***TASK*** the task is to summarize an input biomedical literature in six sentences 
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    Input: OBJECTIVE To examine whether intensive glycemic control could decrease the frequency or severity of diabetic microvascular complications , an 8-year prospect i ve study of Japanese patients with type 2 diabetes was performed . RESEARCH DESIGN AND METHODS A total of 110 patients with type 2 diabetes ( 55 with no retinopathy [ the primary prevention cohort ] and 55 with simple retinopathy [ the secondary intervention cohort ] ) were r and omly assigned to multiple insulin injection therapy ( MIT ) groups and administered three or more daily insulin injections or assigned to conventional insulin injection therapy ( CIT ) groups and administered one or two daily intermediate-acting insulin injections . Worsening of microvascular complications was regularly assessed during 8 years . Two or more steps up in the 19 stages of the modified Early Treatment of Diabetic Retinopathy Study classification in retinopathy and one or more stages up among three stages in nephropathy ( normoalbuminuria , microalbuminuria , and albuminuria ) were defined as worsening of complications . RESULTS In both primary prevention and secondary intervention cohorts , the cumulative percentages of worsening in retinopathy and nephropathy were significantly lower ( P < 0.05 ) in the MIT group than in the CIT group . In neurological tests after 8 years , the MIT group showed significant improvement ( P < 0.05 ) in the median nerve conduction velocities ( motor and sensory nerves ) , whereas the CIT group showed significant deterioration ( P < 0.05 ) in the nerve conduction velocities and vibration threshold . From this study , the glycemic threshold to prevent the onset and progression of diabetic microvascular complications was as follows : HbA1c < 6.5 % , fasting blood glucose concentration < 110 mg/dl , and 2-h postpr and ial blood glucose concentration < 180 mg/dl . CONCLUSIONS Intensive glycemic control can delay the onset and progression of the early stages of diabetic microvascular complications in Japanese patients with type 2 diabetes Diabetes mellitus is the most frequently reported cause of kidney failure in the United States . In 1990 , it was considered to be the underlying cause of kidney failure in 34 % of patients starting therapy for end-stage renal disease [ 1 ] . These statistics , based on clinical diagnoses made by patients ' nephrologists , prompted the National Institutes of Health to identify diabetic nephropathy as a research priority [ 2 ] . However , the validity of clinical diagnoses of underlying renal disease in patients with kidney failure is unknown . Clinical diagnoses may misrepresent the importance of diabetes-associated end-stage renal disease for several reasons . First , diabetes may contribute to the progression of kidney insufficiency in patients in whom another underlying disease is reported . If so , clinical diagnoses would underestimate the true effect of diabetes . Second , diseases unrelated to diabetes may cause kidney failure in patients with diabetes and may be mistaken for diabetic nephropathy ; thus , clinical diagnoses would overestimate the importance of diabetes . Finally , a single underlying disease may be impossible to select in patients whose kidney insufficiency is caused by multiple processes , involving , for instance , diabetes mellitus , hypertension , and repeated kidney infections . In such patients , forcing the physician to select a single underlying disease may produce statistics that reflect a diagnostic preference rather than the true distribution of disease . Despite the need for disease-specific statistics in allocating research re sources and in developing prevention policy , little empirical evidence exists about the validity of such statistics . Computing the population -attributable risk provides an alternative approach to the estimation of the effect of diabetes on the occurrence of end-stage renal disease [ 3 , 4 ] . This statistic requires no assumption about the cause of renal failure in any person and thus avoids the issue of diagnostic uncertainty . The population -attributable risk attempts to estimate the proportion of cases of a disease ( for example , end-stage renal disease ) that would be avoided in the population if a particular risk factor ( for example , diabetes ) were withdrawn . To do this , the incidence of disease in the total population ( I population ) , which includes exposed and nonexposed persons , is compared with the incidence among nonexposed persons ( Inonexposed ) , which represents the baseline risk for disease . The difference between these two values of incidence is attributed to the risk factor . This attribution is correct only if the association between the risk factor and the disease is causal and is not altered by confounding or by biased methods . The population -attributable risk is often expressed as a percentage of the population incidence ( PAR% ) : I population Inonexposed PAR% = - 100 I population The same quantity can also be deduced from estimates