***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: Prognosis studies are investigations of future events or the evaluation of associations between risk factors and health outcomes in population s of patients ( 1 ) . The results of such studies improve our underst and ing of the clinical course of a disease and assist clinicians in making informed decisions about how best to manage patients . Prognostic research also informs the design of intervention studies by helping define subgroups of patients who may benefit from a new treatment and by providing necessary information about the natural history of a disorder ( 2 ) . There has recently been a rapid increase in the use of systematic review methods to synthesize the evidence on research questions related to prognosis . It is essential that investigators conducting systematic review s thoroughly appraise the method ologic quality of included studies to be confident that a study 's design , conduct , analysis , and interpretation have adequately reduced the opportunity for bias ( 3 , 4 ) . Caution is warranted , however , because inclusion of method ologically weak studies can threaten the internal validity of a systematic review ( 4 ) . This follows abundant empirical evidence that inadequate attention to biases can cause invalid results and inferences ( 5 - 9 ) . However , there is limited consensus on how to appraise the quality of prognosis studies ( 1 ) . A useful framework to assess bias in such studies follows the basic principles of epidemiologic research ( 10 , 11 ) . We focus on 6 areas of potential bias : study participation , study attrition , prognostic factor measurement , confounding measurement and account , outcome measurement , and analysis . The main objectives of our review of review s are to describe methods used to assess the quality of prognosis studies and to describe how well current practice s assess potential biases . Our secondary objective is to develop recommendations to guide future quality appraisal , both within single studies of prognostic factors and within systematic review s of the evidence . We hope this work facilitates future discussion and research on biases in prognosis studies and systematic review s. Methods Literature Search and Study Selection We identified systematic review s of prognosis studies by search ing MEDLINE ( 1966 to October 2005 ) using the search strategy recommended by McKibbon and colleagues ( 12 ) . This strategy combines broad search terms for systematic review s ( systematic review .mp ; meta- analysis .mp ) and a sensitive search strategy for prognosis studies ( cohort , incidence , mortality , follow-up studies , prognos * , predict * , or course ) . We also search ed the reference lists of included review s and method ologic papers to identify other relevant publications . We restricted our search to English- language publications . One review er conducted the search and selected the studies . Systematic review s , defined as review s of published studies with a comprehensive search and systematic selection , were included if they assessed the method ologic quality of the included studies by using 1 or more explicit criteria . We excluded studies if they were meta-analyses of independent patient data only , if their primary goal was to investigate the effectiveness of an intervention or specific diagnostic or screening tests , or if they included studies that were not done on humans . Data Extraction and Synthesis Individual items included in the quality assessment of the systematic review s were recorded as they were reported in the publication ( that is , the information that would be available to readers and future review ers ) . We review ed journal Web sites and contacted the authors of the systematic review s for additional information when authors made such an offer in their original papers . When review s assessed different study design s by using different sets of quality items , we extracted only those items used to assess cohort studies . We constructed a comprehensive list of distinct items that the review s used to assess the quality of their included studies . The full text of each review was screened . All items used by the review authors to assess the quality of studies were extracted into a computerized spreadsheet by 1 review er . Two experienced review ers , a clinical epidemiologist and an epidemiologist , independently synthesized the quality items extracted from the prognosis review s to determine how well the systematic review s assessed potential biases . We did this in 3 steps : 1 ) identified distinct concepts or domains addressed by the quality items ; 2 ) grouped each extracted quality item into the appropriate domain or domains ; and 3 ) identified the domains necessary to assess potential biases in prognosis studies . We then used this information to assess how well the review s ' quality assessment included items from the domains necessary to assess potential biases . After completing each of the first 3 steps , the review ers met to attempt to reach a consensus . The consensus process involved each review er presenting his or her observations and results , followed by discussion and debate . A third review er was available in cases of persistent disagreement or uncertainty . In the first step , all domains addressed by the quality items were identified . The first review er iteratively and progressively defined the domains as items were extracted from the included review s. The second review er defined domains from a r and om list of all extracted quality items . Limited guidance was provided to the review ers so that their assessment s and definitions of domains would be independent . The review ers agreed on a final set of domains that adequately and completely defined all of the extracted items . In the second step , review ers independently grouped each extracted item into the appropriate domains . Review ers considered each extracted item by asking , What is each particular quality item addressing ? or What are the review 's authors getting at with the particular quality assessment item ? . Items were grouped into the domain or domains that best represented the concepts being addressed . For example , the extracted items at least 80 % of the group originally identified was located for follow-up and follow-up was sufficiently complete or does n't jeopardize validity were each independently classified by both review ers as assessing the domain completeness of follow-up adequate , whereas the extracted item quantification and description of all subjects lost to follow-up was classified as assessing the domain completeness of follow-up described . In the third step , we identified the domains necessary to assess potential biases . Each review er considered the ability of the identified domains to adequately address , at least in part , 1 of the following 6 potential biases : 1 ) study participation , 2 ) study attrition , 3 ) prognostic factor measurement , 4 ) confounding measurement and account , 5 ) outcome measurement , and 6 ) analysis . Domains were considered to adequately address part of the framework if information garnered from that domain would inform the assessment of potential bias . For example , both review ers judged that the identified domain study population represents source population or population of interest assessed potential bias in a prognosis study , whereas the domain research question definition did not , although the latter is an important consideration in assessing the inclusion of studies in a systematic review . Finally , on the basis of our previous ratings , we looked at whether each review included items from the domains necessary to assess the 6 potential biases . We calculated the frequency of systematic review s by assessing each potential bias and the number of review s that adequately assessed bias overall . From this systematic synthesis , we developed recommendations for improving quality appraisal in future systematic review s of prognosis studies . We used Microsoft Access and Excel 2002 ( Microsoft Corp. , Redmond , Washington ) for data management and SAS for Windows , version 9.1 ( SAS Institute , Inc. , Cary , North Carolina ) for descriptive statistics . Role of the Funding Sources The funding sources , the Canadian Institutes of Health Research , the Canadian Chiropractic Research Foundation , the Ontario Chiropractic Association , and the Ontario Ministry of Health and Long Term Care , did not have a role in the collection , analysis , or interpretation of the data or in the decision to su bmi t the manuscript for publication . Results We identified 1384 potentially relevant articles . Figure 1 shows a flow chart of studies that were included and excluded . Figure 2 shows the number of review s identified by year of publication . We excluded 131 systematic review s of prognosis studies that did not seem to include any quality assessment of the included studies ; this represented 44 % of prognosis review s. We included 163 review s of prognosis studies in our analysis ( 13 - 175 ) . The most common topics were cancer ( 15 % ) , musculoskeletal disorders and rheumatology ( 13 % ) , cardiovascular ( 10 % ) , neurology ( 10 % ) , and obstetrics ( 10 % ) . Other review s included a wide range of health and health care topics . Sixty-three percent of the review s investigated the association between a specific prognostic factor and a particular outcome ; the remainder investigated multiple prognostic factors or models . The number of primary studies included in each systematic review ranged from 3 to 167 ( median , 18 [ interquartile range , 12 to 31 ] ) . A complete description of the included review s is available from the authors on request . Figure 1 . Flow diagram of inclusion and exclusion criteria of systematic review s. Figure 2 . Number of systematic review s of prognosis studies identified over time . Quality Items One hundred fifty-three review s provided adequate detail to allow extraction of quality items . Eight hundred eighty-two distinct quality items were extracted from the review s. Most review s developed their own set of quality items , with only a few applying criteria from previous review s. Most quality items Purpose It is not always possible to collect utility-based outcome data , like EQ-5D , needed for conducting economic evaluations in population s of older people . Sometimes , information on other non-utility outcome measures may have been collected . This paper examines the possibility of mapping the EQ-5D from a non-utility-based outcome , the Barthel index . Methods Data for 1,189 UK intermediate care patients were used .  