8 questionnaire, in detection of all-cause (undifferentiated) dementia in adults. Where data were available, we described the following: the diagnostic accuracy of the AD-8 at various predefined threshold scores; the diagnostic accuracy of the AD-8 for each healthcare setting and the effects of heterogeneity on the reported diagnostic accuracy of the AD-8., Search Methods: We searched the following sources on 27 May 2014, with an update to 7 June 2018: 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 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 the AD-8 to try to find additional studies. We developed a sensitive search strategy and used standardised database subject headings as appropriate. Foreign language publications were translated., Selection Criteria: We selected those studies which included the AD-8 to assess for the presence of dementia and where dementia diagnosis was confirmed with clinical assessment. We only included those studies where the AD-8 was used as an informant assessment. We made no exclusions in relation to healthcare setting, language of AD-8 or the AD-8 score used to define a 'test positive' case., Data Collection and Analysis: We screened all titles generated by electronic database searches, and reviewed abstracts of potentially relevant studies. Two independent assessors checked full papers for eligibility and extracted data. We extracted data into two-by-two tables to allow calculation of accuracy metrics for individual studies. We then created summary estimates of sensitivity, specificity and likelihood ratios using the bivariate approach and plotting results in receiver operating characteristic (ROC) space. We determined quality assessment (risk of bias and applicability) using the QUADAS-2 tool., Main Results: From 36 papers describing AD-8 test accuracy, we included 10 papers. We utilised data from nine papers with 4045 individuals, 1107 of whom (27%) had a clinical diagnosis of dementia. Pooled analysis of seven studies, using an AD-8 informant cut-off score of two, indicated that sensitivity was 0.92 (95% confidence interval (CI) 0.86 to 0.96); specificity was 0.64 (95% CI 0.39 to 0.82); the positive likelihood ratio was 2.53 (95% CI 1.38 to 4.64); and the negative likelihood ratio was 0.12 (95% CI 0.07 to 0.21). Pooled analysis of five studies, using an AD-8 informant cut-off score of three, indicated that sensitivity was 0.91 (95% CI 0.80 to 0.96); specificity was 0.76 (95% CI 0.57 to 0.89); the positive likelihood ratio was 3.86 (95% CI 2.03 to 7.34); and the negative likelihood ratio was 0.12 (95% CI 0.06 to 0.24).Four studies were conducted in community settings; four were in secondary care (one in the acute hospital); and one study was in primary care. The AD-8 has a higher relative sensitivity (1.11, 95% CI 1.02 to 1.21), but lower relative specificity (0.51, 95% CI 0.23 to 1.09) in secondary care compared to community care settings.There was heterogeneity across the included studies. Dementia prevalence rate varied from 12% to 90% of included participants. The tool was also used in various different languages. Among all the included studies there was evidence of risk of bias. Issues included the selection of participants, conduct of index test, and flow of assessment procedures., Authors' Conclusions: The high sensitivity of the AD-8 suggests it can be used to identify adults who may benefit from further specialist assessment and diagnosis, but is not a diagnostic test in itself. This pattern of high sensitivity and lower specificity is often suited to a screening test. Test accuracy varies by setting, however data in primary care and acute hospital settings are limited. This review identified significant heterogeneity and risk of bias, which may affect the validity of its summary findings.

