Neurocritical Care最新文献

Background: Identifying patients likely to regain consciousness early on is a challenge. The assessment of consciousness levels and the prediction of wakefulness probabilities are facilitated by ¹⁸F-fluorodeoxyglucose (¹⁸F-FDG) positron emission tomography (PET). This study aimed to develop a prognostic model for predicting 1-year postinjury outcomes in prolonged disorders of consciousness (DoC) using ¹⁸F-FDG PET alongside clinical behavioral scores.

Methods: Eighty-seven patients with prolonged DoC newly diagnosed with behavioral Coma Recovery Scale-Revised (CRS-R) scores and ¹⁸F-FDG PET/computed tomography (18F-FDG PET/CT) scans were included. PET images were normalized by the cerebellum and extracerebral tissue, respectively. Images were divided into training and independent test sets at a ratio of 5:1. Image-based classification was conducted using the DenseNet121 network, whereas tabular-based deep learning was employed to train depth features extracted from imaging models and behavioral CRS-R scores. The performance of the models was assessed and compared using the McNemar test.

Results: Among the 87 patients with DoC who received routine treatments, 52 patients showed recovery of consciousness, whereas 35 did not. The classification of the standardized uptake value ratio by extracerebral tissue model demonstrated a higher specificity and lower sensitivity in predicting consciousness recovery than the classification of the standardized uptake value ratio by cerebellum model. With area under the curve values of 0.751 ± 0.093 and 0.412 ± 0.104 on the test sets, respectively, the difference is not statistically significant (P = 0.73). The combination of standardized uptake value ratio by extracerebral tissue and computed tomography depth features with behavioral CRS-R scores yielded the highest classification accuracy, with area under the curve values of 0.950 ± 0.027 and 0.933 ± 0.015 on the training and test sets, respectively, outperforming any individual mode.

Conclusions: In this preliminary study, a multimodal prognostic model based on ¹⁸F-FDG PET extracerebral normalization and behavioral CRS-R scores facilitated the prediction of recovery in DoC.

Background: Augmented renal clearance (ARC) is an increase in the measured creatinine clearance (CLCR), the cause of which remains poorly understood. ARC may be associated with drug underdosing and appears to be more frequent in patients with brain damage, such as subarachnoid hemorrhage (SaH), although the incidence of ARC remains poorly understood. The aim of this study was to investigate the prevalence of ARC in patients with SaH in a neurointensive care unit (neuro-ICU) and to identify factors associated with ARC.

Methods: All consecutive patients hospitalized in the neuro-ICU of Bordeaux University Hospital between June 2018 and June 2019 for SaH treatment were retrospectively included. CLCR was measured daily via 24-h urine collection. ARC was defined as a CLCR ≥ 130 mL/min/1.73 m². The effects of different covariates on the time course of CLCR were investigated using a linear mixed model.

Results: Of the 205 included study participants, 168 developed ARC during their neuro-ICU stay; the estimated ARC prevalence was 82% (95% confidence interval 76-87) with a median of 4 days (range 3-6 days) after hemorrhage; ARC persisted for a median of 5 days (range 2-8 days). Patients with ARC were younger and had a lower BMI and lower mortality rate. In multivariate analysis, younger patients with a higher mean arterial pressure, no history of hypertension, and greater nitrogen loss were more likely to have ARC.

Conclusions: Augmented renal clearance is very common in critically ill patients with SaH, persists over time, and seems to lack specific risk factors. Daily CLCR measurements could be essential.

The Full Outline of UnResponsiveness (FOUR) score was developed to overcome the limitations of the Glasgow Coma Scale (GCS) when assessing individuals with impaired consciousness. We sought to review the evidence regarding the predictive validity of the GCS and FOUR score in intensive care unit (ICU) settings. This review was prospectively registered in PROSPERO (CRD42023420528). Systematic searches of CINAHL, MEDLINE, and Embase were undertaken. Prospective observational studies were included if both GCS and FOUR score were assessed in adults during ICU admission and if mortality and/or validated functional outcome measure scores were collected. Studies were excluded if they exclusively investigated patients with traumatic brain injury. Screening, data extraction, and quality assessment using the Quality in Prognosis Studies tool were conducted by two reviewers. Twenty studies of poor to moderate quality were included. Many studies only included patients with neurological illness and excluded sedated patients, despite high proportions of intubated patients. The FOUR score achieved higher area under the receiver operating characteristic curve values for mortality prediction compared with the GCS, and the FOUR score achieved significantly higher area under the receiver operating characteristic curve values for predictions of ICU mortality. Both coma scales showed similar accuracy in predicting "unfavorable" functional outcome. The FOUR score appeared to be more responsive than the GCS in the ICU, as most patients with a GCS score of 3 obtained FOUR scores between 1 and 8 due to preserved brainstem function. The FOUR score may be superior to the GCS for predicting mortality in ICU settings. Further adequately powered studies with clear, reliable methods for assessment of index and outcome scores are required to clarify the predictive performance of both coma scales in ICUs. Inclusion of sedated patients may improve generalizability of findings in general ICU populations.

Although evaluation of disorders of consciousness (DoC) following brain injury has traditionally relied on bedside behavioral examination, advances in neurotechnology have elucidated novel approaches to detecting and predicting recovery of consciousness. Professional society guidelines now recommend that clinicians integrate these neurotechnologies into clinical practice as part of multimodal evaluations for some patients with DoC but have not crafted concrete protocols for this translation. Little is known about the experiences and ethical perspectives held by key stakeholder groups around the clinical implementation of advanced neurotechnologies to detect and predict recovery of consciousness. Recognizing this knowledge gap, the Data-Driven Neuroethics for Consciousness Detection (DECODE) survey examined clinicians' perspectives on advanced neurotechnologies for DoC care, including access to and rates of adoption, perceived utility, facilitators and barriers to adoption in clinical settings, ethical considerations surrounding clinical implementation, and challenges encountered in ensuring care for patients with acute and prolonged DoC. Mixed-methods analysis including qualitative analysis, grounded theory methodology, and ethical analysis was employed to assess responses and key themes. Ninety-two clinicians consented to the survey. More than 70% believed that standard bedside behavioral examination is insufficient, and nearly 60% viewed advanced neurotechnologies as integral in optimal DoC evaluation. Training gaps and limited institutional infrastructure were identified as salient barriers to clinical implementation. Thematic analysis revealed concerns about the interpretation of results, impact on surrogates, and validity of test results. Ethical themes of prognostic uncertainty, nihilism, and access also permeated multiple domains. Considerations surrounding access, knowledge base, results interpretation, and communication with surrogates are cross-cutting ethical threads shaping the clinical translation of advanced neurotechnologies for DoC. These components represent opportunities for implementation science work focused on democratizing access to neurotechnologies, educating clinicians on the use of novel techniques and interpretation of results, conducting multisite validation studies, and standardizing approaches to communicating test results.