Multicenter Evaluation of the Quantra QPlus System in Adult Patients Undergoing Major Surgical Procedures.

BACKGROUND: The management of perioperative bleeding and the optimization of the available therapies are subjects of significant clinical interest. Clinical guidelines recommend the use of whole blood viscoelastic testing devices to target the utilization of blood products during major surgical procedures. The Quantra QPlus System is a new cartridge-based viscoelastic testing device based on an innovative ultrasound technology. The aim of this study was to evaluate this new system in a surgical population. METHODS: Two hundred seventy-seven adult subjects were enrolled in a multicenter, prospective observational study consisting primarily of patients undergoing cardiac and major orthopedic surgeries. Samples were obtained at multiple time points for testing on the Quantra QPlus System, the rotational thromboelastometry (ROTEM) delta, and standard coagulation tests. Quantra measurements included Clot Time (CT), Heparinase Clot Time (CTH), Clot Time Ratio (CTR), Clot Stiffness (CS), Fibrinogen (FCS), and Platelet (PCS) Contributions to CS. Data analyses included assessment of the concordance of Quantra parameters with a series of clinical composite indexes formed on the basis of standard coagulation tests in 3 domains representing increased, decreased, and normal/subclinical coagulation function. Linear regression and receiver operator characteristic (ROC) analyses of Quantra parameters with corresponding parameters from ROTEM assays were also performed. RESULTS: The accuracy (overall percent agreement or ratio of true positives and true negatives over the entire population) between the Quantra and the composite indexes was between 72% and 98% depending on the specific parameter. Linear regression analysis indicated that the correlation between ROTEM delta and Quantra was very strong with r values ranging between 0.84 and 0.89. Results from ROC analysis demonstrated sensitivities and specificities in the 80%-90% range when QPlus parameters were used to discriminate ROTEM threshold values currently used in goal-directed treatment algorithms. CONCLUSIONS: This study demonstrated that the Quantra QPlus System is strongly correlated with a well-established viscoelastic testing device and its parameters effectively represent the results from multiple standard laboratory assays. The Quantra has been designed to operate at the point of care with the potential to provide rapid and comprehensive results to aid in the management of coagulopathic patients.

Intraoperative Renal Resistive Index as an Acute Kidney Injury Biomarker: Development and Validation of an Automated Analysis Algorithm.

OBJECTIVE: Intraoperative Doppler-determined renal resistive index (RRI) is a promising early acute kidney injury (AKI) biomarker. As RRI continues to be studied, its clinical usefulness and robustness in research settings will be linked to the ease, efficiency, and precision with which it can be interpreted. Therefore, the authors assessed the usefulness of computer vision technology as an approach to developing an automated RRI-estimating algorithm with equivalent reliability and reproducibility to human experts. DESIGN: Retrospective. SETTING: Single-center, university hospital. PARTICIPANTS: Adult cardiac surgery patients from 7/1/2013 to 7/10/2014 with intraoperative transesophageal echocardiography-determined renal blood flow measurements. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: Renal Doppler waveforms were obtained retrospectively and assessed by blinded human expert raters. Images (430) were divided evenly into development and validation cohorts. An algorithm for automated RRI analysis was built using computer vision techniques and tuned for alignment with experts using bootstrap resampling in the development cohort. This algorithm then was applied to the validation cohort for an unbiased assessment of agreement with human experts. Waveform analysis time per image averaged 0.144 seconds. Agreement was excellent by intraclass correlation coefficient (0.939; 95% confidence interval [CI] 0.921 to 0.953) and in Bland-Altman analysis (mean difference [human-algorithm] -0.0015; 95% CI -0.0054 to 0.0024), without evidence of systematic bias. CONCLUSION: The authors confirmed the value of computer vision technology to develop an algorithm for RRI estimation from automatically processed intraoperative renal Doppler waveforms. This simple-to-use and efficient tool further adds to the clinical and research value of RRI, already the "earliest" among several early AKI biomarkers being assessed.

Intraoperative renal resistive index threshold as an acute kidney injury biomarker.

