From ICU Syndromes to ICU Subphenotypes: Consensus Report and Recommendations For Developing Precision Medicine in ICU.

Critical care uses syndromic definitions to describe patient groups for clinical practice and research. There is growing recognition that a "precision medicine" approach is required and that integrated biologic and physiologic data identify reproducible subpopulations that may respond differently to treatment. This article reviews the current state of the field and considers how to successfully transition to a precision medicine approach. In order to impact clinical care, identified subpopulations must do more than differentiate prognosis. They must differentiate response to treatment, ideally by defining subgroups with distinct functional or pathobiological mechanisms (endotypes). There are now multiple examples of reproducible subpopulations of sepsis, acute respiratory distress syndrome, and acute kidney or brain injury described using clinical, physiological, and/or biological data. Many of these subpopulations have demonstrated the potential to define differential treatment response, largely in retrospective studies, and that the same treatment-responsive subpopulations may cross multiple clinical syndromes (treatable traits). To bring about a change in clinical practice, a precision medicine approach must be evaluated in prospective clinical studies requiring novel adaptive trial designs. Several such studies are underway but there are multiple challenges to be tackled. Such subpopulations must be readily identifiable and be applicable to all critically ill populations around the world. Subdividing clinical syndromes into subpopulations will require large patient numbers. Global collaboration of investigators, clinicians, industry and patients over many years will therefore be required to transition to a precision medicine approach and ultimately realize treatment advances seen in other medical fields. This article is open access and distributed under the terms of the Creative Commons Attribution Non-Commercial No Derivatives License 4.0 (http://creativecommons.org/licenses/by-nc-nd/4.0/).

Thiamine for Renal Protection in Septic Shock (TRPSS): A Randomized, Placebo-controlled, Clinical Trial.

Rationale: Kidney injury is common and associated with worse outcomes in patients with septic shock. Mitochondrial resuscitation with thiamine (vitamin B1) may attenuate septic kidney injury. Objectives: To assess whether thiamine supplementation attenuates kidney injury in septic shock. Methods: The TRPSS (Thiamine for Renal Protection in Septic Shock) trial was a multicenter, randomized, placebo-controlled trial of thiamine versus placebo in septic shock. The primary outcome was change in serum creatinine between enrollment and 72 hours after enrollment. Measurements and Main Results: Eighty-eight patients were enrolled (42 patients received the intervention, and 46 received placebo). There was no significant between-groups difference in creatinine at 72 hours (mean difference, -0.57 mg/dl; 95% confidence interval, -1.18, 0.04; P = 0.07). There was no difference in receipt of kidney replacement therapy (14.3% vs. 21.7%, P = 0.34), acute kidney injury (as defined by stage 3 of the Kidney Disease: Improving Global Outcomes acute kidney injury scale; 54.7% vs. 73.9%, P = 0.07), or mortality (35.7% vs. 54.3%, P = 0.14) between the thiamine and placebo groups. Patients who received thiamine had more ICU-free days (median [interquartile range]: 22.5 [0.0-25.0] vs. 0.0 [0.0-23.0], P < 0.01). In the thiamine-deficient cohort (27.4% of patients), there was no difference in rates of kidney failure (57.1% thiamine vs. 81.5% placebo) or in-hospital mortality (28.6% vs. 68.8%) between groups. Conclusions: In the TRPSS trial, there was no statistically significant difference in the primary outcome of change in creatinine over time. Patients who received thiamine had more ICU-free days, but there was no difference in other secondary outcomes. Clinical trial registered with www.clinicaltrials.gov (NCT03550794).

Impact of ABCDE Bundle Implementation in the Intensive Care Unit on Specific Patient Costs.

OBJECTIVES: To measure the impact of full versus partial ABCDE bundle implementation on specific cost centers and related resource utilization. DESIGN: Retrospective cohort study. SETTING: Two medical ICUs within Montefiore Health System (Bronx, NY). PATIENTS: Four hundred and seventy-two mechanically ventilated patients admitted to the medical ICUs during a hospitalization which began and ended between January 1, 2013 and December 31, 2013. INTERVENTIONS: The full (A)wakening, (B)reathing, (C)oordination, (D)elirium Monitoring/Management and (E)arly Mobilization bundle was implemented in the intervention ICU while a portion of the bundle (A, B, and D components) was implemented in the comparison ICU. MEASUREMENTS AND MAIN RESULTS: Relative to the comparison ICU, implementation of the entire bundle in the intervention ICU was associated with a 27.3% (95% CI: 9.9%, 41.3%; P = 0.004) decrease in total hospital laboratory costs and a 2,888.6% (95% CI: 77.9%, 50,113.2%; P = 0.018) increase in total hospital physical therapy costs. Cost of total hospital medications, diagnostic radiology and respiratory therapy were unchanged. Relative to the comparison ICU, total hospital resource use decreased in the intervention ICU (incidence rate ratio [95% CI], laboratory: 0.68 [0.54, 0.87], P = 0.002; diagnostic radiology: 0.75 [0.59, 0.96], P = 0.020). CONCLUSIONS: Full ABCDE bundle implementation resulted in a decrease in total hospital laboratory costs and total hospital laboratory and diagnostic resource utilization while leading to an increase in physical therapy costs.

