Ronaldo Sevilla Berrios

Correlation of left ventricular systolic dysfunction determined by low ejection fraction and 30-day mortality in patients with severe sepsis and septic shock: a systematic review and meta-analysis.

INTRODUCTION The prognostic implications of myocardial dysfunction in patients with sepsis and its association with mortality are controversial. Several tools have been proposed to evaluate cardiac function in these patients, but their usefulness beyond guiding therapy is unclear. We review the value of echocardiographic estimate of left ventricular ejection fraction (LVEF) in the setting of severe sepsis and/or septic shock and its correlation with 30-day mortality. METHODS We conducted a systematic review and meta-analysis to evaluate the prognostic functionality of newly diagnosed LV systolic dysfunction by transthoracic echocardiography on critical ill patients admitted to the intensive care unit with severe sepsis or septic shock. RESULTS A search of EMBASE and PubMed, Ovide MEDLINE, and Cochrane CENTRAL medical databases yielded 7 studies meeting inclusion criteria reporting on a total of 585 patients. The pooled sensitivity of depressed LVEF for mortality was 52% (95% confidence interval [CI], 29%-73%), and pooled specificity was 63% (95% CI, 53%-71%). Summary receiver operating characteristic curve showed an area under the curve of 0.62 (95% CI, 0.58-0.67). The overall mortality diagnostic odd ratio for septic patients with LV systolic dysfunction was 1.92 (95% CI, 1.27-2.899). Statistical heterogeneity of studies was moderate. CONCLUSION The presence of new LV systolic dysfunction associated with sepsis and defined as low LVEF is neither a sensitive nor a specific predictor of mortality. These findings are limited because of the heterogeneity and underpower of the studies. Further research into this method is warranted.

The Effect of an Electronic Checklist on Critical Care Provider Workload, Errors, and Performance

Purpose: The strategy used to improve effective checklist use in intensive care unit (ICU) setting is essential for checklist success. This study aimed to test the hypothesis that an electronic checklist could reduce ICU provider workload, errors, and time to checklist completion, as compared to a paper checklist. Methods: This was a simulation-based study conducted at an academic tertiary hospital. All participants completed checklists for 6 ICU patients: 3 using an electronic checklist and 3 using an identical paper checklist. In both scenarios, participants had full access to the existing electronic medical record system. The outcomes measured were workload (defined using the National Aeronautics and Space Association task load index [NASA-TLX]), the number of checklist errors, and time to checklist completion. Two independent clinician reviewers, blinded to participant results, served as the reference standard for checklist error calculation. Results: Twenty-one ICU providers participated in this study. This resulted in the generation of 63 simulated electronic checklists and 63 simulated paper checklists. The median NASA-TLX score was 39 for the electronic checklist and 50 for the paper checklist (P = .005). The median number of checklist errors for the electronic checklist was 5, while the median number of checklist errors for the paper checklist was 8 (P = .003). The time to checklist completion was not significantly different between the 2 checklist formats (P = .76). Conclusion: The electronic checklist significantly reduced provider workload and errors without any measurable difference in the amount of time required for checklist completion. This demonstrates that electronic checklists are feasible and desirable in the ICU setting.

The role of the primary care team in the rapid response system

PURPOSE The purpose of the study is to evaluate the impact of primary service involvement on rapid response team (RRT) evaluations. MATERIALS AND METHODS The study is a combination of retrospective chart review and prospective survey-based evaluation. Data included when and where the activations occurred and the patients code status, primary service, and ultimate disposition. These data were correlated with survey data from each event. A prospective survey evaluated the primary teams involvement in decision making and the overall subjective quality of the interaction with primary service through a visual analog scale. RESULTS We analyzed 4408 RRTs retrospectively and an additional 135 prospectively. The primary teams involvement by telephone or in person was associated with significantly more transfers to higher care levels in retrospective (P < .01) and prospective data sets. Code status was addressed more frequently in primary team involvement, with more frequent changes seen in the retrospective analysis (P = .01). Subjective ratings of communication by the RRT leader were significantly higher when the primary service was involved (P < .001). CONCLUSIONS Active primary team involvement influences RRT activation processes of care. The RRT role should be an adjunct to, but not a substitute for, an engaged and present primary care team.

Intensive care unit readmission prevention checklist: is it worth the effort?

RATIONALE, AIMS AND OBJECTIVES Checklists have been adopted by various institutions to improve patient outcomes. In particular, readmission prevention checklists may be of potential value to improve patient care and reduce medical costs. As a result, a prior quality improvement study was conducted to create an intensive care unit readmission prevention checklist. The previous pilot demonstrated zero readmissions when the readmission prevention checklist was utilized but yielded low compliance (30%). Thus, a subsequent quality initiative was undertaken to refine the readmission prevention checklist with the primary aim of improved compliance while maintaining a reduced readmission rate that was observed with the original quality improvement study. METHOD A single-centre, cross-sectional study for assessing baseline data and a prospective observational study to assess the effectiveness of a refined readmission prevention checklist tool in a 20-bed tertiary medical-surgical intensive care unit at an academic medical centre in Rochester, MN was conducted. Medical patients admitted through the emergency department, upon direct transfer from outside facility, and post-operative surgical patients at our institution were included. A refined readmission prevention checklist tool was administered during an 8-week pilot period for medical and post-operative surgical patients. RESULTS The refined readmission prevention checklist resulted in an even lower compliance (10.5%) from the initial phase likely resulting from utilization of a paper readmission prevention checklist in an electronic medical environment. Moreover, the refined readmission prevention checklist demonstrated a 22% unplanned readmission rate for patients in which the tool was utilized. CONCLUSIONS In conclusion, the findings of the current quality improvement study may serve to rethink the process of health care delivery that applies paper tools in an electronic medical environment.

