Valerie Banner-Goodspeed

Data collection in randomized trials is expensive and labor intensive. With the rise in ongoing pragmatic trials, the use of electronic medical records (EMR) as a source of data has increased. Although potentially faster and cheaper, EMR use can lead to errors. Therefore, to ensure accurate data collection and to avoid systematic errors we performed a study comparing automated data extraction (ADE) with manual data extraction (MDE). We performed a retrospective cohort study to compare the accuracy of ADE using Structured Query Language with MDE by blinded physicians from our EMR. We tested the interrater agreement and intraclass correlation coefficient of clinical baseline data and outcomes of a random sample of 30 patients admitted to the ICU, on mechanical ventilation, requiring opioids for analgosedation for an upcoming pragmatic clinical trial. Key data compared included, but not limited to, patient’s demographics, laboratory and vital signs, daily morphine milligram equivalent (MME), days alive and free of mechanical ventilation, days alive and free of hospitalization, days alive and free of ICU, days alive and free of vasopressors, and death. Among 238 patients screened over 1-month period, 72 fulfilled inclusion criteria and 30 were randomly selected to be included in the evaluation. We blindly collected 1320 baseline data, 2160 categorical outcomes and 705 continuous outcomes for a total of 4185 data points. The intraclass correlation coefficient and the Cohen’s Kappa were perfect or almost perfect for all data, including outcomes such as daily MME, days alive and free of mechanical ventilation, days alive and free of ICU and days alive and free of hospital with p < 0.001. Among all rechecked data, the ADE was correct in 53 (77.9%) of cases, while MDE in 15 (22.1%). The inaccurate data collected by ADE accounted for 0.36% of the total data-points. The performance of ADE had almost perfect agreement for all outcomes and when rechecking for disagreements, it was more accurate than MDE.

Purpose Latent class analysis (LCA) has identified hyper- and non-hyper-inflammatory subphenotypes in patients with acute respiratory distress syndrome (ARDS). It is unknown how early inflammatory subphenotypes can be identified in patients at risk of ARDS. We aimed to test for inflammatory subphenotypes upon presentation to the emergency department. Methods LIPS-A was a trial of aspirin to prevent ARDS in at-risk patients presenting to the emergency department. In this secondary analysis, we performed LCA using clinical, blood test, and biomarker variables. Results Among 376 (96.4%) patients from the LIPS-A trial, two classes were identified upon presentation to the emergency department (day 0): 72 (19.1%) patients demonstrated characteristics of a hyper-inflammatory and 304 (80.9%) of a non-hyper-inflammatory subphenotype. 15.3% of patients in the hyper- and 8.2% in the non-hyper-inflammatory class developed ARDS (p = 0.07). Patients in the hyper-inflammatory class had fewer ventilator-free days (median [interquartile range, IQR] 28[23–28] versus 28[27–28]; p = 0.010), longer intensive care unit (3[2–6] versus 0[0–3] days; p < 0.001) and hospital (9[6–18] versus 5[3–9] days; p < 0.001) length of stay, and higher 1-year mortality (34.7% versus 20%; p = 0.008). Subphenotypes were identified on day 1 and 4 in a subgroup with available data (n = 244). 77.9% of patients remained in their baseline class throughout day 4. Patients with a hyper-inflammatory subphenotype throughout the study period (n = 22) were at higher risk of ARDS (36.4% versus 10.4%; p = 0.003). Conclusion Hyper- and non-hyper-inflammatory subphenotypes may precede ARDS development, remain identifiable over time, and can be identified upon presentation to the emergency department. A hyper-inflammatory subphenotype predicts worse outcomes.

INTRODUCTION Multiple large clinical trauma trials have documented an increased susceptibility to infection after injury. Although neutrophils (polymorphonuclear leukocytes [PMNs]) were historically considered a homogeneous cell type, we hypothesized that injury could alter neutrophil heterogeneity and predispose to dysfunction. To explore whether trauma modifies PMN heterogeneity, we performed an observational mass-spectrometry–based cytometry study on total leukocytes and low-density PMNs found in the peripheral blood mononuclear cell fraction of leukocytes from healthy controls and trauma patients. METHODS A total of 74 samples from 12 trauma patients, each sampled at 1 or more time points, and matched controls were fractionated and profiled by mass-spectrometry–based cytometry using a panel of 44 distinct markers. After deconvolution and conservative gating on neutrophils, data were analyzed using Seurat, followed by clustering of principal components. RESULTS Eleven distinct neutrophil populations were resolved in control and trauma neutrophils based on differential protein surface marker expression. Trauma markedly altered the basal heterogeneity of neutrophil subgroups seen in the control samples, with loss of a dominant population of resting neutrophils marked by high expression of C3AR and low levels of CD63, CD64, and CD177 (cluster 1), and expansion of two alternative neutrophil populations, one of which is marked by high expression of CD177 with suppression of CD10, CD16, C3AR, CD63, and CD64 (cluster 6). Remarkably, following trauma, a substantially larger percentage of neutrophils sediment in the monocyte fraction. These low-density neutrophils bear markers of functional exhaustion and form a unique trauma-induced population (cluster 9) with markedly upregulated expression of active surface adhesion molecules (activated CD11b/CD18), with suppression of nearly all other surface markers, including receptors for formyl peptides, leukotrienes, chemokines, and complement. CONCLUSION Circulating neutrophils demonstrate considerable evidence of functional heterogeneity that is markedly altered by trauma. Trauma induces evolution of a novel, exhausted, low-density neutrophil population with immunosuppressive features. Export

Introduction: Common anesthesia practice for hand surgery combines a preoperative regional anesthetic and intraoperative monitored anesthesia care (MAC). Despite adequate regional anesthesia, patients may receive doses of intraoperative sedatives which can result in oversedation and potentially avoidable complications. VR could prove to be a valuable tool for patients and providers by distracting the mind from processing noxious stimuli resulting in minimized sedative use and reduced risk of oversedation without negatively impacting patient satisfaction. Our hypothesis was that intraoperative VR use reduces sedative dosing during elective hand surgery without detracting from patient satisfaction as compared to a usual care control. Methods: Forty adults undergoing hand surgery were randomized to receive either intraoperative VR in addition to MAC, or usual MAC. Patients in both groups received preoperative regional anesthesia at provider discretion. Intraoperatively, the VR group viewed programming of their choice via a head-mounted display. The primary outcome was intraoperative propofol dose per hour (mg · hr^-1). Secondary outcomes included patient reported pain and anxiety, overall satisfaction, functional outcome, and post anesthesia care unit (PACU) length of stay (LOS). Results: Of the 40 enrolled patients, 34 completed the perioperative portion of the trial. VR group patients received significantly less propofol per hour than the control group (Mean (±SD): 125.3 (±296.0) vs 750.6 (±334.6) mg · hr^-1, p<0.001). There were no significant differences between groups in patient reported overall satisfaction, (0–100 scale, Median (IQR) 92 (77–100) vs 100 (100–100), VR vs control, p = 0.087). There were no significant differences between groups in PACU pain scores, perioperative opioid analgesic dose, or in postoperative functional outcome. PACU LOS was significantly decreased in the VR group (53.0 (43.0–72.0) vs 75.0 (57.5–89.0) min, p = 0.018). Conclusion: VR immersion during hand surgery led to significant reductions in intraoperative propofol dose and PACU LOS without negatively impacting key patient reported outcomes.