Surviving Sepsis Campaign: Guidelines on the Management of Critically Ill Adults with Coronavirus Disease 2019 (COVID-19).

BACKGROUND: The novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the cause of a rapidly spreading illness, Coronavirus Disease 2019 (COVID-19), affecting thousands of people around the world. Urgent guidance for clinicians caring for the sickest of these patients is needed. METHODS: We formed a panel of 36 experts from 12 countries. All panel members completed the World Health Organization conflict of interest disclosure form. The panel proposed 53 questions that are relevant to the management of COVID-19 in the ICU. We searched the literature for direct and indirect evidence on the management of COVID-19 in critically ill patients in the ICU. We identified relevant and recent systematic reviews on most questions relating to supportive care. We assessed the certainty in the evidence using the Grading of Recommendations, Assessment, Development and Evaluation (GRADE) approach, then generated recommendations based on the balance between benefit and harm, resource and cost implications, equity, and feasibility. Recommendations were either strong or weak, or in the form of best practice recommendations. RESULTS: The Surviving Sepsis Campaign COVID-19 panel issued 54 statements, of which four are best practice statements, nine are strong recommendations, and 35 are weak recommendations. No recommendation was provided for six questions. The topics were: 1) infection control, 2) laboratory diagnosis and specimens, 3) hemodynamic support, 4) ventilatory support, and 5) COVID-19 therapy. CONCLUSION: The Surviving Sepsis Campaign COVID-19 panel issued several recommendations to help support healthcare workers caring for critically ill ICU patients with COVID-19. When available, we will provide new evidence in further releases of these guidelines.

Frailty, Acute Organ Dysfunction, and Increased Disability After Hospitalization in Older Adults Who Survive Critical Illness: A Prospective Cohort Study.

PURPOSE: We aimed to describe the association between prehospital frailty (PHF), acute organ dysfunction (AOD), and posthospital disability (PHD) outcome in older adults admitted to the intensive care unit (ICU). METHODS: In a prospective observational cohort study, we assessed PHF using the Clinical Frailty Scale (CFS) and assessed the level of AOD using Sequential Organ Failure Assessment (SOFA) scores on ICU day 1. We assessed Activities of Daily Living disability levels through to 6 months after discharge and used generalized estimating equations (log link and negative binomial family) to determine the independent association of PHF and AOD with PHD. RESULTS: Of the 302 patients enrolled, 221 (73.1%) survived the hospitalization. Prehospital frailty was associated with PHD (adjusted incident rate ratio [aIRR] 95% confidence interval [95% CI] per unit increase in CFS 1.38 [1.15-1.67], P = .001). Total day 1 SOFA score was weakly associated with PHD, (aIRR [95% CI] 1.05 [1.00-1.10], P = .037) while day 1 SOFA neurologic score was strongly associated with PHD (aIRR [95% CI] 1.42 [1.24-1.62] per unit increase in SOFA neurologic score, P < .001), and these effects were independent of PHF and other premorbid factors. CONCLUSIONS: Both PHF and early acute brain dysfunction are important factors associated with increasing PHD in older adults who survive critical illness.

Staged Implementation of Awakening and Breathing, Coordination, Delirium Monitoring and Management, and Early Mobilization Bundle Improves Patient Outcomes and Reduces Hospital Costs.

