Outcomes and Predictors of 28-Day Mortality in Patients With Solid Tumors and Septic Shock Defined by Third International Consensus Definitions for Sepsis and Septic Shock Criteria.

BACKGROUND: Data assessing outcomes of patients with solid tumors demonstrating septic shock using the Third International Consensus Definitions for Sepsis and Septic Shock are scarce. RESEARCH QUESTION: What are the independent predictors of 28-day mortality in critically ill adults with solid tumors and septic shock? STUDY DESIGN AND METHODS: Cohort of solid tumor patients admitted to the ICU with septic shock. Demographic and clinical characteristics were gathered from the electronic health records. We developed a reduced multivariate logistics regression model to identify independent predictors of 28-day mortality and used Kaplan-Meier plots to assess survival. RESULTS: A total of 271 patients were included. The median age was 62 years (range, 19-94 years); 57.2% were men and 53.5% were White. The most common underlying malignancies were lung (19.2%), breast (7.7%), pancreatic (7.7%), and colorectal (7.4%) cancers. Most patients (84.5%) harbored metastatic disease. Twenty-eight days after ICU admission, 188 patients (69.4%) had died. Nonsurvivors showed a higher rate of advanced cancer, longer hospital stays before ICU admission, and higher Sequential Organ Failure Assessment scores at admission and throughout the ICU stay (P < .001 for all). The multivariate analysis identified metastatic disease (OR, 3.17; 95% CI, 1.43-7.03), respiratory failure (OR, 2.34; 95% CI, 1.15-4.74), elevated lactate levels (OR, 3.19; 95% CI, 1.90-5.36), and Eastern Cooperative Oncology Group performance scores of 3 or 4 (OR, 2.72; 95% CI, 1.33-5.57) as independent predictors of 28-day mortality. Only 38 patients (14%) were discharged home without medical assistance. INTERPRETATION: The 28-day mortality rate of patients with solid tumors and septic shock was considerably high. Factors associated with worse survival included advanced oncologic disease, poor performance status, high lactate level, and concomitant acute respiratory failure. Early goals-of-care discussions should be considered for frail patients with septic shock and advanced metastatic disease without denying access to the appropriate level of care.

Outcomes and Predictors of 28-Day Mortality in Patients With Hematologic Malignancies and Septic Shock Defined by Sepsis-3 Criteria.

BACKGROUND: To describe short-term outcomes and independent predictors of 28-dayx mortality in adult patients with hematologic malignancies and septic shock defined by the new Third International Consensus Definitions (Sepsis-3) criteria. METHODS: We performed a retrospective cohort study of patients admitted to the medical ICU with septic shock from April 2016 to March 2019. Demographic and clinical features and short-term outcomes were collected. We used descriptive statistics to summarize patient characteristics, logistic regression to identify predictors of 28-day mortality, and Kaplan-Meier plots to assess survival. RESULTS: Among the 459 hematologic patients with septic shock admitted to the ICU, 109 (23.7%) had received hematopoietic stem cell transplant. The median age was 63 years (range, 18-89 years), and 179 (39%) were women. Nonsurvivors had a higher Charlson comorbidity index (P=.007), longer length of stay before ICU admission (P=.01), and greater illness severity at diagnosis and throughout the hospital course (P<.001). The mortality rate at 28 days was 67.8% and increased with increasing sequential organ failure assessment score on admission (odds ratio [OR], 1.11; 95% CI, 1.03-1.20), respiratory failure (OR, 3.12; 95% CI, 1.49-6.51), and maximum lactate level (OR, 1.16; 95% CI, 1.10-1.22). Aminoglycosides administration (OR, 0.42; 95% CI, 0.26-0.69), serum albumin (OR, 0.51; 95% CI, 0.31-0.86), and granulocyte colony-stimulating factor (G-CSF) (OR, 0.40; 95% CI, 0.24-0.65) were associated with lower 28-day mortality. Life support limitations were present in 81.6% of patients at death. At 90 days, 19.4% of the patients were alive. CONCLUSIONS: Despite efforts to enhance survival, septic shock in patients with hematologic malignancies is still associated with high mortality rates and poor 90-day survival. These results demonstrate the need for an urgent call to action with higher awareness, including the further evaluation of interventions such as earlier ICU admission, aminoglycosides administration, and G-CSF treatment.

