Resource use in the ICU: short- vs. long-term patients

Validating the APACHE IV score in predicting length of stay in the intensive care unit among patients with sepsis

The Acute Physiology and Chronic Health Evaluation (APACHE) IV model can predict the intensive care unit (ICU) length of stay (LOS) in critically ill patients. Thus, this study aimed to validate the performance of the APACHE IV score in predicting ICU LOS among patients with sepsis. This retrospective study was conducted in the medical ICU of a tertiary university between 2017 and 2020. A total of 1,039 sepsis patients were enrolled. Patients with an ICU stay of 1 and > 3 days accounted for 20.1% and 43.9%. The overall observed and APACHE IV predicted ICU LOS were 6.3 ± 6.5 and 6.8 ± 6.5, respectively. The APACHE IV slightly over-predicted ICU LOS with standardized length of stay ratio 0.95 (95% CI 0.89-1.02). The predicted ICU LOS based on the APACHE IV score was statistically longer than the observed ICU LOS (p < 0.001) and were poorly correlated (R² = 0.02, p < 0.001), especially in patients with a lower severity of illness. In conclusions the APACHE IV model poorly predicted ICU LOS in patients with sepsis. The APACHE IV score needs to be modified or we need to make a new specific model to predict ICU stays in patients with sepsis.

Closed Collaborative Surgical Intensive Care Unit Modeling and Its Association With Trauma Patient Outcomes

INTRODUCTION

The optimization of intensive care unit (ICU) care impacts clinical outcomes and resource utilization. In 2017, our surgical ICU (SICU) adopted a "closed-collaborative" model. The aim of this study is to compare patient outcomes in the closed-collaborative model versus the previous open model in a cohort of trauma surgical patients admitted to our adult level 1 trauma center.

METHODS

A retrospective review of trauma patients in the SICU from August 1, 2015 to July 31, 2019 was performed. Patients were divided into those admitted prior to August 1, 2017 (the "open" cohort) and those admitted after August 1, 2017 (the "closed-collaborative" cohort). Demographic variables and clinical outcomes were analyzed. Trauma severity was assessed using injury severity score (ISS).

RESULTS

We identified 1669 patients (O: 895; C: 774). While no differences in demographics were observed, the closed-collaborative cohort had a higher overall ISS (O: 21.5 ± 12.14; C: 25.10 ± 2.72; P < 0.0001). There were no significant differences between the two cohorts in the incidence of strokes (O: 1.90%; C: 2.58%, P = 0.3435), pulmonary embolism (O: 0.78%; C: 0.65%; P = 0.7427), sepsis (O: 5.25%; C: 7.49%; P = 0.0599), median ICU charges (O: $7784.50; C: $8986.53; P = 0.5286), mortality (O: 11.40%; C: 13.18%; P = 0.2678), or ICU length of stay (LOS) (O: 4.85 ± 6.23; C: 4.37 ± 4.94; P = 0.0795).

CONCLUSIONS

Patients in the closed-collaborative cohort had similar clinical outcomes despite having a sicker cohort of patients. We hypothesize that the closed-collaborative ICU model was able to maintain equivalent outcomes due to the dedicated multidisciplinary critical care team caring for these patients. Further research is warranted to determine the optimal model of ICU care for trauma patients.

Dynamics of immune responses are inconsistent when trauma patients are grouped by injury severity score and clinical outcomes

The injury severity score (ISS) is used in daily practice to evaluate the severity of trauma patients; however, the score is not always consistent with the prognosis. After injury, systemic inflammatory response syndrome (SIRS) and compensatory anti-inflammatory response syndrome (CARS) are related to the prognosis of trauma patients. We aimed to evaluate the associations between the immune response and prognosis in trauma patients. Patients who admitted to the Trauma Intensive Care Unit (ICU) were eligible. Whole blood samples were collected at admission, and then 6, 12, 24, 48 and 72 h after admission. Natural killer (NK) cells, lymphocyte subset population and cytokines release were identified using flow cytometry. We grouped patients by their ISS (≤ 25 and > 25 as very severe injury) and ICU stay (≤ 10 days as a short ICU stay and > 10 days as a long ICU stay) for evaluation. Fifty-three patients were enrolled. ICU stay but not ISS was close correlated with activity daily living (ADL) at discharge. Patients with a long ICU stay had an immediate increase in NK cells followed by lymphopenia which persisted for 48 h. Immediate activation of CD8⁺ T cells and then exhaustion with a higher programmed cell death-1 (PD-1) expression and suppression of CD4⁺ T cells with a shift to an anti-inflammatory Th2 phenotype were also observed in the patients with a long ICU stay. When the patients were grouped by ISS, the dynamics of immune responses were inconsistent to those when the patients were grouped by ICU stay. Immune responses are associated with the prognosis of trauma patients, however the currently used clinical parameters may not accurately reflect immune responses. Further investigations are needed to identify accurate predictors of prognosis in trauma patients.

Machine Learning-based Prediction of Prolonged Intensive Care Unit Stay for Critical Patients with Spinal Cord Injury

STUDY DESIGN

A retrospective cohort study.

OBJECTIVE

The objective of the study was to develop machine-learning (ML) classifiers for predicting prolonged intensive care unit (ICU)-stay and prolonged hospital-stay for critical patients with spinal cord injury (SCI).

SUMMARY OF BACKGROUND DATA

Critical patients with SCI in ICU need more attention. SCI patients with prolonged stay in ICU usually occupy vast medical resources and hinder the rehabilitation deployment.

METHODS

A total of 1599 critical patients with SCI were included in the study and labeled with prolonged stay or normal stay. All data were extracted from the eICU Collaborative Research Database and the Medical Information Mart for Intensive Care III-IV Database. The extracted data were randomly divided into training, validation and testing (6:2:2) subdatasets. A total of 91 initial ML classifiers were developed, and the top three initial classifiers with the best performance were further stacked into an ensemble classifier with logistic regressor. The area under the curve (AUC) was the main indicator to assess the prediction performance of all classifiers. The primary predicting outcome was prolonged ICU-stay, while the secondary predicting outcome was prolonged hospital-stay.

RESULTS

In predicting prolonged ICU-stay, the AUC of the ensemble classifier was 0.864 ± 0.021 in the three-time five-fold cross-validation and 0.802 in the independent testing. In predicting prolonged hospital-stay, the AUC of the ensemble classifier was 0.815 ± 0.037 in the three-time five-fold cross-validation and 0.799 in the independent testing. Decision curve analysis showed the merits of the ensemble classifiers, as the curves of the top three initial classifiers varied a lot in either predicting prolonged ICU-stay or discriminating prolonged hospital-stay.

CONCLUSION

The ensemble classifiers successfully predict the prolonged ICU-stay and the prolonged hospital-stay, which showed a high potential of assisting physicians in managing SCI patients in ICU and make full use of medical resources.Level of Evidence: 3.

