***TASK*** the task is to summarize an input biomedical literature in six sentences 
    ***INPUT*** the input is a biomedical literature 
    ***OUTPUT*** the output is the summary of an input biomedical literature in six sentences 
    ***DOCUMENTATION*** 
    ***EXAMPLES*** 
    Input: The 1990 guidelines for adult weight published by the U.S. Department of Agriculture [ 1 ] recommend higher weights than previous st and ards . In particular , the guidelines for increased weight ( about 7 kg on average ) for persons age 35 years and older , with allowance for major weight gain in midlife , have stimulated much debate [ 2 - 4 ] . The basis for these recommendations is unclear . The report by And res [ 5 ] on which the recommendations may be based is fundamentally flawed because it ignored cigarette smoking . Although no apparent biological rationale exists for suggesting that persons increase their weight as they grow older , the health consequences of weight gain during adult life have not been clearly documented . In general , a strong association between body mass index and the risk for noninsulin-dependent diabetes mellitus has been observed . However , few studies have examined the consequences of weight gain during various periods of life . From a public health perspective , weight and weight gain are more easily understood than body mass index . Also , using change in weight as a basis for recommendations is attractive because it allows for differences in frame size , which are difficult to characterize . For these reasons , we quantified the relations between change in adult weight and the risk for noninsulin-dependent diabetes mellitus among women during 14 years of follow-up . We previously reported the relation between body mass index and clinical diabetes in this cohort after 8 years of follow-up [ 6 ] . Methods Established in 1976 , the Nurses ' Health Study cohort consists of 121 700 female registered nurses aged 30 to 55 years who responded to a mail question naire about their medical history and health behaviors .  Additional details have been reported elsewhere [ 7 ] . The participants for our study were the 114 824 women who did not have diagnosed diabetes mellitus , coronary heart disease , stroke , or cancer when the cohort was enrolled in 1976 . On the basis of a sub sample of participants , we estimate that 98 % of the participants are white , a percentage that reflects the ethnic background of women trained as registered nurses before 1977 [ 8 ] . Ascertainment of Risk Factors Height and weight were ascertained on the 1976 question naire . On biennial follow-up question naires , we inquired about current weight and asked for information on whether diabetes mellitus , coronary heart disease , cancer , or other major illnesses had been diagnosed during the 2 years since the previous question naire . In 1980 , we asked women to record their weight at age 18 years , and in 1982 we inquired about a history of diabetes in the participants ' mothers , fathers , brothers , or sisters . Weight reported by the participants in this study has been shown to be highly valid in two sample s of Boston-area study participants . Self-reported current weight was highly correlated with measured weight ( Spearman correlation coefficient , 0.97 ) ; the average measured weight was 1.5 kg lower [ 9 , 10 ] . In a sub study done in a cohort of nurses aged 27 to 44 years , recalled weight at age 18 years was compared with self-reported weights at ages 17 to 21 years that were recorded on nursing-school physical examination forms . The mean recalled self-reported body mass index was 21.6 kg/m2 compared with an index of 22.1 kg/m2 noted on the examination records ( mean difference in weight , 1.4 kg ) . The Pearson correlation coefficient for weight was 0.87 and was independent of current age . Participants in the Nurses ' Health Study cohort weighed , on average , 3 kg less than a national sample of women in 1976 [ 11 ] . We used body mass index ( weight in kg divided by height in m2 ) as an index of relative weight and grouped it into 10 categories using whole-number cutpoints . We divided weight change between age 18 years and 1976 into eight categories . A body mass index of 24.0 kg/m2 represents the 50th percentile for middle-aged , white U.S. women , and an index of 29.0 kg/m2 represents the 75th percentile [ 11 ] . Diagnosis of Diabetes Mellitus We mailed supplementary question naires on  symptoms , diagnostic tests , and therapy for hypoglycemia  to women who responded positively on any follow-up question naire to the query Have you had physician-diagnosed