Comparison of Mechanical Power During Adaptive Support Ventilation Versus Nonautomated Pressure-Controlled Ventilation-A Pilot Study.

OBJECTIVES: The aim of this pilot study was to compare the amount of "mechanical power of ventilation" under adaptive support ventilation with nonautomated pressure-controlled ventilation. DESIGN: Single-center, observational prospective pilot study adjoining unitwide implementation of adaptive support ventilation in our department. SETTING: The ICU of a nonacademic teaching hospital in the Netherlands. PATIENTS: Twenty-four passive invasively ventilated critically ill patients expected to need of invasive ventilation beyond the following calendar day. MEASUREMENTS AND MAIN RESULTS: In patients under adaptive support ventilation, only positive end-expiratory pressure and Fio2 were set by the caregivers-all other ventilator settings were under control of the ventilator; in patients under pressure-controlled ventilation, maximum airway pressure (Pmax), positive end-expiratory pressure, Fio2, and respiratory rate were set by the caregivers. Mechanical power of ventilation was calculated three times per day. Compared with pressure-controlled ventilation, mechanical power of ventilation with adaptive support ventilation was lower (15.1 [10.5-25.7] vs 22.9 [18.7-28.8] J/min; p = 0.04). Tidal volume was not different, but Pmax (p = 0.012) and respiratory rate (p = 0.012) were lower with adaptive support ventilation. CONCLUSIONS: This study suggests adaptive support ventilation may have benefits compared with pressure-controlled ventilation with respect to the mechanical power of ventilation transferred from the ventilator to the respiratory system in passive invasively ventilated critically ill patients. The difference in mechanical power of ventilation is not a result of a difference in tidal volume, but the reduction in applied pressures and respiratory rate. The findings of this observational pilot study need to be confirmed in a larger, preferably randomized clinical trial.

Peripheral Photopenia on Whole-Body PET/CT Imaging With 18F-FDG in Patients With Compartment Syndrome and Mesenteric Venous Thrombosis.

We present 2 cases that demonstrate photopenia in peripheral areas on whole-body PET/CT imaging with F-FDG as a sign of absent perfusion with severe short-term complications. The scan of the first patient shows photopenia in the right ankle and foot, resulting from compartment syndrome, caused by hemolytic group A streptococcus bacteremia with endocarditis and septic emboli, necessitating lower leg amputation. The scan of the second patient shows photopenia in the transverse colon, resulting from mesenteric venous thrombosis caused by polycythemia vera, leading to necrosis and perforation of the transverse colon, necessitating transverse and right hemicolectomy.

Crew resource management training in the intensive care unit. A multisite controlled before-after study.

INTRODUCTION: There is a growing awareness today that adverse events in the intensive care unit (ICU) are more often caused by problems related to non-technical skills than by a lack of technical, or clinical, expertise. Team training, such as crew resource management (CRM), aims to improve these non-technical skills. The present study evaluated the effectiveness of CRM in the ICU. METHODS: Six ICUs participated in a paired controlled trial, with one pretest and two post-test measurements (after 3 and 12 months). Three ICUs received CRM training and were compared with a matched control unit. The 2-day classroom-based training was delivered to multidisciplinary groups (ie, ICU physicians, nurses, managers). All levels of Kirkpatrick's evaluation framework were assessed using a mixed method design, including questionnaires, observations and routinely administered patient outcome data. RESULTS: Level I-reaction: participants were very positive directly after the training. Level II-learning: attitudes towards behaviour aimed at optimising situational awareness were relatively high at baseline and remained stable. Level III-behaviour: self-reported behaviour aimed at optimising situational awareness improved in the intervention group. No changes were found in observed explicit professional oral communication. Level IV-organisation: patient outcomes were unaffected. Error management culture and job satisfaction improved in the intervention group. Patient safety culture improved in both control and intervention units. CONCLUSIONS: We can conclude that CRM, as delivered in the present study, does not change behaviour or patient outcomes by itself, yet changes how participants think about errors and risks. This indicates that CRM requires a combination with other initiatives in order to improve clinical outcomes.

Outcomes Associated With the Nationwide Introduction of Rapid Response Systems in The Netherlands.

