Effect of the treatment of Type II diabetes mellitus on the development of cognitive impairment and dementia (Review)

Transcription

1 Effect of the treatment of Type II diabetes mellitus on the development of cognitive impairment and dementia (Review) Grimley Evans J, Areosa Sastre A This is a reprint of a Cochrane review, prepared and maintained by The Cochrane Collaboration and published in The Cochrane Library 2009, Issue 1

2 T A B L E O F C O N T E N T S HEADER ABSTRACT PLAIN LANGUAGE SUMMARY BACKGROUND OBJECTIVES METHODS RESULTS DISCUSSION AUTHORS CONCLUSIONS ACKNOWLEDGEMENTS REFERENCES CHARACTERISTICS OF STUDIES DATA AND ANALYSES WHAT S NEW HISTORY CONTRIBUTIONS OF AUTHORS DECLARATIONS OF INTEREST INDEX TERMS i

3 [Intervention Review] Effect of the treatment of Type II diabetes mellitus on the development of cognitive impairment and dementia John Grimley Evans 2, Almudena Areosa Sastre 1 1 Madrid, Spain. 2 Division of Clinical Geratology, Nuffield Department of Clinical Medicine, University of Oxford, Oxford, UK Contact address: Almudena Areosa Sastre, Madrid, Spain. Editorial group: Cochrane Dementia and Cognitive Improvement Group. Publication status and date: Edited (no change to conclusions), published in Issue 1, Review content assessed as up-to-date: 3 August Citation: Grimley Evans J, Areosa Sastre A. Effect of the treatment of Type II diabetes mellitus on the development of cognitive impairment and dementia. Cochrane Database of Systematic Reviews 2003, Issue 1. Art. No.: CD DOI: / CD Background A B S T R A C T There is increasing interest in preventing cognitive impairment and dementia in later life. Epidemiological evidence shows a relationship between cognitive impairment and Type II diabetes. This association is stronger in patients who have been diagnosed for longer periods of time and in those who are on insulin therapy. There is little information on the short- and long-term influence of type of treatment and level of metabolic control on cognitive function of people with diabetes. Objectives To assess the effects of different types and intensities of treatments for Type II diabetes on cognitive function. Search methods The CENTRAL Register of Controlled Trials, MEDLINE, EMBASE, PsycINFO, SIGLE LILACS and CINAHL as well as a number of ongoing trials databases were last searched on 4 August 2005 using appropriate strategies. Selection criteria Randomized controlled trials in which different treatments for Type II diabetes have been compared and in which measures of cognitive function were made at entry and after the treatment. Data collection and analysis Two reviewers independently assessed trial quality. Five trials were identified for possible inclusion but none of them could be included. In one, cognitive function was assessed before and after intensive or conventional diabetic treatment, but the comparison was not double-blind. The three other studies explored the effect of different treatments on QOL but did not include appropriate evaluation of cognitive function. The fifth did not report baseline data on cognitive function in the trial groups. Main results No studies were found to be appropriate for inclusion in meta-analysis. 1

4 Authors conclusions There is no convincing evidence relating type or intensity of diabetic treatment to the prevention or management of cognitive impairment in Type II diabetes. Future research on treatments for diabetes should include standardized assessments of cognitive function as outcome measures. P L A I N L A N G U A G E S U M M A R Y No evidence that treatment or level of control of Type II diabetes influences cognitive function Type II diabetes is a chronic disease characterized by high blood glucose levels. It needs to be treated with diet, oral drugs and sometimes insulin to control symptoms and avoid organ damage. Patients may develop features of cognitive decline (e.g. memory problems) earlier than healthy people. This review tries to clarify whether the type of treatment or control of the glycemia influences cognitive function. None of the studies identified had sufficient high quality data to justify any conclusion. Future trials of treatment for Type II diabetes should include measures of cognitive function as an outcome. B A C K G R O U N D People with diabetes mellitus have abnormally high blood levels of glucose. This may be associated with the symptoms and signs of excessive thirst, increased urine production, and weight loss. Over time, particular types of damage to body organs and tissues may ensue, including arterial disease - such as heart attack, stroke and gangrene of the legs - renal failure, and impairment of vision due to damage to blood vessels in the eyes. Type I diabetes typically has onset in childhood or early adult life and is characterized by a need for treatment with insulin. Type II diabetes has a different cause; it appears in adult life, and can often be treated by drugs other than insulin, particularly the so-called oral hypoglycaemic drugs. Impaired glucose tolerance is a condition in which blood glucose rises abnormally high after a meal but later returns to normal. This condition may be an early stage in the development of diabetes. Cognition is a collective term for a range of higher brain functions, including memory, perception, language, and reasoning. Some degree of impairment of one or more cognitive functions (particularly memory) is common, though not universal, in later life. For a minority of older people impairment becomes severe, progressive, and disabling and is described as dementia. The commonest diseases leading to dementia are Alzheimer s disease, a degenerative condition of brain cells of unknown cause, and cerebrovascular disease in which brain cells are starved of blood and oxygen due to narrowing of the blood vessels serving the brain. Dementia is a tragedy for affected individuals and their families, and challenging and costly to health and social services. Measurement of cognitive function requires validated and reliable tests covering the range of different domains of interest including memory, reasoning and language. Tests for acquired impairment need to take into account previous intelligence and education. This may be assessed by a patient s educational and occupational history, but can also be estimated by verbal skills such as vocabulary since these are more resistant than some other aspects of cognitive function to the effects of brain damage. Some forms of cognitive impairment, associated for example with temporary metabolic derangement, are reversible, but there is as yet no curative treatment for established dementia. There is therefore interest in possibilities for prevention by identifying and modifying risk factors (Fillit 2002). Although it has been suspected from the early 1970s that there is a risk of impairment of cognitive function associated with Type II diabetes mellitus (Bale 1973), it is only more recently that interest has increased in research on possible mechanisms of this association. It is not easy to study the relationship because diabetes is frequently associated with other vascular risks factors such as hypertension and dyslipidemia, and with comorbidity such as cerebrovascular or cardiovascular disease (Khanel 1979) that can contribute to cognitive impairment (Prince 1996; Stewart 1998; Kilander 1998; Rockwood 2002). The relationship may be spurious; in particular depression can be mistaken for dementia. It has been reported that depression occurs more frequently in people with diabetes, particularly in those with complications (Anderson 2001), and depression can be one of the most difficult disorders to differentiate clinically from dementia (Swainson 2001). Depression is often associated with deficits in episodic memory and learning, similar to those 2