of relative risk ( RR ) and of the prevalence of exposure to the risk factor in the general population ( pexp ) : pexp ( RR 1 ) PAR% = x 100 1 + pexp ( RR 1 ) This second Equation shows that the population -attributable risk depends on the strength of the relative risk but also on the prevalence of the risk factor : Common risk factors carry larger population -attributable risks than do rare risk factors . The magnitude of population -attributable risks for end-stage renal disease can guide policy decisions about the adoption of aggressive , and potentially costly , approaches to primary and secondary [ 5 ] prevention of diabetes . Estimation of the population -attributable risk requires a comparison of the risk for end-stage renal disease in persons with and without diabetes . However , prospect i ve studies [ 6 - 12 ] of kidney disease in diabetes have not included a control group of persons without diabetes . Such studies can not yield estimates of population -attributable risk . Moreover , all but one of these studies [ 6 ] were concerned exclusively with insulin-dependent diabetes mellitus . Two additional studies [ 13 , 14 ] examined the association of diabetes and end-stage renal disease  in the general population , but these studies used ecologic , not individual , data . In our population -based , casecontrol study , we assessed the association between diabetes mellitus ( insulin-dependent and noninsulin-dependent ) and the  risk for end-stage renal disease . We then estimated the population -attributable risk for end-stage renal disease associated with diabetes mellitus in a biracial community . Methods This study had a population -based , casecontrol design [ 15 ] . Study procedures were tested in a pilot study and approved by institutional review boards at the Johns Hopkins University and the Health Care Financing Administration . Patients and Controls The study population included residents of Maryl and , Virginia , West Virginia , and Washington , D.C. , aged 20 to 64 years who had working telephones at their homes . Persons who lived in institutions ( such as nursing homes , prisons , and military facilities ) , had been absent from their homes for more than 2 weeks at the time of contact , were mentally incompetent , were physically unable to complete a telephone interview , or did not speak English were excluded . Patients who started renal replacement therapy between January and July 1991 and who satisfied the criteria cited above were identified by the Mid-Atlantic Renal Coalition , which is part of the Medicare End-Stage Renal Disease Program . Patient identifiers ( including telephone numbers ) were transmitted to the study investigators . The sample was not restricted to Medicare registrants ; it also included patients whose care for end-stage renal disease was being paid for by private insurance policies , Medicaid , and Veterans Affairs benefits . During the study period , 978 potentially eligible patients with end-stage renal disease were identified , of whom 885 ( 90 % ) had use of a private telephone line . Of these , 133 ( 15 % ) were ineligible for participation in the study : Sixty-five had died , 19 were institutionalized , 14 had moved out of the study area , 8 had renal function that had returned to normal , 8 were too sick to be interviewed , 7 had a hearing problem , 5 did not speak English , 5 were hospitalized for more than 2 weeks , and 2 older than 64 years had been preselected by mistake . Of the 752 eligible patients , 716 ( 95 % ) were interviewed , 16 refused to participate , 5 interrupted the interview , and 15 could not be reached . The median delay between the onset of therapy for end-stage renal disease and the interview was 5 months . Patients were further divided in two subgroups : those who had diabetic end-stage renal disease according to the patient 's nephrologist ( n = 239 ) and those with other underlying causes of renal failure ( n = 477 ) . Control persons from the general population , frequency-matched with case- patients within 5-year age groups , were identified by r and om-digit dialing [ 16 ] . Of 1311 residences reached during enrollment , 1259 ( 96 % ) were screened for eligibility , and 402 were found to have one or more eligible residents . When several persons in the same household were eligible , one was chosen r and omly . Reasons for in eligibility in the remaining 857 households were the following : no members within eligible age groups ( 846 households ) , English language not spoken ( 7 persons ) , hearing problems ( 3 persons ) , and end-stage renal disease in respondent ( 1 person ) . Of those eligible , 361 ( 90 % ) completed the interview . Data Collection Trained , certified interviewers contacted potential participants by telephone ( persons with end-stage renal disease , but not controls , received an explanatory letter before the telephone call ) , informed them about the purpose of the study , provided them with a telephone number at which additional information could be obtained , and asked for consent to participate . Whenever possible , the interview was done immediately . The average duration