OBJECTIVES: To measure the impact of staged implementation of full versus partial ABCDE bundle on mechanical ventilation duration, ICU and hospital lengths of stay, and cost. DESIGN: Prospective cohort study. SETTING: Two medical ICUs within Montefiore Healthcare Center (Bronx, NY). PATIENTS: One thousand eight hundred fifty-five mechanically ventilated patients admitted to ICUs between July 2011 and July 2014. INTERVENTIONS: At baseline, spontaneous (B)reathing trials (B) were ongoing in both ICUs; in period 1, (A)wakening and (D)elirium (AD) were implemented in both full and partial bundle ICUs; in period 2, (E)arly mobilization and structured bundle (C)oordination (EC) were implemented in the full bundle (B-AD-EC) but not the partial bundle ICU (B-AD). MEASUREMENTS AND MAIN RESULTS: In the full bundle ICU, 95% patient days were spent in bed before EC (period 1). After EC was implemented (period 2), 65% of patients stood, 54% walked at least once during their ICU stay, and ICU-acquired pressure ulcers and physical restraint use decreased (period 1 vs 2: 39% vs 23% of patients; 30% vs 26% patient days, respectively; p < 0.001 for both). After adjustment for patient-level covariates, implementation of the full (B-AD-EC) versus partial (B-AD) bundle was associated with reduced mechanical ventilation duration (-22.3%; 95% CI, -22.5% to -22.0%; p < 0.001), ICU length of stay (-10.3%; 95% CI, -15.6% to -4.7%; p = 0.028), and hospital length of stay (-7.8%; 95% CI, -8.7% to -6.9%; p = 0.006). Total ICU and hospital cost were also reduced by 24.2% (95% CI, -41.4% to -2.0%; p = 0.03) and 30.2% (95% CI, -46.1% to -9.5%; p = 0.007), respectively. CONCLUSIONS: In a clinical practice setting, the addition of (E)arly mobilization and structured (C)oordination of ABCDE bundle components to a spontaneous (B)reathing, (A)wakening, and (D) elirium management background led to substantial reductions in the duration of mechanical ventilation, length of stay, and cost.

Multicenter derivation and validation of an early warning score for acute respiratory failure or death in the hospital.

BACKGROUND: Acute respiratory failure occurs frequently in hospitalized patients and often starts before ICU admission. A risk stratification tool to predict mortality and risk for mechanical ventilation (MV) may allow for earlier evaluation and intervention. We developed and validated an automated electronic health record (EHR)-based model-Accurate Prediction of Prolonged Ventilation (APPROVE)-to identify patients at risk of death or respiratory failure requiring >= 48 h of MV. METHODS: This was an observational study of adults admitted to four hospitals in 2013 or a fifth hospital in 2017. Clinical data were extracted from the EHRs. The 2013 patients were randomly split 50:50 into a derivation/validation cohort. The qualifying event was death or intubation leading to MV >= 48 h. Random forest method was used in model derivation. APPROVE was calculated retrospectively whenever data were available in 2013, and prospectively every 4 h after hospital admission in 2017. The Modified Early Warning Score (MEWS) and National Early Warning Score (NEWS) were calculated at the same times as APPROVE. Clinicians were not alerted except for APPROVE in 2017cohort. RESULTS: There were 68,775 admissions in 2013 and 2258 in 2017. APPROVE had an area under the receiver operator curve of 0.87 (95% CI 0.85-0.88) in 2013 and 0.90 (95% CI 0.84-0.95) in 2017, which is significantly better than the MEWS and NEWS in 2013 but similar to the MEWS and NEWS in 2017. At a threshold of > 0.25, APPROVE had similar sensitivity and positive predictive value (PPV) (sensitivity 63% and PPV 21% in 2013 vs 64% and 16%, respectively, in 2017). Compared to APPROVE in 2013, at a threshold to achieve comparable PPV (19% at MEWS > 4 and 22% at NEWS > 6), the MEWS and NEWS had lower sensitivity (16% for MEWS and NEWS). Similarly in 2017, at a comparable sensitivity threshold (64% for APPROVE > 0.25 and 67% for MEWS and NEWS > 4), more patients who triggered an alert developed the event with APPROVE (PPV 16%) while achieving a lower false positive rate (FPR 5%) compared to the MEWS (PPV 7%, FPR 14%) and NEWS (PPV 4%, FPR 25%). CONCLUSIONS: An automated EHR model to identify patients at high risk of MV or death was validated retrospectively and prospectively, and was determined to be feasible for real-time risk identification. TRIAL REGISTRATION: ClinicalTrials.gov, NCT02488174 . Registered on 18 March 2015.

Outcomes after Rehospitalization at the Same Hospital or a Different Hospital Following Critical Illness.

