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Objective: We test the hypothesis that for low-acuity surgical patients, postoperative intensive care unit (ICU) admission is associated with lower value of care compared with ward admission. Background: Overtriaging low-acuity patients to ICU consumes valuable resources and may not confer better patient outcomes. Associations among postoperative overtriage, patient outcomes, costs, and value of care have not been previously reported. Methods: In this longitudinal cohort study, postoperative ICU admissions were classified as overtriaged or appropriately triaged according to machine learning-based patient acuity assessments and requirements for immediate postoperative mechanical ventilation or vasopressor support. The nearest neighbors algorithm identified risk-matched control ward admissions. The primary outcome was value of care, calculated as inverse observed-to-expected mortality ratios divided by total costs. Results: Acuity assessments had an area under the receiver operating characteristic curve of 0.92 in generating predictions for triage classifications. Of 8592 postoperative ICU admissions, 423 (4.9%) were overtriaged. These were matched with 2155 control ward admissions with similar comorbidities, incidence of emergent surgery, immediate postoperative vital signs, and do not resuscitate order placement and rescindment patterns. Compared with controls, overtraiged admissions did not have a lower incidence of any measured complications. Total costs for admission were $16.4K for overtriage and $15.9K for controls (P =0.03). Value of care was lower for overtriaged admissions [2.9 (2.0–4.0)] compared with controls [24.2 (14.1–34.5), P <0.001]. Conclusions: Low-acuity postoperative patients who were overtriaged to ICUs had increased total costs, no improvements in outcomes, and received low-value care. [ABSTRACT FROM AUTHOR]

Objective: To characterize endothelial function, inflammation, and immunosuppression in surgical patients with distinct clinical trajectories of AKI and to determine the impact of persistent kidney injury and renal non-recovery on clinical outcomes, resource utilization, and long-term disability and survival. Summary of Background Data: AKI is associated with increased healthcare costs and mortality. Trajectories that account for duration and recovery of AKI have not been described for sepsis patients, who are uniquely vulnerable to renal dysfunction. Methods: This prospective observational study included 239 sepsis patients admitted and enrolled between January 2015 and July 2017. Kidney Disease: Improving Global Outcomes (KDIGO) and Acute Disease Quality Initiative (ADQI) criteria were used to classify subjects as having no AK I, rapidly reversed AKI, persistent AKI with renal recovery, or persistent AK I without renal recovery. Serial biomarker profiles, clinical outcomes, resource utilization, and long-term physical performance status and survival were compared among AKI trajectories. Results: Sixty-two percent of the study population developed AKI. Only one-third of AKI episodes rapidly reversed within 48 hours; the remaining had persistent AKI , among which 57% did not have renal recovery by discharge. One-year survival and proportion of subjects fully active 1 year after sepsis was lowest among patients with persistent AKI compared with other groups. Long-term mortality hazard rates were 5-fold higher for persistent AKI without renal recovery compared with no AKI. Conclusions: Among critically ill surgical sepsis patients, persistent AKI and the absence of renal recovery are associated with distinct early and sustained immunologic and endothelial biomarker signatures and decreased long-term physical function and survival. [ABSTRACT FROM AUTHOR]

Supplemental Digital Content is available in the text Objective: Develop unifying definitions and paradigms for data-driven methods to augment postoperative resource intensity decisions. Summary Background Data: Postoperative level-of-care assignments and frequency of vital sign and laboratory measurements (ie, resource intensity) should align with patient acuity. Effective, data-driven decision-support platforms could improve value of care for millions of patients annually, but their development is hindered by the lack of salient definitions and paradigms. Methods: Embase, PubMed, and Web of Science were searched for articles describing patient acuity and resource intensity after inpatient surgery. Study quality was assessed using validated tools. Thirty-five studies were included and assimilated according to PRISMA guidelines. Results: Perioperative patient acuity is accurately represented by combinations of demographic, physiologic, and hospital-system variables as input features in models that capture complex, non-linear relationships. Intraoperative physiologic data enriche these representations. Triaging high-acuity patients to low-intensity care is associated with increased risk for mortality; triaging low-acuity patients to intensive care units (ICUs) has low value and imparts harm when other, valid requests for ICU admission are denied due to resource limitations, increasing their risk for unrecognized decompensation and failure-to-rescue. Providing high-intensity care for low-acuity patients may also confer harm through unnecessary testing and subsequent treatment of incidental findings, but there is insufficient evidence to evaluate this hypothesis. Compared with data-driven models, clinicians exhibit volatile performance in predicting complications and making postoperative resource intensity decisions. Conclusion: To optimize value, postoperative resource intensity decisions should align with precise, data-driven patient acuity assessments augmented by models that accurately represent complex, non-linear relationships among risk factors. [ABSTRACT FROM AUTHOR]

