Diaphragm function in acute respiratory failure and the potential role of phrenic nerve stimulation.

PURPOSE OF REVIEW: The aim of this review was to describe the risk factors for developing diaphragm dysfunction, discuss the monitoring techniques for diaphragm activity and function, and introduce potential strategies to incorporate diaphragm protection into conventional lung-protective mechanical ventilation strategies. RECENT FINDINGS: It is increasingly apparent that an approach that addresses diaphragm-protective ventilations goals is needed to optimize ventilator management and improve patient outcomes. Ventilator-induced diaphragm dysfunction (VIDD) is common and is associated with increased ICU length of stay, prolonged weaning and increased mortality. Over-assistance, under-assistance and patient-ventilator dyssynchrony may have important downstream clinical consequences related to VIDD. Numerous monitoring techniques are available to assess diaphragm function, including respiratory system pressures, oesophageal manometry, diaphragm ultrasound and electromyography. Novel techniques including phrenic nerve stimulation may facilitate the achievement of lung and diaphragm-protective goals for mechanical ventilation. SUMMARY: Diaphragm protection is an important consideration in optimizing ventilator management in patients with acute respiratory failure. The delicate balance between lung and diaphragm-protective goals is challenging. Phrenic nerve stimulation may be uniquely situated to achieve and balance these two commonly conflicting goals.

Can Early Warning Systems Enhance Detection of High Risk Patients by Rapid Response Teams?

PURPOSE: We sought to evaluate if incorporating an early warning system (EWS), the Visensia Safety Index (VSI) and the National Early Warning Systems 2 (NEWS2), may lead to earlier identification of rapid response team (RRT) patients. METHODS: This was a retrospective study (2015-2018) of patients experiencing RRT activation within a tertiary care network. We evaluated the proportion of patients with an EWS alert prior to RRT activation and their associated outcomes (primary: hospital mortality). RESULTS: There were 6,346 RRT activations over the study period. Of these, 2042 (50.8%) patients would have had a VSI alert prior to RRT activation, with a median advanced time of 3.6 (IQR 0.5-12.8) hours, compared to 2351 (58.4%) patients and 9.8 (IQR 2.0-18.7) hours for NEWS2. Patients with a potential alert prior to RRT activation had an increased odds of mortality for both VSI (OR 1.2, 95%CI 1.1-1.3) and NEWS2 (OR 2.7, 95% CI 2.4-3.1). Prognostic accuracy for hospital mortality was similar between groups. CONCLUSION: Utilization of an EWS by an RRT has potential to provide earlier recognition of deterioration and mortality risk among hospitalized inpatients.

Costs and Outcomes of Patients Admitted to the Intensive Care Unit With Cancer.

INTRODUCTION: Cancer is associated with significant health-care expenditure, but few studies have examined the cost of patients with cancer in the intensive care unit (ICU). We aimed to describe the costs and outcomes of patients admitted to the ICU with cancer. METHODS: We conducted a retrospective cohort study of patients admitted between 2011 and 2016 to 2 tertiary-care ICUs. We included patients with a cancer-related most responsible diagnosis using International Classification of Disease, 10th Revision, Canada codes. We compared costs and outcomes of patients having cancer with noncancer controls matched for age, sex, and Elixhauser comorbidity score. We used logistic regression to determine predictors of mortality among patients with cancer. RESULTS: There were 1022 patients with cancer during the study period. Mean age was 63.2 years and 577 (56.5%) were male. Inhospital mortality for all patients with cancer was 24.0%. Total cost per patient was higher for patients with cancer compared to noncancer patients (CAD$57 084 vs CAD$40 730; P < .001) but there were no differences in the cost per day (CAD$2868 vs CAD$2887; P = .76) or ICU cost (CAD$30 495 vs CAD$29 382; P = .42). Among patients with cancer, the cost per day was higher for nonsurvivors (CAD$3477 vs CAD$2677; P < .001). Liver disease (odds ratio [OR]: 2.96; 95% confidence interval [CI]: 1.22-7.81), mechanical ventilation (OR: 1.73; 95% CI: 1.25-2.39), hematologic malignancy (OR: 3.88; 95% CI: 2.31-6.54), and unknown primary site (OR: 2.13; 95% CI: 1.36-3.35) were independently associated with mortality in patients with cancer. CONCLUSION: Patients admitted to the ICU with cancer did not differ in cost per day, ICU cost, or mortality compared to matched noncancer controls. Among patients with cancer, nonsurvivors had significantly higher cost per day compared to survivors. Hematologic and unknown primaries, liver disease, and mechanical ventilation were independently associated with mortality in patients with cancer.