RATIONALE: Intensive care unit (ICU) patients who receive mechanical ventilation are at high risk for early rehospitalization. Given the medical complexity of these patients, a lack of continuity of care may adversely affect their outcomes during rehospitalization. OBJECTIVES: To determine whether outcomes differ for patients who are rehospitalized at a different hospital versus the hospital of their index ICU stay. METHODS: We conducted a retrospective cohort study of mechanically ventilated ICU patients rehospitalized within 30 days in New York State hospitals between 2008 and 2013. MEASUREMENTS AND MAIN RESULTS: We measured frequency of rehospitalization at a different hospital, mortality, length of stay, and costs during rehospitalization. Of 26,947 mechanically ventilated ICU patients rehospitalized within 30 days of discharge, 8,443 (31.3%) were rehospitalized at a different hospital than that of the index ICU stay. For patients at a different hospital, 13.7% died during rehospitalization versus 11.1% who died at the index hospital (adjusted rate ratio [aRR], 1.11; 95% confidence interval [CI], 1.03-1.20; P = 0.009). Patients who died at a different hospital had shorter length of stay (aRR, 0.80; 95% CI, 0.70-0.92; P = 0.001) and decreased costs (adjusted mean difference, -$9,632.73; 95% CI, -$16,387.60 to -$2,877.88; P = 0.005), whereas survivors of rehospitalization at a different hospital had a modest increase in length of stay (aRR, 1.06; 95% CI, 1.01-1.11; P = 0.009) and increased costs of care (adjusted mean difference, $1,665.34; 95% CI, $602.12-$2,728.56; P = 0.002). CONCLUSIONS: Almost one-third of mechanically ventilated critically ill patients were rehospitalized at a different hospital than that of the index ICU stay. This care discontinuity was associated with increased mortality.

An Official American Thoracic Society/American College of Chest Physicians Clinical Practice Guideline: Liberation from Mechanical Ventilation in Critically Ill Adults. Rehabilitation Protocols, Ventilator Liberation Protocols, and Cuff Leak Tests.

BACKGROUND: Interventions that lead to earlier liberation from mechanical ventilation can improve patient outcomes. This guideline, a collaborative effort between the American Thoracic Society and the American College of Chest Physicians, provides evidence-based recommendations to optimize liberation from mechanical ventilation in critically ill adults. METHODS: Two methodologists performed evidence syntheses to summarize available evidence relevant to key questions about liberation from mechanical ventilation. The methodologists appraised the certainty in the evidence (i.e., the quality of evidence) using the Grading of Recommendations, Assessment, Development, and Evaluation approach and summarized the results in evidence profiles. The guideline panel then formulated recommendations after considering the balance of desirable consequences (benefits) versus undesirable consequences (burdens, adverse effects, and costs), the certainty in the evidence, and the feasibility and acceptability of various interventions. Recommendations were rated as strong or conditional. RESULTS: The guideline panel made four conditional recommendations related to rehabilitation protocols, ventilator liberation protocols, and cuff leak tests. The recommendations were for acutely hospitalized adults mechanically ventilated for more than 24 hours to receive protocolized rehabilitation directed toward early mobilization, be managed with a ventilator liberation protocol, be assessed with a cuff leak test if they meet extubation criteria but are deemed high risk for postextubation stridor, and be administered systemic steroids for at least 4 hours before extubation if they fail the cuff leak test. CONCLUSIONS: The American Thoracic Society/American College of Chest Physicians recommendations are intended to support healthcare professionals in their decisions related to liberating critically ill adults from mechanical ventilation.

Official Executive Summary of an American Thoracic Society/American College of Chest Physicians Clinical Practice Guideline: Liberation from Mechanical Ventilation in Critically Ill Adults.

BACKGROUND: This clinical practice guideline addresses six questions related to liberation from mechanical ventilation in critically ill adults. It is the result of a collaborative effort between the American Thoracic Society and the American College of Chest Physicians. METHODS: A multidisciplinary panel posed six clinical questions in a Population, Intervention, Comparator, and Outcomes format. A comprehensive literature search and evidence synthesis was performed for each question, which included appraising the certainty in the evidence (i.e., the quality of evidence) using the Grading of Recommendations, Assessment, Development, and Evaluation approach. The Evidence-to-Decision framework was applied to each question, requiring the panel to evaluate and weigh the importance of the problem, the confidence in the evidence, the certainty about how much the public values the main outcomes, the magnitude and balance of desirable and undesirable outcomes, the resources and costs associated with the intervention, the impact on health disparities, and the acceptability and feasibility of the intervention. RESULTS: Evidence-based recommendations were formulated and graded initially by subcommittees and then modified after full-panel discussions. The recommendations were confirmed by confidential electronic voting; approval required that at least 80% of the panel members agree with the recommendation. CONCLUSIONS: The panel provides recommendations regarding liberation from mechanical ventilation. The details regarding the evidence and rationale for each recommendation are presented in the American Journal of Respiratory and Critical Care Medicine and Chest.

Quantifying the Effects of Prior Acetyl-Salicylic Acid on Sepsis-Related Deaths: An Individual Patient Data Meta-Analysis Using Propensity Matching.