5 occurring in the mild stages of dementia due to Alzheimer s disease (Austin 1997; Reding 1985; Visser 2000). A further complication is that depressive features may be among the early manifestations of dementia (Ganguli 1999; Berger 1999). In addition to reversible impairment of cognitive function due to short-term metabolic disturbance, there are several possible mechanisms that might underlie an association between diabetes and irreversible cognitive impairment. In Type I (insulin-dependent) diabetes there has been concern about possible deleterious effects on cognitive function of repeated hypoglycaemic episodes that may occur when tight control of blood sugar levels is attempted (Diabetes 1998; Hung 1984; Prescott 1990; Langan 1991; Lincoln 1996; Reichard 1996). This possibility has not been studied in people with Type II diabetes, although hypoglycaemia can occur with some types of oral antidiabetic drugs, and some people with Type II diabetes are treated with insulin. The frequency of hypoglycaemia may be underestimated in older people because the symptoms may be less distinctive in later life (Thomson 1991). The effect of acute hyperglycemia on cognitive function has also been studied. During acute hyperglycemia, cognitive function was impaired and mood state deteriorated in a group of people with Type II diabetes (Sommerfield 2004). A gene that produces a particular lipid-carrying protein the blood (apoliprotein e4 - APOE-e4) is known to increase the risk of brain damage from a range of causes and may be relevant to the effect of diabetes on cognitive function (Haan 1999). Another possible link between diabetes and cognitive impairment would be through brain ischaemia due to cerebrovascular disease, a well-established complication of diabetes (Folsom 1999). Cerebrovascular disease is the commonest cause of the clinical syndromes of vascular and mixed dementia, but might also, it has been postulated, trigger a cascade of events that leads to Alzheimer s disease (De la Torre 2000; Kalaria 2000; Shi 2000). This raises another possible aetiopathogenic mechanism to link diabetes and dementia (Katzman 1989; Mortel 1993; Brayne 1998). Consideration of this possibility was delayed perhaps by the diagnostic criteria used for research in Alzheimer s disease that exclude risk of cerebrovascular disease (McKhann 1994). It is now recognised that mixed forms involving both pathologies are common (Kalaria 1999). The relationship between diabetes and dementia after stroke is well recognised (Lindsay 1997; Pohjasvaara 1998; Ross 1999; Tatemichi 1993), but the suggestion that diabetes might have a pathogenic role in nonvascular dementia (Launer 1999; Shalat 1987; Van Duijn 1992) has received less attention. Other mechanisms have been suggested in which insulin might play an important role (Freychet 2000; Park 2001). Insulin receptors are widely distributed in the brain, especially in neurons of areas related to memory and learning such as the hippocampus and parts of the cerebral cortex (Wickelgren 1998). It is possible that insulin may play a part in glucose utilization in these areas. It has been found that an intraventricular injection of streptozotocin, which damages insulin receptors, impairs the ability of an experimental animal to remember an electric shock (Launer 1999). The giving of glucose produced a temporary improvement in the memory of people with Alzheimer s disease, and this effect was later demonstrated to be attributable to an increase in the release of insulin (Craft 1996; Fujisawa 1991). People with Alzheimer s disease have significantly increased blood insulin levels (Carantoni 2000; Kuusisto 1993; Razay 1994; Stolk 1997) and there is an inverse relationship between the ratio of blood to cerebrospinal fluid insulin levels and the severity of the dementia (Craft 1998). One possible interpretation is that insulin function is impaired and there is a compensatory increase in secretion. It has even been proposed that desensitization of the neuronal insulin receptor is a fundamental factor in the aetiopathogenesis of Alzheimer s disease (Henneberg 1995). Insulin resistance represents the earliest biochemical characteristic of Type II diabetes (Meneilly 1999) and may therefore be a predisposing factor for cognitive impairment. Insulin has also been controversially implicated in other beneficial roles in cognitive function, but it is not the purpose of this work to explore them (Boyt 2000; Gasparini 2001; Hong 1997; Lovestone 1999). EPIDEMIOLOGICAL EVIDENCE Cross-sectional studies The epidemiology of the relationship of diabetes or impaired glucose tolerance with cognitive impairment has for many years been restricted to cross-sectional (prevalence) studies, which examine the associations between diseases and risk factors in a population at a single point in time (Assisi 1996; Bent 2000; Cerizza 1990; Cosway 2001; Croxon 1995; Dey 1997; Grodstein 2001; Helkala 1995; Hiltunen 2001; Jagusch 1992; Kalmijn 1995; Lindeman 2001; Mattlar 1985; Mooradian 1988; Motta 1996; Ott 1996; Perlmuter 1987; Reaven 1990; Ryan 2000a; Scott 1998; Soininen 1992; Stewart 1998; Tun 1987; U Ren 1990; Vanhanen 1998; Worral 1993; Zalavsky 1995). These have suggested a link between the disorders, but with some discrepancies because of variable methodology and heterogeneity of the populations studied. Many studies depended on recruiting small samples of volunteer patients from clinics (Drinka 1988; Drinka 1989), with inadequate controls, and using variable inclusion criteria that limited generalization of the results. Many of the reports failed to explore and control for potential confounding factors (Grimes 2002), especially those related to poor cognitive performance that are highly prevalent in later life and also common among people with diabetes. Not all of the studies controlled plasma glucose during testing in order to prevent any effect of hypoglycaemia on cognitive function (Holmes 1983). 3

