***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: The objective of this study was to refine the APACHE ( Acute Physiology , Age , Chronic Health Evaluation ) methodology in order to more accurately predict hospital mortality risk for critically ill hospitalized adults . We prospect ively collected data on 17,440 unselected adult medical/surgical intensive care unit ( ICU ) admissions at 40 US hospitals ( 14 volunteer tertiary-care institutions and 26 hospitals r and omly chosen to represent intensive care services nationwide ) . We analyzed the relationship between the patient 's likelihood of surviving to hospital discharge and the following predictive variables : major medical and surgical disease categories , acute physiologic abnormalities , age , preexisting functional limitations , major comorbidities , and treatment location immediately prior to ICU admission . The APACHE III prognostic system consists of two options : ( 1 ) an APACHE III score , which can provide initial risk stratification for severely ill hospitalized patients within independently defined patient groups ; and ( 2 ) an APACHE III predictive equation , which uses APACHE III score and reference data on major disease categories and treatment location immediately prior to ICU admission to provide risk estimates for hospital mortality for individual ICU patients . A five-point increase in APACHE III score ( range , 0 to 299 ) is independently associated with a statistically significant increase in the relative risk of hospital death ( odds ratio , 1.10 to 1.78 ) within each of 78 major medical and surgical disease categories . The overall predictive accuracy of the first-day APACHE III equation was such that , within 24 h of ICU admission , 95 percent of ICU admissions could be given a risk estimate for hospital death that was within 3 percent of that actually observed ( r2 = 0.41 ; receiver operating characteristic = 0.90 ) . Recording changes in the  APACHE III score on each subsequent day of ICU therapy provided daily up date s in these risk estimates . When applied across the individual ICUs , the first-day APACHE III equation accounted for the majority of variation in observed death rates ( r2 = 0.90 , p less than 0.0001 ) BACKGROUND The timely assessment and treatment of ICU patients is important for neurosurgeons and neurointensivists . We hypothesized that the use of RTP can improve physician rapid response to unstable ICU patients . METHODS This is a prospect i ve study using a before-after , cohort-control design to test the effectiveness of RTP .  Physicians used RTP to make rounds in the ICU in response to nursing pages . Data concerning several aspects of the RTP interaction including the latency of the response , the problem being treated , the intervention that was ordered , and the type of information gathered using the RTP were documented . The effect of RTP on ICU length of stay and cost was assessed . RESULTS The use of RTP was associated with a reduction in latency of attending physician face-to-face response for routine and urgent pages compared to conventional care ( RTP : 9.2 + /- 9.3 minutes vs conventional : 218 + /- 186 minutes ) . The response latencies to brain ischemia ( 7.8 + /- 2.8 vs 152 + /- 85 minutes ) and elevated ICP ( 11 + /- 14 vs 108 + /- 55 minutes ) were reduced ( P < .001 ) , as was the LOS for patients with SAH ( 2 days ) and brain trauma ( 1 day ) . There was an increase in ICU occupancy by 11 % compared with the prerobot era , and there was an ICU cost savings of $ 1.1 million attributable to the use of RTP . CONCLUSION The use of RTP enabled rapid face-to-face attending physician response to ICU patients and result ed in decreased ICU cost and LOS Non-r and omised studies of the effects of interventions are critical to many areas of healthcare evaluation , but their results may be biased . It is therefore important to underst and and appraise their strengths and weaknesses . We developed ROBINS-I ( “ Risk Of Bias In Non-r and omised Studies - of Interventions ” ) , a new tool for evaluating risk of bias in estimates of the comparative effectiveness ( harm or benefit ) of interventions from studies that did not use r and omisation  to allocate units ( individuals or clusters of individuals ) to comparison groups . The tool will be particularly useful to those undertaking systematic review s that include non-r and omised studies BACKGROUND Few studies have evaluated