[Figure: see text]. [ABSTRACT FROM AUTHOR]

Objective: This review assimilates and critically evaluates available literature regarding the use of metabolomic profiling in surgical decision-making. Background: Metabolomic profiling is performed by nuclear magnetic resonance spectroscopy or mass spectrometry of biofluids and tissues to quantify biomarkers (ie, sugars, amino acids, and lipids), producing diagnostic and prognostic information that has been applied among patients with cardiovascular disease, inflammatory bowel disease, cancer, and solid organ transplants. Methods: PubMed was searched from 1995 to 2019 to identify studies investigating metabolomic profiling of surgical patients. Articles were included and assimilated into relevant categories per PRISMA-ScR guidelines. Results were summarized with descriptive analytical methods. Results: Forty-seven studies were included, most of which were retrospective studies with small sample sizes using various combinations of analytic techniques and types of biofluids and tissues. Results suggest that metabolomic profiling has the potential to effectively screen for surgical diseases, suggest diagnoses, and predict outcomes such as postoperative complications and disease recurrence. Major barriers to clinical adoption include a lack of high-level evidence from prospective studies, heterogeneity in study design regarding tissue and biofluid procurement and analytical methods, and the absence of large, multicenter metabolome databases to facilitate systematic investigation of the efficacy, reproducibility, and generalizability of metabolomic profiling diagnoses and prognoses. Conclusions: Metabolomic profiling research would benefit from standardization of study design and analytic approaches. As technologies improve and knowledge garnered from research accumulates, metabolomic profiling has the potential to provide personalized diagnostic and prognostic information to support surgical decision-making from preoperative to postdischarge phases of care. [ABSTRACT FROM AUTHOR]

Supplemental Digital Content is available in the text Objective: To accurately calculate the risk for postoperative complications and death after surgery in the preoperative period using machine-learning modeling of clinical data. Background: Postoperative complications cause a 2-fold increase in the 30-day mortality and cost, and are associated with long-term consequences. The ability to precisely forecast the risk for major complications before surgery is limited. Methods: In a single-center cohort of 51,457 surgical patients undergoing major inpatient surgery, we have developed and validated an automated analytics framework for a preoperative risk algorithm (MySurgeryRisk) that uses existing clinical data in electronic health records to forecast patient-level probabilistic risk scores for 8 major postoperative complications (acute kidney injury, sepsis, venous thromboembolism, intensive care unit admission >48 hours, mechanical ventilation >48 hours, wound, neurologic, and cardiovascular complications) and death up to 24 months after surgery. We used the area under the receiver characteristic curve (AUC) and predictiveness curves to evaluate model performance. Results: MySurgeryRisk calculates probabilistic risk scores for 8 postoperative complications with AUC values ranging between 0.82 and 0.94 [99% confidence intervals (CIs) 0.81–0.94]. The model predicts the risk for death at 1, 3, 6, 12, and 24 months with AUC values ranging between 0.77 and 0.83 (99% CI 0.76–0.85). Conclusions: We constructed an automated predictive analytics framework for machine-learning algorithm with high discriminatory ability for assessing the risk of surgical complications and death using readily available preoperative electronic health records data. The feasibility of this novel algorithm implemented in real time clinical workflow requires further testing. [ABSTRACT FROM AUTHOR]