6 The studies cited have focused on cognitive test performance, rarely with the assessors blind to the participants diabetic status, at a single time point. The issue of greater importance is change in cognitive function over time. Test performance at a single point can be influenced by many factors including education (Farmer 1995; Ott 1995; Kittner 1986; Stern 1999) but there will also be other factors. The majority of authors have controlled for the level of education in their analyses. Others have argued that low education can reflect more a lack of social opportunity than deficient aptitude and have preferred to estimate pre-morbid abilities (Atiea 1995). (In the process of cognitive impairment verbal skills are preserved better than other mental skills, so that tests of verbal ability - such as ability to pronounce and define unusual words - are an indication of original mental abilities even when reasoning abilities or memory have been damaged by disease). More than sixty tests have been used to explore various domains of cognitive function in different settings, and this makes it difficult to compare the results of studies. In broad terms, cross-sectional studies have shown a tendency for lower scores by people with diabetes than by control subjects, mainly in learning and verbal memory. Some studies, however, have not found significant differences between people with diabetes and controls. It is not clear how far variations in findings reflect differences in methods. Longitudinal studies Some longitudinal studies, particularly those designed for the study of cardiovascular risk factors (Elias 1997), have taken the opportunity of a subsequent long period of follow-up to evaluate the cognitive performance of participants at the time of entry. This provides valuable and reliable information of function at the time of the diagnosis and sometimes of the severity of relevant risk factors. This information is useful because cardiovascular risk factors predominantly manifest in middle life (Harris 1998) but it is reasonable to suspect that their effect on cognitive function has begun earlier. Another virtue of longitudinal studies is that they can provide evidence on the quality of risk factor control over the years. People with established dementia have worse diabetic control (Sinclair 2000) partly because of their difficulties in self-care and partly because of having their treatment suspended (Farmer 1990). A report from the Baltimore Longitudinal Study of Aging (Robertson 1986) found no evidence of accelerated cognitive decline in 52 diabetic men compared with 610 controls matched for age and education. The sample was, however, composed of volunteers and not representative of a definable population.the studies of particular relevance are those that are population-based studies avoiding selection bias, and that have longitudinal designs measuring cognitive performance in several assessments over time (Morris 1999). A problem with these studies is determining what constitutes a clinically or functionally important change in cognitive function (Colsher 1991). It could also be useful to address the impact of cognitive impairment on basic, instrumental and advanced daily living activities. In an observational study of 77 patients with diabetes, no significant association was found between cognitive function and HbA1c (Worrall 1996). HbA1C is a compound of the blood red pigment haemoglobin and glucose. It s level reflects the average blood sugar level over a period of time and is therefore a widely used index of the quality of diabetes control In an historical study of medical records of people resident in Rochester, Minnesota, USA from 1970 to 1985 (Leibson 1997), it was found that people with a diagnosis of adult onset diabetes experienced a significantly higher risk of developing dementia than did the rest of the population (RR=1.66, 95% CI for men and 1.37, CI for women). Elias 1997 administered a neuropsychological test battery to the Framingham cohort who had been followed for years. They concluded that Type II diabetes and higher blood pressure were associated independently with increased risk of poor cognitive performance in neuropsychological tests measuring immediate and delayed memory for prose. The duration of diabetes was predictive of poor performance in complex verbal memory tasks, abstract reasoning and concept formation. Insulin treated patients were at higher risk of poor performance compared with a nondiabetic referent group for three of the neuropsychological test involving verbal and visual memory. However the number of people with diabetes on insulin was low. The Rotterdam Study (Ott 1999) is a community-based prospective study in which 7,046 participants at risk for dementia were followed up for a period of up to 6 years (average 2.2 years) and changes in their cognitive function were monitored. Although 18% of the participants were not re-screened in person, information about their cognitive status was obtained from general practitioners and medical records. The conclusion of the study was that Type II diabetes doubled the risk of dementia (RR: % CI: ). Unfortunately the duration of the diabetes was not examined. They detected that the risk of dementia was modified by baseline treatment with the lowest risk in untreated patients (RR: 1,3, 95% CI 0,7 to 2,3) and the highest among patients treated with insulin (RR 4,3, 95% CI 1,7 to 10,5). This higher risk for the insulin treated patients might be interpreted like a mark of the length or severity of the disease. Patients on insulin may have more severe diabetes or a longer history and thus, have been exposed to the risk factor for a greater time. In addition patients on oral medication have an intermediate risk between those receiving insulin and those patients controlled by diet alone. However we cannot exclude other possible explanations as the higher rate of hypoglycaemic events with this treatment. The Epidemiology of Vascular Aging Study (Fontbonne 2001), involved a community-dwelling volunteer cohort of 926 people aged between years at baseline. Cardiovascular risk factors were measured and changes in cognitive function assessed over four years. A broad battery of tests was employed under blinded 4

