Critical illness hyperglycemia: is failure of the beta-cell to meet extreme insulin demand indicative of dysfunction?

In the recent study by Preissig and Rigby in Critical Care, the authors argue that critical illness hyperglycemia in children with both respiratory failure and cardiovascular failure is due to a primary failure of the beta-cell. However, alternative explanations that the failure is secondary to an increase in insulin resistance leading to beta-cell exhaustion, or a negative impact of exogenous glucocorticoid therapy, may be equally likely

Measuring and reporting glycemic control in clinical trials: building a path to consensus

Clinical trials over time have used a variety of approaches for both measuring tight glycemic control and reporting results. The review by Finfer and colleagues in this issue of Critical Care is a step toward consensus within the research community to standardize the way blood glucose is measured and reported in clinical trials. The authors propose using specific measures of central tendency and dispersion for reporting glucose, advocate the use of blood gas analyzers and elimination of point-of-care glucose monitors in the intensive care unit, and comment on performance of continuous glucose monitors. As we await the release of updated rules from the International Standards Organization and process the new rules from the Clinical Laboratory and Standards Institute to regulate glucose monitoring, these recommendations should trigger many more conversations within the field as we strive for uniformity. However, we need to be cautious in prematurely proposing and adopting standards of care that fail to account for newer technology and data in this rapidly growing area of research

The correlation and level of agreement between end-tidal and blood gas pCO2 in children with respiratory distress: a retrospective analysis

<p>Abstract</p> <p>Background</p> <p>To investigate the correlation and level of agreement between end-tidal carbon dioxide (EtCO₂) and blood gas pCO₂in non-intubated children with moderate to severe respiratory distress.</p> <p>Methods</p> <p>Retrospective study of patients admitted to an intermediate care unit (InCU) at a tertiary care center over a 20-month period with moderate to severe respiratory distress secondary to asthma, bronchiolitis, or pneumonia. Patients with venous pCO₂(vpCO₂) and EtCO₂measurements within 10 minutes of each other were eligible for inclusion. Patients with cardiac disease, chronic pulmonary disease, poor tissue perfusion, or metabolic abnormalities were excluded.</p> <p>Results</p> <p>Eighty EtCO₂-vpCO₂paired values were available from 62 patients. The mean ± <smcaps>SD</smcaps> for EtCO₂and vpCO₂was 35.7 ± 10.1 mmHg and 39.4 ± 10.9 mmHg respectively. EtCO₂and vpCO₂values were highly correlated (r = 0.90, p < 0.0001). The correlations for asthma, bronchiolitis and pneumonia were 0.74 (p < 0.0001), 0.83 (p = 0.0002) and 0.98 (p < 0.0001) respectively. The mean bias ± <smcaps>SD</smcaps> between EtCO₂and vpCO₂was -3.68 ± 4.70 mmHg. The 95% level of agreement ranged from -12.88 to +5.53 mmHg. EtCO₂was found to be more accurate when vpCO₂was 35 mmHg or lower.</p> <p>Conclusion</p> <p>EtCO₂is correlated highly with vpCO₂in non-intubated pediatric patients with moderate to severe respiratory distress across respiratory illnesses. Although the level of agreement between the two methods precludes the overall replacement of blood gas evaluation, EtCO₂monitoring remains a useful, continuous, non-invasive measure in the management of non-intubated children with moderate to severe respiratory distress.</p

Tight glycemic control in the ICU - is the earth flat?

Tight glycemic control in the ICU has been shown to reduce mortality in some but not all prospective randomized control trials. Confounding the interpretation of these studies are differences in how the control was achieved and underlying incidence of hypoglycemia, which can be expected to be affected by the introduction of continuous glucose monitoring (CGM). In this issue of Critical Care, a consensus panel provides a list of the research priorities they believe are needed for CGM to become routine practice in the ICU. We reflect on these recommendations and consider the implications for using CGM today

Pediatric intermediate care and pediatric intensive care units: PICU metrics and an analysis of patients that use both

