Evaluation of acute physiology and chronic health evaluation III predictions of hospital mortality in an independent database

Intensive care utilisation after elective surgery in Australia and New Zealand: A point prevalence study

Objective

We aimed to describe the characteristics, outcomes and resource utilisation of patients being cared for in an ICU after undergoing elective surgery in Australia and New Zealand (ANZ).

Methods

This was a point prevalence study involving 51 adult ICUs in ANZ in June 2021. Patients met inclusion criteria if they were being treated in a participating ICU on he study dates. Patients were categorised according to whether they had undergone elective surgery, admitted directly from theatre or unplanned from the ward. Descriptive and comparative analysis was performed according to the source of ICU admission. Resource utilisation was measured by Length of stay, organ support and occupied bed days.

Results

712 patients met inclusion criteria, with 172 (24%) have undergone elective surgery. Of these, 136 (19%) were admitted directly to the ICU and 36 (5.1%) were an unplanned admission from the ward. Elective surgical patients occupied 15.8% of the total ICU patient bed days, of which 44.3% were following unplanned admissions. Elective surgical patients who were an unplanned admission from the ward, compared to those admitted directly from theatre, had a higher severity of illness (AP2 17 vs 13, p<0.01), require respiratory or vasopressor support (75% vs 44%, p<0.01) and hospital mortality (16.7% vs 2.2%, p < 0.01).

Conclusions

ICU resource utilisation of patients who have undergone elective surgery is substantial. Those patients admitted directly from theatre have good outcomes and low resource utilisation. Patient admitted unplanned from the ward, although fewer, were sicker, more resource intensive and had significantly worse outcomes.

Impact of missing values on the ability of the acute physiology and chronic health evaluation III and Japan risk of death models to predict mortality

PURPOSE

This study assessed model performance of the Acute Physiology and Chronic Health Evaluation (APACHE) III and Japan Risk of Death (JROD) when degraded by the number and category of missing variables. We also examined the impact of missing data on predicted mortality for facilities with missing physiological variables.

METHODS

We obtained data from the Japanese Intensive care PAtient Database (JIPAD). We calculated observed and predicted mortality rates using the APACHE III and JROD and the standardized mortality ratio (SMR) by the number and category of missing variables. Smoothed spline curves were calculated for the SMR to the missing proportion of the facility.

RESULTS

A total of 61,357 patients from 57 ICUs were included between April 2015 and March 2019. The APACHE III and JROD SMRs increased as the number of missing values increased. The SMR in the APACHE III model was elevated in facilities with a larger proportion of missing in each of the APS categories, arterial blood gas, albumin, glucose, and bilirubin. Facilities with a high proportion of missing albumin data preserved their SMRs in only the JROD model.

CONCLUSION

An increased number of missing physiological variables resulted in falsely low predicted mortality rates and high SMRs.

Predictive Modeling Using Artificial Intelligence and Machine Learning Algorithms on Electronic Health Record Data: Advantages and Challenges

The rapid adoption of electronic health record (EHR) systems in US hospitals from 2008 to 2014 produced novel data elements for analysis. Concurrent innovations in computing architecture and machine learning (ML) algorithms have made rapid consumption of health data feasible and a powerful engine for clinical innovation. In critical care research, the net convergence of these trends has resulted in an exponential increase in outcome prediction research. In the following article, we explore the history of outcome prediction in the intensive care unit (ICU), the growing use of EHR data, and the rise of artificial intelligence and ML (AI) in critical care.

Screening for Social Risk Factors in the ICU During the Pandemic

Due to limitations in data collected through electronic health records, the social risk factors (SRFs) that predate severe illness and restrict access to critical care services are poorly understood.

OBJECTIVES

This study explored the feasibility and utility of directly eliciting SRFs in the ICU by implementing a screening program.

DESIGN SETTING AND PARTICIPANTS

Five hundred sixty-six critically ill patients at the medical ICU of Robert Wood Johnson University Hospital from July 1, 2019, to September 31, 2021, were interviewed for SRFs using an adapted version of the American Academy of Family Physicians' Social Needs Screening Tool.

MAIN OUTCOMES AND MEASURES

For each SRFs, we compared basic demographic factors, proxies of socioeconomic status, and severity score between those with and without the SRFs through chi-square tests and Wilcoxon rank-sum tests. Furthermore, we determined the prevalence of SRFs overall, before, and during the COVID-19 pandemic.

RESULTS

Of critically ill patients, 39.58% reported at least one SRF. Age, zip-code matched median household income, and insurance type differed depending on the SRFs. Notably, patients with SRFs were admitted with a lower average severity score, indicating reduced risk in mortality. Since March 2020, the prevalence of SRFs in the ICU overall fell from 54.47% to 35.44%. Conversely, the proportion of patients unable to afford healthcare increased statistically significantly from 7.32% to 18.06%.

CONCLUSIONS AND RELEVANCE

Screening for SRFs in the ICU detected the presence of disproportionally low-risk patients whose access to critical care services became restricted throughout the pandemic.

Can we reliably automate clinical prognostic modelling? A retrospective cohort study for ICU triage prediction of in-hospital mortality of COVID-19 patients in the Netherlands

BACKGROUND

Building Machine Learning (ML) models in healthcare may suffer from time-consuming and potentially biased pre-selection of predictors by hand that can result in limited or trivial selection of suitable models. We aimed to assess the predictive performance of automating the process of building ML models (AutoML) in-hospital mortality prediction modelling of triage COVID-19 patients at ICU admission versus expert-based predictor pre-selection followed by logistic regression.

METHODS

We conducted an observational study of all COVID-19 patients admitted to Dutch ICUs between February and July 2020. We included 2,690 COVID-19 patients from 70 ICUs participating in the Dutch National Intensive Care Evaluation (NICE) registry. The main outcome measure was in-hospital mortality. We asessed model performance (at admission and after 24h, respectively) of AutoML compared to the more traditional approach of predictor pre-selection and logistic regression.

FINDINGS

Predictive performance of the autoML models with variables available at admission shows fair discrimination (average AUROC = 0·75-0·76 (sdev = 0·03), PPV = 0·70-0·76 (sdev = 0·1) at cut-off = 0·3 (the observed mortality rate), and good calibration. This performance is on par with a logistic regression model with selection of patient variables by three experts (average AUROC = 0·78 (sdev = 0·03) and PPV = 0·79 (sdev = 0·2)). Extending the models with variables that are available at 24h after admission resulted in models with higher predictive performance (average AUROC = 0·77-0·79 (sdev = 0·03) and PPV = 0·79-0·80 (sdev = 0·10-0·17)).

CONCLUSIONS

AutoML delivers prediction models with fair discriminatory performance, and good calibration and accuracy, which is as good as regression models with expert-based predictor pre-selection. In the context of the restricted availability of data in an ICU quality registry, extending the models with variables that are available at 24h after admission showed small (but significantly) performance increase.

Effects of Timing of Invasive Mechanical Ventilation in Patients with Shock. An Analysis of the Multicenter Prospective Observational VOLUME–CHASERS Cohort

Objectives: Describe the variation in practice and identify predictors of invasive mechanical ventilation (IMV) use in shock. Explore the association between the timing of IMV initiation (“Early” vs. “Delayed”) on shock duration. Design: Multicenter, prospective, observational cohort study between September 2017 and February 2018 Setting: 34 hospitals in the United States and Jordan. Patients: Consecutive, adult, critically ill patients with shock, defined as a systolic blood pressure less than or equal to 90mm Hg, mean arterial pressure less than or equal to 65mm Hg, or need for a vasopressor medication. Interventions: None. Measurements and Main Results: “Early” IMV was defined as starting IMV 0–6 hours of shock onset and “Delayed” IMV was defined as starting IMV between 6 and 48 hours of shock onset. The primary outcome was shock–free days, defined as the number of days without shock after the first 48 hours of shock onset. Variation and predictors of IMV use were examined within the whole cohort as well as the subgroup of those intubated within 0–48 hours of shock onset. Mixed effects modeling with hospital site as a random effect showed that there was 7% variation by site in the use and timing of IMV in this shock cohort. In a propensity–matched model for the timing of IMV, “Early” IMV after shock onset was associated with more shock–free days when compared to “Delayed” IMV in those intubated within 0–48 hours of shock onset (Beta coefficient 0.65 days, 95% CI 0.14-1.16 days). Conclusions: Timing of IMV initiation for patients in shock has potentially important implications for patient outcomes and merits further study.