Objective: The aim of the study was to determine the long-term cardiovascular-specific mortality in patients with acute kidney injury (AKI) or chronic kidney disease (CKD) after major surgery. Background: In surgical patients, pre-existing CKD and postoperative AKI are associated with increases in all-cause mortality. Methods: In a single-center cohort of 51,457 adult surgical patients undergoing major inpatient surgery, long-term cardiovascular-specific mortality was modeled using a multivariable subdistributional hazards model while treating any other cause of death as a competing risk and accounting for the progression to end-stage renal disease (ESRD) after discharge. Pre-existing CKD and ESRD, and postoperative AKI were the main independent predictors. Results: Before the admission, 4% and 8% of the cohort had pre-existing ESRD and CKD not requiring renal replacement therapy, respectively. During hospitalization, 39% developed AKI. At 10-year follow-up, adjusted cardiovascular-specific mortality estimates were 6%, 11%, 12%, 19%, and 27% for patients with no kidney disease, AKI with no CKD, CKD with no AKI, AKI with CKD, and ESRD, respectively (P < 0.001). This association remained after excluding 916 patients who progressed to ESRD after discharge, although it was significantly amplified among them. Compared with patients having no kidney disease, adjusted hazard ratios for cardiovascular mortality were significantly higher among patients with kidney disease, ranging from 1.95 (95% confidence interval, 1.80–2.11) for patients with de novo AKI to 5.70 (95% confidence interval, 5.00–6.49) for patients with pre-existing ESRD. Conclusions: Both AKI and CKD were associated with higher long-term cardiovascular-specific mortality compared with patients having no kidney disease. [ABSTRACT FROM AUTHOR]

Objective: Calculate mortality risk that accounts for both severity and recovery of postoperative kidney dysfunction using the pattern of longitudinal change in creatinine. Background: Although the importance of renal recovery after acute kidney injury (AKI) is increasingly recognized, the complex association that accounts for longitudinal creatinine changes and mortality is not fully described. Methods: We used routinely collected clinical information for 46,299 adult patients undergoing major surgery to develop a multivariable probabilistic model optimized for nonlinearity of serum creatinine time series that calculates the risk function for 90-day mortality. We performed a 70/30 cross validation analysis to assess the accuracy of the model. Results: All creatinine time series exhibited nonlinear risk function in relation to 90-day mortality and their addition to other clinical factors improved the model discrimination. For any given severity of AKI, patients with complete renal recovery, as manifested by the return of the discharge creatinine to the baseline value, experienced a significant decrease in the odds of dyingwithin 90 days of admission compared with patients with partial recovery. Yet, for any severity of AKI, even complete renal recovery did not entirely mitigate the increased odds of dying, as patients with mildAKI and complete renal recovery still had significantly increased odds for dying compared with patients without AKI [odds ratio: 1.48 (95% confidence interval: 1.30-1.68)]. Conclusions: We demonstrate the nonlinear relationship between both severity and recovery of renal dysfunction and 90-day mortality after major surgery. We have developed an easily applicable computer algorithm that calculates this complex relationship. [ABSTRACT FROM AUTHOR]

Objectives: In a single-center cohort of surgical patients, we assessed the association between postoperative change in serum creatinine and adverse outcomes and compared the American College of Surgeons National Surgical Quality Improvement Program's definition for acute kidney injury with consensus risk, injury, failure, loss, and end-stage kidney and Kidney Disease: Improving Global Outcomes definitions. Design: Retrospective single-center cohort. Setting: Academic tertiary medical center. Patients: Twenty-seven thousand eight hundred forty-one adult patients with no previous history of chronic kidney disease undergoing major surgery. Interventions: Risk, injury, failure, loss, and end-stage kidney defines acute kidney injury as change in serum creatinine greater than or equal to 50% while Kidney Disease: Improving Global Outcomes uses 0.3 mg/dL change from the reference serum creatinine. Since National Surgical Quality Improvement Program defines acute kidney injury as serum creatinine change greater than 2 mg/dL, it may underestimate the risk associated with less severe acute kidney injury. Measurements and Main Results: The optimal discrimination limits for both percent and absolute serum creatinine changes were calculated by maximizing sensitivity and specificity along the receiver operating characteristic curves for postoperative complications and mortality. Although prevalence of risk, injury, failure, loss, and end-stage kidney-acute kidney injury was 37%, only 7% of risk, injury, failure, loss, and end-stage kidney-acute kidney injury patients would be diagnosed with acute kidney injury using the National Surgical Quality Improvement Program definition. In multivariate logistic models, patients with risk, injury, failure, loss, and end-stage kidney or Kidney Disease: Improving Global Outcomes-acute kidney injury had a 10 times higher odds of dying compared to patients without acute kidney injury. The optimal discrimination limits for change in serum creatinine associated with adverse postoperative outcomes were as low as 0.2 mg/dL while the National Surgical Quality Improvement Program discrimination limit of 2.0 mg/dL had low sensitivity (0.05-0.28). Conclusions: Current American College of Surgeons National Surgical Quality Improvement Program definition underestimates the risk associated with mild and moderate acute kidney injury otherwise captured by the consensus risk, injury, failure, loco, and end-stage kidney and Kidney Disease: Improving Global Outcomes criteria. [ABSTRACT FROM AUTHOR]

