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BACKGROUND:. Early diagnostic uncertainty for infection causes delays in antibiotic administration in infected patients and unnecessary antibiotic administration in noninfected patients. OBJECTIVE:. To develop a machine learning model for the early detection of untreated infection (eDENTIFI), with the presence of infection determined by clinician chart review. DERIVATION COHORT:. Three thousand three hundred fifty-seven adult patients hospitalized between 2006 and 2018 at two health systems in Illinois, United States. VALIDATION COHORT:. We validated in 1632 patients in a third Illinois health system using area under the receiver operating characteristic curve (AUC). PREDICTION MODEL:. Using a longitudinal discrete-time format, we trained a gradient boosted machine model to predict untreated infection in the next 6 hours using routinely available patient demographics, vital signs, and laboratory results. RESULTS:. eDENTIFI had an AUC of 0.80 (95% CI, 0.79–0.81) in the validation cohort and outperformed the systemic inflammatory response syndrome criteria with an AUC of 0.64 (95% CI, 0.64–0.65; p < 0.001). The most important features were body mass index, age, temperature, and heart rate. Using a threshold with a 47.6% sensitivity, eDENTIFI detected infection a median 2.0 hours (interquartile range, 0.9–5.2 hr) before antimicrobial administration, with a negative predictive value of 93.6%. Antibiotic administration guided by eDENTIFI could have decreased unnecessary IV antibiotic administration in noninfected patients by 10.8% absolute or 46.4% relative percentage points compared with clinicians. CONCLUSION:. eDENTIFI could both decrease the time to antimicrobial administration in infected patients and unnecessary antibiotic administration in noninfected patients. Further prospective validation is needed.

OBJECTIVES:. While opioids are part of usual care for analgesia in the ICU, there are concerns regarding excess use. This is a systematic review of nonsteroidal anti-inflammatory drugs (NSAIDs) use in postoperative critical care adult patients. DATA SOURCES:. We searched Medical Literature Analysis and Retrieval System Online, Excerpta Medica database, Cumulative Index to Nursing and Allied Health Literature, Cochrane Library, trial registries, Google Scholar, and relevant systematic reviews through March 2023. STUDY SELECTION:. Titles, abstracts, and full texts were reviewed independently and induplicate by two investigators to identify eligible studies. We included randomized control trials (RCTs) that compared NSAIDs alone or as an adjunct to opioids for systemic analgesia. The primary outcome was opioid utilization. DATA EXTRACTION:. In duplicate, investigators independently extracted study characteristics, patient demographics, intervention details, and outcomes of interest using predefined abstraction forms. Statistical analyses were conducted using Review Manager software Version 5.4. (The Cochrane Collaboration, Copenhagen, Denmark). DATA SYNTHESIS:. We included 15 RCTs (n = 1,621 patients) for admission to the ICU for postoperative management after elective procedures. Adjunctive NSAID therapy to opioids reduced 24-hour oral morphine equivalent consumption by 21.4 mg (95% CI, 11.8–31.0 mg reduction; high certainty) and probably reduced pain scores (measured by Visual Analog Scale) by 6.1 mm (95% CI, 12.2 decrease to 0.1 increase; moderate certainty). Adjunctive NSAID therapy probably had no impact on the duration of mechanical ventilation (1.6 hr reduction; 95% CI, 0.4 hr to 2.7 reduction; moderate certainty) and may have no impact on ICU length of stay (2.1 hr reduction; 95% CI, 6.1 hr reduction to 2.0 hr increase; low certainty). Variability in reporting adverse outcomes (e.g., gastrointestinal bleeding, acute kidney injury) precluded their meta-analysis. CONCLUSIONS:. In postoperative critical care adult patients, systemic NSAIDs reduced opioid use and probably reduced pain scores. However, the evidence is uncertain for the duration of mechanical ventilation or ICU length of stay. Further research is required to characterize the prevalence of NSAID-related adverse outcomes.

OBJECTIVES:. Current guidance recommends initiation of early enteral nutrition (early EN) within 24–36 hours of ICU admission in critically ill COVID-19 patients. Despite this recommendation, there is quite limited evidence describing the effect of early EN on outcomes in COVID-19 patients. The association between early EN (within 3 d post intubation) and clinical outcomes in adult COVID-19 patients requiring mechanical ventilation (within 2 d post ICU admission) was evaluated. DESIGN:. We performed a nationwide observational cohort study using a nationwide administrative-financial database (Premier) in United States. SETTING:. Information pertaining to all COVID-19 patients admitted to ICU from 75 hospitals between April and December 2020 was analyzed. PATIENTS:. A total of 861 COVID-19 patients were included. INTERVENTIONS:. None. MEASUREMENTS AND MAIN RESULTS:. Clinical outcomes were assessed via regression models to control for patient and hospital characteristics. We identified 513 COVID-19 ICU patients (59.2%) requiring mechanical ventilation who received early EN and had similar baseline characteristics to late EN group. Compared with late EN group, the early EN group had shorter ICU (hazard ratio [HR], 1.39; 95% CI, 1.15–1.68) and hospital length of stays (LOS) (HR, 1.53; 95% CI, 1.23–1.91), fewer mechanical ventilation days (HR, 1.25; 95% CI, 1.01–1.54), and lower cost (–$22,443; 95% CI, –$32,342 to –$12,534). All comparisons were statistically significant (p < 0.05). CONCLUSIONS:. In patients with COVID-19 requiring mechanical ventilation, early EN is associated with earlier liberation from mechanical ventilation, shorter ICU and hospital LOS, and decreased cost. Our results are among the first to support guideline recommendations for initiation of early EN in COVID-19 ICU patients. Further, our data show nearly 40% of critically ill COVID-19 patients fail to have early EN initiated, even at 3 d post initiation of mechanical ventilation. These results emphasize the need for targeted strategies promoting initiation of early EN, as this may lead to improved clinical and economic outcomes in severe COVID-19 patients.

Objectives:. Since the beginning of the coronavirus disease 2019 pandemic, hundreds of thousands of patients have been treated in ICUs across the globe. The severe acute respiratory syndrome–associated coronavirus 2 virus enters cells via the angiotensin-converting enzyme 2 receptor and activates several distinct inflammatory pathways, resulting in hematologic abnormalities and dysfunction in respiratory, cardiac, gastrointestinal renal, endocrine, dermatologic, and neurologic systems. This review summarizes the current state of research in coronavirus disease 2019 pathophysiology within the context of potential organ-based disease mechanisms and opportunities for translational research. Data Sources:. Investigators from the Research Section of the Society of Critical Care Medicine were selected based on expertise in specific organ systems and research focus. Data were obtained from searches conducted in Medline via the PubMed portal, Directory of Open Access Journals, Excerpta Medica database, Latin American and Caribbean Health Sciences Literature, and Web of Science from an initial search from December 2019 to October 15, 2020, with a revised search to February 3, 2021. The medRxiv, Research Square, and clinical trial registries preprint servers also were searched to limit publication bias. Study Selection:. Content experts selected studies that included mechanism-based relevance to the severe acute respiratory syndrome–associated coronavirus 2 virus or coronavirus disease 2019 disease. Data Extraction:. Not applicable. Data Synthesis:. Not applicable. Conclusions:. Efforts to improve the care of critically ill coronavirus disease 2019 patients should be centered on understanding how severe acute respiratory syndrome–associated coronavirus 2 infection affects organ function. This review articulates specific targets for further research.