Timing of Intraoperative Transitions of Care Among Anesthesiologists Is Not Associated With Postoperative Adverse Outcomes: Retrospective Cohort Study.

BACKGROUND: The majority of published research suggests that anesthesia handovers during major surgical procedures are associated with unintended harmful consequences. It is still unclear if the number or quality of the transition of care is the main driver of the adverse outcomes. There is even less data if the timing of the anesthesiologist handovers during the critical portion of the anesthetic continuum (induction or emergence versus surgical period) plays a role in patient outcomes. Therefore, we investigated if the anesthesiologist handovers during induction and emergence are associated with adverse patient outcomes. METHODS: This retrospective investigation included noncardiac surgical procedures occurring between January 1, 2012 and December 31, 2019 that had exactly 1 attending anesthesiologist handover. We categorized transitions of care between attending anesthesiologists as being before incision, between incision and closing, and after closing. Our primary outcome was a composite of 6 categories of surgical complications and in-hospital mortality. We created logistic generalized estimating equation models to estimate the average relative effect odds ratio between each pair of the 3 transition timing groups across the components of the composite outcome. Inverse probability of treatment weights were used to mitigate confounding on a host of baseline variables. We used Bonferroni correction to adjust for multiple comparisons between the transition groups. RESULTS: In total, we studied 36,937 procedures with exactly 1 attending anesthesiologist handover. Of these records, 4370 had the transition during induction, 24,999 between incision and closure, and 7568 during emergence. No differences were found between the transition periods and the composite outcome. The estimated average relative effect odds ratio (98.3% confidence interval [CI]) across the components of the composite outcome was as follows: (1.0002 [0.81-1.24], P = .99) between the induction and surgical period; (1.10 [0.87-1.40], P = .32) between the induction and emergence periods; and (0.91 [0.79-1.04], P = .08) between the emergence and surgical periods. CONCLUSIONS: Timing of intraoperative handover among attending anesthesiologists during noncardiac surgery is not associated with adverse patient outcomes.

Derivation and Validation of Clinical Phenotypes of the Cardiopulmonary Bypass-Induced Inflammatory Response.

BACKGROUND: Precision medicine aims to change treatment from a "one-size-fits-all" approach to customized therapies based on the individual patient. Applying a precision medicine approach to a heterogeneous condition, such as the cardiopulmonary bypass (CPB)-induced inflammatory response, first requires identification of homogeneous subgroups that correlate with biological markers and postoperative outcomes. As a first step, we derived clinical phenotypes of the CPB-induced inflammatory response by identifying patterns in perioperative clinical variables using machine learning and simulation tools. We then evaluated whether these phenotypes were associated with biological response variables and clinical outcomes. METHODS: This single-center, retrospective cohort study used Cleveland Clinic registry data from patients undergoing cardiac surgery with CPB from January 2010 to March 2020. Biomarker data from a subgroup of patients enrolled in a clinical trial were also included. Patients undergoing emergent surgery, off-pump surgery, transplantation, descending thoracoabdominal aortic surgery, and planned ventricular assist device placement were excluded. Preoperative and intraoperative variables of patient baseline characteristics (demographics, comorbidities, and laboratory data) and perioperative data (procedural data, CPB duration, and hemodynamics) were analyzed to derive clinical phenotypes using K-means-based consensus clustering analysis. Proportion of ambiguously clustered was used to assess cluster size and optimal cluster numbers. After clusters were formed, we summarized perioperative profiles, inflammatory biomarkers (eg, interleukin [IL]-6 and IL-8), kidney biomarkers (eg, urine neutrophil gelatinase-associated lipocalin [NGAL] and IL-18), and clinical outcomes (eg, mortality and hospital length of stay). Pairwise standardized difference was reported for all summarized variables. RESULTS: Of 36,865 eligible cardiac surgery cases, 25,613 met inclusion criteria. Cluster analysis derived 3 clinical phenotypes: α, ß, and γ. Phenotype α (n = 6157 [24%]) included older patients with more comorbidities, including heart and kidney failure. Phenotype ß (n = 10,572 [41%]) patients were younger and mostly male. Phenotype γ (n = 8884 [35%]) patients were 58% female and had lower body mass index (BMI). Phenotype α patients had worse outcomes, including longer hospital length of stay (mean = 9 days for α versus 6 for both ß [absolute standardized difference {ASD} = 1.15] and γ [ASD = 1.08]), more kidney failure, and higher mortality. Inflammatory biomarkers (IL-6 and IL-8) and kidney injury biomarkers (urine NGAL and IL-18) were higher with the α phenotype compared to ß and γ immediately after surgery. CONCLUSIONS: Deriving clinical phenotypes that correlate with response biomarkers and outcomes represents an initial step toward a precision medicine approach for the management of CPB-induced inflammatory response and lays the groundwork for future investigation, including an evaluation of the heterogeneity of treatment effect.

