Association Between an Increase in Serum Sodium and In-Hospital Mortality in Critically Ill Patients.

OBJECTIVES: In critically ill patients, dysnatremia is common, and in these patients, in-hospital mortality is higher. It remains unknown whether changes of serum sodium after ICU admission affect mortality, especially whether normalization of mild hyponatremia improves survival. DESIGN: Retrospective cohort study. SETTING: Ten Dutch ICUs between January 2011 and April 2017. PATIENTS: Adult patients were included if at least one serum sodium measurement within 24 hours of ICU admission and at least one serum sodium measurement 24-48 hours after ICU admission were available. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: A logistic regression model adjusted for age, sex, and Acute Physiology and Chronic Health Evaluation-IV-predicted mortality was used to assess the difference between mean of sodium measurements 24-48 hours after ICU admission and first serum sodium measurement at ICU admission (Δ48 hr-[Na]) and in-hospital mortality. In total, 36,660 patients were included for analysis. An increase in serum sodium was independently associated with a higher risk of in-hospital mortality in patients admitted with normonatremia (Δ48 hr-[Na] 5-10 mmol/L odds ratio: 1.61 [1.44-1.79], Δ48 hr-[Na] > 10 mmol/L odds ratio: 4.10 [3.20-5.24]) and hypernatremia (Δ48 hr-[Na] 5-10 mmol/L odds ratio: 1.47 [1.02-2.14], Δ48 hr-[Na] > 10 mmol/L odds ratio: 8.46 [3.31-21.64]). In patients admitted with mild hyponatremia and Δ48 hr-[Na] greater than 5 mmol/L, no significant difference in hospital mortality was found (odds ratio, 1.11 [0.99-1.25]). CONCLUSIONS: An increase in serum sodium in the first 48 hours of ICU admission was associated with higher in-hospital mortality in patients admitted with normonatremia and in patients admitted with hypernatremia.

Pain Measurement in Mechanically Ventilated Patients After Cardiac Surgery: Comparison of the Behavioral Pain Scale (BPS) and the Critical-Care Pain Observation Tool (CPOT).

OBJECTIVES: The Behavioral Pain Scale (BPS) and Critical-Care Pain Observation Tool (CPOT) are behavioral pain assessment tools for sedated and unconscious critically ill patients. The aim of this study was to compare the reliability, internal consistency, and discriminant validation of the BPS and the CPOT simultaneously in mechanically ventilated patients after cardiac surgery. DESIGN: A prospective, observational cohort study. SETTING: A 20-bed closed-format intensive care unit with mixed medical, surgical, and cardiac surgery patients in a teaching hospital in Amsterdam, The Netherlands. PARTICIPANTS: The study comprised 72 consecutive intubated and mechanically ventilated patients after cardiac surgery who were not able to self-report pain. MEASUREMENTS AND MAIN RESULTS: Two nurses assessed the BPS and CPOT simultaneously and independently at the following 4 moments: rest, a nonpainful procedure (oral care), rest, and a painful procedure (turning). Both scores showed a significant increase of 2 points between rest and turning. The median BPS score of nurse 1 showed a significant increase of 1 point between rest and the nonpainful procedure (oral care), whereas both median CPOT scores did not change. The interrater reliability of the BPS and CPOT showed fair-to-good agreement of 0.74 overall. During the periods of rest 1 and rest 2, values ranged from 0.24 to 0.46. Cronbach's alpha values for the BPS were 0.62 (nurse 1) and 0.59 (nurse 2) compared with 0.65 and 0.58, respectively, for the CPOT. CONCLUSIONS: The BPS and CPOT are reliable and valid pain assessment tools in a daily clinical setting. However, the discriminant validation of both scores seems less satisfactory in sedated or agitated patients and this topic requires further investigation.

Effectiveness and Clinical Outcomes of a Two-Step Implementation of Conservative Oxygenation Targets in Critically Ill Patients: A Before and After Trial.