Predicting Prolonged Length of ICU Stay through Machine Learning

This study aimed to construct machine learning (ML) models for predicting prolonged length of stay (pLOS) in intensive care units (ICU) among general ICU patients. A multicenter database called eICU (Collaborative Research Database) was used for model derivation and internal validation, and the Medical Information Mart for Intensive Care (MIMIC) III database was used for external validation. We used four different ML methods (random forest, support vector machine, deep learning, and gradient boosting decision tree (GBDT)) to develop prediction models. The prediction performance of the four models were compared with the customized simplified acute physiology score (SAPS) II. The area under the receiver operation characteristic curve (AUROC), area under the precision-recall curve (AUPRC), estimated calibration index (ECI), and Brier score were used to measure performance. In internal validation, the GBDT model achieved the best overall performance (Brier score, 0.164), discrimination (AUROC, 0.742; AUPRC, 0.537), and calibration (ECI, 8.224). In external validation, the GBDT model also achieved the best overall performance (Brier score, 0.166), discrimination (AUROC, 0.747; AUPRC, 0.536), and calibration (ECI, 8.294). External validation showed that the calibration curve of the GBDT model was an optimal fit, and four ML models outperformed the customized SAPS II model. The GBDT-based pLOS-ICU prediction model had the best prediction performance among the five models on both internal and external datasets. Furthermore, it has the potential to assist ICU physicians to identify patients with pLOS-ICU risk and provide appropriate clinical interventions to improve patient outcomes.

Characteristics and Survival of Patients with Acute Traumatic Spinal Cord Injury Above T6 with Prolonged Intensive Care Unit Stays

OBJECTIVE

To characterize patients with acute traumatic spinal cord injury (ATSCI) above T6 who were admitted to the intensive care unit (ICU) for ≥30 days and their 1-year mortality compared with patients admitted for <30 days.

METHODS

A retrospective observational study was performed on 211 patients with an acute traumatic spinal cord injury above T6 who were admitted to an ICU between 1998 and 2017. Multivariate logistic regression analysis was performed to determine the relationship between an ICU stay ≥30 days and mortality after ICU discharge.

RESULTS

Of patients, 29.4% were admitted to the ICU for ≥30 days, accounting for 53.4% of total days of ICU stays generated by all patients. An ICU stay ≥30 days was not identified as an independent risk factor for mortality (1-year survival: 88.5% vs. 88.1%; adjusted hazard ratio [HR] 0.80, P = 0.699). Variables identified as predictors of 1-year post-ICU discharge mortality were severity at admission according to the Acute Physiology and Chronic Health Evaluation II score (HR 1.18) and the American Spinal Injury Association Impairment Scale motor score (HR 0.97). Among patients who required invasive mechanical ventilation, a longer duration of the respiratory support was associated with increased mortality (HR 1.01).

CONCLUSIONS

Three out of 10 patients with acute traumatic spinal cord injury above T6 require prolonged stays in the ICU. Variables found to be associated with 1-year post-ICU discharge mortality in these patients were American Spinal Injury Association Impairment Scale motor score, severity, and greater duration of invasive mechanical ventilation, but not an ICU stay ≥30 days.

Number of intensivists per bed is associated with efficiency of Dutch intensive care units

PURPOSE

To measure efficiency in Intensive Care Units (ICUs) and to determine which organizational factors are associated with ICU efficiency, taking confounding factors into account.

MATERIALS AND METHODS

We used data of all consecutive admissions to Dutch ICUs between January 1, 2016 and January 1, 2019 and recorded ICU organizational factors. We calculated efficiency for each ICU by averaging the Standardized Mortality Ratio (SMR) and Standardized Resource Use (SRU) and examined the relationship between various organizational factors and ICU efficiency. We thereby compared the results of linear regression models before and after covariate adjustment using propensity scores.

RESULTS

We included 164,399 admissions from 83 ICUs. ICU efficiency ranged from 0.51-1.42 (average 0.99, 0.15 SD). The unadjusted model as well as the propensity score adjusted model showed a significant association between the ratio of employed intensivists per ICU bed and ICU efficiency. Other organizational factors had no statistically significant association with ICU efficiency after adjustment.

CONCLUSIONS

We found marked variability in efficiency in Dutch ICUs. After applying covariate adjustment using propensity scores, we identified one organizational factor, ratio intensivists per bed, having an association with ICU efficiency.

Epidemiology and Predictors of Long-Stays in Medical ICU: A Retrospective Cohort Study

INTRODUCTION

Prolonged stays in ICU have been associated with overconsumption of resources but little is known about their epidemiology. We aimed to identify predictors and prognostic factors of extended stays, studying a long-stay population.

METHODS

We present a retrospective cohort study between July 2000 and December 2013 comparing patients hospitalized in a medical ICU for ≥30 days (long-stay patients-LSP) with patients hospitalized for <30 days (short-stay patients-SSP). Admission characteristics were collected from the local database for every patient and evolution during the ICU stay was retrieved from LSP files.

RESULTS

Among 8906 patients hospitalized in the ICU, 417 (4.7%) were LSP. At admission, male sex (adjusted odds-ratio (aOR) 1.4 [1.1; 1.7]), inpatient (aOR 2.0 [1.6; 2.4]) and in-ICU hospitalizations for respiratory (aOR 2.9 [1.6; 3.5]) or infectious diseases (aOR 1.6 [1.1; 2.5]) were all independently associated with a long stay in the ICU, while hospitalizations for metabolic (aOR 0.2 [0.1; 0.5]) or cardiovascular diseases (aOR 0.3 [0.2; 0.5]) were in favor of a short stay. In-ICU and in-hospital LSP mortality were 38.8% and 48.2%. Age (aOR 1.02 [1.00-1.04]), catecholamines (aOR 3.9 [1.9; 8.5]), renal replacement therapy (aOR 2.4 [1.3; 4.3]), primary disease-related complications (aOR 2.5 [1.4; 4.6]) and nosocomial infections (aOR 4.1 [1.8; 10.1]) were independently associated with mortality in LSP.

CONCLUSION

LSP were highly comorbid patients mainly hospitalized for respiratory diseases. Their mortality was mostly related to nosocomial infections but the majority were discharged alive from the hospital.

Predictors of Trauma High Resource Consumers in a Mature Trauma System

Background

Extended hospital length of stay (LOS) is widely associated with significant healthcare costs. Since LOS is a known surrogate for cost, we sought to evaluate outliers. We hypothesized that particular characteristics are likely predictive of trauma high resource consumers (THRC) and can be used to more effectively manage care of this population.

Methods

The Pennsylvania Trauma Outcome Study database was retrospectively queried from 2003-2017 for all adult (age ≥15) trauma patients admitted to accredited trauma centers in Pennsylvania. THRC were defined as patients with hospital LOS two standard deviations above the population mean or ≥22 days (p<0.05). Patient demographics, comorbid conditions and clinical variables were compared between THRC and non-THRC to identify potential predictor variables. A multilevel mixed-effects logistic regression model controlling for age, gender, injury severity, admission Glasgow coma score, systolic blood pressure, and injury year assessed the adjusted impact of clinical factors in predicting THRC status. The National Trauma Data Bank (NTDB) was retrospectively queried from 2014-2016 for all adult (age ≥15) trauma patients admitted to state-accredited trauma centers and likewise were assessed for factors associated with THRC.