diabetes mellitus ? The supplementary question naires were mailed in 1984 to women who reported that diabetes had been diagnosed between 1976 and 1984 and in 1986 , 1988 , and 1990 to women who reported diabetes on the question naires in those years . We excluded women who reported that diabetes had been diagnosed before they entered the study in 1976 . An incident case of diabetes was confirmed if at least one of the following was reported on the supplementary question naire : 1 ) one or more classic symptoms ( thirst , polyuria , weight loss , hunger , pruritus ) plus a fasting plasma glucose level of at least 140 mg/dL ( 7.8 mmol/L ) or a r and om plasma glucose level of at least 200 mg/dL [ 11.1 mmol/L ] ; 2 ) two or more elevated plasma glucose values on different occasions [ fasting level 140 mg/dL or r and om level 200 mg/dL , or both , or fasting level 200 mg/dL after 2 or more hours of testing for oral glucose tolerance ] in the absence of symptoms ; or 3 ) treatment with medication for hypoglycemia ( insulin or oral hypoglycemic agent ) .  All women were 30 years of age or older at diagnosis . We excluded cases ( and subsequent follow-up after diagnosis ) of incident insulin-dependent ( type 1 ) diabetes ( n = 89 ) . We also excluded women classified as having gestational diabetes only ( diabetes first diagnosed during pregnancy and that persisted no more than 1 month after the end of pregnancy , with no subsequent diagnosis of diabetes when the woman was not pregnant ) . The remaining women with confirmed diabetes ( n = 2204 ) were classified as having noninsulin-dependent diabetes mellitus ; these women form the basis for our analysis . Our criteria for diabetes classification are consistent with those proposed by the National Diabetes Data Group [ 12 ] except that we did not use any weight criteria in classifying diabetes . To document the validity of the confirmation of diabetes by the supplementary question naire , we examined medical records in a r and om sample of the participants who reported diabetes . Of 84 women who reported diabetes and were classified as having noninsulin-dependent diabetes mellitus by supplementary question naires , 71 gave permission for review of their medical records ; medical records were obtained for 62 . An endocrinologist ( JEM ) who was unaware of the information reported on the supplementary question naires review ed the available records using the National Diabetes Data Group criteria . The diagnosis of noninsulin-dependent diabetes mellitus was confirmed by medical records in 61 of the 62 women ( 98.4 % ) . Statistical Analysis We computed incidence rates of noninsulin-dependent diabetes mellitus during the 14 years of follow-up for categories of body mass index calculated at baseline in 1976 and for categories of weight change between age 18 years and 1976 . Follow-up began when the 1976 question naire was returned and ended on the date of death or diagnosis of diabetes , cardiovascular disease , or cancer , or 1 June 1990 , whichever came first . Women who reported  diabetes mellitus , coronary heart disease , stroke , or cancer on the baseline or follow-up question naires were excluded from subsequent follow-up . We obtained rates by dividing the number of incident cases by the number of person-years of follow-up in each category of body mass index or weight change . We computed relative risks as the rate of noninsulin-dependent diabetes mellitus in a specific category of body mass index divided by the rate among women with a body mass index less than 22.0 kg/m2 . Because family history was recorded in 1982 , we repeated analyses from 1982 to 1990 to examine weight change within strata of family history and defined weight change in adulthood as weight in 1982 minus weight at age 18 years . We used proportional hazard models to simultaneously evaluate the association with family history , body mass index at age 18 years , and weight gain . We calculated 95 % CIs for each relative risk . Results The  mean weight SD of women in this cohort at age 18 years was 126.2 19.4 pounds ( 57 8.8 kg ) . Mean weight gain between age 18 years and 1976 varied monotonically with age from 7.6 pounds ( 3.4 kg ) among women 30 years of age to 19.0 pounds ( 8.6 kg ) for women 55 years of age . Reflecting these weight changes , the mean weight for each birth cohort ( in single years ) increased from 133 pounds ( 60.3 kg ) for women 35 years of age to 144 pounds ( 65.3 kg ) for women 55 years of age . The risk for diabetes increased as attained body mass index increased over the 1976 value ( index was up date d every 