***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: BACKGROUND Patients ' deaths in the ICU have been associated with a high burden of psychologic symptoms in families . This study identifies characteristics associated with psychologic symptoms in family members . METHODS Families of patients dying in the ICU or within 30 h of ICU discharge in 11 hospitals previously participated in a r and omized trial . In the current study , we assessed these families for symptoms of posttraumatic stress disorder ( PTSD ) and depression with follow-up surveys . Outcomes included vali date d measures of PTSD ( PTSD Checklist ) and depressive ( Patient Health Question naire ) symptoms . Predictors included family member mental-health history , involvement in decision making , and demographics . RESULTS Surveys were completed by 226 families . Response rate was 46 % in the original r and omized trial and 82 % in this study . Prevalence ( 95 % CI ) of PTSD and depressive symptoms were 14.0 % ( 9.7%-19.3 % ) and 18.4 % ( 13.5%-24.1 % ) , respectively . Family characteristics associated with increased symptoms included : female gender ( PTSD , P = .020 ; depression , P = .005 ) , knowing the patient for a shorter duration ( PTSD , P = .003 ; depression , P = .040 ) , and discordance between family members ' preferences for decision making and their actual decision-making roles ( PTSD , P = .005 ; depression , P = .049 ) . Depressive symptoms were also associated with lower educational level ( P = .002 ) . Families with psychologic symptoms were more likely to report that access to a counselor ( PTSD , P < .001 ; depression , P = .003 ) and information about spiritual services might have been helpful while the patient was in the ICU ( PTSD , P = .024 ; depression , P = .029 ) . CONCLUSIONS Families demonstrated a high prevalence of psychologic symptoms after a death in the ICU . Characteristics associated with symptoms may help target interventions to reduce these symptoms . TRIAL REGISTRATION clinical trials.gov ; Identifier : NCT00685893 OBJECTIVES To analyze the utilization of intensive care unit ( ICU ) days in a Canadian medical-surgical ICU and to identify ICU patients with prolonged ICU length of stay ( LOS ) .  DESIGN Prospect i ve descriptive study . SETTING A Canadian tertiary care medical-surgical ICU . PATIENTS Consecutive patients admitted to an adult medical-surgical ICU . Neurosurgical , cardiac surgical , and coronary care unit patients were excluded . MEASUREMENTS For each ICU admission , patient demographics , diagnosis , Acute Physiology and Chronic Health Evaluation II ( APACHE II ) score , ICU LOS , and hospital mortality were collected . The patients ' risk of death was calculated using the APACHE II equation . Admissions were stratified by ICU LOS into four groups : 1 to 2 , 3 to 6 , 7 to 13 , and > or = 14 days . Among the four LOS groups , the number of ICU days and observed and predicted death rates were compared . Admissions were also stratified by risk of death into five probability range quintiles . Among the five risk groups , ICU LOS was compared between survivors and nonsurvivors . RESULTS A total of 1,960 admissions utilized 9,298 ICU days . ICU LOS ( mean + /- SEM ) was 4.74 + /- 0.2 ( median , 2 ; range , 1 to 178 ) days . Short-stay patients ( ICU LOS < or = 2 days ) accounted for 60.3 % of total admissions but consumed only 16.4 % of total ICU days . Long-stay patients ( ICU LOS > or = 14 days ) accounted for 7.3 % of total admissions but consumed 43.5 % of total ICU days . Among the long-stay patients , the most common reasons for admission were pneumonia , multiple trauma , neuromuscular weakness , and septic shock . The mortality for long-stay patients approached 50 % . When analyzed by patients ' mortality risks , those with a risk of death > 0.8 ( predicted to die ) or < 0.2 ( predicted to live ) whose outcomes were opposite to that predicted had twice the ICU LOS compared with patients whose outcomes were consistent with prediction . CONCLUSION In a Canadian medical-surgical ICU , patients with ICU LOS > or = 14 days accounted for 7.3 % of total admissions but consumed 43.5 % of total ICU days . Identification of patients with prolonged ICU LOS who would ultimately die in the ICU may lead to earlier withdrawal of therapy in these patients , result ing in a substantial reduction in suffering and cost savings . In our study population , outcome prediction using the APACHE II equation did not provide sufficient power to accurately discriminate between nonsurvivors and survivors Objective : To revise and up date