7 conditions to explore various areas of cognitive function at three time points. The results indicated a more than twofold enhanced probability of serious worsening in people with diabetes in tests assessing immediate verbal memory, attention and psychomotor speed. The Study of Osteoporotic Fractures (Gregg 2000) assessed the cognitive function of 9,679 community-dwelling women aged years. This study employed used the Mini-Mental State Evaluation (MMSE) (Folstein 1972), a general cognitive function test widely employed as a screening test, at baseline and over the subsequent 3 and 6 years. In the last two visits, other tests were used to explore attention, psychomotor performance and visual scanning. It was found that women with self-reported diabetes had a twofold increase in risk of major cognitive decline, as defined by the greatest 10th percentile reduction in performance from initial to followup. As in the Framingham study, an association was found between the length of the time since diabetes had been diagnosed and the probability of developing cognitive impairment, this relationship being particularly strong in participants who had had diabetes for 15 years or longer. This study observed that women reporting insulin use had an appreciably higher risk of major cognitive decline as well. The results of the study have the limitation that they are based on self-reported diagnosis of diabetes. This is relevant in that approximately one-third of all older people with diabetes remains undiagnosed (Franse 2001) and untreated, and are at least at the same risk from the morbidity and mortality associated with the disease (Harris 1993). Another consideration is that the tests used in the study did not adequately explore memory tasks, which show the earliest changes detectable in the majority of people with mild cognitive decline (Small 1999; Hogan 2001; Petersen 2001). The nurses health study (Logroscino 2004) examined the association of type II diabetes with baseline cognitive function and cognitive decline over two years of follow up. After multivariate adjustment, women with self-reported diabetes mellitus performed worse on all cognitive tests than women without diabetes at baseline. Odds of poor cognition were particularly high for women who had had diabetes for a long time as well (1.52, 1.15 to 1.99, and 1.49, 1.11 to 2.00, respectively, for diabetes for 15 years or longer) In the Atherosclerosis Risk in Communities (ARIC) Study (Knopman 2001) cognitive assessments were administered to 10,963 middle-aged individuals on two occasions separated by 6 years. This study observed small performance decrements associated with hypertension and diabetes in tests measuring sustained attention, psychomotor speed and logical reasoning in a young age group. These results suggest that alterations in cognitive function begin earlier than is generally recognised, although the expression of their effects is more marked in later life (Ryan 2000a). The Honolulu Asia Heart Study investigated the relationship of being diabetic (Curb 1999), or having a group of clustered metabolic cardiovascular risk factors (Kalmijn 2000) measured at middle age, with the development of dementia in old age. In both studies an increase of vascular dementia was found, but no connection with AD. However the study was cross-sectional in design. At the time of neurological diagnosis the patients were old and the lower rate of survival in diabetics could have biased the findings. The Fremantle Study (Bruce 2001) determined whether vascular or diabetes-related risk factors predicted the development of dementia three years later in a small sample of people with type II diabetes. The results suggested that the association between diabetes and dementia might be better explained by the increased incidence of hypertension in this population. The Hisayama Study (Yohitake 1995) followed up 887 subjects for seven years with the objective of determining the incidence of dementia risk factors for the condition. The authors concluded that diabetes may have a role only in the development of vascular dementia. However, the lack of specific data about the evolution of the 70 diabetic patients makes interpretation of the results difficult. Luchsinger et al (Luchsinger 2001) published another longitudinal study in which a random sample of 1,799 multiethnic participants was followed up annually for 4 years. Diabetes was found to be related to stroke-associated dementia (hazard ratio 1.6, 95% CI: ) and to a composite outcome of Alzheimer s disease and cognitive deficit without dementia (hazard ratio=1.6, 95% CI: ). They detected a higher risk of stroke-associated dementia (Hazard Ratio 3,9, 95%: 1,29-11,56) and a slightly greater risk of Alzheimer s disease (Hazard Ratio: 1,4, 95% CI: 0,61, 3,24) among patients using insulin than hypoglycaemic agents. Again there is the limitation of self-reported risk factor status leading to possible under-diagnosis, and a high proportion (30%) of participants lost to follow-up. The Canadian Study of Health and Aging (MacKnight 2002) included 5574 participants at risk of cognitive impairment after a 5-year period (62% of the 9131 who were initially selected for following-up). Only 27.6% of the participants underwent diabetes assessment at baseline. This consisted of self-report diagnosis that was confirmed by laboratory testing in 45%. Of the diabetics, 1,5% were on insulin treatment suggesting that the duration or severity of the diabetes was low in this group although these factors were not specifically assessed. The authors concluded that diabetes mellitus was associated with incident vascular cognitive impairment (RR: 1,62; 95% CI: 1,12-2,33) but not with mixed Alzheimer s/vascular dementia (RR: 0,87; 95% CI: 0,34-2,21) or incident Alzheimer s disease (RR: 1,30; 95% CI: 0,0,83-2,03). This study observed that insulin users were more likely to develop vascular cognitive impairment but not Alzheimer s disease. Results from the Religious Orders Study have been recently published (Arvanitakis 2004). For up to 9 years, 824 older Catholic nuns, priests, and brothers underwent annual clinical evaluations. In a proportional hazards model adjusted for age, sex, and educational level, those with self reported Diabetes Mellitus had a 65% increase in the risk of developing AD compared to those without diabetes mellitus (Hazard ratio 1.65; 95% CI ). In random effects models, diabetes mellitus was associated with lower 5

8 levels of global cognition, episodic memory, semantic memory, working memory and visuospatial ability at baseline. There are two complete reviews about this topic. Strachan (Strachan 1997) published in 1997 a critical analysis of the literature, before the majority of the longitudinal studies were finished. Stewart (Stewart 1999) later on in 1999, added more evidence to this link explaining all the possible mechanisms of this association. Cognitive function has not been included as an outcome variable in large scale RCTs (Stratton 2000; UKPDS ; UKPDS ). Nor has the effect of diabetes been taken into account in interventional studies exploring the effect of other vascular risk factors such as hypertension (Forette 1998) on cognitive function. In summary, there is now sufficient evidence to support the view that there is an up to twofold increase in risk of cognitive impairment or dementia in people with diabetes in comparison with the general population, and especially in patients who have been diagnosed for longer periods. There is little information about the influence of the severity or level of control of the disease in this relationship. The negative effect of diabetes on cognitive function probably begins in middle life. The issue is whether treatment for diabetes can affect the risk for cognitive impairment. From a public health point of view, if there is a connection between diabetes and dementia, Type II diabetes will present a greater problem than Type I, both numerically and because of the greater range of possible treatments. Observational studies are subject to possible confounding and the issue can only be settled by appropriate intervention studies comparing different forms of treatment in terms of their impact on the incidence and severity of cognitive impairment and dementia. The primary need therefore is for a review of RCT evidence on the relationship of cognitive impairment and Type II diabetes mellitus with particular regard to: -Type of treatment -Effects of improvement of metabolic control -Effects of treatments improving insulin resistance -Differentiation of vascular dementia and Alzheimer s disease. -Impact of the impairment on daily life activities -Significance of predisposing factors and comorbidity O B J E C T I V E S Primary objective: Determine the influence of diabetes management on cognitive function. Secondary objective: Determine the quality and quantity of available evidence from clinical trials about this topic. M E T H O D S Criteria for considering studies for this review Types of studies Randomized controlled trials in which different treatments for Type II diabetes mellitus have been compared and in which measures of cognitive function of participants have been made at entry and after treatment. Types of participants All patients diagnosed by accepted criteria as having Type II diabetes mellitus. Types of interventions Any form of treatment for Type II diabetes mellitus. Types of outcome measures -Cognitive function measured by neuropsychological tests -Diagnosis of dementia by explicit criteria -Severity and significance of cognitive impairment as reflected in impact on social and behavioural functions -Relevant indices of rigour of diabetic metabolic control including fasting and random blood glucose, HbAic, insulin levels -Where appropriate, indices of effectiveness of prevention of complications of diabetes including diabetic retinopathy and renal disease, incidence of vascular disease (all forms) and total mortality, and mortality form diabetes-related causes. Search methods for identification of studies On 4 August 2005 the following databases were searched: CCTR (Cochrane Library): issue 3/2005 Search strategy: 1 DIABETES-MELLITUS-NON-INSULIN-DEPENDENT*: ME 2 OBESITY-IN-DIABETES*:ME 3 ((NIDDM or II DM) or DM2) 4 ((#1 or #2 or #3) 5 (COGN* or DEMENT* or MEMOR*) 6 (#4 and #5) MEDLINE: /08 week 1 Search strategy: 1 explode Diabetes-Mellitus-Type-2 / all subheadings 2 diabet* near ( 2 or type II ) 3 DM2 or NIDDM or IIDM 4 #1 or #2 or #3 5 cognit* or memor* or QOL or quality of life 6 #4 and #5 7 (randomized-controlled-trial in PT) or (controlled-trial in PT) 6