PurposeTo examine how intermediate care units (IMCUs) are used in relation to pediatric intensive care units (PICUs), characterize PICU patients that utilize IMCUs, and estimate the impact of IMCUs on PICU metrics.Materials &amp; methodsRetrospective study of PICU patients discharged from 108 hospitals from 2009 to 2011. Patients admitted from or discharged to IMCUs were characterized. We explored the relationships between having an IMCU and several PICU metrics: physical length-of-stay (LOS), medical LOS, discharge wait time, admission severity of illness, unplanned PICU admissions from wards, and early PICU readmissions.ResultsThirty-three percent of sites had an IMCU. After adjusting for known confounders, there was no association between having an IMCU and PICU LOS, mean severity of illness of PICU patients admitted from general wards, or proportion of PICU readmissions or unplanned ward admissions. At sites with an IMCU, patients waited 3.1h longer for transfer from the PICU once medically cleared (p&lt;0.001).ConclusionsThere was no association between having an IMCU and most measures of PICU efficiency. At hospitals with an IMCU, patients spent more time in the PICU once they were cleared for discharge. Other ways that IMCUs might affect PICU efficiency or particular patient populations should be investigated

A National Approach to Pediatric Sepsis Surveillance

Pediatric sepsis is a major public health concern, and robust surveillance tools are needed to characterize its incidence, outcomes, and trends. The increasing use of electronic health records (EHRs) in the United States creates an opportunity to conduct reliable, pragmatic, and generalizable population-level surveillance using routinely collected clinical data rather than administrative claims or resource-intensive chart review. In 2015, the US Centers for Disease Control and Prevention recruited sepsis investigators and representatives of key professional societies to develop an approach to adult sepsis surveillance using clinical data recorded in EHRs. This led to the creation of the adult sepsis event definition, which was used to estimate the national burden of sepsis in adults and has been adapted into a tool kit to facilitate widespread implementation by hospitals. In July 2018, the Centers for Disease Control and Prevention convened a new multidisciplinary pediatric working group to tailor an EHR-based national sepsis surveillance approach to infants and children. Here, we describe the challenges specific to pediatric sepsis surveillance, including evolving clinical definitions of sepsis, accommodation of age-dependent physiologic differences, identifying appropriate EHR markers of infection and organ dysfunction among infants and children, and the need to account for children with medical complexity and the growing regionalization of pediatric care. We propose a preliminary pediatric sepsis event surveillance definition and outline next steps for refining and validating these criteria so that they may be used to estimate the national burden of pediatric sepsis and support site-specific surveillance to complement ongoing initiatives to improve sepsis prevention, recognition, and treatment

A cross-platform toolkit for mass spectrometry and proteomics

To the Editor: Mass spectrometry–based proteomics has become an important component of biological research. Numerous proteomics methods have been developed to identify and quantify the proteins in biological and clinical samples1, identify pathways affected by endogenous and exogenous perturbations2 and characterize protein complexes3. Despite successes, the interpretation of vast proteomics data

A Glycemia Risk Index (GRI) of Hypoglycemia and Hyperglycemia for Continuous Glucose Monitoring Validated by Clinician Ratings.

BackgroundA composite metric for the quality of glycemia from continuous glucose monitor (CGM) tracings could be useful for assisting with basic clinical interpretation of CGM data.MethodsWe assembled a data set of 14-day CGM tracings from 225 insulin-treated adults with diabetes. Using a balanced incomplete block design, 330 clinicians who were highly experienced with CGM analysis and interpretation ranked the CGM tracings from best to worst quality of glycemia. We used principal component analysis and multiple regressions to develop a model to predict the clinician ranking based on seven standard metrics in an Ambulatory Glucose Profile: very low-glucose and low-glucose hypoglycemia; very high-glucose and high-glucose hyperglycemia; time in range; mean glucose; and coefficient of variation.ResultsThe analysis showed that clinician rankings depend on two components, one related to hypoglycemia that gives more weight to very low-glucose than to low-glucose and the other related to hyperglycemia that likewise gives greater weight to very high-glucose than to high-glucose. These two components should be calculated and displayed separately, but they can also be combined into a single Glycemia Risk Index (GRI) that corresponds closely to the clinician rankings of the overall quality of glycemia (r = 0.95). The GRI can be displayed graphically on a GRI Grid with the hypoglycemia component on the horizontal axis and the hyperglycemia component on the vertical axis. Diagonal lines divide the graph into five zones (quintiles) corresponding to the best (0th to 20th percentile) to worst (81st to 100th percentile) overall quality of glycemia. The GRI Grid enables users to track sequential changes within an individual over time and compare groups of individuals.ConclusionThe GRI is a single-number summary of the quality of glycemia. Its hypoglycemia and hyperglycemia components provide actionable scores and a graphical display (the GRI Grid) that can be used by clinicians and researchers to determine the glycemic effects of prescribed and investigational treatments