Preadmission Antiplatelet Use and Associated Outcomes and Costs Among ICU Patients With Intracranial Hemorrhage.

INTRODUCTION: Patients with intracranial hemorrhage (including intracerebral hemorrhage, subarachnoid hemorrhage, and traumatic hemorrhage) are commonly admitted to the intensive care unit (ICU). Although indications for oral antiplatelet agents are increasing, the impact of preadmission use on outcomes in patients with intracranial hemorrhage admitted to the ICU is unknown. We sought to evaluate the association between preadmission oral antiplatelet use, in-hospital mortality, resource utilization, and costs among ICU patients with intracranial hemorrhage. METHODS: We retrospectively analyzed a prospectively collected registry (2011-2016) and included consecutive adult patients from 2 hospitals admitted to ICU with intracranial hemorrhage. Patients were categorized on the basis of preadmission oral antiplatelet use. We excluded patients with preadmission anticoagulant use. The primary outcome was in-hospital mortality and was analyzed using a multivariable logistic regression model. Contributors to total hospital cost were analyzed using a generalized linear model with log link and gamma distribution. RESULTS: Of 720 included patients with intracranial hemorrhage, 107 (14.9%) had been using an oral antiplatelet agent at the time of ICU admission. Oral antiplatelet use was not associated with in-hospital mortality (adjusted odds ratio: 1.31 [95% confidence interval [CI]: 0.93-2.22]). Evaluation of total costs also revealed no association with oral antiplatelet use (adjusted ratio of means [aROM]: 0.92 [95% CI: 0.82-1.02, P = .10]). Total cost among patients with intracranial hemorrhage was driven by illness severity (aROM: 1.96 [95% CI: 1.94-1.98], P < .001), increasing ICU length of stay (aROM: 1.05 [95% CI: 1.05-1.06], P < .001), and use of invasive mechanical ventilation (aROM: 1.76 [95% CI: 1.68-1.86], P < .001). CONCLUSIONS: Among ICU patients admitted with intracranial hemorrhage, preadmission oral antiplatelet use was not associated with increased in-hospital mortality or hospital costs. These findings have important prognostic implications for clinicians who care for patients with intracranial hemorrhage.

Predictors of mortality and cost among surgical patients requiring rapid response team activation.

Background: Prior studies of rapid response team (RRT) implementation for surgical patients have demonstrated mixed results with respect to reductions in poor outcomes. The aim of this study was to identify predictors of in-hospital mortality and hospital costs among surgical inpatients requiring RRT activation. Methods: We analyzed data prospectively collected from May 2012 to May 2016 at The Ottawa Hospital. We included patients who were at least 18 years of age, who were admitted to hospital, who received either preoperative or postoperative care, and and who required RRT activation. We created a multivariable logistic regression model to describe mortality predictors and a multivariable generalized linear model to describe cost predictors. Results: We included 1507 patients. The in-hospital mortality rate was 15.9%. The patient-related factors most strongly associated with mortality included an Elixhauser Comorbidity Index score of 20 or higher (odds ratio [OR] 3.60, 95% confidence interval [CI] 1.96-6.60) and care designations excluding admission to the intensive care unit and cardiopulmonary resuscitation (OR 3.52, 95% CI 2.25-5.52). The strongest surgical predictors included neurosurgical admission (OR 2.09, 95% CI 1.17-3.75), emergent surgery (OR 2.04, 95% CI 1.37-3.03) and occurrence of 2 or more operations (OR 1.73, 95% CI 1.21-2.46). Among RRT factors, occurrence of 2 or more RRT assessments (OR 2.01, 95% CI 1.44-2.80) conferred the highest mortality. Increased cost was strongly associated with admitting service, multiple surgeries, multiple RRT assessments and medical comorbidity. Conclusion: RRT activation among surgical inpatients identifies a population at high risk of death. We identified several predictors of mortality and cost, which represent opportunities for future quality improvement and patient safety initiatives.