A letter to the editor is presented in response to the article about the significance of intensive care unit (ICU) structure on improved patients in the 2015 issue.

Objectives: Multicenter data on the characteristics and outcomes of children hospitalized with coronavirus disease 2019 are limited. Our objective was to describe the characteristics, ICU admissions, and outcomes among children hospitalized with coronavirus disease 2019 using Society of Critical Care Medicine Discovery Viral Infection and Respiratory Illness Universal Study: Coronavirus Disease 2019 registry., Design: Retrospective study., Setting: Society of Critical Care Medicine Viral Infection and Respiratory Illness Universal Study (Coronavirus Disease 2019) registry., Patients: Children (< 18 yr) hospitalized with coronavirus disease 2019 at participating hospitals from February 2020 to January 2021., Interventions: None., Measurements and Main Results: The primary outcome was ICU admission. Secondary outcomes included hospital and ICU duration of stay and ICU, hospital, and 28-day mortality. A total of 874 children with coronavirus disease 2019 were reported to Viral Infection and Respiratory Illness Universal Study registry from 51 participating centers, majority in the United States. Median age was 8 years (interquartile range, 1.25-14 yr) with a male:female ratio of 1:2. A majority were non-Hispanic (492/874; 62.9%). Median body mass index (n = 817) was 19.4 kg/m2 (16-25.8 kg/m2), with 110 (13.4%) overweight and 300 (36.6%) obese. A majority (67%) presented with fever, and 43.2% had comorbidities. A total of 238 of 838 (28.2%) met the Centers for Disease Control and Prevention criteria for multisystem inflammatory syndrome in children, and 404 of 874 (46.2%) were admitted to the ICU. In multivariate logistic regression, age, fever, multisystem inflammatory syndrome in children, and pre-existing seizure disorder were independently associated with a greater odds of ICU admission. Hospital mortality was 16 of 874 (1.8%). Median (interquartile range) duration of ICU (n = 379) and hospital (n = 857) stay were 3.9 days (2-7.7 d) and 4 days (1.9-7.5 d), respectively. For patients with 28-day data, survival was 679 of 787, 86.3% with 13.4% lost to follow-up, and 0.3% deceased., Conclusions: In this observational, multicenter registry of children with coronavirus disease 2019, ICU admission was common. Older age, fever, multisystem inflammatory syndrome in children, and seizure disorder were independently associated with ICU admission, and mortality was lower among children than mortality reported in adults., Competing Interests: Dr. Bhalala is currently funded by the National Institutes of Health (NIH) (Site Principal Investigator [PI] for Stress Hydrocortisone in Pediatric Septic Shock—R01HD096901), The Children’s Hospital of Philadelphia (Site-PI for Pediatric Resuscitation Quality Collaborative – PediResQ), Voelcker Pilot Grant (PI for project on prearrest electrocardiographic changes), The Children’s Hospital of San Antonio Endowed Chair Funds for ancillary projects related to Society of Critical Care Medicine (SCCM) Viral Infection and Respiratory Illness Universal Study (VIRUS) (coronavirus disease 2019 [COVID-19]) Registry and SCCM VIRUS electronic medical records, automation pilot. Ms. Boman’s institution received