***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: BACKGROUND Although the Pneumonia Severity Index ( PSI ) has been extensively vali date d , little is known of the impact of its routine use as an aid to site-of-treatment decisions for patients with pneumonia who present to emergency departments ( EDs ) . METHODS A prospect i ve , observational , controlled cohort study of patients with pneumonia was conducted in 8 EDs that used the PSI ( PSI-user EDs ) and 8 EDs that did not use the PSI ( PSI-nonuser EDs ) in France . The outcomes examined included the proportion of " low-risk " patients ( PSI risk classes I-III ) treated as out patients , all-cause 28-day mortality , admission of in patients to the intensive care unit , and subsequent hospitalization of out patients . RESULTS Of the 925 patients enrolled in the study , 472 ( 51.0 % ) were treated at PSI-user EDs , and 453 ( 49.0 % ) were treated at PSI-nonuser EDs ; 449 ( 48.5 % ) of all patients were considered to be at low risk . In PSI-user EDs , 92 ( 42.8 % ) of 215 patients at low risk were treated as out patients , compared with 56 ( 23.9 % ) of 234 patients at low risk in PSI-nonuser EDs . The adjusted odds ratios for outpatient treatment were higher for patients in PSI risk classes I and II who were treated in PSI-user EDs , compared with PSI-nonuser EDs ( adjusted odds ratio , 7.0 [ 95 % confidence interval , 2.0 - 25.0 ] and 4.6 [ 95 % confidence interval , 1.3 - 16.2 ] , respectively ) , whereas the adjusted odds ratio did not differ by PSI-user status among patients in risk class III or among patients at high risk . After adjusting for pneumonia severity , mortality was lower in patients who were treated in PSI-user EDs ; other safety outcomes did not differ between patients treated in PSI-user and PSI-nonuser EDs . CONCLUSIONS The routine use of the PSI was associated with a larger proportion of patients in PSI risk classes I and II who had pneumonia and who were treated in the outpatient environment without compromising their safety 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 Background : Several severity scores have been proposed to predict patient outcome and to guide initial management of patients with community acquired pneumonia ( CAP ) . Most have been derived as predictors of mortality . A study was undertaken to compare the predictive value of these tools using different clinical ly meaningful outcomes as constructs for “ severe pneumonia ” . Methods : A prospect i ve cohort study was performed of all patients presenting to the emergency department with an admission diagnosis of CAP from March 2003 to March 2004 . Clinical and laboratory features at presentation were used to calculate severity scores using the  pneumonia severity index  (  PSI  ) , the revised American Thoracic Society score  ( rATS ) , and the  British Thoracic Society ( BTS ) severity scores CURB , modified BTS severity score , and CURB-65 .  The sensitivity , specificity , positive and negative predictive values were compared for four different outcomes ( death , need for ICU admission , and combined outcomes of death and /or need for ventilatory or inotropic support ) . Results : 392 patients were included in the analysis ; 37 ( 9.4 % ) died and 26 ( 6.6 % ) required ventilatory and /or inotropic support . The modified BTS severity score performed best for all four outcomes . The PSI ( classes IV+V ) and CURB had a very similar performance as predictive tools for each outcome . The rATS identified the need for ICU admission well but not mortality . The CURB-65 score predicted mortality well but performed less well when requirement for ICU was included in the outcome of interest . When the combined outcome was evaluated ( excluding patients aged > 90 years and those from nursing homes ) , the best predictors were the modified BTS severity score ( sensitivity 94.3 % ) and the PSI and CURB score ( sensitivity 83.3 % for both ) . Conclusions : Different severity scores have different strengths and weaknesses as prediction tools . Validation should be done in the most relevant clinical setting , using more appropriate constructs of “ severe pneumonia ” to ensure that these potentially useful tools truly deliver what clinicians expect of them Background : A study was undertaken to vali date the modified American Thoracic Society ( ATS ) rule and two British Thoracic Society ( BTS ) rules for the prediction of ICU admission and mortality of community acquired pneumonia and to provide a validation of these predictions on the basis of the pneumonia severity index ( PSI ) . Method : Six hundred and ninety six consecutive patients ( 457 men ( 66 % ) , mean ( SD ) age 67.8 ( 17.1 ) years , range 18–101 ) admitted to a tertiary care hospital were studied prospect ively . Of these , 116 ( 16.7 % ) were admitted to the ICU . Results : The modified ATS rule achieved a sensitivity of 69 % ( 95 % CI 50.7 to 77.2 ) , specificity of 97 % ( 95 % CI 96.4 to 98.9 ) , positive predictive value of 87 % ( 95 % CI 78.3 to 93.1 
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Conclusions New severity scores for predicting the need for ICU or intensive treatment in patients with CAP , such as ATS/IDSA 2007 minor criteria , SCAP score , and SMART-COP , have better discriminative performances compared with PSI and CURB-65 .
High negative predictive value is the most consistent finding among the different prediction rules .