Results

A total of 465,601 patients met inclusion criteria [THRC: 16,818 (3.6%); non-THRC 448,783 (96.4%)]. Compared to non-THRC counterparts, THRC patients were significantly more severely injured (median ISS: 9 vs. 22, p<0.001). In adjusted analysis, gunshot wound (GSW) to the abdomen, undergoing major surgery and reintubation along with injury to the spine, upper or lower extremities were significantly associated with THRC. From the NTDB, 2 323 945 patients met inclusion criteria. In adjusted analysis, GSW to the abdomen was significantly associated with THRC. Penetrating injury overall was associated with decreased risk of being a THRC in the NTDB dataset. Those who had either GSW to abdomen, surgery, or reintubation required significantly longer LOS (p<0.001).

Conclusions

Reintubation, major surgery, gunshot wound to abdomen, along with injury to the spine, upper or lower extremities are all strongly predictive of THRC. Understanding the profile of the THRC will allow clinicians and case management to proactively put processes in place to streamline care and potentially reduce costs and LOS.

Determining the Cost and Length of Stay at Intensive Care Units and the Factors Influencing Them in a Teaching Hospital in Malaysia

OBJECTIVES

Escalating healthcare costs calls for the efficiency of health services, especially in the intensive care unit (ICU) where the bulk of resources are used. This study aims to identify the length of stay (LOS) and cost of care at ICUs, which are proxy indicators of efficiency and the factors determining them.

METHODS

A cross-sectional study of patients requiring ICU admissions in a teaching hospital in Malaysia from 2013 to 2015 was conducted. The cost at the ICU was estimated using the step down approach. Factors that determined the cost and LOS at the ICU were also explored by using multivariate regression analysis.

RESULTS

Each day of stay cost $427 (USD) at the pediatric intensive care unit and $1324 at the general intensive care unit. The mean LOS at the ICU was 5.7 days (standard deviation [SD]: 8.4) with a median of 4 days (95% confidence interval [CI] 1-16.7 days). Average cost of care at the ICU per episode of care was $5473 (SD $6499), and the median was $3463. ICU patients spent 29.3% of the total stay and 47.2% of the cost at ICU units. Upon multivariate regression analysis, severity, case base-group, and type of ICU that the patient was admitted to were associated with the cost and LOS at ICU.

CONCLUSIONS

Compared with critical care practices in hospitals from more developed nations, a Malaysian teaching hospital required a longer length of ICU stay. Hence, implementations of strategies that can reduce the length of stay and hospital costs without compromising healthcare quality are required.

Intensive care unit length of stay is reduced by protocolized family support intervention: a systematic review and meta-analysis

PURPOSE

This study aimed to elucidate the impact of protocolized family support intervention on length of stay (LOS) in the intensive care unit (ICU) through a systematic review and meta-analysis.

METHODS

Medline, EMBASE, the Cochrane Central Register of Controlled Trials, and other web-based databases were referenced since inception until November 26, 2018. We included randomized-controlled trials wherein protocolized family support interventions were conducted for enhanced communication and shared medical decision-making. LOS (in days) and mortality were evaluated using a random-effects model, and adjusted LOS was estimated using a mixed-effects model.

RESULTS

We included seven randomized-controlled trials with 3477 patients. Protocolized family support interventions were found to significantly reduce the ICU LOS {mean difference = - 0.89 [95% confidence interval (CI) = - 1.50 to - 0.27]} and hospital LOS [mean difference = - 3.78 (95% CI = - 5.26 to - 2.29)]; the results of the mixed-effect model showed that they significantly reduced ICU LOS after adjusting for the therapeutic goal [mean difference = - 1.30 (95% CI = - 2.35 to - 0.26)], methods of measurement [mean difference = - 0.89 (95% CI = - 1.55 to - 0.22)], and timing of intervention [mean difference = - 1.05 (95% CI = - 2.05 to - 0.05)]. Similar results were found after adjusting for patients' disease severity [mean difference = - 1.21 (95% CI = - 2.03 to - 0.39)] and the trim-and-fill method [mean difference = - 0.86 (95% CI = - 1.44 to - 0.28)]. There was no difference in mortality rate in ICU and hospital between the protocolized intervention and control groups.

CONCLUSIONS

Protocolized family support intervention for enhanced communication and shared decision-making with the family reduced ICU LOS in critically ill patients without impacting mortality.

Survival and Quality of Life after Prolonged Intensive Care Unit Stay

There are few data on long-term outcomes in mixed groups of intensive care unit (ICU) patients with prolonged stays. We evaluated the relationship between length of stay in the ICU and long-term outcome in all patients admitted to our 31-bed department of medico-surgical intensive care over a one-year period who stayed in the department for more than 10 days (n=189, 7% of all ICU admissions). Mortality increased with length of stay from 1 to 10 days (1 day 5%, 5 days 15%, 9 days 24%, 10 days 33%) but remained stable at about 35% for longer ICU stays. In the long-stay patients, the most common reasons for ICU admission were intracranial bleeding (23%), polytrauma (14%), respiratory failure (13%) and septic shock (11%). The main reasons for prolonged ICU stay were ventilator dependency (40%), infectious complications (23%) and coma (16%). Long-stay patients had a 65% ICU survival, 55% hospital survival and 37% one-year survival. At one-year follow-up, 73% of surviving patients reported no or minor persistent physical complaints compared to before the acute illness; 27% had a major functional impairment, including 8% who required daily assistance. In conclusion, in ICU patients, mortality increases with length of stay up to 10 days. Patients staying in the ICU for more than 10 days have a relatively good long-term survival. Most survivors have an acceptable quality of life.

Long-term outcomes in patients treated in the intensive care unit after hematopoietic stem cell transplantation

The number of patients who are successfully discharged from the intensive care unit (ICU) after hematopoietic stem cell transplantation (HSCT) remains limited. Most previous studies have evaluated short-term outcomes using ICU mortality; there have been comparatively fewer reports of long-term outcomes. We retrospectively analyzed 39 HSCT patients admitted to the ICU for the first time between April 2008 and July 2014. Performance status was evaluated in four long-term survivors in July 2016. Median age at ICU admission was 54 years (range 30-68). In total, 33 patients (70.2%) required mechanical ventilation and 31 patients (66%) required dialysis. The median OS from first ICU admission was 41 days (95% confidence interval [CI]: 22-64) and the 1-year survival rate was 12.8% (95% CI 4.7-25.2). No statistically significant factors were associated with short-term outcomes. Among long-term outcomes, a second or subsequent HSCT and neutropenia at ICU admission were significant risk factors. Four of 10 ICU survivors have survived with good performance status for a median of 1994 (1203-2633) days. Our results suggest that the number of prior transplants and neutropenia at ICU admission may influence OS.

Effect of diagnosis related groups implementation on the intensive care unit of a Swiss tertiary hospital: a cohort study

BACKGROUND

In 2013 the Swiss Diagnosis Related Groups ((Swiss)-DRG) was implemented in Intensive Care Units (ICU). Its impact on hospitalizations has not yet been examined. We compared the number of ICU admissions, according to clinical severity and referring institution, and screened whether implementation of Swiss-DRG affected admission policy, ICU length-of-stay (ICU-LOS) or ICU mortality.

