Postoperative Cerebral Oxygen Saturation in Children After Congenital Cardiac Surgery and Long-Term Total Intelligence Quotient: A Prospective Observational Study

OBJECTIVES

During the early postoperative period, children with congenital heart disease can suffer from inadequate cerebral perfusion, with possible long-term neurocognitive consequences. Cerebral tissue oxygen saturation can be monitored noninvasively with near-infrared spectroscopy. In this prospective study, we hypothesized that reduced cerebral tissue oxygen saturation and increased intensity and duration of desaturation (defined as cerebral tissue oxygen saturation < 65%) during the early postoperative period, independently increase the probability of reduced total intelligence quotient, 2 years after admission to a PICU.

DESIGN

Single-center, prospective study, performed between 2012 and 2015.

SETTING

The PICU of the University Hospitals Leuven, Belgium.

PATIENTS

The study included pediatric patients after surgery for congenital heart disease admitted to the PICU.

INTERVENTIONS

None.

MEASUREMENTS AND MAIN RESULTS

Postoperative cerebral perfusion was characterized with the mean cerebral tissue oxygen saturation and dose of desaturation of the first 12 and 24 hours of cerebral tissue oxygen saturation monitoring. The independent association of postoperative mean cerebral tissue oxygen saturation and dose of desaturation with total intelligence quotient at 2-year follow-up was evaluated with a Bayesian linear regression model adjusted for known confounders. According to a noninformative prior, reduced mean cerebral tissue oxygen saturation during the first 12 hours of monitoring results in a loss of intelligence quotient points at 2 years, with a 90% probability (posterior β estimates [80% credible interval], 0.23 [0.04-0.41]). Similarly, increased dose of cerebral tissue oxygen saturation desaturation would result in a loss of intelligence quotient points at 2 years with a 90% probability (posterior β estimates [80% credible interval], -0.009 [-0.016 to -0.001]).

CONCLUSIONS

Increased dose of cerebral tissue oxygen saturation desaturation and reduced mean cerebral tissue oxygen saturation during the early postoperative period independently increase the probability of having a lower total intelligence quotient, 2 years after PICU admission.

Association of Dose of Intracranial Hypertension with Outcome in Subarachnoid Hemorrhage

BACKGROUND

In patients with aneurysmal subarachnoid hemorrhage (aSAH) the burden of intracranial pressure (ICP) and its contribution to outcomes remains unclear. In this multicenter study, the independent association between intensity and duration, or "dose," of episodes of intracranial hypertension and 12-month neurological outcomes was investigated.

METHODS

This was a retrospective analysis of multicenter prospectively collected data of 98 adult patients with aSAH amendable to treatment. Patients were admitted to the intensive care unit of two European centers (Medical University of Innsbruck [Austria] and San Gerardo University Hospital of Monza [Italy]) from 2009 to 2013. The dose of intracranial hypertension was visualized. The obtained visualizations allowed us to investigate the association between intensity and duration of episodes of intracranial hypertension and the 12-month neurological outcomes of the patients, assessed with the Glasgow Outcome Score. The independent association between the cumulative dose of intracranial hypertension and outcome for each patient was investigated by using multivariable logistic regression models corrected for age, occurrence of delayed cerebral ischemia, and the Glasgow Coma Scale score at admission.

RESULTS

The combination of duration and intensity defined the tolerance to intracranial hypertension for the two cohorts of patients. A semiexponential transition divided ICP doses that were associated with better outcomes (in blue) with ICP doses associated with worse outcomes (in red). In addition, in both cohorts, an independent association was found between the cumulative time that the patient experienced ICP doses in the red area and long-term neurological outcomes. The ICP pressure-time burden was a stronger predictor of outcomes than the cumulative time spent by the patients with an ICP greater than 20 mmHg.

CONCLUSIONS

In two cohorts of patients with aSAH, an association between duration and intensity of episodes of elevated ICP and 12-month neurological outcomes could be demonstrated and was visualized in a color-coded plot.

Clinical prediction models for acute kidney injury

Objective

To report on the currently available prediction models for the development of acute kidney injury in heterogeneous adult intensive care units.