Contexte: Les études sur la mobilisation d'équipes d'intervention rapide (EIR) auprès de patients en chirurgie ont donné des résultats mitigés quant à la réduction des issues négatives. La présente étude visait à déterminer les facteurs prédictifs de coûts pour les hôpitaux et de mortalité chez les patients en chirurgie nécessitant la mobilisation d'une EIR. Méthodes: Nous avons analysé des données recueillies de manière prospective de mai 2012 à mai 2016 à l'Hôpital d'Ottawa. Nous avons inclus les patients hospitalisés de 18 ans et plus qui ont reçu des soins préopératoires ou postopératoires et qui ont nécessité l'intervention d'une EIR. Nous avons ensuite créé un modèle de régression logistique multivariée pour décrire les facteurs prédictifs de mortalité et un modèle linéaire généralisé multivarié pour décrire les facteurs prédictifs de coûts. Résultats: Nous avons retenus 1507 patients. Le taux global de mortalité à l'hôpital était de 15,9 %. Les principaux facteurs de mortalité liés au patient étaient un indice de comorbidité d'Elixhauser supérieur ou égal à 20 (rapport de cotes [RC] 3,60, intervalle de confiance [IC] à 95 % 1,96­6,60) et des objectifs de soins excluant l'admission à l'unité des soins intensifs et la réanimation cardiorespiratoire (RC 3,52, IC à 95 % 2,25­5,52). Les principaux facteurs prédictifs liés aux interventions sont l'admission en neurochirurgie (RC 2,09, IC à 95 % 1,17­3,75), l'intervention chirurgicale d'urgence (RC 2,04, IC à 95 % 1,37­3,03) et le fait d'avoir subi au moins 2 opérations (RC 1,73, IC à 95 % 1,21­2,46). Parmi les facteurs liés aux EIR, la tenue d'au moins 2 évaluations par l'EIR s'accompagnait du mortalité le plus élevé (RC 2,01, IC à 95 % 1,44­2,80). L'augmentation des coûts était étroitement associée au service d'admission, aux interventions chirurgicales multiples, aux évaluations multiples par l'EIR et à la comorbidité médicale. Conclusion: La mobilisation d'EIR auprès de patients en chirurgie permet de mettre en évidence une population à risque élevé de décès. Nous avons découvert plusieurs facteurs prédictifs de mortalité et de coûts, dont on pourra se servir pour améliorer la qualité des soins et la sécurité des patients.

Dynamic Assessment of Fluid Responsiveness in Surgical ICU Patients Through Stroke Volume Variation is Associated With Decreased Length of Stay and Costs: A Systematic Review and Meta-Analysis.