2 years ) ( Table 1 ) . Even women with a body mass index of 22.0 to 22.9 kg/m2 had a significant threefold elevation in age-adjusted relative risk compared with women with an index less than 22.0 kg/m2 . Women of average weight ( body mass index , 24 to 24.9 kg/m2 ) had a relative risk of 5.0 ( 95 % CI , 3.6 to 6.6 ) compared with women with an index less than 22 kg/m2 . Women with a body mass index of 31.0 kg/m2 or more had an age-adjusted relative risk of 40.0 or greater ( Table 1 ) . This association persisted within age strata , and body mass index remained a strong risk factor , even for women as old as 69 years . After adjustment for body mass index , women aged 60 to 64 years had a relative risk of 3.4 ( CI , 2.5 to 4.6 ) compared with women aged 40 to 44 years . The relation between body mass index and diabetes mellitus was similar in white and black women . The strong association between body mass index and the risk for diabetes mellitus persisted ( that is , remained unchanged ) when we repeated analyses that were limited to symptomatic cases of noninsulin-dependent diabetes mellitus ( report of at least one symptom at diagnosis , including thirst , polyuria , weight loss , hunger , or pruritus ) . Table 1 . Attained Body Mass Index and Objective To examine the prevalence of outcome reporting bias — the selection for publication of a subset of the original recorded outcome variables on the basis of the results — and its impact on Cochrane review s. Design A nine point classification system for missing outcome data in r and omised trials was developed and applied to the trials assessed in a large , unselected cohort of Cochrane systematic review s. Research ers who conducted the trials were contacted and the reason sought for the non-reporting of data . A sensitivity analysis was undertaken to assess the impact of outcome reporting bias on review s that included a single meta- analysis of the review primary outcome . Results More than half ( 157/283 ( 55 % ) ) the review s did not include full data for the review primary outcome of interest from all eligible trials . The median amount of review outcome data missing for any reason was 10 % , whereas 50 % or more of the potential data were missing in 70 ( 25 % ) review s. It was clear from the publications for 155 ( 6 % ) of the 2486 assessable trials that the research ers had measured and analysed the review primary outcome but did not report or only partially reported the results . For reports that did not mention the review primary outcome , our classification regarding the presence of outcome reporting bias was shown to have a sensitivity of 88 % ( 95 % CI 65 % to 100 % ) and specificity of 80 % ( 95 % CI 69 % to 90 % ) on the basis of responses from 62 trialists . A third of Cochrane review s ( 96/283 ( 34 % ) ) contained at least one trial with high suspicion of outcome reporting bias for the review primary outcome . In a sensitivity analysis undertaken for 81 review s with a single meta- analysis of the primary outcome of interest , the treatment effect estimate was reduced by 20 % or more in 19 ( 23 % ) . Of the 42 meta-analyses with a statistically significant result only , eight ( 19 % ) became non-significant after adjustment for outcome reporting bias and 11 ( 26 % ) would have overestimated the treatment effect by 20 % or more . Conclusions Outcome reporting bias is an under-recognised problem that affects the conclusions in a substantial proportion of Cochrane review s. Individuals conducting systematic review s need to address explicitly the issue of missing outcome data for their review to be considered a reliable source of evidence . Extra care is required during data extraction , review ers should identify when a trial reports that an outcome was measured but no results were reported or events observed , and contact with trialists should be encouraged Background and Purpose — Impaired glucose tolerance (IGT)–a prediabetic state – is an important risk factor for atherosclerosis . Acarbose , an & agr;-glucosidase inhibitor , was shown in the placebo-controlled prospect i ve study to prevent noninsulin-dependent diabetes mellitus ( STOP-NIDDM ) trial to reduce the risk of diabetes by 36 % in IGT subjects . This article reports 
    Output:
    
There were no clear differences for any outcome measure between these two acarbose interventions and the associated comparator groups .
AUTHORS ' CONCLUSIONS AGI may prevent or delay the development of T2DM  in people with IGT .
There is no firm evidence that AGI have a beneficial effect on cardiovascular mortality or cardiovascular events