Recent Trends in Admission Diagnosis and Related Mortality in the Medically Critically Ill

PURPOSE

With decades of declining ICU mortality, we hypothesized that the outcomes and distribution of diseases cared for in the ICU have changed and we aimed to further characterize them.

STUDY DESIGN AND METHODS

A retrospective cohort analysis of 287,154 nonsurgical-critically ill adults, from 237 U.S. ICUs, using the manually abstracted Cerner APACHE Outcomes database from 2008 to 2016 was performed. Surgical patients, rare admission diagnoses (<100 occurrences), and low volume hospitals (<100 total admissions) were excluded. Diagnoses were distributed into mutually exclusive organ system/disease-based categories based on admission diagnosis. Multi-level mixed-effects negative binomial regression was used to assess temporal trends in admission, in-hospital mortality, and length of stay (LOS).

RESULTS

The number of ICU admissions remained unchanged (IRR 0.99, 0.98-1.003) while certain organ system/disease groups increased (toxicology [25%], hematologic/oncologic [55%] while others decreased (gastrointestinal [31%], pulmonary [24%]). Overall risk-adjusted in-hospital mortality was unchanged (IRR 0.98, 0.96-1.0004). Risk-adjusted ICU LOS (Estimate -0.06 days/year, -0.07 to -0.04) decreased. Risk-adjusted mortality varied significantly by disease.

CONCLUSION

Risk-adjusted ICU mortality rate did not change over the study period, but there was evidence of shifting disease burden across the critical care population. Our data provides useful information regarding future ICU personnel and resource needs.

Association of patient-to-intensivist ratio with hospital mortality in Australia and New Zealand

Purpose

The impact of intensivist workload on intensive care unit (ICU) outcomes is incompletely described and assessed across healthcare systems and countries. We sought to examine the association of patient-to-intensivist ratio (PIR) with hospital mortality in Australia/New Zealand (ANZ) ICUs.

Methods

We conducted a retrospective study of adult admissions to ANZ ICUs (August 2016–June 2018) using two cohorts: “narrow”, based on previously used criteria including restriction to ICUs with a single daytime intensivist; and “broad”, refined by individual ICU daytime staffing information. The exposure was average daily PIR and the outcome was hospital mortality. We used summary statistics to describe both cohorts and multilevel multivariable logistic regression models to assess the association of PIR with mortality. In each, PIR was modeled using restricted cubic splines to allow for non-linear associations. The broad cohort model included non-PIR physician and non-physician staffing covariables.

Results

The narrow cohort of 27,380 patients across 67 ICUs (predicted mortality: median 1.2% [IQR 0.4–1.4%]; mean 5.9% [sd 13.2%]) had a median PIR of 10.1 (IQR 7–14). The broad cohort of 91,206 patients across 73 ICUs (predicted mortality: 1.9% [0.6–6.5%]; 7.6% [14.9%]) had a median PIR of 7.8 (IQR 5.8–10.2). We found no association of PIR with mortality in either the narrow (PIR 1st spline term odds ratio [95% CI]: 1 [0.94, 1.06], Wald testing of spline terms p = 0.61) or the broad (1.02 [0.97, 1.07], p = 0.4) cohort.

Conclusion

We found no association of PIR with hospital mortality across ANZ ICUs. The low cohort predicted mortality may limit external validity.

Supplementary Information

The online version contains supplementary material available at 10.1007/s00134-021-06575-z.

Mortality prediction in intensive care units including premorbid functional status improved performance and internal validity

OBJECTIVE

Prognostic models are key for benchmarking intensive care units (ICUs). They require up-to-date predictors and should report transportability properties for reliable predictions. We developed and validated an in-hospital mortality risk prediction model to facilitate benchmarking, quality assurance, and health economics evaluation.

STUDY DESIGN AND SETTING

We retrieved data from the database of an international (Finland, Estonia, Switzerland) multicenter ICU cohort study from 2015 to 2017. We used a hierarchical logistic regression model that included age, a modified Simplified Acute Physiology Score-II, admission type, premorbid functional status, and diagnosis as grouping variable. We used pooled and meta-analytic cross-validation approaches to assess temporal and geographical transportability.

RESULTS

We included 61,224 patients treated in the ICU (hospital mortality 10.6%). The developed prediction model had an area under the receiver operating characteristic curve 0.886, 95% confidence interval (CI) 0.882-0.890; a calibration slope 1.01, 95% CI (0.99-1.03); a mean calibration -0.004, 95% CI (-0.035 to 0.027). Although the model showed very good internal validity and geographic discrimination transportability, we found substantial heterogeneity of performance measures between ICUs (I-squared: 53.4-84.7%).

CONCLUSION

A novel framework evaluating the performance of our prediction model provided key information to judge the validity of our model and its adaptation for future use.

Inflammation and Liver Cell Death in Patients with Hepatitis C Viral Infection

Hepatitis C virus (HCV)-induced liver disease contributes to chronic hepatitis. The immune factors identified in HCV include changes in the innate and adaptive immune system. The inflammatory mediators, known as "inflammasome", are a consequence of the metabolic products of cells and commensal or pathogenic bacteria and viruses. The only effective strategy to prevent disease progression is eradication of the viral infection. Immune cells play a pivotal role during liver inflammation, triggering fibrogenesis. The present paper discusses the potential role of markers in cell death and the inflammatory cascade leading to the severity of liver damage. We aim to present the clinical parameters and laboratory data in a cohort of 88 HCV-infected non-cirrhotic and 25 HCV cirrhotic patients, to determine the characteristic light microscopic (LM) and transmission electron microscopic (TEM) changes in their liver biopsies and to present the link between the severity of liver damage and the serum levels of cytokines and caspases. A matched HCV non-infected cohort was used for the comparison of serum inflammatory markers. We compared the inflammation in HCV individuals with a control group of 280 healthy individuals. We correlated the changes in inflammatory markers in different stages of the disease and the histology. We concluded that the serum levels of cytokine, chemokine, and cleaved caspase markers reveal the inflammatory status in HCV. Based upon the information provided by the changes in biomarkers the clinician can monitor the severity of HCV-induced liver damage. New oral well-tolerated treatment regimens for chronic hepatitis C patients can achieve cure rates of over 90%. Therefore, using the noninvasive biomarkers to monitor the evolution of the liver damage is an effective personalized medicine procedure to establish the severity of liver injury and its repair.

Less is more: Detecting clinical deterioration in the hospital with machine learning using only age, heart rate, and respiratory rate

AIM

We sought to develop a machine learning analytic (eCART Lite) for predicting clinical deterioration using only age, heart rate, and respiratory data, which can be pulled in real time from patient monitors and updated continuously without need for additional inputs or cumbersome electronic health record integrations.

METHODS

We utilized a multicenter dataset of adult admissions from five hospitals. We trained a gradient boosted machine model using only current and 24-hour trended heart rate, respiratory rate, and patient age to predict the probability of intensive care unit (ICU) transfer, death, or the combined outcome of ICU transfer or death. The area under the receiver operating characteristic curve (AUC) was calculated in the validation cohort and compared to those for the Modified Early Warning Score (MEWS), National Early Warning Score (NEWS), and eCARTv2, a previously-described, 27-variable, cubic spline, logistic regression model without trends.

RESULTS

Of the 556,848 included admissions, 19,509 (3.5%) were transferred to an ICU and 5764 (1.0%) died within 24 hours of a ward observation. eCART Lite significantly outperformed the MEWS, NEWS, and eCART v2 for predicting ICU transfer (0.79 vs 0.71, 0.74, and 0.78, respectively; p < 0.01) and the combined outcome (0.80 vs 0.72, 0.76, and 0.79, respectively; p < 0.01). Two of the strongest predictors were respiratory rate and heart rate.