both the overall effect of ICU telemedicine programs and the effect of individual components of the intervention on clinical outcomes . METHODS The effects of nonr and omized ICU telemedicine interventions on crude and adjusted mortality and length of stay ( LOS ) were measured . Additionally , individual intervention components related to process and setting of care were evaluated for their association with mortality and LOS . RESULTS Overall , 118,990 adult patients ( 11,558 control subjects , 107,432 intervention group patients ) from 56 ICUs in 32 hospitals from 19 US health-care systems were included . After statistical adjustment , hospital ( hazard ratio [HR]=0.84 ; 95 % CI , 0.78 - 0.89 ; P<.001 ) and ICU ( HR=0.74 ; 95 % CI , 0.68 - 0.79 ; P<.001 ) mortality in the ICU telemedicine intervention group was significantly better than that of control subjects . Moreover , adjusted hospital LOS was reduced , on average , by 0.5 ( 95 % CI , 0.4 - 0.5 ) , 1.0 ( 95 % CI , 0.7 - 1.3 ) , and 3.6 ( 95 % CI , 2.3 - 4.8 ) days , and adjusted ICU LOS was reduced by 1.1 ( 95 % CI , 0.8 - 1.4 ) , 2.5 ( 95 % CI , 1.6 - 3.4 ) , and 4.5 ( 95 % CI , 1.5 - 7.2 ) days among those who stayed in the ICU for ≥7 , ≥14 , and ≥30 days , respectively . Individual components of the interventions that were associated with lower mortality , reduced LOS , or both included ( 1 ) intensivist case review within 1 h of admission , ( 2 ) timely use of performance data , ( 3 ) adherence to ICU best practice s , and ( 4 ) quicker alert response times . CONCLUSIONS ICU telemedicine interventions , specifically interventions that increase early intensivist case involvement , improve adherence to ICU best practice s , reduce response times to alarms , and encourage the use of performance data , were associated with lower mortality and LOS Objective : To improve the accuracy of the Acute Physiology and Chronic Health Evaluation ( APACHE ) method for predicting hospital mortality  among critically ill adults and to evaluate changes in the accuracy of earlier APACHE models . Design : Observational cohort study . Setting : A total of 104 intensive care units ( ICUs ) in 45 U.S. hospitals . Patients : A total of 131,618 consecutive ICU admissions during 2002 and 2003 , of which 110,558 met inclusion criteria and had complete data . Interventions : None . Measurements and Main Results : We developed APACHE IV using ICU day 1 information and a multivariate logistic regression procedure to estimate the probability of hospital death for r and omly selected patients who comprised 60 % of the data base . Predictor variables were similar to those in APACHE III , but new variables were added and different statistical modeling used . We assessed the accuracy of  APACHE IV predictions by comparing observed and predicted hospital mortality for the excluded patients ( validation set ) . We tested discrimination and used multiple tests of calibration in aggregate and for patient subgroups . APACHE IV had good discrimination ( area under the receiver operating characteristic curve = 0.88 ) and calibration ( Hosmer-Lemeshow C statistic = 16.9 , p = .08 ) . For 90 % of 116 ICU admission diagnoses , the ratio of observed to predicted mortality was not significantly different from 1.0 . We also used the validation data set to compare the accuracy of APACHE IV predictions to those using APACHE III versions developed 7 and 14 yrs previously . There was little change in discrimination , but aggregate mortality was systematic ally overestimated as model age increased . When examined across disease , predictive accuracy was maintained for some diagnoses but for others seemed to reflect changes in practice or therapy . Conclusions : APACHE IV  predictions of hospital mortality have good discrimination and calibration and should be useful for benchmarking performance in U.S. ICUs . The accuracy of predictive models is dynamic and should be periodically retested . When accuracy deteriorates they should be revised and up date OBJECTIVE To develop and vali date a new Simplified Acute Physiology Score , the SAPS II , from a large sample of surgical and medical patients , and to provide a method to convert the score to a probability of hospital mortality . DESIGN AND SETTING The SAPS II and the probability of hospital mortality were developed and vali date d using data from consecutive admissions to 137 adult medical and /or surgical intensive care units in 