Static indices, such as the central venous pressure, have proven to be inaccurate predictors of fluid responsiveness. An emerging approach uses dynamic assessment of fluid responsiveness (FT-DYN), such as stroke volume variation (SVV) or surrogate dynamic variables, as more accurate measures of volume status. Recent work has demonstrated that goal-directed therapy guided by FT-DYN was associated with reduced intensive care unit (ICU) mortality; however, no study has specifically assessed this in surgical ICU patients. This study aimed to conduct a systematic review and meta-analysis on the impact of employing FT-DYN in the perioperative care of surgical ICU patients on length of stay in the ICU. As secondary objectives, we performed a cost analysis of FT-DYN and assessed the impact of FT-DYN versus standard care on hospital length of stay and mortality. We identified all randomized controlled trials (RCTs) through MEDLINE, EMBASE, and CENTRAL that examined adult patients in the ICU who were randomized to standard care or to FT-DYN from inception to September 2017. Two investigators independently reviewed search results, identified appropriate studies, and extracted data using standardized spreadsheets. A random effect meta-analysis was carried out. Eleven RCTs were included with a total of 1015 patients. The incorporation of FT-DYN through SVV in surgical patients led to shorter ICU length of stay (weighted mean difference [WMD], -1.43d; 95% confidence interval [CI], -2.09 to -0.78), shorter hospital length of stay (WMD, -1.96d; 95% CI, -2.34 to -1.59), and trended toward improved mortality (odds ratio, 0.55; 95% CI, 0.30-1.03). There was a decrease in daily ICU-related costs per patient for those who received FT-DYN in the perioperative period (WMD, US$ -1619; 95% CI, -2173.68 to -1063.26). Incorporation of FT-DYN through SVV in the perioperative care of surgical ICU patients is associated with decreased ICU length of stay, hospital length of stay, and ICU costs.

Outcomes and Costs of Patients Admitted to the Intensive Care Unit Due to Accidental or Intentional Poisoning.

INTRODUCTION: Acute poisoning represents a major cause of morbidity and mortality, and many of these patients are admitted to the intensive care unit (ICU). However, little is known regarding ICU costs of acute poisoning. METHODS: This was a retrospective matched database analysis of patients admitted to the ICU with acute poisoning from 2011 to 2014. It was performed in 2 ICUs within a single tertiary care hospital system. All patient information, outcomes, and costs were stored in the hospital data warehouse. Control patients were defined as randomly selected age-, sex-, severity index-, and comorbidity index-matched nonpoisoned ICU patients (1:4 matching ratio). RESULTS: A total of 8452 critically ill patients were admitted during the study period, of whom 277 had a diagnosis of acute poisoning. The mean age was 44.5 years, and the most common xenobiotics implicated were sedative hypnotics (20.2%), antidepressants (15.2%), and opioids (10.5%). Of these, 73.6% of poisonings were deemed intentional. In-hospital mortality of poisoned patients was 5.1%, compared to 11.1% for control patients (P < .01). The median ICU length of stay (LOS) for poisoned patients was 3.0 days, compared with 4.0 days for control patients (P < .01). The mean total cost for poisoned patients was CAD$18 958. Control patients had a significantly higher mean total cost of CAD$60 628 (P < .01). The xenobiotics associated with the highest costs were acetaminophen (CAD$18 585), toxic alcohols (CAD$16 771), and opioids (CAD$12 967). CONCLUSIONS: In our cohort, we confirmed the long-held belief that patients admitted to the ICU with a primary diagnosis of poisoning have a lower mortality rate, ICU LOS, and overall cost per ICU admission than nonpoisoned patients. However, poisoned patients still accrue significant daily costs, with the highest costs attributed to xenobiotics with known antidotes, such as acetaminophen, toxic alcohols, and opioids.

Optimizing the Early Resuscitation After Out-of-Hospital Cardiac Arrest.

Resuscitation after out-of-hospital cardiac arrest can be one of the most challenging scenarios in acute-care medicine. The devastating effects of postcardiac arrest syndrome carry a substantial morbidity and mortality that persist long after return of spontaneous circulation. Management of these patients requires the clinician to simultaneously address multiple emergent priorities including the resuscitation of the patient and the efficient diagnosis and management of the underlying etiology. This review provides a concise evidence-based overview of the core concepts involved in the early postcardiac arrest resuscitation. It will highlight the components of an effective management strategy including addressing hemodynamic, oxygenation, and ventilation goals as well as carefully considering cardiac catheterization and targeted temperature management. An organized approach is paramount to providing effective care to patients in this vulnerable time period.