the Acute Physiology and Chronic Health Evaluation ( APACHE ) model for predicting intensive care unit ( ICU ) length of stay . Design : Observational cohort study . Setting : One hundred and four ICUs in 45 U.S. hospitals . Patients : Patients included 131,618 consecutive ICU admissions during 2002 and 2003 , of which 116,209 met inclusion criteria . Interventions : None . Measurements and Main Results : The APACHE IV model for predicting ICU length of stay was developed using ICU day 1 patient data and a multivariate linear regression procedure to estimate the precise ICU stay for r and omly selected patients who comprised 60 % of the data base . New variables were added to the previous APACHE III model , and advanced statistical modeling techniques were used . Accuracy was assessed by comparing mean observed and mean predicted ICU stay for the excluded 40 % of patients . Aggregate mean observed ICU stay was 3.86 days and mean predicted 3.78 days ( p < .001 ) , a difference of 1.9 hrs . For 108 ( 93 % ) of 116 diagnoses , there was no significant difference between mean observed and mean predicted ICU stay . The model accounted for 21.5 % of the variation in ICU stay across individual patients and 62 % across ICUs . Correspondence between mean observed and mean predicted length of stay was reduced for patients with a short ( ≤1.7 days ) or long ( ≥9.4 days ) ICU stay and a low ( < 20 % ) or high ( > 80 % ) risk of death on ICU day 1 . Conclusions : The APACHE IV model provides clinical ly useful ICU length of stay predictions for critically ill patient groups , but its accuracy and utility are limited for individual patients . APACHE IV benchmarks for ICU stay are useful for assessing the efficiency of unit throughput and support examination of structural , managerial , and patient factors that affect ICU stay BACKGROUND Ten percent to 20 % of trauma patients admitted to the intensive care unit ( ICU ) will die from their injuries . Providing appropriate end-of-life care in this setting is difficult and often late in the patients ' course . Patients are young , prognosis uncertain , and conflict common around goals of care . We hypothesized that early , structured communication in the trauma ICU would improve end-of-life care practice . METHODS Prospect i ve , observational , prepost study on consecutive trauma patients admitted to the ICU before and after a structured palliative care intervention was integrated into st and ard ICU care . The program included part I , early ( at admission ) family bereavement support , assessment of prognosis , and patient preferences , and part II ( within 72 hours ) interdisciplinary family meeting . Data on goals of care discussion s , do-not-resuscitate ( DNR ) orders and withdrawal of life support ( W/D ) were collected from physician rounds , family meetings , and medical records . RESULTS Eighty-three percent of patients received part I and 69 % part II intervention . Discussion of goals of care by physicians on rounds increased from 4 % to 36 % of patient-days . During intervention , rates of mortality ( 14 % ) , DNR ( 43 % ) , and W/D ( 24 % ) were unchanged , but DNR orders and W/D were instituted earlier in hospital course . ICU length of stay was decreased in patients who died . CONCLUSIONS Structured communication between physician and families result ed in earlier consensus around goals of care for dying trauma patients . Integration of early palliative care alongside aggressive trauma care can be accomplished without change in mortality and has the ability to change the culture of care in the trauma ICU Flaws in the design , conduct , analysis , and reporting of r and omised trials can cause the effect of an intervention to be underestimated or overestimated . The Cochrane Collaboration ’s tool for assessing risk of bias aims to make the process clearer and more STUDY OBJECTIVES To assess the impact of a proactive case finding approach to end-of-life care for critically ill patients experiencing global cerebral ischemia ( GCI ) after cardiopulmonary resuscitation and multiple organ system failure ( MOSF ) in comparison to historical control subjects . DESIGN Comparative study of retrospective and prospect i ve cohorts . SETTING Medical ICU of a university hospital . INTERVENTIONS Patterns of end-of life care for patients with MOSF and GCI obtained through a retrospective chart review  were compared to proactive case finding facilitated by the inpatient palliative care service . Interventions included identification of patient 's advance directives or preferences about end-of life care , if