Improving Decision Making in Intensive Care

Many decisions are made during a day’s work in critical care. Should this octogenarian with pneumonia and cancer be admitted to the ICU or left on the ward with palliative care? And if admitted to the ICU, will she benefit from being ventilated or should she only be treated with antibiotics and inotropes? How long should we continue administrating antibiotics in a patient with peritonitis due to anastomotic leakage after low anterior resection? Will antibiotics do the job or does he have to go back to the operating theatre? Should we give more fluids in a patient with shock, should we start vasoconstrictors or vasodilators or should we accept this low blood pressure? Continue treatment with a curative intent or accept the inevitable? Act on a laboratory result or stop ‘just treating the numbers’

In Critically Ill Patients, Serum Procalcitonin Is More Useful in Differentiating between Sepsis and SIRS than CRP, Il-6, or LBP

We studied the usefulness of serum procalcitonin (PCT), interleukin-6 (IL-6), lipopolysaccharide binding protein (LBP) levels and C-reactive protein (CRP) levels, in differentiating between systemic inflammatory response syndrome (SIRS) and sepsis in critically ill patients. Methods. In this single centre prospective observational study we included all consecutive patients admitted with SIRS or sepsis to the ICU. Blood samples for measuring CRP, PCT, IL-6 and LBP were taken every day until ICU discharge. Results. A total of 76 patients were included, 32 with sepsis and 44 with SIRS. Patients with sepsis were sicker on admission and had a higher mortality. CRP, PCT, IL-6 and LBP levels were significantly higher in patients with sepsis as compared to SIRS. With PCT levels in the first 24 hours after ICU admission <2 ng/mL, sepsis was virtually excluded (negative predictive value 97%). With PCT >10 ng/mL, sepsis with bacterial infection was very likely (positive predictive value 88%). PCT was best at discriminating between SIRS and sepsis with the highest area under the ROC curve (0.95, 95% CI 0.90–0.99). Discussion. This study showed that PCT is more useful than LBP, CRP and IL-6 in differentiating sepsis from SIRS

Wie verlässlich ist die Bestimmung von Procalcitonin als Entzündungsmarker auf Intensivstation?

The role of procalcitonin (PCT) plasma levels as a diagnostic tool for intensive care patients has been intensively investigated during the past years. In particular for recognition of bacterial infections, PCT levels have been shown to be superior to other clinical and biochemical markers. Furthermore, some very recent studies show that in patients with lower respiratory tract infections PCT guided antibiotic therapy reduces antibiotic use and thereby may also reduce duration of stay of patients in hospital and thus cut hospitalisation costs. However, various studies indicate that the value of PCT as a prognostic marker is limited because of false positive or negative values. Despite these limitations PCT plasma levels are currently measured in intensive care units. The present study summarises the possible clinical uses of this lab marker as a diagnostic tool for the assessment of critically of ill patients

Off hour admission to an intensivist-led ICU is not associated with increased mortality

Introduction: Caring for the critically ill is a 24-hour-a-day responsibility, but not all resources and staff are available during off hours. We evaluated whether intensive care unit (ICU) admission during off hours affects hospital mortality. Methods: This retrospective multicentre cohort study was carried out in three non-academic teaching hospitals in the Netherlands. All consecutive patients admitted to the three ICUs between 2004 and 2007 were included in the study, except for patients who did not fulfil APACHE II criteria (readmissions, burns, cardiac surgery, younger than 16 years, length of stay less than 8 hours). Data were collected prospectively in the ICU databases. Hospital mortality was the primary endpoint of the study. Off hours was defined as the interval between 10 pm and 8 am during weekdays and between 6 pm and 9 am during weekends. Intensivists, with no responsibilities outside the ICU, were present in the ICU during daytime and available for either consultation or assistance on site during off hours. Residents were available 24 hours a day 7 days a week in two and fellows in one of the ICUs. Results: A total of 6725 patients were included in the study, 4553 (67.7%) admitted during daytime and 2172 (32.3%) admitted during off hours. Baseline characteristics of patients admitted during daytime were significantly different from those of patients admitted during off hours. Hospital mortality was 767 (16.8%) in patients admitted during daytime and 469 (21.6%) in patients admitted during off hours (P < 0.001, unadjusted odds ratio 1.36, 95%CI 1.20-1.55). Standardized mortality ratios were similar for patients admitted during off hours and patients admitted during daytime. In a logistic regression model APACHE II expected mortality, age and admission type were all significant confounders but off-hours admission was not significantly associated with a higher mortality (P = 0.121, adjusted odds ratio 1.125, 95%CI 0.969-1.306). Conclusions: The increased mortality after ICU admission during off hours is explained by a higher illness severity in patients admitted during off hours