12 countries . PATIENTS The 13,152 patients were r and omly divided into developmental ( 65 % ) and validation ( 35 % ) sample s. Patients younger than 18 years , burn patients , coronary care patients , and cardiac surgery patients were excluded . OUTCOME MEASURE Vital status at hospital discharge . RESULTS The SAPS II includes only 17 variables : 12 physiology variables , age , type of admission ( scheduled surgical , unscheduled surgical , or medical ) , and three underlying disease variables ( acquired immunodeficiency syndrome , metastatic cancer , and hematologic malignancy ) . Goodness-of-fit tests indicated that the model performed well in the developmental sample and vali date d well in an independent sample of patients ( P = .883 and P = .104 in the developmental and validation sample s , respectively ) . The area under the receiver operating characteristic curve was 0.88 in the developmental sample and 0.86 in the validation sample . CONCLUSION The SAPS II , based on a large international sample of patients , provides an estimate of the risk of death without having to specify a primary diagnosis . This is a starting point for future evaluation of the efficiency of intensive care units CONTEXT The association of an  adult tele-intensive care unit ( ICU ) intervention  with hospital mortality , length of stay , best practice adherence , and preventable complications for an academic medical center has not been reported . OBJECTIVE To quantify the association of a tele-ICU intervention with hospital mortality , length of stay , and complications that are preventable by adherence to best practice s. DESIGN , SETTING , AND PATIENTS Prospect i ve stepped-wedge clinical practice study of 6290 adults admitted to any of 7 ICUs ( 3 medical , 3 surgical , and 1 mixed cardiovascular ) on 2 campuses of an 834-bed academic medical center that was performed from April 26 , 2005 , through September 30 , 2007 .  Electronically supported and monitored processes for best practice adherence , care plan creation , and clinician response times to alarms were evaluated . MAIN OUTCOME MEASURES Case-mix and severity-adjusted hospital mortality . Other outcomes included hospital and ICU length of stay , best practice adherence , and complication rates . RESULTS The hospital mortality rate was 13.6 % ( 95 % confidence interval [ CI ] , 11.9%-15.4 % ) during the preintervention period compared with 11.8 % ( 95 % CI , 10.9%-12.8 % ) during the tele-ICU intervention period ( adjusted odds ratio [ OR ] , 0.40 [ 95 % CI , 0.31 - 0.52 ] ) . The tele-ICU intervention period compared with the preintervention period was associated with higher rates of best clinical practice adherence for the prevention of deep vein thrombosis ( 99 % vs 85 % , respectively ; OR , 15.4 [ 95 % CI , 11.3 - 21.1 ] ) and prevention of stress ulcers ( 96 % vs 83 % , respectively ; OR , 4.57 [ 95 % CI , 3.91 - 5.77 ] , best practice adherence for cardiovascular protection ( 99 % vs 80 % , respectively ; OR , 30.7 [ 95 % CI , 19.3 - 49.2 ] ) , prevention of ventilator-associated pneumonia ( 52 % vs 33 % , respectively ; OR , 2.20 [ 95 % CI , 1.79 - 2.70 ] ) , lower rates of preventable complications ( 1.6 % vs 13 % , respectively , for ventilator-associated pneumonia [ OR , 0.15 ; 95 % CI , 0.09 - 0.23 ] and 0.6 % vs 1.0 % , respectively , for catheter-related bloodstream infection [ OR , 0.50 ; 95 % CI , 0.27 - 0.93 ] ) , and shorter hospital length of stay ( 9.8 vs 13.3 days , respectively ; hazard ratio for discharge , 1.44 [ 95 % CI , 1.33 - 1.56 ] ) . The results for medical , surgical , and cardiovascular ICUs were similar . CONCLUSION In a single academic medical center study , implementation of a tele-ICU intervention was associated with reduced adjusted odds of mortality and reduced hospital length of stay , as well as with changes in best practice adherence and lower rates of preventable complications 
    Output:
    
Conclusions : After evaluating all included studies , tele-ICU implementation was associated with an overall reduction in ICU mortality .
Subgroup analysis suggests that publications exhibiting observed to predicted ICU mortality ratios of greater than 1 before tele-ICU implementation was associated with a reduction in ICU mortality  after tele-ICU implementation .
No significant ICU mortality reduction was noted in the subgroup of observed to predicted ICU mortality ratio less than 1 before tele-ICU implementation .