OBJECTIVE: The primary objective was to conduct a meta-analysis on published observational cohort data describing the association between acetyl-salicylic acid (aspirin) use prior to the onset of sepsis and mortality in hospitalized patients. STUDY SELECTION: Studies that reported mortality in patients on aspirin with sepsis with a comparison group of patients with sepsis not on prior aspirin therapy were included. DATA SOURCES: Fifteen studies described hospital-based cohorts (n = 17,065), whereas one was a large insurance-based database (n = 683,421). Individual-level patient data were incorporated from all selected studies. DATA EXTRACTION: Propensity analyses with 1:1 propensity score matching at the study level were performed, using the most consistently available covariates judged to be associated with aspirin. Meta-analyses were performed to estimate the pooled average treatment effect of aspirin on sepsis-related mortality. DATA SYNTHESIS: Use of aspirin was associated with a 7% (95% CI, 2-12%; p = 0.005) reduction in the risk of death as shown by meta-analysis with considerable statistical heterogeneity (I = 61.6%). CONCLUSIONS: These results are consistent with effects ranging from a 2% to 12% reduction in mortality risk in patients taking aspirin prior to sepsis onset. This association anticipates results of definitive studies of the use of low-dose aspirin as a strategy for reduction of deaths in patients with sepsis.

Lung Injury Prediction Score in Hospitalized Patients at Risk of Acute Respiratory Distress Syndrome.

OBJECTIVE: The Lung Injury Prediction Score identifies patients at risk for acute respiratory distress syndrome in the emergency department, but it has not been validated in non-emergency department hospitalized patients. We aimed to evaluate whether Lung Injury Prediction Score identifies non-emergency department hospitalized patients at risk of developing acute respiratory distress syndrome at the time of critical care contact. DESIGN: Retrospective study. SETTING: Five academic medical centers. PATIENTS: Nine hundred consecutive patients (≥ 18 yr old) with at least one acute respiratory distress syndrome risk factor at the time of critical care contact. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: Lung Injury Prediction Score was calculated using the worst values within the 12 hours before initial critical care contact. Patients with acute respiratory distress syndrome at the time of initial contact were excluded. Acute respiratory distress syndrome developed in 124 patients (13.7%) a median of 2 days (interquartile range, 2-3) after critical care contact. Hospital mortality was 22% and was significantly higher in acute respiratory distress syndrome than non-acute respiratory distress syndrome patients (48% vs 18%; p < 0.001). Increasing Lung Injury Prediction Score was significantly associated with development of acute respiratory distress syndrome (odds ratio, 1.31; 95% CI, 1.21-1.42) and the composite outcome of acute respiratory distress syndrome or death (odds ratio, 1.26; 95% CI, 1.18-1.34). A Lung Injury Prediction Score greater than or equal to 4 was associated with the development of acute respiratory distress syndrome (odds ratio, 4.17; 95% CI, 2.26-7.72), composite outcome of acute respiratory distress syndrome or death (odds ratio, 2.43; 95% CI, 1.68-3.49), and acute respiratory distress syndrome after accounting for the competing risk of death (hazard ratio, 3.71; 95% CI, 2.05-6.72). For acute respiratory distress syndrome development, the Lung Injury Prediction Score has an area under the receiver operating characteristic curve of 0.70 and a Lung Injury Prediction Score greater than or equal to 4 has 90% sensitivity (misses only 10% of acute respiratory distress syndrome cases), 31% specificity, 17% positive predictive value, and 95% negative predictive value. CONCLUSIONS: In a cohort of non-emergency department hospitalized patients, the Lung Injury Prediction Score and Lung Injury Prediction Score greater than or equal to 4 can identify patients at increased risk of acute respiratory distress syndrome and/or death at the time of critical care contact but it does not perform as well as in the original emergency department cohort.

Acute respiratory distress syndrome: shifting the emphasis from treatment to prevention.

PURPOSE OF REVIEW: Although results from clinical trials have advanced the treatment of acute respiratory distress syndrome (ARDS), mortality remains high. More recently, focus has shifted from treatment of ARDS to early identification and prevention in at-risk populations. RECENT FINDINGS: There have been 30 published and registered clinical trials with either the primary or secondary goal of reducing ARDS. SUMMARY: With this change in paradigm, come additional challenges and consideration in study design that depends not only on the intervention but also whether the intervention aims for a primary, secondary, or tertiary prevention of ARDS that targets a patient population for universal, selective, or indicated prevention. These epidemiologic concepts of prevention in public health also apply to ARDS and are relevant to the study population to target, the timing of the intervention relative to critical illness, the study design and outcomes to measure in an ARDS prevention study. This shift in focus is reflected by the new National Heart Lung Blood Institute Prevention and Early Treatment of Acute Lung Injury network, and signifies an overall movement away from reacting to and supporting acute organ failure after it is established to early detection and prevention in acute critical illness wherever and whenever it may occur.