Methods

A systematic review of clinical prediction models for acute kidney injury in adult intensive care unit populations was carried out. PubMed^® was searched for publications reporting on the development of a novel prediction model, validation of an established model, or impact of an existing prediction model for early acute kidney injury diagnosis in intensive care units.

Results

We screened 583 potentially relevant articles. Among the 32 remaining articles in the first selection, only 5 met the inclusion criteria. The nonstandardized adaptations that were made to define baseline serum creatinine when the preadmission value was missing led to heterogeneous definitions of the outcome. Commonly included predictors were sepsis, age, and serum creatinine level. The final models included between 5 and 19 risk factors. The areas under the Receiver Operating Characteristic curves to predict acute kidney injury development in the internal validation cohorts ranged from 0.78 to 0.88. Only two studies were externally validated.

Conclusion

Clinical prediction models for acute kidney injury can help in applying more timely preventive interventions to the right patients. However, in intensive care unit populations, few models have been externally validated. In addition, heterogeneous definitions for acute kidney injury and evaluation criteria and the lack of impact analysis hamper a thorough comparison of existing models. Future research is needed to validate the established models and to analyze their clinical impact before they can be applied in clinical practice.

Machine learning versus physicians' prediction of acute kidney injury in critically ill adults: a prospective evaluation of the AKIpredictor

Background

Early diagnosis of acute kidney injury (AKI) is a major challenge in the intensive care unit (ICU). The AKIpredictor is a set of machine-learning-based prediction models for AKI using routinely collected patient information, and accessible online. In order to evaluate its clinical value, the AKIpredictor was compared to physicians’ predictions.

Methods

Prospective observational study in five ICUs of a tertiary academic center. Critically ill adults without end-stage renal disease or AKI upon admission were considered for enrollment. Using structured questionnaires, physicians were asked upon admission, on the first morning, and after 24 h to predict the development of AKI stages 2 or 3 (AKI-23) during the first week of ICU stay. Discrimination, calibration, and net benefit of physicians’ predictions were compared against the ones by the AKIpredictor.

Results

Two hundred fifty-two patients were included, 30 (12%) developed AKI-23. In the cohort of patients with predictions by physicians and AKIpredictor, the performance of physicians and AKIpredictor were respectively upon ICU admission, area under the receiver operating characteristic curve (AUROC) 0.80 [0.69–0.92] versus 0.75 [0.62–0.88] (n = 120, P = 0.25) with net benefit in ranges 0–26% versus 0–74%; on the first morning, AUROC 0.94 [0.89–0.98] versus 0.89 [0.82–0.97] (n = 187, P = 0.27) with main net benefit in ranges 0–10% versus 0–48%; after 24 h, AUROC 0.95 [0.89–1.00] versus 0.89 [0.79–0.99] (n = 89, P = 0.09) with main net benefit in ranges 0–67% versus 0–50%.

Conclusions

The machine-learning-based AKIpredictor achieved similar discriminative performance as physicians for prediction of AKI-23, and higher net benefit overall, because physicians overestimated the risk of AKI. This suggests an added value of the systematic risk stratification by the AKIpredictor to physicians’ predictions, in particular to select high-risk patients or reduce false positives in studies evaluating new and potentially harmful therapies. Due to the low event rate, future studies are needed to validate these findings.

Trial registration

ClinicalTrials.gov, NCT03574896 registration date: July 2nd, 2018

Electronic supplementary material

The online version of this article (10.1186/s13054-019-2563-x) contains supplementary material, which is available to authorized users.

Visualizing Cerebrovascular Autoregulation Insults and Their Association with Outcome in Adult and Paediatric Traumatic Brain Injury

OBJECTIVE

The aim of this study is to assess visually the impact of duration and intensity of cerebrovascular autoregulation insults on 6-month neurological outcome in severe traumatic brain injury.

MATERIAL AND METHODS

Retrospective analysis of prospectively collected minute-by-minute intracranial pressure (ICP) and mean arterial blood pressure data of 259 adult and 99 paediatric traumatic brain injury (TBI) patients from multiple European centres. The relationship of the 6-month Glasgow Outcome Scale with cerebrovascular autoregulation insults (defined as the low-frequency autoregulation index above a certain threshold during a certain time) was visualized in a colour-coded plot. The analysis was performed separately for autoregulation insults occurring with cerebral perfusion pressure (CPP) below 50 mmHg, with ICP above 25 mmHg and for the subset of adult patients that did not undergo decompressive craniectomy.