OBJECTIVES: Conservative oxygen therapy is aimed at the prevention of harm by iatrogenic hyperoxia while preserving adequate tissue oxygenation. Our aim was to study the effectiveness and clinical outcomes of a two-step implementation of conservative oxygenation targets in the ICU. DESIGN: This was a before and after stepwise implementation study of conservative oxygenation targets, between July 2011 and July 2014. The primary endpoint was the proportion of PaO2 values within the target range. Secondary outcomes included ventilator-free days at day 28, length of stay, and mortality. SETTING: Three closed-format ICUs in the Netherlands. PATIENTS: We analyzed data on 15,045 eligible admissions. INTERVENTIONS: The first implementation phase consisted of providing training and feedback on new guidelines instructing for explicit targets for arterial oxygen tension (PaO2, 55-86 mm Hg) and oxyhemoglobin saturation (SpO2, 92-95%). In the second phase, bedside clinicians were additionally assisted in guideline adherence by a computerized decision-support system. MEASUREMENTS AND MAIN RESULTS: The proportion of PaO2 in the target range increased from 47% at baseline to 63% in phase 1 and to 68% in phase 2 (p < 0.0001). Episodes of hyperoxia decreased (p < 0.0001), whereas hypoxic episodes remained unchanged (p = 0.06) during the study. Mechanical ventilation time was significantly lower (p < 0.01) during both study phases. After adjustment for potential confounders, ventilator-free days in phase 1 and phase 2 were higher than baseline: adjusted mean difference, 0.55 (95% CI, 0.25-0.84) and 0.48 (95% CI, 0.11-0.86), respectively. Adjusted ICU mortality and ICU-free days did not significantly differ between study phases. Hospital mortality decreased in reference to baseline: adjusted odds ratio, 0.84 (95% CI, 0.74-0.96) for phase 1 and 0.82 (95% CI, 0.69-0.96) for phase 2. CONCLUSIONS: Stepwise implementation of conservative oxygenation targets was feasible, effective, and seemed safe in critically ill patients. The implementation was associated with several changes in clinical outcomes, but the causal impact of conservative oxygenation is still to be determined.

The effect of diabetes mellitus on the association between measures of glycaemic control and ICU mortality: a retrospective cohort study.

INTRODUCTION: In critical illness, four measures of glycaemic control are associated with ICU mortality: mean glucose concentration, glucose variability, the incidence of hypoglycaemia (≤2.2 mmol/l) or low glucose (2.3 to 4.7 mmol/l). Underlying diabetes mellitus (DM) might affect these associations. Our objective was to study whether the association between these measures of glycaemic control and ICU mortality differs between patients without and with DM and to explore the cutoff value for detrimental low glucose in both cohorts. METHODS: This retrospective database cohort study included patients admitted between January 2004 and June 2011 to a 24-bed medical/surgical ICU in a teaching hospital. We analysed glucose and outcome data from 10,320 patients: 8,682 without DM and 1,638 with DM. The cohorts were subdivided into quintiles of mean glucose and quartiles of glucose variability. Multivariable regression models were used to examine the independent association between the four measures of glycaemic control and ICU mortality, and for defining the cutoff value for detrimental low glucose. RESULTS: Regarding mean glucose, a U-shaped relation was observed in the non-DM cohort with an increased ICU mortality in the lowest and highest glucose quintiles (odds ratio=1.4 and 1.8, P<0.001). No clear pattern was found in the DM cohort. Glucose variability was related to ICU mortality only in the non-DM cohort, with highest ICU mortality in the upper variability quartile (odds ratio=1.7, P<0.001). Hypoglycaemia was associated with ICU mortality in both cohorts (odds ratio non-DM=2.5, P<0.001; odds ratio DM=4.2, P=0.001), while low-glucose concentrations up to 4.9 mmol/l were associated with an increased risk of ICU mortality in the non-DM cohort and up to 3.5 mmol/l in the DM cohort. CONCLUSION: Mean glucose and high glucose variability are related to ICU mortality in the non-DM cohort but not in the DM cohort. Hypoglycaemia (≤2.2 mmol/l) was associated with ICU mortality in both. The cutoff value for detrimental low glucose is higher in the non-DM cohort (4.9 mmol/l) than in the DM cohort (3.5 mmol/l). While hypoglycaemia (≤2.2 mmol/l) should be avoided in both groups, DM patients seem to tolerate a wider glucose range than non-DM patients.

Presence of tobramycin in blood and urine during selective decontamination of the digestive tract in critically ill patients, a prospective cohort study.