Frailty and associated outcomes and resource utilization following in-hospital cardiac arrest.

BACKGROUND: In-hospital cardiac arrest (IHCA) is common and associated with high mortality. Frailty is increasingly recognized as a predictor of worse prognosis among critically ill patients, but its association with outcomes and resource utilization following IHCA is unknown. METHODS: We performed a retrospective analysis (2013-2016) of a prospectively collected registry from two hospitals of consecutive hospitalized adult patients with IHCA occurring on the hospital wards. We defined frailty using the Clinical Frailty Scale (CFS) score ≥5. CFS scores were based on validated medical review criteria. The primary outcome is hospital mortality. Secondary outcomes include return of spontaneous circulation (ROSC), discharge to long-term care, and hospital costs. We used multivariable logistic regression to adjust for known confounders. RESULTS: We included 477 patients, and 124 (26.0%) had frailty. Frailty was associated with increased odds of hospital death (adjusted odds ratio [aOR]: 2.91 [95% confidence interval [CI]: 2.37-3.48) and discharge to long-term care (aOR 1.94 [95% CI: 1.57-2.32]). Compared with patients without frailty, patients with frailty had decreased odds of ROSC following IHCA (aOR 0.63 [95% CI: 0.41-0.93]). No difference in mean total costs was demonstrated between patients with and without frailty ($50,799 vs. $45,849). Frail patients did have higher cost-per-survivor ($947,546 vs. $161,550). CONCLUSIONS: Frail individuals who experience an IHCA are more likely to die in hospital or be discharged to long-term care, and less likely to achieve ROSC in comparison with individuals who are not frail. The hospital costs per-survivor of IHCA are increased when frailty is present.

Outcomes of hospitalized hematologic oncology patients receiving rapid response system activation for acute deterioration.

BACKGROUND: Patients with hematologic malignancies who are admitted to hospital are at increased risk of deterioration and death. Rapid response systems (RRSs) respond to hospitalized patients who clinically deteriorate. We sought to describe the characteristics and outcomes of hematologic oncology inpatients requiring rapid response system (RRS) activation, and to determine the prognostic accuracy of the SIRS and qSOFA criteria for in-hospital mortality of hematologic oncology patients with suspected infection. METHODS: We used registry data from two hospitals within The Ottawa Hospital network, between 2012 and 2016. Consecutive hematologic oncology inpatients who experienced activation of the RRS were included in the study. Data was gathered at the time of RRS activation and assessment. The primary outcome was in-hospital mortality. Logistical regression was used to evaluate for predictors of in-hospital mortality. RESULTS: We included 401 patients during the study period. In-hospital mortality for all included patients was 41.9% (168 patients), and 145 patients (45%) were admitted to ICU following RRS activation. Among patients with suspected infection at the time of RRS activation, Systemic Inflammatory Response Syndrome (SIRS) criteria had a sensitivity of 86.9% (95% CI 80.9-91.6) and a specificity of 38.2% (95% CI 31.9-44.8) for predicting in-hospital mortality, while Quick Sequential Organ Failure Assessment (qSOFA) criteria had a sensitivity of 61.9% (95% CI 54.1-69.3) and a specificity of 91.4% (95% CI 87.1-94.7). Factors associated with increased in-hospital mortality included transfer to ICU after RRS activation (adjusted odds ratio [OR] 3.56, 95% CI 2.12-5.97) and a higher number of RRS activations (OR 2.45, 95% CI 1.63-3.69). Factors associated with improved survival included active malignancy treatment at the time of RRS activation (OR 0.54, 95% CI 0.34-0.86) and longer hospital length of stay (OR 0.78, 95% CI 0.70-0.87). CONCLUSIONS: Hematologic oncology inpatients requiring RRS activation have high rates of subsequent ICU admission and mortality. ICU admission and higher number of RRS activations are associated with increased risk of death, while active cancer treatment and longer hospital stay are associated with lower risk of mortality. Clinicians should consider these factors in risk-stratifying these patients during RRS assessment.

