Statins: a role in infected critically ill patients?

Terblanche and colleagues add to the ongoing controversy over the role, if any, for statins in patients with sepsis. The authors note that statins fail to prevent progression to organ dysfunction in critically ill patients. However, like most publications, the study is retrospective and stimulates the controversy but fails to resolve it. The time has come for robust randomized controlled clinical trials.     

Red cell transfusion triggers in critically ill patients: time for some new TRICCs?

The present study describes the impact on renal function of a modern starch used for resuscitation in the intensive care unit. The role of starch in renal dysfunction, the importance of the definition of acute kidney injury and acute renal failure, and hyperoncoticity are reviewed.     

Leptin in sepsis: a well-suited biomarker in critically ill patients?

The value of monitoring serum leptin in critically ill patients is important for early diagnosis and differentiation between sepsis and non-infectious systemic inflammatory response syndrome (SIRS). The early diagnosis of sepsis, the identification of its origin, and an adequate therapeutic management are crucial to overcome sepsis-associated mortality. Cytokine levels are an obvious choice as sepsis markers, since cytokines are key mediators of the inflammatory response to sepsis. Leptin, a hormone mainly generated by adipocytes, acts centrally in the hypothalamus to regulate body weight and energy expenditure. There is, however, strong evidence that leptin is also involved in cell-mediated immunity and cytokine crosstalk. The finding that a serum leptin threshold of 38 μg/l can distinguish between sepsis and non-infectious SIRS (sensitivity 91.2%, specificity 85%) is the major finding in the article by Yousef and colleagues (in this issue). Much remains to be learned about the precise mechanisms by which leptin signaling participates in sepsis and non-infectious SIRS. This knowledge will potentially contribute to new therapeutic approaches.     

Does gender influence outcomes in critically ill patients?

ABSTRACT: Investigators continue to debate whether gender plays any role in patient outcome following injury/critical illness. We submit that age and hormonal milieu at the time of injury, rather than gender, are the critical factors influencing patient outcome under those conditions.     

Hyperglycaemia in critically ill patients: marker or mediator of mortality?

Acute hyperglycaemia has been associated with complications, prolonged intensive care unit and hospital stay, and increased mortality. We made an inventory of the prevalence and prognostic value of hyperglycaemia, and of the effects of glucose control in different groups of critically ill patients. The prevalence of hyperglycaemia in critically ill patients, using stringent criteria, approaches 100%. An unambiguous negative correlation between hyperglycaemia and mortality has been described in various groups of critically ill patients. Although the available evidence remains inconsistent, there appears to be a favourable effect of glucose regulation. This effect on morbidity and mortality depends on patient characteristics. To be able to compare results of future studies involving glucose regulation, better definitions of hyperglycaemia (and consequently of normoglycaemia) and patient populations are needed.     

Serum selenium and glutathione peroxidase-3 activity: biomarkers of systemic inflammation in the critically ill?

Objectives  To confirm the influence of systemic inflammatory response syndrome (SIRS) on selenium (Se) levels and prospectively evaluate the relationship between serum Se concentration [Se], glutathione peroxidase activity [GPx-3] and injury severity in patients at the time of intensive care unit (ICU) admission. Design  Prospective, observational study. Setting  Multidisciplinary University Hospital ICU. Patients and participants  A total of 36 ICU patients and 23 healthy volunteer subjects (HVS). Measurements and results  Healthy volunteer subjects were designated as controls (Group 1). ICU patients were divided into three groups: without SIRS (Group 2); with SIRS (Group 3); with SIRS and multiple organ dysfunction syndrome (MODS) (Group 4). The latter groups had APACHE II scores >15. [GPx-3] and [Se] were determined by standard methods within the first 48 h of admission to ICU. Kruskal–Wallis and Mann–Whitney U test were used for analysis of non-parametric continuous variables. The predictive value of [Se] and [GPx-3] for SIRS was calculated using a receiver operating characteristics (ROC) analysis. In SIRS and MODS patients [GPx-3] and [Se] decreased significantly (P = 0.0001 and P = 0.002, respectively). After ICU admission [GPx-3] and [Se] had a predictive value for SIRS ([GPx-3] sensitivity: 90%, specificity: 86.2% (cut-off value: 0.5 U/mL); [Se]: sensitivity 90%, specificity 72.4% (cut-off value: 60 μg/L). [Se] had predictive value for ICU mortality (P = 0.034). Conclusions  Systemic inflammatory response syndrome and MODS were associated with early decreases in [Se] and [GPx-3]. Low [Se] and [GPx-3] after ICU admission had a predictive value for SIRS, which may aid future selection of patients who could benefit from Se supplementation.     

