Glutamate infusion associated with reduced rises of p-Copeptin after coronary surgery: Substudy of GLUTAMICS II

Background

Glutamate plays a key role for post-ischaemic recovery of myocardial metabolism. According to post hoc analyses of the two GLUTAMICS trials, patients without diabetes benefit from glutamate with less myocardial dysfunction after coronary artery bypass surgery (CABG). Copeptin reflects activation of the Arginine Vasopressin system and is a reliable marker of heart failure but available studies in cardiac surgery are limited. We investigated whether glutamate infusion is associated with reduced postoperative rises of plasma Copeptin (p-Copeptin) after CABG.

Methods

A prespecified randomised double-blind substudy of GLUTAMICS II. Patients had left ventricular ejection fraction ≤0.30 or EuroSCORE II ≥3.0 and underwent CABG ± valve procedure. Intravenous infusion of 0.125 M L-glutamic acid or saline at 1.65 mL/kg/h was commenced 10–20 min before the release of the aortic cross-clamp and then continued for another 150 min P-Copeptin was measured preoperatively and postoperatively on day one (POD1) and day three. The primary endpoint was an increase in p-Copeptin from the preoperative level to POD1. Postoperative stroke ≤24 h and mortality ≤30 days were safety outcomes.

Results

We included 181 patients of whom 48% had diabetes. The incidence of postoperative mortality ≤30 days (0% vs. 2.1%; p = .50) and stroke ≤24 h (0% vs. 3.2%; p = .25) did not differ between the glutamate group and controls. P-Copeptin increased postoperatively with the highest values recorded on POD1 without significant inter-group differences. Among patients without diabetes, p-Copeptin did not differ preoperatively but postoperative rise from preoperative level to POD1 was significantly reduced in the glutamate group (73 ± 66 vs. 115 ± 102 pmol/L; p = .02). P-Copeptin was significantly lower in the Glutamate group on POD1 (p = .02) and POD 3 (p = .02).

Conclusions

Glutamate did not reduce rises of p-Copeptin significantly after moderate to high-risk CABG. However, glutamate was associated with reduced rises of p-Copeptin among patients without diabetes. These results agree with previous observations suggesting that glutamate mitigates myocardial dysfunction after CABG in patients without diabetes. Given the exploratory nature of these findings, they need to be confirmed in future studies.     

Selecting patients for early interdisciplinary rehabilitation during neurointensive care after moderate to severe traumatic brain injury

Background

Early interdisciplinary rehabilitation (EIR) in neurointensive care is a limited resource reserved for patients with moderate to severe traumatic brain injury (TBI) believed to profit from treatment. We evaluated how key parameters related to injury severity and patient characteristics were predictive of receiving EIR, and whether these parameters changed over time.

Methods

Among 1003 adult patients with moderate to severe TBI admitted over 72 h to neurointensive care unit during four time periods between 2005 and 2020, EIR was given to 578 and standard care to 425 patients. Ten selection criteria thought to best represent injury severity and patient benefit were evaluated (Glasgow Coma Scale, Head Abbreviated Injury Scale, New-Injury-Severity-Scale, intracranial pressure monitoring, neurosurgery, age, employment, Charlson Comorbidity Index, severe psychiatric disease, and chronic substance abuse).

Results

In multivariate regression analysis, patients who were employed (adjOR 1.99 [95% CI 1.41, 2.80]), had no/mild comorbidity (adjOR 3.15 [95% CI 1.72, 5.79]), needed neurosurgery, had increasing injury severity and were admitted by increasing time period were more likely to receive EIR, whereas receiving EIR was less likely with increasing age (adjOR 0.97 [95% CI 0.96, 0.98]) and chronic substance abuse. Overall predictive ability of the model was 71%. Median age and comorbidity increased while employment decreased from 2005 to 2020, indicating patient selection became less restrictive with time.

Conclusion

Injury severity and need for neurosurgery remain important predictors for receiving EIR, but the importance of age, employment, and comorbidity have changed over time. Moderate prediction accuracy using current clinical criteria suggest unrecognized factors are important for patient selection.     

Quality and denoising in real‐time functional magnetic resonance imaging neurofeedback: A methods review

Neurofeedback training using real‐time functional magnetic resonance imaging (rtfMRI‐NF) allows subjects voluntary control of localised and distributed brain activity. It has sparked increased interest as a promising non‐invasive treatment option in neuropsychiatric and neurocognitive disorders, although its efficacy and clinical significance are yet to be determined. In this work, we present the first extensive review of acquisition, processing and quality control methods available to improve the quality of the neurofeedback signal. Furthermore, we investigate the state of denoising and quality control practices in 128 recently published rtfMRI‐NF studies. We found: (a) that less than a third of the studies reported implementing standard real‐time fMRI denoising steps, (b) significant room for improvement with regards to methods reporting and (c) the need for methodological studies quantifying and comparing the contribution of denoising steps to the neurofeedback signal quality. Advances in rtfMRI‐NF research depend on reproducibility of methods and results. Notably, a systematic effort is needed to build up evidence that disentangles the various mechanisms influencing neurofeedback effects. To this end, we recommend that future rtfMRI‐NF studies: (a) report implementation of a set of standard real‐time fMRI denoising steps according to a proposed COBIDAS‐style checklist ( https://osf.io/kjwhf/ ), (b) ensure the quality of the neurofeedback signal by calculating and reporting community‐informed quality metrics and applying offline control checks and (c) strive to adopt transparent principles in the form of methods and data sharing and support of open‐source rtfMRI‐NF software. Code and data for reproducibility, as well as an interactive environment to explore the study data, can be accessed at https://github.com/jsheunis/quality‐and‐denoising‐in‐rtfmri‐nf.