Frailty and Associated Outcomes and Resource Utilization Among Older ICU Patients With Suspected Infection.

OBJECTIVES: Suspected infection and sepsis are common conditions seen among older ICU patients. Frailty has prognostic importance among critically ill patients, but its impact on outcomes and resource utilization in older patients with suspected infection is unknown. We sought to evaluate the association between patient frailty (defined as a Clinical Frailty Scale ≥ 5) and outcomes of critically ill patients with suspected infection. We also evaluated the association between frailty and the quick Sequential Organ Failure Assessment score. DESIGN: Analysis of a prospectively collected registry. SETTING: Two hospitals within a single tertiary care level hospital system between 2011 and 2016. PATIENTS: We analyzed 1,510 patients 65 years old or older (at the time of ICU admission) and with suspected infection at the time of ICU admission. Of these, 507 (33.6%) were categorized as "frail" (Clinical Frailty Scale ≥ 5). INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: The primary outcome was in-hospital mortality. A total of 558 patients (37.0%) died in-hospital. Frailty was associated with increased risk of in-hospital death (adjusted odds ratio, 1.81 [95% CIs, 1.34-2.49]). Frailty was also associated with higher likelihood of discharge to long-term care (adjusted odds ratio, 2.06 [95% CI, 1.50-2.64]) and higher likelihood of readmission within 30 days (adjusted odds ratio, 1.83 [95% CI, 1.38-2.34]). Frail patients had increased ICU resource utilization and total costs. The combination of frailty and quick Sequential Organ Failure Assessment greater than or equal to 2 further increased the risk of death (adjusted odds ratio, 7.54 [95% CI, 5.82-9.90]). CONCLUSIONS: The presence of frailty among older ICU patients with suspected infection is associated with increased mortality, discharge to long-term care, hospital readmission, resource utilization, and costs. This work highlights the importance of clinical frailty in risk stratification of older ICU patients with suspected infection.

Diagnostic Accuracy and Financial Implications of Age-Adjusted D-Dimer Strategies for the Diagnosis of Deep Venous Thrombosis in the Emergency Department.

BACKGROUND: Multiple D-dimer cutoffs have been suggested for older patients to improve diagnostic specificity for venous thromboembolism. These approaches are better established for pulmonary embolism. OBJECTIVES: We evaluated the diagnostic performance and compared the health system cost for previously suggested cutoffs and a new D-dimer cutoff for low-risk emergency department (ED) deep venous thrombosis (DVT) patients. METHODS: We conducted a retrospective cohort study in two large EDs involving patients aged > 50 years who had low pretest probability for DVT and had a D-dimer performed. The outcome was a diagnosis of DVT at 30 days. We evaluated the diagnostic accuracy and estimated the difference in cost for cutoffs of 500 ng/mL and the age-adjusted (age × 10) rule. A derived cutoff of 1000 ng/mL was also assessed. RESULTS: Nine hundred and seventy-two patients were included (median age 66 years; 59.5% female); 63 (6.5%) patients were diagnosed with DVT. The conventional cutoff of < 500 ng/mL demonstrated a sensitivity of 100% (95% confidence interval [CI] 94.3-100%) and a specificity of 35.6% (95% CI 32.5-38.8%). The age-adjusted approach increased specificity while maintaining high sensitivity. A new cutoff of 1000 ng/mL demonstrated improved performance: sensitivity 100% (95% CI 94.3-00%) and specificity 66.3% (95% CI 63.2-69.4%). Compared to the conventional approach, both the 1000 ng/mL cutoff and the age-adjusted cutoffs could save healthcare dollars. A cutoff of 1000 ng/mL could have saved 310 ED length of stay hours and $166,909 (Canadian dollars) in our cohort, or an average savings of 0.32 h and $172 per patient. CONCLUSIONS: Among patients aged > 50 years with suspected DVT, the age-adjusted D-dimer and a cutoff of 1000 ng/mL improved specificity without compromising sensitivity, and lowered the health care system cost compared to that for the conventional approach.