STUDY OBJECTIVE: The lag in creatinine-mediated diagnosis of cardiac surgery-associated acute kidney injury (AKI) may be impeding the development of renoprotection therapies. Postoperative renal resistive index (RRI) measured by transabdominal Doppler ultrasound is a promising early AKI biomarker. RRI measured intraoperatively by transesophageal echocardiography (TEE) is available even earlier but is less evaluated. Therefore, we conducted an assessment of intraoperative RRI as an AKI biomarker using previously reported post-renal insult thresholds. DESIGN: Retrospective convenience sample. SETTING: Intraoperative. PATIENTS: 180 adult cardiac surgical patients between July 2013 and July 2014. INTERVENTION: None. MEASUREMENTS: Pre- and post-cardiopulmonary bypass (CPB) RRI thresholds, measured using intraoperative TEE, exceeding 0.74 or 0.79 were used to evaluate for an association with KDIGO AKI risk using the Chi-square test. Other consensus AKI criteria (AKIN, RIFLE) were similarly evaluated. Additional t-test analyses examined the relationship of pre- and pre-to-post (delta) CPB RRI with AKI. MAIN RESULTS: Post-CPB RRI for 99 patients included 36 and 23 with values exceeding 0.74 and 0.79, respectively. Analyses confirmed associations of both RRI thresholds with all consensus AKI definitions (0.74; KDIGO: p = 0.05, AKIN: p = 0.03, RIFLE: p = 0.03, 0.79; KDIGO: p = 0.002, AKIN: p = 0.001, RIFLE: p = 0.004). In contrast, pre-CPB and pre-to post-CPB RRI were not associated with AKI. CONCLUSIONS: RRI obtained intraoperatively in cardiac surgery patients, assessed using previously reported thresholds, is highly associated with AKI and warrants further evaluation as a promising "earliest" AKI biomarker. These significant findings suggest that RRI assessment should be included in the standard intraoperative TEE exam.

The Association of Aortic Valve Pathology With Renal Resistive Index as a Kidney Injury Biomarker.

BACKGROUND: Acute kidney injury (AKI) is a common serious complication after cardiac surgery. Doppler-determined renal resistive index (RRI) is a promising early AKI biomarker in this population. However, the relationship between aortic valve pathology (insufficiency and/or stenosis) and RRI is unknown. This study aimed to investigate RRI variability related to aortic valve pathology. METHODS: In a retrospective review of cardiac surgery patients, RRI and aortic valve pathology were assessed prior to cardiopulmonary bypass using transesophageal echocardiography. Aortic valve status was categorized into four subgroups: normal (insufficiency and stenosis, none/trace/mild), insufficiency (insufficiency, moderate/severe; stenosis, none/trace/mild), combined insufficiency/stenosis (insufficiency and stenosis, moderate/severe), or stenosis (insufficiency, none/trace/mild; stenosis, moderate/severe). RRI and time-matched hemodynamic and Doppler measurements were compared among subgroups. RESULTS: Of 175 patients, 60 had aortic valve pathology (16 insufficiency, 18 insufficiency/stenosis, 26 stenosis). Compared with the normal subgroup, patients with aortic insufficiency had lower diastolic blood pressure and trough renal Doppler velocities, and higher RRI (0.77 versus 0.69; p < 0.001); patients with combined insufficiency/stenosis also had higher RRI (0.72 versus 0.69, p = 0.042). CONCLUSIONS: Patients with aortic insufficiency and combined insufficiency/stenosis had higher median RRI values compared with normal patients. For these individuals, diastolic flow differences related to aortic insufficiency may explain why their presurgery RRI values often exceeded postoperative thresholds typically associated with AKI. Strategies to account for the potentially confounding effects of aortic insufficiency on renal flow patterns, independent of renal injury, may add to the value of RRI as an early AKI biomarker.

Developing a model for effective leadership in healthcare: a concept mapping approach.

PURPOSE: Despite increasing awareness of the importance of leadership in healthcare, our understanding of the competencies of effective leadership remains limited. We used a concept mapping approach (a blend of qualitative and quantitative analysis of group processes to produce a visual composite of the group's ideas) to identify stakeholders' mental model of effective healthcare leadership, clarifying the underlying structure and importance of leadership competencies. METHODS: Literature review, focus groups, and consensus meetings were used to derive a representative set of healthcare leadership competency statements. Study participants subsequently sorted and rank-ordered these statements based on their perceived importance in contributing to effective healthcare leadership in real-world settings. Hierarchical cluster analysis of individual sortings was used to develop a coherent model of effective leadership in healthcare. RESULTS: A diverse group of 92 faculty and trainees individually rank-sorted 33 leadership competency statements. The highest rated statements were "Acting with Personal Integrity", "Communicating Effectively", "Acting with Professional Ethical Values", "Pursuing Excellence", "Building and Maintaining Relationships", and "Thinking Critically". Combining the results from hierarchical cluster analysis with our qualitative data led to a healthcare leadership model based on the core principle of Patient Centeredness and the core competencies of Integrity, Teamwork, Critical Thinking, Emotional Intelligence, and Selfless Service. CONCLUSION: Using a mixed qualitative-quantitative approach, we developed a graphical representation of a shared leadership model derived in the healthcare setting. This model may enhance learning, teaching, and patient care in this important area, as well as guide future research.