Burnout, resilience and work engagement among Dutch intensivists in the aftermath of the COVID-19 crisis: A nationwide survey.

PURPOSE: The COVID-19 crisis put a strain on intensive care resources everywhere in the world increasing the risk of burnout. Previously, the prevalence of burnout among Dutch intensivists was found to be low. Engagement and resilience among intensivists have not previously been studied quantitatively, however, both are related to burnout and provide a possible way to mitigate burnout. Our objective was to study burnout and its association with work engagement and resilience among Dutch intensivists in the aftermath of the COVID-19 crisis. METHODS: An online questionnaire was sent to all Dutch intensivists. The questionnaire consisted of questions on personal and work-related characteristics and validated questionnaires: the Maslach Burnout Inventory, the Utrecht Work Engagement Scale, and the Resilience Evaluation Scale. RESULTS: The response rate was 27.2% with 162 evaluable responses. Thirteen respondents (8.0%) were classified as having burnout, 63 (38.9%) respondents were reporting high work engagement. Burnout was found to be negatively associated with both work engagement and resilience. CONCLUSION: In the aftermath of the 2020 COVID-19 crisis, we found a raised prevalence of burnout among intensivists, however this is still low in international comparisons. Intensivists with burnout scored low on resilience and low on work engagement.

[Learning from incidents in healthcare: the value of incident investigation and improvement measures]. / Leren van incidenten in de zorg.

Incidents in healthcare are often followed by an investigation to find out what happened and how it was possible for them to happen. It is often difficult to find good answers to these questions, partly because it is usually not possible for complex reality to be described in simple cause-and-effect reconstructions. Another objective of incident investigations is the prevention of incident reoccurrence. In this respect, answers are not simple either, as it is difficult to think of improvement measures that are both effective and easy to implement. As a result, incident reporting and investigation do not automatically lead to prevention of incident reoccurrence. It is, however, possible to recommend some measures that lead to better investigations and effective improvement measures after incidents.

Effect of off-hour staffing in Chinese ICUs.

Analysis of Chinese ICU staffing in relation to final outcome yields comparable results as those reported in Western ICUs. This underlines the general principle that we would all like to apply in our hospitals; that is, availability of knowledgeable staff that are adequately trained to recognize and treat an acutely deteriorating critically ill patient as soon as possible.

Outcomes of cancer patients after unplanned admission to general intensive care units.

BACKGROUND: Acute admission to an intensive care unit (ICU) of cancer patients is considered with increasing frequency due to a better life expectancy and more aggressive therapies. The aim of this study was to determine the characteristics and outcomes of cancer patients with unplanned admissions to general ICUs, and to compare these with outcomes of critically ill patients without cancer. MATERIAL AND METHODS: All unplanned ICU admissions in the Netherlands collected in the National Intensive Care Evaluation registry between January 2007 and January 2011 were analyzed. RESULTS AND CONCLUSION: Of the 140,154 patients with unplanned ICU admission 10.9% had a malignancy. Medical cancer patients were more severely ill on ICU admission in comparison with medical non-cancer patients, as reflected by higher needs for mechanical ventilation (50.8% vs. 46.4%, p < 0.001) and vasopressors within 24 hours after admission (41.5% vs. 33.0%, p < 0.001), higher Acute Physiology and Chronic Health Evaluation (APACHE) IV scores (88.1 vs. 67.5, p < 0.001) and a longer ICU stay (5.1 vs. 4.6 days, p < 0.001). In contrast, surgical cancer patients only displayed a modestly higher APACHE IV score on admission when compared with non-cancer surgical patients, whereas the other afore mentioned parameters were lower in the surgical cancer patients group. In-hospital mortality was almost twice as high in medical cancer patients (40.6%) as in medical patients without cancer (23.7%). In-hospital mortality of surgical cancer patients (17.4%) was slightly higher than in patients without cancer (14.6%). These data indicate that unplanned ICU admission is associated with a high mortality in patients with cancer when admitted for medical reasons.

Blood glucose amplitude variability as predictor for mortality in surgical and medical intensive care unit patients: a multicenter cohort study.

PURPOSE: The aim of this study was to test the hypothesis that blood glucose amplitude variability (BGAV) is associated with mortality in critically ill patients. METHOD: A prospectively collected multicenter data set including all glucose measurements during intensive care unit (ICU) treatment and outcome was analyzed. We used logistic regression to assess the association between hospital mortality and standard deviation (SD), mean amplitude of glycemic excursions (MAGE), mean absolute glucose change per hour (MAG), and glycemic lability index (GLI). The analysis was adjusted for ICU, Acute Physiology And Chronic Health Evaluation IV-expected mortality, the presence of severe hypoglycemia, mean glucose, mean glucose measurement interval, and interaction between the latter 2. RESULTS: There were 855,032 glucose measurements included of 20,375 patients admitted to 37 Dutch ICUs in 2008 and 2009. Median Acute Physiology And Chronic Health Evaluation IV-predicted mortality was 14%, and median glucose was 7.3 mmol/L. In all patients combined, adjusted hospital mortality was associated with SD and MAGE, but not with MAG and GLI. In surgical patients, adjusted hospital mortality was associated with SD, MAGE, and MAG, but not GLI. In medical patients, adjusted mortality was associated with SD but not with other BGAV measures. CONCLUSION: Not all BGAV measures were associated with mortality. Blood glucose amplitude variability as quantified by SD was consistently independently associated with hospital mortality.

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.

[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.

Hospital mortality is associated with ICU admission time.

INTRODUCTION: 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. METHODS: 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. RESULTS: 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. CONCLUSIONS: 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 difference.

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.

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.

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

Serum neuron-specific enolase predicts outcome in post-anoxic coma: a prospective cohort study.

OBJECTIVE: The aim of this study was to investigate whether serial serum neuron-specific enolase (NSE) can be used to predict neurological prognosis in patients remaining comatose after cardiopulmonary resuscitation (CPR). DESIGN. Observational cohort study. Clinicians were blinded to NSE results. SETTING: Eighteen-bed general ICU. PATIENTS: Comatose patients admitted to the ICU after CPR. INTERVENTIONS: Serum NSE was measured at admission and daily for 5 days. MEASUREMENTS AND RESULTS: Patients received full intensive treatment until recovery or until absence of cortical response to somatosensory evoked potentials more than 48 h after CPR proved irreversible coma. Of the 110 patients included (mean GCS at ICU admission 3, range 3--9), 34 regained consciousness, five of whom died in hospital. Seventy-six patients did not regain consciousness, 72 of whom died in hospital. Serum NSE at 24 h and at 48 h after CPR was significantly higher in patients who did not regain consciousness than in patients who regained consciousness (at 24 h: median NSE 29.9 microg/l, range 1.8-250 vs 9.9 microg/l, range 4.5-21.5, P<0.001; at 48 h: median 37.8 microg/l, range 4.4-411 vs 9.5 microg/l, range 6.2-22.4, P= 0.001). No patient with a serum NSE level >25.0 microg/l at any time regained consciousness. Addition of NSE to GCS and somatosensory evoked potentials increased predictability of poor neurological outcome from 64% to 76%. CONCLUSIONS: High serum NSE levels in comatose patients at 24 h and 48 h after CPR predict a poor neurological outcome. Addition of NSE to GCS and somatosensory evoked potentials increases predictability of neurological outcome.