Humanizing the intensive care unit experience in a comprehensive cancer center: A patient- and family-centered improvement study.

OBJECTIVES: Improving family-centered outcomes is a priority in oncologic critical care. As part of the Intensive Care Unit (ICU) Patient-Centered Outcomes Research Collaborative, we implemented patient- and family-centered initiatives in a comprehensive cancer center. METHODS: A multidisciplinary team was created to implement the initiatives. We instituted an open visitation policy (OVP) that revamped the use of the two-way communication boards and enhanced the waiting room experience by hosting ICU family-centered events. To assess the initiatives' effects, we carried out pre-intervention (PRE) and post-intervention (POST) family/caregiver and ICU practitioner surveys. RESULTS: A total of 159 (PRE = 79, POST = 80) family members and 147 (PRE = 95, POST = 52) ICU practitioners participated. Regarding the decision-making process, family members felt more included (40.5% vs. 68.8%, p < 0.001) and more supported (29.1% vs. 48.8%, p = 0.011) after the implementation of the initiatives. The caregivers also felt more control over the decision-making process in the POST survey (34.2% vs. 56.3%, p = 0.005). Although 33% of the ICU staff considered OVP was beneficial for the ICU, 41% disagreed and 26% were neutral. Only half of them responded that OVP was beneficial for patients and 63% agreed that OVP was beneficial for families. Half of the practitioners agreed that OVP resulted in additional work for staff. SIGNIFICANCE OF RESULTS: Our project effectively promoted patient- and family-centered care. The families expressed satisfaction with the communication of information and the decision-making process. However, the ICU staff felt that the initiatives increased their work load. Further research is needed to understand whether making this project universal or introducing additional novel practices would significantly benefit patients admitted to the ICU and their family.

Pain management during the withholding and withdrawal of life support in critically ill patients at the end-of-life: a systematic review and meta-analysis.

PURPOSE: To review and summarize the most frequent medications and dosages used during withholding and withdrawal of life-prolonging measures in critically ill patients in the intensive care unit. METHODS: We searched PubMed, EMBASE, the Cochrane Database of Systematic Reviews, and the Virtual Health Library from inception through March 2019. We considered any study evaluating pharmaceutical interventions for pain management during the withholding or withdrawing of life support in adult critically ill patients at the end-of-life. Two independent investigators performed the screening and data extraction. We pooled data on utilization rate of analgesic and sedative drugs and summarized the dosing between the moment prior to withholding or withdrawal of life support and the moment before death. RESULTS: Thirteen studies met inclusion criteria. Studies were conducted in the United States (38%), Canada (31%), and the Netherlands (31%). Eleven studies were single-cohort and twelve had a Newcastle-Ottawa Scale score of less than 7. The mean age of the patients ranged from 59 to 71 years, 59-100% were mechanically ventilated, and 47-100% of the patients underwent life support withdrawal. The most commonly used opioid and sedative were morphine [utilization rate 60% (95% CI 48-71%)] and midazolam [utilization rate 28% (95% CI 23-32%)], respectively. Doses increased during the end-of-life process (pooled mean increase in the dose of morphine: 2.6 mg/h, 95% CI 1.2-4). CONCLUSIONS: Pain control is centered on opioids and adjunctive benzodiazepines, with dosages exceeding those recommended by guidelines. Despite consistency among guidelines, there is significant heterogeneity among practices in end-of-life care.

Clinical Practice Guidelines and Consensus Statements About Pain Management in Critically Ill End-of-Life Patients: A Systematic Review.

