***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: Introduction Delirium is a serious and prevalent problem in intensive care units ( ICUs ) . The purpose of this study was to develop a research algorithm to enhance detection of delirium in critically ill ICU patients using chart review to complement a vali date d clinical delirium instrument . Methods A prospect i ve cohort study was conducted in 178 patients aged 60 years and older who were admitted to the medical ICU . The Confusion Assessment Method for the ICU ( CAM-ICU ) and a vali date d chart review method for detecting delirium were performed daily . We assessed the diagnostic accuracy of the chart-based delirium method  using the CAM-ICU as the ' gold st and ard ' . We then used an algorithm to detect delirium first using the CAM-ICU ratings and then chart review when the CAM-ICU was unavailable . Results When using both the CAM-ICU and the chart-based review , the prevalence of delirium was found to be 80 % of patients ( 143 out of 178 ) or 64 % of patient-days ( 929 out of 1,457 ) . Of these patient-days , 292 were classified as delirium by the CAM-ICU . The remainder ( 637 patient-days ) were classified as delirium by the vali date d chart review method when CAM-ICU was missing because the assessment was conducted for weekends or holidays ( 404 patient-days ) , when CAM-ICU was not performed because of stupor or coma ( 205 patient-days ) , and when the CAM-ICU was negative ( 28 patient-days ) . Sensitivity of the chart-based method was 64 % and specificity was 85 % . Overall agreement between chart and the CAM-ICU was 72 % . Conclusion Eight out of 10 patients in this cohort study developed delirium in the ICU . Although use of a vali date d delirium instrument with frequent direct observations is recommended for clinical care , this approach may not always be feasible , especially in a research setting . The algorithm proposed here comprises a more comprehensive method for detecting delirium in a research setting , taking into account the fluctuation that occurs with delirium , which is a key component of accurate determination of delirium status . Improving detection of delirium is of paramount importance both to advance delirium research and to enhance clinical care and patient safety BACKGROUND Delirium occurs commonly among older hospitalized patients and is frequently not recognized . In an effort to identify tools useful to clinicians in the diagnosis of delirium , test characteristics of four screening instruments were compared . METHODS Patients 65 years of age or older who were admitted to one of four medical and surgical wards of a university teaching hospital were followed up prospect ively . Potential subjects were excluded if unavailable for interviews or discharged within 48 hours of admission , or if judged too impaired to participate in the daily interviews . Research assistants administered four instruments used to detect delirium : Digit Span Test , Vigilance ' A ' Test , Clinical Assessment of Confusion , and Confusion Assessment Method .  Abnormal scores on these tests or suspicion of acute confusion prompted a referral to the clinician-investigators who then assessed the patient daily for delirium based on the Diagnostic and Statistical Manual of Mental Disorders , Revised Third Edition criteria . RESULTS Delirium occurred in 64 ( 14.8 % ) of 432 subjects . The positive likelihood ratios for all of the instruments were significantly more than 1 . The instruments remained useful when applied to selected subgroups : subjects in whom acute mental status changes were documented , subjects on surgical services , and subjects with impaired cognitive status on admission . Combinations of any two instruments did not perform substantially better than the instrument with the best test characteristics : the Clinical Assessment of Confusion . All instruments were more useful at confirming delirium than in excluding it . CONCLUSION The four instruments studied , which are suitable for use at the bedside , can aid the clinician in identifying patients likely to be suffering from delirium Objective : To implement sedation and delirium monitoring via a process-improvement project in accordance with Society of Critical Care Medicine guidelines and to evaluate the challenges of modifying intensive care unit ( ICU ) organizational practice styles . Design : Prospect i ve observational cohort study . Setting : The medical ICUs at two institutions : the V and erbilt University Medical Center ( VUMC ) and a community Veterans Affairs hospital ( York-VA ) . Subjects : Seven hundred eleven patients admitted to the medical ICUs for > 24 hrs and followed over 4,163 days during a 21-month study period . Interventions : Unit-wide nursing documentation was changed to accommo date a sedation scale ( Richmond Agitation-Sedation Scale ) and delirium instrument ( Confusion Assessment Method for the ICU ) . A 20-min introductory in-service was performed for all ICU nurses , followed by grade d , staged educational interventions at regular intervals . Data were collected daily for compliance , and r and omly 40 % of nurses each day were chosen for accuracy spot-checks by reference raters . An implementation survey question naire was distributed at 6 months . Measurements and Main Results : The implementation project involved 64 nurses ( 40 at VUMC and 24 at York-VA ) .  Sedation and delirium monitoring data were recorded for 711 patients ( 614 at VUMC and 97 at York-VA ) .  Compliance with the Richmond Agitation-Sedation Scale was 94.4 % ( 21,931 of 23,220 ) at VUMC and 99.7 % ( 5,387 of 5,403 ) at York-VA . Compliance with the Confusion Assessment Method for the ICU was 90 % ( 7,323 of 8,166 ) at VUMC and 84 % ( 1,571 of 1,871 ) at York-VA . The Confusion Assessment Method for the ICU was performed more often than requested on 63 % of shifts ( 5,146 of 8,166 ) at VUMC and on 8 % ( 151 of 1871 ) of shifts at York-VA . Overall weighted-&kgr ; between bedside nurses and references raters for the Richmond Agitation-Sedation Scale were 0.89 ( 95 % confidence interval , 0.88 to 0.92 ) at VUMC and 0.77 ( 95 % confidence interval , 0.72 to 0.83 ) at York-VA . Overall agreement ( & kgr ; ) between bedside nurses and reference raters using the Confusion Assessment Method for the ICU was 0.92 ( 95 % confidence interval , 0.90–0.94 ) at VUMC and 0.75 ( 95 % confidence interval , 0.68–0.81 ) at York-VA . The two most-often-cited barriers to implementation were physician buy-in and time . Conclusions : With minimal training , the compliance of bedside nurses using sedation and delirium instruments was excellent . Agreement of data from bedside nurses and a reference-st and ard rater was very high for both the sedation scale and the delirium assessment over the duration of this process-improvement project OBJECTIVE To develop and vali date a new st and ardized confusion assessment method ( CAM ) that enables nonpsychiatric clinicians to detect delirium quickly in high-risk setting s. DESIGN Prospect i ve validation study . SETTING Conducted in general medicine wards and in an outpatient geriatric assessment center at Yale University ( site 1 ) and in general medicine wards at the University of Chicago ( site 2 ) . PATIENTS The study included 56 subjects , ranging in age from 65 to 98 years . At site 1 , 10 patients with and 20 without delirium participated ; at site 2 , 16 patients with and 10 without delirium participated . MEASUREMENTS AND MAIN RESULTS An expert panel developed the CAM through a consensus building process . The CAM instrument , which can be completed in less than 5 minutes , consists of nine operationalized criteria from the Diagnostic and Statistical Manual of Mental Disorders ( DSM-III-R ) . An a priori hypothesis was established for the diagnostic value of four criteria : acute onset and fluctuating course , inattention , disorganized thinking , and altered level of consciousness . The CAM algorithm for diagnosis of delirium required the presence of both the first and the second criteria and of either the third or the fourth criterion . At both sites , the diagnoses made by the CAM were concurrently vali date d against the diagnoses made by psychiatrists . At sites 1 and 2 values for sensitivity were 100 % and 94 % , respectively ; values for specificity were 95 % and 90 % ; values for positive predictive accuracy were 91 % and 94 % ; and values for negative predictive accuracy were 100 % and 90 % . The CAM algorithm had the highest predictive accuracy for all possible combinations of the nine features of delirium . The CAM was shown to have convergent agreement with four other mental status tests , including the Mini-Mental