***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: Since its inception during the severe outbreak of poliomyelitis almost 50 years ago , the intensive care unit ( ICU ) has become a key feature in almost every hospital . Increasingly sick patient population s , improved life-support systems , newer , more effective therapeutic agents , and greater underst and ing of the pathophysiology of many disease processes have led to a growing need for ICU beds , with the ICU increasingly accounting for a larger and larger proportion of the hospital budget [ 1 ] . Intensive care is un question ably expensive care [ 2 , 3 ] and re sources are not always readily available . As an example , there are frequently insufficient ICU beds available to cater for dem and . Indeed , in a recent question naire survey of 504 ICUs in 16 Western European countries , 46 % of respondents stated that ICU admissions were generally or commonly affected by bed shortages [ 4 ] . With increasingly expensive technology being developed , ICU spending is likely further to exceed available funding , and the need for explicit rationing is rapidly becoming a reality . However rationing is applied , the aim must be to provide , without restriction , high- quality intensive care for those who will benefit from it . To this end , several suggestions have been made to limit ICU costs and improve the efficiency of the service . These include the development and implementation of strict admission and discharge criteria , and the use of intermediate care units . These intermediate care units , also termed high-dependency or astepdowno , units , generally have a higher nurse/patient ratio and greater facilities for intensive monitoring than would be found on a general ward , but fewer staff and less invasive equipment than on an ICU [ 5 , 6 ] ( Fig. 1 ) . Such areas cater for patients who do not require full ICU care but are thought to need more care than could be offered on the general ward . Intermediate care units have been adopted by some hospitals , particularly for specific patient groups , such as cardiac [ 7 ] , neurosurgical [ 8 ] , or respiratory [ 9 ] patients . The use of such units has been promoted as a means of enabling the earlier discharge of some ICU patients and of providing an alternative to intensive care for patients who merely require intensive monitoring , thus freeing ICU beds . However , such units are not necessarily the solution to overutilization of ICU beds and may merely divert the issue rather than solve it [ 10 ] . They may also have negative effects on patient care and staff morale . Importantly , there are few , if any , prospect i ve studies on the benefits of intensive care versus intermediate care which provide objective and hence comparable , admission and discharge criteria . In addition , the literature that is available comes predominantly from the United States , where intensive care training , organisation and management are very different than Europe . In this paper , we will discuss the pros and cons of  intermediate care units and conclude with our thoughts and recommendations on the appropriate place of such units in our hospitals today Introduction The aim of the study was to assess whether adults admitted to hospitals with both Intensive Care Units ( ICU ) and Intermediate Care Units ( IMCU ) have lower in-hospital mortality than those admitted to ICUs without an IMCU . Methods An observational multinational cohort study performed on patients admitted to participating ICUs during a four-week period .  IMCU was defined as any physically and administratively independent unit open 24 hours a day , seven days a week providing a level of care lower than an ICU but higher than a ward . Characteristics of hospitals , ICUs and patients admitted to study ICUs were recorded . The main outcome was all-cause in-hospital mortality until hospital discharge ( censored at 90 days ) . Results One hundred and sixty-seven ICUs from 17 European countries enrolled 5,834 patients . Overall , 1,113 ( 19.1 % ) patients died in the ICU and 1,397 died in hospital , with a total of 1,397 ( 23.9 % ) deaths . The illness severity was higher for patients in ICUs with an IMCU ( median Simplified Acute Physiology Score ( SAPS ) II : 37 ) than for patients in ICUs without an IMCU ( median SAPS II : 29 , P < 0.001 ) . After adjustment for patient characteristics at admission such as illness severity , and ICU and hospital characteristics , the odds ratio of mortality was 0.63 ( 95 % CI 0.45 to 0.88 , P = 0.007 ) in favour of the presence of IMCU . The protective effect of the IMCU was absent in patients who were admitted for basic observation , for example , after surgery ( odds ratio 1.15 , 95 % CI 0.65 to 2.03 , P = 0.630 ) but was strong in patients admitted to an ICU for other reasons ( odds ratio 0.54 , 95 % CI 0.37 to 0.80 , P = 0.002 ) . Conclusions The presence of an IMCU in the hospital is associated with significantly reduced adjusted hospital mortality for adults admitted to the ICU . This effect is relevant for the patients requiring full intensive treatment . Trial registration Clinical trials.gov NCT01422070 . Registered 19 August 2011 Objective To evaluate short- and long-term outcomes of elderly patients ( ≥ 65 years ) treated at an intermediate care unit ( IMCU )  and to identify outcome predictors . Design and setting Prospect i ve observational study in the IMCU of a university teaching hospital . Participants We studied 412 patients over 8 months , classified into three groups : under 65 years ( control group , n = 158 ) , 65–80 ( n = 186 ) , and > 80 ( n = 68 ) . Measurements At admission : APACHE II , TISS-28 first day , Charlson Index , diagnosis , and prior Barthel Index . Outcome measures : in-hospital mortality , length of stay , discharge destination , and 2-year mortality and readmissions . Data analysis included multivariate logistic regression and receiver operating characteristics area under the curve ( ROC AUC ) . Results No statistically significant differences between groups were observed in hospital mortality ( 14.1 % ) , discharge to a long-term facility ( 2.7 % ) , or 2-year readmissions ( 1.2 ± 2.1 ) . However , hospital stay was longer in patients aged 65–80 years ( 14 vs.10 days ) and 2-year mortality was higher in those 65 or over ( 34 % vs.10.6 % ) . In the overall series in-hospital mortality was predicted by APACHE II , first-day TISS-28 , and diagnosis ( ROC AUC 0.81 ) , and 2-year mortality by Charlson Index and age ( ROC AUC 0.77 ) . In the elderly patients 2-year mortality was predicted by Charlson and Barthel indices ( ROC AUC 0.70 ) . Conclusions Illness severity and therapeutic intervention at admission to IMCU were predictors of short-term mortality , whereas the strongest predictor of long-term mortality was comorbidity . Our results suggest that comprehensive assessment of elderly patients at admission to IMCUs may improve outcome prediction Objectives : Cardiorespiratory instability may be undetected in monitored step-down unit patients . We explored whether using an integrated monitoring system that continuously amalgamates single noninvasive monitoring parameters ( heart rate , respiratory rate , blood pressure , and peripheral oxygen saturation ) into AN instability index value ( INDEX ) correlated with our single-parameter cardiorespiratory instability concern criteria , and whether nurse response to INDEX alert for patient attention was associated with instability reduction . Design : Prospect i ve , longitudinal evaluation in sequential 8- , 16- , and 8-wk phases ( phase I , phase II , and phase III , respectively ) . Setting : A 24-bed trauma step-down unit in single urban tertiary care center . Patients : All monitored patients . Interventions : Phase I : Patients received continuous single-channel monitoring ( heart rate , respiratory rate , blood pressure , and peripheral oxygen saturation ) and st and ard care ; INDEX background was recorded but not displayed . Phase II : INDEX was background -recorded ; staff was educated on use . Phase III : Staff used a clinical response algorithm for INDEX alerts . Measurement and Main Results : Any monitored parameters even transiently beyond local cardiorespiratory instability concern triggers ( heart rate of < 40 or > 140 beats/min , respiratory rate of < 8 or > 36 breaths/min , systolic blood pressure of < 80 or > 200 mm Hg , diastolic blood pressure of > 110 mm Hg , and peripheral oxygen saturation of < 85 % ) defined INSTABILITYmin . INSTABILITYmin further judged as both persistent and serious defined INSTABILITYfull . The INDEX alert states were defined as INDEXmin and INDEXfull by using same classification . Phase I and phase III admissions ( 323 vs. 308 ) and monitoring ( 18,258 vs. 18,314 hrs ) were similar . INDEXmin and INDEXfull correlated significantly with INSTABILITYmin and INSTABILITYfull ( r = .713 and r = .815 , respectively , p < .0001 ) . INDEXmin occurred before INSTABILITYmin in 80 % of cases ( mean advance time 9.4 ± 9.2 mins ) . Phase I and