INTRODUCTION: Tobramycin is one of the components used for selective decontamination of the digestive tract (SDD), applied to prevent colonization and subsequent infections in critically ill patients. Tobramycin is administered in the oropharynx and gastrointestinal tract and is normally not absorbed. However, critical illness may convey gut barrier failure. The aim of the study was to assess the prevalence and amount of tobramycin leakage from the gut into the blood, to quantify tobramycin excretion in urine, and to determine the association of tobramycin leakage with markers of circulation, kidney function and other organ failure. METHODS: This was a prospective observational cohort study. The setting was the 20-bed closed format-mixed ICU of a teaching hospital. The study population was critically ill patients with an expected stay of more than two days, receiving SDD with tobramycin, polymyxin-E and amphotericin-B four times daily in the oropharynx and stomach. Tobramycin concentration was measured in serum (sensitive high performance liquid chromatography - mass spectrometry/mass spectrometry (HLPC-MS/MS) assay) and 24-hour urine (conventional immunoassay), in 34 patients, 24 hours after ICU admission, and in 71 patients, once daily for 7 days. Tobramycin leakage was defined as tobramycin detected in serum at least once (> 0.05 mg/L). Ototoxicity was not monitored. RESULTS: Of the 100 patients with available blood samples, 83 had tobramycin leakage. Median highest serum concentration for each patient was 0.12 mg/L; 99% of the patients had at least one positive urinary sample (> 0.5 mg/L), 49% had a urinary concentration ≥ 1 mg/L. The highest tobramycin serum concentration was significantly associated with vasopressor support, renal and hepatic dysfunction, and C-reactive protein. At binary logistic regression analysis, high dopamine dose and low urinary output on Day 1 were the significant predictors of tobramycin leakage. Nephrotoxicity could not be shown. CONCLUSIONS: The majority of acute critically ill patients treated with enteral tobramycin as a component of SDD had traces of tobramycin in the blood, especially those with severe shock, inflammation and subsequent acute kidney injury, suggesting loss of gut barrier and decreased renal removal. Unexpectedly, urinary tobramycin was above the therapeutic trough level in half of the patients. Nephrotoxicity could not be demonstrated.

Glucose variability is associated with intensive care unit mortality.

OBJECTIVE: Mounting evidence suggests a role for glucose variability in predicting intensive care unit (ICU) mortality. We investigated the association between glucose variability and intensive care unit and in-hospital deaths across several ranges of mean glucose. DESIGN: Retrospective cohort study. SETTING: An 18-bed medical/surgical ICU in a teaching hospital. PATIENTS: All patients admitted to the ICU from January 2004 through December 2007. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: Two measures of variability, mean absolute glucose change per hour and sd, were calculated as measures of glucose variability from 5728 patients and were related to ICU and in-hospital death using logistic regression analysis. Mortality rates and adjusted odds ratios for ICU death per mean absolute glucose change per hour quartile across quartiles of mean glucose were calculated. Patients were treated with a computerized insulin algorithm (target glucose 72-126 mg/dL). Mean age was 65 +/- 13 yrs, 34% were female, and 6.3% of patients died in the ICU. The odds ratios for ICU death were higher for quartiles of mean absolute glucose change per hour compared with quartiles of mean glucose or sd. The highest odds ratio for ICU death was found in patients with the highest mean absolute glucose change per hour in the upper glucose quartile: odds ratio 12.4 (95% confidence interval, 3.2-47.9; p < .001). Mortality rates were lowest in the lowest mean absolute glucose change per hour quartiles. CONCLUSIONS: High glucose variability is firmly associated with ICU and in-hospital death. High glucose variability combined with high mean glucose values is associated with highest ICU mortality. In patients treated with strict glycemic control, low glucose variability seemed protective, even when mean glucose levels remained elevated.

Hypoglycemia is associated with intensive care unit mortality.