OBJECTIVE: To describe the effect of implementation of a rapid response system on the composite endpoint of cardiopulmonary arrest, unplanned ICU admission, or death. DESIGN: Pragmatic prospective Dutch multicenter before-after trial, Cost and Outcomes analysis of Medical Emergency Teams trial. SETTING: Twelve hospitals participated, each including two surgical and two nonsurgical wards between April 2009 and November 2011. The Modified Early Warning Score and Situation-Background-Assessment-Recommendation instruments were implemented over 7 months. The rapid response team was then implemented during the following 17 months. The effects of implementing the rapid response team were measured in the last 5 months of this period. PATIENTS: All patients 18 years old and older admitted to the study wards were included. MEASUREMENTS AND MAIN RESULTS: In total, 166,569 patients were included in the study representing 1,031,172 hospital admission days. No differences were observed in patient demographics between periods. The composite endpoint of cardiopulmonary arrest, unplanned ICU admission, or death per 1,000 admissions was significantly reduced in the rapid response team versus the before phase (adjusted odds ratio, 0.847; 95% CI, 0.725-0.989; p = 0.036). Cardiopulmonary arrests and in-hospital mortality were also significantly reduced (odds ratio, 0.607; 95% CI, 0.393-0.937; p = 0.018 and odds ratio, 0.802; 95% CI, 0.644-1.0; p = 0.05, respectively). Unplanned ICU admissions showed a declining trend (odds ratio, 0.878; 95% CI, 0.755-1.021; p = 0.092), whereas severity of illness at the moment of ICU admission was not different between periods. CONCLUSIONS: In this study, introduction of nationwide implementation of rapid response systems was associated with a decrease in the composite endpoint of cardiopulmonary arrests, unplanned ICU admissions, and mortality in patients in general hospital wards. These findings support the implementation of rapid response systems in hospitals to reduce severe adverse events.

A controlled trial of electronic automated advisory vital signs monitoring in general hospital wards.

OBJECTIVES: Deteriorating ward patients are at increased risk. Electronic automated advisory vital signs monitors may help identify such patients and improve their outcomes. SETTING: A total of 349 beds, in 12 general wards in ten hospitals in the United States, Europe, and Australia. PATIENTS: Cohort of 18,305 patients. DESIGN: Before-and-after controlled trial. INTERVENTION: We deployed electronic automated advisory vital signs monitors to assist in the acquisition of vital signs and calculation of early warning scores. We assessed their effect on frequency, type, and treatment of rapid response team calls; survival to hospital discharge or to 90 days for rapid response team call patients; overall type and number of serious adverse events and length of hospital stay. MEASUREMENTS AND MAIN RESULTS: We studied 9,617 patients before (control) and 8,688 after (intervention) deployment of electronic automated advisory vital signs monitors. Among rapid response team call patients, intervention was associated with an increased proportion of calls secondary to abnormal respiratory vital signs (from 21% to 31%; difference [95% confidence interval] 9.9 [0.1-18.5]; p=.029). Survival immediately after rapid response team treatment and survival to hospital discharge or 90 days increased from 86% to 92% (difference [95% confidence interval] 6.3 [0.0-12.6]; p=.04). Intervention was also associated with a decrease in median length of hospital stay in all patients (unadjusted p<.0001; adjusted p=.09) and more so in U.S. patients (from 3.4 to 3.0 days; unadjusted p<.0001; adjusted ratio [95% confidence interval] 1.03 [1.00-1.06]; p=.026). The time required to complete and record a set of vital signs decreased from 4.1±1.3 mins to 2.5±0.5 mins (difference [95% confidence interval] 1.6 [1.4-1.8]; p<.0001). CONCLUSIONS: Deployment of electronic automated advisory vital signs monitors was associated with an improvement in the proportion of rapid response team-calls triggered by respiratory criteria, increased survival of patients receiving rapid response team calls, and decreased time required for vital signs measurement and recording (NCT01197326).

[Rapid response system in derangement of vital signs: five years experience in a large general hospital]. / Spoedinterventiesysteem bij vitale bedreiging: 5 jaar ervaring in een groot algemeen ziekenhuis.