Unmeasured anions in critically ill patients: can they predict mortality?

OBJECTIVE: To determine whether base excess, base excess caused by unmeasured anions, and anion gap can predict lactate in adult critically ill patients, and also to determine whether acid-base variables can predict mortality in these patients. DESIGN: Retrospective study. SETTING: Adult intensive care unit of tertiary hospital. PATIENTS: Three hundred adult critically ill patients admitted to the intensive care unit. INTERVENTIONS: Retrieval of admission biochemical data from computerized records, quantitative biophysical analysis of data with the Stewart-Figge methodology, and statistical analysis. MEASUREMENTS AND MAIN RESULTS: We measured plasma Na+, K+, Mg2+, Cl-, HCO3-, phosphate, ionized Ca2+, albumin, lactate, and arterial pH and Paco2. All three variables (base excess, base excess caused by unmeasured anions, anion gap) were significantly correlated with lactate (r2 =.21, p <.0001; r2 =.30, p <.0001; and r2 =.31. p <.0001, respectively). Logistic regression analysis showed that the area under the receiver operating characteristic (AUROC) curves had moderate to high accuracy for the prediction of a lactate concentration >5 mmol/L: AUROC curves, 0.86 (95% confidence interval [CI], 0.78-0.94), 0.86 (95% CI, 0.78-0.93), and 0.85 (95% CI, 0.77-0.92), respectively.Logistic regression analysis showed that hospital mortality rate correlated significantly with Acute Physiology and Chronic Health Evaluation (APACHE) II score, anion gap corrected (anion gap corrected by albumin), age, lactate, anion gap, chloride, base excess caused by unmeasured anions, strong ion gap, sodium, bicarbonate, strong ion difference effective, and base excess. However, except for APACHE II score, AUROC curves for mortality prediction were relatively small: 0.78 (95% CI, 0.72-0.84) for APACHE II, 0.66 (95% CI, 0.59-0.73) for lactate, 0.64 (95% CI, 0.57-0.71) for base excess caused by unmeasured anions, and 0.63 (95% CI, 0.56-0.70) for strong ion gap. CONCLUSIONS: Base excess, base excess caused by unmeasured anions, and anion gap are good predictors of hyperlactatemia (>5 mmol/L). Acid-base variables and, specifically, "unmeasured anions" (anion gap, anion gap corrected, base excess caused by unmeasured anions, strong ion gap), irrespective of the methods used to calculate them, are not accurate predictors of hospital mortality rate in critically ill patients.     

Measuring pain in non-verbal critically ill patients: which pain instrument?