of an interview was 24 minutes . Those who refused to participate or who were not sure whether they should take part were contacted again 2 weeks later ; about 40 % of them then agreed to participate . Exposure Variables Diabetes-related variables included the following : previous diagnosis of diabetes mellitus ; month and year of diagnosis ; use of insulin therapy , diabetes medications , and diabetic diet ; month and year of first insulin treatment ; and history of retinal laser photocoagulation  treatment , heart disease , and numbness or amputations of toes or feet . Type of diabetes was assigned using an algorithm adapted from Cowie and colleagues [ 13 ] ( Figure 1 ) . This algorithm was developed to select the type of diabetes in patients with diabetes-related end-stage renal disease using data routinely available in medical records . The algorithm predicted assessment s of diabetes type by attending nephrologists in 84 % of patients with insulin-dependent diabetes and in 92 % of patients with noninsulin-dependent diabetes [ 13 ] . Potential confounders included sex , race , and history of hypertension ( time since diagnosis and hospitalization because of hypertension ) . Figure 1 . Decision algorithm for distinguishing between insulin-dependent and noninsulin-dependent diabetes . Statistical Analysis All-cause end-stage renal disease was the primary outcome variable . Persons with end-stage renal disease and controls were compared by cross-tabulations , race-stratified analyses , and logistic regression [ 17 ] . Odds ratios were used to estimate relative risks . Successive regression models were compared using the likelihood ratio test . Population -attributable risks were computed by means of a procedure developed for casecontrol studies [ 18 ] . Polychotomous logistic regression [ 17 ] , using a three-level outcome variable ( kidney failure attributed to diabetes , kidney failure attributed to other causes , and control ) , was used to assess risk factors for diabetic and other nephropathy . Analyses were done using SYSTAT software ( Evanston , Illinois ) [ 19 ] ; the ATFRAC program was used To determine whether a difference in HbA(1c ) could be safely sustained between a st and ard therapy ( STD ) arm and an intensive therapy ( INT ) arm , while maintaining HbA(1c ) levels in both arms within a range acceptable in community practice . The effects of intensive treatment on various parameters were studied in this feasibility trial . We report here the results of 24 months of INT on peripheral and autonomic neuropathy . A prospect i ve trial was conducted in five medical centers in 153 men of 60 + /- 6 years of age who had a known diagnosis of diabetes for 7.8 + /- 4 years . They were r and omly assigned to a st and ard insulin treatment group ( one morning injection per day ) or to an intensive therapy group design ed to attain near-normal glycemia and a clinical ly significant separation of glycohemoglobin from the st and ard arm . A four-step plan was used in the intensive therapy group along with daily self-monitoring of glucose : ( 1 ) an evening insulin injection , ( 2 ) the same injection adding daytime glipizide , ( 3 ) two injections of insulin alone , and ( 4 ) multiple daily injections . Peripheral neuropathy was diagnosed clinical ly by a history and physical examination , and by abnormal autonomic neuropathy Valsalva ratio ( VR < 1.2 ) and RR variation ( RRV < 10 ) . An average HbA(1c ) separation of 2.07 % was achieved with INT , having HbA(1c ) at or below 7.3 % ( p = 0 . 001 versus STD ) . Baseline prevalence of peripheral neuropathy was 53 % in STD , and 48 % in INT . By 24 months , the prevalence increased to 69 % in STD ( p = 0.005 versus baseline ) , and to 64 % in INT ( p = 0 . 008 versus baseline , but no different than STD ) . Though INT did not reverse all 
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Results For the USPSTF to conclude that screening reduces diabetic complications , the evidence must demonstrate that feasible screening tests can detect diabetes during a pre clinical phase and that the knowledge of the diagnosis of diabetes in this phase will lead to earlier treatment that will reduce complications more than would treatment begun after clinical detection .
Furthermore , the magnitude of this additional benefit ( that is , the reduction in complications from initiation of treatment in the pre clinical phase minus the reduction in complications from starting treatment after clinical diagnosis ) must be great enough to outweigh the harms and effort of screening .
The length of this asymptomatic period is less clear .
All three tests ( 2-hour postload plasma glucose , FPG , and hemoglobin A1c ) are associated with future cardiovascular events in a linear fashion both above and below the present diabetes cut-points , with no obvious threshold ( 34 - 39 ) .
Hemoglobin A1c level is more closely related to FPG than to 2-hour postload plasma glucose level ( 42 ) , but it is not sensitive to low levels of hyperglycemia ( 30 ) .
Reliability is higher for FPG than for hemoglobin A1c or 2-hour postload plasma glucose level ( 43 - 45 ) .