OBJECTIVE: Hospitalized patients are at risk for adverse events such as unexpected cardiac arrest or admission to an Intensive Care Unit (ICU). Prior to these adverse events these patients often have derangements in vital signs that are not recognized and treated adequately. To identify and treat those patients at risk, our hospital implemented a rapid response system in 2004. The purpose of this paper is to describe implementation and results of our rapid response system. DESIGN: Prospective cohort study. METHOD: The implementation of the rapid response system started by training all doctors and nurses to score vital signs using a dedicated score card. If a patient scores 3 or more points, the patients' treating physician has to see the patient and - if necessary - call the medical emergency team (MET), consisting of an ICU physician and an ICU nurse. We analyzed all consecutive MET calls in the period January 2005-December 2009. RESULTS: A total of 1058 MET calls for 981 patients were analyzed. In 606 patients (57.3%) it was decided to transfer the patient to a higher dependency unit, in most cases the ICU. In 353 patients (33.4%) treatment could be continued on the ward. In 88 patients (8.4%) it was decided that ICU treatment would not be beneficial and limits on treatment were put in place. Of the 981 patients, 255 (26.0%) died in hospital. CONCLUSION: In our hospital the rapid response system has developed into an important tool for the early identification and treatment of patients at risk. However, our data cannot prove the efficacy of the rapid response system in terms of reducing hospital mortality.

Accuracy of AccuChek glucose measurement in intensive care patients.

OBJECTIVE: To evaluate the accuracy of the AccuChek Inform point-of-care glucose measurement device as compared with central laboratory glucose measurement. DESIGN: Prospective, observational study. SETTING: A ten-bed mixed closed format intensive care unit ina 500-bed general hospital. The unit has a computerized insulin protocol aiming for 81 to 135 mg/dL. PATIENTS: All intensive care unit patients were eligible. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: Paired samples (AccuChek glucose in whole blood calibrated to give whole blood results and central laboratory glucose in serum) were taken simultaneously. In 32 critically ill patients, we obtained the following information: mean +/- standard deviation age 71.6 +/- 11.9 yrs; mean Acute Physiology and Chronic Health Evaluation II score at admission 17.8 +/- 6.7; 239 paired samples were taken from arterial catheters. Mean AccuChek whole blood glucose was 126 +/- 36 mg/dL (7.0 +/- 2.0 mmol/L); mean central laboratory serum glucose was 137 +/- 38 mg/dL (7.6 +/- 2.1 mmol/L). Mean difference was 11 mg/dL (0.61 mmol/L) (8%) (95% Confidence Interval 9-13 mg/dL, p < .001). ISO 15197 guideline requires 95% of point-of-care measurements to be within 15 mg/dL margins with reference <75 mg/dL or within 20% if reference is higher. In total, 216 (90.4%) of AccuChek measurements were within ISO 15197 margins. Because AccuChek was calibrated to give whole blood results, we calculated a correction factor of 1.086 from the two mean values to correct whole blood AccuChek into serum-like results. This is almost the same as the correction factor of 1.080 given by Roche Diagnostics. By multiplying AccuChek whole blood results with 1.086, 225 (94.1%) of results were within the ISO 15197 margins. Hematocrit did not influence AccuChek results in the 0.20 to 0.44 range. Beyond this range, there were not enough data to draw conclusions. CONCLUSIONS: In critically ill patients, the accuracy of AccuChek glucose measurement calibrated to give serum-like results with blood samples derived from arterial catheters is acceptable but falls short by about 1% of complying with the ISO 15197 guideline.

Introduction and evaluation of a computerised insulin protocol.

OBJECTIVE: To lower glucose levels in all patients in the intensive care unit (ICU) to the target range of 4.5-7.5 mmol/l using a nurse-driven computerised insulin protocol in combination with bedside glucose measurement. DESIGN: Cohort study. SETTING: Mixed adult ICU. PATIENTS AND PARTICIPANTS: All 182 patients admitted to the ICU during a 3-month period were studied, except for 3 patients admitted for diabetic keto-acidosis. INTERVENTIONS: Five steps were taken to improve glucose regulation: (1) Nurses were authorised to adjust insulin dosage using a protocol. (2) Glucose was measured more often. (3) Glucose was measured at the bedside. (4) Consecutive protocols aimed for successively lower glucose levels; the final protocol had a target range of 4.5-7.5 mmol/l. (5) The protocol was computerised. MEASUREMENTS AND RESULT: Mean glucose decreased from 9.23 mmol/l without protocol to 7.68 mmol/l with the final protocol. This final protocol with the target of 4.5-7.5 mmol/l was evaluated more extensively. Glucose levels were measured a total of 1854 times in 179 ICU admissions during 552 ICU treatment days. The median glucose level was 7.0 mmol/l, and 53.1% of glucose measurements were within the target range of 4.5-7.5 mmol/l. One episode of hypoglycaemia (glucose