9 8 Randomized-Controlled-Trials / all subheadings 9 random* and (allocat* or assign*) 10 (doubl* or singl* or trebl* or tripl*) near (blind* or mask*) 11 placebo* 12 Double-Blind-Method in MIME,MJME 13 cross-over or crossover 14 #7 or #8 or #9 or #10 or #11 or #12 or #13 * 15 #6 and #14 EMBASE: /06 Searchstrategy: 1 non-insulin-dependent-diabetes-mellitus / all subheadings 2 diabetic-obesity / all subheadings 3 diabetes mellitus and ( type 2 or type II ) 4 DM2 or NIDDM or IIDM 5 (typ* 2 or typ* II ) near (diabet* or DM) 6 diabetes type 2 or diabetes type II 7 #1 or #2 or #3 or #4 or #5 or #6 8 cogn* or dement* or alzheimer* or memor* or QOL or quality of life 9 #7 and #8 10 explode clinical-trial / all subheadings 11 double-blind-procedure / all subheadings 12 single-blind-procedure / all subheadings 13 alloc* 14 random* and (assign* or alloc*) 15 (singl* or double* or trebl* or tripl*) and (blind* or mask*) 16 #10 or #11 or #12 or #13 or #14 or #15 17 #9 and #16 PsycINFO: /07 week 4 searchstrategy: 1 Diabetes-Mellitus in DE 2 #1 and ( type 2 or type II ) 3 DM2 or NIDDM ir IIDM 4 diabetes mellitus type 2 5 diabetes mellitus type II 6 ( type 2 or type II ) near (diab* or DM) 7 diabetes type 2 or diabetes type II 8 #2 or #3 or #4 or #5 or #6 or #7 9 cogn* or dement* or alzheimer* or QOL or quality of life 10 #8 and #9 11 random* and (alloc* or assign*) 12 (doubl* or singl* or trebl* or tripl*) near (blind* or mask*) 13 randomi?ed 14 controlled trial* 15 placebo* 16 #11 or #12 or #13 or #14 or #15 17 #10 and #16 Cinahl: /07 Searchstrategy: 1 Diabetes-Mellitus-Non-Insulin-Dependent / all topical subheadings / all age subheadings 2 DM2 or NIDDM or IIDM 3 diabetes mellitus type 2 or diabetes mellitus type II 4 diabetes type 2 or diabetes type II 5 ( type 2 or type II ) near (diab* or DM) 6 #1 or #2 or #3 or #4 or #5 7 cogn* or dement* or alzheimer* or memor* or QOL or quality of life 8 #6 and #7 9 random* near (assign* or alloc*) 10 randomi?ed 11(singl* or doubl* or trebl* or tripl*) near (blind* or mask*) 12 placebo* 13 controlled trial 14 #9 or #10 or #11 or #12 or #13 15 #8 and #14 SIGLE: /12: no results ClinicalTrials.gov : USA based databases of ongoing trials: last search 4 August 2005: no results CurrentControlledTrials: UK based databases of ongoing trials: last search 4 August 2005: no results Data collection and analysis SELECTION OF STUDIES Abstracts of the references retrieved by the search were read by one reviewer to discard those that were clearly not eligible for inclusion. The two reviewers studied the full text of the remaining references and independently selected studies for inclusion. Any disparity in the final lists (there was none) were to be resolved by discussion in order to arrive at the final list of included studies. QUALITY ASSESSMENT The reviewers assessed the methodological quality of each trial using the Cochrane Collaboration guidelines (Mulrow 1997). Category A (adequate) is where the report describes allocation of treatment by: (i) some form of centralized randomized scheme, such as having to provide details of an enrolled participant to an office by phone to receive the treatment group allocation; (ii) some form of randomization scheme controlled by a pharmacy; (iii) numbered or coded containers, such as in a pharmaceutical trial in which capsules from identical-looking numbered bottles are administrated sequentially to enrolled participants; (iv) an on-site or coded computer system, given that the allocations were in a locked, unreadable file that could be accessed only after inputting the characteristics of an enrolled participant; or (v) if assignment envelopes were used, the report should at least specify that they were sequentially numbered, sealed, and opaque; (vi) other combinations of described elements of the process that provide assurance of adequate concealment. Category B (intermediate) is where the report 7