Prognostic accuracy of the Hamilton Early Warning Score (HEWS) and the National Early Warning Score 2 (NEWS2) among hospitalized patients assessed by a rapid response team.

BACKGROUND: Rapid response teams (RRTs) respond to hospitalized patients experiencing clinical deterioration and help determine subsequent management and disposition. We sought to evaluate and compare the prognostic accuracy of the Hamilton Early Warning Score (HEWS) and the National Early Warning Score 2 (NEWS2) for prediction of in-hospital mortality following RRT activation. We secondarily evaluated a subgroup of patients with suspected infection. METHODS: We retrospectively analyzed prospectively collected data (2012-2016) of consecutive RRT patients from two hospitals. The primary outcome was in-hospital mortality. We calculated the number needed to examine (NNE), which indicates the number of patients that need to be evaluated in order to detect one future death. RESULTS: Five thousand four hundred ninety-one patients were included, of whom 1837 (33.5%) died in-hospital. Mean age was 67.4 years, and 51.6% were male. A HEWS above the low-risk threshold (≥ 5) had a sensitivity of 75.9% (95% confidence interval (CI) 73.9-77.9) and specificity of 67.6% (95% CI 66.1-69.1) for mortality, with a NNE of 1.84. A NEWS2 above the low-risk threshold (≥ 5) had a sensitivity of 84.5% (95% CI 82.8-86.2), and specificity of 49.0% (95% CI: 47.4-50.7), with a NNE of 2.20. The area under the receiver operating characteristic curve (AUROC) was 0.76 (95% CI 0.75-0.77) for HEWS and 0.72 (95% CI: 0.71-0.74) for NEWS2. Among suspected infection patients (n = 1708), AUROC for HEWS was 0.79 (95% CI 0.76-0.81) and for NEWS2, 0.75 (95% CI 0.73-0.78). CONCLUSIONS: The HEWS has comparable clinical accuracy to NEWS2 for prediction of in-hospital mortality among RRT patients.

Comparison of outcomes and costs between adult diabetic ketoacidosis patients admitted to the ICU and step-down unit.

PURPOSE: There is wide variation in the utilization of Intensive Care Unit (ICU) beds for treatment and monitoring of adult patients with Diabetic Ketoacidosis (DKA). We sought to compare the outcomes and hospital costs of adult DKA patients admitted to ICUs as compared to those admitted to step-down units. MATERIALS AND METHODS: We included consecutive adult patients from two hospitals with a diagnosis of DKA. Patients were either admitted to the ICU, or a step-down unit, which has a nurse-to-patient ratio of 2:1, but does not have capability for mechanical ventilation or administration of vasoactive agents. The primary outcome was in-hospital mortality. RESULTS: We included 872 patients in the analysis. 71 (8.1%) were admitted to ICU, while 801 (91.9%) were admitted to a step-down unit. We found no difference in in-hospital mortality between patients admitted to the ICU and those admitted to the step-down unit (adjusted odds ratio [OR]: 1.14, 95% confidence interval [CI]: 0.87-2.64). Mean total hospital costs were significantly higher for patients admitted to the ICU ($20,428 vs. $6484, P < 0.001). CONCLUSIONS: Adult DKA patients admitted to a step-down unit had comparable in-hospital mortality and lower hospital costs as compared to those admitted to the ICU.

Prevalence, Risk Factors, and Clinical Consequences of Recurrent Activation of a Rapid Response Team: A Multicenter Observational Study.