CONCLUSION

Using only three inputs, we developed a tool for predicting clinical deterioration that is similarly or more accurate than commonly-used algorithms, with potential for use in inpatient settings with limited resources or in scenarios where low-cost tools are needed.

Non-invasive Biomarkers of Liver Inflammation and Cell Death in Response to Alcohol Detoxification

Introduction

Alcohol-related liver disease (ALD) represents the most common liver disease worldwide, however, the underlying molecular mechanisms are still poorly understood. Namely centrilobular inflammation and programmed cell death are characteristic to ALD and it remains to be elucidated why they persist despite the absence of alcohol.

Aims

To study the effects of alcohol withdrawal in a cohort of heavy drinkers and the role of cirrhosis by using non-invasive biomarkers such as cytokines, apoptotic and angiogenic markers.

Methods

Caspase 3-cleaved M30, M65, cytokines (IL-6, IL-8), tumor necrosis factor alpha (TNF-α), transforming growth factor (TGF-β) and vascular endothelial growth factor (VEGF) were measured in 114 heavy drinkers. The role of alcohol detoxification was investigated in 45 patients. The liver histology was available in 23 patients. Fibrosis stage and steatosis were assessed by measuring liver stiffness (LS) and controlled attenuation parameter (CAP) in all patients using transient elastography (FibroScan, Echosens, Paris). Mean observation interval between the measurements was 5.7 ± 1.4 days (mean + -SD).

Results

Patients consumed a mean of 204 ± 148 g/day alcohol with a heavy drinking duration of 15.3 ± 11.0 years. Mean LS was 20.7 ± 24.4 kPa and mean CAP was 303 ± 51 dB/m. Fibrosis distribution was F0-38.1%, F1-2-31%, F3-7.1 and F4-23.9%. Apoptotic markers M30 and M65 were almost five times above normal. In contrast, TNF- α a, IL-8 and VEGF were only slightly elevated. Patients with manifest liver cirrhosis (F4) had significantly higher levels of M30, M65, IL-6 and IL-8. Histology features such as hepatocyte ballooning, Mallory-Denk bodies, inflammation and fibrosis were all significantly associated with elevated LS, and serum levels of TNF-alpha, M30 and M65 but not with CAP and other cytokines. During alcohol detoxification, LS, transaminases, TGF- β, IL-6, IL-8 and VEGF decreased significantly. In contrast, no significant changes were observed for M30, M65 and TNF- α and M30 even increased during detoxification in non-cirrhotic patients. Profibrogenic cytokine TGF-beta and pro-angiogenic cytokine VEGF showed a delayed decrease in patients with manifest cirrhosis.

Conclusion

Patients with alcohol-related cirrhosis have a pronounced apoptotic activity and a distinct inflammatory response that only partly improves after 1 week of alcohol detoxification. Alcohol withdrawal may represent an important approach to better dissect the underlying mechanisms in the setting of alcohol metabolism.

Incident haemodialysis and outcomes in the Top End of Australia

Objective The Northern Territory has the highest incidence of haemodialysis care for end-stage kidney disease in Australia. Although acute kidney injury (AKI) is a recognised risk for chronic kidney disease (CKD), the effect of AKI causing incident haemodialysis (iHD) is unknown. Audits identifying antecedents of iHD may inform health service planning. Thus, the aims of this study were to describe: (1) the development of an iHD recording system involving patients with AKI and CKD; and (2) the incidence, patient characteristics and mortality for patients with dialysis-requiring AKI. Methods A retrospective data linkage study was conducted using eight clinical and administrative datasets of adults receiving iHD during the period from July 2011 to December 2012 within a major northern Australian hospital for AKI without CKD (AKI), AKI in people with pre-existing CKD (AKI/CKD) and CKD (without AKI). The time to death was identified by the Northern Territory Register of deaths. Results In all, 121 iHD treatments were provided for the cohort, whose mean age was 51.5 years with 53.7% female, 68.6% Aboriginal ethnicity and 46.3% with diabetes. iHD was provided for AKI (23.1%), AKI/CKD (47.1%) and CKD (29.8%). The 90-day mortality rate was 25.6% (AKI 39.3%, AKI/CKD 22.8%, CKD 19.4%). The 3-year mortality rate was 45.5% (AKI 53.6%, AKI/CKD 22.8%, CKD 19.4%). The time between requesting data from custodians and receipt of data ranged from 15 to 1046 days. Conclusion AKI in people with pre-existing CKD was a common cause of iHD. Health service planning and community health may benefit from AKI prevention strategies and the implementation of sustainable and permanent linkages with the datasets used to monitor prospective incident haemodialysis. What is known about the topic? AKI is a risk factor for CKD. The Northern Territory has the highest national incidence rates of dialysis-dependent end-stage kidney disease, but has no audit tool describing outcomes of dialysis-requiring AKI. What does this paper add? We audited all iHD and showed 25.6% mortality within the first 90 days of iHD and 45.5% overall mortality at 3 years. AKI in people with pre-existing CKD caused 47.1% of iHD. What are the implications for practitioners? Health service planning and community health may benefit from AKI prevention strategies and the implementation of sustainable and permanent linkages with the datasets used to monitor prospective incident haemodialysis.

Early prediction of in-hospital mortality in acute pancreatitis: a retrospective observational cohort study based on a large multicentre critical care database

OBJECTIVE

To develop and validate a prediction model for predicting in-hospital mortality in patients with acute pancreatitis (AP).

DESIGN

A retrospective observational cohort study based on a large multicentre critical care database.

SETTING

All subject data were collected from the eICU Collaborative Research Database (eICU-CRD), which covers 200 859 intensive care unit admissions of 139 367 patients in 208 US hospitals between 2014 and 2015.

PARTICIPANTS

A total of 746 patients with AP were drawn from eICU-CRD. Due to loss to follow-up (four patients) or incomplete data (364 patients), 378 patients were enrolled in the primary cohort to establish a nomogram model and to conduct internal validation.

PRIMARY AND SECONDARY OUTCOME MEASURES

The outcome of the prediction model was in-hospital mortality. All risk factors found significant in the univariate analysis were considered for multivariate analysis to adjust for confounding factors. Then a nomogram model was established. The performance of the nomogram model was evaluated by the concordance index (C-index) and the calibration plot. The nomogram model was internally validated using the bootstrap resampling method. The predictive accuracy of the nomogram model was compared with that of Acute Physiology, Age, and Chronic Health Evaluation (APACHE) IV. Decision curve analysis (DCA) was performed to evaluate and compare the potential net benefit using of different predictive models.

RESULTS

The overall in-hospital mortality rate is 4.447%. Age, BUN (blood urea nitrogen) and lactate (ABL) were the independent risk factors determined by multivariate analysis. The C-index of nomogram model ABL (0.896 (95% CI 0.825 to 0.967)) was similar to that of APACHE IV (p=0.086), showing a comparable discriminating power. Calibration plot demonstrated good agreement between the predicted and the actual in-hospital mortality. DCA showed that the nomogram model ABL was clinically useful.

CONCLUSIONS

Nomogram model ABL, which used readily available data, exhibited high predictive value for predicting in-hospital mortality in AP.

Triage and Prognostication of Cancer Patients Admitted to the Intensive Care Unit

Cancer remains a leading cause of morbidity and mortality. Advances in cancer screening, early detection, targeted therapies, and supportive care have led to improvements in outcomes and quality of life. The rapid increase in novel cancer therapies can cause life-threatening adverse events. The need for intensive care unit (ICU) care is projected to increase. Until 2 decades ago, cancer diagnosis often precluded ICU admission. Recently, substantial cancer survival has been achieved; therefore, ICU denial is not recommended. ICU resources are limited and expensive; hence, appropriate utilization is needed. This review focuses on triage and prognosis in critically ill cancer patients requiring ICU admission.

Epidemiological trends of surgical admissions to the intensive care unit in the United States

BACKGROUND

Epidemiologic assessment of surgical admissions into intensive care units (ICUs) provides a framework to evaluate health care system efficiency and project future health care needs.