METHODS

Retrospective, single centre, cohort study conducted at the University Hospital Zurich, Switzerland between January 2009 and end of September 2013. Demographic and clinical data was retrieved from a quality assurance database.

RESULTS

Admissions (n = 17,231) before the introduction of Swiss-DRG were used to model expected admissions after DRG, and then compared to the observed admissions. Forecasting matched observations in patients with a high clinical severity admitted from internal units and external hospitals (admitted / predicted: 709 / 703, [95% Confidence Interval (CI), 658-748] and 302 / 332, [95% CI, 269-365] respectively). In patients with low severity of disease, in-house admissions became more frequent than expected and external admission were less frequent (admitted / predicted: 1972 / 1910, [95% CI, 1898-1940] and 436 / 518, [95% CI, 482-554] respectively). Various mechanisms related to Swiss-DRG may have led to these changes. DRG could not be linked to significant changes in regard to ICU-LOS and ICU mortality.

CONCLUSIONS

DRG introduction had not affected ICU admissions policy, except for an increase of in-house patients with a low clinical severity of disease. DRG had neither affected ICU mortality nor ICU-LOS.

Factors Associated with Postoperative Prolonged Mechanical Ventilation in Pediatric Liver Transplant Recipients

Introduction

Almost all pediatric orthotopic liver transplant (OLT) recipients require mechanical ventilation in the early postoperative period. Prolonged postoperative mechanical ventilation (PPMV) may be a marker of severe disease and may be associated with morbidity and mortality. We determined the incidence and risk factors for PPMV in children who underwent OLT.

Methods

This was a retrospective analysis of data collected on 128 pediatric OLT recipients. PPMV was defined as postoperative ventilation ≥ 4 days. Perioperative characteristics were compared between cases and control groups. Multivariable logistic regression analysis was used to calculate odds ratios for PPMV after controlling for relevant cofactors.

Results

An estimated 25% (95% CI, 17.4%–32.6%) required PPMV. The overall incidence of PPMV varied significantly by age group with the highest incidence among infants. PPMV was associated with higher postoperative mortality (p = 0.004) and longer intensive care unit (p < 0.001) and hospital length of stay (p < 0.001). Multivariable analysis identified young patient age, preoperative hypocalcemia, and increasing duration of surgery as independent predictors of PPMV following OLT.

Conclusion

The incidence of PPMV is high and it was associated with prolonged ICU and hospital LOS and higher posttransplant mortality. Surgery duration appears to be the only modifiable predictor of PPMV.

A Mortality Study for ICU Patients using Bursty Medical Events

The study of patients in Intensive Care Units (ICUs) is a crucial task in critical care research which has significant implications both in identifying clinical risk factors and defining institutional guidances. The mortality study of ICU patients is of particular interest because it provides useful indications to healthcare institutions for improving patients experience, internal policies, and procedures (e.g. allocation of resources). To this end, many research works have been focused on the length of stay (LOS) for ICU patients as a feature for studying the mortality. In this work, we propose a novel mortality study based on the notion of burstiness, where the temporal information of patients longitudinal data is taken into consideration. The burstiness of temporal data is a popular measure in network analysis and time-series anomaly detection, where high values of burstiness indicate presence of rapidly occurring events in short time periods (i.e. burst). Our intuition is that these bursts may relate to possible complications in the patient's medical condition and hence provide indications on the mortality. Compared to the LOS, the burstiness parameter captures the temporality of the medical events providing information about the overall dynamic of the patients condition. To the best of our knowledge, we are the first to apply the burstiness measure in the clinical research domain. Our preliminary results on a real dataset show that patients with high values of burstiness tend to have higher mortality rate compared to patients with more regular medical events. Overall, our study shows promising results and provides useful insights for developing predictive models on temporal data and advancing modern critical care medicine.

Relationship Between ICU Length of Stay and Long-Term Mortality for Elderly ICU Survivors

OBJECTIVES

To evaluate the association between length of ICU stay and 1-year mortality for elderly patients who survived to hospital discharge in the United States.

DESIGN

Retrospective cohort study of a random sample of Medicare beneficiaries who survived to hospital discharge, with 1- and 3-year follow-up, stratified by the number of days of intensive care and with additional stratification based on receipt of mechanical ventilation.

INTERVENTIONS

None.

PATIENTS

The cohort included 34,696 Medicare beneficiaries older than 65 years who received intensive care and survived to hospital discharge in 2005.

MEASUREMENTS AND MAIN RESULTS

Among 34,696 patients who survived to hospital discharge, the mean ICU length of stay was 3.4 days (± 4.5 d). Patients (88.9%) were in the ICU for 1-6 days, representing 58.6% of ICU bed-days. Patients (1.3%) were in the ICU for 21 or more days, but these patients used 11.6% of bed-days. The percentage of mechanically ventilated patients increased with increasing length of stay (6.3% for 1-6 d in the ICU and 71.3% for ≥ 21 d). One-year mortality was 26.6%, ranging from 19.4% for patients in the ICU for 1 day, up to 57.8% for patients in the ICU for 21 or more days. For each day beyond 7 days in the ICU, there was an increased odds of death by 1 year of 1.04 (95% CI, 1.03-1.05) irrespective of the need for mechanical ventilation.

CONCLUSIONS

Increasing ICU length of stay is associated with higher 1-year mortality for both mechanically ventilated and non-mechanically ventilated patients. No specific cutoff was associated with a clear plateau or sharp increase in long-term risk.

Quadrimodal distribution of death after trauma suggests that critical injury is a potentially terminal disease

BACKGROUND

Patterns of death after trauma are changing due to advances in critical care. We examined mortality in critically injured patients who survived index hospitalization.

METHODS

Retrospective analysis of adults admitted to a Level-1 trauma center (1/1/2000-12/31/2010) with critical injury was conducted comparing patient characteristics, injury, and resource utilization between those who died during follow-up and survivors.

RESULTS

Of 1,695 critically injured patients, 1,135 (67.0%) were discharged alive. As of 5/1/2012, 977/1,135 (86.0%) remained alive; 75/158 (47.5%) patients who died during follow-up, died in the first year. Patients who died had longer hospital stays (24 vs. 17 days) and ICU LOS (17 vs. 8 days), were more likely to undergo tracheostomies (36% vs. 16%) and gastrostomies (39% vs. 16%) and to be discharged to rehabilitation (76% vs. 63%) or skilled nursing (13% vs. 5.8%) facilities than survivors. In multivariable models, male sex, older age, and longer ICU LOS predicted mortality. Patients with ICU LOS >16 days had 1.66 odds of 1-year mortality vs. those with shorter ICU stays.

CONCLUSIONS

ICU LOS during index hospitalization is associated with post-discharge mortality. Patients with prolonged ICU stays after surviving critical injury may benefit from detailed discussions about goals of care after discharge.