Effect of a Rapid Response Team on the Incidence of In-Hospital Mortality.

BACKGROUND: Approximately half of the life-limiting events, such as cardiopulmonary arrests or cardiac arrhythmias occurring in hospitals, are considered preventable. These critical events are usually preceded by clinical deterioration. Rapid response teams (RRTs) were introduced to intervene early in the course of clinical deterioration and possibly prevent progression to an event. An RRT was introduced at the Cleveland Clinic in 2009 and transitioned to an anesthesiologist-led system in 2012. We evaluated the association between in-hospital mortality and: (1) the introduction of the RRT in 2009 (primary analysis), and (2) introduction of the anesthesiologist-led system in 2012 and other policy changes in 2014 (secondary analyses). METHODS: We conducted a single-center, retrospective analysis using the medical records of overnight hospitalizations from March 1, 2005, to December 31, 2018, at the Cleveland Clinic. We assessed the association between the introduction of the RRT in 2009 and in-hospital mortality using segmented regression in a generalized estimating equation model to account for within-subject correlation across repeated visits. Baseline potential confounders (demographic factors and surgery type) were controlled for using inverse probability of treatment weighting on the propensity score. We assessed whether in-hospital mortality changed at the start of the intervention and whether the temporal trend (slope) differed from before to after initiation. Analogous models were used for the secondary outcomes. RESULTS: Of 628,533 hospitalizations in our data set, 177,755 occurred before and 450,778 after introduction of our RRT program. Introduction of the RRT was associated with a slight initial increase in in-hospital mortality (odds ratio [95% confidence interval {CI}], 1.17 [1.09-1.25]; P < .001). However, while the pre-RRT slope in in-hospital mortality over time was flat (odds ratio [95% CI] per year, 1.01 [0.98-1.04]; P = .60), the post-RRT slope decreased over time, with an odds ratio per additional year of 0.961 (0.955-0.968). This represented a significant improvement (P < .001) from the pre-RRT slope. CONCLUSIONS: We found a gradual decrease in mortality over a 9-year period after introduction of an RRT program. Although mechanisms underlying this decrease are unclear, possibilities include optimization of RRT implementation, anesthesiology department leadership of the RRT program, and overall improvements in health care delivery over the study period. Our findings suggest that improvements in outcome after RRT introduction may take years to manifest. Further work is needed to better understand the effects of RRT implementation on in-hospital mortality.

Hemodynamic Responses to Crystalloid and Colloid Fluid Boluses during Noncardiac Surgery.

BACKGROUND: Colloids are thought to sustain blood pressure and cardiac index better than crystalloids. However, the relative effects of intraoperative hydroxyethyl starch and crystalloid administration on the cardiac index and blood pressure remain unclear. This study therefore tested in this subanalysis of a previously published large randomized trial the hypothesis that intraoperative goal-directed colloid administration increases the cardiac index more than goal-directed crystalloid administration. Further, the effects of crystalloid and colloid boluses on blood pressure were evaluated. METHODS: This planned subanalysis of a previous trial analyzed data from 973 patients, of whom 480 were randomized to colloids and 493 were randomized to crystalloids. Fluid administration was guided by esophageal Doppler. The primary outcome was the time-weighted average cardiac index during surgery between the colloid and crystalloid group. The secondary outcomes were the cardiac index just after bolus administration, time elapsed between boluses, and the average real variability during surgery. The study recorded cardiac index, corrected flow time, and blood pressure at 10-min intervals, as well as before and after each bolus. RESULTS: Time-weighted average of cardiac index over the duration of anesthesia was only slightly greater in patients given colloid than crystalloid, with the difference being just 0.20 l · min-1 · m-2 (95% CI, 0.11 to 0.29; P < 0.001). However, the hazard for needing additional boluses was lower after colloid administration (hazard ratio [95% CI], 0.60 [0.55 to 0.66]; P < 0.001) in a frailty time-to-event model accounting for within-subject correlation. The median [quartiles] number of boluses per patient was 4 [2, 6] for colloids and 6 [3, 8] for crystalloids, with a median difference (95% CI) of -1.5 (-2 to -1; P < 0.001). The average real mean arterial pressure variability did not differ significantly between the groups (difference in means [95% CI] of -0.03 (-0.07 to 0.02) mmHg, P = 0.229). CONCLUSIONS: There were not clinically meaningful differences in the cardiac index or mean pressure variability in patients given goal-directed colloid and crystalloids. As might be expected from longer intravascular dwell time, the interval between boluses was longer with colloids. However, on a case basis, the number of boluses differed only slightly. Colloids do not appear to provide substantial hemodynamic benefit.