Improving the Quality of Handoffs in Patient Care Between Critical Care Providers in the Intensive Care Unit.

With the ever-increasing adoption of shift models for intensive care unit (ICU) staffing, improving shift-to-shift handoffs represents an important step in reducing medical errors. The authors developed an electronic handoff tool integrated within the existing electronic medical record to improve handoffs in an adult ICU. First, stakeholder (staff intensivists, fellows, and nurse practitioners/physician assistants) input was sought to define what elements they perceived as being essential to a quality handoff. The principal outcome measure of handoff accuracy was the concordance between data transmitted by the outgoing team and data received by the incoming team (termed as agreement). Based on stakeholder input, the authors developed the handoff tool and provided regular education on its use. Handoffs were observed before and after implementation of the tool. There was an increase in the level of agreement for tasks and other important data points handed off without an increase in the time required to complete the handoff.

Differentiating infectious and noninfectious ventilator-associated complications: A new challenge

BACKGROUND The purpose of this study was to develop an electronic search algorithm which reliably differentiates infectious and noninfectious ventilator-associated events (VAEs). This was a retrospective cohort study used to derive a predictive model. It took place at a tertiary care hospital campus. METHODS Participants included all ventilated patients who met the Centers for Disease Control and Preventions National Health Safety Network definitions for VAEs between January 1, 2012, and December 31, 2013. There were 164 patients who experienced 185 VAEs in the study period. RESULTS The most predictive variables were fever 2 days before VAE onset, oxygenation changes, and appearance of respiratory secretions. No other variable, including laboratory tests, radiologic findings, and vital sign values, reached statistical significance. A multivariate regression model was constructed, with 68% sensitivity and 75% specificity (receiver operator characteristic area under the curve [ROC-AUC], 0.83). This was modestly better than the clinical pulmonary infection score (CPIS), which had sensitivity of 50%, specificity of 59%, and ROC-AUC of 0.60. CONCLUSIONS Although diagnosis of VAEs remains challenging, our data indicate that clinical signs and symptoms of a VAE may be present up to 2 days before they screen positive. Sputum, fever, and oxygenation requirements all were indicative, but aggregate models failed to create a sensitive and specific model for differentiation of VAEs. The existing clinical tool, the CPIS, is also insufficiently sensitive and specific. Further research is needed to create a clinically viable tool for differentiating VAE types at the bedside.

883Is the Patient the Problem? A look at baseline characteristics of patients with Infectious Ventilator Associated Events

Background. Ventilator associated events (VAEs) are associated with increased hospital length of stay, duration of ventilation, costs and mortality. VAEs exist along a continuum ranging from ventilator associated complications (VAC) to infectious ventilator associated complications (IVAC) to ventilator associated pneumonia (VAP). Because these events occur on ventilators, most research looks to environment or pathogen factors for prevention and intervention. We sought to examine host characteristics and compare patients with VAC, IVAC and VAP in terms of demographics and severity of illness. Methods. This study was performed as a retrospective chart review. Eligible patients were age >18 with a ventilator associated event as defined by Centers for Disease Control/National Health Surveillance Network definition, and research authorization on file with our institution. Case finding was done via an infection control database maintained at our institution which identifies all VAEs. VAEs were then categorized as VAC, IVAC or VAP by one of the investigators via chart review. Demographic data, including Acute Physiology and Chronic Health Evaluation (APACHE) score calculated 1 and 24 hours after intensive care unit admission abstracted using an electronic data mart maintained on all intensive care patients. Results. In the study period, 122 VAC, 31 IVAC and 14 VAP were identified. Demographic data characteristics were not significantly different between groups including age (means in years, VAP = 51.8, IVAC = 57.6, VAC = 56.3, p = 0.41), gender (% male, VAP = 64.3%, IVAC = 71.9%, VAC = 69.7%, p = 0.87), or BMI (vac = 30.4, IVAC = 31.0, VAP = 29.5). APACHE scores were similarly no different at 1 hour (VAC = 58.0, IVAC = 62.3, VAP = 56.6, p = 0.69) or 24 hours (VAC = 78.0, IVAC = 73.6, VAP = 86.0, p = 0.43). Sensitivity analyses treating variables as dichotomous (VAC vs all others) similarly showed no difference. Conclusion. Although limited by the low baseline rate of VAE at our institution and thus small sample size, these data indicate that host factors in terms of acute physiology or demographics are not major determinants of which patient will progress to VAP. Pathogen and environment factors should be focus of further efforts for VAC detection and prevention. Disclosures. All authors: No reported disclosures.

501: The Impact of the Primary Team presence during Rapid Response Team Activation

Introduction: The optimal role of the primary service in Rapid Response Team (RRT) has not been well studied. We previously evaluated the impact of primary service presence on RRT activations in a retrospective review, finding their presence to positively correlate with transfers to higher levels of