Improving the Patient Handoff Process in the Intensive Care Unit: Keys to Reducing Errors and Improving Outcomes.

Patient handoffs are highly variable and error prone. They have been recognized as a major health care challenge. Patients in the intensive care unit are particularly vulnerable due to their complex clinical history and the critical nature of their condition. Given a general movement from traditional long call to shift schedules, the number of patient handoffs will likely continue to increase. Optimization of the handoff process has become even more critical to ensure patient safety. In this review, we reflect on the importance of the handoff process, review common errors, identify barriers and challenges, and propose different methods to improving the handoff process. The purpose of this article is to examine the overall scope of the problem; provide the most up-to-date evidence on the handoff process; and identify ways to perform handoffs in an accurate, safe, and efficient manner to provide high-quality patient care. The direction of future research is also proposed.

Effect of Aspirin on Development of ARDS in At-Risk Patients Presenting to the Emergency Department: The LIPS-A Randomized Clinical Trial.

IMPORTANCE: Management of acute respiratory distress syndrome (ARDS) remains largely supportive. Whether early intervention can prevent development of ARDS remains unclear. OBJECTIVE: To evaluate the efficacy and safety of early aspirin administration for the prevention of ARDS. DESIGN, SETTING, AND PARTICIPANTS: A multicenter, double-blind, placebo-controlled, randomized clinical trial conducted at 16 US academic hospitals. Between January 2, 2012, and November 17, 2014, 7673 patients at risk for ARDS (Lung Injury Prediction Score ≥4) in the emergency department were screened and 400 were randomized. Ten patients were excluded, leaving 390 in the final modified intention-to-treat analysis cohort. INTERVENTIONS: Administration of aspirin, 325-mg loading dose followed by 81 mg/d (n = 195) or placebo (n = 195) within 24 hours of emergency department presentation and continued to hospital day 7, discharge, or death. MAIN OUTCOMES AND MEASURES: The primary outcome was the development of ARDS by study day 7. Secondary measures included ventilator-free days, hospital and intensive care unit length of stay, 28-day and 1-year survival, and change in serum biomarkers associated with ARDS. A final α level of .0737 (α = .10 overall) was required for statistical significance of the primary outcome. RESULTS: Among 390 analyzed patients (median age, 57 years; 187 [48%] women), the median (IQR) hospital length of stay was 6 3-10) days. Administration of aspirin, compared with placebo, did not significantly reduce the incidence of ARDS at 7 days (10.3% vs 8.7%, respectively; odds ratio, 1.24 [92.6% CI, 0.67 to 2.31], P = .53). No significant differences were seen in secondary outcomes: ventilator-free to day 28, mean (SD), 24.9 (7.4) days vs 25.2 (7.0) days (mean [90% CI] difference, -0.26 [-1.46 to 0.94] days; P = .72); ICU length of stay, mean (SD), 5.2 (7.0) days vs 5.4 (7.0) days (mean [90% CI] difference, -0.16 [-1.75 to 1.43] days; P = .87); hospital length of stay, mean (SD), 8.8 (10.3) days vs 9.0 (9.9) days (mean [90% CI] difference, -0.27 [-1.96 to 1.42] days; P = .79); or 28-day survival, 90% vs 90% (hazard ratio [90% CI], 1.03 [0.60 to 1.79]; P = .92) or 1-year survival, 73% vs 75% (hazard ratio [90% CI], 1.06 [0.75 to 1.50]; P = .79). Bleeding-related adverse events were infrequent in both groups (aspirin vs placebo, 5.6% vs 2.6%; odds ratio [90% CI], 2.27 [0.92 to 5.61]; P = .13). RESULTS: Among 390 analyzed patients (median age, 57 years; 187 [48%] women), median (IQR) hospital length of stay was 6 (3-10) days. Administration of aspirin, compared with placebo, did not significantly reduce the incidence of ARDS at 7 days (OR, 1.24; 92.6%CI, 0.67-2.31). No significant differences were seen in secondary outcomes or adverse events. [table: see text] CONCLUSIONS AND RELEVANCE: Among at-risk patients presenting to the ED, the use of aspirin compared with placebo did not reduce the risk of ARDS at 7 days. The findings of this phase 2b trial do not support continuation to a larger phase 3 trial. TRIAL REGISTRATION: clinicaltrials.gov Identifier: NCT01504867.