OBJECTIVES: To identify and synthesize available recommendations from scientific societies and experts on pain management at the end-of-life in the ICU. DATA SOURCES: We conducted a systematic review of PubMed, EMBASE, the Cochrane Database of Systematic Reviews, and Biblioteca Virtual en Salud from their inception until March 28, 2019. STUDY SELECTION: We included all clinical practice guidelines, consensus statements, and benchmarks for quality. DATA EXTRACTION: Study selection, methodological quality, and data extraction were performed independently by two investigators. A quality assessment was performed by four investigators using the Appraisal of Guidelines for Research and Evaluation II instrument. The recommendations were then synthesized and categorized. DATA SYNTHESIS: Ten publications were included. The Appraisal of Guidelines for Research and Evaluation II statement showed low scores in various quality domains, especially in the applicability and rigor of development. Most documents were in agreement on five topics: 1) using a quantitative tool for pain assessment; 2) administering narcotics for pain relief and benzodiazepines for anxiety relief; 3) against prescribing neuromuscular blockers during withdrawal of life support to assess pain; 4) endorsing the use of high doses of opioids and sedatives for pain control, regardless of the risk that they will hasten death; and 5) using quality indicators to improve pain management during end-of-life in the ICU. CONCLUSIONS: In spite of the lack of high-quality evidence, recommendations for pain management at the end-of-life in the ICU are homogeneous and are justified by ethical principles and agreement among experts. Considering the growing demand for the involvement of palliative care teams in the management of the dying patients in the ICU, there is a need to clearly define their early involvement and to further develop comprehensive evidence-based pain management strategies. Based on the study findings, we propose a management algorithm to improve the overall care of dying critically ill patients.

Variability in triage practices for critically ill cancer patients: A randomized controlled trial.

PURPOSE: Intensive care triage practices and end-user interpretation of triage guidelines have rarely been assessed. We evaluated agreement between providers on the prioritization of patients for ICU admission using different triage guidelines. MATERIALS AND METHODS: A multi-centered randomized study on providers from 18 different countries was conducted using clinical vignettes of oncological patients. The level of agreement between providers was measured using two different guidelines, with one being cancer specific. RESULTS: Amongst 257 providers, 52.5% randomly received the Society of Critical Care Prioritization Model, and 47.5% received a cancer specific flowchart as a guide. In the Prioritization Model arm the average entropy was 1.193, versus 1.153 in the flowchart arm (P = .095) indicating similarly poor agreement. The Fleiss' kappa coefficients were estimated to be 0.2136 for the SCCMPM arm and 0.2457 for the flowchart arm, also similarly implying poor agreement. CONCLUSIONS: The low agreement amongst practitioners on the prioritization of cancer patient cases for ICU admission existed using both general triage guidelines and guidelines tailored only to cancer patients. The lack of consensus on intensive care unit triage practices in the oncological population exposes a potential barrier to appropriate resource allocation that needs to be addressed.

Out-of-Hospital ICU Transfers to an Oncological Referral Center: Characteristics, Resource Utilization, and Patient Outcomes.

OBJECTIVE:: To determine resource utilization and outcomes of out-of-hospital transfer patients admitted to the intensive care unit (ICU) of a cancer referral center. DESIGN:: Single-center cohort. SETTING:: A tertiary oncological center. PATIENTS:: Patients older than 18 years transferred to our ICU from an outside hospital between January 2013 and December 2015. MEASUREMENTS AND MAIN RESULTS:: A total of 2127 (90.3%) were emergency department (ED) ICU admissions and 228 (9.7%) out-of-hospital transfers. The ICU length of stay (LOS) was longer in the out-of-hospital transfers when compared to all other ED ICU admissions ( P = .001); however, ICU and hospital mortality were similar between both groups. The majority of patients were transferred for a higher level of care (77.2%); there was no difference in the amount of interventions performed, ICU LOS, and ICU mortality between nonhigher level-of-care and higher level-of-care patients. Factors associated with an ICU LOS ≥10days were a higher Sequential Organ Failure Assessment (SOFA) score, weekend admissions, presence of shock, need for mechanical ventilation, and acute kidney injury on admission or during ICU stay ( P < .008). The ICU mortality of transferred patients was 17.5% and associated risk factors were older age, higher SOFA score on admission, use of mechanical ventilation and vasopressors during ICU stay, and renal failure on admission ( P < .0001). Data related to the transfer such as LOS at the outside facility, time of transfer, delay in transfer, and longer distance traveled were not associated with increased LOS or mortality in our study. CONCLUSION:: Organ failure severity on admission, and not transfer-related factors, continues to be the best predictor of outcomes of critically ill patients with cancer when transferred from other facilities to the ICU. Our data suggest that transferring critically ill patients with cancer to a specialized center does not lead to worse outcomes or increased resource utilization when compared to patients admitted from the ED.

Prognostic Index for Critically Ill Allogeneic Transplantation Patients.