Hospital mortality is associated with ICU admission time

Previous studies have shown that patients admitted to the intensive care unit (ICU) after "office hours" are more likely to die. However these results have been challenged by numerous other studies. We therefore analysed this possible relationship between ICU admission time and in-hospital mortality in The Netherlands. This article relates time of ICU admission to hospital mortality for all patients who were included in the Dutch national ICU registry (National Intensive Care Evaluation, NICE) from 2002 to 2008. We defined office hours as 08:00-22:00 hours during weekdays and 09:00-18:00 hours during weekend days. The weekend was defined as from Saturday 00:00 hours until Sunday 24:00 hours. We corrected hospital mortality for illness severity at admission using Acute Physiology and Chronic Health Evaluation II (APACHE II) score, reason for admission, admission type, age and gender. A total of 149,894 patients were included in this analysis. The relative risk (RR) for mortality outside office hours was 1.059 (1.031-1.088). Mortality varied with time but was consistently higher than expected during "off hours" and lower during office hours. There was no significant difference in mortality between different weekdays of Monday to Thursday, but mortality increased slightly on Friday (RR 1.046; 1.001-1.092). During the weekend the RR was 1.103 (1.071-1.136) in comparison with the rest of the week. Hospital mortality in The Netherlands appears to be increased outside office hours and during the weekends, even when corrected for illness severity at admission. However, incomplete adjustment for certain confounders might still play an important role. Further research is needed to fully explain this differenc

Time of Day and its Association with Risk of Death and Chance of Discharge in Critically Ill Patients: A Retrospective Study.

Outcomes following admission to intensive care units (ICU) may vary with time and day. This study investigated associations between time of day and risk of ICU mortality and chance of ICU discharge in acute ICU admissions. Adult patients (age ≥ 18 years) who were admitted to ICUs participating in the Austrian intensive care database due to medical or surgical urgencies and emergencies between January 2012 and December 2016 were included in this retrospective study. Readmissions were excluded. Statistical analysis was conducted using the Fine-and-Gray proportional subdistribution hazards model concerning ICU mortality and ICU discharge within 30 days adjusted for SAPS 3 score. 110,628 admissions were analysed. ICU admission during late night and early morning was associated with increased hazards for ICU mortality; HR: 1.17; 95% CI: 1.08-1.28 for 00:00-03:59, HR: 1.16; 95% CI: 1.05-1.29 for 04:00-07:59. Risk of death in the ICU decreased over the day; lowest HR: 0.475, 95% CI: 0.432-0.522 for 00:00-03:59. Hazards for discharge from the ICU dropped sharply after 16:00; lowest HR: 0.024; 95% CI: 0.019-0.029 for 00:00-03:59. We conclude that there are "time effects" in ICUs. These findings may spark further quality improvement efforts

Evaluation of an open access software for calculating glucose variability parameters of a continuous glucose monitoring system applied at pediatric intensive care unit.

BACKGROUND: Continuous Glucose Monitoring (CGM) has become an increasingly investigated tool, especially with regards to monitoring of diabetic and critical care patients. The continuous glucose data allows the calculation of several glucose variability parameters, however, without specific application the interpretation of the results is time-consuming, utilizing extreme efforts. Our aim was to create an open access software [Glycemic Variability Analyzer Program (GVAP)], readily available to calculate the most common parameters of the glucose variability and to test its usability. METHODS: The GVAP was developed in MATLAB(R) 2010b environment. The calculated parameters were the following: average area above/below the target range (Avg. AUC-H/L); Percentage Spent Above/Below the Target Range (PATR/PBTR); Continuous Overall Net Glycemic Action (CONGA); Mean of Daily Differences (MODD); Mean Amplitude of Glycemic Excursions (MAGE). For verification purposes we selected 14 CGM curves of pediatric critical care patients. Medtronic(R) Guardian(R) Real-Time with Enlite(R) sensor was used. The reference values were obtained from Medtronic(R)'s own software for Avg. AUC-H/L and PATR/PBTR, from GlyCulator for MODD and CONGA, and using manual calculation for MAGE. RESULTS: The Pearson and Spearman correlation coefficients were above 0.99 for all parameters. The initial execution took 30 minutes, for further analysis with the Windows(R) Standalone Application approximately 1 minute was needed. CONCLUSIONS: The GVAP is a reliable open access program for analyzing different glycemic variability parameters, hence it could be a useful tool for the study of glycemic control among critically ill patients