METHODS

We performed a 9-year (2008-2016), retrospective, cohort analysis of all adult admissions to 88 surgical ICUs using the prospectively and manually abstracted Cerner Acute Physiology and Chronic Health Evaluation Outcomes database. We stratified patients into 13 surgical cohorts and modeled temporal trends in admission, mortality, surgical ICU length of stay (LOS), and change in functional status (FS) using generalized mixed-effects and Quasi-Poisson models to obtain risk-adjusted outcomes.

RESULTS

We evaluated 78,053 ICU admissions and observed a significant decrease in admissions after transplant and thoracic surgery, with a concomitant increase in admissions after otolaryngological and facial reconstructive procedures (all p < 0.05). While overall risk-adjusted mortality remained stable over the study period; mortality significantly declined in orthopedic, cardiac, urologic, and neurosurgical patients (all p < 0.05). Cardiac, urologic, gastrointestinal, neurosurgical, and orthopedic admissions showed significant reductions in LOS (all p < 0.05). The overall rate of FS deterioration increased per year, suggesting ICU-related disability increased over the study period.

CONCLUSION

Temporal analysis demonstrates a significant change in the type of surgical patients admitted to the ICU over the last decade, with decreasing mortality and LOS in selected cohorts, but an increasing rate of FS deterioration. Improvement in ICU outcomes may highlight the success of health care advancements within certain surgical cohorts, while simultaneously identifying cohorts that may benefit from future intervention. Our findings have significant implications in health care systems planning, including resource and personnel allocation, education, and surgical training.

LEVEL OF EVIDENCE

Economic/decision, level IV.Epidemiologic, level IV.

Serum Albumin Levels: Who Needs Them?

OBJECTIVES

The purpose of this critical narrative review is to discuss common indications for ordering serum albumin levels in adult critically ill patients, evaluate the literature supporting these indications, and provide recommendations for the appropriate ordering of serum albumin levels.

DATA SOURCES

PubMed (1966 to August 2020), Cochrane Library, and current clinical practice guidelines were used, and bibliographies of retrieved articles were searched for additional articles.

STUDY SELECTION AND DATA EXTRACTION

Current clinical practice guidelines were the preferred source of recommendations regarding serum albumin levels for guiding albumin administration and for nutritional monitoring. When current comprehensive reviews were available, they served as a baseline information with supplementation by subsequent studies.

DATA SYNTHESIS

Serum albumin is a general marker of severity of illness, and hypoalbuminemia is associated with poor patient outcome, but albumin is an acute phase protein, so levels vacillate in critically ill patients in conjunction with illness fluctuations. The most common reasons for ordering serum albumin levels in intensive care unit (ICU) settings are to guide albumin administration, to estimate free phenytoin or calcium levels, for nutritional monitoring, and for severity-of-illness assessment.

RELEVANCE TO PATIENT CARE AND CLINICAL PRACTICE

Because hypoalbuminemia is common in the ICU setting, inappropriate ordering of serum albumin levels may lead to unnecessary albumin administration or excessive macronutrient administration in nutritional regimens, leading to possible adverse effects and added costs.

CONCLUSIONS

With the exception of the need to order serum albumin levels as a component of selected severity-of-illness scoring systems, there is little evidence or justification for routinely ordering levels in critically ill patients.

Surgical Intensive Care Unit Admission Variables Predict Subsequent Readmission

Intensive care unit (ICU) readmissions are associated with increased resource use. Defining predictors may improve resource use. Surgical ICU patients requiring readmission will have different characteristics than those who do not. We conducted a retrospective cohort study of a prospectively maintained database. The Acute Physiology and Chronic Health Evaluation (APACHE) IV quality database identified patients admitted January 1 through December 31, 2011. Patients were divided into groups: NREA = patients admitted to the ICU, discharged, and not readmitted versus REA = patients admitted to the ICU, discharged, and readmitted. Comparisons were made at index admission, not readmission. Categorical variables were compared by Fisher's exact testing and continuous variables by t test. Multivariate logistic regression identified independent predictors of readmission. There were 765 admissions. Seventy-seven patients required readmission 94 times (12.8% rate). Sixty-two patients died on initial ICU admission. Admission severity of illness was significantly higher (APACHE III score: 69.54 ± 21.11 vs 54.88 ± 23.48) in the REA group. Discharge acute physiology scores were equal between groups (47.0 ± 39.2 vs 44.2 ± 34.0, P = nonsignificant). In multivariate analysis, REA patients were more likely admitted to emergency surgery (odds ratio, 1.9; 95% confidence interval, 1.01 ± 3.5) more likely to have a history of immunosuppression (2.7, 1.4 ± 5.3) or higher Acute Physiology Score (1.02; 1.0 ± 1.03) than NREA. Patients who require ICU readmission have a different admission profile than those who do not “bounce back.” Understanding these differences may allow for quality improvement projects such as instituting different discharge criteria for different patient populations.

INSMA: An integrated system for multimodal data acquisition and analysis in the intensive care unit

Modern intensive care units (ICU) are equipped with a variety of different medical devices to monitor the physiological status of patients. These devices can generate large amounts of multimodal data daily that include physiological waveform signals (arterial blood pressure, electrocardiogram, respiration), patient alarm messages, numeric vitals data, etc. In order to provide opportunities for increasingly improved patient care, it is necessary to develop an effective data acquisition and analysis system that can assist clinicians and provide decision support at the patient bedside. Previous research has discussed various data collection methods, but a comprehensive solution for bedside data acquisition to analysis has not been achieved. In this paper, we proposed a multimodal data acquisition and analysis system called INSMA, with the ability to acquire, store, process, and visualize multiple types of data from the Philips IntelliVue patient monitor. We also discuss how the acquired data can be used for patient state tracking. INSMA is being tested in the ICU at University Hospitals Cleveland Medical Center.

Comparing Eight Prognostic Scores in Predicting Mortality of Patients with Acute-On-Chronic Liver Failure Who Were Admitted to an ICU: A Single-Center Experience

Limited data is available on long-term outcome predictions for patients with acute-on-chronic liver failure (ACLF) in an intensive care unit (ICU) setting. Assessing the reliability and accuracy of several mortality prediction models for these patients is helpful. Two hundred forty-nine consecutive patients with ACLF and admittance to the liver ICU in a single center in northern Taiwan between December 2012 and March 2015 were enrolled in the study and were tracked until February 2017. Ninety-one patients had chronic hepatitis B-related cirrhosis. Clinical features and laboratory data were collected at or within 24 h of the first ICU admission course. Eight commonly used clinical scores in chronic liver disease were calculated. The primary endpoint was overall survival. Acute physiology and chronic health evaluation (APACHE) III and chronic liver failure consortium (CLIF-C) ACLF scores were significantly superior to other models in predicting overall mortality as determined by time-dependent receiver operating characteristic (ROC) curve analysis (area under the ROC curve (AUROC): 0.817). Subgroup analysis of patients with chronic hepatitis B-related cirrhosis displayed similar results. CLIF-C organ function (OF), CLIF-C ACLF, and APACHE III scores were statistically superior to the mortality probability model III at zero hours (MPM0-III) and the simplified acute physiology (SAP) III scores in predicting 28-day mortality. In conclusion, for 28-day and overall mortality prediction of patients with ACLF admitted to the ICU, APACHE III, CLIF-OF, and CLIF-C ACLF scores might outperform other models. Further prospective study is warranted.

Clinical and Epidemiological Characteristics of Severe Acute Adult Poisoning Cases in Martinique: Implicated Toxic Exposures and Their Outcomes

The epidemiology of severe acute poisonings in the French overseas departments of the Americas remains poorly reported. The main objective of this study was to determine the epidemiology and characteristics of severe acutely poisoned adult patients.

METHODS

A retrospective descriptive study was conducted from 1 January 2000 to 31 December 2010 in severely poisoned patients presenting to the emergency department (ED) of the University Hospital of Martinique, and the general public hospitals of Lamentin and Trinité.