Outcomes of intensive care for allogeneic hematopoietic stem cell transplantation (Allo-SCT) patients remain poor. Better selection of critically ill Allo-SCT patients for intensive care may alleviate costs to the patients, families, and the health care system. We aimed to develop a prognostic index tailored for critically ill Allo-SCT patients as traditional instruments are of limited value in this setting. Six hundred fifty-six Allo-SCT patients admitted to intensive care unit (ICU) at MD Anderson Cancer Center between 2001 and 2010 were divided into training and test sets. Of the 3 multivariable regression models built to predict hospital mortality in the training set, the model with the largest area under receiver operating curve (AUC) in the test set was selected as the prognostic index for intensive care after allogeneic hematopoietic stem cell transplantation (PICAT). The parameters included in the regression model with the highest AUC (.81) were time to ICU from hospital admission, lactate dehydrogenase, bilirubin, albumin, reason for ICU admission, prothrombin time-international normalized ratio, conditioning intensity, age, and comorbidity score. AUC for hospital mortality of PICAT (.80) was significantly larger than that of Acute Physiology and Chronic Health Evaluation (APACHE) (.61) and Sequential Organ Failure Assessment (SOFA) (.72) in all patients. Hospital mortality and median overall survival of patients with PICAT scores of 0 to 2 (n = 141), >2 to 4 (n = 242), and >4 (n = 182) were 34%, 69%, and 91%; and 7.59, .67, and .30 months, respectively. PICAT has good calibration and accuracy in predicting mortality for Allo-SCT patients requiring intensive care. Its AUC was significantly higher than APACHE II and SOFA scores and is also associated with overall survival.

Noninvasivepositive pressure ventilation vsinvasive mechanical ventilation as first-line therapy for acute hypoxemic respiratory failure in cancer patients.

PURPOSE: The objective was to describe the characteristics and outcomes of critically ill cancer patients who received noninvasive positive pressure ventilation (NIPPV) vs invasive mechanical ventilation as first-line therapy for acute hypoxemic respiratory failure. MATERIAL AND METHODS: A retrospective cohort study of consecutive adult intensive care unit (ICU) cancer patients who received either conventional invasive mechanical ventilation or NIPPV as first-line therapy for hypoxemic respiratory failure. RESULTS: Of the 1614 patients included, the NIPPV failure group had the greatest hospital length of stay, ICU length of stay, ICU mortality (71.3%), and hospital mortality (79.5%) as compared with the other 2 groups (P < .0001). The variables independently associated with NIPPV failure included younger age (odds ratio [OR], 0.99; 95% confidence interval [CI], 0.98-0.99; P=.031), non-Caucasian race (OR, 1.61; 95% CI, 1.14-2.26; P=.006), presence of a hematologic malignancy (OR, 1.87; 95% CI, 1.33-2.64; P=.0003), and a higher Sequential Organ Failure Assessment score (OR, 1.12; 95% CI, 1.08-1.17; P < .0001). There was no difference in mortality when comparing early vs late intubation (less than or greater than 24 or 48 hours) for the NIPPV failure group. CONCLUSION: Noninvasive positive pressure ventilation failure is an independent risk factor for ICU mortality, but NIPPV patients who avoided intubation had the best outcomes compared with the other groups. Early vs late intubation did not have a significant impact on outcomes.

Two Decades of ICU Utilization and Hospital Outcomes in a Comprehensive Cancer Center.

OBJECTIVE: To investigate ICU utilization and hospital outcomes of oncological patients admitted to a comprehensive cancer center. DESIGN: Observational cohort study. SETTING: The University of Texas MD Anderson Cancer Center. PATIENTS: Consecutive adults with cancer discharged over a 20-year period. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: The Cochran-Armitage test for trend was used to evaluate ICU utilization and hospital mortality rates by primary service over time. A negative binomial log linear regression model was fitted to the data to investigate length of stay over time. Among 387,306 adult hospitalized patients, the ICU utilization rate was 12.9%. The overall hospital mortality rate was 3.6%: 16.2% among patients with an ICU stay and 1.8% among non-ICU patients. Among those admitted to the ICU, the mean (SD) admission Sequential Organ Failure Assessment score was 6.1 (3.8) for all ICU patients: 7.3 (4.4) for medical ICU patients and 4.9 (2.8) for surgical ICU patients. Hematologic disorders were associated with the highest hospital mortality rate in ICU patients (42.8%); metastatic disease had the highest mortality rate in non-ICU patients (4.2%); sepsis, pneumonia, and other infections had the highest mortality rate for all inpatients (8.5%). CONCLUSIONS: This study provides a longitudinal view of ICU utilization rates, hospital and ICU length of stay, and severity-adjusted mortality rates. Although the data arise from a single institution, it encompasses a large number of hospital admissions over two decades and can serve as a point of comparison for future oncological studies at similar institutions. More studies of this nature are needed to determine whether consolidation of cancer care into specialized large-volume facilities may improve outcomes, while simultaneously sustaining appropriate resource utilization and reducing unnecessary healthcare costs.