Preoperative Vitamin D Deficiency Is Associated With Postoperative Delirium in Critically Ill Patients.

INTRODUCTION: Postoperative delirium is common, with a reported incidence of 11% to 80% in critically ill patients. Delirium is an independent prognostic factor for poor hospital outcomes. Low vitamin D concentrations are associated with a decline in cognitive function. We therefore tested the hypothesis that low preoperative serum 25-hydroxyvitamin D [25(OH)D] concentrations are associated with postoperative delirium in critically ill patients. METHOD: We conducted a retrospective analysis of adults in a surgical intensive care unit for at least 48 hours immediately after non-cardiac and non-neurosurgical operations at Cleveland Clinic between 2013 and 2018. Delirium was assessed by trained nurses using CAM-ICU twice daily for the initial 5 postoperative days. Any positive value was considered evidence of delirium. We assessed the association between 25(OH)D concentrations within a year before surgery and the incidence of postoperative delirium using logistic regression, adjusted for potential confounders. A linear spline term with a knot at 30 ng/ml, the threshold for normal 25(OH)D concentration, was added to accommodate a nonlinear relationship between 25(OH)D concentrations and delirium. RESULTS: We included 632 patients, who had a mean (SD) 25(OH)D concentration of 25 (15) ng/ml; 55% (346/632) experienced delirium. We observed an adjusted odds ratio of 1.4 (95% CI: [1.1, 1.8], P = 0.01) for delirium per 10 ng/ml decrease in 25(OH)D concentrations when patients' 25(OH)D concentrations were less than 30 ng/ml. In patients whose 25(OH)D concentrations were at least 30 ng/ml, the adjusted odds ratio was 0.9 (95% CI: [0.7, 1.1], P = 0.36). CONCLUSION: Preoperative 25(OH)D concentrations are associated with postoperative delirium in patients whose concentrations are below the normal threshold, but not at concentrations ≥30 ng/ml. A trial will be needed to determine whether the relationship is causal, and whether vitamin D supplementation before surgery might reduce the incidence of delirium.

Risk factors, resource use, and cost of postoperative low cardiac output syndrome.

OBJECTIVE: Low cardiac output syndrome complicates recovery after cardiac surgery. We examined the incidence and risk factors for low cardiac output syndrome and its association with postoperative mortality, morbidity, resource use, and cost. METHODS: This cross-sectional retrospective observational study examined patients having cardiac surgery captured in the Premier Healthcare Database. Low cardiac output syndrome was defined as the requirement for postoperative mechanical circulatory support and/or hemodynamic instability requiring prolonged inotropic support. Incidence, risk factors, and association of low cardiac output syndrome with postoperative outcomes, including mortality, hospital and intensive care unit length of stay, hospital readmission, and cost at 30 days, 90 days, and 6 months, were examined. RESULTS: Among 59,810 patients from 164 hospitals having cardiac surgery between July 1, 2012, and June 30, 2014, low cardiac output syndrome developed in 6067 (10.1%) patients. Patients presenting in cardiogenic shock or systolic (± diastolic) heart failure were at greatest risk. Risk-adjusted in-hospital mortality was 12-fold greater with low cardiac output syndrome (odds ratio, 12.0; 95% confidence interval, 10.6-13.5). Risk-adjusted hospital costs (2019$; median [Q1, Q3]) were $64,041 [21,439] in patients who developed low cardiac output syndrome versus $48,086 [16,098] without; P < .001. Increased costs were driven by longer risk-adjusted hospital stay (10.1 [4.5] vs 8.5 [3.8] days); P < .001, intensive care unit (5.5 [2.5] vs 3.3 [1.5] days; P < .001) stay, and all-cause 30-day adjusted hospital readmission rates (mean [SD] 16.6 [8.2]% vs 13.9 [7.2]%; P < .001). CONCLUSIONS: Cardiac surgical patients who develop postoperative low cardiac output syndrome suffer greater mortality and have greater resource use, health care costs, and all-cause readmission, which informs perioperative decision making, and impacts hospital performance metrics and federal priority to reduce health care costs.