***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: In clinical measurement comparison of a new measurement technique with an established one is often needed to see whether they agree sufficiently for the new to replace the old . Such investigations are often analysed inappropriately , notably by using correlation coefficients . The use of correlation is misleading . An alternative approach , based on graphical techniques and simple calculations , is described , together with the relation between this analysis and the assessment of repeatability Background Synthesis of multiple r and omized controlled trials ( RCTs ) in a systematic review can summarize the effects of individual outcomes and provide numerical answers about the effectiveness of interventions . Filtering of search es is time consuming , and no single method fulfills the principal requirements of speed with accuracy . Automation of systematic review s is driven by a necessity to expedite the availability of current best evidence for policy and clinical decision-making . We developed Rayyan ( http://rayyan.qcri.org ) , a free web and mobile app , that helps expedite the initial screening of abstract s and titles using a process of semi-automation while incorporating a high level of usability . For the beta testing phase , we used two published Cochrane review s in which included studies had been selected manually . Their search es , with 1030 records and 273 records , were uploaded to Rayyan . Different features of Rayyan were tested using these two review s. We also conducted a survey of Rayyan ’s users and collected feedback through a built-in feature . Results Pilot testing of Rayyan focused on usability , accuracy against manual methods , and the added value of the prediction feature . The “ taster ” review ( 273 records ) allowed a quick overview of Rayyan for early comments on usability . The second review ( 1030 records ) required several iterations to identify the previously identified 11 trials . The “ suggestions ” and “ hints , ” based on the “ prediction model , ” appeared as testing progressed beyond five included studies . Post rollout user experiences and a reflexive response by the developers enabled real-time modifications and improvements . The survey respondents reported 40 % average time savings when using Rayyan compared to others tools , with 34 % of the respondents reporting more than 50 % time savings . In addition , around 75 % of the respondents mentioned that screening and labeling studies as well as collaborating on review s to be the two most important features of Rayyan . As of November 2016 , Rayyan users exceed 2000 from over 60 countries conducting hundreds of review s totaling more than 1.6 M citations . Feedback from users , obtained mostly through the app web site and a recent survey , has highlighted the ease in exploration of search es , the time saved , and simplicity in sharing and comparing include-exclude decisions . The strongest features of the app , identified and reported in user feedback , were its ability to help in screening and collaboration as well as the time savings it affords to users . Conclusions Rayyan is responsive and intuitive in use with significant potential to lighten the load of review ers Background Sepsis is a common condition in the emergency department ( ED ) . Lactate measurement is an important part of management : arterial lactate ( A-LACT ) measurement is the gold st and ard . There is increasing use of peripheral venous lactate ( PV-LACT ) ; however , there is little research supporting the interchangeability of the two measures . If PV-LACT has good agreement with A-LACT , it would significantly reduce patient discomfort and the risks of arterial sampling for a large group of acutely unwell patients , while allowing faster and wider screening , with potential reduced costs to the healthcare system . Objective The aim of this study is to determine the agreement between PV-LACT and A-LACT in septic patients attending the ED . Methods We carried out a prospect i ve observational cohort study of 304 consented patients presenting with sepsis to a single UK NHS ED ( 110 000 adult attendances annually ) taking paired PV-LACT and A-LACT . Bl and –Altman analysis was carried out to determine agreement . Receiver operating characteristic curves and 2 × 2 tables were constructed to explore the predictive value of PV-LACT for A-LACT . Results The mean difference ( PV-LACT−A-LACT ) is 0.4 mmol/l [ 95 % confidence interval ( CI ) : 0.37–0.45 ] , with 95 % limits of agreement from −0.4 ( 95 % CI : −0.45 to −0.32 ) to 1.2 ( 95 % CI : 1.14–1.27 ) . A PV-LACT of at least 2 mmol/l predicts an A-LACT of at least 2 with 100 % sensitivity ( 95 % CI : 89–100 % ) and 83 % specificity ( 95 % CI : 77–87 % ) . Conclusion This study is the largest comparing the two measurements , and shows good clinical agreement . We recommend using PV-LACT in the routine screening of septic patients .  