Background: Changing population demographics have led to an increasing number of functionally dependent older people who require care and medical treatment. In many countries, government policy aims to shift resources into the community from institutional care settings with the expectation that this will reduce costs and improve the quality of care compared., Objectives: To assess the effects of long-term home or foster home care versus institutional care for functionally dependent older people., Search Methods: We searched the Cochrane Central Register of Controlled Trials (CENTRAL) via the Cochrane Library, MEDLINE, Embase, CINAHL, and two trials registers to November 2015., Selection Criteria: We included randomised and non-randomised trials, controlled before-after studies and interrupted time series studies complying with the EPOC study design criteria and comparing the effects of long-term home care versus institutional care for functionally dependent older people., Data Collection and Analysis: Two reviewers independently extracted data and assessed the risk of bias of each included study. We reported the results narratively, as the substantial heterogeneity across studies meant that meta-analysis was not appropriate., Main Results: We included 10 studies involving 16,377 participants, all of which were conducted in high income countries. Included studies compared community-based care with institutional care (care homes). The sample size ranged from 98 to 11,803 (median N = 204). There was substantial heterogeneity in the healthcare context, interventions studied, and outcomes assessed. One study was a randomised trial (N = 112); other included studies used designs that had potential for bias, particularly due lack of randomisation, baseline imbalances, and non-blinded outcome assessment. Most studies did not select (or exclude) participants for any specific disease state, with the exception of one study that only included patients if they had a stroke. All studies had methodological limitations, so readers should interpret results with caution.It is uncertain whether long-term home care compared to nursing home care decreases mortality risk (2 studies, N = 314, very-low certainty evidence). Estimates ranged from a nearly three-fold increased risk of mortality in the homecare group (risk ratio (RR) 2.89, 95% confidence interval (CI) 1.57 to 5.32) to a 62% relative reduction (RR 0.38, 95% CI 0.17 to 0.61). We did not pool data due to the high degree of heterogeneity (I 2 = 94%).It is uncertain whether the intervention has a beneficial effect on physical function, as the certainty of evidence is very low (5 studies, N = 1295). Two studies reported that participants who received long-term home care had improved activities of daily living compared to those in a nursing home, whereas a third study reported that all participants performed equally on physical function.It is uncertain whether long-term home care improves happiness compared to nursing home care (RR 1.97, 95% CI 1.27 to 3.04) or general satisfaction because the certainty of evidence was very low (2 studies, N = 114).The extent to which long-term home care was associated to more or fewer adverse health outcomes than nursing home care was not reported.It is uncertain whether long-term home care compared to nursing home care decreases the risk of hospital admission (very low-certainty evidence, N = 14,853). RR estimates ranged from 2.75 (95% CI 2.59 to 2.92), showing an increased risk for those receiving care at home, to 0.82 (95% CI 0.72 to 0.93), showing a slightly reduced risk for the same group. We did not pool data due to the high degree of heterogeneity (I 2 = 99%)., Authors' Conclusions: There are insufficient high-quality published data to support any particular model of care for functionally dependent older people. Community-based care was not consistently beneficial across all the included studies; there were some data suggesting that community-based care may be associated with improved quality of life and physical function compared to institutional care. However, community alternatives to institutional care may be associated with increased risk of hospitalisation. Future studies should assess healthcare utilisation, perform economic analysis, and consider caregiver burden.

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.

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.

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.

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.

Background: A substantial component of care is provided to stroke survivors by informal caregivers. However, providing such care is often a new and challenging experience and has been linked to a number of adverse outcomes. A range of interventions targeted towards stroke survivors and their family or other informal caregivers have been tested in randomised controlled trials (RCTs). , Objectives: To evaluate the effect of interventions targeted towards informal caregivers of stroke survivors or targeted towards informal caregivers and the care recipient (the stroke survivor)., Search Strategy: We searched the Cochrane Stroke Group Trials Register (March 2011), CENTRAL (The Cochrane Library Issue 2010, Issue 4), MEDLINE (1950 to August 2010), EMBASE (1980 to December 2010), CINAHL (1982 to August 2010), AMED (1985 to August 2010), PsycINFO (1967 to August 2010) and 11 additional databases. In an effort to identify further published, unpublished and ongoing studies, we searched conference proceedings and trials registers, scanned reference lists of relevant articles and contacted authors and researchers. There were no language restrictions., Selection Criteria: We included RCTs if they evaluated the effect of non-pharmacological interventions (compared with no care or routine care) on informal caregivers of stroke survivors. We included trials of interventions delivered to stroke survivors and informal caregivers only if the stroke survivor and informal caregiver were randomised as a dyad. We excluded studies which included stroke survivors and caregivers if the stroke survivors were the primary target of the intervention., Data Collection and Analysis: Two review authors selected studies for inclusion, independently extracted data and assessed methodological quality. We sought original data from trialists. We categorised interventions into three groups: support and information, teaching procedural knowledge/vocational training type interventions, and psycho-educational type interventions. The primary outcome was caregivers' stress or strain. We resolved disagreements by consensus., Main Results: Eight studies, including a total of 1007 participants, met our inclusion criteria. We did not pool the results of all the studies because of substantial methodological, statistical and clinical heterogeneity. For caregivers' stress or strain we found no significant results within categories of intervention, with the exception of one single-centre study examining the effects of a 'vocational training' type intervention which found a mean difference between the intervention and comparator group at the end of scheduled follow-up of -8.67 (95% confidence interval -11.30 to -6.04, P < 0.001) in favour of the 'teaching procedural knowledge' type intervention group., Authors' Conclusions: It was not possible to carry out a meta-analysis of the evidence from RCTs because of methodological, clinical and statistical heterogeneity. One limitation across all studies was the lack of a description of important characteristics that define the informal caregiver population. However, 'vocational educational' type interventions delivered to caregivers prior to the stroke survivor's discharge from hospital appear to be the most promising intervention. However, this is based on the results from one, small, single-centre study.