OBJECTIVE: The implementation of intensive insulin therapy in the intensive care unit is accompanied by an increase in hypoglycemia. We studied the relation between hypoglycemia on intensive care unit mortality, because the evidence on this subject is conflicting. DESIGN: Retrospective database cohort study. SETTING: An 18-bed medical/surgical intensive care unit in a teaching hospital (Onze Lieve Vrouwe Gasthuis Hospital, Amsterdam, The Netherlands). PATIENTS: A total of 5961 patients admitted to from 2004 to 2007 were analyzed. Readmissions and patients with a withholding care policy or with hypoglycemia on the first glucose measurement were excluded. Patients were treated with a computerized insulin algorithm (target glucose range, 72-126 mg/dL). INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: All first episodes of hypoglycemia (glucose < or =45 mg/dL) were derived from 154,015 glucose values. Using Poisson regression, the incidence rates for intensive care unit death and incidence rate ratio comparing exposure and nonexposure to hypoglycemia were calculated. Patients were considered to be exposed to hypoglycemia from the event until the end of intensive care unit admittance. We corrected for severity of disease using the daily Sequential Organ Failure Assessment score. Age, sex, cardiothoracic surgery, sepsis, and diabetes mellitus were also included as possible confounders. Two hundred eighty-eight (4.8%) patients experienced at least one episode of hypoglycemia. Median age was 68 yrs (range, 58-75 yrs), 66% were male, and 6.4% died in the intensive care unit. The incidence rate of death in patients exposed to hypoglycemia was 40 per 1000 intensive care unit days compared with 17 per 1000 intensive care unit days in patients without exposure. The adjusted incidence rate ratio for intensive care unit death was 2.1 (95% confidence interval, 1.6-2.8; p < .001). CONCLUSIONS: Hypoglycemia is related to intensive care unit mortality, also when adjusted for a daily adjudicated measure of disease severity, indicating the possibility of a causal relationship.

Mean glucose during ICU admission is related to mortality by a U-shaped curve in surgical and medical patients: a retrospective cohort study.

INTRODUCTION: Lowering of hyperglycemia in the intensive care unit (ICU) is widely practiced. We investigated in which way glucose regulation, defined as mean glucose concentration during admission, is associated with ICU mortality in a medical and a surgical cohort. METHODS: Retrospective database cohort study including patients admitted between January 2004 and December 2007 in a 20-bed medical/surgical ICU in a teaching hospital. Hyperglycemia was treated using a computerized algorithm targeting for glucose levels of 4.0-7.0 mmol/l. Five thousand eight hundred twenty-eight patients were eligible for analyses, of whom 1,339 patients had a medical and 4,489 had a surgical admission diagnosis. RESULTS: The cohorts were subdivided in quintiles of increasing mean glucose. We examined the relation between these mean glucose strata and mortality. In both cohorts we observed the highest mortality in the lowest and highest strata. Logistic regression analysis adjusted for age, sex, Acute Physiology and Chronic Health Evaluation II (APACHE II) score, admission duration and occurrence of severe hypoglycemia showed that in the medical cohort mean glucose levels <6.7 mmol/l and >8.4 mmol/l and in the surgical cohort mean glucose levels < 7.0 mmol/l and >9.4 mmol/l were associated with significantly increased ICU mortality (OR 2.4-3.0 and 4.9-6.2, respectively). Limitations of the study were its retrospective design and possible incomplete correction for severity of disease. CONCLUSIONS: Mean overall glucose during ICU admission is related to mortality by a U-shaped curve in medical and surgical patients. In this cohort of patients a 'safe range' of mean glucose regulation might be defined approximately between 7.0 and 9.0 mmol/l.

Association between administered oxygen, arterial partial oxygen pressure and mortality in mechanically ventilated intensive care unit patients.

INTRODUCTION: The aim of this study was to investigate whether in-hospital mortality was associated with the administered fraction of oxygen in inspired air (FiO2) and achieved arterial partial pressure of oxygen (PaO2). METHODS: This was a retrospective, observational study on data from the first 24 h after admission from 36,307 consecutive patients admitted to 50 Dutch intensive care units (ICUs) and treated with mechanical ventilation. Oxygenation data from all admission days were analysed in a subset of 3,322 patients in 5 ICUs. RESULTS: Mean PaO2 and FiO2 in the first 24 h after ICU admission were 13.2 kPa (standard deviation (SD) 6.5) and 50% (SD 20%) respectively. Mean PaO2 and FiO2 from all admission days were 12.4 kPa (SD 5.5) and 53% (SD 18). Focusing on oxygenation in the first 24 h of admission, in-hospital mortality was shown to be linearly related to FiO2 value and had a U-shaped relationship with PaO2 (both lower and higher PaO2 values were associated with a higher mortality), independent of each other and of Simplified Acute Physiology Score (SAPS) II, age, admission type, reduced Glasgow Coma Scale (GCS) score, and individual ICU. Focusing on the entire ICU stay, in-hospital mortality was independently associated with mean FiO2 during ICU stay and with the lower two quintiles of mean PaO2 value during ICU stay. CONCLUSIONS: Actually achieved PaO2 values in ICU patients in The Netherlands are higher than generally recommended in the literature. High FiO2, and both low PaO2 and high PaO2 in the first 24 h after admission are independently associated with in-hospital mortality in ICU patients. Future research should study whether this association is causal or merely a reflection of differences in severity of illness insufficiently corrected for in the multivariate analysis.