A PV-LACT less than 2 mmol/l is predictive of an A-LACT less than 2 mmol/l Introduction In the emergency department ( ED ) , lactate is routinely used for risk stratification . Whether venous or arterial lactate measured on blood gas is interchangeable is not known . We hypothesized that venous lactate can be used instead of arterial lactate for the evaluation of acute patients in the ED . Patients and methods This was a prospect i ve single-center study . All patients requiring a lactate measurement were enrolled and we simultaneously drew arterial and venous blood . We followed up all patients to hospital discharge . Our primary aim was to evaluate agreements between the two measurements using Bl and and Altman plots with the report of bias ( mean difference ) and limits of agreements . We also aim ed to determine the rate of misclassification ( defined as one measurement<1.8 mmol/l and the other>2.2 ) . Our secondary aim was to evaluate their respective prognostic value to predict in-hospital death or admission in the ICU longer than 72 h. Results The mean age of the 132 analyzed patients was 62 years ( SD : 18 years ) , and 59 % were men .  The mean difference ( bias ) between arterial and venous lactate was −0.6 mmol/l ( limits of agreement : −1.7 to 0.6 mmol/l ) . The rate of misclassification was 8 % ( 95 % confidence interval : 3–2 % ) . Both methods present similar performances for the prediction of poor outcomes , with an area under the receiving operator characteristic curves of 0.67 for both . Results were similar when focused only on septic patients . Conclusion Venous and arterial lactates do not agree well , and there is a high misclassification rate . Venous lactate does not appear to be interchangeable with arterial sampling OBJECTIVE We evaluate the capacity of arterial ( ABL ) , peripheral venous ( VBL ) , and capillary ( CBL ) blood lactate concentration to early detect the presence of severe sepsis in patients admitted to the emergency department for a septic syndrome . METHODS Patients with signs of sepsis presenting to the emergency department were prospect ively enrolled .  Blood lactate  was measured using a h and held point-of-care analyzer on micro sample s of arterial , peripheral venous , and capillary blood . An arterial blood sample was dispatched to the central laboratory as a reference measurement . RESULTS A total of 103 patients were enrolled in the study , with 63 patients presenting with a severe sepsis . There was a strong correlation between the point of care and the reference blood lactate measurement . The CBL , VBL , and ABL were all significantly different ( 3.01±0.29 , 2.51±0.21 , and 2.03±0.18 mmol/L , respectively ; P<.001 ) . The VBL value was the most efficient to detect early the presence of severe sepsis ( areas under the receiver operating characteristic curves were 0.85±0.04 , 0.76±0.05 , and 0.75±0.05 for VBL , ABL , and CBL , respectively ; P<.01 ) . Mortality at 28 days was related to the severity of sepsis ( 28.6 % vs 7.5 % ) and to the number or organ dysfunctions ( P<.01 ) . Arterial blood lactate , VBL , and CBL were all significantly associated with the 28th-day mortality . CONCLUSIONS Initial VBL may be used efficiently to assess the severity of sepsis , and it could even be more effective than ABL and CBL to early detect the presence of severe sepsis OBJECTIVE We aim ed to generate equation to predict arterial lactate ( a-Lac ) using venous lactate ( v-Lac ) and other lab data . METHODS A prospect i ve cross-sectional study was conducted on emergency patients in the emergency department for 6 months at a general hospital in Tokyo , Japan . We collected  arterial and venous gas analysis data . Patients were eligible for entry into the study if an arterial blood gas analysis was required for appropriate diagnostic care by the treating physician . Univariate linear regression analysis was conducted to generate an equation to calculate a-Lac incorporating only v-Lac . A multivariate forward stepwise logistic regression model ( p-value of 0.05 for entry , 0.1 for removal ) was used to generate an equation including v-Lac and other potentially relevant