funding from The Gordon and Betty Moore Foundation. Ms. Boman and Drs. Kumar and Kashyap's institutions received funding from Janssen Research and Development, LLC. Dr. Kumar is currently funded by Gordon and Betty Moore Foundation, Centers for Disease Control and Prevention (CDC) Foundation through University of Washington and Janssen Research & Development, LLC. Dr. Chiotos funded by Agency for Healthcare Research and Quality(K12-HS026393). Dr. Bjornstad’s institution received funding from the International Society of Nephrology, The NIH-National Institute of Diabetes and Digestive and Kidney Diseases/T32, and Bioporto. Dr. Dapul disclosed that the deidentified data of some patients submitted to the VIRUS registry were also used in the Overcoming COVID-19 Virus Registry. Dr. Blatz funded by NIH grant T32GM-075766. Dr. Levy’s institution received funding from the CDC (No. 75D30120C07725) and the National Institute of Allergy and Infectious Diseases (AI 144301); she received funding from SinoUnited Health Shanghai Children’s Hospital. Drs. Kaufman’s, Abdelaty’s, and Briton’s institutions received funding from SCCM. Dr. Kaufman received funding from EngleWood Health for consulting work as medical director. Dr. Khanna’s institution received funding for COVID-19 trials Blood Volume Analyzer-Daxor and Chair Steering Committee for the Siltuximab in Selected Hospitalized Patients With Viral Acute Respiratory Distress Syndrome trial. Dr. Khanna is currently funded by a Clinical Translational Science Institute NIH/National Center for Advanced Translational Science KL2 TR001421 award for a trial on continuous postoperative hemodynamic and saturation monitoring and is a site PI (institutional funding) for a randomized trial of cytokine filtration in severe COVID-19 and a prospective observational trial of blood volume assessment in COVID-19. His institution also received funding for the SCCM VIRUS EMR automation pilot. Dr. Stulce received funding from the American Physician Institute. Dr. Anderson III disclosed that he is on the Advisory Board for the Gift of Life Michigan. Dr. Bello disclosed government work. Dr. Walkey currently funded the NIH/National Heart, Lung and Blood Institute (NHLBI) grants R01HL151607, R01HL139751, R01HL136660, Agency of Healthcare Research and Quality, R01HS026485, Boston Biomedical Innovation Center/NIH/NHLBI 5U54HL119145-07, and royalties from UptoDate. Dr. Bihorac received support for article research from the NIH. His institution received funding from the NIH (R01 GM110240 R21 EB 027344), Atox Bio, Astute Medical Research, Mallinckrodt Pharmaceuticals, and La Jolla Pharmaceuticals; she disclosed three institutional patents (20200161000, WO2020172607A12020, and 20190326013). Dr. Zimmerman’s institution received funding from the NIH-National Institute of Child Health and Human Development and Immunexpress; he received funding from Elsevier Publishing. Dr. Kashyap receives funding from the NIH/NHLBI: R01HL 130881, UG3/UH3HL 141722; Gordon and Betty Moore Foundation, and Janssen Research & Development, LLC; and royalties from Ambient Clinical Analytics. The remaining authors have disclosed that they do not have any potential conflicts of interest., (Copyright © 2021 by the Society of Critical Care Medicine and Wolters Kluwer Health, Inc. All Rights Reserved.)