Long-term admission to the intensive care unit: a cost-benefit analysis

OBJECTIVE

To assess outcomes in long-term ICU patients, with follow-ups carried out at one year post discharge, in order to calculate the costs incurred by the hospital in relation to the benefits gained.

MATERIAL

Of 3639 patients consecutively admitted over the course of three years to ICU, 235 (6.5%) were assessed for the purposes of the study, having spent a period exceeding 20 days in intensive care.

METHOD

The survey tool used was the Spanish Minimum Data Set (MDS). The length of ICU stay and hospital stay following discharge from ICU were calculated, and one year post discharge the patient/next of kin was contacted in order to carry out a follow-up survey on survival and functional status (according to GOS-E scale).

RESULTS

The 235 study patients had a mean stay of 37 days, occupied 34% of ICU beds available and consumed 29% of the ICU's economic resources ($14,400,175). Their stay on hospital wards was (mean) 33 days. Mortality in ICU and on hospital wards was 40% higher amongst older patients, and those with a higher APACHE II and Charlson index score. Mortality rates were three times higher among neurosurgical patients: mortality at follow-up was 25%, and only 21% recovered an acceptable functional status.

CONCLUSIONS

Mortality rates in long-term ICU patients are high, both during their hospital stay and in the first year post discharge. Surviving patients do not exhibit a good level of recovery, and consume a large proportion of economic resources.

Scope of nursing care in Polish intensive care units

INTRODUCTION

The TISS-28 scale, which may be used for nursing staff scheduling in ICU, does not reflect the complete scope of nursing resulting from varied cultural and organizational conditions of individual systems of health care.

AIM

The objective of the study was an attempt to provide an answer to the question what scope of nursing care provided by Polish nurses in ICU does the TISS-28 scale reflect?

MATERIAL AND METHODS

The methods of working time measurement were used in the study. For the needs of the study, 252 hours of continuous observation (day-long observation) and 3.697 time-schedule measurements were carried out.

RESULTS

The total nursing time was 4125.79 min. (68.76 hours), that is, 60.15% of the total working time of Polish nurses during the period analyzed. Based on the median test, the difference was observed on the level of χ(2) = 16945.8,P < 0.001 between the nurses' workload resulting from performance of activities qualified into the TISS-28 scale and load resulting from performance of interventions within the scopes of care not considered in this scale in Polish ICUs.

CONCLUSIONS

The original version of the TISS-28 scale does not fully reflect the workload among Polish nurses employed in ICUs.

Economic evaluation in critical care: a focus on severe sepsis in oncology

Hospital care, physician and clinical services, and prescription drugs continue to drive healthcare expenditures across healthcare systems and nations. The critical-care setting, owing to the complexity and intensity of care, is a high user of the resources that drive healthcare spending. Information regarding the cost and effectiveness of critical-care therapies is necessary to properly guide care and policies for this unique population. Many challenges exist for conducting and comparing economic evaluation in critical care. Recently, recommendations on cost and cost-effectiveness analysis in critical care have been developed that will guide future research. A focus area, severe sepsis in oncology, is reviewed to highlight the challenges and opportunities of economic evaluation in this setting.

Prediction of length of ICU stay using data-mining techniques: an example of old critically Ill postoperative gastric cancer patients

OBJECTIVE

With the background of aging population in China and advances in clinical medicine, the amount of operations on old patients increases correspondingly, which imposes increasing challenges to critical care medicine and geriatrics. The study was designed to describe information on the length of ICU stay from a single institution experience of old critically ill gastric cancer patients after surgery and the framework of incorporating data-mining techniques into the prediction.

METHODS

A retrospective design was adopted to collect the consecutive data about patients aged 60 or over with a gastric cancer diagnosis after surgery in an adult intensive care unit in a medical university hospital in Shenyang, China, from January 2010 to March 2011. Characteristics of patients and the length their ICU stay were gathered for analysis by univariate and multivariate Cox regression to examine the relationship with potential candidate factors. A regression tree was constructed to predict the length of ICU stay and explore the important indicators.

RESULTS

Multivariate Cox analysis found that shock and nutrition support need were statistically significant risk factors for prolonged length of ICU stay. Altogether, seven variables entered the regression model, including age, APACHE II score, SOFA score, shock, respiratory system dysfunction, circulation system dysfunction, diabetes and nutrition support need. The regression tree indicated comorbidity of two or more kinds of shock as the most important factor for prolonged length of ICU stay in the studied sample.

CONCLUSIONS

Comorbidity of two or more kinds of shock is the most important factor of length of ICU stay in the studied sample. Since there are differences of ICU patient characteristics between wards and hospitals, consideration of the data-mining technique should be given by the intensivists as a length of ICU stay prediction tool.

Staff satisfaction between 2 models of care for the chronically critically ill

INTRODUCTION

Chronically critically ill (CCI) patients are a growing population in intensive care units (ICUs), and evidence suggests that this patient group is perceived as demanding by healthcare professionals. However, information is scarce regarding organizational factors that affect staff satisfaction during the care of CCI patients.

PURPOSE

The purpose of this study was to evaluate staff satisfaction between 2 models of care for the CCI. In the first model, a patient-centered program of care in a traditional ICU was evaluated. In the second model, care of patients hospitalized in a multidisciplinary ICU ward dedicated to the CCI was further evaluated. Indicators of staff satisfaction with respect to the care of the CCI were also identified.

METHODS

A before and after study was used to evaluate the 2 models of care. After implementation of the first model in 2006, an initial evaluation was performed using a questionnaire given to ICU health-care personnel. In 2009, after implementing the second model (a separate ward for the CCI), a second evaluation took place.

RESULTS

A total of 147 participants answered the questionnaire in both phases. Participants described CCI as a burden, and grouping these patients into 1 ward only increased this perception. Overall, the staff was more satisfied with the first model of care. In this model, the indicators of increased satisfaction were perceived access to professional development and the availability of information.

CONCLUSIONS

Results from this study provide information about health-care professionals' perceived burden of care when treating CCI patients. Strategies promoting professional development have a potential to increase staff satisfaction when it comes to the care of this patient group.

The Going Home Initiative: Getting Critical Care Patients Home With Hospice

Although considerable effort is being directed at providing patients and their families with a “good death,” most patients in intensive care units, if given the choice, would prefer to die at home. With little guidance from the literature, the palliative care committee of an intensive care unit developed guidelines to get patients home from the intensive care unit to die. In the past few years, the unit has transferred many patients home with hospice care, much to the delight of their families. Although several obstacles to achieving this goal exist, the unit has achieved success in a small-scale implementation of its Going Home Initiative.