10 describes allocation of treatment by: (i) use of a list of table to allocate assignments; (ii) use of envelopes or sealed envelopes ; (iii) stating the study as randomized without further detail. Category C (inadequate) is where the report describes allocation of treatment by: (i) alternation; (ii) reference to case record numbers, dates of birth, day of week, or any other such approach; (iii) any allocation procedure that is entirely transparent before assignment, such as an open list of random numbers or assignments. Empirical research has shown that lack of adequate allocation concealment is associated with bias. Trials with unclear concealment measures have been shown liable to yield more pronounced estimates of treatment effects than trials that have taken adequate measures to conceal allocation schedules, but the effect is less pronounced than in inadequately concealed trials (Chalmers 1983; Schulz 1995). Trials were to be considered if they conformed to categories A or B, but those falling into category C were excluded. Other aspects of trial quality were not assessed by a scoring system although details were noted of blinding, appropriateness of methods and the number of patients lost to follow-up. DATA COLLECTION Data for any meta-analyses were to be based on reported summary statistics for each study. For the intention-to-treat analyses data would be sought for each outcome measure that included every patient randomized, irrespective of compliance. For the analyses of completer data would include every patient who completed the study on treatment. For continuous variables, or ordinal variables which can be approximated to continuous variables, the main outcomes of interest would be the final assessment and the change from baseline at final assessment. For some ordinal and binary outcomes, the endpoint category relative to baseline category would be the outcome of interest. For others, such as the global impression of change, the endpoint itself is of clinical relevance as all patients will, by definition, have been at the same baseline score. The baseline assessment is defined as the latest available assessment prior to randomization, but no longer than two months before. DATA ANALYSIS The analysis strategy implemented for each outcome depends on the type of data (ordinal, continuous, dichotomous) and whether the analysis is based on intention-to-treat or completer. Ordinal scales with many categories, such as psychometric test scores, are treated as continuous data, and ordinal scales with few categories as ordinal data. A vast number of rating scales and tests have been devised to assess cognition in clinical trials. Meta-analyses are fairly straightforward in the situation where the included studies use the same outcome measures and the method of weighted mean difference is used. When different scales are used in the studies the method of standardized mean difference is used where it is considered appropriate to combine the scales. The second approach, which may not exclude the first, is to concatenate the data into two categories which best represent the contrasting states of interest, and to treat the outcome measure as binary. For binary outcomes, the endpoint itself is of interest and the Peto method of the typical odds ratio is used. A test for heterogeneity of treatment effect between the trials is made using a chi-square statistic. If no heterogeneity is indicated then a fixed effect parametric approach can be taken. A separate meta-analysis is performed for each single comparison of two treatments. The age range of patients in the selected studies may differ, in which case meta-analyses have to be considered for different age bands. The duration of disease before entering the study may also be a factor that varies considerably and again separate meta-analyses may have to be undertaken to take this into account. Subgroup and sensitivity analyses will be performed relevant to linking changes in cognitive function to other outcomes of diabetes treatment (including vascular disease) and to pre-existing characteristics including lifestyle (e.g. smoking and exercise) and the presence of comorbidity (such as hypertension). R E S U L T S Description of studies See: Characteristics of included studies; Characteristics of excluded studies. Five studies that met the inclusion criteria for the review were identified. Ginseng is a plant extract claimed to elevate mood and reduce fatigue. It has been reported to improve glucose homoeostasis and increase insulin sensitivity. Sotaniemi 1995 reported a doubleblind randomized parallel-group comparison of ginseng, 100 mg or 200 mg daily, with placebo as additional therapy for 36 newly diagnosed patients with Type II diabetes treated by diet alone. Memory was tested by digit span (maximum number of random digits accurate in immediate recall) and a timed diagram completion test. After 8 weeks the two ginseng groups had better scores in the diagram test but there was no differences in digit span scores between the three groups. The scores at entry were not reported. The two ginseng groups reported better mood. Fasting blood glucose was lower in the ginseng groups and HbA1c was lower in the group taking 200 mg daily of ginseng. Again, entry data were not reported. The authors suggest that the improvement in diabetic control was secondary to elevation of mood and motivation due to ginseng. The improvement in scores in the timed diagram completion test with no change in digit-span is also compatible 8

11 with a change in mood and motivation rather than in cognitive capabilities. Naor 1997 compared the effect of intensive inpatient diabetic therapy with unchanged regular diabetic therapy on cognitive function. In this RCT the investigators assessing outcomes were blind to the treatment group to which each patient had been assigned. At the time of randomization there were 20 patients in each group, all of them treated by diet and oral antidiabetic drugs. The mean age was 64 years and there was a predominance of females. The investigators recorded the years of education of participants, and noted that the duration and severity of diabetes was similar in the two groups. Patients with a history of cerebrovascular events, uncontrolled hypertension, depression or use of drugs affecting central nervous system function were excluded. The intensive treatment regimen comprised an individually adapted diet, daily monitoring of blood glucose, a standardized educational programme, and such changes in the treatment as were needed to achieve fasting blood glucose levels below 130 mg/dl and postprandial blood glucose levels below 180 mg/dl during a two-week period in hospital. The patients were encouraged to follow the same diet and treatment at home for six weeks after discharge. No change in established treatments was made for patients assigned to the regular therapy group. Cognitive function was assessed on three occasions in each group: on admission, at discharge, and six weeks after leaving the hospital. Measurements included reaction time to visual and auditory stimuli, cognitive flexibility, psychomotor speed and concentration using a range of validated tests. These comprised a simple reaction time test, the Zahlen-Verbidungs test (a German version of the Trail Making Test-A), and two letter-cancelling tests - Test d2 and the Bourdon-Freyberg-concentration test. Blood glucose concentrations were measured before testing to exclude possible effects of hypoglycaemia. Test results at baseline were similar in the two groups. At six weeks the mean scores of the intensive treatment group in the letter-cancelling tests were significantly better statistically than those of the regular therapy group. Performance in the Zahlen-Verbidungs test, but not in the reaction time tests, was significantly and inversely related to HbA1c levels. Three trials studied the effect of different diabetic treatment on Quality of Life (QOL) using questionnaires that included the respondents subjective impressions of cognitive function. Testa 1998 compared the QOL of a heterogeneous group of people with Type II diabetes assigned to glipizide or placebo in a randomized, double-blind parallel trial. Five hundred and ninety-four patients of a wide range of age (mean: 58 years) and variable diabetes duration were randomized; 202 were assigned to diet and placebo, and 393 patients to diet and glipizide. The investigators explored possible confounding factors such as education, occupation, other vascular risks like hypertension or dyslipidemia, and perceived mental and emotional health were included in the questionnaires. Self-reported cognitive function was assessed with a Visual Analogue Scale at screening, randomization, and at 4,8,12 weeks after randomization. At 15 weeks there was a statistically significant improvement in self-assessed cognitive function in the glipizide group but a non-significant decline in mean score in the placebo group. Tovi 1998 compared quality of life assessments by Type II diabetic patients with suspected secondary failure on oral antidiabetic drug therapy. In parallel group open trial, 40 participants were randomly divided into two groups, 22 to receive insulin and 18 to continue on the previous treatment. Cognitive function at entry to the study was assessed with the Mini-Mental State Examination (MMSE) to ensure comparability of the groups. Quality of life was evaluated at baseline, and again at 6 and 12 months using the Goteborg Quality of Life instrument that includes an item of perceived memory on a self-report scale graded from 1 to 7. No data are reported on the effect of different treatments in this specific area. UKPDS compared the effects on QOL of two regimens for improving blood glucose and blood pressure control in with a randomized, parallel and open trial. Randomization was performed by centrally produced, computer-generated therapy allocations. A total of 374 patients were included; 105 were assigned to conventional treatment and 269 to an intensive treatment regimen (UKPDS ). Patients were 52 years old on average at entry and predominantly male. The effect of education was not taken into account in the assessment of memory changes. Blood pressure and BMI were measured. Questionnaires, administered at 6 months, and 1,2,3,4,5, and 6 years after randomization included self-report of cognitive mistakes using the Cognitive Failures Questionnaire (Broadbent 1982). No significant differences in responses to the Questionnaire emerged over a 6-year period between patients allocated to conventional or to intensive diabetes therapy. Grandman (Gradman 1993) in a non-randomized control trial studied cognitive function changes after one month of treatment for improving glycemic control in type II diabetes. They recruited healthy people as controls. We cannot include this study for these reasons. Meneilly (Meneilly 1993) designed a similar study. Sixteen type II diabetes patients were tested with a neuropsychological battery before and after improving diabetes control. This study could not be included because of the lack of a control group. Update 2005: No new studies were found which were suitable for inclusion in this review. Risk of bias in included studies Sotaniemi 1995 did not describe the method of randomization, and reported mean results after 8 weeks rather than mean changes in cognitive function scores. The comparability of the three groups with regard to cognitive function at entry is unattested. Naor 1997 did not specify the method of randomization. The follow up was complete in eighteen (90%) of the intensive therapy group and fifteen (75%) of the regular therapy group. The investigator assessing outcomes was blind to the assignment of the patients but all the patients recruited gave informed consent so were 9