RESULTS

The colour-coded plots showed a time-intensity-dependent association with outcome for cerebrovascular autoregulation insults in adult and paediatric TBI patients. Insults with a low-frequency autoregulation index above 0.2 were associated with worse outcomes and below -0.6 with better outcomes, with and approximately exponentially decreasing transition curve between the two intensity thresholds. All insults were associated with worse outcomes when CPP was below 50 mmHg or ICP was above 25 mmHg.

CONCLUSIONS

The colour-coded plots indicate that cerebrovascular autoregulation is disturbed in a dynamic manner, such that duration and intensity play a role in the determination of a zone associated with better neurological outcome.

Generalisability of a Virtual Trials Method for Glycaemic Control in Intensive Care

BACKGROUND

Elevated blood glucose (BG) concentrations (Hyperglycaemia) are a common complication in critically ill patients. Insulin therapy is commonly used to treat hyperglycaemia, but metabolic variability often results in poor BG control and low BG (hypoglycaemia).

OBJECTIVE

This paper presents a model-based virtual trial method for glycaemic control protocol design, and evaluates its generalisability across different populations.

METHODS

Model-based insulin sensitivity (SI) was used to create virtual patients from clinical data from three different ICUs in New Zealand, Hungary, and Belgium. Glycaemic results from simulation of virtual patients under their original protocol (self-simulation) and protocols from other units (cross simulation) were compared.

RESULTS

Differences were found between the three cohorts in median SI and inter-patient variability in SI. However, hour-to-hour intra-patient variability in SI was found to be consistent between cohorts. Self and cross-simulation results were found to have overall similarity and consistency, though results may differ in the first 24-48 h due to different cohort starting BG and underlying SI.

CONCLUSIONS AND SIGNIFICANCE

Virtual patients and the virtual trial method were found to be generalisable across different ICUs. This virtual trial method is useful for in silico protocol design and testing, given an understanding of the underlying assumptions and limitations of this method.

AKIpredictor, an online prognostic calculator for acute kidney injury in adult critically ill patients: development, validation and comparison to serum neutrophil gelatinase-associated lipocalin

PURPOSE

Early diagnosis of acute kidney injury (AKI) remains a major challenge. We developed and validated AKI prediction models in adult ICU patients and made these models available via an online prognostic calculator. We compared predictive performance against serum neutrophil gelatinase-associated lipocalin (NGAL) levels at ICU admission.

METHODS

Analysis of the large multicenter EPaNIC database. Model development (n = 2123) and validation (n = 2367) were based on clinical information available (1) before and (2) upon ICU admission, (3) after 1 day in ICU and (4) including additional monitoring data from the first 24 h. The primary outcome was a comparison of the predictive performance between models and NGAL for the development of any AKI (AKI-123) and AKI stages 2 or 3 (AKI-23) during the first week of ICU stay.

RESULTS

Validation cohort prevalence was 29% for AKI-123 and 15% for AKI-23. The AKI-123 model before ICU admission included age, baseline serum creatinine, diabetes and type of admission (medical/surgical, emergency/planned) and had an AUC of 0.75 (95% CI 0.75-0.75). The AKI-23 model additionally included height and weight (AUC 0.77 (95% CI 0.77-0.77)). Performance consistently improved with progressive data availability to AUCs of 0.82 (95% CI 0.82-0.82) for AKI-123 and 0.84 (95% CI 0.83-0.84) for AKI-23 after 24 h. NGAL was less discriminant with AUCs of 0.74 (95% CI 0.74-0.74) for AKI-123 and 0.79 (95% CI 0.79-0.79) for AKI-23.

CONCLUSIONS

AKI can be predicted early with models that only use routinely collected clinical information and outperform NGAL measured at ICU admission. The AKI-123 models are available at http://akipredictor.com/ . Trial registration Clinical Trials.gov NCT00512122.