Impact of antibiotic exposure patterns on selection of community-associated methicillin-resistant Staphylococcus aureus in hospital settings

Community-associated methicillin-resistant S. aureus (CA-MRSA) is increasingly common in hospitals, with potentially serious consequences. The aim of this study was to assess the impact of antibiotic prescription patterns on the selection of CA-MRSA within hospitals, in a context of competition with other circulating staphylococcal strains, including methicillin-sensitive (MSSA) and hospital-associated methicillin-resistant (HA-MRSA) strains. We developed a computerized agent-based model of S. aureus transmission in a hospital ward in which CA-MRSA, MSSA, and HA-MRSA strains may cocirculate. We investigated a wide range of antibiotic prescription patterns in both intensive care units (ICUs) and general wards, and we studied how differences in antibiotic exposure may explain observed variations in the success of CA-MRSA invasion in the hospitals of several European countries and of the United States. Model predictions underlined the influence of antibiotic prescription patterns on CA-MRSA spread in hospitals, especially in the ICU, where the endemic prevalence of CA-MRSA carriage can range from 3% to 20%, depending on the simulated prescription pattern. Large antibiotic exposure with drugs effective against MSSA but not MRSA was found to promote invasion by CA-MRSA. We also found that, should CA-MRSA acquire fluoroquinolone resistance, a major increase in CA-MRSA prevalence could ensue in hospitals worldwide. Controlling the spread of highly community-prevalent CA-MRSA within hospitals is a challenge. This study demonstrates that antibiotic exposure strategies could participate in this control. This is all the more important in wards such as ICUs, which may play the role of incubators, promoting CA-MRSA selection in hospitals.

Definition, risk factors and outcome of prolonged surgical intensive care unit stay

There is no generally accepted definition for a "prolonged surgical intensive care unit (SICU) stay". The aims of the current study were to: (1) define prolonged SICU stay; (2) identify risk factors of prolonged SICU stay; and (3) identify risk factors of hospital mortality in patients with a prolonged SICU stay. All SICU patients aged >16 years and with an intensive care unit (ICU) stay longer than three days without ICU readmission between 1 January 2004 and 30 November 2006 at the National Taiwan University Hospital were recruited to the study. A total of 2598 patients were recruited. ICU stay >16 days was defined as a prolonged SICU stay since rates of ICU mortality, hospital mortality and mortality one year after ICU discharge remained stationary after ICU stay was >16 days. A multivariate logistic regression model identified factors associated with a prolonged SICU stay, including age more than 70 years old, (odds ratio 1.587, 95% confidence interval 1.246 to 2.022), increasing pre-ICU hospital days (odds ratio 1.009, 95% confidence interval 1.003 to 1.015), admission from emergency (odds ratio 1.925, 95% confidence interval 1.455 to 2.548), use of mechanical circulation support (odds ratio 2.314, 95% confidence interval 1.458 to 3.674) and renal replacement therapy (odds ratio 5.140, 95% confidence interval 3.781 to 6.987). A multivariate logistic regression model identified factors associated with ICU mortality in patients with ICU stay >16 days, including renal replacement therapy (odds ratio 4.780, 95% confidence interval 2.687 to 8.504). An ICU stay >16 days could be used to define prolonged SICU stay when hospital and one-year mortality rates are considered. Prevention of organ failure requiring renal replacement therapy might prove a useful goal to avoid prolonged ICU stay and even hospital mortality.

A predictive model for the early identification of patients at risk for a prolonged intensive care unit length of stay

BACKGROUND

Patients with a prolonged intensive care unit (ICU) length of stay account for a disproportionate amount of resource use. Early identification of patients at risk for a prolonged length of stay can lead to quality enhancements that reduce ICU stay. This study developed and validated a model that identifies patients at risk for a prolonged ICU stay.

METHODS

We performed a retrospective cohort study of 343,555 admissions to 83 ICUs in 31 U.S. hospitals from 2002-2007. We examined the distribution of ICU length of stay to identify a threshold where clinicians might be concerned about a prolonged stay; this resulted in choosing a 5-day cut-point. From patients remaining in the ICU on day 5 we developed a multivariable regression model that predicted remaining ICU stay. Predictor variables included information gathered at admission, day 1, and ICU day 5. Data from 12,640 admissions during 2002-2005 were used to develop the model, and the remaining 12,904 admissions to internally validate the model. Finally, we used data on 11,903 admissions during 2006-2007 to externally validate the model.

RESULTS

The variables that had the greatest impact on remaining ICU length of stay were those measured on day 5, not at admission or during day 1. Mechanical ventilation, PaO2: FiO2 ratio, other physiologic components, and sedation on day 5 accounted for 81.6% of the variation in predicted remaining ICU stay. In the external validation set observed ICU stay was 11.99 days and predicted total ICU stay (5 days + day 5 predicted remaining stay) was 11.62 days, a difference of 8.7 hours. For the same patients, the difference between mean observed and mean predicted ICU stay using the APACHE day 1 model was 149.3 hours. The new model's r2 was 20.2% across individuals and 44.3% across units.

CONCLUSIONS

A model that uses patient data from ICU days 1 and 5 accurately predicts a prolonged ICU stay. These predictions are more accurate than those based on ICU day 1 data alone. The model can be used to benchmark ICU performance and to alert physicians to explore care alternatives aimed at reducing ICU stay.

Demand for nursing care for patients in intensive care units in Southeast Poland

BACKGROUND

The Therapeutic Intervention Scoring System is widely used in both Western Europe and the United States to assess the level of patients' need for nursing care. Poland currently has 3 types of intensive care according to a territorial division of the country and the scope of medical treatment offered: poviat, voivodeship, and clinical.

OBJECTIVE

To determine the need for nursing care for patients in the 3 types of intensive care units in southeastern Poland.

METHODS

The investigation was conducted at 6 intensive care units in southeastern Poland in 2005 and 2006. Two units were randomly selected from each type of intensive care unit. A total of 155 patients from the units were categorized according to scores on the Therapeutic Intervention Scoring System 28.

RESULTS

Among the 3 types of units, patients varied significantly with respect to age, length of hospitalization, and scores on the Therapeutic Intervention Scoring System 28. Nevertheless, demand for nursing care during night and day shifts was similar in all 3 types. On the basis of the patients' scores, all 3 types of units provided appropriate staffing levels necessary to meet the demands for nursing care. Most patients required category III level of care.

CONCLUSION

Need or demand for nursing care in intensive care units in Poland varies according to the type of intensive care unit and can be determined on the basis of scores on the Therapeutic Intervention Scoring System 28.

Effect of length of stay in intensive care unit on hospital and long-term mortality of critically ill adult patients

BACKGROUND

Critical illness leading to prolonged length of stay (LOS) in an intensive care unit (ICU) is associated with significant mortality and resource utilization. This study assessed the independent effect of ICU LOS on in-hospital and long-term mortality after hospital discharge.

METHODS

Clinical and mortality data of 22 298 patients, aged 16 yr and older, admitted to ICU between 1987 and 2002 were included in this linked-data cohort study. Cox's regression with restricted cubic spline function was used to model the effect of LOS on in-hospital and long-term mortality after adjusting for age, gender, acute physiology score (APS), maximum number of organ failures, era of admission, elective admission, Charlson's co-morbidity index, and diagnosis. The variability each predictor explained was calculated by the percentage of the chi(2) statistic contribution to the total chi(2) statistic.

RESULTS

Most hospital deaths occurred within the first few days of ICU admission. Increasing LOS in ICU was not associated with an increased risk of in-hospital mortality after adjusting for other covariates, but was associated with an increased risk of long-term mortality after hospital discharge. The variability on the long-term mortality effect associated with ICU LOS (2.3%) appeared to reach a plateau after the first 10 days in ICU and was not as important as age (35.8%), co-morbidities (18.6%), diagnosis (10.9%), and APS (3.6%).