A Markov model to describe daily changes in organ failure for patients at the ICU.

As the support and stabilization of organ function is a major goal of treatment in the Intensive Care Unit (ICU), changes in the function of organ systems are an important indicator of the progression of the disease and recovery. This paper presents how to construct a model that describes changes in organ failure of ICU patients on a day-to-day basis. The model is based on the daily Sequential Organ Failure Assessment (SOFA) scores for six organ systems and predicts, for each of these organ systems, whether failure or recovery is due on the next day, using six logistic regression equations. The joint set of equations, extended with equations for predicting ICU discharge and death, constitutes a firstorder multivariate Markov model. We applied the procedure on a dataset and found that most types of organ failure are highly persistent.

Self-reported attitudes versus actual practice of oxygen therapy by ICU physicians and nurses.

BACKGROUND: High inspiratory oxygen concentrations are frequently administered in ventilated patients in the intensive care unit (ICU) but may induce lung injury and systemic toxicity. We compared beliefs and actual clinical practice regarding oxygen therapy in critically ill patients. METHODS: In three large teaching hospitals in the Netherlands, ICU physicians and nurses were invited to complete a questionnaire about oxygen therapy. Furthermore, arterial blood gas (ABG) analysis data and ventilator settings were retrieved to assess actual oxygen practice in the same hospitals 1 year prior to the survey. RESULTS: In total, 59% of the 215 respondents believed that oxygen-induced lung injury is a concern. The majority of physicians and nurses stated that minimal acceptable oxygen saturation and partial arterial oxygen pressure (PaO2) ranges were 85% to 95% and 7 to 10 kPa (52.5 to 75 mmHg), respectively. Analysis of 107,888 ABG results with concurrent ventilator settings, derived from 5,565 patient admissions, showed a median (interquartile range (IQR)) PaO2 of 11.7 kPa (9.9 to 14.3) [87.8 mmHg], median fractions of inspired oxygen (FiO2) of 0.4 (0.4 to 0.5), and median positive end-expiratory pressure (PEEP) of 5 (5 to 8) cm H2O. Of all PaO2 values, 73% were higher than the upper limit of the commonly self-reported acceptable range, and in 58% of these cases, neither FiO2 nor PEEP levels were lowered until the next ABG sample was taken. CONCLUSIONS: Most ICU clinicians acknowledge the potential adverse effects of prolonged exposure to hyperoxia and report a low tolerance for high oxygen levels. However, in actual clinical practice, a large proportion of their ICU patients was exposed to higher arterial oxygen levels than self-reported target ranges.

External validation of Acute Physiology and Chronic Health Evaluation IV in Dutch intensive care units and comparison with Acute Physiology and Chronic Health Evaluation II and Simplified Acute Physiology Score II.

PURPOSE: The aim of this study was to validate and compare the performance of the Acute Physiology and Chronic Health Evaluation (APACHE) IV in the Dutch intensive care unit (ICU) population to the APACHE II and Simplified Acute Physiology Score (SAPS) II. MATERIALS AND METHODS: This is a prospective study based on data from a national quality registry between 2006 and 2009 from 59 Dutch ICUs. The validation set consisted of 62,737 patients; the 3 models were compared using 44,112 patients. Measures of discrimination, accuracy, and calibration (area under the receiver operating characteristic curve (AUC), Brier score, R(2), and C-statistic) were calculated using bootstrapping. In addition, the standardized mortality ratios were calculated. RESULTS: The original APACHE IV showed good discrimination and accuracy (AUC = 0.87, Brier score = 0.10, R(2) = 0.29) but poor calibration (C-statistic = 822.67). Customization significantly improved the performance of the APACHE IV. The overall discrimination and accuracy of the customized APACHE IV were statistically better, and the overall C-statistic was inferior to those of the customized APACHE II and SAPS II, but these differences were small in perspective of clinical use. CONCLUSIONS: The 3 models have comparable capabilities for benchmarking purposes after customization. Main advantage of APACHE IV is the large number of diagnoses that enable subgroup analysis. The APACHE IV coronary artery bypass grafting (CABG) model has a good performance in the Dutch ICU population and can be used to complement the 3 models.