RESULTS

During the study period, 291 patients were admitted for severe poisoning, giving an incidence rate of 7.7 severe cases/100,000 inhabitants. The mean age was 46 ± 19 years and 166 (57%) were male. Psychiatric disorders were recorded in 143 (49.8%) patients. Simplified Acute Psychological Score (SAPS II) at admission was 39 ± 23 points and Poisoning Severity Score (PSS) was 2.7 ± 0.8 points. Death was recorded in 30 (10.3%) patients and hospital length of stay was 6 ± 7 days. The mode of intoxication was intentional self-poisoning in 87% of cases and drug overdose was recorded in 13% of cases. The toxic agent involved was a therapeutic drug in 58% and a chemical product in 52% of cases. The predominant clinical manifestations were respiratory failure (59%), hemodynamic failure (27%), neurologic failure (45%), gastrointestinal manifestations (27%), and renal failure (11%). Polypnea, shock, ventricular fibrillation or tachycardia, and gastro-intestinal disorders were the main symptoms associated with death. The main biological abnormalities associated with death in our patients were metabolic acidosis, hypokalemia, hyperlactatemia, hypocalcemia, renal injury, rhabdomyolysis, increased aspartate aminotransferases, and thrombocytopenia. Extracorporal membrane oxygenation (ECMO) was used in three patients and specific antidotes were used in 21% of patients.

CONCLUSIONS

Acute poisonings remain a major public health problem in Martinique with different epidemiological characteristics to those in mainland France, with a high incidence of poisoning by rural and household toxins.

The malnutrition in polytrauma patients (MaPP) study: Research protocol

BACKGROUND

Polytrauma patients are at risk of considerable harm from malnutrition due to the metabolic response to trauma. However, there is little knowledge of (the risk of) malnutrition and its consequences in these patients. Recognition of sub-optimally nourished polytrauma patients and their nutritional needs is crucial to prevent complications and optimize their clinical outcomes.

AIM

The primary objective is to investigate whether polytrauma patients admitted to the Intensive Care Unit (ICU) who have or develop malnutrition have a higher complication rate than patients who are and remain well nourished. Secondary objectives are to determine the prevalence of pre-existent and in-hospital acquired malnutrition in these patients, to assess the association between malnutrition and long-term outcomes, and to determine the association between serum biomarkers (albumin and pre-albumin) and malnutrition.

METHODS

This international observational prospective cohort study will be performed at three Level-1 trauma centers in the United States and two Level-1 centers in the Netherlands. Adult polytrauma patients (Injury Severity Score ≥16) admitted to the ICU of one of the participating centers directly from the Emergency Department are eligible for inclusion. Nutritional status and risk of malnutrition will be assessed using the Subjective Global Assessment (SGA) scale and Nutritional Risk in Critically Ill (NUTRIC) score, respectively. Nutritional intake, biomarkers and complications will be collected daily. Patients will be followed up to one year after discharge for long-term outcomes.

CONCLUSIONS

This international prospective cohort study aims to gain more insight into the effect and consequences of malnutrition in polytrauma patients admitted to the ICU.

Prediction of 60-Day Case Fatality in Critically Ill Patients Receiving Renal Replacement Therapy: External Validation of a Prediction Model

BACKGROUND

A recent prognostic model, predicting 60-day case fatality in critically ill patients requiring renal replacement therapy (RRT), has been developed (Acute Renal Failure Trial Network [ATN] study). Because many prognostic models are suggested in literature, but just a few have found its way into clinical practice, we aimed to externally validate this prediction model in an independent cohort.

METHODS

A total of 1,053 critically ill patients requiring RRT from the MIMIC-III database were analyzed. The models' discrimination was evaluated using c-statistics. Calibration was evaluated by Hosmer-Lemeshow (H-L) test and GiViTi calibration belt.

RESULTS

In a case-mix population, including patients with normal or altered serum creatinine (sCr) at intensive care unit admission, discrimination was moderate, with a c-statistic of 0.71 in the nonintegerized risk model. In patients with altered baseline sCr, better discrimination was achieved with the integer risk model (0.76, 95% confidence interval, 0.71-0.81). As for the calibration, although the H-L test was good only in patients with normal/slightly altered sCr at admission, the calibration belt disclosed no significant deviations from the bisector line for any of the models in patients, regardless of admission sCr. Of note, a refitted model had a c-statistics of 0.85, similar to the derivation cohort.

CONCLUSIONS

The ATN prognostic model can be useful in a broad cohort of critically ill patients. Although it showed only moderate discrimination capacity when patients with elevated admission sCr were included, using a refitted model improved it, illustrating the need for continuous external validation and updating of prognostic models over time before their implementation in clinical practice.

Renal replacement therapy intensity for acute kidney injury and recovery to dialysis independence: a systematic review and individual patient data meta-analysis

Background

There is no consensus whether higher intensity dose renal replacement therapy (RRT) compared with standard intensity RRT has survival benefit and achieves better renal recovery in acute kidney injury (AKI).

Methods

In an individual patient data meta-analysis, we merged individual patient data from randomized controlled trials (RCTs) comparing high with standard intensity RRT in intensive care unit patients with severe AKI. The primary outcome was all-cause mortality. The secondary outcome was renal recovery assessed as the proportion of patients who were RRT dependent at key trial endpoints and by time to the end of RRT dependence.

Results

Of the eight prospective RCTs assessing different RRT intensities, seven contributed individual patient data (n = 3682) to the analysis. Mortality was similar between the two groups at 28 days [769/1884 (40.8%) and 744/1798 (41.4%), respectively; P = 0.40] after randomization. However, more participants assigned to higher intensity therapy remained RRT dependent at the most common key study point of 28 days [e.g. 292/983 (29.7%) versus 235/943 (24.9%); relative risk 1.15 (95% confidence interval 1.00-1.33); P = 0.05]. Time to cessation of RRT through 28 days was longer in patients receiving higher intensity RRT (log-rank test P = 0.02) and when continuous renal replacement therapy was used as the initial modality of RRT (log-rank test P = 0.03).

Conclusions

In severe AKI patients, higher intensity RRT does not affect mortality but appears to delay renal recovery.

Trial Registration

Australian New Zealand Clinical Trials Registry (ANZCTR) identifier ACTRN12615000394549 (https://www.anzctr.org.au/Trial/Registration/TrialReview.aspx?ACTRN=12615000394549).

Combination of APACHE Scoring Systems with Adductor Pollicis Muscle Thickness for the Prediction of Mortality in Patients Who Spend More Than One Day in the Intensive Care Unit

Background

The objective of the present study was to compare the ability of Acute Physiology and Chronic Health Evaluation (APACHE) scoring systems with the combination of an anthropometric variable score “adductor pollicis muscle (APM) thickness” to the APACHE systems in predicting mortality in the intensive care unit.

Methods

A prospective observational study was conducted with the APM thickness in the dominant hand, and APACHE II and III scores were measured for each patient upon admission. Given scores for the APM thickness were added to APACHE score systems to make two composite scores of APACHE II-APM and APACHE III-APM. The accuracy of the two composite models and APACHE II and III systems in predicting mortality of patients was compared using the area under the ROC curve.

Results

Three hundred and four patients with the mean age of 54.75 ± 18.28 years were studied, of which 96 (31.57%) patients died. Median (interquartile range) of APACHE II and III scores was 15 (12–20) and 47 (33–66), respectively. Median (interquartile range) of APM thickness was 15 (12–17) mm, respectively. The area under the ROC curves for the prediction of mortality was 0.771 (95% CI: 0.715–0.827), 0.802 (95% CI: 0.751–0.854), 0.851 (95% CI: 0.807–0.896), and 0.865 (95% CI: 0.822–0.908) for APACHE II, APACHE III, APACHE II-APM, and APACHE III-APM, respectively.

Conclusion

Although improvements in the area under ROC curves were not statistically significant when the APM thickness added to the APACHE systems, but the numerical value added to AUCs are considerable.