phase III admissions were similarly likely to develop INSTABILITYmin ( 35 % vs. 33 % ) , but INSTABILITYmin duration /admission decreased from phase I to phase III ( p = .018 ) . Both INSTABILITYfull episodes/admission ( p = .03 ) and INSTABILITYfull duration /admission ( p = .05 ) decreased in phase III . Conclusion : The integrated monitoring system INDEX correlated significantly with cardiorespiratory instability concern criteria , usually occurred before overt instability , and when coupled with a nursing alert was associated with decreased cardiorespiratory instability concern criteria in step-down unit patients BACKGROUND Patients in step-down units are at higher risk for developing cardiorespiratory instability than are patients in general care areas . A triage tool is needed to identify at-risk patients who therefore require increased surveillance . OBJECTIVES To determine demographic ( age , race , sex ) and clinical ( Charlson Comorbidity Index at admission , admitting diagnosis , care area of origin , admission service ) differences between patients in step-down units who did and did not experience cardiorespiratory instability . METHODS In a prospect i ve longitudinal pilot study , 326 surgical-trauma patients had continuous monitoring of heart rate , respirations , and oxygen saturation and intermittent noninvasive measurement of blood pressure .  Cardiorespiratory instability was defined as heart rate less than 40/min or greater than 140/min , respirations less than 8/min or greater than 36/min , oxygen saturation less than 85 % , or blood pressure less than 80 or greater than 200 mm Hg systolic or greater than 110 mm Hg diastolic . Patients ' status was classified as unstable if their values crossed these thresholds even once during their stay . RESULTS Cardiorespiratory instability occurred in 34 % of patients . The Charlson Comorbidity Index was the only variable associated with instability conditions . Compared with patients with no comorbid conditions ( 50 % ) , more patients with at least 1 comorbid condition ( 66 % ) experienced instability ( P = .006 ) . Each 1-unit increase in the Charlson Index increased the odds for cardiorespiratory instability by 1.17 ( P = .03 ) . CONCLUSION Although the relationship between Charlson Comorbidity Index and cardiorespiratory instability was weak , adding it to current surveillance systems might improve detection of instability BACKGROUND : The medium care unit ( MCU ) or “ stepdown ” unit is an increasingly important , but understudied care environment . With an aging population and more patients with complex multiple diseases , many patients often require a higher level of inpatient care even when full intensive care is not indicated . However , the nurse-to-patient ratio required on a MCU is neither well defined nor clear whether this ratio should be adjusted per shift . The  Nursing Activities Score ( NAS )  is an effective instrument for measuring nursing workload in the intensive care unit ( ICU ) but has not been used in an MCU . The aim of this study was to measure the nursing workload per 8-hour shift on an MCU using the NAS and compare it with the NAS from an ICU in the same hospital . We also compared the NAS between groups of patients with different admission sources . METHODS : The  NAS  was prospect ively measured per patient per shift for 2 months in a 9-bed tertiary referral university hospital MCU and during a similar period in an ICU in the same hospital . RESULTS : The mean NAS per patient did not differ between day ( 7:30 AM to 4:00 PM ) and evening ( 3:00 PM to 11:30 PM ) shifts , but the NAS was significantly lower during the night shift ( 11:00 PM to 8:00 AM ) than during the day ( P < 0.0001 ) and evening ( P < 0.0001 ) shifts . The mean NASs in the ICU for day and night shifts were significantly lower than the scores in the MCU ( P = 0.0056 and P < 0.0001 , respectively ) , but NAS during the evening shift did not differ between the ICU and the MCU . The mean NAS for patients admitted to the MCU from the accident and emergency department was significantly higher than for those admitted from the ICU ( P = 0.002 ) , recovery ( P = 0.002 ) , and general ward ( P < 0.0001 ) . Patients on the MCU had a NAS comparable with that of IC 
    Output:
    
IMCUs often have a specific task in a hospital , which is reflected in location , format , and utilisation .
Common IMCU denominators are continuous monitoring and respiratory support , without mechanical ventilation and multiple vasoactive medications