Neurological Pupil Index for the Early Prediction of Outcome in Severe Acute Brain Injury Patients.

In this study, we examined the early value of automated quantitative pupillary examination, using the Neurological Pupil index (NPi), to predict the long-term outcome of acute brain injured (ABI) patients. We performed a single-centre retrospective study (October 2016−March 2019) in ABI patients who underwent NPi measurement during the first 3 days following brain insult. We examined the performance of NPi­alone or in combination with other baseline demographic (age) and radiologic (CT midline shift) predictors­to prognosticate unfavourable 6-month outcome (Glasgow Outcome Scale 1−3). A total of 145 severely brain-injured subjects (65 traumatic brain injury, TBI; 80 non-TBI) were studied. At each time point tested, NPi <3 was highly predictive of unfavourable outcome, with highest specificity (100% (90−100)) at day 3 (sensitivity 24% (15−35), negative predictive value 36% (34−39)). The addition of NPi, from day 1 following ABI to age and cerebral CT scan, provided the best prognostic performance (AUROC curve 0.85 vs. 0.78 without NPi, p = 0.008; DeLong test) for 6-month neurological outcome prediction. NPi, assessed at the early post-injury phase, has a superior ability to predict unfavourable long-term neurological outcomes in severely brain-injured patients. The added prognostic value of NPi was most significant when complemented with baseline demographic and radiologic information.

Eyeing up the injured brain: automated pupillometry and optic nerve sheath diameter.

PURPOSE OF REVIEW: Multimodal monitoring has emerged as a novel paradigm of care in acute brain injury, and in this context the value of noninvasive devices is increasingly under scrutiny. This narrative review summarizes recent clinical investigation focused on the role of automated infrared pupillometry (AIP) and optic nerve sheath diameter (ONSD) ultrasound as novel techniques to monitor and manage neurocritical care patients. RECENT FINDINGS: AIP provides a quantitative measurement of the pupillary light reflex that is more precise and reliable than the traditional examination of the pupillary light reflex using manual flashlight lamps. AIP helps detect raised intracranial pressure (ICP) and brain herniation in patients with intracranial mass lesions. Using an automatically computed scalar index - the neurological pupil index - AIP has great accuracy to predict poor neurological outcome in patients in coma after cardiac arrest. Recent data indicate that ONSD may diagnose intracranial hypertension with better accuracy than other ultrasound-based methods. SUMMARY: Noninvasive AIP and ONSD appear useful complements to multimodality monitoring of acute brain injury, in particular in patients at risk of elevated ICP and for early neuroprognostication following cardiac arrest.

Standardized EEG analysis to reduce the uncertainty of outcome prognostication after cardiac arrest.

PURPOSE: Post-resuscitation guidelines recommend a multimodal algorithm for outcome prediction after cardiac arrest (CA). We aimed at evaluating the prevalence of indeterminate prognosis after application of this algorithm and providing a strategy for improving prognostication in this population. METHODS: We examined a prospective cohort of comatose CA patients (n = 485) in whom the ERC/ESICM algorithm was applied. In patients with an indeterminate outcome, prognostication was investigated using standardized EEG classification (benign, malignant, highly malignant) and serum neuron-specific enolase (NSE). Neurological recovery at 3 months was dichotomized as good (Cerebral Performance Categories [CPC] 1-2) vs. poor (CPC 3-5). RESULTS: Using the ERC/ESICM algorithm, 155 (32%) patients were prognosticated with poor outcome; all died at 3 months. Among the remaining 330 (68%) patients with an indeterminate outcome, the majority (212/330; 64%) showed good recovery. In this patient subgroup, absence of a highly malignant EEG by day 3 had 99.5 [97.4-99.9] % sensitivity for good recovery, which was superior to NSE < 33 µg/L (84.9 [79.3-89.4] % when used alone; 84.4 [78.8-89] % when combined with EEG, both p < 0.001). Highly malignant EEG had equal specificity (99.5 [97.4-99.9] %) but higher sensitivity than NSE for poor recovery. Further analysis of the discriminative power of outcome predictors revealed limited value of NSE over EEG. CONCLUSIONS: In the majority of comatose CA patients, the outcome remains indeterminate after application of ERC/ESICM prognostication algorithm. Standardized EEG background analysis enables accurate prediction of both good and poor recovery, thereby greatly reducing uncertainty about coma prognostication in this patient population.

Neurological Pupil index for Early Prognostication After Venoarterial Extracorporeal Membrane Oxygenation.

BACKGROUND: Venoarterial extracorporeal membrane oxygenation therapy (VA-ECMO) after refractory cardiogenic shock or cardiac arrest has significant morbidity and mortality. Early outcome prediction is crucial in this setting, but data on neuroprognostication are limited. We examined the prognostic value of clinical neurologic examination, using an automated device for the quantitative measurement of pupillary light reactivity. METHODS: An observational cohort of sedated, mechanically ventilated VA-ECMO patients was analyzed during the early phase after ECMO insertion (first 72 h). Using the NPi-200 automated infrared pupillometer, pupillary light reactivity was assessed repeatedly (every 12 h) by calculating the Neurological Pupil index (NPi). Trends of NPi over time were correlated to 90-day mortality, and the prognostic performance of the NPi, alone and in combination with the 12-h PREDICT VA-ECMO score, was evaluated. RESULTS: One hundred consecutive patients were studied (51 with refractory cardiogenic shock and 49 with refractory cardiac arrest; 12-h PREDICT VA-ECMO, 40%; observed 90-day survival, 43%). Nonsurvivors (n = 57) had significantly lower NPi than did survivors at all time points (all P < .01). Abnormal NPi (< 3, at any time from 24 to 72 h) was 100% specific for 90-day mortality, with 0% false positives. Adding the 12-h PREDICT VA-ECMO score to the NPi provided the best prognostic performance (specificity, 100% [95% CI, 92%-100%]; sensitivity, 60% [95% CI, 46%-72%]; area under the receiver operating characteristic curve, 0.82). CONCLUSIONS: Quantitative NPi alone had excellent ability to predict a poor outcome from day 1 after VA-ECMO insertion, with no false positives. Combining NPi and 12-h PREDICT-VA ECMO score increased the sensitivity of outcome prediction, while maintaining 100% specificity.