Polytrauma patients in the Netherlands and the USA: A bi-institutional comparison of processes and outcomes of care

BACKGROUND

Modern trauma systems differ worldwide, possibly leading to disparities in outcomes. We aim to compare characteristics and outcomes of blunt polytrauma patients admitted to two Level 1 Trauma Centers in the US (USTC) and the Netherlands (NTC).

METHODS

For this retrospective study the records of 1367 adult blunt trauma patients with an Injury Severity Score (ISS) ≥ 16 admitted between July 1, 2011 and December 31, 2013 (640 from NTC, 727 from USTC) were analysed.

RESULTS

The USTC group had a higher Charlson Comorbidity Index (mean [standard deviation] 1.15 [2.2] vs. 1.73 [2.8], p<0.0001) and Injury Severity Score (median [interquartile range, IQR] 25 [17-29] vs. 21 [17-26], p<0.0001). The in-hospital mortality was similar in both centers (11% in USTC vs. 10% NTC), also after correction for baseline differences in patient population in a multivariable analysis (adjusted odds ratio 0.95, 95% confidence interval 0.61-1.48, p=0.83). USTC patients had a longer Intensive Care Unit stay (median [IQR] 4 [2-11] vs. 2 [2-7] days, p=0.006) but had a shorter hospital stay (median [IQR] 6 [3-13] vs. 8 [4-16] days, p<0.0001). USTC patients were discharged more often to a rehabilitation center (47% vs 10%) and less often to home (46% vs. 66%, p<0.0001), and had a higher readmission rate (8% vs. 4%, p=0.01).

CONCLUSION

Although several outcome parameters differ in two urban area trauma centers in the USA and the Netherlands, the quality of care for trauma patients, measured as survival, is equal. Other outcomes varied between both trauma centers, suggesting that differences in local policies and processes do influence the care system, but not so much the quality of care as reflected by survival.

Late-onset moderate to severe acute respiratory distress syndrome is associated with shorter survival and higher mortality: a two-stage association study

PURPOSE

To evaluate the association between acute respiratory distress syndrome (ARDS) onset time and prognosis.

METHODS

Patients with moderate to severe ARDS (N = 876) were randomly assigned into derivation (N = 520) and validation (N = 356) datasets. Both 28-day and 60-day survival times after ARDS onset were analyzed. A data-driven cutoff point between early- and late-onset ARDS was determined on the basis of mortality risk effects of onset times. We estimated the hazard ratio (HR) and odds ratio (OR) of late-onset ARDS using a multivariate Cox proportional hazards model of survival time and a multivariate logistic regression model of mortality rate, respectively.

RESULTS

Late-onset ARDS, defined as onset over 48 h after intensive care unit (ICU) admission (N = 273, 31%), was associated with shorter 28-day survival time: HR = 2.24, 95% CI 1.48-3.39, P = 1.24 × 10^-4 (derivation); HR = 2.16, 95% CI 1.33-3.51, P = 1.95 × 10^-3 (validation); and HR = 2.00, 95% CI 1.47-2.72, P = 1.10 × 10^-5 (combined dataset). Late-onset ARDS was also associated with shorter 60-day survival time: HR = 1.70, 95% CI 1.16-2.48, P = 6.62 × 10^-3 (derivation); HR = 1.78, 95% CI 1.15-2.75, P = 9.80 × 10^-3 (validation); and HR = 1.59, 95% CI 1.20-2.10, P = 1.22 × 10^-3 (combined dataset). Meanwhile, late-onset ARDS was associated with higher 28-day mortality rate (OR = 1.46, 95% CI 1.04-2.06, P = 0.0305) and 60-day mortality rate (OR = 1.44, 95% CI 1.03-2.02, P = 0.0313).

CONCLUSIONS

Late-onset moderate to severe ARDS patients had both shorter survival time and higher mortality rate in 28-day and 60-day observations.

Defining a High-Performance ICU System for the 21st Century: A Position Paper

In the fall of 1997 George D. Lundberg and John E. Wennberg wrote an editorial in JAMA calling for comprehensive quality improvement programs to become the driver of the American health care system. The suggestion came during the Second European Forum on Quality Improvement in Health Care held in Paris, France, in April 1997 and was based on comments made by Donald Berwick. The concept was to focus on an organized response to problem identification and proposed solutions to improve patient care and protect the health of the public. Critical care medicine represents a large segment of health care and is undergoing dramatic changes during our managed care revolution. General ICU severity of illness models have been developed, tested, and shown to provide a useful estimate of hospital mortality for populations of critically ill patients. These systems have captured the imagination of clinical researchers and have become an integral component of a large number of publications as well as a part of many ICU databases. These risk adjustment severity models are remarkably robust for heterogeneous patient populations but the models have not been shown to validate well in new settings. We feel that by focusing on the episode of critical illness rather than each individual ICU admission and by going beyond the traditional acute hospital discharge to determine whether the patient lives or dies, we can better evaluate critical care system performance and cost-effectiveness. The incentives for high quality/low cost should favor integrated comprehensive critical care delivery systems. Programs that score well should be identified as high quality and be honored as medallion level 1 ICUs. We challenge national and international critical care societies to evaluate and then debate the described definitions and recommendations as a call to action.

Obese ICU Patients

This project described prospectively obese, critically ill patients and the resources critical care nurses used to care for these challenging patients. It also examined the relationship between resources used by nurses and patient outcomes, including complications and length of stay. Forty-three participants were enrolled. Patients with a body mass index (BMI) 40 kg/m2 used the majority of equipment and personnel resources and experienced a prolonged length of stay. The most common equipment used was a specialty bed or mattress; the most common complications were related to the pulmonary system. Initial use of multiple resources may indicate a patient at risk for adverse outcomes. Nurses can use findings to anticipate care needs and develop interventions, such as optimal positioning, to avoid adverse outcomes.

Use of a supportive care pathway for end-of-life care in an intensive care unit: a qualitative study

BACKGROUND

Providing palliative care support in intensive care settings is beneficial, however, barriers to delivering high-quality end-of-life care remain. To address this, pathways have been used to improve the quality of palliative care in generalist settings. This study describes the views of health professionals using a supportive care pathway in intensive care.

DESIGN

Qualitative semi-structured interviews were conducted with ten health professionals working in a surgical intensive care unit. The data were analysed thematically.

RESULTS

Participants were positive about the effect of the supportive care pathway on patient care, particularly in enabling consensus in care planning. Some expressed concerns including the difficulty of identifying the 'correct patients' for the pathway, the risk of it becoming a 'self-fulfilling prophecy', and a euphemism for dying.

CONCLUSION

Pathways are one potential mechanism for guiding care planning and communicating the goals of care to colleagues, patients and families, thus contributing to improvements in palliative care.

The Acute Physiology and Chronic Health Evaluation IV, a New Scoring System for Predicting Mortality and Complications of Severe Acute Pancreatitis

OBJECTIVES

Severe acute pancreatitis is associated with significant morbidity/mortality; thus, the ability to predict hospital course is imperative. An updated version of the Acute Physiology and Chronic Health Evaluation II (APACHE), APACHE IV, has recently been validated. Unlike other versions, APACHE IV uses hepatobiliary parameters and accounts for multiple comorbid conditions and sedation. The intention of this study was to examine APACHE IV for predicting mortality and secondary outcomes for pancreatitis in a prospective cohort. In addition, we compared APACHE IV to APACHE II, Bedside Index for Severity in Acute Pancreatitis, and Ranson criterion.

METHODS

We prospectively collected physiologic parameters for each scoring system in 266 patients with severe acute pancreatitis from August 2011 to April 2014. Prognostic value of each score was determined using the area under the receiver operating characteristic curve.

RESULTS

Among 266 patients, 59% were men, 52% were white, and 36.5% had alcohol-induced pancreatitis. Mortality occurred in 15 (5.6%), and an APACHE IV of 44 or greater predicted mortality in 100% of cases. The receiver operating characteristic curve for APACHE IV was 0.93 (confidence interval [CI], 0.88-0.97); APACHE II, 0.87 (CI, 0.80-0.94); Bedside Index for Severity in Acute Pancreatitis, 0.86 (CI, 0.78-0.94); and Ranson criterion, 0.90 (CI, 0.94-0.96).