any ; assistance with discussion of the prognosis and treatment options with patients or their surrogates ; and implementation of palliative care strategies when treatment goals changed to a focus on comfort measures . RESULTS Although our retrospective data demonstrated a high percentage of do-not-resuscitate decisions for the patients under investigation , a considerable time lag elapsed between identification of the poor prognosis and the establishment of end-of-life treatment goals ( 4.7 + /- 2.4 days and 3.5 + /- 0.5 days for patients with MOSF and GCI , respectively [ mean + /- SE ] ) . The proactive case finding approach decreased hospital length of stay ( mean , 20.6 + /- 4.1 days vs 15.1 + /- 2.5 days and 8.6 + /- 1.6 days vs 4.7 + /- 0.6 days for MOSF and GCI patients , respectively ; p = 0.063 and < 0.001 , respectively ) . More importantly , a proactive palliative care intervention decreased the time between identification of the poor prognosis and the establishment of comfort care goals ( 7.3 + /- 2.9 days vs 2.2 + /- 0.8 days and 6.3 + /- 1.2 days vs 3.5 + /- 0.4 days for MOSF and GCI patients , respectively ; p < 0.05 for both ) , decreased the time dying patients  with MOSF remained in the ICU , and reduced the use of nonbeneficial re sources , thus reducing the cost of care . CONCLUSIONS Proactive interventions from a palliative care consultant within this subset of patients decreased the use of nonbeneficial re sources and avoided protracted dying PURPOSE We sought to determine the effects of a communication process that was design ed to encourage the use of advanced supportive technology when it is of benefit , but to limit its burdens when it is ineffective . We compared usual care with a proactive , multidisciplinary method of communicating that prospect ively identified for patients and families the criteria that would determine whether a care plan was effective at meeting the goals of the patient . This process allowed caregivers to be informed of patient preferences about continued advanced supportive technology when its continuation would result in a compromised functional outcome or death . MATERIAL S AND METHODS We performed a before- and -after study in 530 adult medical patients who were consecutively admitted to a university tertiary care hospital for intensive care .  Multidisciplinary meetings were held within 72 hours of critical care admission . Patients , families , and the critical care team discussed the care plan and the patients ' goals and expectations for the outcome of critical care . Clinical " milestones " indicative of recovery were identified with time frames for their occurrence . Follow-up meetings were held to discuss palliative care options when continued advanced supportive technology was not achieving the patient 's goals . We measured length of stay , mortality , and provider team and family consensus in 134 patients before the intensive communication intervention and in 396 patients after the intervention . RESULTS Intensive communication significantly reduced the median length of stay from 4 days ( interquartile range , 2 to 11 days ) to 3 days ( 2 to 6 days , P = 0.01 by survival analysis ) . This reduction remained significant after adjustment for acute physiology and chronic health evaluation ( APACHE ) 3 score [ risk ratio ( RR ) = 0.81 ; 95 % confidence interval ( CI ) , 0.66 to 0.99 ; P = 0.04 ) . Subgroup analysis revealed that this reduction occurred in our target group , patients with acuity scores in the highest quartile who died ( RR = 0.60 ; 95 % CI , 0.38 to 0.92 ; P = 0.02 ) . The intervention , which allowed dying patients earlier access to palliative care , was not associated with increased mortality . CONCLUSIONS Intensive communication was associated with a reduction in critical care use by patients who died . Our multidisciplinary process targeted advanced supportive technology to patients who survived and allowed the earlier withdrawal of advanced supportive technology when it was ineffective CONTEXT Patients , families , and surgeons often have high expectations of life-saving surgery following liver transplantation ( LT ) , despite the presence of a severe life-limiting underlying illness . Hence , transition from curative to palli 
    Output:
    
There was no difference in mortality rate in ICU and hospital between the protocol ized intervention and control groups .
Conclusions Protocol ized family support intervention for enhanced communication and shared decision-making with the family reduced ICU LOS in critically ill patients without impacting mortality