Ordinary least squares ( OLS ) , censored least absolute deviations ( CLAD ) estimator and multinomial logistic ( ML ) models were used . The mean absolute error ( MAE ) and root-mean-squared error ( RMSE ) were used to estimate the predictive accuracy of eight regression models . Validation of primary models was carried out on r and om sample s of data collected at admission and discharge . Results Models where the EQ-5D was entered as a continuous dependent variable and Barthel dimensions used as explanatory variables performed better . CLAD performed best on MAE and OLS on the RMSE , while the ML performed the worst on both measures . The CLAD predicted EQ-5D scores that matched the observed values more closely than the OLS . Conclusions It is possible to reasonably predict that the EQ-5D from the Barthel using regression methods and the CLAD model ( 4 ) is recommended As part of a controlled clinical trial of a geriatric consultation team ( GCT ) , we investigated whether a GCT could affect the incidence of hospital-acquired complications in elderly patients . One hundred eighty-five patients , aged 75 years and older , were r and omized into an intervention ( N = 92 ) and a control ( N = 93 ) group . Members of the intervention group received a GCT consultation and were routinely followed up throughout their hospitalization . The incidence of hospital-acquired complications for the entire study population was 38 % . The type and rate of hospital-acquired complications in the intervention and control groups were not significantly different . Functional status on admission and admission to the psychiatry service were predictive for the occurrence of a hospital-acquired complication . In a broadly selected population such as this , the intensity of care available through a GCT was unable to reduce the occurrence of hospital-acquired complications . However , since this is only one aspect of a GCT function , and others may be of great importance , such aspects , and more targeted population s , must be evaluated before final conclusions can be reached about GCT efficiency OBJECTIVES To compare the effects of community hospital care on independence for older people needing rehabilitation  with that of general hospital care . DESIGN R and omized , controlled trial . SETTING Seven community hospitals and five general hospitals in the midl and s and north of Engl and . PARTICIPANTS Four hundred ninety patients needing rehabilitation after hospital admission with an acute illness . INTERVENTION Multidisciplinary team care for older people in community hospitals . MEASUREMENTS The primary outcome was the Nottingham extended activities of daily living scale ( NEADL ) ; secondary outcomes were the Barthel Index , Nottingham Health Profile , Hospital Anxiety and Depression Scale , mortality , discharge destination , 6-month residence status , and satisfaction with services . RESULTS Loss of independence at 6 months was significantly less likely in the community hospital group ( mean adjusted NEADL change score group difference 3.27 ; 95 % confidence interval 0.26 - 6.28 ; P=.03 ) . The results for the secondary outcome measures were similar for the two groups . CONCLUSION Postacute community hospital rehabilitation care for older people is associated with greater independence Background Approximately 40 % of hospitalized older adults have cognitive impairment ( CI ) and are more prone to hospital-acquired complications . The Institute of Medicine suggests using health information technology to improve the overall safety and quality of the health care system . Objective Evaluate the efficacy of a clinical decision support system ( CDSS ) to improve the quality of care for hospitalized older adults with CI . Design A r and omized controlled clinical trial . Setting A public hospital in Indianapolis . Population A total of 998 hospitalized older adults were screened for CI , and 424 patients ( 225 intervention , 199 control ) with CI were enrolled in the trial with a mean age of 74.8 , 59 % African Americans , and 68 % female . InterventionA CDSS alerts the physicians of the presence of CI , recommends early referral into a geriatric consult , and suggests discontinuation of the use of Foley catheterization , physical restraints , and anticholinergic drugs . Measurements Orders of a geriatric consult and discontinuation orders of Foley catheterization , physical restraints , or anticholinergic drugs .  Results Using intent-to-treat analyses , there were no differences between the intervention and the control groups in geriatric consult orders ( 56 % vs 49 % , P = 0.21 ) ; discontinuation orders for Foley catheterization ( 61.7 % vs 64.6 % , P = 0.86 ) ; physical restraints ( 4.8 % vs 0 % , P = 0.86 ) , or anticholinergic drugs ( 48.9 % vs 31.2 % , P = 0.11 ) . Conclusion A simple screening program for CI followed by a CDSS did not change physician prescribing behaviors or improve the process of care for hospitalized older adults with CI OBJECTIVE to prove the effectiveness of geriatric evaluation and management for elderly , hospitalized patients , combined 
    Output:
    
Older patients are more likely to be alive and in their own homes at follow-up if they received CGA on admission to hospital .