CONCLUSION

The APACHE IV is a valid means for predicting mortality and disease-related complications in acute pancreatitis.

Predictive validity of the Braden Scale for pressure ulcer risk in hospitalized patients

PURPOSE

Although the Braden Scale has been used as a basic tool to assess pressure ulcer risk, the validity of its effectiveness and accuracy was insufficient. Therefore, this study developed the groundwork for the predictive validity of the Braden Scale through a meta-analysis of prospective diagnosis assessment research.

METHODS

Articles published between 1966 and 2013 from periodicals indexed in the Ovid Medline, Embase, CINAHL, KoreaMed, NDSL and other databases were selected, using the keyword 'pressure ulcer'. QUADAS-II was applied to assess the internal validity of the diagnostic studies. Selected studies were analyzed using meta-analysis with MetaDiSc 1.4.

RESULTS

Twenty-one diagnostic studies with high methodological quality, involving 6070 patients, were included. The meta-analysis revealed that the pooled sensitivity was 0.72 (95% CI 0.68, 0.75); pooled specificity was 0.81 (95% CI 0.80, 0.82), and the sROC AUC was 0.84 (SE = 0.02). A detail analysis confirmed that age and reference standards were the factors that affected the diagnostic accuracy of the Braden Scale.

CONCLUSION

The results suggest that the Braden Scale has a moderate predictive validity. This research also revealed the possibility that the predictive validity of the Braden Scale could be enhanced if it was applied differently according to the attributes of the study subjects.

A history of outcome prediction in the ICU

PURPOSE OF REVIEW

There are few first-hand accounts that describe the history of outcome prediction in critical care. This review summarizes the authors' personal perspectives about the development and evolution of Acute Physiology and Chronic Health Evaluation over the past 35 years.

RECENT FINDINGS

We emphasize what we have learned in the past and more recently our perspectives about the current status of outcome prediction, and speculate about the future of outcome prediction.

SUMMARY

There is increasing evidence that superior accuracy in outcome prediction requires complex modeling with detailed adjustment for diagnosis and physiologic abnormalities. Thus, an automated electronic system is recommended for gathering data and generating predictions. Support, either public or private, is required to assist users and to update and improve models. Current outcome prediction models have increasingly focused on benchmarks for resource use, a trend that seems likely to increase in the future.

Predicting one-year mortality of critically ill patients with early acute kidney injury: data from the prospective multicenter FINNAKI study

INTRODUCTION

No predictive models for long-term mortality in critically ill patients with acute kidney injury (AKI) exist. We aimed to develop and validate two predictive models for one-year mortality in patients with AKI based on data (1) on intensive care unit (ICU) admission and (2) on the third day (D3) in the ICU.

METHODS

This substudy of the FINNAKI study comprised 774 patients with early AKI (diagnosed within 24 hours of ICU admission). We selected predictors a priori based on previous studies, clinical judgment, and differences between one-year survivors and non-survivors in patients with AKI. We validated the models internally with bootstrapping.

RESULTS

Of 774 patients, 308 (39.8%, 95% confidence interval (CI) 36.3 to 43.3) died during one year. Predictors of one-year mortality on admission were: advanced age, diminished premorbid functional performance, co-morbidities, emergency admission, and resuscitation or hypotension preceding ICU admission. The area under the receiver operating characteristic curve (AUC) (95% CI) for the admission model was 0.76 (0.72 to 0.79) and the mean bootstrap-adjusted AUC 0.75 (0.74 to 0.75). Advanced age, need for mechanical ventilation on D3, number of co-morbidities, higher modified SAPS II score, the highest bilirubin value by D3, and the lowest base excess value on D3 remained predictors of one-year mortality on D3. The AUC (95% CI) for the D3 model was 0.80 (0.75 to 0.85) and by bootstrapping 0.79 (0.77 to 0.80).

CONCLUSIONS

The prognostic performance of the admission data-based model was acceptable, but not good. The D3 model for one-year mortality performed fairly well in patients with early AKI.

The safety and prognostic factors for mortality in extremely elderly patients undergoing an emergency operation

PURPOSE

As the number of elderly people has increased, the number of elderly patients who need emergency operations has also increased. Although there are many models to evaluate the risk of surgery in elderly patients, they all are associated with limitations. We herein evaluated the prognostic factors for surgical mortality in elderly patients more than 80 years old who needed emergency operations.

METHODS

A total of 171 patients more than 80 years old underwent emergency operations from January 2001 to December 2012. Among them, 79 patients with acute cholecystitis, panperitonitis and intestinal obstruction with strangulation, which included mortality cases, were included. We retrospectively reviewed the medical records of the patients and analyzed the prognostic factors for surgical mortality.

RESULTS

Forty-eight patients had a co-morbidity. Thirty-one patients initially had systemic inflammatory response syndrome. There were 27 surgical mortality cases. A univariate analysis revealed that panperitonitis, a positive blood culture and the level of albumin were significant prognostic factors predicting a worse prognosis. However, a multivariate analysis revealed that a serum albumin level more than 3.5 g/dL was the only significant prognostic factor (p = 0.037).

CONCLUSION

Surgeons cannot fully evaluate the risk of emergency operation cases. However, our data indicate that if patients do not show hypoalbuminemia, the surgeon may be able to perform an emergency operation without a high risk of surgical mortality.

Inpatient Stroke Care Quality for Veterans: Are There Differences between Veterans Affairs Medical Centers in the Stroke Belt and other Areas?

Background

Stroke mortality has been found to be much higher among residents in the stroke belt region than in the rest of United States, but it is not known whether differences exist in the quality of stroke care provided in Department of Veterans Affairs medical centers in states inside and outside this region.

Objective

We compared mortality and inpatient stroke care quality between Veterans Affairs medical centers inside and outside the stroke belt region.

Methods

Study patients were veterans hospitalized for ischemic stroke at 129 Veterans Affairs medical centers. Inpatient stroke care quality was assessed by 14 quality indicators. Multivariable logistic regression models were fit to examine differences in quality between facilities inside and outside the stroke belt, adjusting for patient characteristics and Veterans Affairs medical centers clustering effect.

Results

Among the 3909 patients, 28·1% received inpatient ischemic stroke care in 28 stroke belt Veterans Affairs medical centers, and 71·9% obtained care in 101 non-stroke belt Veterans Affairs medical centers. Patients cared for in stroke belt Veterans Affairs medical centers were more likely to be younger, Black, married, have a higher stroke severity, and less likely to be ambulatory pre-stroke. We found no statistically significant differences in short- and long-term post-admission mortality and inpatient care quality indicators between the patients cared for in stroke belt and non-stroke belt Veterans Affairs medical centers after risk adjustment.

Conclusions

These data suggest that a stroke belt does not exist within the Veterans Affairs health care system in terms of either post-admission mortality or inpatient care quality.

A pilot assessment of alpha-stat vs pH-stat arterial blood gas analysis after cardiac arrest

PURPOSE

Resuscitated cardiac arrest (CA) patients typically receive therapeutic hypothermia, but arterial blood gases (ABGs) are often assessed after adjustment to 37°C (alpha-stat) instead of actual body temperature (pH-stat). We sought to compare alpha-stat and pH-stat assessment of PaO2 and PaCO2 in such patients.

MATERIALS AND METHODS

Using ABG data obtained during the first 24 hours of intensive care unit admission, we determined the impact of measured alpha vs calculated pH-stat on PaO2 and PaCO2 on patient classification and outcomes for CA patients.

RESULTS

We assessed 1013 ABGs from 120 CA patients with a median age of patients 66 years (interquartile range, 50-76). Median alpha-stat PaO2 changed from 122 (95-156) to 107 (82-143) mm Hg with pH-stat and median PaCO2 from 39 (34-46) to 35 (30-41) mm Hg (both P < .001). Using the categories of hyperoxemia, normoxemia, and hypoxemia, pH-stat estimation of PaO2 reclassified approximately 20% of patients. Using the categories of hypercapnia, normocapnia, and hypocapnia, pH stat estimation of PaCO2 reclassified approximately 40% of patients. The mortality of patients in different PaO2 and PaCO2 categories was similar for pH-stat and alpha-stat.