State Examination . The interobserver reliability of the CAM was high ( kappa = 0.81 - 1.0 ) . CONCLUSIONS The CAM is sensitive , specific , reliable , and easy to use for identification of delirium CONTEXT In the intensive care unit ( ICU ) , delirium is a common yet underdiagnosed form of organ dysfunction , and its contribution to patient outcomes is unclear . OBJECTIVE To determine if delirium is an independent predictor of clinical outcomes , including 6-month mortality and length of stay among ICU patients receiving mechanical ventilation . DESIGN , SETTING , AND PARTICIPANTS Prospect i ve cohort study enrolling 275 consecutive mechanically ventilated patients admitted to adult medical and coronary ICUs of a US university-based medical center between February 2000 and May 2001 . Patients were followed up for development of delirium over 2158 ICU days using the Confusion Assessment Method for the ICU and the Richmond Agitation-Sedation Scale . MAIN OUTCOME MEASURES Primary outcomes included 6-month mortality , overall hospital length of stay , and length of stay in the post-ICU period . Secondary outcomes were ventilator-free days and cognitive impairment at hospital discharge . RESULTS Of 275 patients , 51 ( 18.5 % ) had persistent coma and died in the hospital . Among the remaining 224 patients , 183 ( 81.7 % ) developed delirium at some point during the ICU stay . Baseline demographics including age , comorbidity scores , dementia scores , activities of daily living , severity of illness , and admission diagnoses were similar between those with and without delirium ( P>.05 for all ) . Patients who developed delirium had higher 6-month mortality rates ( 34 % vs 15 % , P = .03 ) and spent 10 days longer in the hospital than those who never developed delirium ( P<.001 ) . After adjusting for covariates ( including age , severity of illness , comorbid conditions , coma , and use of sedatives or analgesic medications ) , delirium was independently associated with higher 6-month mortality ( adjusted hazard ratio [ HR ] , 3.2 ; 95 % confidence interval [ CI ] , 1.4 - 7.7 ; P = .008 ) , and longer hospital stay ( adjusted HR , 2.0 ; 95 % CI , 1.4 - 3.0 ; P<.001 ) . Delirium in the ICU was also independently associated with a longer post-ICU stay ( adjusted HR , 1.6 ; 95 % CI , 1.2 - 2.3 ; P = .009 ) , fewer median days alive and without mechanical ventilation ( 19 [ interquartile range , 4 - 23 ] vs 24 [ 19 - 26 ] ; adjusted P = .03 ) , and a higher incidence of cognitive impairment at hospital discharge ( adjusted HR , 9.1 ; 95 % CI , 2.3 - 35.3 ; P = .002 ) . CONCLUSION Delirium was an independent predictor of higher 6-month mortality and longer hospital stay even after adjusting for relevant covariates including coma , sedatives , and analgesics in patients receiving mechanical ventilation A prospect i ve , descriptive study was used to assess the diagnostic validity of the Confusion Assessment Method ( CAM ) administered at the bedside by nurses in daily practice . Two different scoring methods of the CAM ( the specific ( SPEC ) and sensitive ( SENS ) methods ) were compared with a criterion st and ard ( CAM completed by trained research nurses ) . During a 5-month period , all patients consecutively admitted to an acute geriatric ward of the University Hospitals of Leuven ( Belgium ) were enrolled in the study . The 258 elderly in patients who were included underwent 641 paired but independent ratings of delirium by bedside and trained research nurses . Delirium was identified in 36 of the 258 patients ( 14 % ) or in 42 of the 641 paired observations ( 6.5 % ) . The SENS method of the CAM algorithm as administered by bedside nurses had the greatest diagnostic accuracy , with 66.7 % sensitivity and 90.7 % specificity ; the SPEC method had 23.8 % sensitivity and 97.7 % specificity . Bedside nurses had difficulties recognizing the features of acute onset , fluctuation , and altered level of consciousness . For both scoring methods , bedside nurses had difficulties with the identification of elderly patients with delirium but succeeded in diagnosing correctly those patients without delirium in more than 90 % of observations . 
    Output:
    
In application studies ,  CAM-rated delirium is most commonly used as a risk factor or outcome but also as an intervention or reference st and ard .