***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 OBJECTIVE Many authors have identified prognostic factors for external cephalic version success , but there has not been an attempt to integrate these factors into a simple , quantitative scoring system for predicting version success . Nor have any prognostic factors been prospect ively tested . STUDY DESIGN We examined the clinical characteristics of 108 consecutive breech versions performed between 1984 and 1986 . These characteristics were evaluated by stepwise linear regression and discriminate analysis to identify those factors associated with success . Five factors explained the majority of the variability in outcome ( parity , placental location , dilation , station , and estimated fetal weight ) . A model was developed to incorporate the trends identified among these five variables to create a scoring system similar to that of Bishop . This scoring system was then applied to 286 women undergoing external cephalic version since October 1986 . RESULTS There was a positive relationship between a rising version score and the likelihood of successful breech version . No versions were successful with a score < or = 2 , and all breech versions were successful with a score of 9 or 10 . The results of the version score may have significantly altered physician recommendations in more than one third of cases . CONCLUSION We believe that this simple , quantifiable scoring system is a refinement in our ability to predict the likelihood of external cephalic version success We aim ed to develop a predictive model for the chance of a successful external cephalic version ( ECV ) .  We performed a prospect i ve cohort study of women with a singleton fetus in breech presentation with a gestational age of 36 weeks or more . Data on parity , maternal age , body mass index , ethnicity , gestational age , placental location , fetal position , estimated fetal weight , and amniotic fluid were recorded in all participants . Multivariable logistic regression analysis with a stepwise backward selection procedure was used to construct a prediction model for the occurrence of successful ECV .  We included a total of 310 women . Multivariable logistic regression analysis demonstrated that multiparity , increasing estimated fetal weight , and normal amniotic fluid were favorable predictors of successful ECV . Anterior placenta location was an unfavorable predictor for ECV outcome . Discrimination of the model was fair ( area under the curve 0.71 ) , and the calibration of the model was acceptable . Our prediction model appears to discriminate between women with a poor chance of successful ECV ( less than 20 % ) and women with a good chance of success ( more than 60 % ) . When this model is vali date d externally , it could be used for patient counseling and clinical decision making Objective To assess the risks and benefits associated with  caesarean delivery compared with vaginal delivery . Design Prospect i ve cohort study within the 2005 WHO global survey on maternal and perinatal health . Setting 410 health facilities in 24 areas in eight r and omly selected Latin American countries ; 123 were r and omly selected and 120 participated and provided data Participants 106 546 deliveries reported during the three month study period , with data available for 97 095 ( 91 % coverage ) . Main outcome measures Maternal , fetal , and neonatal morbidity and mortality associated with intrapartum or elective caesarean delivery , adjusted for clinical , demographic , pregnancy , and institutional characteristics . Results Women undergoing caesarean delivery  had an increased risk of severe maternal morbidity compared with women undergoing vaginal delivery ( odds ratio 2.0 ( 95 % confidence interval 1.6 to 2.5 ) for intrapartum caesarean and 2.3 ( 1.7 to 3.1 ) for elective caesarean ) . The risk of antibiotic treatment after delivery for women having either type of caesarean was five times that of women having vaginal deliveries . With cephalic presentation , there was a trend towards a reduced odds ratio for fetal death with elective caesarean , after adjustment for possible confounding variables and gestational age ( 0.7 , 0.4 to 1.0 ) . With breech presentation , caesarean delivery had a large protective effect for fetal death . With cephalic presentation , however , independent of possible confounding variables and gestational age , intrapartum and  elective caesarean increased the risk for a stay of seven or more days in neonatal intensive care ( 2.1 ( 1.8 to 2.6 ) and 1.9 ( 1.6 to 2.3 ) , respectively ) and the risk of neonatal mortality up to hospital discharge ( 1.7 ( 1.3 to 2.2 ) and 1.9 ( 1.5 to 2.6 ) , respectively ) , which remained higher even after exclusion of all caesarean deliveries for fetal distress . Such increased risk was not seen for breech presentation . Lack of labour was a risk factor for a stay of seven or more days in neonatal intensive care and neonatal mortality up to hospital discharge for babies delivered by elective caesarean delivery , but rupturing of membranes may be protective . Conclusions Caesarean delivery independently reduces overall risk in breech presentations and risk of intrapartum fetal death in cephalic presentations but increases the risk of severe maternal and neonatal morbidity and mortality in cephalic presentations AIM To investigate the effect of implementation of a number of process policy guidelines ( protocol ) , on the success rate of  external cephalic version ( ECV )  for breech presentation . DESIGN Prospect i ve study . METHODS During a 3 
    Output:
    
For none of the models their impact on clinical practice was evaluated .
We found one prediction model for breech presentation that was vali date d in an external cohort and had acceptable predictive performance .