12 necessarily aware of their assignment status and of the alternative form of care being assessed. This may have introduced bias. The three studies that explored the effect of different types of treatment on quality of life have some characteristics in common. All were randomized controlled trials with low drop-out rates. In the UKPDS Testa 1998 and Sotaniemi 1995 were the only doubleblind trials. Testa 1998 used a visual analogue scale, and Tovi 1998 a graded scale from 1 very bad to 7 excellent to quantify how patients perceived their memory. None of these tests is validated as an adequate measure of cognitive function. Self-reported memory may not be related, or is only weakly related, to cognitive function (Schmidt 2001). Metamemory, knowledge about the limitations and characteristics of one s own memory, was traditionally thought to be unaffected by age, but is now known to be affected by ageassociated decrements (Rabbitt 1991) and may reflect changes in confidence or attitude rather than in cognitive ability. Some patients with Alzheimer s disease report normal memory (Feher 1994). Reliable screening for dementia requires objective cognitive tests (Ganguli 1997) accompanied by informant questionnaires (Jorm 1997). A similar problem affects the interpretation of UKPDS This study compared long-term effects on quality of life of therapies for improving blood glucose and blood pressure, diabetic complications and hypoglycaemic episodes. The tests used included the Cognitive Failures Questionnaire (CFQ) (Broadbent 1982), for which the patient and a relative have to report the frequency in which minor cognitive mistakes occur. The CFQ was devised initially for measuring perceptual memory and action failure; later, the authors suggested that it could be a promising measure for showing individual vulnerability to stress (Broadbent 1982). The ability of the CFQ to detect memory difficulties has been controversial, at least in studies of students (Matthews 1990; Pollina 1992), and it has been demonstrated to have limitations in the study of cognitive ageing (Matthews 1990). At present the CFQ is not considered a reliable test for measuring cognitive function (Wagle 1999). Effects of interventions No studies were found to be appropriate for inclusion in metaanalysis. D I S C U S S I O N The epidemiological evidence, both cross-sectional and longitudinal provides compelling evidence that diabetes mellitus is associated with an increased risk of cognitive impairment and dementia. A number of factors could contribute to this relationship. These include disturbance to the metabolism of neurons consequent on hyperglycaemia or non-optimal insulin levels, and impaired blood supply to the central nervous system. The latter might be due to the atherosclerosis of arteries associated with diabetes causing regional hypoperfusion or stroke, or more diffuse brain ischaemia due to obstruction of blood supply at the arteriolar level, sometimes referred to as small vessel disease. There is also the possibility that cognitive impairment might be in part an adverse effect of one or more forms of treatment, perhaps some direct metabolic effect of a drug of the cumulative impact of recurrent episodes of hypoglycaemia. But depression can impair cognitive function and people with diabetes may be more likely than coevals to he depressed. This may arise partly by the knowledge of having the condition, by the some of its symptoms, the cost of drug treatment and the impact on lifestyle of dietary and exercise prescriptions, both for the diabetes and significant exacerbating factors such as smoking and high blood pressure. Moreover, as pointed out by Sotaniemi 1995, the onset of Type II disease is often in middle age when a range of other psychosocial factors may increase a person s predisposition to depression. It may be that the primary effect of ginseng was to heighten mood; this would be compatible with the observation that it was associated with an improvement in scores on the timed diagram test but not in memory as assessed by digit span. It is not clear whether the risk of cognitive impairment and dementia is globally associated with diabetes or is linked to particular subgroups characterised by severity or comorbidity. If the mechanism were predominantly vascular it would not be surprising if the main impact were on those people with diabetes who are also hypertensive or who smoke. These issues could be most reliably resolved by appropriately designed and analysed clinical trials linking measures of cognitive function with individual characteristics of participants, mode of treatment and metabolic and clinical outcomes. It is therefore disappointing to find that so few clinical trial of treatment for Type II diabetes have included measures of cognitive function as outcome variables. While it might well take years of follow-up to identify an impact on the prevention of dementia, direct metabolic effects of disease and treatment on neurons, or the influence of depression, are likely to be detectable in short-term trials. As detailed above, there was some suggestion in the studies reviewed that more rigorous control of diabetes was associated with improvement in various indices of cognitive function. None of the studies as reported was without methodological failings. At present, therefore, it is impossible to draw useful conclusions. No large-scale randomized controlled trial in Type II diabetes has included validated tests of cognitive function among the outcome measures. However, there is compelling evidence that, whether as a consequence of the disease and its associated conditions, or its treatment, diabetes is associated with an increased risk of cognitive impairment. Appropriate indices of cognitive function should be included among the outcome measures of future short- and longterm interventional studies of treatment of diabetes. 10

