***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 We sought to assess the validity and short-term responsiveness of the Pediatric Quality of Life Inventory ™ 4.0 Generic Core Scales ( PedsQL ™ ) for febrile illnesses evaluated in the pediatric emergency department ( ED ) . Design Prospect i ve cohort study of children 2–18 years discharged after ED evaluation for fever ( ≥ 38 ° C ) .  Self-administered , parent-report of health-related quality of life ( HRQOL ) was assessed using the PedsQL ™ Acute Version , a vali date d HRQOL instrument . HRQOL was measured on ED presentation and at 7–10 day follow-up . At follow-up , duration of fever , child functional impairment , missed daycare/school , and disrupted family unit functioning , were assessed . Results Of 160 subjects enrolled , 97 ( 61 % ) completed the study ; mean follow-up was 8.7 days . Mean total HRQOL score on ED presentation was 76.4 ; mean follow-up score was 86.3 . Compared to subjects that returned to baseline , statistically significant differences in HRQOL were noted for those with prolonged fever , child functional impairment , and relapse . Significant correlation was observed between HRQOL at follow-up and days of daycare/school missed ( r = -0.35 , p = .003 ) and days of family disruption ( r = -0.43 , p < .001 ) . Mean change in HRQOL within subjects , from ED visit to follow-up , was + 9.8 ( 95 % CI : 5.6–14.6 ) . Effect size was 0.53 , indicating moderate responsiveness . Conclusion The PedsQL ™ appears to be a valid and responsive indicator of HRQOL for short-term febrile illnesses evaluated in the ED OBJECTIVE To test the hypothesis that educating parents about use of their primary care provider and providing information about common pediatric illnesses will reduce visits to the pediatric emergency department ( PED ) . DESIGN Prospect i ve , r and omized , controlled trial conducted from September 1 , 1993 , to October 31 , 1994 . SETTING Pediatric emergency department of an urban university hospital . PARTICIPANTS Parents of 130 patients seen in the PED for minor illness . INTERVENTIONS Subjects were r and omized to intervention or control groups . Parents in both groups were interviewed about their child 's health and use of health care services . The intervention group received education on pediatric health care issues ; the control group received usual PED discharge instructions . Use of the PED by all subjects was tracked for 6 months by telephone follow-up and medical record review . MAIN OUTCOME MEASURES Differences between the two groups in total number of return visits to the PED and return visits to the PED for minor illness . RESULTS Sixty-seven ( 97 % ) of the 69 patients in the intervention group and 56 ( 92 % ) of the 61 patients in the control group identified a primary care provider . At 6-month follow-up , 21 patients ( 30 % ) from the intervention group and 16 ( 26 % ) from the control group had returned to the PED ( P = .68 , chi 2 ) . Seventeen ( 81 % ) of intervention group returnees to the PED had minor illness , as did 11 ( 69 % ) of control group returnees . CONCLUSIONS A one-time educational intervention in the PED does not alter long-term emergency department utilization habits . More extensive education and greater availability of primary care providers may be needed to decrease use of the PED  for minor illness Aims : To assess the clinical effectiveness of a  paediatric hospital at home service compared to conventional hospital care . Methods : A total of 399 children suffering from breathing difficulty ( n = 202 ) , diarrhoea and vomiting ( n = 125 ) , or fever ( n = 72 ) were r and omised to Hospital at Home or in-patient paediatric care .  Main outcome measures were : comparative clinical effectiveness as measured by readmission rate within three months ( used as a proxy for parental coping with illness ) ; and length of stay/care and comparative satisfaction of both patients and carers . Results : Clinical effectiveness of both services was not significantly different . Length of care was one day longer in the Hospital at Home group ; however , most parents and children preferred home care . Conclusions : Hospital at Home is a clinical ly acceptable form of care for these groups of acute paediatric illness . Readmission rates within three months failed to show any advantage in terms of parental coping . Parents and patients expressed a strong preference for hospital at home Background A substantial percentage of emergency department ( ED ) patients return within 72 hours of their initial evaluation . Quality review s typically demonstrate that most revisits do not seem to be directly related to problematic care provided on the first evaluation . We examined the possibility that return visits are related to nonmedical issues on the first visit , most notably patient discharge education . Objective We prospect ively surveyed a convenience sample of caregivers in a pediatric ED to determine why they returned with their  children  within 72 hours of their initial ED visit . Design / Methods All patients who returned within 72 hours of a previous visit were identified and prospect ively interviewed using a survey instrument with nominal ( multiple choice ) and brief descriptive responses . Results Caregivers of 124 children were prospect 
    Output:
    
Limited evidence was observed for different strategies of safety netting  , with educational interventions being mostly studied .
Young children , a relevant medical history , infectious/respiratory symptoms or seizures and progression/persistence of symptoms were strongly associated with ED revisits .
Gender , emergency crowding , physicians ' characteristics and diagnostic tests and /or therapeutic interventions at the index visit were not associated with revisits .
Within the heterogeneous available evidence , we identified a set of strong determinants of revisits that identify high-risk groups in need for safety netting in paediatric emergency care being related to age and clinical symptoms .