Early and late unplanned rehospitalizations for survivors of critical illness*.

OBJECTIVES: Preventing rehospitalizations for patients with serious chronic illnesses is a focus of national quality initiatives. Although 8 million people are admitted yearly to an ICU, the frequency of rehospitalizations (readmissions to the hospital after discharge) is unknown. We sought to determine the frequency of rehospitalization after an ICU stay, outcomes for rehospitalized patients, and factors associated with rehospitalization. DESIGN: Retrospective cohort study using the New York Statewide Planning and Research Cooperative System, an administrative database of all hospital discharges in New York State. SETTING: ICUs in New York State. PATIENTS: ICU patients who survived to hospital discharge in 2008-2010. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: Primary outcome was the cumulative incidence of first early rehospitalization (within 30 days of discharge), and secondary outcome was the cumulative incidence of late rehospitalization (between 31 and 180 d). Factors associated with rehospitalization within both time periods were identified using competing risk regression models. Of 492,653 ICU patients, 79,960 had a first early rehospitalization (cumulative incidence, 16.2%) and an additional 73,250 late rehospitalizations (cumulative incidence, 18.9%). Over one quarter of all rehospitalizations (28.6% for early; 26.7% for late) involved ICU admission. Overall hospital mortality for rehospitalized patients was 7.6% for early and 4.6% for late rehospitalizations. Longer index hospitalization (adjusted hazard ratio, 1.61; 95% CI, 1.57-1.66 for 7-13 d vs < 3 d), discharge to a skilled nursing facility versus home (adjusted hazard ratio, 1.54; 95% CI, 1.51-1.58), and having metastatic cancer (adjusted hazard ratio, 1.46; 95% CI, 1.41-1.51) were associated with the greatest hazard of early rehospitalization. CONCLUSIONS: Approximately 16% of ICU survivors were rehospitalized within 30 days of hospital discharge; rehospitalized patients had high rates of ICU admission and hospital mortality. Few characteristics were strongly associated with rehospitalization, suggesting that identifying high-risk individuals for intervention may require additional predictors beyond what is available in administrative databases.

Validation of cell-cycle arrest biomarkers for acute kidney injury using clinical adjudication.

RATIONALE: We recently reported two novel biomarkers for acute kidney injury (AKI), tissue inhibitor of metalloproteinases (TIMP)-2 and insulin-like growth factor binding protein 7 (IGFBP7), both related to G1 cell cycle arrest. OBJECTIVES: We now validate a clinical test for urinary [TIMP-2]·[IGFBP7] at a high-sensitivity cutoff greater than 0.3 for AKI risk stratification in a diverse population of critically ill patients. METHODS: We conducted a prospective multicenter study of 420 critically ill patients. The primary analysis was the ability of urinary [TIMP-2]·[IGFBP7] to predict moderate to severe AKI within 12 hours. AKI was adjudicated by a committee of three independent expert nephrologists who were masked to the results of the test. MEASUREMENTS AND MAIN RESULTS: Urinary TIMP-2 and IGFBP7 were measured using a clinical immunoassay platform. The primary endpoint was reached in 17% of patients. For a single urinary [TIMP-2]·[IGFBP7] test, sensitivity at the prespecified high-sensitivity cutoff of 0.3 (ng/ml)(2)/1,000 was 92% (95% confidence interval [CI], 85-98%) with a negative likelihood ratio of 0.18 (95% CI, 0.06-0.33). Critically ill patients with urinary [TIMP-2]·[IGFBP7] greater than 0.3 had seven times the risk for AKI (95% CI, 4-22) compared with critically ill patients with a test result below 0.3. In a multivariate model including clinical information, urinary [TIMP-2]·[IGFBP7] remained statistically significant and a strong predictor of AKI (area under the curve, 0.70, 95% CI, 0.63-0.76 for clinical variables alone, vs. area under the curve, 0.86, 95% CI, 0.80-0.90 for clinical variables plus [TIMP-2]·[IGFBP7]). CONCLUSIONS: Urinary [TIMP-2]·[IGFBP7] greater than 0.3 (ng/ml)(2)/1,000 identifies patients at risk for imminent AKI. Clinical trial registered with www.clinicaltrials.gov (NCT 01573962).

Comparison of risk prediction scoring systems for ward patients: a retrospective nested case-control study.