Does Thrombolysis Have a Place in the Cardiopulmonary Resuscitation of Patients With Acute Pulmonary Embolism? A Case of Successful Thrombolysis During Pulmonary Embolism Induced Cardiopulmonary Arrest.

OBJECTIVE: Pulmonary embolism often causes cardiac arrest. When this occurs, thrombolytic therapy is not routinely administered. There are multiple reasons for this, including difficulty with rapidly adequately diagnosing the embolus, the lack of good data supporting the use of thrombolytics during resuscitation, the belief that thrombolytic therapy is ineffective once a patient has already arrested, the difficulty of obtaining thrombolytics at the bedside rapidly enough to administer during a code, and the increased risks of bleeding, particularly with ongoing chest compressions. In this case report, we present a patient who was successfully treated with thrombolytic therapy during pulmonary embolism-induced cardiopulmonary arrest and discuss the role of thrombolytics in cardiopulmonary resuscitation. DESIGN: Case report. SETTING: Surgical ICU in a comprehensive cancer center. PATIENT: A 56-year-old man who developed hypotension, dyspnea, hypoxia, and pulseless electrical activity 10 days after resection of a benign colon lesion with a right hemicolectomy and primary end-to-end anastomosis. INTERVENTIONS: After a rapid bedside echocardiogram suggesting pulmonary embolus, thrombolytic therapy was administered during cardiopulmonary resuscitative efforts. MEASUREMENTS AND MAIN RESULTS: The patient had a return of spontaneous circulation and showed improvement in repeat echocardiographic imaging. He had a prolonged course in the ICU and hospital, but eventually made an essentially complete clinical recovery. CONCLUSION: As bedside echocardiographic technology becomes more rapidly and readily available, the rapid diagnosis of pulmonary embolism and use of thrombolytics during cardiopulmonary resuscitation may need to be more routinely considered a potential therapeutic adjunctive measure.

Place of Death among Hospitalized Patients with Cancer at the End of Life.

BACKGROUND: The majority of hospital deaths in the United States occur after ICU admission. The characteristics associated with the place of death within the hospital are not known for patients with cancer. OBJECTIVE: The study objective was to identify patient characteristics associated with place of death among hospitalized patients with cancer who were at the end of life. METHODS: A retrospective cohort study design was implemented. Subjects were consecutive patients hospitalized between 2003 and 2007 at a large comprehensive cancer center in the United States. Multinomial logistic regression analysis was used to identify patient characteristics associated with place of death (ICU, hospital following ICU, hospital without ICU) among hospital decedents. RESULTS: Among 105,157 hospital discharges, 3860 (3.7%) died in the hospital: 42% in the ICU, 14% in the hospital following an ICU stay, and 44% in the hospital without ICU services. Individuals with the following characteristics had an increased risk of dying in the ICU: nonlocal residence, newly diagnosed hematologic or nonmetastatic solid tumor malignancies, elective admission, surgical or pediatric services. A palliative care consultation on admission was associated with dying in the hospital without ICU services. CONCLUSIONS: Understanding existing patterns of care at the end of life will help guide decisions about resource allocation and palliative care programs. Patients who seek care at dedicated cancer centers may elect more aggressive care; thus the generalizability of this study is limited. Although dying in a hospital may be unavoidable for patients who have uncontrolled symptoms that cannot be managed at home, palliative care consultations with patients and their families in advance regarding end-of-life preferences may prevent unwanted admission to the ICU.