CONCLUSIONS

Using the pH-stat method, fewer resuscitated CA patients admitted to intensive care unit were classified as hyperoxemic or hypercapnic compared with alpha-stat. These findings suggest an impact of ABG assessment methodology on PaO2, PaCO2 , and patient classification but not on associated outcomes.

Increased ICU resource needs for an academic emergency general surgery service*

OBJECTIVE

ICU needs of nontrauma emergency general surgery patients are poorly described. This study was designed to compare ICU utilization of emergency general surgery patients admitted to an acute care emergency surgery service with other general surgery patients. Our hypothesis is that tertiary care emergency general surgery patients utilize more ICU resources than other general surgical patients.

DESIGN

Retrospective database review.

SETTING

Academic, tertiary care, nontrauma surgical ICU.

PATIENTS

All patients admitted to the surgical ICU over age 18 between March 2004 and June 2012.

INTERVENTIONS

None.

MEASUREMENTS AND MAIN RESULTS

Six thousand ninety-eight patients were evaluated: 1,053 acute care emergency surgery, 1,964 general surgery, 1,491 transplant surgery, 995 facial surgery/otolaryngology, and 595 neurosurgery. Acute care emergency surgery patients had statistically significantly longer ICU lengths of stay than other groups: acute care emergency surgery (13.5 ± 17.4 d) versus general surgery (8.7 ± 12.9), transplant (7.8 ± 11.6), oral-maxillofacial surgery (5.5 ± 4.2), and neurosurgery (4.47 ± 9.8) (all p< 0.01). Ventilator usage, defined by percentage of total ICU days patients required mechanical ventilation, was significantly higher for acute care emergency surgery patients: acute care emergency surgery 73.4% versus general surgery 64.9%, transplant 63.3%, oral-maxillofacial surgery 58.4%, and neurosurgery 53.1% (all p < 0.01). Continuous renal replacement therapy usage, defined as percent of patients requiring this service, was significantly higher in acute care emergency surgery patients: acute care emergency surgery 10.8% versus general surgery 4.3%, transplant 6.6%, oral-maxillofacial surgery 0%, and neurosurgery 0.5% (all p < 0.01). Acute care emergency surgery patients were more likely interhospital transfers for tertiary care services than general surgery or transplant (24.5% vs 15.5% and 8.3% respectively, p < 0.001 for each) and more likely required emergent surgery (13.7% vs 6.7% and 3.5%, all p < 0.001). Chronic comorbidities were similar between acute care emergency surgery and general surgery, whereas transplant had fewer.

CONCLUSIONS

Emergency general surgery patients have increased ICU needs in terms of length of stay, ventilator usage, and continuous renal replacement therapy usage compared with other services, perhaps due to the higher percentage of transfers and emergent surgery required. These patients represent a distinct population. Understanding their resource needs will allow for better deployment of hospital resources.

Elevated cardiac troponin T levels in critically ill patients with sepsis

BACKGROUND

It is known that troponin elevations have prognostic importance in critically ill patients. We examined whether cardiac troponin T elevations are independently associated with in-hospital, short-term (30 days), and long-term (3 years) mortality in intensive care unit (ICU) patients admitted with sepsis, severe sepsis, and septic shock after adjusting for the severity of disease with the Acute Physiology, Age and Chronic Health Evaluation III system.

METHODS

We studied the Mayo Clinic's Acute Physiology, Age and Chronic Health Evaluation III database and cardiac troponin T levels from patients admitted consecutively to the medical ICU. Between January 2001 and December 2006, 926 patients with sepsis had cardiac troponin T measured at ICU admission. In-hospital, short-term, and long-term all-cause mortality were determined.

RESULTS

Among study patients, 645 (69.7%) had elevated cardiac troponin T levels and 281 (30.3%) had undetectable cardiac troponin T. During hospitalization, 15% of the patients with troponin T <0.01 ng/mL died compared with 31.9% of those with troponin T ≥ 0.01 ng/mL (P < .0001). At 30 days, mortality was 31% and 17% in patients with and without elevations, respectively (P < .0001). The Kaplan-Meier probability of survival at 1-, 2-, and 3-year follow-ups was 68.1%, 56.3%, and 46.8% with troponin T ≥ 0.01 ng/mL, respectively, and 76.4%, 69.1%, and 62.0% with troponin T <0.01 μg/L, respectively (P < .0001). After adjustment for severity of disease and baseline characteristics, cardiac troponin T levels remained associated with in-hospital and short-term mortality but not with long-term mortality.

CONCLUSIONS

In patients with sepsis who are admitted to an ICU, cardiac troponin T elevations are independently associated with in-hospital and short-term mortality but not long-term mortality.

Facial expression as an indicator of pain in critically ill intubated adults during endotracheal suctioning

BACKGROUND

Facial expression is often used to evaluate pain in noncommunicative critically ill patients.

OBJECTIVES

To describe facial behavior during endotracheal suctioning, determine facial behaviors that characterize the pain response, and describe the effect of patient factors on facial behavior during pain response.

METHODS

Fifty noncommunicative patients receiving mechanical ventilation were video recorded during 2 phases (rest and endotracheal suctioning). Pain ratings were gathered by using the Behavioral Pain Scale. Facial behaviors were coded by using the Facial Action Coding System for 30 seconds for each phase.

RESULTS

Fourteen facial actions were associated more with endotracheal suctioning than with rest (z = 5.78; P < .001). The sum of intensity of the 14 actions correlated with total mean scores on the Behavioral Pain Scale (ρ = 0.71; P < .001) and with the facial expression component of the scale (ρ = 0.67; P < .001) during suctioning. In stepwise multivariate analysis, 5 pain-relevant facial behaviors (brow raiser, brow lower, nose wrinkling, head turned right, and head turned up) accounted for 71% of the variance (adjusted R² = 0.682; P < .001) in pain response. The sum of intensity of the 5 actions correlated with total mean scores on the behavioral scale (ρ = 0.72; P < .001) and with the facial expression component of that scale (ρ = 0.61; P < .001) during suctioning. Patient factors had no association with pain intensity scores.

CONCLUSIONS

Upper facial expressions are most frequently activated during pain response in noncommunicative critically ill patients and might be a valid alternative to self-report ratings.

Rural-urban differences in inpatient quality of care in US Veterans with ischemic stroke

PURPOSE

Differences in stroke care quality for patients in rural and urban locations have been suggested, but whether differences exist across Veteran Administration Medical Centers (VAMCs) is unknown. This study examines whether rural-urban disparities exist in inpatient quality among veterans with acute ischemic stroke.

METHODS

In this retrospective study, inpatient stroke care quality was assessed in a national sample of veterans with acute ischemic stroke using 14 quality indicators (QIs). Rural-Urban Commuting Areas codes defined each VAMC's rural-urban status. A hierarchical linear model assessed the rural-urban differences across the 14 QIs, adjusting for patient and facility characteristics, and clustering within VAMCs.

FINDINGS

Among 128 VAMCs, 18 (14.1%) were classified as rural VAMCs and admitted 284 (7.3%) of the 3,889 ischemic stroke patients. Rural VAMCs had statistically significantly lower unadjusted rates on 6 QIs: Deep vein thrombosis (DVT) prophylaxis, antithrombotic at discharge, antithrombotic at day 2, lipid management, smoking cessation counseling, and National Institutes of Health Stroke Scale completion, but they had higher rates of stroke education, functional assessment, and fall risk assessment. After adjustment, differences in 2 QIs remained significant-patients treated in rural VAMCs were less likely to receive DVT prophylaxis, but more likely to have documented functional assessment.

CONCLUSIONS

After adjustment for key demographic, clinical, and facility-level characteristics, there does not appear to be a systematic difference in inpatient stroke quality between rural and urban VAMCs. Future research should seek to understand the few differences in care found that could serve as targets for future quality improvement interventions.