CONCLUSIONS

LOS in ICU was not an independent risk factor for in-hospital mortality, but it had a small effect on long-term mortality after hospital discharge after adjustment for other risk factors.

Review of a large clinical series: intrahospital transport of critically ill patients: outcomes, timing, and patterns

The purpose of this study was to analyze the relationship of intrahospital transport patterns with patient throughput and outcomes in an oncological intensive care unit. We retrospectively reviewed all patients admitted to a closed medical-surgical intensive care unit at a cancer center between January 1, 2004 and December 31, 2005. We compared the clinical characteristics and outcomes of patients with and without transport and analyzed all intrahospital transports in relation to intensive care unit occupancy, length of stay, and intensive care unit and hospital outcomes. Transport patterns were also assessed by day of week, time of day, timing of the first transport to intensive care unit admission, and destination. Transported patients (n = 413, 43.5%) had significantly higher severity of illness scores on intensive care unit admission, greater use of vasopressors and mechanical ventilation, and longer intensive care unit and hospital length of stay and higher hospital mortality than nontransported patients (n = 535, 56.5%). Multiple transports (!2) occurred in 45% of the transported patients. The number of transports was directly proportional to intensive care unit length of stay. The highest transport rates and nearly half of all first transports occurred during the first 24 hours of intensive care unit admission. Transports were most common during weekdays and on afternoon and evening hours and most frequently to the computed tomography suite. Our study shows that intrahospital transport of the critically ill is a multifaceted process with important implications for intensive care unit resource analysis, workload and throughput.

Case-mix-adjusted length of stay and mortality in 23 Finnish ICUs

OBJECTIVES

To create a tool for benchmarking intensive care units (ICUs) with respect to case-mix adjusted length of stay (LOS) and to study the association between clinical and economic measures of ICU performance.

DESIGN

Observational cohort study.

SETTING

Twenty-three ICUs in Finland.

PATIENTS

A total of 80,854 consecutive ICU admissions during 2000-2005, of which 63,304 met the inclusion criteria.

INTERVENTIONS

None.

MEASUREMENTS AND RESULTS

Linear regression was used to create a model that predicted ICU LOS. Simplified Acute Physiology Score (SAPS) II, age, disease categories according to Acute Physiology and Chronic Health Evaluation III, single highest Therapeutic Intervention Scoring System score collected during the ICU stay and presence of other ICUs in the hospital were included in the model. Probabilities of hospital death were calculated using SAPS II, age, and disease categories as covariates. In the validation sample, the created model accounted for 28% of variation in ICU LOS across individual admissions and 64% across ICUs. The expected ICU LOS was 2.53 +/- 2.24 days and the observed ICU LOS was 3.29 +/- 5.37 days, P < 0.001. There was no association between the mean observed - mean expected ICU LOS and standardized mortality ratios of the ICUs (Spearman correlation 0.091, P = 0.680).

CONCLUSIONS

We developed a tool for the assessment of resource use in a large nationwide ICU database. It seems that there is no association between clinical and economic quality indicators.

[Characteristics and prognosis of patients with very long stay in an Intensive Care Unit]

OBJECTIVE

To describe the characteristics and prognostic factors of elderly patients hospitalized for > or = 30 days in an Intensive Care Unit (ICU).

DESIGN

Retrospective analysis of prospectively collected simple data over 6 consecutive years.

SETTING

Polyvalent ICU of the Insular University Hospital in the Canary Islands (Spain).

PATIENTS

Adult patients > or = 70 years who were hospitalized in the ICU for a period of 30 or more days.

PRIMARY VARIABLES OF INTEREST

Demographic data, clinical diagnosis on ICU admission, Apache II, days of renal replacement therapy (RRT), days of mechanical ventilation and the outcome of the survivors one year later were collected. Mortality at one year of the surviving patients was studied.

RESULTS

During the study period, 3,786 patients were admitted to the ICU. Of these, 853 (22.5%) patients were > or = 70 years old and only 42 (4.92%) of these patients remained in the ICU for > or = 30 days. We compared the latter with the > or = 70 year old patients whose stay in the ICU stay was < 30 days. No statistically significant differences in ICU mortality, Apache II, age, gender and the need for RRT were found. As independent variables associated with the long stay, the multivariate analysis showed only the days of mechanical ventilation (p < 0.05). The surviving patients (> or = 70 years old and whose stay in the ICU was > or = 30 days) were older and 21 (65.62%) were still alive one year later.

CONCLUSIONS

ICU mortality rates in elderly patients with a stay < or > or = 30 days in the ICU were comparable. Survival at one year of the > or = 70 year-old patients whose long-term intensive care unit stay was > or = 30 days was high. These results are sufficient in our unit to justify prolonged ICU care for elderly patients.

Resource use and outcome in critically ill patients with hematological malignancy: a retrospective cohort study

Introduction

The paucity of data on resource use in critically ill patients with hematological malignancy and on these patients' perceived poor outcome can lead to uncertainty over the extent to which intensive care treatment is appropriate. The aim of the present study was to assess the amount of intensive care resources needed for, and the effect of treatment of, hemato-oncological patients in the intensive care unit (ICU) in comparison with a nononcological patient population with a similar degree of organ dysfunction.

Methods

A retrospective cohort study of 101 ICU admissions of 84 consecutive hemato-oncological patients and 3,808 ICU admissions of 3,478 nononcological patients over a period of 4 years was performed.

Results

As assessed by Therapeutic Intervention Scoring System points, resource use was higher in hemato-oncological patients than in nononcological patients (median (interquartile range), 214 (102 to 642) versus 95 (54 to 224), P < 0.0001). Severity of disease at ICU admission was a less important predictor of ICU resource use than necessity for specific treatment modalities. Hemato-oncological patients and nononcological patients with similar admission Simplified Acute Physiology Score scores had the same ICU mortality. In hemato-oncological patients, improvement of organ function within the first 48 hours of the ICU stay was the best predictor of 28-day survival.

Conclusion

The presence of a hemato-oncological disease per se is associated with higher ICU resource use, but not with increased mortality. If withdrawal of treatment is considered, this decision should not be based on admission parameters but rather on the evolutional changes in organ dysfunctions.

Review of A Large Clinical Series: A Microcosting Study of Intensive Care Unit Stay in the Netherlands

The primary objective of this study was to estimate the actual daily costs of intensive care unit stay using a microcosting methodology. As a secondary objective, the degree of association between daily intensive care unit costs and some patient characteristics was examined. This multicenter, retrospective cost analysis was conducted in the medical-surgical adult intensive care units of 1 university and 2 general hospitals in the Netherlands for 2006, from a hospital perspective. A total of 576 adult patients were included, consuming a total of 2868 nursing days. The mean total costs per intensive care unit day were 1911, with labour (33%) and indirect costs (33%) as the most important cost drivers. An ordinary least squares analysis including age, Nine Equivalent of Nursing Manpower Use score/Therapeutic Intervention Scoring System score, mechanical ventilation, blood products, and renal replacement therapy was able to predict 50% of the daily intensive care unit costs.