Hematopoietic cell transplantation-specific comorbidity index predicts inpatient mortality and survival in patients who received allogeneic transplantation admitted to the intensive care unit.

PURPOSE: To investigate the prognostic value of the Hematopoietic Cell Transplantation-Specific Comorbidity Index (HCT-CI) in patients who received transplantation admitted to the intensive care unit (ICU). PATIENTS AND METHODS: We investigated the association of HCT-CI with inpatient mortality and overall survival (OS) among 377 patients who were admitted to the ICU within 100 days of allogeneic stem-cell transplantation (ASCT) at our institution. HCT-CI scores were collapsed into four groups and were evaluated in univariate and multivariate analyses using logistic regression and Cox proportional hazards models. RESULTS: The most common pretransplantation comorbidities were pulmonary and cardiac diseases, and respiratory failure was the primary reason for ICU admission. We observed a strong trend for higher inpatient mortality and shorter OS among patients with HCT-CI values ≥ 2 compared with patients with values of 0 to 1 in all patient subsets studied. Multivariate analysis showed that patients with HCT-CI values ≥ 2 had significantly higher inpatient mortality than patients with values of 0 to 1 and that HCT-CI values ≥ 4 were significantly associated with shorter OS compared with values of 0 to 1 (hazard ratio, 1.74; 95% CI, 1.23 to 2.47). The factors associated with lower inpatient mortality were ICU admission during the ASCT conditioning phase or the use of reduced-intensity conditioning regimens. The overall inpatient mortality rate was 64%, and the 1-year OS rate was 15%. Among patients with HCT-CI scores of 0 to 1, 2, 3, and ≥ 4, the 1-year OS rates were 22%, 17%, 18%, and 9%, respectively. CONCLUSION: HCT-CI is a valuable predictor of mortality and survival in critically ill patients after ASCT.

Cross-validation of a Sequential Organ Failure Assessment score-based model to predict mortality in patients with cancer admitted to the intensive care unit.

PURPOSE: This study aims to validate the performance of the Sequential Organ Failure Assessment (SOFA) score to predict death of critically ill patients with cancer. MATERIAL AND METHODS: We conducted a retrospective observational study including adults admitted to the intensive care unit (ICU) between January 1, 2006, and December 31, 2008. We randomly selected training and validation samples in medical and surgical admissions to predict ICU and in-hospital mortality. By using logistic regression, we calculated the probabilities of death in the training samples and applied them to the validation samples to test the goodness-of-fit of the models, construct receiver operator characteristics curves, and calculate the areas under the curve (AUCs). RESULTS: In predicting mortality at discharge from the unit, the AUC from the validation group of medical admissions was 0.7851 (95% confidence interval [CI], 0.7437-0.8264), and the AUC from the surgical admissions was 0.7847 (95% CI, 0.6319-0.937). The AUCs of the SOFA score to predict mortality in the hospital after ICU admission were 0.7789 (95% CI, 0.74-0.8177) and 0.7572 (95% CI, 0.6719-0.8424) for the medical and surgical validations groups, respectively. CONCLUSIONS: The SOFA score had good discrimination to predict ICU and hospital mortality. However, the observed underestimation of ICU deaths and unsatisfactory goodness-of-fit test of the model in surgical patients to indicate calibration of the score to predict ICU mortality is advised in this group.

Costs and outcomes of acute kidney injury in critically ill patients with cancer.

BACKGROUND: Acute kidney injury (AKI) is a common complication in critically ill patients with cancer. The RIFLE criteria define three levels of AKI based on the percent increase in serum creatinine (Scr) from baseline: risk (> or = 50%), injury (> or = 100%), and failure (> or = 200% or requiring dialysis). The utility of the RIFLE criteria in critically ill patients with cancer is not known. OBJECTIVE: To examine the incidence, outcomes, and costs associated with AKI in critically ill patients with cancer. METHODS: We retrospectively analyzed all patients admitted to a single-center ICU over a 13-month period with a baseline Scr < or = 1.5 mg/dL (n = 2,398). Kaplan-Meier estimates for survival by RIFLE category were calculated. Logistic regression was used to determine the association of AKI on 60-day mortality. A log-linear regression model was used for economic analysis. Costs were assessed by hospital charges from the provider's perspective. RESULTS: For the risk, injury, and failure categories of AKI, incidence rates were 6%, 2.8%, and 3.7%; 60-day survival estimates were 62%, 45%, and 14%; and adjusted odds ratios for 60-day mortality were 2.3, 3, and 14.3, respectively (P < or = 0.001 compared to patients without AKI). Hematologic malignancy and hematopoietic cell transplant were not associated with mortality in the adjusted analysis. Hospital cost increased by 0.16% per 1% increase in creatinine and by 21% for patients requiring dialysis. LIMITATIONS: Retrospective analysis. Single-center study. No adjustment by cost-to-charge ratios. CONCLUSIONS: AKI is associated with higher mortality and costs in critically ill patients with cancer.