13 A U T H O R S C O N C L U S I O N S Implications for practice There is no evidence on which to recommend any type of diabetic treatment to prevent cognitive impairment in people with Type II diabetes. Implications for research Interventional studies of treatment for Type II diabetes should include reliable and validated measures of cognitive function. A battery of tests covering a range of domains of cognitive function is desirable, to detect differential changes and to assist in avoiding confounding from factors such as education and premorbid abilities. Studies should be designed to permit analysis of changes in cognitive function in relation to the mechanisms and metabolic effects of treatment, in particular insulin and glucose levels, and indices of glucose homoeostasis. Relationships of cognitive function with mood and other aspects of functional status and quality of life also need further elucidation. A C K N O W L E D G E M E N T S The contributions of the consumer editor, Corinne Cavender, the support of the Cochrane Dementia and Cognitive Improvement Group and particularly the advice of Helen Lee, Research Assistant, are gratefully acknowledged. We are grateful for helpful comments on an early draft from peer reviewers, in particular from colleagues in the Cochrane Endocrine, Metabolic and Diabetes Group R E F E R E N C E S References to studies included in this review Naor 1997 {published data only} Naor M, Steingruber HJ, Westhoff K, Schottenfeld-Naor Y, Gries AF. Cognitive function in elderly non-insulindependent diabetic patients before and after inpatient treatment for metabolic control. Journal of Diabetes and its Complications 1997;11(1): Sotaniemi 1995 {published data only} Sotaniemi EA, Haapakosi E, Rautio A. Ginseng therapy in non-insulin-dependent diabetic patients. Diabetes Care 1995;18(10): Testa 1998 {published data only} Testa MA, Simonson DC. Health economics benefits and quality of life during improved glycemic control in patients with type 2 diabetes mellitus: a randomized, controlled, double-blind trial. Journal of the American Medical Association 1998;280(17): Tovi 1998 {published data only} Tovi J, Engfeldt P. Well-being and symptoms in the elderly type 2 diabetes patients with poor metabolic control: effect of insulin treatment. Practical Diabetes International 1998; 15(3): UKPDS {published data only} UK Prospective Study Diabetes Group. Quality of life in type 2 diabetic patients is affected by complications but not by intensive policies to improve blood glucose or blood pressure control. Diabetes Care 1999;22(7): References to studies excluded from this review Gradman 1993 {published data only} Gradman TJ, Laws A, Thompson LW, Reaven GM. Verbal learning and/or memory improves with glycemic control in older subjects with non-insulin dependent diabetes mellitus. Journal of the American Geriatrics Society 1993;41: Meneilly 1993 {published data only} Meneilly GS, Cheung E, Tessier D, Yakura C, Tuokko H. The effect of improved glycemic control on cognitive functions in the elderly with diabetes. Journals of Gerontology 1993;48(4):M117 M121. Additional references Anderson 2001 Anderson RJ, Freeedland KE, Clouse RE, Lustman PJ. The prevalence of comorbid depression in adults with diabetes. Diabetes Care 2001; Vol. 24: Arvanitakis 2004 Arvanitakis Z, Wilson RS, Bienias JL, Evans DA, Bennett DA. Diabetes mellitus and risk of Alzheimer disease and decline in cognitive function. Archives of neurology 2004;61 (5): Assisi 1996 Assisi A, Alimenti M, Maceli F, Di Petro S, Lalloni g, Montera P. Diabetes and cognitive function preliminary studies. Archives of Gerontology and Geriatrics 1996; Vol. S5: Atiea 1995 Atiea JA, Moses JL, Sinclair AJ. Neuropsychological Function in Older Subjects with Non-Insulin-dependent Diabetes Mellitus. Diabetes Care 1995; Vol. 12: Austin 1997 Austin MP, Mitchell P. The anatomy of melancholia does fronto-subcortical pathophysiology underpin its psychomotor and cognitive manifestations. Psychological Medicine 1997; Vol. 25: Bale 1973 Bale RN. Brain damage in diabetes mellitus. British Journal of Psychiatry 1973; Vol. 122:

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20 C H A R A C T E R I S T I C S O F S T U D I E S Characteristics of included studies [ordered by study ID] Naor 1997 Methods Participants Interventions Outcomes Randomized Controlled Parallel group Single blind Duration: 6 Weeks Country: Germany Number: 40 participants (15 M; 25 F) Inclusion criteria: Type II diabetic patients referred to the outpatient clinic at the Diabetes Research Institute Dusseldorf in poor metabolic control. All treated by diet and oral antidiabetic of sulfonylurea type. Exclusion criteria: descompensate cardiac failure, renal failure, cerebrovascular events, uncontrolled hypertension, liver cirrhosis, alcoholism, use neuroleptics, depression 1- Intensive inpatient treatment: individually adapted diet, daily monitoring of blood glucose, standardized educational programme for NIDDM. Fasting blood glucose levels below 130 mg/dl and postprandial blood glucose levels below 180 mg/dl. 2- Regular treatment: Continued with unchanged previous therapy Cognitive and metabolic parameters were assessed on three occasions in each group. They measured: Reaction time test Zahlen-Verbindungs test Test d2 Bourdon-Freyberg concentration test Notes Sotaniemi 1995 Methods Participants Interventions Outcomes Randomized placebo-controlled doble-blind parallel-group design Duration: 8 weeks Country: Finland. Number: 36 newly diagnosed patients with Type II stabilized on diet alone Ginseng at doses of 100mg or 200 mg daily Indices of glucose homoeostasis, serum lipids, mood, physical activity. Memory assessed by digit-span, psychophysical performance by a numbered digram completion test Notes 18