INTRODUCTION: Rapid response teams (RRTs) are groups of health-care providers, implemented by hospitals to respond to distressed hospitalized patients on the hospital wards. Patients assessed by the RRT for deterioration may be admitted to the intensive care unit (ICU) or may be triaged to remain on the wards, putting them at risk of recurrent deterioration and repeat RRT activation. Previous studies evaluating outcomes of patients with recurrent deterioration and multiple RRT activations have produced conflicting results. METHODS: We used a prospectively collected multicenter registry from 2 hospitals within a single tertiary-level hospital system between 2012 and 2016. Comparisons were made between patients with a single RRT activation and those with multiple RRT activations over the course of their admission. Primary outcome was in-hospital mortality, which was analyzed using multivariable logistic regression. RESULTS: A total of 5995 patients who had any RRT activation were analyzed. Of that, 1183 (19.7%) patients had recurrent deterioration and multiple RRT activations during their admission. Risk factors for recurrent deterioration included admission from a home setting (as opposed to a long-term care facility), RRT activation during nighttime hours, and delay (>1 hour) to RRT activation. Recurrent deterioration was associated with increased odds of mortality (adjusted odds ratio [OR]: 1.44 [1.28-1.64], P = <.001). Increasing number of RRT activations were associated with increasing risk of mortality. Patients with recurrent deterioration had prolonged median hospital length of stay (21.0 days vs 12.0 days, P < .001), while patients with only a single activation were more likely to be admitted to the ICU (adjusted OR: 2.30 [1.96-2.70], P < .001). CONCLUSIONS: Recurrent deteriorations leading to RRT activations among hospitalized patients are associated with increased odds of mortality and prolonged hospital length of stay. This work identifies a group of patients who warrant closer attention to help reduce adverse outcomes.

Contemporary Management of the High-Risk Pulmonary Embolism: The Clot Thickens.

Pulmonary embolism (PE) is a common disease process encountered in the acute care setting. It presents on a spectrum of severity with the most severe presentations carrying a substantial risk of morbidity and mortality. In recent years, a wide range of competing treatment strategies have been proposed for the high-risk PE including new catheter-based and extracorporeal techniques, and management has become more challenging. There is currently no consensus as to the optimal approach to treatment. Contemporary management decisions are informed by the balance between the risk of deterioration and the risk of harm from intervention, within the available resources. This review will summarize the current evidence to better inform clinical decision-making in high-risk PE and highlight future directions in management.

Incorporating Laboratory Values Into a Machine Learning Model Improves In-Hospital Mortality Predictions After Rapid Response Team Call.

OBJECTIVES: Machine learning models have been used to predict mortality among patients requiring rapid response team activation. The goal of our study was to assess the impact of adding laboratory values into the model. DESIGN: A gradient boosted decision tree model was derived and internally validated to predict a primary outcome of in-hospital mortality. The base model was then augmented with laboratory values. SETTING: Two tertiary care hospitals within The Ottawa Hospital network. PATIENTS: Inpatients over the age of 18 years who experienced a rapid response team activation between January 1, 2015, and May 31, 2016. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: A total of 2,061 rapid response team activations occurred during the study period. The in-hospital mortality rate was 29.4%. Patients who died were older (median age, 72 vs 68 yr; p < 0.001), had a longer length of stay (length of stay) prior to rapid response team activation (4 vs 2 d; p < 0.001), and more often had respiratory distress (31% vs 22%; p < 0.001). Our base model without laboratory values performed with an area under the receiver operating curve of 0.71 (95% CI, 0.71-0.72). When the base model was augmented with laboratory values, the area under the receiver operating curve improved to 0.77 (95% CI, 0.77-0.78). Important mortality predictors in the base model were age, estimated ratio of Pao2 to Fio2 (calculated using oxygen saturation and estimated Fio2), length of stay prior to rapid response team activation, and systolic blood pressure. CONCLUSIONS: Machine learning models can identify rapid response team patients at a high risk of mortality and potentially supplement clinical decision making. Incorporating laboratory values into model development significantly improved predictive performance in this study.