***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 
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    Input: Abstract Introduction Low-dose hydrocortisone treatment is widely accepted therapy for the treatment of vasopressor-dependent septic shock . The question of whether corticosteroids should be given to septic shock patients by continuous or by bolus infusion is still unanswered . Hydrocortisone induces hyperglycemia and it is possible that continuous hydrocortisone infusion would reduce the fluctuations in blood glucose levels and that tight blood glucose control could be better achieved with this approach . Methods In this prospect i ve r and omized study , we compared the blood glucose profiles , insulin requirements , amount of nursing workload needed , and shock reversal in 48 septic shock patients who received hydrocortisone treatment either by bolus or by continuous infusion with equivalent dose ( 200 mg/day ) . Duration of hydrocortisone treatment was five days . Results The mean blood glucose levels were similar in the two groups , but the number of hyperglycemic episodes was significantly higher in those patients who received bolus therapy ( 15.7 ± 8.5 versus 10.5 ± 8.6 episodes per patient , p = 0.039 ) . Also , more changes in insulin infusion rate were needed to maintain strict normoglycemia in the bolus group ( 4.7 ± 2.2 versus 3.4 ± 1.9 adjustments per patient per day , p = 0.038 ) . Hypoglycemic episodes were rare in both groups . No difference was seen in shock reversal . ConclusionS trict normoglycemia is more easily achieved if the hydrocortisone therapy is given to septic shock patients by continuous infusion . This approach also reduces nursing workload needed to maintain tight blood glucose control . Trial Registration Number IS RCT CONTEXT AND OBJECTIVE Sepsis and septic shock are very common conditions among critically ill patients that lead to multiple organ dysfunction syndrome ( MODS ) and death . Our purpose was to investigate the efficacy of early administration of dexamethasone for patients with septic shock , with the aim of halting the progression towards MODS and death . DESIGN AND SETTING Prospect i ve , r and omized , double-blind , single-center study , developed in a surgical intensive care unit at Hospital das Clínicas , Faculdade de Medicina da Universidade de São Paulo . METHODS The study involved 29 patients with septic shock . All eligible patients were prospect ively r and omized to receive either a dose of 0.2 mg/kg of dexamethasone ( group D ) or placebo ( group P ) , given three times at intervals of 36 hours . The patients were monitored over a seven-day period by means of the sequential organ failure assessment score . RESULTS Patients treated with dexamethasone did not require vasopressor therapy for as much time over the seven-day period as did the placebo group ( p = 0.043 ) . Seven-day mortality was 67 % in group P ( 10 out of 15 ) and 21 % in group D ( 3 out of 14 ) ( relative risk = 0.31 , 95 % confidence interval 0.11 to 0.88 ) . Dexamethasone enhanced the effects of vasopressor drugs . CONCLUSIONS Early treatment with dexamethasone reduced the seven-day mortality among septic shock patients and showed a trend towards reduction of 28-day mortality There is considerable debate regarding the choice of test for treatment difference in a r and omized clinical trial in the presence of competing risks . This question arose in the study of st and ard  and new antiepileptic drugs ( SANAD ) trial comparing new and st and ard antiepileptic drugs .  This paper provides simulation results for the log-rank test comparing cause-specific hazard rates and Gray 's test comparing cause-specific cumulative incidence curves . To inform the analysis of the SANAD trial , competing-risks setting s were considered where both events are of interest , events may be negatively correlated , and the degree of correlation may differ in the 2 treatment groups . In setting s where there are effects in opposite directions for the 2 event types , a likely situation for the SANAD trial , Gray 's test has greater power to detect treatment differences than log-rank analysis . For the epilepsy application , conclusions were qualitatively similar for both log-rank and Gray 's tests Background The heterogeneity statistic I2 , interpreted as the percentage of variability due to heterogeneity between studies rather than sampling error , depends on precision , that is , the size of the studies included . Methods Based on a real meta- analysis , we simulate artificially ' inflating ' the sample size under the r and om effects model . For a given inflation factor M = 1 , 2 , 3 , ... and for each trial i , we create a M-inflated trial by drawing a treatment effect estimate from the r and om effects model , using si2MathType@MTEF@5@5@+=feaagaart1ev2aaatCvAUfKttLearuWrP9MDH5MBPbIqV92AaeXatLxBI9gBaebbnrfifHhDYfgasaacPC6xNi = xH8viVGI8Gi = hEeeu0xXdbba9frFj0xb9qqpG0dXdb9aspeI8k8fiI+fsY = rqGqVepae9pg0db9vqaiVgFr0xfr = xfr = xc9adbaqaaeGaciGaaiaabeqaaeqabiWaaaGcbaGaem4Cam3aa0baaSqaaiabdMgaPbqaaiabikdaYaaaaaa@2FBE@/M as within-trial sampling variance . Results As precision increases , while estimates of the heterogeneity variance τ2 remain unchanged on average , estimates of I2 increase rapidly to nearly 100 % . A similar phenomenon is apparent in a sample of 157 meta-analyses . Conclusion When deciding whether or not to pool treatment estimates in a meta- analysis , the yard-stick should be the clinical relevance of any heterogeneity present . τ2 , rather than I2 , is the appropriate measure for this purpose Context Clinicians rely on systematic review s for current , evidence -based information . Contribution This survival analysis of 100 meta-analyses indexed in ACP Journal Club from 1995 to 2005 found that new evidence that substantively changed conclusions about the effectiveness or harms of therapies arose frequently and within relatively short time periods . The median survival time without substantive new evidence for the meta-analyses was 5.5 years . Significant new evidence was already available for 7 % of the review s at the time of publication and became available for 23 % within 2 years . Implication Clinical ly important evidence that alters conclusions about the effectiveness and harms of treatments can accumulate rapidly . The Editors Systematic review s have become increasingly common in recent years ( 1 ) and are recommended by many as the best sources of evidence to guide both clinical decisions ( 2 ) and health care policy ( 3 ) . For systematic review s to fulfill these roles , their findings must remain relatively stable for at least several years or effective mechanisms must exist for alerting end users to important changes in evidence . Yet , surprisingly little research has assessed the extent to which systematic review s become out of date or the rate at which this occurs ( 47 ) . Some organizations , such as the Cochrane Collaboration , recommend updating systematic review s every 2 years , but few empirical data guide this or other recommendations about updating . We sought to determine how quickly systematic review s meet explicitly defined criteria for changes in evidence of sufficient importance to warrant updating . We also sought to identify predictors of survival time , the time to such important changes in evidence . Survival time might vary depending on many factors , including the type of question posed by the original review ( for example , therapeutic or diagnostic ) , the types of studies included ( for example , r and omized trials or observational studies ) , and whether the systematic review provided quantitative synthesis . To limit such variation , we focused on systematic review s of r and omized , controlled trials that evaluated therapeutic benefit or harm by providing quantitative synthesis ( meta- analysis ) for at least 1 outcome . Methods Study Design and Sample We used a quasi-r and om process ( alphabetical sort order by author ) to select 100 systematic review s that were indexed in ACP Journal Club with an accompanying commentary between January 1995 and December 2005 ( with a search date no later than 31 December 2004 to ensure at least 1 full year for new evidence to appear ) . We chose this sampling frame because ACP Journal Club selects systematic review s that meet explicit quality st and ards and are deemed directly relevant to clinical practice ( 8) . We regarded the sample size of 100 as sufficiently large to achieve suitably narrow confidence intervals and to permit evaluation of up to 5 potential predictors of survival . Eligibility Criteria Eligible review s evaluated the benefit or harm of a specific drug , class of drug , device , or procedure ( invasive procedure or surgery ) and included r and omized or quasi-r and omized , controlled trials . We excluded evaluations of alternative and complementary medicines because the stability of review s of such therapies might differ substantially from review s of conventional therapies . We required that review s provide a point estimate and 95 % confidence interval for at least 1 outcome in the form of a relative risk , odds ratio , or absolute risk difference for binary outcomes and weighted mean differences for continuous outcomes . We excluded meta-analyses of individual-patient data , meta-regressions , and indirect meta-analyses because of the difficulty of determining whether new data would alter previous quantitative results . Two team members independently assessed eligibility , with disagreements resolved by consensus involving a third review er . When more than 1 review on the same topic was identified , only the earliest was included . Search ing For each review , search es for new trials included identifying new systematic review s on the same topic , su bmi tting relevant content terms to the Clinical Queries function in Ovid , applying the Related Articles function in PubMed to the 3 largest and the 3 most recent trials in the original review ( up to 6 trials in total ) , and using Scopus ( www . scopus .com/ scopus /home.url ) to identify new r and omized trials that cited the original review . When these search strategies yielded no eligible new trials , we conducted more comprehensive electronic search es and review ed relevant chapters in such sources as Clinical Evidence and UpTo Date to ensure that we had not missed new trials . Team members who had background s in both medicine and clinical research screened