Purpose of Review: Acute and chronic kidney diseases (AKI and CKD) have far-reaching implications for surgical patients in regards to postoperative outcomes and hospital cost. We review the recent literature on the effects of AKI and CKD on morbidity, mortality, and resource utilization among cardiac surgery patients., Recent Findings: Both AKI and CKD increase the risk for short-term and long-term mortalities, morbidity, length of stay, and hospital cost among postoperative patients, with increasing disease stage correlating with worse outcomes. Even the mildest forms of AKI (RIFLE-R) and CKD (proteinuria without an observed reduction in estimated glomerular filtration rate) demonstrate worse clinical outcomes compared with patients with no AKI or CKD. Outcomes are worse even in patients who achieve full renal recovery before hospital discharge. These complications dramatically increase ICU length of stay, hospital length of stay, resource utilization, and both in-hospital and postdischarge costs, as evidenced by lower rates of discharges to home., Summary: AKI and CKD remain prevalent, morbid, and costly conditions for cardiac surgery patients. Better risk stratification, early diagnosis, and earlier interventions are needed to prevent the consequences of these diseases.

Objective: To determine clinical and genomic characteristics and in-hospital mortality risk associated with acute kidney injury (AKI) in the multicenter prospective cohort of patients with blunt trauma., Summary Background Data: Less severe stages of AKI characterized by small changes in serum creatinine (sCr) are inadequately studied among trauma patients., Methods: We performed a secondary analysis of the "Inflammation and the Host Response to Injury" (Glue Grant) database to include adult blunt trauma patients without history of kidney disease. AKI was defined by the Risk, Injury, Failure, Loss, and End-stage Kidney (RIFLE) classification, which requires a 50% increase in sCr and stratifies patients into following 3 severity stages: risk, injury, and failure. Association between all stages of AKI and in-hospital mortality was analyzed using a multivariable logistic regression analysis. Genome-wide expression analysis was performed on whole blood leukocytes obtained within 12 hours of trauma., Results: AKI occurred in 26% of 982 patients. The adjusted risk for hospital death was 3 times higher for patients with AKI compared with patients without AKI (odds ratio = 3.05) (95% confidence interval, 1.73-5.40). This risk was evident in a dose-response manner and even patients with mild AKI had odds ratio for dying of 2.57 (95% confidence interval, 1.19-5.50) compared with patients without AKI. Genome-wide expression analysis failed to show a significant number of genes whose expression could discriminate among patients with and without AKI., Conclusions: In a multicenter prospective cohort of blunt trauma patients, AKI characterized by small changes in sCr was associated with an independent risk of hospital death.

Background: Long-term survival after acute kidney injury (AKI) is poorly studied. We report the relationship between long-term mortality and AKI with small changes in serum creatinine during hospitalization after various cardiothoracic surgery procedures., Methods and Results: This was a retrospective study of 2973 patients with no history of chronic kidney disease who were discharged from the hospital after cardiothoracic surgery between 1992 and 2002. AKI was defined by the RIFLE classification (Risk, Injury, Failure, Loss, and End stage), which requires at least a 50% increase in serum creatinine and stratifies patients into 3 grades of AKI: Risk, injury, and failure. Patient survival was determined through the National Social Security Death Index. Long-term survival was analyzed with a risk-adjusted Cox proportional hazards regression model. Survival was worse among patients with AKI and was proportional to its severity, with an adjusted hazard ratio of 1.23 (95% CI 1.06 to 1.42) for the least severe RIFLE risk class and 2.14 (95% CI 1.73 to 2.66) for the RIFLE failure class compared with patients without AKI. Survival was worse among all subgroups of cardiothoracic surgery with AKI except for valve surgery. Patients with complete renal recovery after AKI still had an increased adjusted hazard ratio for death of 1.28 (95% CI 1.11 to 1.48) compared with patients without AKI., Conclusions: The risk of death associated with AKI after cardiothoracic surgery remains high for 10 years regardless of other risk factors, even for those patients with complete renal recovery. Improved renal protection and closer postdischarge follow-up of renal function may be warranted.

Objective: To determine the relationship between long-term mortality and acute kidney injury (AKI) during hospitalization after major surgery., Summary Background Data: AKI is associated with a risk of short-term mortality that is proportional to its severity; however the long-term survival of patients with AKI is poorly studied., Methods: This is a retrospective cohort study of 10,518 patients with no history of chronic kidney disease who were discharged after a major surgery between 1992 and 2002. AKI was defined by the RIFLE (Risk, Injury, Failure, Loss, and End-stage Kidney) classification, which requires at least a 50% increase in serum creatinine (sCr) and stratifies patients into 3 severity stages: risk, injury, and failure. Patient survival was determined through the National Social Security Death Index. Long-term survival was analyzed using a risk-adjusted Cox proportional hazards regression model., Results: In the risk-adjusted model, survival was worse among patients with AKI and was proportional to its severity with an adjusted hazard ratio of 1.18 (95% confidence interval [CI], 1.08-1.29) for the RIFLE-Risk class and 1.57 (95% CI, 1.40-1.75) for the RIFLE-Failure class, compared with patients without AKI (P < 0.001). Patients with complete renal recovery after AKI still had an increased adjusted hazard ratio for death of 1.20 (95% CI, 1.10-1.31) compared with patients without AKI (P < 0.001)., Conclusions: In a large single-center cohort of patients discharged after major surgery, AKI with even small changes in sCr level during hospitalization was associated with an independent long-term risk of death.