INTRODUCTION: The rising prevalence of rapid response teams has led to a demand for risk-stratification tools that can estimate a ward patient's risk of clinical deterioration and subsequent need for intensive care unit (ICU) admission. Finding such a risk-stratification tool is crucial for maximizing the utility of rapid response teams. This study compares the ability of nine risk prediction scores in detecting clinical deterioration among non-ICU ward patients. We also measured each score serially to characterize how these scores changed with time. METHODS: In a retrospective nested case-control study, we calculated nine well-validated prediction scores for 328 cases and 328 matched controls. Our cohort included non-ICU ward patients admitted to the hospital with a diagnosis of infection, and cases were patients in this cohort who experienced clinical deterioration, defined as requiring a critical care consult, ICU admission, or death. We then compared each prediction score's ability, over the course of 72 hours, to discriminate between cases and controls. RESULTS: At 0 to 12 hours before clinical deterioration, seven of the nine scores performed with acceptable discrimination: Sequential Organ Failure Assessment (SOFA) score area under the curve of 0.78, Predisposition/Infection/Response/Organ Dysfunction Score of 0.76, VitalPac Early Warning Score of 0.75, Simple Clinical Score of 0.74, Mortality in Emergency Department Sepsis of 0.74, Modified Early Warning Score of 0.73, Simplified Acute Physiology Score II of 0.73, Acute Physiology and Chronic Health Evaluation II of 0.72, and Rapid Emergency Medicine Score of 0.67. By measuring scores over time, it was found that average SOFA scores of cases increased as early as 24 to 48 hours prior to deterioration (P = 0.01). Finally, a clinical prediction rule which also accounted for the change in SOFA score was constructed and found to perform with a sensitivity of 75% and a specificity of 72%, and this performance is better than that of any SOFA scoring model based on a single set of physiologic variables. CONCLUSIONS: ICU- and emergency room-based prediction scores can also be used to prognosticate risk of clinical deterioration for non-ICU ward patients. In addition, scoring models that take advantage of a score's change over time may have increased prognostic value over models that use only a single set of physiologic measurements.

Estimated glomerular filtration rate among intensive care unit survivors: From the removal of race coefficient to cystatin C-based equations.

PURPOSE: Black race coefficient used in serum creatinine (sCr)-based estimated glomerular filtration rate (eGFR) calculation may perpetuate racial disparities. Among intensive care unit (ICU) survivors, sCr overestimates kidney function due to sarcopenia. Cystatin C (cysC) is a race- and muscle mass-independent eGFR marker. We investigated the impact of removing the race coefficient from sCr-based eGFR and compared cysC- and sCr-based eGFR in ICU survivors. MATERIALS AND METHODS: Among 30,920 patients from 2 institutions in the Bronx and Boston, eGFR was calculated at hospital discharge using sCr-based equations with and without race coefficient (eGFRsCr2009 and eGFRsCr2021). In a subset with available cysC between ICU admission and 1-year follow-up, sCr- and cysC-based estimates were compared. RESULTS: eGFRsCr2021 was higher than eGFRsCr2009 by a median of 4 ml/min/1.73 m2 among non-Black patients and lower by a median of 8 ml/min/1.73 m2 among Black patients. Removing race coefficient reclassified 12.9% of non-Black subjects and 16.1% of Black subjects to better and worse eGFR category, respectively, and differentially impacted the prevalence of kidney dysfunction between the institutions due to differences in racial composition. Among 51 patients with available cysC (108 measurements), cysC-based estimates were lower than sCr-based estimates (median difference 9 to 16 ml/min/1.73 m2), resulting in reclassification to worse eGFR category in 34% to 53.5% of measurements. CONCLUSIONS: Among ICU survivors, removal of race coefficient leads to lower eGFR in Black patients and may contribute to overestimation of kidney function in non-Black patients. While cysC is rarely used, estimates based on this marker are significantly lower than those based on sCr.

Design and implementation of the hospital airway resuscitation trial.

Guidelines for the management of in-hospital cardiac arrest resuscitation are often drawn from evidence generated in out-of-hospital cardiac arrest populations and applied to the in-hospital setting. Approach to airway management during resuscitation is one example of this phenomenon, with the recommendation to place either a supraglottic airway or endotracheal tube when performing advanced airway management during in-hospital cardiac arrest based mainly in clinical trials conducted in the out-of-hospital setting. The Hospital Airway Resuscitation Trial (HART) is a pragmatic cluster-randomized superiority trial comparing a strategy of first choice supraglottic airway to a strategy of first choice endotracheal intubation during resuscitation from in-hospital cardiac arrest. The design includes a number of innovative elements such as a highly pragmatic design drawing from electronic health records and a novel primary outcome measure for cardiac arrest trials-alive-and-ventilator free days. Many of the topics explored in the design of HART have wide relevance to other trials in in-hospital cardiac arrest populations.