citations retrieved by the preceding methods to identify trials that would have met the inclusion criteria in the original review . Retrieved articles were screened in chronological order to ascertain quantitative or qualitative signals for the need for updating . The review protocol stopped when any criteria for updating were met . Each systematic review was discussed in detail , with the final statussignal for updating was or was not detectedadjudicated by consensus ( Figure 1 ) . Figure 1 . Overall process for determining updating status . ACP Journal Club Signals for the Need to Up date Systematic Review s In design ing criteria for comparing new findings with those in a previous review , we adapted methods used by other investigators to address similar problems with comparing 2 sets of results relating to the same question ( 913 ) , such as r and omized and nonr and omized studies of the same intervention . These investigators identified conflicting findings among different publications using a combination of quantitative thresholds for differences in effect magnitude and qualitative judgments about the language used to describe the results . We have similarly conceptualized quantitative and qualitative signals of potential changes in evidence that are sufficiently important to warrant updating previous systematic review s. Quantitative Signals Quantitative signals consisted of a change in statistical significance or relative change in effect magnitude of at least 50 % . We restricted these changes to those involving 1 of the primary outcomes of the original review or any mortality outcome . We also ignored trivial changes in statistical significance when the original and up date d meta-analytic results both had P values between 0.04 and 0.06so that quantitative signals of changes in evidence would represent robust indicators of the need to up date previous review s. Quantitative signals were detected by combining data from eligible new trials with the previous results using a fixed-effects approach . Use of fixed-effect models allowed pooling of the new trials with the previous meta-analytic result , as opposed to having to obtain original data from all of the included trials in each of 100 systematic review s. Although r and om-effects models are usually preferred to avoid spurious precision in the face of heterogeneity , our goal was to detect potential changes in evidence that would warrant a formal up date , not produce exact estimates of the up date d results . Qualitative Signals Qualitative signals included new information about harm sufficient to affect clinical decision making , important caveats to the original results , emergence of a superior alternate therapy , and important changes in certainty or direction of effect . Qualitative signals were detected by using explicit criteria for comparing the language in the original review with descriptions of findings in new systematic review s that addressed the same topic , pivotal trials , clinical practice guidelines , or recent editions of major textbooks ( for example , UpTo Date ) . Pivotal trials were defined as trials that had a sample size at least 3 times larger than that of the previous largest trial or were published in 1 of the 5 highest-impact general medical journals ( The New Engl and Journal of Medicine , Lancet , Journal of the American Medical Association , Annals of Internal Medicine , and the British Medical Journal ) . We defined 2 levels of importance for qualitative signals : potentially invalidating changes in evidence , which would make one no longer want clinicians or policymakers to base decisions on the original findings ( such as a pivotal trial that characterized treatment effectiveness in terms opposite of those in the original systematic review ) , and major changes in evidence , which would affect clinical decision making in important ways without invalidating the previous results ( such as the identification of patient population s for whom treatment is more or less beneficial ) . Major changes also included differing characterizations of effectiveness that were less extreme than those for potentially invalidating signals but that would still affect clinical decision making ( for example , a change from possibly beneficial to definitely beneficial ) . Of importance , such characterizations as possibly effective , probably effective , and promising , were all categorized as possibly effective . Thus , qualitative signals for changes in evidence captured substantive differences in the characterization of treatment effects , not merely semantic differences . Full definitions for each of the specific 
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Odds of complications were not increased with corticosteroids .
Conclusions Although a null effect for mortality treatment efficacy of low dose corticosteroid therapy in severe sepsis and septic shock was not excluded , there remained a high probability of treatment efficacy , more so with outlier exclusion .
Similarly , although a null effect was not excluded , advantageous effects of low dose steroids had a high probability of dependence upon patient underlying risk .
Low dose steroid efficacy was not demonstrated in corticotrophin non-responders .