The impact of different prognostic models and their customization on institutional comparison of intensive care units.

OBJECTIVES: To evaluate the influence of choice of a prognostic model and the effect of customization of these models on league tables (i.e., rank-order listing) in which intensive care units (ICUs) are ranked by standardized mortality ratios using Acute Physiology and Chronic Health Evaluation (APACHE) II, Simplified Acute Physiology Score (SAPS) II, and Mortality Probability Model II (MPM24II). DESIGN: Retrospective analysis of prospectively collected data on ICU admissions. SETTING: Forty Dutch ICUs. PATIENTS: A data set from a national registry of 86,427 patients from January 2002 to October 2006. INTERVENTIONS: The league tables associated with the different models were compared to evaluate their agreement. Bootstrapping was used to quantify the uncertainty in the ranks for ICUs. First, for each ICU the median rank and its 95% confidence interval were identified for each model. Then, for a given pair of models, for each ICU the median difference in rank and its associated 95% confidence interval were computed. A difference in rank for an ICU for a given pair of models was considered relevant if it was statistically significant and if one of the models would categorize this ICU as a performance outlier (excellent performer or very poor performer) while the other did not. MEASUREMENTS AND MAIN RESULTS: For 20 ICUs, there was a significant difference in rank (2-19 positions) between one or more pairs of models. Three ICUs were rated as performance outliers by one of the models, while the other excluded this possibility with 95% certainty. Furthermore, for ten ICUs, one or more pairs of models classified these ICUs as performance outliers while the other model did not do so with certainty. Regarding the agreement between the original models and their customized versions, in all cases the median change in rank was three positions or less and the models fully agreed with respect to which ICUs should be classified as performance outliers. CONCLUSIONS: Institutional comparison based on case-mix adjusted league tables is sensitive to the choice of prognostic model but not to customization of these models. League tables should always display the uncertainty associated with institutional ranks.

Influence of entry criteria on mortality risk and number of eligible patients in recent studies on severe sepsis.

OBJECTIVE: To understand the impact of patient selection criteria used in recent sepsis trials on baseline mortality risk and number of eligible patients. DESIGN: Observational cohort study, with retrospective analysis of prospectively collected data. METHODS AND MAIN RESULTS: Using a MEDLINE search, we selected recent randomized controlled trials in patients with severe sepsis and studied the mortality rate in the control groups of these trials. Nine articles fulfilled the search criteria and were used in our analyses. The 28-day mortality rate in the control groups of these trials varied between 28.0% and 89.0%. Differences in this mortality rate might be due to the use of different entry criteria but also to other factors that vary between the trials. To eliminate the influence of these confounding factors when studying the effect of the use of entry criteria on baseline mortality risk and number of eligible patients, we projected the entry criteria of these nine trials on a large independent database of >70,000 Dutch intensive care patients admitted between 1996 and 2003. This yielded nine groups of patients who would have been eligible for the respective trials. The percentage of patients who would have been eligible for these trials varied between 1.5% and 6.0%. Six of these groups had a similar intensive care mortality rate (between 25.0% and 28.9%). The projection of the entry criteria of the three other trials onto the database resulted in groups of patients with considerably higher intensive care mortality. For in-hospital mortality rate in these groups, similar results were found. CONCLUSIONS: The majority of the trials we studied used entry criteria that select patients with a similar mortality risk. This suggests that differences in baseline mortality risk reported in recent sepsis trials are to be attributed to other factors that vary between trials rather than to differences in entry criteria. However, entry criteria do have an important influence on the number of eligible patients for sepsis trials without influencing baseline mortality rate.