variables . Bl and -Altman plot was drawn and the two equations were compared for model fitting using R-squares . RESULTS Seventy-two arterial sample s from 72 participants ( 61 % male ; mean age , 58.2 years ) were included in the study . An initial regression equation was derived from univariate linear regression analysis : " ( a-Lac ) = -0.259 + ( v-Lac ) × 0.996 " . Subsequent multivariate forward stepwise logistic regression analysis , incorporating v-Lac and Po2 , generated the following equation:"(a-Lac ) = -0.469+(venous Po2 ) × 0.005 + ( v-Lac ) × 0.997 " . Calculated R-squares by single and multiple regression were 0.94 and 0.96 , respectively . CONCLUSION v-Lac estimates showed a high correlation with arterial values and our data provide two clinical ly useful equations to calculate a-Lac from v-Lac data . Considering clinical flexibility , " Lac = -0.259 + v-Lac × 0.996 " might be more useful while avoiding a time-consuming and invasive procedure Objectives Lactate measurements are routinely carried out in emergency departments and are associated with increased mortality in septic patients . However , no definitive research has been carried out into whether lactate measurements can be used as a prognostic marker in a clinical ly unwell population in the emergency department . Methods We carried out a prospect i ve observational cohort study in consecutive patients whose arterial lactate concentration was measured in the emergency department of a tertiary referral hospital assessing 110 000 patients per year between 11th May and 11th August 2011 . The main outcome measure was 30-day mortality . Results There were 120 deaths ( 16.1 % ) at 30 days postattendance in our cohort of 747 patients . Multivariate logistic regression revealed lower lactate levels were associated with 30-day survival : ORs for 30-day death compared with lactate ≥4 were 0.125 ( 95 % CI 0.068 to 0.229 ) for lactate < 2 and 0.273 ( 95 % CI 0.140 to 0.533 ) for lactate 2–<4 . Kaplan – Meier analysis showed a survival difference when dividing lactate concentrations into strata ( p<0.0001 ) . This survival difference was maintained when septic diagnoses were taken into account . Conclusions A single arterial lactate measurement on presentation to the emergency department predicts 30-day mortality independent of other measures of illness severity Objectives : This study aim ed to compare the prognostic value of lactate level and lactate clearance at 6 hours after septic shock recognition . And , we performed it to determine lactate kinetics in the Sepsis-3 defined septic shock . Design : This retrospective study was performed from a prospect i ve septic shock registry . Setting s : This study was performed at single urban tertiary center . And , all patients were treated with protocol -driven resuscitation bundle therapy between 2010 and 2016 . Patients : We included septic shock patients who met the Sepsis-3 definition , which involves lactate levels greater than or equal to 2 mmol/L and vasopressor use . Interventions :  Serum lactate levels  were measured at initial and 6 hours from septic shock recognition . Measurements and Main Results : Lactate clearance was calculated as ( [ initial lactate – 6-hr lactate]/initial lactate ) × 100 . The prognostic value of measured lactate levels and lactate clearance for 28-day mortality was analyzed and compared with that of subsequent lactate levels greater than or equal to 2 mmol/L , greater than or equal to 3 mmol/L , and greater than or equal to 4 mmol/L and less than 10 % , less than 20 % , and less than 30 % lactate clearance . A total of 1,060 septic shock patients by Sepsis-3 , 265 patients died ( 28-d mortality : 25 % ) . In survivor , groups had lower median 6-hour lactate level and higher lactate clearance than nonsurvivors ( 2.5 vs 4.6 mmol/L and 35.4 % vs 14.8 % ; p < 0.01 ) . Both lactate and lactate clearance were associated with mortality after adjusting for confounders ( odd ratio , 1.27 [ 95 % CI , 1.21–1.34 ] and 0.992 [ 95 % CI , 0.9 
    Output:
    
Importantly , poorer agreement occurs in hyperlactatemia .
Conclusion : Agreement between arterial and peripheral venous lactate is poor in hyperlactatemia , making peripheral venous lactate an unreliable parameter to use interchangeably in the ED .
In clinical practice , peripheral venous lactate can be used as a screening tool to rule out arterial hyperlactatemia at a cut‐off value of 2 mmol/l .
However , hyperlactatemia should be confirmed using arterial sampling in case of a peripheral venous lactate level > 2 mmol/l