Quality of life after stay in surgical intensive care unit

BACKGROUND

In addition to mortality, Health Related Quality of Life (HRQOL) has increasingly been claimed as an important outcome variable. The aim of this study was to assess HRQOL and independence in activities of daily living (ADL) six months after discharge from an Intensive Care Unit (ICU), and to study its determinants.

METHODS

All post-operative adult patients admitted to a surgical ICU between October 2004 and July 2005, were eligible for the study. The following variables were recorded on admission: age, gender, American Society of Anesthesiologists physical status (ASA-PS), type and magnitude of surgical procedure, ICU and hospital length of stay (LOS), mortality and Simplified Acute Physiology Score II (SAPS II). Six months after discharge, a Short Form-36 questionnaire (SF-36) and a questionnaire to assess dependency in ADL were sent to all survivors. Descriptive statistics was used to summarize data. Patient groups were compared using non-parametric tests. A logistic regression analysis was performed to identify covariate effects of each variable on dependency in personal and instrumental ADL, and for the change-in-health question of SF-36.

RESULTS

Out of 333 hospital survivors, 226 completed the questionnaires. Fifty-nine percent reported that their general level of health was better on the day they answered the questionnaire than 12 months earlier. Patients with greater co-morbidities (ASA-PS III/IV), had lower SF-36 scores in all domains and were more frequently dependent in instrumental and personal ADL. Logistic regression showed that SAPS II was associated with changes in general level of health (OR 1.06, 95%CI, 1.01-1.11, p = 0,016). Six months after ICU discharge, 60% and 34% of patients, respectively, were dependent in at least one activity in instrumental ADL (ADLI) and personal ADL (ADLP). ASA-PS (OR 3.00, 95%CI 1.31-6.87, p = 0.009) and age (OR 2.36, 95%CI, 1.04-5.34, p = 0.04) were associated with dependency in ADLI. For ADLP, only ASA-PS (OR 4.58, 95%CI, 1.68-12.46, p = 0.003) was associated with higher dependency.

CONCLUSION

ASA-PS, age, type of surgery, ICU LOS and SAPS II could be seen as determinants of HRQOL.

Variability in outcome and resource use in intensive care units

OBJECTIVE

To examine variability in outcome and resource use between ICUs. Secondary aims: to assess whether outcome and resource use are related to ICU structure and process, to explore factors associated with efficient resource use.

DESIGN AND SETTING

Cohort study, based on the SAPS 3 database in 275 ICUs worldwide.

PATIENTS

16,560 adults.

MEASUREMENTS AND RESULTS

Outcome was defined by standardized mortality rate (SMR). Standardized resource use (SRU) was calculated based on length of stay in the ICU, adjusted for severity of acute illness. Each unit was assigned to one of four groups: "most efficient" (SMR and SRU < median); "least efficient" (SMR, SRU > median); "overachieving" (low SMR, high SRU), "underachieving" (high SMR, low SRU). Univariate analysis and stepwise logistic regression were used to test for factors separating "most" from "least efficient" units. Overall median SMR was 1.00 (IQR 0.77-1.28) and SRU 1.07 (0.76-1.58). There were 91 "most efficient", 91 "least efficient", 47 "overachieving", and 46 "underachieving" ICUs. Number of physicians, of full-time specialists, and of nurses per bed, clinical rounds, availability of physicians, presence of emergency department, and geographical region were significant in univariate analysis. In multivariate analysis only interprofessional rounds, emergency department, and geographical region entered the model as significant.

CONCLUSIONS

Despite considerable variability in outcome and resource use only few factors of ICU structure and process were associated with efficient use of ICU. This suggests that other confounding factors play an important role.

Family satisfaction in the intensive care unit: cross-cultural adaptation of a questionnaire

PURPOSE

Family needs and expectations are often unmet in the intensive care unit (ICU), leading to dissatisfaction. This study assesses cross-cultural adaptability of an instrument evaluating family satisfaction in the ICU.

MATERIALS AND METHODS

A Canadian instrument on family satisfaction was adapted for German language and central European culture and then validated for feasibility, validity, internal consistency, reliability, and sensitivity.

RESULTS

Content validity of a preliminary translated version was assessed by staff, patients, and next of kin. After adaptation, content and comprehensibility were considered good. The adapted translation was then distributed to 160 family members. The return rate was 71.8%, and 94.4% of questions in returned forms were clearly answered. In comparison with a Visual Analogue Scale, construct validity was good for overall satisfaction with care (Spearman rho = 0.60) and overall satisfaction with decision making (rho = 0.65). Cronbach alpha was .95 for satisfaction with care and .87 for decision-making. Only minor differences on repeated measurements were found for interrater and intrarater reliability. There was no floor or ceiling effect.

CONCLUSIONS

A cross-cultural adaptation of a questionnaire on family satisfaction in the ICU can be feasible, valid, internally consistent, reliable, and sensitive.

Long-term outcomes and clinical predictors of hospital mortality in very long stay intensive care unit patients: a cohort study

Introduction

Little information is available on prognosis and outcomes of very long stay intensive care unit (ICU) patients. The purpose of this study was to identify long-term outcomes after hospital discharge and readily available clinical predictors of hospital mortality for patients requiring prolonged care in the ICU.

Method

Clinical data were collected from consecutive patients requiring at least 30 days of ICU care admitted over 3 calendar years (2001 to 2003) to a medical/surgical ICU in a university-affiliated tertiary care centre.

Results

A total of 182 patients met the inclusion criteria, with a mean age of 63 years, median ICU stay of 48.5 days (interquartile range 36–78 days) and ICU mortality of 32%. They accounted for 8% of total admissions and 48% of total occupied beds. Of these patients, 42% died in hospital, 44% returned to their previous place of residence, and 14% were transferred to long-term care institutions. By 6 months after hospital discharge a further 8% of the patients had died, 40% remained at their previous place of residence, and 10% were in long-term care. Predictors of hospital mortality, identified using multivariate logistic regression, included age (odds ratio [OR] 1.45 per additional decade, 95% confidence interval [CI] 1.10–1.91), any immunosuppression (OR 5.2, 95% CI 1.7–15.5), mechanical ventilation for longer than 90 days (OR 4.0, 95% CI 1.3–12.0), treatment with inotropes or vasopressors for more than 3 days at or after day 30 in the ICU (OR 7.1, 95% CI 2.6–19.3), and acute renal failure requiring dialysis at or after day 30 in the ICU (OR 6.3, 95% CI 2.0–19.7).

Conclusion

Patients with very long stays in the ICU appear to have a reasonable chance of survival, with most survivors in our cohort residing at their previous place of residence 6 months after hospital discharge. Prolonged requirement for life support therapies (ventilation, vasoactive agents, or acute dialysis) and a limited number of pre-existing co-morbidities (immunosuppression and, to a lesser extent, patient age) were predictors of increased hospital mortality. These predictors may assist in clinical decision making for this resource intensive patient population, and their reproducibility in other very long stay patient populations should be explored.