Pain is experienced by many critically ill patients. Although the patient’s self-report represents the gold-standard measure for pain, many patients are unable to communicate in the ICU. In this commentary, we discuss the study findings comparing three objective scales for the assessment of pain in non-verbal patients and the importance of the tool selection process.In the previous issue of Critical Care, Chanques and colleagues [1] evaluate the psychometric properties of three behavioral pain scales validated for use in non-communicative critically ill patients. The authors compare two scales recommended in the practice guidelines for pain management of adult ICU patients by the Society of Critical Care Medicine [2] - that is, the Behavioral Pain Scale (BPS) [3] and the Critical-Care Pain Observation Tool (CPOT) [4] - and a routine scale in use at the host institution, the Non-Verbal Pain Scale (NVPS) [5].Assessing pain in non-communicative adult patients in the ICU must rely on the observation of behavioral indicators of pain. Selection of pain assessment tools in clinical practice must be done with rigor. Indeed, an assessment tool can be shown to be valid only for a specific purpose and a given group of respondents and context of care. All steps of scale development are important. The first step, selection of items and scale scoring, can be done by using a combination of various strategies, including an in-depth literature review, consultation of end users (for example, ICU clinicians and patients), and direct clinical observation and other sources. Content validation is a method of examining the content and relevance of the items that are useful for selecting or revising them. Once developed, reliability and validity of the scale use must be tested with the targeted patient group [6]. Reliability refers to the overall reproducibility of scale scores. The examination of inter-rater reliability is crucial to determine whether two or more trained raters reach similar scores using the same scale for the same patient and at the same time. Validity refers to the interpretation of the pain scale scores and its ability to indicate that the individual is actually in pain. As behavioral pain scales aim to detect the presence of significant pain, the examination of criterion and discriminant validation is necessary. Criterion validation allows the comparison between behavioral scores and the gold standard (that is, the patient’s self-report of pain). Discriminant validation refers to the ability of the pain scale to discriminate between conditions or procedures known to be painful or not and its ability to detect significant changes over time (responsiveness). Because validation is an ongoing process, it is imperative that its use be evaluated by independent groups of caregivers who were not involved in its development, with various ICU patient groups or with a translated version of the scale. Finally, the ease of their implementation in ICU settings and the impact of their use on pain management practices and patient outcomes must be evaluated.Evaluation of the psychometric properties of behavioral pain scales in ICU patients unable to self-report has been recently performed [7,8]. Of the eight pain scales developed for adult ICU patients, the BPS and the CPOT were found to be the most valid and reliable. The present study [1] is the first to compare psychometric properties of these two pain scales in addition to the NVPS, at rest and during noxious (for example, turning and endotracheal suctioning) and non-noxious (for example, simple repositioning) procedures. Both the BPS and the CPOT showed the strongest psychometric properties in both intubated and non-intubated patients in comparison with the NVPS. These findings add arguments to the recommendations for the use of these two pain scales [2].What are the next steps in relation to pain assessment in the ICU? First, there is a clear need to better evaluate the impact of pain assessment and management on patient outcomes. Few studies have shown that evaluating pain was associated with positive outcomes such as a shorter duration of mechanical ventilation and ICU length of stay and reduced adverse events [9-11]. Whether better management in the ICU may lead to reducing long-term negative consequences such as chronic pain and symptoms of post-traumatic stress disorder remains largely unknown. Second, there is a need for valid physiologic measures of pain, especially in ICU patients too sedated or paralyzed in whom behavioral responses cannot be observed. The use of pupillary reflex dilation has shown some promising findings [12-14]. Meanwhile, the best alternative measure to assess pain in non-verbal patients remains the use of behavioral scales.Assessing pain in non-communicative ICU patients is challenging. The BPS and the CPOT have shown the strongest psychometric properties for this purpose. These scales should be incorporated into pain management protocols to target the desired levels of analgesia in order to optimize inter-professional practices and to achieve better patient outcomes.     

Scoring systems in critically ill: Which one to use in cancer patients?

BACKGROUNDScoring systems have not been evaluated in oncology patients. We aimed to assess the performance of Acute Physiology and Chronic Health Evaluation (APACHE) II, APACHE III, APACHE IV, Simplified Acute Physiology Score (SAPS) II, SAPS III, Mortality Probability Model (MPM) II₀ and Sequential Organ Failure Assessment (SOFA) score in critically ill oncology patients.AIMTo compare the efficacy of seven commonly employed scoring systems to predict outcomes of critically ill cancer patients.METHODSWe conducted a retrospective analysis of 400 consecutive cancer patients admitted in the medical intensive care unit over a two-year period. Primary outcome was hospital mortality and the secondary outcome measure was comparison of various scoring systems in predicting hospital mortality. RESULTSIn our study, the overall intensive care unit and hospital mortality was 43.5% and 57.8%, respectively. All of the seven tested scores underestimated mortality. The mortality as predicted by MPM II₀ predicted death rate (PDR) was nearest to the actual mortality followed by that predicted by APACHE II, with a standardized mortality rate (SMR) of 1.305 and 1.547, respectively. The best calibration was shown by the APACHE III score (χ² = 4.704, P = 0.788). On the other hand, SOFA score (χ² = 15.966, P = 0.025) had the worst calibration, although the difference was not statistically significant. All of the seven scores had acceptable discrimination with good efficacy however, SAPS III PDR and MPM II₀ PDR (AUROC = 0.762), had a better performance as compared to others. The correlation between the different scoring systems was significant (P < 0.001).CONCLUSIONAll the severity scores were tested under-predicted mortality in the present study. As the difference in efficacy and performance was not statistically significant, the choice of scoring system used may depend on the ease of use and local preferences.