Cross-validation of a modified score to predict mortality in cancer patients admitted to the intensive care unit.

PURPOSE: The aim of this study was to cross-validate an automated and customized severity of illness score as a means of predicting death among adult cancer patients admitted to the intensive care unit (ICU). MATERIALS AND METHODS: We conducted a retrospective study of ICU discharges between January 1, 2001, and December 31, 2005, in a university comprehensive cancer center. We randomly selected training and validation samples in 2 ICU groups (medical and surgical patients). We used logistic regression to calculate the probabilities of death in the ICU and in-hospital death in training samples and applied these probabilities to the validation samples to calculate sensitivity and specificity, construct curves, and determined the areas under the receiver operating characteristic curve (AUC). RESULTS: We included 6880 patients. In predicting ICU mortality, the AUC was 0.77 (95% confidence interval [CI], 0.73-0.82) for the medical validation group and 0.8207 (95% CI, 0.7304-0.9109) for the surgical validation group. For in-hospital mortality, the AUCs for the groups of medical and surgical patients were 0.73 (95% CI, 0.69-0.76) and 0.77 (95% CI, 0.73-0.80), respectively. CONCLUSIONS: The modified Sequential Organ Failure Assessment score is a good and valid predictor of cancer patients' risk of dying in the ICU and/or hospital despite the modifications needed to automate the score using existing electronic data.

Demographic and clinical determinants of having do not resuscitate orders in the intensive care unit of a comprehensive cancer center.

To understand the needs of patients and family members as physicians communicate their expectations about patients admitted to the intensive care unit (ICU), we evaluated the demographic and clinical determinants of having a Do Not Resuscitate (DNR) order for adults with cancer. Patients included were admitted from June 16, 2008-August 16, 2008, to the ICU in a comprehensive cancer center. We conducted a prospective chart review and collected data on patient demographics, length of stay, advance directives, clinical characteristics, and DNR orders. A total of 362 patients met the inclusion criteria; only 15.2% had DNR orders before ICU discharge. In the multivariate analysis, we found that medical admission was an independent predictor of having a DNR order during the ICU stay (odds ratio = 3.65; 95% confidence interval, 1.44-9.28); we also found a significant two-way interaction between race/ethnicity and type of admission (medical vs. surgical) with having a DNR order (p = .04). Although medical admissions were associated with significantly more DNR orders than were surgical admissions, we observed that the subgroup of non-white patients admitted for medical reasons was significantly less likely to have DNR orders. This finding could reflect different preferences for aggressive care by race/ethnicity in patients with cancer, and deserves further investigation.

Automating and simplifying the SOFA score in critically ill patients with cancer.

The aim was to demonstrate the performance of a modified version of the Sequential Organ Failure Assessment (SOFA) score to predict mortality in medical and surgical patients with cancer. We performed an electronic retrospective review of databases. We included adult patients with cancer admitted into a 53-bed ICU over 28 months. We electronically calculated a modified SOFA (mSOFA) score at admission. A majority of the patients were admitted into the surgical ICU. Of 328 nonsurvivors, 85.1 per cent were medical patients and only 14.9 per cent surgical patients. The mean admission mSOFA scores for medical and surgical patients were 4.7 +/- 3.2 and 1.7 +/- 1.9, respectively. The overall area under the curve (AUC) of the mSOFA score was 0.84. The AUCs for medical and surgical patients were 0.72 and 0.78, respectively. Our results demonstrate that electronic assessment of mSOFA score has potential in resource allocation decisions as well as in critical care outreach programs.